HIV–TB co-infection in Liangshan, a resource-limited region of Southwest China: trends and implications in the context of integrated prevention, 2019–2024

HIV–TB co-infection in Liangshan, a resource-limited region of Southwest China: trends and implications in the context of integrated prevention, 2019–2024 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Case Report HIV–TB co-infection in Liangshan, a resource-limited region of Southwest China: trends and implications in the context of integrated prevention, 2019–2024 Xuefei Bai, Ju Wang, Gang Yu, Jinhong Shi, Sisi Fan, Ruobing Wang, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9028669/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract Objective To analyze epidemiological trends and key factors of HIV–TB co-infection in Liangshan Yi Autonomous Prefecture (2019–2024), a resource-limited region in Southwest China, and inform integrated prevention strategies. Methods A retrospective analysis was conducted on 3,367 HIV–TB co-infected cases extracted from the National HIV/AIDS and TB surveillance systems. Records were linked via unique identifiers. Descriptive statistics and chi-square tests for trend assessed incidence trends, demographics, transmission routes, treatment outcomes, and drug resistance. Results Under the Integrated Prevention and Control of Four Diseases policy and precision prevention and control model, HIV–TB incidence declined from 12.26 to 8.76 per 100,000 ( χ ² trend =40.459, P < 0.001), driven by high-burden counties and populations under 45 years (all P < 0.001). Patients were predominantly young males (61.10%) and farmers (92.40%). The main HIV transmission routes were heterosexual contact (48.29%) and injection drug use (41.31%), with marked sex and age disparities: injection drug use predominated in males (50.92%) and those aged 30–45 years (50.32%), while heterosexual transmission prevailed in females (77.07%) and older adults (≥ 60 years, 87.62%). Treatment success rate was 81.76%, significantly lower in the elderly (69.52%, P < 0.05). Any drug resistance (3.30%) increased from 1.54% to 3.10% ( χ ² trend =8.481, P trend =0.004), driven by rifampicin resistance ( χ ² trend =9.890, P trend =0.002). Conclusion Integrated strategies achieved initial success reducing HIV–TB incidence, particularly in high-burden areas and younger populations. Persistent challenges—stagnant incidence and poor outcomes in the elderly, high loss to follow-up (10.87%), rising drug resistance—require targeted interventions: leveraging the Yi “clan” ( Jiazhi ) system, strengthening active screening and nutritional support for older adults, optimizing drug resistance surveillance, and integrating digital health tools. HIV–TB co-infection integrated prevention and control epidemiological trend drug resistance Liangshan Yi Autonomous Prefecture resource-limited region Jiazhi (clan) system Figures Figure 1 Figure 2 Background Tuberculosis (TB) remains a serious global public health threat. According to the World Health Organization, the estimated global TB incidence rate in 2023 was 134 per 100,000 population, a rise from 2020 [ 1 ], and still far from the 2025 and 2035 targets set by the End TB Strategy [ 2 ]. China, as one of the world's high-burden countries, had an estimated approximately 741,000 new TB cases in 2023, ranking third globally, and the absolute number of newly reported cases remaining a notable public health concern [ 1 ]. Within China, Sichuan Province is a key region for persistent TB transmission, with marked spatial heterogeneity in its epidemic distribution [ 3 ]. Liangshan Yi Autonomous Prefecture bears one of the heaviest TB burdens in Sichuan. During the 13th Five-Year Plan period (2016–2020), the reported pulmonary TB incidence in Liangshan consistently ranked among the highest in the province. This situation is closely linked to socioeconomic vulnerabilities, including geographic remoteness, economic underdevelopment, and limited healthcare resources [ 4 , 5 ]. Key populations, including ethnic minorities and children in rural areas—face a disproportionately high TB incidence [ 6 ]. This burden is compounded by significantly low vaccination coverage among ethnic minority children, which poses an additional transmission risk [ 7 ]. In addition to its high TB burden, Liangshan also faces a severe and long-standing HIV epidemic. As the largest Yi-inhabited area in China and a resource-limited region, its unique socio-cultural context—including relatively open attitudes toward sexuality, very low condom use within marriage, unique marriage customs, and a history of drug production and trafficking—has shaped a complex HIV epidemic landscape [ 8 , 9 ]. In recent years, the local HIV epidemic shifted from concentrated transmission among high-risk groups (e.g., people who inject drugs) to general population spread, with heterosexual transmission gradually replacing injection drug use as the main route, reflecting the increasing complexity of the local transmission network [ 10 , 11 ]. This community-based, widespread HIV transmission pattern creates conditions conducive to the synergistic spread of opportunistic infections such as TB. The convergence of these two epidemics presents a major global public health challenge. They exacerbate each other pathologically: HIV infection not only increases the risk of latent TB reactivation and progression to active disease but also complicates TB diagnosis and treatment, leading to significantly higher mortality among co-infected patients [ 12 , 13 ]. Globally, TB is the leading cause of death among people living with HIV, with case fatality rates far exceeding those in HIV-negative individuals [ 1 ]. Global Burden of Disease studies show that the burden of HIV-TB co-infection falls most heavily on young adults and is strongly negatively correlated with the Socio-demographic Index (SDI) [ 14 ]. Low- and middle-income countries with a high disease burden face escalating challenges in clinical diagnosis and treatment delivery [ 15 – 19 ]. These challenges are equally evident in China, where TB is one of the most common opportunistic infections among people living with HIV [ 20 ]. Reports from several provinces—including Guangxi and Guizhou—indicate that HIV-TB co-infection has emerged as a critical public health issue affecting local populations [ 21 – 24 ]. This dual epidemic is particularly prominent in Liangshan. As early as 2008, Butuo County became the first county in China where the proportion of reported people living with HIV/AIDS exceeded 1% of the permanent population [ 25 ]. Local studies have found an HIV co-infection rate of 14.4% among hospitalized smear-positive pulmonary TB patients [ 26 ]. The two diseases exhibit significant spatial and demographic overlap, with synergistic transmission effects, posing a persistent threat to high-risk groups such as children and ethnic minorities [ 27 – 29 ]. In response to the severe HIV-TB co-infection crisis in Liangshan, the Chinese government launched the Integrated Prevention and Control of Four Diseases (IPC4D) policy in 2021, integrating HIV, TB, hepatitis C, and syphilis into a unified prevention and control framework. At the grassroots level, the multi-sectoral "1 + M + N+P" precision prevention and control model was gradually established: local governments provide coordination and leadership ("1"); township health centers deliver technical support ("M"); village doctors, HIV prevention workers, and maternal and child health workers are responsible for follow-up and health education ("N"); and public security departments assist with epidemiological investigations and patient tracing ("P"). Through integrated planning, information sharing, and coordinated service delivery, this initiative aims to improve patient management efficiency and treatment success rates. Attributable to targeted policy support and increased financial investment, HIV and TB screening efforts in Liangshan have been systematically expanded, and health education activities have been innovatively promoted to raise public awareness and reduce disease-related discrimination [ 30 ]. However, local prevention and control efforts still face considerable challenges: uneven resource allocation, with TB (particularly drug-resistant TB) remaining chronically underfunded; health workforce shortages, excessive workload at the grassroots level, and widespread professional burnout [ 31 ]; and timely treatment initiation and patient adherence continue to be affected by disease-related stigma, economic burden, and cultural and language barriers—all of which increase the risk of adverse outcomes for anti-tuberculosis treatment (ATT) [ 32 ]. In this context, analyzing the epidemiological trends of HIV-TB co-infection in Liangshan based on surveillance data serves two key purposes: to evaluate the interim effectiveness of the IPC4D policy and to identify critical weak links in real-world prevention and control practices. By objectively characterizing population-level trends, this analysis can help consolidate and optimize local control strategies and provide important insights for other resource-limited regions with a high burden of HIV-TB co-infection. Methods Study design and setting We conducted a retrospective case study in Liangshan Yi Autonomous Prefecture, Sichuan Province, a resource-limited region in Southwest China with a population of approximately 5.5 million and a dual high burden of HIV and tuberculosis. Data sources and linkage Data on HIV and TB cases among permanent residents of Liangshan Prefecture from 2019 to 2024 were obtained from the National Comprehensive HIV/AIDS Information Management System (CRIMS) and the Tuberculosis Information Management System (TBIMS) of the Chinese Center for Disease Control and Prevention. We extracted the TB database from the TBIMS and, in parallel, exported the HIV database (including both the real-time database and historical records from the CRIMS). All data were retrieved by designated personnel and encrypted prior to analysis. Individual records from the two databases were linked using unique national identification numbers to create an integrated, de-identified database of HIV-TB co-infected cases. Demographic data for Liangshan Prefecture for the period 2019–2024 were obtained from the annual household registration records of the Sichuan Provincial Department of Public Security. For patients with recorded deaths during follow-up, causes of death were supplemented through linkage with the China Cause of Death Reporting System (CDRS) (Fig. 1 ). Study population and definitions Data Cleaning, Study Population and Definitions We performed data cleaning on records of incident TB cases among permanent residents in Liangshan Prefecture from 2019 to 2024 in the integrated database. Records were excluded if they had incomplete treatment initiation dates, revised diagnoses, or TB infection alone (without HIV co-infection). Ultimately, 3,367 patients with HIV-TB co-infection were included in the analysis. Definitions of HIV/AIDS, TB cases, and treatment outcomes in this study strictly adhered to China's current national health industry standards and technical specifications [ 33 , 34 ], and were aligned with relevant WHO guidelines [ 35 , 36 ]. All case information was reported in a standardized manner. Data analysis We used SPSS version 30.0 and Excel 2007 to conduct descriptive statistical analyses of annual reported incidence, age, sex, ethnicity, marital status, education level, occupation, probable transmission routes and anti-TB treatment outcomes among the screened co-infected patients. Non-normally distributed continuous data were presented as median with interquartile range (P25, P75). The chi-square test was used for comparison of proportions, and the chi-square test for trend was used to assess temporal changes. Statistical significance was set at α = 0.05. Results Epidemiological trends and population profile From 2019 to 2024, a total of 3,367 HIV–TB co-infected cases were identified in Liangshan Prefecture, Sichuan Province. The majority of patients were male: 2,547 cases (75.60%) were male and 820 (24.40%) were female. The median age was 37 years (interquartile range [IQR]: 32–43). The predominant age group was 30–45 years, accounting for 61.10%, followed by 45–60 years (18.40%), 15–30 years (13.60%), < 15 years (3.70%), and ≥ 60 years (3.10%). Most patients were farmers (92.40%), with smaller proportions being students (2.90%), homemakers or unemployed individuals (1.10%), and other occupations. Against the policy backdrop of integrated prevention such as the IPC4D initiative, the reported incidence of HIV–TB co-infection in Liangshan Prefecture showed a significant downward trend from 2019 to 2024 ( χ ² trend = 40.459, P trend < 0.001). According to local demographic data, incidence varied significantly across population subgroups over the six years: it was markedly higher in males (15.26 per 100,000) than in females (5.19 per 100,000) ( χ ²= 793.847, P < 0.001). Differences in incidence by age group and county were also statistically significant (both P < 0.001). The highest incidence was in the 30–45-year age group (33.08 per 100,000), followed by the 45–60-year group (9.88 per 100,000). Butuo County (50.90 per 100,000), Zhaojue County (36.40 per 100,000), Meigu County (17.78 per 100,000), Yuexi County (17.41 per 100,000), and Jinyang County (17.24 per 100,000) ranked as the top five high-burden areas by incidence (Table 1 ). Table 1 Reported incidence of HIV–TB co-infection in Liangshan Prefecture, 2019–2024, by