Five-year tuberculosis trends analysis in eight districts of Mwanza region, Tanzania; (2017- 2021)

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In Tanzania like other developing countries, TB detection is hindered by totally missed, late notification and delayed diagnosis of active cases. Apart from having TB control strategies and interventions to detect patients and put them on treatment to cut down the chain of transmission, we are unaware of the existing burden and trends of tuberculosis for the previous five years in the Mwanza region. This study aimed at determining trends of tuberculosis in Mwanza region Tanzania for a period of five years, from 2017 to 2021. Methods. We extracted routine TB diagnostic data from 2017 to 2021 from eight districts of the Mwanza region of Tanzania from the electronic TB database. Data were captured in Microsoft office Excel 2007 in collaboration with district TB and leprosy coordinators and then imported into STATA 13 (Stata corp LLC, College Station, TX, USA) for analysis. We estimated TB case detection rate per 100,000 population. Results. A total of 6,414 laboratory confirmed tuberculosis cases were detected in eight districts of Mwanza region in Tanzania during the year 2017 to 2021. Average tuberculosis detection rate in five years was 34.7 per 100,000 population. Overall, TB the detection rate was two times higher in people without HIV (30.5) compared to those infected with HIV; 13.4 per 100,000 population. Of the 15 rifampicin resistant TB cases detected, 66.7% (10/15) were uninfected with HIV compared to 33.3% (5/15) that were detected in year 2018. Conclusion The TB case detection rate decreased in Mwanza region from 43.9 in 2017 to 21.4 per 100,000 population in 2021. Other parameters were missing in the data base which highlight remarkable gaps in the established database to monitor TB management in the region. The program require to investigate and improve on barriers hindering fully documentation of cases information’s which are very necessary for the program to attain its goals. Tuberculosis trends detection rate Figures Figure 1 Figure 2 Introduction Tuberculosis continue to infect people and cause death globally, despite the availability of effective drugs to cure the disease[ 1 ]. In the year 2022, TB was estimated to cause about 1.3 million deaths worldwide[ 2 ]. TB incidence rate (new cases per 100,000 population per year) reduced to 2% between 2010 and 2020. However, due to the COVID-19 pandemic, the worldwide incidence rate increased up to 3.6% between 2020 and 2022 pulling back the global effort to end TB by 2030[ 2 ]. In Tanzania, TB incidence rate reduced by 27% from 306 in 2015 to 222 per 100,000 population per year in 2020, although TB cases notification were still at 136 per 100,000 population per year[ 3 ]. Like many other African countries, the most limiting factors for TB notification continues to be totally missed, late notification and delayed diagnosis of TB active cases[ 4 ]. Sputum smear microscopy, the most commonly used method to diagnose the disease leaves about 37% of patients undiagnosed because of its poor sensitivity[ 5 ] Therefore, programs are working with unrealistic burden estimates because cases remain undetected and where detection is done, documentation is inefficient to report all cases accurately[ 6 ]. We are unaware of the existing burden and trends of tuberculosis for the previous five years in the Mwanza region Tanzania. Apart from having TB control strategies and interventions to detect patients and put them on treatment to cut down the chain of transmission, it is necessary to provide updated information regarding the TB detection rate so that the National TB and Leprosy control program (NTLP) can revise available guidelines based of scientific evidence[ 7 ]. Five –Year’s trends analysis of TB in Mwanza region is the first attempt and is critical to understand the burden and detection rates, especially during COVID-19 pandemic so that NTLP can be informed accordingly. Therefore, the present study aims at determining the trends of tuberculosis in Mwanza region Tanzania for a period of five years, from 2017 to 2022. Methods Study setting and period of the study : Mwanza region shares a boundary with five regions and is occupied by mainly fishing and peasant’s populations. It is bordering Simiyu to the east, Geita to the west, Shinyanga to the south and on the Lake Victoria is bordering Kagera and Mara. Mwanza is the second biggest region in Tanzania after Dar es Salaam having a population of 3,699,872 people as per 2022 National census[ 8 ]. The region occupies an area of 25,233 square kilometers where by 9,743 Km 2 is water and 11,796 Km 2 is dry land[ 9 ]. Eight districts of Mwanza region with their population are Buchosa (413,110), Ilemela (509,687), Kwimba (480,025) and Magu (421,119). Other districts include Misungwi (467,867), Nyamagana (594,834), Sengerema (425,415) and Ukerewe (387,815)[ 8 ]. Like other regions in Tanzania, TB notification, treatment, prevention and control is overseen by the district TB and leprosy coordinators (DTLCs). The coordinators supervises health centers and primary health care facilities where TB patients attends like other normal patients. Each district hospital and health center has a designed TB clinic where TB patients are notified, diagnosed and managed using pre-trained health care workers. Each TB clinic is assigned by personnel to serve as a direct observed therapy short course (DOTS) site and carry out community surveillance of the disease, monitor treatments and traces lost follow up patients. Other tasks carried out by a DOTS nurse includes collaborative community engagement and forms linkage between Partners and Government in his or her area of work. DTLCs report to the Regional Medical Officer (RMO) all issues regarding the TB program, then to the National TB and Leprosy control program. The trends analysis study was carried out in December 2022. Study design : This is a retrospective review of TB data collected as routine notification, diagnosis and treatment of TB patients as per Tanzania National TB and leprosy control program (NTLP). Data were extracted from the National TB data base on TB indicators. Data collection and analysis: We extracted TB case data from an electronic database developed to manage routine data collected for five years, from 2017 to 2021, for the Mwanza region. Data were cleaned and transferred into Microsoft office Excel 2007 in collaboration with district TB and leprosy coordinators (DTLCs) under the supervision of the regional TB and leprosy coordinators (RTLCs). Data were then imported into STATA 13 (Stata corp LLC, College Station, TX, USA) for analysis. TB tendencies analysis were reported based on Chi square and results were reported as simple descriptive data using tables and graphs. The detection rate was estimated based on per 100,000 population. Case definitions Tuberculosis positive case (TB+) as used in the current study implies any person who was microbiologically confirmed to have TB by smear microscopy, culture or xpert MTB/RIF assay from at least one specimen[ 10 ]. Ethical considerations The study was approved by the joint Catholic University of Health and Allied Sciences (CUHAS)/Bugando Medical Centre (BMC) Research Ethics and Review Committee (CREC) (Number CREC/398/2019) and the Health Research Ethics Committee of Stellenbosch University, Cape Town, South Africa (reference number: S21/5/081). Permission for access to the TB program database was obtained from the National TB and Leprosy control program manager, through the Ministry of Health. Results A total of 6,414 laboratory confirmed tuberculosis cases were detected in the eight districts of Mwanza region in Tanzania during the year 2017 to 2021. Most cases (n=4186; 65.3%) were females ( Table 1 ). Of all the TB cases that were detected during the study period, 0.7% (47) were below 9 years, 4.4% (284) between the ages of 10 and 19years, 65.5% (4203) were between the ages of 20 and 49 years and 29.3% (1,880) ≥50 years, up to 99 years (Figure 1) . Adults ranging from 20-49 years accounted for 65.5% of all TB cases detected and only 0.7% (47) were children below 9 years. Regarding the method used for diagnosing TB in the cases, majority (63.1%) n= 4,043 were detected using smear microscopy and (39.6%) N=2539 by geneXpert MTB/RIF. Average tuberculosis detection rate in five years (2017 to 2021) were 34.7 per 100,000 population. We observed a 2-fold annual decline in the TB detection rate, from 43.9 cases in 2017, to 21.4 cases per 100,000 population in 2021. More than half (71.7%, n=4596) of the TB cases detected were HIV negative and 0.23% (15/6414) cases were TB rifampicin resistant (RR) (Table 4). In 2018, Magu and Nyamagana districts had high detection rate compared to other districts 58.4 and 84.2 per 100,000 population respectively (Table 2). Of the 15 patients that were diagnosed with rifampicin resistant TB during the study period, 66.7% (10/15) were uninfected with HIV and 33.3% (5/15) of cases were detected in year 2018. Among laboratory reported TB cases, 6365 cases were classified as pulmonary, 32 extra pulmonary and 17 cases were classified as both pulmonary and extra pulmonary tuberculosis. Majority of patients 98.4% (6311) were on 2 month rifampicin, isoniazid, pyrazinamide and ethambutol followed by 4 month rifampicin and isoniazid (2RHZE/4RH), 1.25% (80) were on 2 month streptomycin, rifampicin, isoniazid, pyrazinamide and ethambutol followed by one month