demographic and geographic characteristics ( n = 3,367) Characteristic Reported cases, n Reported incidence (per 100,000) χ ² / χ ² trend P value/ P trend value Year of report 40.459* < 0.001 2019 651 12.26 2020 605 11.35 2021 570 10.57 2022 524 9.65 2023 533 9.72 2024 484 8.76 Sex 793.847 < 0.001 male 2547 15.26 female 820 5.19 Age group (years) 4097.936 < 0.001 < 15 126 1.51 15–30 459 5.97 30–45 2057 33.08 45–60 620 9.88 ≥ 60 105 2.67 Place of residence 4927.384 < 0.001 Butuo County 675 50.90 Zhaojue County 742 36.40 Meigu County 307 17.78 Yuexi County 401 17.41 Jinyang County 225 17.24 Puge County 202 15.10 Xide County 163 12.28 Ganluo County 149 10.26 Xichang City 190 4.25 Leibo County 66 3.79 Mianning county 83 3.39 Dechang County 42 3.18 Yanyuan County 65 2.79 Ningnan County 26 2.14 Muli Tibetan Autonomous County 9 1.09 Huidong County 12 0.47 HuiLi City 10 0.36 Note: * indicates chi-square test for trend. Temporal trends and drivers of decline Analysis of annual incidence trends among HIV–TB co-infected patients with different characteristics in Liangshan from 2019 to 2024 showed that the overall decline was primarily driven by geographic and age factors. Geographically, the overall decline was mainly attributable to significant improvements in high-burden counties: Butuo, Zhaojue, Yuexi, Jinyang, and Xide—counties with higher baseline incidence—all showed significant downward trends in average annual reported incidence (all P trend < 0.05), whereas counties with lower baseline incidence showed no temporal changes. By age, all age groups under 45 years showed significant declines (all P trend < 0.001). For the 45–60-year group, the downward trend approached the threshold of statistical significance ( χ ² trend = 4.021, P trend = 0.045), while the ≥ 60-year group showed no significant decline ( χ ² trend =2.757, P trend = 0.097). The average annual incidence for both sexes showed downward trends over the six years (both P trend < 0.001) (Table 2 ). Table 2 Annual reported incidence of HIV–TB co-infection in Liangshan Prefecture, 2019–2024 ( n = 3,367) Characteristic 2019 2020 2021 2022 2023 2024 χ ² trend P trend value Cases, n Incidence (per 100,000) Cases, n Incidence (per 100,000) Cases, n Incidence (per 100,000) Cases, n Incidence (per 100,000) Cases, n Incidence (per 100,000) Cases, n Incidence (per 100,000) Place of residence Butuo County 156 72.80 139 64.74 71 32.57 104 46.72 94 41.38 111 48.38 18.985 < 0.001 Zhaojue County 88 25.84 110 33.49 162 48.25 118 34.66 142 41.15 122 35.01 4.043 0.044 Jinyang County 64 30.04 36 16.78 45 20.78 26 11.91 32 14.52 22 9.91 24.217 < 0.001 Yuexi County 86 22.99 81 21.60 64 16.78 65 16.84 54 13.80 51 12.89 17.122 < 0.001 Xide County 47 20.85 21 9.72 29 13.22 24 10.86 22 9.89 20 8.95 10.005 0.002 Meigu County 50 17.95 49 17.47 44 15.40 56 19.30 60 20.38 48 16.16 0.030 0.863 Puge County 33 15.12 40 18.26 39 17.54 38 17.00 22 9.74 30 13.10 2.803 0.094 Ganluo County 33 13.97 19 7.99 31 12.83 22 9.04 28 11.39 16 6.46 3.293 0.070 Leibo County 21 7.38 19 6.65 9 3.11 4 1.37 6 2.04 7 2.36 17.879 < 0.001 Mianning County 20 4.94 23 5.68 12 2.94 7 1.72 12 2.91 9 2.18 9.317 0.002 Ningnan County 7 3.49 3 1.49 5 2.46 2 0.99 7 3.44 2 0.98 0.895 0.344 Yanyuan County 13 3.38 16 4.15 10 2.57 10 2.57 9 2.31 7 1.80 3.572 0.059 Xichang City 21 3.04 42 5.79 34 4.59 33 4.39 34 4.41 26 3.30 0.328 0.567 Muli Tibetan Autonomous County 4 2.89 1 0.73 0 0.00 1 0.73 2 1.45 1 0.73 1.145 0.285 Dechang County 5 2.29 2 0.92 11 4.99 11 4.98 5 2.25 8 3.60 1.069 0.301 Huidong County 3 0.70 2 0.47 1 0.24 2 0.47 1 0.24 3 0.71 0.024 0.878 Huili City 0 0.00 2 0.43 3 0.65 1 0.22 3 0.65 1 0.22 0.308 0.579 Age group (years) < 15 30 2.12 34 2.40 15 1.07 20 1.44 16 1.16 11 0.81 12.905 < 0.001 15–30 105 8.34 97 7.74 73 5.74 68 5.29 66 5.09 50 3.80 29.547 < 0.001 30–45 405 39.41 367 35.86 352 34.53 324 31.49 331 31.54 278 26.02 31.095 < 0.001 45–60 87 8.92 89 8.77 111 10.40 101 9.34 108 10.07 124 11.63 4.021 0.045 ≥ 60 24 3.80 18 2.88 19 3.02 11 1.71 12 1.74 21 2.90 2.757 0.097 Sex Male 475 17.40 444 16.20 432 15.59 390 13.98 428 15.19 378 13.32 16.260 < 0.001 Female 176 6.82 161 6.21 138 5.26 134 5.07 105 3.94 106 3.94 33.145 < 0.001 Characteristics of HIV transmission and TB treatment profiles The HIV transmission routes, anti-TB treatment outcomes, and drug resistance profiles of newly reported HIV–TB co-infected patients in Liangshan from 2019 to 2024 are shown in Table 3 . Heterosexual transmission was the predominant HIV route (48.29%), followed by injection drug use (41.31%) and mother-to-child transmission (3.42%); homosexual transmission accounted for the smallest proportion (0.30%). Regarding anti-TB treatment outcomes, 81.76% of patients completed treatment or were cured, approximately 1.93% were transferred to multidrug-resistant TB (MDR-TB) treatment, 0.80% experienced adverse treatment outcomes (adverse reactions, treatment failure, or TB-related death), and 10.87% were lost to follow-up or had unknown outcomes. Drug resistance testing revealed that 3.30% of co-infected patients had TB drug resistance. Among resistant cases, the main types were resistance to rifampicin (46.85%) and isoniazid (28.83%), followed by MDR-TB (23.42%). Table 3 Characteristics of HIV transmission routes, anti-TB treatment outcomes, and drug resistance among HIV–TB co-infected patients in Liangshan Prefecture, 2019–2024 ( n = 3,367) Characteristic Cases, n Proportion (%) HIV transmission route Heterosexual transmission 1626 48.29 Injection drug use 1391 41.31 Sexual contact + injection drug use 137 4.07 Mother-to-child transmission 115 3.42 Unknown 63 1.87 Homosexual transmission 10 0.30 Other 25 0.74 Anti-TB drug resistance No drug resistance 3256 96.70 Rifampicin-resistant 52 1.54 Isoniazid-resistant 32 0.95 Multidrug-resistant (MDR) 26 0.77 Pre-extensively drug-resistant 1 0.03 Anti-TB treatment outcome Completed treatment or cured 2753 81.76 Transferred to MDR-TB treatment 65 1.93 Adverse TB treatment outcome 27 0.80 Death not due to TB 156 4.63 Lost to follow-up or unknown 366 10.87 Factors associated with HIV transmission and TB outcomes To further explore the distribution of the above characteristics across different populations, we performed a stratified analysis by sex and age group for HIV transmission routes, drug resistance, and anti-TB treatment outcomes (Table 4 ). By sex, there were statistically significant differences in HIV transmission routes and anti-TB drug resistance (both P < 0.05), while the difference in anti-TB treatment outcomes was not significant ( χ ²=5.446, P = 0.245). By age group, there were statistically significant differences in HIV transmission routes and anti-TB treatment outcomes (both P < 0.05), while the difference in anti-TB drug resistance was not significant ( χ ²=2.824, P = 0.588). These differences were primarily manifested in the fact that injection drug use was the predominant HIV route for males, while heterosexual transmission was predominant for females; the proportion of females who completed treatment or were cured was slightly higher than that of males. Regarding age groups, injection drug use was the main HIV route for those aged 30–45 years (50.32%), whereas heterosexual transmission was the main route for all other age groups, notably reaching 87.62% in those aged ≥ 60 years. Importantly, the proportion of patients aged ≥ 60 years who completed treatment or were cured was less than 70% (69.52%), significantly lower than that of other age groups (pairwise comparisons with Bonferroni correction, P < 0.05). Table 4 Factors associated with HIV transmission routes, drug resistance, and anti-TB treatment outcomes among HIV–TB co-infected patients in Liangshan Prefecture, 2019–2024, by sex and age group (n = 3,367) Characteristic Sex Age group (years) Male Female χ ² P value < 15 15–30 30- <45 45 - <60 ≥ 60 χ ² P value HIV transmission route 501.741 < 0.001 2446.684 < 0.001 Heterosexual transmission 994 (39.03) 632 (77.07) 501.741 < 0.001 2 (1.59) 292 (63.62) 914 (44.43) 326 (52.58) 92 (87.62) 2446.684 < 0.001 Injection drug use 1297 (50.92) 94 (11.46) 501.741 < 0.001 1 (0.79) 98 (21.35) 1035 (50.32) 245 (39.52) 12 (11.43) 2446.684 < 0.001 Sexual contact + injection drug use 132 (5.18) 5 (0.61) 501.741 < 0.001 0(0.00) 11 (2.40) 85 (4.13) 41 (6.61) 0(0.00) 2446.684 < 0.001 Mother-to-child transmission 58 (2.28) 57 (6.95) 501.741 < 0.001 90 (71.43) 25 (5.45) 0(0.00) 0(0.00) 0(0.00) 2446.684 < 0.001 Unknown 39 (1.53) 24 (2.93) 501.741 < 0.001 25 (19.84) 17 (3.70) 14 (0.68) 6 (0.97) 1 (0.95) 2446.684 < 0.001 Homosexual transmission 10 (0.39) 0(0.00) 501.741 < 0.001 0(0.00) 4 (0.87) 5 (0.24) 1 (0.16) 0(0.00) 2446.684 < 0.001 Other 17 (0.67) 8 (0.98) 501.741 < 0.001 8 (6.35) 12 (2.61) 4 (0.19) 1 (0.16) 0(0.00) 2446.684 < 0.001 Anti-TB drug resistance 4.126 0.042 2.824 0.588 No drug resistance 2454 (96.35) 802 (97.80) 4.126 0.042 124 (98.41) 446 (97.17) 1990 (96.74) 596 (96.13) 100 (95.24) 2.824 0.588 Rifampicin-resistant 42 (1.65) 10 (1.22) 4.126 0.042 1 (0.79) 5 (1.09) 36 (1.75) 7 (1.13) 3 (2.86) 2.824 0.588 Isoniazid-resistant 27 (1.06) 5 (0.61) 4.126 0.042 1 (0.79) 6 (1.31) 17 (0.83) 7 (1.13) 1 (0.95) 2.824 0.588 Multidrug-resistant (MDR) 23 (0.90) 3 (0.37) 4.126 0.042 0 2 (0.44) 13 (0.63) 10 (1.61) 1 (0.95) 2.824 0.588 Pre-extensively drug-resistant 1 (0.04) 0(0.00) 4.126 0.042 0(0.00) 0(0.00) 1 (0.05) 0(0.00) 0(0.00) 2.824 0.588 Anti-TB treatment outcome 5.446 0.245 28.749 0.026 Completed treatment or cured 2069 (81.23) 684 (83.41) 5.446 0.245 105 (83.33) 384 (83.66) 1698 (82.55) 493 (79.52) 73 (69.52) 28.749 0.026 Transferred to MDR-TB treatment 54 (2.12) 11 (1.34) 5.446 0.245 1 (0.79) 8 (1.74) 40 (1.94) 13 (2.10) 3 (2.86) 28.749 0.026 Adverse TB treatment outcome 18 (0.71) 9 (1.10) 5.446 0.245 1(0.80) 2(0.44) 22 (0.32) 2(5.00) 0(0.00) 28.749 0.026 Death not due to TB 125 (4.91) 31 (3.78) 5.446 0.245 5 (3.97) 13 (2.83) 97 (4.72) 31 (5.32) 10 (9.52) 28.749 0.026 Lost to follow-up or unknown 281 (11.03) 85 (10.37) 5.446 0.245 14 (11.11) 52 (11.33) 200 (9.72) 81 (13.06) 19 (18.10) 28.749 0.026 Note: Values in parentheses are column percentages (%). Drug resistance trends in the context of integrated prevention From 2019 to 2024, the overall TB drug resistance rate among HIV–TB co-infected patients in Liangshan was 3.30%. Rifampicin resistance was the most common type (46.85% of resistant cases), followed by isoniazid resistance (28.83%) and MDR-TB (23.42%). Regarding temporal trends, though it slightly decreased in 2024, the overall drug resistance rate showed a significant upward trend ( χ ² trend = 8.481, P trend = 0.004), rising from 1.54% in 2019 to 3.10% in 2024, with the highest reported rate in 2023 (4.88%). Analyzing specific resistance types, this upward trend was primarily driven by a significant increase in rifampicin resistance ( χ ² trend = 9.890, P trend = 0.002). Trends for isoniazid resistance, MDR-TB, and pre-extensively drug-resistant TB were not statistically significant ( χ ² trend = 0.334, 2.323, and 0.946, P trend = 0.853, 0.127, and 0.331, respectively) (Fig. 1 ). Discussion Liangshan Prefecture in Sichuan Province is an area with a dual high burden of HIV and TB. HIV–TB co-infection in this region warrants particular attention and may provide important insights for other high-burden, resource-limited settings worldwide. Overall trends in the context of integrated prevention Against the policy backdrop of the IPC4D policy and “1 + M + N+P” precision prevention and control models, the reported incidence of HIV–TB co-infection in Liangshan showed a significant downward trend from 2019 to 2024 (from 12.26 per 100,000 to 8.76 per 100,000), consistent with reports from other regions in China [ 37 ]. However, global burden of disease models and local studies suggest that the age-standardized burden of HIV–TB in low-SDI regions may continue to rise in the coming years [ 1 , 14 ], indicating that Liangshan's prevention and control achievements need sustained consolidation. Studies have indicated that relying solely on symptom-based screening is insufficient to detect all TB cases, recommending systematic TB screening for people living with HIV during every healthcare encounter to reduce diagnostic delays [ 38 ]. This evidence offers valuable insights for optimizing screening strategies in Liangshan. Geographic and demographic drivers of decline The demographic profile of HIV–TB co-infected patients in Liangshan from 2019 to 2024 was highly concentrated, predominantly involving young adult males (30–45 years) and farmers (92.37%), similar to reports from other countries and Chinese provinces [ 13 , 23 , 37 , 39 ]. The decline in incidence in high-burden counties such as Butuo, Zhaojue, Yuexi, and Jinyang was a major driver of the Liangshan's overall decline. This reflects the effectiveness of the Chinese government's strategy of concentrated resource allocation and precision interventions (e.g., expanded screening, community mobilization, multi-sectoral collaboration) in key disease control areas. The significant decline in all age groups under 45 years suggests a good response to prevention and control measures among the younger population. The downward trend in incidence for both sexes indicates that local interventions have achieved good coverage across genders. These findings demonstrate that Liangshan's prevention and control strategies have achieved initial success in key areas and populations, offering valuable lessons for other high-burden regions. Persistent challenges: the neglected older adults In stark contrast to the positive trends above, the incidence in the ≥ 60-year age group showed no significant decline over the six years, and their treatment success rate (69.52%) was significantly lower than that of other age groups. Older patients may face barriers to active participation in screening and regular follow-up due to declining physical function, multiple comorbidities, poverty, and limited healthcare access [ 40 ]. Concurrently, weak social support networks—including being empty nesters, widowhood, and adult child out-migration—leave them without adequate supervision and care during treatment. Local studies have shown that low BMI is a strong predictor of death among HIV/AIDS patients [ 41 ], and malnutrition is common among the elderly, further increasing the risk of adverse outcomes. Notably, 87.62% of older patients were infected with HIV via heterosexual transmission, indicating that health education and disease prevention efforts related to sexual activity need to be strengthened for this population. Older adults should become a key focus for the next phase of prevention and control efforts, with an urgent need for targeted active screening, simplified treatment procedures, and nutritional support programs. Transmission route syndemic and its implications The HIV transmission routes among co-infected patients in this study reveal a deeper “syndemic” pattern: injection drug use predominates in males (50.92%), while heterosexual transmission predominates in females (77.07%); injection drug use is dominant in the 30–45-year age group (50.32%), whereas heterosexual transmission is dominant in all other age groups, reaching 87.62% in those aged ≥ 60 years. This pattern reflects the complexity of HIV transmission within Liangshan's unique socio-cultural context. This syndemic presents multidimensional requirements for prevention and control. First, young adult male farmers face both drug-related risks and difficulties in regular follow-up due to high mobility, necessitating strengthened pre-migration screening and mobile population management [ 31 ]. Second, women infected through heterosexual transmission require support to enhance their negotiation skills in sexual activities and access to diverse protective measures [ 8 ]. Third, the varying transmission characteristics across age groups call for targeted sexual health education for those aged ≥ 60 years, and integrated interventions—combining drug prevention, sexual health promotion, and family-based approaches—for the “mixed” transmission pattern seen in the 30–45-year age group [ 42 – 43 ]. Treatment outcomes, loss to follow-up, and the threat of drug resistance The treatment success rate in this study was 81.76%, lower than the provincial average for Sichuan during the same period (89.01%) [ 4 ]. The proportion of patients lost to follow-up or with unknown outcomes was 10.87%, far exceeding that in the general TB population and consistent with findings from an international multi-center study [ 44 ]. Poor treatment adherence and loss to follow-up in this setting stem from multiple interacting factors. At the patient level, the long treatment duration for TB (especially drug-resistant TB), high medication burden, and frequent adverse drug reactions—compounded by potential additive toxicities when combined with ART [ 45 ]—create significant barriers to adherence. These are further exacerbated by low health literacy, economic hardship, and lack of family support [ 46 ]. At the health system level, "N"-level personnel such as village doctors and HIV prevention officers, working under the integrated service model, face dramatically increased workloads, understaffing, heavy caseloads, and insufficient funding, leading to less intensive follow-up supervision [ 31 ]. These factors may compromise timely follow-up and intervention for patients with poor adherence, such as some older adults. Another local study found a paradoxically higher risk of death among patients followed up at county-level hospitals or above [ 47 ], suggesting that reliance solely on higher-level medical institutions is insufficient. Strengthening the tripartite "hospital-community-family" linkage model locally—by promoting consistent medication supervision and supportive care at the grassroots level, and developing objective adherence assessment methods—is needed to address previous shortcomings in long-term follow-up management [ 48 ]. Loss to follow-up not only potentially signifies treatment failure but also acts as a breeding ground for drug resistance. Studies indicate that Liangshan's high drug-resistant TB rate—among the highest in China—is primarily due to patient non-adherence rather than primary resistance to drug-resistant strains [ 31 ]. The upward trend in the overall drug resistance rate observed in this study, particularly for rifampicin, can be seen as a sentinel event signaling inadequate treatment adherence among local co-infected patients. Therefore, it is crucial to strengthen drug resistance surveillance among high-risk groups (males, older adults, those with low education, unmarried/divorced individuals, and farmers), promote rapid molecular testing, explore digital health tools to support supervision [ 48 – 50 ], and consider providing tangible support such as transportation subsidies and nutritional packages. Simultaneously, alleviating the workload of grassroots "N"-level personnel is essential to ensure follow-up quality [ 30 , 51 ]. Through these comprehensive measures, the emergence of additional drug-resistant TB patients can be curbed. Conclusion Drawing on surveillance data of HIV–TB co-infection in Liangshan Prefecture from 2019 to 2024, this study provides a comprehensive analysis of epidemiological trends and infection characteristics within the context of integrated prevention. Key findings include a declining incidence trend, supporting the interim effectiveness of the "Four Diseases Co-prevention" policy. The decline was primarily driven by high-burden counties and younger populations, demonstrating the value of targeted precision interventions. The lack of improvement in incidence and low treatment success rate among older adults highlight a critical weak link in current control efforts, while loss to follow-up and emerging TB drug resistance threaten the progress achieved. Building on these findings, we propose four priorities for comprehensive prevention and control in Liangshan and similar high-burden settings: Place-based strategies: harnessing indigenous social resources. In high-burden counties such as Butuo and Zhaojue, the workload for grassroots follow-up is immense, with village doctors and HIV prevention officers facing staff shortages. Drawing on the Yi “clan” ( Jiazhi ) system, collaboration with clan leaders could be explored to integrate patient follow-up and medication supervision into traditional social networks, thereby improving intervention sustainability and cultural appropriateness. People-centered approaches: implementing precision interventions. For older adults, we recommend establishing active screening mechanisms (e.g., integrated into local chronic disease management clinics), providing simplified treatment regimens, and strengthening nutritional support. For women, empowerment through women's health groups and peer education can enhance sexual health autonomy. For young adult male farmers, integrated screening should be delivered around key periods such as pre-migration and Spring Festival return, with improved follow-up for mobile populations. Resource-optimized initiatives: filling gaps in drug resistance prevention and control. Given that rifampicin resistance continues to drive the increase in overall drug resistance rates, and that local funding for TB (especially drug-resistant TB) remains substantially lower than for HIV, targeted interventions are urgently needed. We recommend expanding rapid drug resistance testing for all HIV–TB patients, establishing dedicated follow-up pathways for drug-resistant cases, and increasing financial support and performance incentives for key diagnostic procedures. Technology- and support-integrated efforts: improving adherence management efficiency. Digital health tools (medication reminder apps, wearable devices) can be deployed to support supervision, with family engagement. Concurrently, tangible support such as transport subsidies and nutritional supplements can reduce patient burden, while task rationalization and performance incentives can alleviate burnout among frontline workers. Global evidence indicates that HIV–TB co-infection control is closely tied to socioeconomic development. In low-SDI settings, disease control is particularly challenging, and expanding treatment coverage alone is insufficient to rapidly reduce disease burden [20]. The Liangshan experience shows that policy integration and targeted resource investment can achieve meaningful progress, but sustained success requires a systemic approach: strengthening grassroots diagnostic capacity, optimizing health system support, improving education for key populations, and improving service accessibility. Future research should prioritize tracing and characterizing patients lost to follow-up to generate further evidence for optimizing follow-up management and care retention. Abbreviations ART: Antiretroviral therapy; ATT: Anti-tuberculosis treatment; BMI: Body mass index;CDRS: China Cause of Death Reporting System; CRIMS: National Comprehensive HIV/AIDS Information Management System; HIV: Human Immunodeficiency Virus; IPC4D: Integrated Prevention and Control of Four Diseases; IQR: Interquartile range; MDR-TB: Multidrug-resistant tuberculosis SDI: Socio-demographic Index; TB: Tuberculosis; TBIMS: Tuberculosis Information Management System; WHO: World Health Organization. Declarations Ethics Declarations Ethics Approval and Consent to Participate The study protocol was reviewed and approved by the Ethics Committee of the Sichuan Center for Disease Control and Prevention (Approval No. SCCDCIRB-2026-002). The need for individual informed consent was waived due to the retrospective, anonymized nature of the routine surveillance data, in accordance with the committee’s guidelines. Consent for Publication Not applicable. Availability of Data and Materials The data that support the findings of this study are available from the Liangshan Center for Disease Control and Prevention, but restrictions apply to the availability of these data, which were used under license for the current study and so are not publicly available. Data are, however, available from the corresponding authors upon reasonable request and with permission of the Liangshan Center for Disease Control and Prevention. Competing Interests The authors declare that they have no competing interests. Funding This research was funded by the Liangshan Prefecture Science and Technology Bureau Program (grant number 23ZDYF0025). The funder had no role in study design, data collection, analysis, interpretation, or writing of the manuscript. Authors' Contributions B.X.F. and W.J. contributed equally to conceptualization, data curation, formal analysis, investigation, methodology, project administration, writing – original draft, and writing – review & editing. Y.G. contributed to conceptualization, data curation, formal analysis, investigation, methodology, and supervision. S.J.H. and F.S.S. were responsible for conceptualization, data curation, software, visualization, and writing – original draft. W.R.B., W.Y.B., and F.X.Y. contributed to conceptualization, data curation, formal analysis, investigation, and project administration. P.R. and L.R.J. served as co-corresponding authors, overseeing conceptualization, formal analysis, funding acquisition, investigation, methodology, project administration, supervision, validation, and writing – review & editing. All authors read and approved the final manuscript. Acknowledgements We are deeply grateful to the healthcare workers at the county, township, and village levels in Liangshan for their tireless efforts in data collection and patient care. We also thank the staff at the Liangshan Center for Disease Control and Prevention for their invaluable support. Authors’ Information Affiliations: ¹ Sichuan Center for Disease Control and Prevention, Chengdu 610041, Sichuan Province, China. ² Liangshan Center for Disease Control and Prevention, Liangshan Yi Autonomous Prefecture 615000, Sichuan Province, China. ³ School of Public Health, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, Sichuan Province, China. Authors’ ORCID: Liao Rujun：0000-0001-8528-0846 Pei Rong：0000-0002-2876-901X Wang Ju: 0009-0000-2588-6977 Bai Xuefei: 0009-0004-5845-3130 Fan Sisi: 0009-0000-7615-360X References Hu XY, Gao JT. Interpretation of WHO Global Tuberculosis Report 2024. J Tuberc Lung Dis. 2024;5(6):500–4. World Health Organization. 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PLoS One. 2018;13(3):e0193491. Singh A, Prasad VR, Balasubramanian N, et al. Drug-Resistant Tuberculosis and HIV Infection: Current Perspectives. HIV/AIDS - Res Palliat Care. 2020;12:9-31. Bi R, Dou L, Pei R, et al. A mixed-methods study on healthcare workers’ perceptions of treatment adherence among HIV-TB co-infected patients in a multi-disease prevention policy context. Front Public Health. 2025;13:1704215. Zhuoma L, Zeng Y, Yu G, et al. Survival of HIV infected patients receiving antiretroviral therapy in four counties in Liangshan Prefecture. Chin J AIDS STD. 2022;28(2):133-137. Liao R, Tang Z, Zhang N, et al. Discrepancies between self-reported medication in adherence and indirect measurement adherence among patients undergoing antiretroviral therapy: a systematic review. Infect Dis Poverty. 