rifampicin, isoniazid, pyrazinamide and ethambutol then 5 month rifampicin, isoniazid and ethambutol (2SRHZE/1RHZE/5RHE). Other 0.3% of patients were on 2RHZE/4RH-KID and 0.09% of TB cases were 2HRZE/10RH. Some patients were not on the standard therapy for example patients that were diagnosed with rifampicin resistance extra pulmonary tuberculosis patients. Table 1; TB cases detected in eight districts of Mwanza region Tanzania (2017-2021) Characteristics Total n= 6414 HIV Pos. n=1818 HIV Neg. n=4596 Year 2017 1625(25.3) 495(27.2) 1130(24.6) 2018 1629(25.4) 525(28.9) 1104(24.0) 2019 1248(19.5) 323() 925(20.0) 2020 1121(17.5) 291(16.0) 830(18.1) 2021 791(12.3) 184(10.1) 607(14.6) Districts Buchosa 663(10.3) 230(12.6) 433(9.4) Ilemela 556(8.7) 151(8.3) 405(8.8) Kwimba 432(6.7) 105(5.8) 327(7.1) Magu 998(15.6) 327(18.0) 671(14.5) Misungwi 691(10.8) 158 (8.6) 533(11.5) Nyamagana 1840(28.7) 506(27.8) 1334(29.0) Sengerema 896(14.0) 263(14.5) 633(13.7) Ukerewe 338(5.3) 78(4.3) 260(5.7) Sex Male 2228(34.7) 772(42.5) 1456(31.7) Female 4186(65.3) 1046(57.5) 3140(36.8 RR-TB 15 (0.2) 5(0.02) 10(0.2) Table 2; Tendency of Overall TB case detection (CDR) eight Districts in Mwanza Tanzania (2017-2021) Total case detection rate (CDR) per 100,000 population Years 2017 2018 2019 2020 2021 Overall 43.9 44 33.7 30.3 21.4 Districts Buchosa 19.3 40.9 29.3 30.3 40.7 Ilemela 15.7 23.9 20.4 18.6 12.8 Kwimba 16.7 17.3 18.5 8.7 21.7 Magu 18.9 58.4 45.8 49.7 25.9 Misungwi 17.1 40.2 26.5 34.8 18.6 Nyamagana 13.4 84.2 68.3 55.8 17.1 Sengerema 18.8 56.9 34.1 26.3 22 Ukerewe 20.6 20.1 17 10.8 15.9 Sex Male 32.3 31 24.1 20.5 15.6 Female 54.9 56.4 42.8 39.6 26.8 Table 3; Tendency of overall TB CDR among HIV infection subgroup in eight districts Mwanza Tanzania (2017-2021) CDR among people with HIV per 100,000 population CDR among people without HIV per 100,000 population Year 2017 2018 2019 2020 2021 2017 2018 2019 2020 2021 Overall 13.4 14.2 8.7 7.9 5 30.5 29.8 25 22.4 16.4 Districts Buchosa 5.1 16.9 10.4 10.7 12.6 14.3 24 18.8 19.6 28.1 Ilemela 10.8 7.8 2.9 4.3 3.7 22.6 16.1 17.5 14.3 9 Kwimba 6.2 4.8 5 3.1 2.7 17.5 12.5 13.5 5.6 18.9 Magu 20.9 22.1 13.8 16.1 4.7 36.1 36.3 32.1 33.7 21.1 Misungwi 8.1 8.1 5.1 7.1 5.3 19.4 32.1 21.4 28 13.3 Nyamagana 24 26.7 17.8 13.1 3.4 59.8 57.5 50.4 42.7 13.8 Sengerema 23 18.8 9.6 4.7 5.6 48.2 38.1 24.4 21.6 16.5 Ukerewe 5.7 5.7 3.1 2.8 2.8 17.5 14.4 13.9 8 13.2 Sex Female 12.6 12.2 7.8 6.2 4.2 19.6 18.9 16.4 14.3 11.5 Male 14.1 16.1 9.6 9.5 5.7 40.8 40.3 33.2 30.1 21.1 Table 4; TB case detection among HIV positive and negative patient in Mwanza region from 2017-2021 Case detection among HIV + Case detection among HIV - 2017 2018 2019 2020 2021 2017 2018 2019 2020 2021 Overall 495 525 323 291 184 1130 1104 925 830 607 Districts Buchosa 21 70 43 44 52 59 99 78 81 116 Ilemela 55 40 15 22 19 115 82 89 73 46 Kwimba 30 23 24 15 13 84 60 65 27 91 Magu 88 93 58 68 20 152 153 135 142 89 Misungwi 38 38 24 33 25 91 150 100 130 62 Nyamagana 143 159 106 78 20 356 342 300 254 82 Sengerema 98 80 41 20 24 205 162 104 92 70 Ukerewe 22 22 12 11 11 68 56 54 31 51 Sex Female 227 219 140 111 75 356 340 295 258 207 Male 268 306 183 180 109 774 764 630 572 400 RR-TB 1 2 0 2 0 1 7 1 0 1 Discussion In the current study we analyzed routine data collected from tuberculosis patient’s management from 2017 to 2021. During the analysis we found an average TB case detection rate of 34.7 cases per 100,000 populations in a period of five years (2017–2021). This finding is very necessary We have conducted the similar study similar to what was studied in rural Uganda involving eight districts which reported the average of 149 cases per 100,000 population in five years (2015–2019), However, the two findings can’t be compared because of different study period[ 11 ]. There was significant decline in annual tuberculosis detection rate (Fig. 2 ) in Mwanza region from 1625 cases in 2017 to 791 cases in 2021, this declined is explained by COVID-19 pandemic which happened worldwide during the period of study. Tanzania did not go for complete lockdown during COVID-19 pandemic. However, several services supporting TB cases diagnosis were interrupted and this hindered TB detection supplies from reaching the testing facilities, for example continuous supply of GeneXpert for TB detection[ 12 ]. Adults ranging from 20-60years accounted for 78.6% of all cases, this observation is quite similar to what was observed in a five years tuberculosis trends analysis conducted in Awi Zone, Northwest Ethiopia which found almost the same age group accounting 87.3% of all TB cases[ 13 ]. Smear microscope diagnostic method detected 63.0% of all TB cases meaning that in absence of geneXpert MTB/RIF 27% percent additional cases could have remained undiagnosed, the major limitation to reach target of stopping TB by 2030. It has been documented that geneXpert MTB/RIF increases TB detection rate up to 47% compared to smear microscopy [ 14 ]. TB detections rate were high 65.3% in men compared to women’s in Mwanza region. This finding complements to what has been strongly reported by a systematic review highlighting that TB is high in men because men does not benefit from accessing TB care in most cases. The report recommends specific TB program strategies that would improve men access to tuberculosis care [ 15 – 17 ]. TB detection rate was high in people without HIV 71.7% (4596) and 0.23% (15/6414) cases were tuberculosis rifampicin resistance (RR) ( Table 3 ). We argue that this is due to strengthened HIV prevention and control response and enhanced TB/HIV collaborative activities. Countries and regions with high burdens of HIV and TB should strengthen and sustain efforts in order to achieve the goal of ending both HIV and TB epidemics in line with the Sustainable "Development Goals.[ 18 ]. Our finding on MDR-TB of 0.23% in Mwanza region were below the pooled prevalence of MDR-TB reported by a systematic review that synthesized evidence on the prevalence of MDR-TB in East Africa. The results of this meta-analysis survey reported the pooled prevalence of newly diagnosed MDR-TB to 4% (95% CI 2–5%)[ 19 ]. Ethiopia reported rifampicin-resistance of 8.73%, almost doubling that of Uganda. Study Limitation The data analyzed were from the TB date base and were retrospectively collected. We encountered missing critical information that could have added more value to our publication. Variables including treatment success rates and their associated factors were missing. Conclusion The TB case detection rate decreased in Mwanza region from 2017 to 2021. Other parameters were missing in the data base which highlight remarkable gaps in established database to monitor tuberculosis managements in the region. The program require to investigate and make continuous improvement barriers hindering fully documentation of cases information’s which are very necessary for the program to attain its goals. Declarations Funding declaration This study was funded by DAHW Deutsche Lepra-und Tuberkulosehilfe e.V, Wurzburg, Germany grant number 7.18.20.19. Data availability Data of this study is available and can be shared once requested. Competing interests The authors has no competing interest Author Contribution MB Conceptualization, methodology, formal analysis, visualization, Writing-review and editing, manuscript writing. NNC Conceptualization, methodology, formal analysis, visualization, writing-review &editing and supervision. GW conceptualization, methodology, writing-review &editing and supervision. SM conceptualization, methodology, formal analysis, writing and reviewing & editing and supervision. KC conceptualization, methodology, writing-reviewing & editing supervision and resources Acknowledgement Mwanza Regional Chief medical Officer and and Districts TB coordinators, References Ding C et al. Epidemic trends in high tuberculosis burden countries during the last three decades and feasibility of achieving the global targets at the country level. 2022. 9: p. 798465. Bagcchi S. WHO's global tuberculosis report 2022. 2023. 4(1): p. e20. Chakaya J et al. The WHO Global Tuberculosis 2021 Report–not so good news and turning the tide back to End TB. 2022. 124: pp. S26-S29. Shah HD, et al. Gaps and interventions across the diagnostic care cascade of TB patients at the level of patient. community health system: qualitative Rev literature. 2022;7(7):136. Ngabonziza JCS, et al. Diagn Perform smear microscopy Increm yield Xpert Detect pulmonary tuberculosis Rwanda. 2016;16:1–7. Mukasa E et al. Challenges and strategies for standardizing information systems for integrated TB/HIV services in Tanzania: a case study of Kinondoni municipality. 2017. 79(1): p. 1–11. Stosic M et al. Trends in tuberculosis notification and mortality and factors associated with treatment outcomes in Serbia, 2005 to 2015. 2020. 25(1): p. 1900322. Statistics TNBo. Population and Housing Census Administrative units Population Distribution and Age and Sex Distribution Report . 2022. Region M. Mwanza region size . Graham SM et al. Clinical case definitions for classification of intrathoracic tuberculosis in children: an update. 2015. 61(suppl_3): pp. S179-S187. Baluku JB et al. Trends of notification rates and treatment outcomes of tuberculosis cases with and without HIV co-infection in eight rural districts of Uganda (2015–2019). 2022. 22(1): p. 651. Hogan AB et al. Potential impact of the COVID-19 pandemic on HIV, tuberculosis, and malaria in low-income and middle-income countries: a modelling study. 2020. 