2024 Jul 5;13(1):51. Sossen B, Kubjane M, Meintjes G. Tuberculosis and HIV coinfection: Progress and challenges towards reducing incidence and mortality. 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Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 10 May, 2026 Reviews received at journal 10 May, 2026 Reviews received at journal 01 May, 2026 Reviewers agreed at journal 01 May, 2026 Reviewers agreed at journal 29 Apr, 2026 Reviewers agreed at journal 17 Apr, 2026 Reviewers invited by journal 08 Mar, 2026 Editor assigned by journal 05 Mar, 2026 Submission checks completed at journal 05 Mar, 2026 First submitted to journal 04 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9028669","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Case Report","associatedPublications":[],"authors":[{"id":603639142,"identity":"a7045e26-4363-4345-a2d3-e6e794e3bab9","order_by":0,"name":"Xuefei Bai","email":"","orcid":"","institution":"Sichuan Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Xuefei","middleName":"","lastName":"Bai","suffix":""},{"id":603639143,"identity":"5398ab8e-0d4e-441b-9ef3-0760eaba2ebc","order_by":1,"name":"Ju Wang","email":"","orcid":"","institution":"Liangshan Center for Disease Control and 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07:42:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":141780,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 1.\u003c/strong\u003e Trends in anti-TB drug resistance patterns among HIV–TB co-infected patients in Liangshan Prefecture, 2019–2024\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9028669/v1/14fed9ec76aa86b94f4978b0.png"},{"id":104548780,"identity":"30c63d5f-4522-427c-b3a3-a163d8ff9d1b","added_by":"auto","created_at":"2026-03-13 07:43:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1848001,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9028669/v1/84b917c5-6b6e-45f4-a7e6-0ff3e2e2f399.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eHIV–TB co-infection in Liangshan, a resource-limited region of Southwest China: trends and implications in the context of integrated prevention, 2019–2024\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eTuberculosis (TB) remains a serious global public health threat. According to the World Health Organization, the estimated global TB incidence rate in 2023 was 134 per 100,000 population, a rise from 2020 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], and still far from the 2025 and 2035 targets set by the End TB Strategy [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. China, as one of the world's high-burden countries, had an estimated approximately 741,000 new TB cases in 2023, ranking third globally, and the absolute number of newly reported cases remaining a notable public health concern [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWithin China, Sichuan Province is a key region for persistent TB transmission, with marked spatial heterogeneity in its epidemic distribution [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Liangshan Yi Autonomous Prefecture bears one of the heaviest TB burdens in Sichuan. During the 13th Five-Year Plan period (2016\u0026ndash;2020), the reported pulmonary TB incidence in Liangshan consistently ranked among the highest in the province. This situation is closely linked to socioeconomic vulnerabilities, including geographic remoteness, economic underdevelopment, and limited healthcare resources [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Key populations, including ethnic minorities and children in rural areas\u0026mdash;face a disproportionately high TB incidence [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This burden is compounded by significantly low vaccination coverage among ethnic minority children, which poses an additional transmission risk [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition to its high TB burden, Liangshan also faces a severe and long-standing HIV epidemic. As the largest Yi-inhabited area in China and a resource-limited region, its unique socio-cultural context\u0026mdash;including relatively open attitudes toward sexuality, very low condom use within marriage, unique marriage customs, and a history of drug production and trafficking\u0026mdash;has shaped a complex HIV epidemic landscape [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In recent years, the local HIV epidemic shifted from concentrated transmission among high-risk groups (e.g., people who inject drugs) to general population spread, with heterosexual transmission gradually replacing injection drug use as the main route, reflecting the increasing complexity of the local transmission network [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. This community-based, widespread HIV transmission pattern creates conditions conducive to the synergistic spread of opportunistic infections such as TB.\u003c/p\u003e \u003cp\u003eThe convergence of these two epidemics presents a major global public health challenge. They exacerbate each other pathologically: HIV infection not only increases the risk of latent TB reactivation and progression to active disease but also complicates TB diagnosis and treatment, leading to significantly higher mortality among co-infected patients [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Globally, TB is the leading cause of death among people living with HIV, with case fatality rates far exceeding those in HIV-negative individuals [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Global Burden of Disease studies show that the burden of HIV-TB co-infection falls most heavily on young adults and is strongly negatively correlated with the Socio-demographic Index (SDI) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Low- and middle-income countries with a high disease burden face escalating challenges in clinical diagnosis and treatment delivery [\u003cspan additionalcitationids=\"CR16 CR17 CR18\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThese challenges are equally evident in China, where TB is one of the most common opportunistic infections among people living with HIV [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Reports from several provinces\u0026mdash;including Guangxi and Guizhou\u0026mdash;indicate that HIV-TB co-infection has emerged as a critical public health issue affecting local populations [\u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This dual epidemic is particularly prominent in Liangshan. As early as 2008, Butuo County became the first county in China where the proportion of reported people living with HIV/AIDS exceeded 1% of the permanent population [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Local studies have found an HIV co-infection rate of 14.4% among hospitalized smear-positive pulmonary TB patients [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The two diseases exhibit significant spatial and demographic overlap, with synergistic transmission effects, posing a persistent threat to high-risk groups such as children and ethnic minorities [\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn response to the severe HIV-TB co-infection crisis in Liangshan, the Chinese government launched the Integrated Prevention and Control of Four Diseases (IPC4D) policy in 2021, integrating HIV, TB, hepatitis C, and syphilis into a unified prevention and control framework. At the grassroots level, the multi-sectoral \"1\u0026thinsp;+\u0026thinsp;M\u0026thinsp;+\u0026thinsp;N+P\" precision prevention and control model was gradually established: local governments provide coordination and leadership (\"1\"); township health centers deliver technical support (\"M\"); village doctors, HIV prevention workers, and maternal and child health workers are responsible for follow-up and health education (\"N\"); and public security departments assist with epidemiological investigations and patient tracing (\"P\"). Through integrated planning, information sharing, and coordinated service delivery, this initiative aims to improve patient management efficiency and treatment success rates.\u003c/p\u003e \u003cp\u003eAttributable to targeted policy support and increased financial investment, HIV and TB screening efforts in Liangshan have been systematically expanded, and health education activities have been innovatively promoted to raise public awareness and reduce disease-related discrimination [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. However, local prevention and control efforts still face considerable challenges: uneven resource allocation, with TB (particularly drug-resistant TB) remaining chronically underfunded; health workforce shortages, excessive workload at the grassroots level, and widespread professional burnout [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]; and timely treatment initiation and patient adherence continue to be affected by disease-related stigma, economic burden, and cultural and language barriers\u0026mdash;all of which increase the risk of adverse outcomes for anti-tuberculosis treatment (ATT) [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this context, analyzing the epidemiological trends of HIV-TB co-infection in Liangshan based on surveillance data serves two key purposes: to evaluate the interim effectiveness of the IPC4D policy and to identify critical weak links in real-world prevention and control practices. By objectively characterizing population-level trends, this analysis can help consolidate and optimize local control strategies and provide important insights for other resource-limited regions with a high burden of HIV-TB co-infection.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective case study in Liangshan Yi Autonomous Prefecture, Sichuan Province, a resource-limited region in Southwest China with a population of approximately 5.5\u0026nbsp;million and a dual high burden of HIV and tuberculosis.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData sources and linkage\u003c/h3\u003e\n\u003cp\u003eData on HIV and TB cases among permanent residents of Liangshan Prefecture from 2019 to 2024 were obtained from the National Comprehensive HIV/AIDS Information Management System (CRIMS) and the Tuberculosis Information Management System (TBIMS) of the Chinese Center for Disease Control and Prevention. We extracted the TB database from the TBIMS and, in parallel, exported the HIV database (including both the real-time database and historical records from the CRIMS). All data were retrieved by designated personnel and encrypted prior to analysis.\u003c/p\u003e \u003cp\u003eIndividual records from the two databases were linked using unique national identification numbers to create an integrated, de-identified database of HIV-TB co-infected cases. Demographic data for Liangshan Prefecture for the period 2019\u0026ndash;2024 were obtained from the annual household registration records of the Sichuan Provincial Department of Public Security. For patients with recorded deaths during follow-up, causes of death were supplemented through linkage with the China Cause of Death Reporting System (CDRS) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eStudy population and definitions\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData Cleaning, Study Population and Definitions\u003c/h2\u003e \u003cp\u003eWe performed data cleaning on records of incident TB cases among permanent residents in Liangshan Prefecture from 2019 to 2024 in the integrated database. Records were excluded if they had incomplete treatment initiation dates, revised diagnoses, or TB infection alone (without HIV co-infection). Ultimately, 3,367 patients with HIV-TB co-infection were included in the analysis. Definitions of HIV/AIDS, TB cases, and treatment outcomes in this study strictly adhered to China's current national health industry standards and technical specifications [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], and were aligned with relevant WHO guidelines [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. All case information was reported in a standardized manner.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eWe used SPSS version 30.0 and Excel 2007 to conduct descriptive statistical analyses of annual reported incidence, age, sex, ethnicity, marital status, education level, occupation, probable transmission routes and anti-TB treatment outcomes among the screened co-infected patients. Non-normally distributed continuous data were presented as median with interquartile range (P25, P75). The chi-square test was used for comparison of proportions, and the chi-square test for trend was used to assess temporal changes. Statistical significance was set at \u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eEpidemiological trends and population profile\u003c/h2\u003e \u003cp\u003eFrom 2019 to 2024, a total of 3,367 HIV\u0026ndash;TB co-infected cases were identified in Liangshan Prefecture, Sichuan Province. The majority of patients were male: 2,547 cases (75.60%) were male and 820 (24.40%) were female. The median age was 37 years (interquartile range [IQR]: 32\u0026ndash;43). The predominant age group was 30\u0026ndash;45 years, accounting for 61.10%, followed by 45\u0026ndash;60 years (18.40%), 15\u0026ndash;30 years (13.60%), \u0026lt;\u0026thinsp;15 years (3.70%), and \u0026ge;\u0026thinsp;60 years (3.10%). Most patients were farmers (92.40%), with smaller proportions being students (2.90%), homemakers or unemployed individuals (1.10%), and other occupations.\u003c/p\u003e \u003cp\u003eAgainst the policy backdrop of integrated prevention such as the IPC4D initiative, the reported incidence of HIV\u0026ndash;TB co-infection in Liangshan Prefecture showed a significant downward trend from 2019 to 2024 (\u003cem\u003eχ\u003c/em\u003e\u0026sup2;\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e = 40.459, \u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e \u0026lt; 0.001). According to local demographic data, incidence varied significantly across population subgroups over the six years: it was markedly higher in males (15.26 per 100,000) than in females (5.19 per 100,000) (\u003cem\u003eχ\u003c/em\u003e\u0026sup2;= 793.847, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Differences in incidence by age group and county were also statistically significant (both \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The highest incidence was in the 30\u0026ndash;45-year age group (33.08 per 100,000), followed by the 45\u0026ndash;60-year group (9.88 per 100,000). Butuo County (50.90 per 100,000), Zhaojue County (36.40 per 100,000), Meigu County (17.78 per 100,000), Yuexi County (17.41 per 100,000), and Jinyang County (17.24 per 100,000) ranked as the top five high-burden areas by incidence (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eReported incidence of HIV\u0026ndash;TB co-infection in Liangshan Prefecture, 2019\u0026ndash;2024, by demographic and geographic characteristics (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3,367)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReported cases, \u003cem\u003en\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReported incidence\u003c/p\u003e \u003cp\u003e(per 100,000)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u0026sup2; /\u003cem\u003eχ\u003c/em\u003e\u0026sup2;\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value/ \u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear of report\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.459*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e651\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e605\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e533\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e484\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e793.847\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2547\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e820\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4097.936\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e459\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlace of residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4927.384\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eButuo County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e675\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZhaojue County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e742\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeigu County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYuexi County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJinyang County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePuge County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eXide County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGanluo County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eXichang City\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeibo County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMianning county\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDechang County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYanyuan County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNingnan County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuli Tibetan Autonomous County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuidong County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuiLi City\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: * indicates chi-square test for trend.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTemporal trends and drivers of decline\u003c/h3\u003e\n\u003cp\u003eAnalysis of annual incidence trends among HIV\u0026ndash;TB co-infected patients with different characteristics in Liangshan from 2019 to 2024 showed that the overall decline was primarily driven by geographic and age factors.\u003c/p\u003e \u003cp\u003eGeographically, the overall decline was mainly attributable to significant improvements in high-burden counties: Butuo, Zhaojue, Yuexi, Jinyang, and Xide\u0026mdash;counties with higher baseline incidence\u0026mdash;all showed significant downward trends in average annual reported incidence (all \u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e \u0026lt; 0.05), whereas counties with lower baseline incidence showed no temporal changes. By age, all age groups under 45 years showed significant declines (all \u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e \u0026lt; 0.001). For the 45\u0026ndash;60-year group, the downward trend approached the threshold of statistical significance (\u003cem\u003eχ\u003c/em\u003e\u0026sup2;\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e = 4.021, \u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e = 0.045), while the \u0026ge;\u0026thinsp;60-year group showed no significant decline (\u003cem\u003eχ\u003c/em\u003e\u0026sup2;\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e =2.757, \u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e = 0.097). The average annual incidence for both sexes showed downward trends over the six years (both \u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e \u0026lt; 0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnnual reported incidence of HIV\u0026ndash;TB co-infection in Liangshan Prefecture, 2019\u0026ndash;2024 (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3,367)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"15\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u0026sup2;\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCases, n\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncidence\u003c/p\u003e \u003cp\u003e(per 100,000)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCases, n\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIncidence\u003c/p\u003e \u003cp\u003e(per 100,000)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCases, n\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIncidence\u003c/p\u003e \u003cp\u003e(per 100,000)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCases, n\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eIncidence\u003c/p\u003e \u003cp\u003e(per 100,000)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCases, n\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eIncidence\u003c/p\u003e \u003cp\u003e(per 100,000)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eCases, \u003cem\u003en\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eIncidence\u003c/p\u003e \u003cp\u003e(per 100,000)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlace of residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eButuo County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e64.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e32.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e46.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e41.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e48.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e18.985\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZhaojue County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e48.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e34.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e41.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e35.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e4.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJinyang County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e11.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e14.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e9.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e24.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYuexi County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e16.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e16.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e13.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e12.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e17.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eXide County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e13.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e10.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e9.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e8.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e10.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeigu County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e15.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e19.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e20.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e16.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.863\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePuge County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e17.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e17.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e9.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e13.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e2.803\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGanluo County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e12.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e9.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e11.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e6.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e3.293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeibo County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e17.879\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMianning County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e9.317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNingnan County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e3.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.344\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYanyuan County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e3.572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eXichang City\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e4.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e3.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.567\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuli Tibetan Autonomous County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e1.145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.285\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDechang County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e3.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e1.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.301\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuidong County\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.878\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuili City\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.579\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e12.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e5.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e5.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e3.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e29.547\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e34.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e31.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e31.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e26.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e31.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e10.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e9.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e10.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e11.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e4.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e2.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e2.757\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e475\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e444\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e15.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e13.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e15.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e378\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e13.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e16.260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e5.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e3.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e3.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e33.145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCharacteristics of HIV transmission and TB treatment profiles\u003c/h2\u003e \u003cp\u003eThe HIV transmission routes, anti-TB treatment outcomes, and drug resistance profiles of newly reported HIV\u0026ndash;TB co-infected patients in Liangshan from 2019 to 2024 are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Heterosexual transmission was the predominant HIV route (48.29%), followed by injection drug use (41.31%) and mother-to-child transmission (3.42%); homosexual transmission accounted for the smallest proportion (0.30%).