8(9): p. e1132–41. Alemu T, H.J.B.R N, Gutema. Trend in magnitude of tuberculosis in Awi Zone, Northwest Ethiopia: a five-year tuberculosis surveillance data analysis. 2019. 12: pp. 1–5. Durovni B et al. Impact of replacing smear microscopy with Xpert MTB/RIF for diagnosing tuberculosis in Brazil: a stepped-wedge cluster-randomized trial. 2014. 11(12): p. e1001766. Horton KC et al. Sex differences in tuberculosis burden and notifications in low-and middle-income countries: a systematic review and meta-analysis. 2016. 13(9): p. e1002119. Neyrolles O, Quintana-Murci LJPm. Sex Inequal tuberculosis. 2009;6(12):e1000199. McQuaid CF et al. The risk of multidrug-or rifampicin-resistance in males versus females with tuberculosis. 2020. 56(3). Gelaw YA et al. HIV prevalence among tuberculosis patients in sub-Saharan Africa: a systematic review and meta-analysis. 2019. 23: pp. 1561–1575. Molla KA, Reta MA, Ayene YYJPo. Prevalence of multidrug-resistant tuberculosis in East Africa: a systematic review and meta-analysis. 2022. 17(6): p. e0270272. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 19 Nov, 2024 Read the published version in BMC Public Health → Version 1 posted Editorial decision: Revision requested 16 Apr, 2024 Editor assigned by journal 11 Apr, 2024 Submission checks completed at journal 11 Apr, 2024 First submitted to journal 06 Apr, 2024 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4226350","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":290261488,"identity":"5439c5a6-5d6c-42be-91ad-e33a4ad4ba42","order_by":0,"name":"Medard Beyanga","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYHACMyC2SQAzEwqI15KWwMAG0mJAvJbDEC0MxGjRbW/e9uBj2/k8fvnuxA8PDBjk+cUOELDizLFyw5ltt4sl23g3SwAdZjhzdgIBLTdyzKR5224nbjjGuwGkJcHgNiEt99+YSf9tOwfSsvkHcVpu8JhJM7YdAGnZRqQtZ9LKDXvOJSfObMvdZpFgIEGEX44f3vbgR5ldYj/z2c03f1TYyPNLE9ACBoxscKYEEcrB4A+xCkfBKBgFo2BEAgDuF0ZrOz19vQAAAABJRU5ErkJggg==","orcid":"","institution":"National Public Health Laboratory Ministry of Health Mabibo Dar es salaam","correspondingAuthor":true,"prefix":"","firstName":"Medard","middleName":"","lastName":"Beyanga","suffix":""},{"id":290261489,"identity":"d99192fb-5b6e-4eee-9c30-962e9479eb1a","order_by":1,"name":"Novel N Chegou","email":"","orcid":"","institution":"Stellenbosch University","correspondingAuthor":false,"prefix":"","firstName":"Novel","middleName":"N","lastName":"Chegou","suffix":""},{"id":290261490,"identity":"549f81b6-7c70-4939-8fab-0cf81b2bfe2d","order_by":2,"name":"Gerhard Walzl","email":"","orcid":"","institution":"Stellenbosch University","correspondingAuthor":false,"prefix":"","firstName":"Gerhard","middleName":"","lastName":"Walzl","suffix":""},{"id":290261491,"identity":"672b74ce-2e45-464a-bc34-c2b2a7fda8a8","order_by":3,"name":"Stephen Mshana","email":"","orcid":"","institution":"Catholic University of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Stephen","middleName":"","lastName":"Mshana","suffix":""},{"id":290261492,"identity":"5a029d80-5b8b-47a2-a08a-a5e69e2ba549","order_by":4,"name":"Kasang Christa","email":"","orcid":"","institution":"Catholic University of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Kasang","middleName":"","lastName":"Christa","suffix":""}],"badges":[],"createdAt":"2024-04-06 07:59:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4226350/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4226350/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12889-024-20684-6","type":"published","date":"2024-11-19T15:57:48+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":55001412,"identity":"e9813b8e-a11d-401b-bf91-141c9395a330","added_by":"auto","created_at":"2024-04-19 18:37:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":19032,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of TB cases in different age groups in eight districts of the Mwanza region, Tanzania from 2017 to 2021.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4226350/v1/eb6acf99615a91a45de5778f.png"},{"id":55001413,"identity":"d299099d-7351-4edb-aab1-ca2175dde8f4","added_by":"auto","created_at":"2024-04-19 18:37:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":25132,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrends of TB case detection among HIV positive individuals in eight districts of the Mwanza region, Tanzania, from 2017 to 2021. \u003c/strong\u003eThe figure indicate the number of TB cases (blue line) and HIV cases (red line) detected each year during the period of study\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4226350/v1/83b10788b96fb4d2e5041a08.png"},{"id":69834927,"identity":"6f406b0d-0041-416a-99da-88af0b637c2d","added_by":"auto","created_at":"2024-11-25 16:10:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":641929,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4226350/v1/1e5f2bbe-662c-44ea-9584-ce81e12aec3e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Five-year tuberculosis trends analysis in eight districts of Mwanza region, Tanzania; (2017- 2021)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTuberculosis continue to infect people and cause death globally, despite the availability of effective drugs to cure the disease[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In the year 2022, TB was estimated to cause about 1.3\u0026nbsp;million deaths worldwide[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. TB incidence rate (new cases per 100,000 population per year) reduced to 2% between 2010 and 2020. However, due to the COVID-19 pandemic, the worldwide incidence rate increased up to 3.6% between 2020 and 2022 pulling back the global effort to end TB by 2030[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In Tanzania, TB incidence rate reduced by 27% from 306 in 2015 to 222 per 100,000 population per year in 2020, although TB cases notification were still at 136 per 100,000 population per year[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Like many other African countries, the most limiting factors for TB notification continues to be totally missed, late notification and delayed diagnosis of TB active cases[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Sputum smear microscopy, the most commonly used method to diagnose the disease leaves about 37% of patients undiagnosed because of its poor sensitivity[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] Therefore, programs are working with unrealistic burden estimates because cases remain undetected and where detection is done, documentation is inefficient to report all cases accurately[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. We are unaware of the existing burden and trends of tuberculosis for the previous five years in the Mwanza region Tanzania. Apart from having TB control strategies and interventions to detect patients and put them on treatment to cut down the chain of transmission, it is necessary to provide updated information regarding the TB detection rate so that the National TB and Leprosy control program (NTLP) can revise available guidelines based of scientific evidence[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Five \u0026ndash;Year\u0026rsquo;s trends analysis of TB in Mwanza region is the first attempt and is critical to understand the burden and detection rates, especially during COVID-19 pandemic so that NTLP can be informed accordingly. Therefore, the present study aims at determining the trends of tuberculosis in Mwanza region Tanzania for a period of five years, from 2017 to 2022.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003eStudy setting and period of the study\u003c/b\u003e:\u003c/h2\u003e \u003cp\u003eMwanza region shares a boundary with five regions and is occupied by mainly fishing and peasant\u0026rsquo;s populations. It is bordering Simiyu to the east, Geita to the west, Shinyanga to the south and on the Lake Victoria is bordering Kagera and Mara. Mwanza is the second biggest region in Tanzania after Dar es Salaam having a population of 3,699,872 people as per 2022 National census[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The region occupies an area of 25,233 square kilometers where by 9,743 Km\u003csup\u003e2\u003c/sup\u003e is water and 11,796 Km\u003csup\u003e2\u003c/sup\u003e is dry land[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Eight districts of Mwanza region with their population are Buchosa (413,110), Ilemela (509,687), Kwimba (480,025) and Magu (421,119). Other districts include Misungwi (467,867), Nyamagana (594,834), Sengerema (425,415) and Ukerewe (387,815)[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Like other regions in Tanzania, TB notification, treatment, prevention and control is overseen by the district TB and leprosy coordinators (DTLCs). The coordinators supervises health centers and primary health care facilities where TB patients attends like other normal patients. Each district hospital and health center has a designed TB clinic where TB patients are notified, diagnosed and managed using pre-trained health care workers. Each TB clinic is assigned by personnel to serve as a direct observed therapy short course (DOTS) site and carry out community surveillance of the disease, monitor treatments and traces lost follow up patients. Other tasks carried out by a DOTS nurse includes collaborative community engagement and forms linkage between Partners and Government in his or her area of work. DTLCs report to the Regional Medical Officer (RMO) all issues regarding the TB program, then to the National TB and Leprosy control program. The trends analysis study was carried out in December 2022.