\u003c/p\u003e \u003cp\u003eRegarding anti-TB treatment outcomes, 81.76% of patients completed treatment or were cured, approximately 1.93% were transferred to multidrug-resistant TB (MDR-TB) treatment, 0.80% experienced adverse treatment outcomes (adverse reactions, treatment failure, or TB-related death), and 10.87% were lost to follow-up or had unknown outcomes. Drug resistance testing revealed that 3.30% of co-infected patients had TB drug resistance. Among resistant cases, the main types were resistance to rifampicin (46.85%) and isoniazid (28.83%), followed by MDR-TB (23.42%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of HIV transmission routes, anti-TB treatment outcomes, and drug resistance among HIV\u0026ndash;TB co-infected patients in Liangshan Prefecture, 2019\u0026ndash;2024 (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3,367)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCases, \u003cem\u003en\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProportion (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIV transmission route\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeterosexual transmission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1626\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInjection drug use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSexual contact\u0026thinsp;+\u0026thinsp;injection drug use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMother-to-child transmission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHomosexual transmission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnti-TB drug resistance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo drug resistance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e96.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRifampicin-resistant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsoniazid-resistant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultidrug-resistant (MDR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-extensively drug-resistant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnti-TB treatment outcome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompleted treatment or cured\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2753\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransferred to MDR-TB treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdverse TB treatment outcome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeath not due to TB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLost to follow-up or unknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eFactors associated with HIV transmission and TB outcomes\u003c/h2\u003e \u003cp\u003eTo further explore the distribution of the above characteristics across different populations, we performed a stratified analysis by sex and age group for HIV transmission routes, drug resistance, and anti-TB treatment outcomes (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). By sex, there were statistically significant differences in HIV transmission routes and anti-TB drug resistance (both \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while the difference in anti-TB treatment outcomes was not significant (\u003cem\u003eχ\u003c/em\u003e\u0026sup2;=5.446, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.245). By age group, there were statistically significant differences in HIV transmission routes and anti-TB treatment outcomes (both P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while the difference in anti-TB drug resistance was not significant (\u003cem\u003eχ\u003c/em\u003e\u0026sup2;=2.824, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.588).\u003c/p\u003e \u003cp\u003eThese differences were primarily manifested in the fact that injection drug use was the predominant HIV route for males, while heterosexual transmission was predominant for females; the proportion of females who completed treatment or were cured was slightly higher than that of males. Regarding age groups, injection drug use was the main HIV route for those aged 30\u0026ndash;45 years (50.32%), whereas heterosexual transmission was the main route for all other age groups, notably reaching 87.62% in those aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years. Importantly, the proportion of patients aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years who completed treatment or were cured was less than 70% (69.52%), significantly lower than that of other age groups (pairwise comparisons with Bonferroni correction, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactors associated with HIV transmission routes, drug resistance, and anti-TB treatment outcomes among HIV\u0026ndash;TB co-infected patients in Liangshan Prefecture, 2019\u0026ndash;2024, by sex and age group (n\u0026thinsp;=\u0026thinsp;3,367)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c12\" namest=\"c6\"\u003e \u003cp\u003eAge group (years)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;15\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15\u0026ndash;30\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e30- \u0026lt;45\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e45 - \u0026lt;60\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;60\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIV transmission route\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e501.741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2446.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeterosexual transmission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e994 (39.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e632 (77.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e501.741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e292 (63.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e914 (44.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e326 (52.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e92 (87.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2446.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInjection drug use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1297 (50.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e94 (11.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e501.741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (0.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e98 (21.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1035 (50.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e245 (39.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e12 (11.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2446.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSexual contact\u0026thinsp;+\u0026thinsp;injection drug use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e132 (5.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (0.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e501.741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0(0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11 (2.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e85 (4.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e41 (6.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0(0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2446.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMother-to-child transmission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58 (2.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57 (6.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e501.741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e90 (71.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e25 (5.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0(0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0(0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0(0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2446.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39 (1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24 (2.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e501.741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25 (19.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e17 (3.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e14 (0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e6 (0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1 (0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2446.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHomosexual transmission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10 (0.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0(0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e501.741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0(0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4 (0.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5 (0.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1 (0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0(0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2446.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17 (0.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8 (0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e501.741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8 (6.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e12 (2.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4 (0.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1 (0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0(0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2446.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnti-TB drug resistance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.588\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo drug resistance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2454 (96.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e802 (97.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e124 (98.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e446 (97.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1990 (96.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e596 (96.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e100 (95.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.588\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRifampicin-resistant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42 (1.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10 (1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (0.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5 (1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e36 (1.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e7 (1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3 (2.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.588\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsoniazid-resistant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27 (1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (0.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (0.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6 (1.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e17 (0.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e7 (1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1 (0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.588\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultidrug-resistant (MDR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23 (0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (0.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2 (0.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e13 (0.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e10 (1.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1 (0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.588\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-extensively drug-resistant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0(0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0(0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0(0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1 (0.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0(0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0(0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.588\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnti-TB treatment outcome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e28.749\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompleted treatment or cured\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2069 (81.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e684 (83.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e105 (83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e384 (83.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1698 (82.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e493 (79.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e73 (69.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e28.749\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransferred to MDR-TB treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54 (2.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (0.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8 (1.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e40 (1.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e13 (2.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3 (2.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e28.749\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdverse TB treatment outcome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18 (0.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1(0.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2(0.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e22 (0.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2(5.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0(0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e28.749\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeath not due to TB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e125 (4.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31 (3.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (3.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e13 (2.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e97 (4.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e31 (5.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e10 (9.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e28.749\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLost to follow-up or unknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e281 (11.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85 (10.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14 (11.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e52 (11.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e200 (9.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e81 (13.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e19 (18.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e28.749\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003eNote: Values in parentheses are column percentages (%).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDrug resistance trends in the context of integrated prevention\u003c/h2\u003e \u003cp\u003eFrom 2019 to 2024, the overall TB drug resistance rate among HIV\u0026ndash;TB co-infected patients in Liangshan was 3.30%. Rifampicin resistance was the most common type (46.85% of resistant cases), followed by isoniazid resistance (28.83%) and MDR-TB (23.42%).\u003c/p\u003e \u003cp\u003eRegarding temporal trends, though it slightly decreased in 2024, the overall drug resistance rate showed a significant upward trend (\u003cem\u003eχ\u003c/em\u003e\u0026sup2;\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e = 8.481, \u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e = 0.004), rising from 1.54% in 2019 to 3.10% in 2024, with the highest reported rate in 2023 (4.88%). Analyzing specific resistance types, this upward trend was primarily driven by a significant increase in rifampicin resistance (\u003cem\u003eχ\u003c/em\u003e\u0026sup2;\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e = 9.890, \u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e = 0.002). Trends for isoniazid resistance, MDR-TB, and pre-extensively drug-resistant TB were not statistically significant (\u003cem\u003eχ\u003c/em\u003e\u0026sup2;\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e = 0.334, 2.323, and 0.946, \u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e = 0.853, 0.127, and 0.331, respectively) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eLiangshan Prefecture in Sichuan Province is an area with a dual high burden of HIV and TB. HIV\u0026ndash;TB co-infection in this region warrants particular attention and may provide important insights for other high-burden, resource-limited settings worldwide.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eOverall trends in the context of integrated prevention\u003c/h2\u003e \u003cp\u003eAgainst the policy backdrop of the IPC4D policy and \u0026ldquo;1\u0026thinsp;+\u0026thinsp;M\u0026thinsp;+\u0026thinsp;N+P\u0026rdquo; precision prevention and control models, the reported incidence of HIV\u0026ndash;TB co-infection in Liangshan showed a significant downward trend from 2019 to 2024 (from 12.26 per 100,000 to 8.76 per 100,000), consistent with reports from other regions in China [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. However, global burden of disease models and local studies suggest that the age-standardized burden of HIV\u0026ndash;TB in low-SDI regions may continue to rise in the coming years [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], indicating that Liangshan's prevention and control achievements need sustained consolidation. Studies have indicated that relying solely on symptom-based screening is insufficient to detect all TB cases, recommending systematic TB screening for people living with HIV during every healthcare encounter to reduce diagnostic delays [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. This evidence offers valuable insights for optimizing screening strategies in Liangshan.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eGeographic and demographic drivers of decline\u003c/h2\u003e \u003cp\u003eThe demographic profile of HIV\u0026ndash;TB co-infected patients in Liangshan from 2019 to 2024 was highly concentrated, predominantly involving young adult males (30\u0026ndash;45 years) and farmers (92.37%), similar to reports from other countries and Chinese provinces [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The decline in incidence in high-burden counties such as Butuo, Zhaojue, Yuexi, and Jinyang was a major driver of the Liangshan's overall decline. This reflects the effectiveness of the Chinese government's strategy of concentrated resource allocation and precision interventions (e.g., expanded screening, community mobilization, multi-sectoral collaboration) in key disease control areas. The significant decline in all age groups under 45 years suggests a good response to prevention and control measures among the younger population. The downward trend in incidence for both sexes indicates that local interventions have achieved good coverage across genders. These findings demonstrate that Liangshan's prevention and control strategies have achieved initial success in key areas and populations, offering valuable lessons for other high-burden regions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003ePersistent challenges: the neglected older adults\u003c/h2\u003e \u003cp\u003eIn stark contrast to the positive trends above, the incidence in the \u0026ge;\u0026thinsp;60-year age group showed no significant decline over the six years, and their treatment success rate (69.52%) was significantly lower than that of other age groups. Older patients may face barriers to active participation in screening and regular follow-up due to declining physical function, multiple comorbidities, poverty, and limited healthcare access [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Concurrently, weak social support networks\u0026mdash;including being empty nesters, widowhood, and adult child out-migration\u0026mdash;leave them without adequate supervision and care during treatment. Local studies have shown that low BMI is a strong predictor of death among HIV/AIDS patients [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], and malnutrition is common among the elderly, further increasing the risk of adverse outcomes. Notably, 87.62% of older patients were infected with HIV via heterosexual transmission, indicating that health education and disease prevention efforts related to sexual activity need to be strengthened for this population. Older adults should become a key focus for the next phase of prevention and control efforts, with an urgent need for targeted active screening, simplified treatment procedures, and nutritional support programs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eTransmission route syndemic and its implications\u003c/h2\u003e \u003cp\u003eThe HIV transmission routes among co-infected patients in this study reveal a deeper \u0026ldquo;syndemic\u0026rdquo; pattern: injection drug use predominates in males (50.92%), while heterosexual transmission predominates in females (77.07%); injection drug use is dominant in the 30\u0026ndash;45-year age group (50.32%), whereas heterosexual transmission is dominant in all other age groups, reaching 87.62% in those aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years. This pattern reflects the complexity of HIV transmission within Liangshan's unique socio-cultural context. This syndemic presents multidimensional requirements for prevention and control. First, young adult male farmers face both drug-related risks and difficulties in regular follow-up due to high mobility, necessitating strengthened pre-migration screening and mobile population management [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Second, women infected through heterosexual transmission require support to enhance their negotiation skills in sexual activities and access to diverse protective measures [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Third, the varying transmission characteristics across age groups call for targeted sexual health education for those aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years, and integrated interventions\u0026mdash;combining drug prevention, sexual health promotion, and family-based approaches\u0026mdash;for the \u0026ldquo;mixed\u0026rdquo; transmission pattern seen in the 30\u0026ndash;45-year age group [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eTreatment outcomes, loss to follow-up, and the threat of drug resistance\u003c/h2\u003e \u003cp\u003eThe treatment success rate in this study was 81.76%, lower than the provincial average for Sichuan during the same period (89.01%) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The proportion of patients lost to follow-up or with unknown outcomes was 10.87%, far exceeding that in the general TB population and consistent with findings from an international multi-center study [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Poor treatment adherence and loss to follow-up in this setting stem from multiple interacting factors. At the patient level, the long treatment duration for TB (especially drug-resistant TB), high medication burden, and frequent adverse drug reactions\u0026mdash;compounded by potential additive toxicities when combined with ART [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]\u0026mdash;create significant barriers to adherence. These are further exacerbated by low health literacy, economic hardship, and lack of family support [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. At the health system level, \"N\"-level personnel such as village doctors and HIV prevention officers, working under the integrated service model, face dramatically increased workloads, understaffing, heavy caseloads, and insufficient funding, leading to less intensive follow-up supervision [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. These factors may compromise timely follow-up and intervention for patients with poor adherence, such as some older adults. Another local study found a paradoxically higher risk of death among patients followed up at county-level hospitals or above [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], suggesting that reliance solely on higher-level medical institutions is insufficient. Strengthening the tripartite \"hospital-community-family\" linkage model locally\u0026mdash;by promoting consistent medication supervision and supportive care at the grassroots level, and developing objective adherence assessment methods\u0026mdash;is needed to address previous shortcomings in long-term follow-up management [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eLoss to follow-up not only potentially signifies treatment failure but also acts as a breeding ground for drug resistance. Studies indicate that Liangshan's high drug-resistant TB rate\u0026mdash;among the highest in China\u0026mdash;is primarily due to patient non-adherence rather than primary resistance to drug-resistant strains [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The upward trend in the overall drug resistance rate observed in this study, particularly for rifampicin, can be seen as a sentinel event signaling inadequate treatment adherence among local co-infected patients. Therefore, it is crucial to strengthen drug resistance surveillance among high-risk groups (males, older adults, those with low education, unmarried/divorced individuals, and farmers), promote rapid molecular testing, explore digital health tools to support supervision [\u003cspan additionalcitationids=\"CR49\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], and consider providing tangible support such as transportation subsidies and nutritional packages. Simultaneously, alleviating the workload of grassroots \"N\"-level personnel is essential to ensure follow-up quality [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Through these comprehensive measures, the emergence of additional drug-resistant TB patients can be curbed.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eDrawing on surveillance data of HIV–TB co-infection in Liangshan Prefecture from 2019 to 2024, this study provides a comprehensive analysis of epidemiological trends and infection characteristics within the context of integrated prevention. Key findings include a declining incidence trend, supporting the interim effectiveness of the \"Four Diseases Co-prevention\" policy. The decline was primarily driven by high-burden counties and younger populations, demonstrating the value of targeted precision interventions. The lack of improvement in incidence and low treatment success rate among older adults highlight a critical weak link in current control efforts, while loss to follow-up and emerging TB drug resistance threaten the progress achieved.