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003eStudy design\u003c/b\u003e:\u003c/h2\u003e \u003cp\u003eThis is a retrospective review of TB data collected as routine notification, diagnosis and treatment of TB patients as per Tanzania National TB and leprosy control program (NTLP). Data were extracted from the National TB data base on TB indicators.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData collection and analysis:\u003c/h2\u003e \u003cp\u003eWe extracted TB case data from an electronic database developed to manage routine data collected for five years, from 2017 to 2021, for the Mwanza region. Data were cleaned and transferred into Microsoft office Excel 2007 in collaboration with district TB and leprosy coordinators (DTLCs) under the supervision of the regional TB and leprosy coordinators (RTLCs). Data were then imported into STATA 13 (Stata corp LLC, College Station, TX, USA) for analysis. TB tendencies analysis were reported based on Chi square and results were reported as simple descriptive data using tables and graphs. The detection rate was estimated based on per 100,000 population.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eCase definitions\u003c/h2\u003e \u003cp\u003eTuberculosis positive case (TB+) as used in the current study implies any person who was microbiologically confirmed to have TB by smear microscopy, culture or xpert MTB/RIF assay from at least one specimen[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eEthical considerations\u003c/h2\u003e \u003cp\u003eThe study was approved by the joint Catholic University of Health and Allied Sciences (CUHAS)/Bugando Medical Centre (BMC) Research Ethics and Review Committee (CREC) (Number CREC/398/2019) and the Health Research Ethics Committee of Stellenbosch University, Cape Town, South Africa (reference number: S21/5/081). Permission for access to the TB program database was obtained from the National TB and Leprosy control program manager, through the Ministry of Health.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 6,414 laboratory confirmed tuberculosis cases were detected in the eight districts of Mwanza region in Tanzania during the year 2017 to 2021. Most cases (n=4186; 65.3%) were females (\u003cstrong\u003eTable 1\u003c/strong\u003e). Of all the TB cases that were detected during the study period, 0.7% (47) were below 9 years, 4.4% (284) between the ages of 10 and 19years, 65.5% (4203) were between the ages of 20 and 49 years and 29.3% (1,880) \u0026ge;50 years, up to 99 years \u003cstrong\u003e(Figure 1)\u003c/strong\u003e. Adults ranging from 20-49 years accounted for 65.5% of all TB cases detected and only 0.7% (47) were children below 9 years.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRegarding the method used for diagnosing TB in the cases, majority (63.1%) n= 4,043 were detected using smear microscopy and (39.6%) N=2539 by geneXpert MTB/RIF. Average tuberculosis detection rate in five years (2017 to 2021) were 34.7 per 100,000 population. We observed a 2-fold annual decline in the TB detection rate, from 43.9 cases in 2017, to 21.4 cases per 100,000 population in 2021. More than half (71.7%, n=4596) of the TB cases detected were HIV negative and 0.23% (15/6414) cases were TB rifampicin resistant (RR) \u003cstrong\u003e(Table 4).\u003c/strong\u003e In 2018, Magu and Nyamagana districts had high detection rate compared to other districts 58.4 and 84.2 per 100,000 population respectively \u003cstrong\u003e(Table 2).\u003c/strong\u003e Of the 15 patients that were diagnosed with rifampicin resistant TB during the study period, 66.7% (10/15) were uninfected with HIV and 33.3% (5/15) of cases were detected in year 2018. Among laboratory reported TB cases, 6365 cases were classified as pulmonary, 32 extra pulmonary and 17 cases were classified as both pulmonary and extra pulmonary tuberculosis. Majority of patients 98.4% (6311) were on 2 month rifampicin, isoniazid, pyrazinamide and ethambutol followed by 4 month rifampicin and isoniazid (2RHZE/4RH), 1.25% (80) were on 2 month streptomycin, rifampicin, isoniazid, pyrazinamide and ethambutol followed by one month rifampicin, isoniazid, pyrazinamide and ethambutol then 5 month rifampicin, isoniazid and ethambutol (2SRHZE/1RHZE/5RHE). Other 0.3% of patients were on 2RHZE/4RH-KID and 0.09% of TB cases were 2HRZE/10RH. Some patients were not on the standard therapy for example patients that were diagnosed with rifampicin resistance extra pulmonary tuberculosis patients.\u003c/p\u003e\n\u003cp\u003eTable 1; TB cases detected in eight districts of Mwanza region Tanzania (2017-2021)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.53191489361702%\" valign=\"top\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.340425531914892%\" valign=\"top\"\u003e\n \u003cp\u003eTotal n= 6414\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.404255319148938%\" valign=\"top\"\u003e\n \u003cp\u003eHIV Pos. n=1818\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.72340425531915%\" valign=\"top\"\u003e\n \u003cp\u003eHIV Neg. n=4596\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.53191489361702%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYear\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.340425531914892%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"23.404255319148938%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.72340425531915%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.53191489361702%\" valign=\"top\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.340425531914892%\" valign=\"top\"\u003e\n \u003cp\u003e1625(25.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.404255319148938%\" valign=\"top\"\u003e\n \u003cp\u003e495(27.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.72340425531915%\" valign=\"top\"\u003e\n \u003cp\u003e1130(24.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.53191489361702%\" valign=\"top\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.340425531914892%\" valign=\"top\"\u003e\n \u003cp\u003e1629(25.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.404255319148938%\" valign=\"top\"\u003e\n \u003cp\u003e525(28.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.72340425531915%\" valign=\"top\"\u003e\n \u003cp\u003e1104(24.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.53191489361702%\" valign=\"top\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.340425531914892%\" valign=\"top\"\u003e\n \u003cp\u003e1248(19.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.404255319148938%\" valign=\"top\"\u003e\n \u003cp\u003e323()\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.72340425531915%\" valign=\"top\"\u003e\n \u003cp\u003e925(20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.53191489361702%\" valign=\"top\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.340425531914892%\" valign=\"top\"\u003e\n \u003cp\u003e1121(17.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.404255319148938%\" valign=\"top\"\u003e\n \u003cp\u003e291(16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.72340425531915%\" valign=\"top\"\u003e\n \u003cp\u003e830(18.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.53191489361702%\" valign=\"top\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.340425531914892%\" valign=\"top\"\u003e\n \u003cp\u003e791(12.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.404255319148938%\" valign=\"top\"\u003e\n \u003cp\u003e184(10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.72340425531915%\" valign=\"top\"\u003e\n \u003cp\u003e607(14.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.53191489361702%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistricts\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.340425531914892%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"23.404255319148938%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.72340425531915%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.53191489361702%\" valign=\"top\"\u003e\n \u003cp\u003eBuchosa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.340425531914892%\" valign=\"top\"\u003e\n \u003cp\u003e663(10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.404255319148938%\" valign=\"top\"\u003e\n \u003cp\u003e230(12.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.72340425531915%\" valign=\"top\"\u003e\n \u003cp\u003e433(9.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.53191489361702%\" valign=\"top\"\u003e\n \u003cp\u003eIlemela\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.340425531914892%\" valign=\"top\"\u003e\n \u003cp\u003e556(8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.404255319148938%\" valign=\"top\"\u003e\n \u003cp\u003e151(8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.72340425531915%\" valign=\"top\"\u003e\n \u003cp\u003e405(8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.53191489361702%\" valign=\"top\"\u003e\n \u003cp\u003eKwimba\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.340425531914892%\" valign=\"top\"\u003e\n \u003cp\u003e432(6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.404255319148938%\" valign=\"top\"\u003e\n \u003cp\u003e105(5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.72340425531915%\" valign=\"top\"\u003e\n \u003cp\u003e327(7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.53191489361702%\" valign=\"top\"\u003e\n \u003cp\u003eMagu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.340425531914892%\" valign=\"top\"\u003e\n \u003cp\u003e998(15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.404255319148938%\" valign=\"top\"\u003e\n \u003cp\u003e327(18.