\u003c/p\u003e\n\u003cp\u003eBuilding on these findings, we propose four priorities for comprehensive prevention and control in Liangshan and similar high-burden settings:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePlace-based strategies:\u0026nbsp;\u003c/strong\u003eharnessing indigenous social resources. In high-burden counties such as Butuo and Zhaojue, the workload for grassroots follow-up is immense, with village doctors and HIV prevention officers facing staff shortages. Drawing on the Yi “clan” (\u003cem\u003eJiazhi\u003c/em\u003e) system, collaboration with clan leaders could be explored to integrate patient follow-up and medication supervision into traditional social networks, thereby improving intervention sustainability and cultural appropriateness.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePeople-centered approaches:\u003c/strong\u003e implementing precision interventions. For older adults, we recommend establishing active screening mechanisms (e.g., integrated into local chronic disease management clinics), providing simplified treatment regimens, and strengthening nutritional support. For women, empowerment through women's health groups and peer education can enhance sexual health autonomy. For young adult male farmers, integrated screening should be delivered around key periods such as pre-migration and Spring Festival return, with improved follow-up for mobile populations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResource-optimized initiatives:\u0026nbsp;\u003c/strong\u003efilling gaps in drug resistance prevention and control. Given that rifampicin resistance continues to drive the increase in overall drug resistance rates, and that local funding for TB (especially drug-resistant TB) remains substantially lower than for HIV, targeted interventions are urgently needed. We recommend expanding rapid drug resistance testing for all HIV–TB patients, establishing dedicated follow-up pathways for drug-resistant cases, and increasing financial support and performance incentives for key diagnostic procedures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTechnology- and support-integrated efforts:\u0026nbsp;\u003c/strong\u003eimproving adherence management efficiency. Digital health tools (medication reminder apps, wearable devices) can be deployed to support supervision, with family engagement. Concurrently, tangible support such as transport subsidies and nutritional supplements can reduce patient burden, while task rationalization and performance incentives can alleviate burnout among frontline workers.\u003c/p\u003e\n\u003cp\u003eGlobal evidence indicates that HIV–TB co-infection control is closely tied to socioeconomic development. In low-SDI settings, disease control is particularly challenging, and expanding treatment coverage alone is insufficient to rapidly reduce disease burden [20]. The Liangshan experience shows that policy integration and targeted resource investment can achieve meaningful progress, but sustained success requires a systemic approach: strengthening grassroots diagnostic capacity, optimizing health system support, improving education for key populations, and improving service accessibility. Future research should prioritize tracing and characterizing patients lost to follow-up to generate further evidence for optimizing follow-up management and care retention.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eART: Antiretroviral therapy; ATT: Anti-tuberculosis treatment; BMI: Body mass index;CDRS: China Cause of Death Reporting System; CRIMS: National Comprehensive HIV/AIDS Information Management System; HIV: Human Immunodeficiency Virus; IPC4D: Integrated Prevention and Control of Four Diseases; IQR: Interquartile range; MDR-TB: Multidrug-resistant tuberculosis\u003c/p\u003e\n\u003cp\u003eSDI: Socio-demographic Index; TB: Tuberculosis; TBIMS: Tuberculosis Information Management System; WHO: World Health Organization.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was reviewed and approved by the Ethics Committee of the Sichuan Center for Disease Control and Prevention (Approval No. SCCDCIRB-2026-002). The need for individual informed consent was waived due to the retrospective, anonymized nature of the routine surveillance data, in accordance with the committee’s guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the Liangshan Center for Disease Control and Prevention, but restrictions apply to the availability of these data, which were used under license for the current study and so are not publicly available. Data are, however, available from the corresponding authors upon reasonable request and with permission of the Liangshan Center for Disease Control and Prevention.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the Liangshan Prefecture Science and Technology Bureau Program (grant number 23ZDYF0025). The funder had no role in study design, data collection, analysis, interpretation, or writing of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eB.X.F. and W.J. contributed equally to conceptualization, data curation, formal analysis, investigation, methodology, project administration, writing – original draft, and writing – review \u0026amp; editing. Y.G. contributed to conceptualization, data curation, formal analysis, investigation, methodology, and supervision. S.J.H. and F.S.S. were responsible for conceptualization, data curation, software, visualization, and writing – original draft. W.R.B., W.Y.B., and F.X.Y. contributed to conceptualization, data curation, formal analysis, investigation, and project administration. P.R. and L.R.J. served as co-corresponding authors, overseeing conceptualization, formal analysis, funding acquisition, investigation, methodology, project administration, supervision, validation, and writing – review \u0026amp; editing. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are deeply grateful to the healthcare workers at the county, township, and village levels in Liangshan for their tireless efforts in data collection and patient care. We also thank the staff at the Liangshan Center for Disease Control and Prevention for their invaluable support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAffiliations:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e¹ Sichuan Center for Disease Control and Prevention, Chengdu 610041, Sichuan Province, China.\u003c/p\u003e\n\u003cp\u003e² Liangshan Center for Disease Control and Prevention, Liangshan Yi Autonomous Prefecture 615000, Sichuan Province, China.\u003c/p\u003e\n\u003cp\u003e³ School of Public Health, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, Sichuan Province, China.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ ORCID:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLiao Rujun：0000-0001-8528-0846\u003c/p\u003e\n\u003cp\u003ePei Rong：0000-0002-2876-901X\u003c/p\u003e\n\u003cp\u003eWang Ju: 0009-0000-2588-6977\u003c/p\u003e\n\u003cp\u003eBai Xuefei: 0009-0004-5845-3130\u003c/p\u003e\n\u003cp\u003eFan Sisi: 0009-0000-7615-360X\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHu XY, Gao JT. 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Infect Dis Poverty. 2024 Jul 5;13(1):51. \u003c/li\u003e\n\u003cli\u003eSossen B, Kubjane M, Meintjes G. Tuberculosis and HIV coinfection: Progress and challenges towards reducing incidence and mortality. Int J Infect Dis. 2025; Published online. \u003c/li\u003e\n\u003cli\u003eFeng Y, Ge L, Cheng W, et al.Survival time and influencing factors among people living with HIV in Guilin City, Guangxi, China: a retrospective cohort study (1996\u0026ndash;2022). Front Public Health. 2026;13:1575990.\u003c/li\u003e\n\u003cli\u003eChen YY, Liu XH, Wang YL, et al. Initial drug resistance of mycobacterium tuberculosis in HIV patients with tuberculosis in Henan. Chin J AIDS STD.2021;27(1):14-16.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"infectious-diseases-of-poverty","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"idop","sideBox":"Learn more about [Infectious Diseases of Poverty](http://idpjournal.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/idop/default.aspx","title":"Infectious Diseases of Poverty","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"HIV–TB co-infection, integrated prevention and control, epidemiological trend, drug resistance, Liangshan Yi Autonomous Prefecture, resource-limited region, Jiazhi (clan) system","lastPublishedDoi":"10.21203/rs.3.rs-9028669/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9028669/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo analyze epidemiological trends and key factors of HIV\u0026ndash;TB co-infection in Liangshan Yi Autonomous Prefecture (2019\u0026ndash;2024), a resource-limited region in Southwest China, and inform integrated prevention strategies.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA retrospective analysis was conducted on 3,367 HIV\u0026ndash;TB co-infected cases extracted from the National HIV/AIDS and TB surveillance systems. Records were linked via unique identifiers. Descriptive statistics and chi-square tests for trend assessed incidence trends, demographics, transmission routes, treatment outcomes, and drug resistance.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eUnder the Integrated Prevention and Control of Four Diseases policy and precision prevention and control model, HIV\u0026ndash;TB incidence declined from 12.26 to 8.76 per 100,000 (\u003cem\u003eχ\u003c/em\u003e\u0026sup2;\u003csub\u003etrend\u003c/sub\u003e=40.459, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), driven by high-burden counties and populations under 45 years (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Patients were predominantly young males (61.10%) and farmers (92.40%). The main HIV transmission routes were heterosexual contact (48.29%) and injection drug use (41.31%), with marked sex and age disparities: injection drug use predominated in males (50.92%) and those aged 30\u0026ndash;45 years (50.32%), while heterosexual transmission prevailed in females (77.07%) and older adults (\u0026ge;\u0026thinsp;60 years, 87.62%). Treatment success rate was 81.76%, significantly lower in the elderly (69.52%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Any drug resistance (3.30%) increased from 1.54% to 3.10% (\u003cem\u003eχ\u003c/em\u003e\u0026sup2;\u003csub\u003etrend\u003c/sub\u003e =8.481, \u003cem\u003eP\u003c/em\u003e \u003csub\u003etrend\u003c/sub\u003e =0.004), driven by rifampicin resistance (\u003cem\u003eχ\u003c/em\u003e\u0026sup2;\u003csub\u003etrend\u003c/sub\u003e =9.890, \u003cem\u003eP\u003c/em\u003e \u003csub\u003etrend\u003c/sub\u003e =0.002).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIntegrated strategies achieved initial success reducing HIV\u0026ndash;TB incidence, particularly in high-burden areas and younger populations. Persistent challenges\u0026mdash;stagnant incidence and poor outcomes in the elderly, high loss to follow-up (10.87%), rising drug resistance\u0026mdash;require targeted interventions: leveraging the Yi \u0026ldquo;clan\u0026rdquo; (\u003cem\u003eJiazhi\u003c/em\u003e) system, strengthening active screening and nutritional support for older adults, optimizing drug resistance surveillance, and integrating digital health tools.\u003c/p\u003e","manuscriptTitle":"HIV–TB co-infection in Liangshan, a resource-limited region of Southwest China: trends and implications in the context of integrated prevention, 2019–2024","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-13 07:41:19","doi":"10.21203/rs.3.rs-9028669/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-11T03:18:58+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-11T03:14:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-01T14:47:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"264803003612027839540635341520528869626","date":"2026-05-01T10:57:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"292889552177902706262313158557415004748","date":"2026-04-30T02:15:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"318975275704205455244855416428297665008","date":"2026-04-17T10:47:56+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-09T03:21:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-05T23:07:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-05T23:06:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"Infectious Diseases of Poverty","date":"2026-03-04T09:38:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"infectious-diseases-of-poverty","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"idop","sideBox":"Learn more about [Infectious Diseases of Poverty](http://idpjournal.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/idop/default.aspx","title":"Infectious Diseases of Poverty","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"661a6ef2-d373-40f3-84a2-f8eb338fc4e1","owner":[],"postedDate":"March 13th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-11T03:18:58+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-11T03:14:23+00:00","index":69,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-01T14:47:07+00:00","index":68,"fulltext":""},{"type":"reviewerAgreed","content":"264803003612027839540635341520528869626","date":"2026-05-01T10:57:17+00:00","index":67,"fulltext":""},{"type":"reviewerAgreed","content":"292889552177902706262313158557415004748","date":"2026-04-30T02:15:26+00:00","index":66,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-11T03:24:33+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-13 07:41:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9028669","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9028669","identity":"rs-9028669","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}