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.72340425531915%\" valign=\"top\"\u003e\n \u003cp\u003e671(14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.53191489361702%\" valign=\"top\"\u003e\n \u003cp\u003eMisungwi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.340425531914892%\" valign=\"top\"\u003e\n \u003cp\u003e691(10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.404255319148938%\" valign=\"top\"\u003e\n \u003cp\u003e158 (8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.72340425531915%\" valign=\"top\"\u003e\n \u003cp\u003e533(11.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.53191489361702%\" valign=\"top\"\u003e\n \u003cp\u003eNyamagana\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.340425531914892%\" valign=\"top\"\u003e\n \u003cp\u003e1840(28.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.404255319148938%\" valign=\"top\"\u003e\n \u003cp\u003e506(27.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.72340425531915%\" valign=\"top\"\u003e\n \u003cp\u003e1334(29.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.53191489361702%\" valign=\"top\"\u003e\n \u003cp\u003eSengerema\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.340425531914892%\" valign=\"top\"\u003e\n \u003cp\u003e896(14.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.404255319148938%\" valign=\"top\"\u003e\n \u003cp\u003e263(14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.72340425531915%\" valign=\"top\"\u003e\n \u003cp\u003e633(13.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.53191489361702%\" valign=\"top\"\u003e\n \u003cp\u003eUkerewe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.340425531914892%\" valign=\"top\"\u003e\n \u003cp\u003e338(5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.404255319148938%\" valign=\"top\"\u003e\n \u003cp\u003e78(4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.72340425531915%\" valign=\"top\"\u003e\n \u003cp\u003e260(5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.53191489361702%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.340425531914892%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"23.404255319148938%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.72340425531915%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.53191489361702%\" valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.340425531914892%\" valign=\"top\"\u003e\n \u003cp\u003e2228(34.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.404255319148938%\" valign=\"top\"\u003e\n \u003cp\u003e772(42.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.72340425531915%\" valign=\"top\"\u003e\n \u003cp\u003e1456(31.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.53191489361702%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.340425531914892%\" valign=\"top\"\u003e\n \u003cp\u003e4186(65.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.404255319148938%\" valign=\"top\"\u003e\n \u003cp\u003e1046(57.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.72340425531915%\" valign=\"top\"\u003e\n \u003cp\u003e3140(36.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.53191489361702%\" valign=\"top\"\u003e\n \u003cp\u003eRR-TB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.340425531914892%\" valign=\"top\"\u003e\n \u003cp\u003e15 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.404255319148938%\" valign=\"top\"\u003e\n \u003cp\u003e5(0.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.72340425531915%\" valign=\"top\"\u003e\n \u003cp\u003e10(0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2; Tendency of Overall TB case detection (CDR) eight Districts in Mwanza Tanzania (2017-2021)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.761245674740483%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"79.23875432525952%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eTotal case detection rate (CDR) per 100,000 population\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.761245674740483%\" valign=\"top\"\u003e\n \u003cp\u003eYears\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.570934256055363%\" valign=\"top\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.53287197231834%\" valign=\"top\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.84083044982699%\" valign=\"top\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.761245674740483%\" valign=\"top\"\u003e\n \u003cp\u003eOverall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e43.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.570934256055363%\" valign=\"top\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.53287197231834%\" valign=\"top\"\u003e\n \u003cp\u003e33.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e30.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.84083044982699%\" valign=\"top\"\u003e\n \u003cp\u003e21.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.761245674740483%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistricts\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.570934256055363%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.53287197231834%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.84083044982699%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.761245674740483%\" valign=\"top\"\u003e\n \u003cp\u003eBuchosa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e19.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.570934256055363%\" valign=\"top\"\u003e\n \u003cp\u003e40.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.53287197231834%\" valign=\"top\"\u003e\n \u003cp\u003e29.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e30.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.84083044982699%\" valign=\"top\"\u003e\n \u003cp\u003e40.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.761245674740483%\" valign=\"top\"\u003e\n \u003cp\u003eIlemela\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e15.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.570934256055363%\" valign=\"top\"\u003e\n \u003cp\u003e23.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.53287197231834%\" valign=\"top\"\u003e\n \u003cp\u003e20.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e18.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.84083044982699%\" valign=\"top\"\u003e\n \u003cp\u003e12.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.761245674740483%\" valign=\"top\"\u003e\n \u003cp\u003eKwimba\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e16.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.570934256055363%\" valign=\"top\"\u003e\n \u003cp\u003e17.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.53287197231834%\" valign=\"top\"\u003e\n \u003cp\u003e18.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e8.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.84083044982699%\" valign=\"top\"\u003e\n \u003cp\u003e21.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.761245674740483%\" valign=\"top\"\u003e\n \u003cp\u003eMagu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e18.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.570934256055363%\" valign=\"top\"\u003e\n \u003cp\u003e58.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.53287197231834%\" valign=\"top\"\u003e\n \u003cp\u003e45.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e49.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.84083044982699%\" valign=\"top\"\u003e\n \u003cp\u003e25.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.761245674740483%\" valign=\"top\"\u003e\n \u003cp\u003eMisungwi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e17.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.570934256055363%\" valign=\"top\"\u003e\n \u003cp\u003e40.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.53287197231834%\" valign=\"top\"\u003e\n \u003cp\u003e26.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e34.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.84083044982699%\" valign=\"top\"\u003e\n \u003cp\u003e18.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.761245674740483%\" valign=\"top\"\u003e\n \u003cp\u003eNyamagana\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e13.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.570934256055363%\" valign=\"top\"\u003e\n \u003cp\u003e84.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.53287197231834%\" valign=\"top\"\u003e\n \u003cp\u003e68.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e55.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.84083044982699%\" valign=\"top\"\u003e\n \u003cp\u003e17.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.761245674740483%\" valign=\"top\"\u003e\n \u003cp\u003eSengerema\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e18.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.570934256055363%\" valign=\"top\"\u003e\n \u003cp\u003e56.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.53287197231834%\" valign=\"top\"\u003e\n \u003cp\u003e34.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e26.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.84083044982699%\" valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.761245674740483%\" valign=\"top\"\u003e\n \u003cp\u003eUkerewe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e20.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.570934256055363%\" valign=\"top\"\u003e\n \u003cp\u003e20.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.53287197231834%\" valign=\"top\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e10.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.84083044982699%\" valign=\"top\"\u003e\n \u003cp\u003e15.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.761245674740483%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.570934256055363%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.53287197231834%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.84083044982699%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.761245674740483%\" valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e32.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.570934256055363%\" valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.53287197231834%\" valign=\"top\"\u003e\n \u003cp\u003e24.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e20.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.84083044982699%\" valign=\"top\"\u003e\n \u003cp\u003e15.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.761245674740483%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e54.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.570934256055363%\" valign=\"top\"\u003e\n \u003cp\u003e56.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.53287197231834%\" valign=\"top\"\u003e\n \u003cp\u003e42.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\" valign=\"top\"\u003e\n \u003cp\u003e39.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.84083044982699%\" valign=\"top\"\u003e\n \u003cp\u003e26.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3; Tendency of overall TB CDR among HIV infection subgroup in eight districts Mwanza Tanzania (2017-2021)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.92776886035313%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"42.21508828250401%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eCDR among people with HIV \u0026nbsp;per 100,000 population\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.857142857142854%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eCDR among people without HIV \u0026nbsp;per 100,000 population\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.92776886035313%\" valign=\"top\"\u003e\n \u003cp\u003eYear\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.149277688603531%\" valign=\"top\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.346709470304976%\" valign=\"top\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.704654895666132%\" valign=\"top\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.98876404494382%\" valign=\"top\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.062600321027287%\" valign=\"top\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.507223113964686%\" valign=\"top\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.92776886035313%\" valign=\"top\"\u003e\n \u003cp\u003eOverall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e13.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.149277688603531%\" valign=\"top\"\u003e\n \u003cp\u003e14.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.346709470304976%\" valign=\"top\"\u003e\n \u003cp\u003e8.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.704654895666132%\" valign=\"top\"\u003e\n \u003cp\u003e7.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.98876404494382%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.062600321027287%\" valign=\"top\"\u003e\n \u003cp\u003e30.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e29.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.507223113964686%\" valign=\"top\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e22.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e16.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.92776886035313%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistricts\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.149277688603531%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.346709470304976%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.704654895666132%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.98876404494382%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.062600321027287%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.507223113964686%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.92776886035313%\" valign=\"top\"\u003e\n \u003cp\u003eBuchosa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.149277688603531%\" valign=\"top\"\u003e\n \u003cp\u003e16.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.346709470304976%\" valign=\"top\"\u003e\n \u003cp\u003e10.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.704654895666132%\" valign=\"top\"\u003e\n \u003cp\u003e10.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.98876404494382%\" valign=\"top\"\u003e\n \u003cp\u003e12.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.062600321027287%\" valign=\"top\"\u003e\n \u003cp\u003e14.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.507223113964686%\" valign=\"top\"\u003e\n \u003cp\u003e18.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e19.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e28.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.92776886035313%\" valign=\"top\"\u003e\n \u003cp\u003eIlemela\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e10.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.149277688603531%\" valign=\"top\"\u003e\n \u003cp\u003e7.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.346709470304976%\" valign=\"top\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.704654895666132%\" valign=\"top\"\u003e\n \u003cp\u003e4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.98876404494382%\" valign=\"top\"\u003e\n \u003cp\u003e3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.062600321027287%\" valign=\"top\"\u003e\n \u003cp\u003e22.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e16.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.507223113964686%\" valign=\"top\"\u003e\n \u003cp\u003e17.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e14.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.92776886035313%\" valign=\"top\"\u003e\n \u003cp\u003eKwimba\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e6.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.149277688603531%\" valign=\"top\"\u003e\n \u003cp\u003e4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.346709470304976%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.704654895666132%\" valign=\"top\"\u003e\n \u003cp\u003e3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.98876404494382%\" valign=\"top\"\u003e\n \u003cp\u003e2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.062600321027287%\" valign=\"top\"\u003e\n \u003cp\u003e17.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.507223113964686%\" valign=\"top\"\u003e\n \u003cp\u003e13.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e18.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.92776886035313%\" valign=\"top\"\u003e\n \u003cp\u003eMagu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e20.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.149277688603531%\" valign=\"top\"\u003e\n \u003cp\u003e22.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.346709470304976%\" valign=\"top\"\u003e\n \u003cp\u003e13.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.704654895666132%\" valign=\"top\"\u003e\n \u003cp\u003e16.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.98876404494382%\" valign=\"top\"\u003e\n \u003cp\u003e4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.062600321027287%\" valign=\"top\"\u003e\n \u003cp\u003e36.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e36.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.507223113964686%\" valign=\"top\"\u003e\n \u003cp\u003e32.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e33.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e21.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.92776886035313%\" valign=\"top\"\u003e\n \u003cp\u003eMisungwi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e8.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.149277688603531%\" valign=\"top\"\u003e\n \u003cp\u003e8.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.346709470304976%\" valign=\"top\"\u003e\n \u003cp\u003e5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.704654895666132%\" valign=\"top\"\u003e\n \u003cp\u003e7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.98876404494382%\" valign=\"top\"\u003e\n \u003cp\u003e5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.062600321027287%\" valign=\"top\"\u003e\n \u003cp\u003e19.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e32.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.507223113964686%\" valign=\"top\"\u003e\n \u003cp\u003e21.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e13.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.92776886035313%\" valign=\"top\"\u003e\n \u003cp\u003eNyamagana\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.149277688603531%\" valign=\"top\"\u003e\n \u003cp\u003e26.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.346709470304976%\" valign=\"top\"\u003e\n \u003cp\u003e17.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.704654895666132%\" valign=\"top\"\u003e\n \u003cp\u003e13.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.98876404494382%\" valign=\"top\"\u003e\n \u003cp\u003e3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.062600321027287%\" valign=\"top\"\u003e\n \u003cp\u003e59.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e57.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.507223113964686%\" valign=\"top\"\u003e\n \u003cp\u003e50.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e42.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e13.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.92776886035313%\" valign=\"top\"\u003e\n \u003cp\u003eSengerema\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.149277688603531%\" valign=\"top\"\u003e\n \u003cp\u003e18.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.346709470304976%\" valign=\"top\"\u003e\n \u003cp\u003e9.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.704654895666132%\" valign=\"top\"\u003e\n \u003cp\u003e4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.98876404494382%\" valign=\"top\"\u003e\n \u003cp\u003e5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.062600321027287%\" valign=\"top\"\u003e\n \u003cp\u003e48.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e38.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.507223113964686%\" valign=\"top\"\u003e\n \u003cp\u003e24.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e21.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e16.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.92776886035313%\" valign=\"top\"\u003e\n \u003cp\u003eUkerewe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.149277688603531%\" valign=\"top\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.346709470304976%\" valign=\"top\"\u003e\n \u003cp\u003e3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.704654895666132%\" valign=\"top\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.98876404494382%\" valign=\"top\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.062600321027287%\" valign=\"top\"\u003e\n \u003cp\u003e17.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e14.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.507223113964686%\" valign=\"top\"\u003e\n \u003cp\u003e13.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e13.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.92776886035313%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.149277688603531%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.346709470304976%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.704654895666132%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.98876404494382%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.062600321027287%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.507223113964686%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.92776886035313%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e12.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.149277688603531%\" valign=\"top\"\u003e\n \u003cp\u003e12.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.346709470304976%\" valign=\"top\"\u003e\n \u003cp\u003e7.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.704654895666132%\" valign=\"top\"\u003e\n \u003cp\u003e6.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.98876404494382%\" valign=\"top\"\u003e\n \u003cp\u003e4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.062600321027287%\" valign=\"top\"\u003e\n \u003cp\u003e19.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e18.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.507223113964686%\" valign=\"top\"\u003e\n \u003cp\u003e16.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e14.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e11.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.92776886035313%\" valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e14.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.149277688603531%\" valign=\"top\"\u003e\n \u003cp\u003e16.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.346709470304976%\" valign=\"top\"\u003e\n \u003cp\u003e9.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.704654895666132%\" valign=\"top\"\u003e\n \u003cp\u003e9.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.98876404494382%\" valign=\"top\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.062600321027287%\" valign=\"top\"\u003e\n \u003cp\u003e40.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.025682182985554%\" valign=\"top\"\u003e\n \u003cp\u003e40.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.507223113964686%\" valign=\"top\"\u003e\n \u003cp\u003e33.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e30.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.630818619582664%\" valign=\"top\"\u003e\n \u003cp\u003e21.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4; TB case detection among HIV positive and negative patient in Mwanza region from 2017-2021\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.032679738562091%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"43.13725490196079%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eCase detection among HIV +\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.830065359477125%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eCase detection among HIV -\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.032679738562091%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.313725490196079%\" valign=\"top\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.49673202614379%\" valign=\"top\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.986928104575163%\" valign=\"top\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.026143790849673%\" valign=\"top\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.823529411764707%\" valign=\"top\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.803921568627452%\" valign=\"top\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.006535947712418%\" valign=\"top\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.032679738562091%\" valign=\"top\"\u003e\n \u003cp\u003eOverall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e495\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.313725490196079%\" valign=\"top\"\u003e\n \u003cp\u003e525\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.49673202614379%\" valign=\"top\"\u003e\n \u003cp\u003e323\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.986928104575163%\" valign=\"top\"\u003e\n \u003cp\u003e291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.026143790849673%\" valign=\"top\"\u003e\n \u003cp\u003e1130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e1104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.823529411764707%\" valign=\"top\"\u003e\n \u003cp\u003e925\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.803921568627452%\" valign=\"top\"\u003e\n \u003cp\u003e830\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.006535947712418%\" valign=\"top\"\u003e\n \u003cp\u003e607\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.032679738562091%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistricts\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.313725490196079%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.49673202614379%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.986928104575163%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.026143790849673%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.823529411764707%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.803921568627452%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.006535947712418%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.032679738562091%\" valign=\"top\"\u003e\n \u003cp\u003eBuchosa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.313725490196079%\" valign=\"top\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.49673202614379%\" valign=\"top\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.986928104575163%\" valign=\"top\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.026143790849673%\" valign=\"top\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.823529411764707%\" valign=\"top\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.803921568627452%\" valign=\"top\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.006535947712418%\" valign=\"top\"\u003e\n \u003cp\u003e116\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.032679738562091%\" valign=\"top\"\u003e\n \u003cp\u003eIlemela\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.313725490196079%\" valign=\"top\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.49673202614379%\" valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.986928104575163%\" valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.026143790849673%\" valign=\"top\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.823529411764707%\" valign=\"top\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.803921568627452%\" valign=\"top\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.006535947712418%\" valign=\"top\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.032679738562091%\" valign=\"top\"\u003e\n \u003cp\u003eKwimba\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.313725490196079%\" valign=\"top\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.49673202614379%\" valign=\"top\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.986928104575163%\" valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.026143790849673%\" valign=\"top\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.823529411764707%\" valign=\"top\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.803921568627452%\" valign=\"top\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.006535947712418%\" valign=\"top\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.032679738562091%\" valign=\"top\"\u003e\n \u003cp\u003eMagu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.313725490196079%\" valign=\"top\"\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.49673202614379%\" valign=\"top\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.986928104575163%\" valign=\"top\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.026143790849673%\" valign=\"top\"\u003e\n \u003cp\u003e152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.823529411764707%\" valign=\"top\"\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.803921568627452%\" valign=\"top\"\u003e\n \u003cp\u003e142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.006535947712418%\" valign=\"top\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.032679738562091%\" valign=\"top\"\u003e\n \u003cp\u003eMisungwi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.313725490196079%\" valign=\"top\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.49673202614379%\" valign=\"top\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.986928104575163%\" valign=\"top\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.026143790849673%\" valign=\"top\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.823529411764707%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.803921568627452%\" valign=\"top\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.006535947712418%\" valign=\"top\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.032679738562091%\" valign=\"top\"\u003e\n \u003cp\u003eNyamagana\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.313725490196079%\" valign=\"top\"\u003e\n \u003cp\u003e159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.49673202614379%\" valign=\"top\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.986928104575163%\" valign=\"top\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.026143790849673%\" valign=\"top\"\u003e\n \u003cp\u003e356\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e342\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.823529411764707%\" valign=\"top\"\u003e\n \u003cp\u003e300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.803921568627452%\" valign=\"top\"\u003e\n \u003cp\u003e254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.006535947712418%\" valign=\"top\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.032679738562091%\" valign=\"top\"\u003e\n \u003cp\u003eSengerema\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.313725490196079%\" valign=\"top\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.49673202614379%\" valign=\"top\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.986928104575163%\" valign=\"top\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.026143790849673%\" valign=\"top\"\u003e\n \u003cp\u003e205\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.823529411764707%\" valign=\"top\"\u003e\n \u003cp\u003e104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.803921568627452%\" valign=\"top\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.006535947712418%\" valign=\"top\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.032679738562091%\" valign=\"top\"\u003e\n \u003cp\u003eUkerewe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.313725490196079%\" valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.49673202614379%\" valign=\"top\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.986928104575163%\" valign=\"top\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.026143790849673%\" valign=\"top\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.823529411764707%\" valign=\"top\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.803921568627452%\" valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.006535947712418%\" valign=\"top\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.032679738562091%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.313725490196079%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.49673202614379%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.986928104575163%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.026143790849673%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.823529411764707%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.803921568627452%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.006535947712418%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.032679738562091%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.313725490196079%\" valign=\"top\"\u003e\n \u003cp\u003e219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.49673202614379%\" valign=\"top\"\u003e\n \u003cp\u003e140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.986928104575163%\" valign=\"top\"\u003e\n \u003cp\u003e111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.026143790849673%\" valign=\"top\"\u003e\n \u003cp\u003e356\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.823529411764707%\" valign=\"top\"\u003e\n \u003cp\u003e295\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.803921568627452%\" valign=\"top\"\u003e\n \u003cp\u003e258\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.006535947712418%\" valign=\"top\"\u003e\n \u003cp\u003e207\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.032679738562091%\" valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e268\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.313725490196079%\" valign=\"top\"\u003e\n \u003cp\u003e306\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.49673202614379%\" valign=\"top\"\u003e\n \u003cp\u003e183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.986928104575163%\" valign=\"top\"\u003e\n \u003cp\u003e180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.026143790849673%\" valign=\"top\"\u003e\n \u003cp\u003e774\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e764\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.823529411764707%\" valign=\"top\"\u003e\n \u003cp\u003e630\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.803921568627452%\" valign=\"top\"\u003e\n \u003cp\u003e572\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.006535947712418%\" valign=\"top\"\u003e\n \u003cp\u003e400\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.032679738562091%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.313725490196079%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.49673202614379%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.986928104575163%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.026143790849673%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.823529411764707%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.803921568627452%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.006535947712418%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.032679738562091%\" valign=\"top\"\u003e\n \u003cp\u003eRR-TB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.313725490196079%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.49673202614379%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.986928104575163%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.026143790849673%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169934640522875%\" valign=\"top\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.823529411764707%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.803921568627452%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.006535947712418%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the current study we analyzed routine data collected from tuberculosis patient\u0026rsquo;s management from 2017 to 2021. During the analysis we found an average TB case detection rate of 34.7 cases per 100,000 populations in a period of five years (2017\u0026ndash;2021).\u003c/p\u003e \u003cp\u003eThis finding is very necessary We have conducted the similar study similar to what was studied in rural Uganda involving eight districts which reported the average of 149 cases per 100,000 population in five years (2015\u0026ndash;2019), However, the two findings can\u0026rsquo;t be compared because of different study period[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. There was significant decline in annual tuberculosis detection rate (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) in Mwanza region from 1625 cases in 2017 to 791 cases in 2021, this declined is explained by COVID-19 pandemic which happened worldwide during the period of study. Tanzania did not go for complete lockdown during COVID-19 pandemic. However, several services supporting TB cases diagnosis were interrupted and this hindered TB detection supplies from reaching the testing facilities, for example continuous supply of GeneXpert for TB detection[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Adults ranging from 20-60years accounted for 78.6% of all cases, this observation is quite similar to what was observed in a five years tuberculosis trends analysis conducted in Awi Zone, Northwest Ethiopia which found almost the same age group accounting 87.3% of all TB cases[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Smear microscope diagnostic method detected 63.0% of all TB cases meaning that in absence of geneXpert MTB/RIF 27% percent additional cases could have remained undiagnosed, the major limitation to reach target of stopping TB by 2030. It has been documented that geneXpert MTB/RIF increases TB detection rate up to 47% compared to smear microscopy [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. TB detections rate were high 65.3% in men compared to women\u0026rsquo;s in Mwanza region. This finding complements to what has been strongly reported by a systematic review highlighting that TB is high in men because men does not benefit from accessing TB care in most cases. The report recommends specific TB program strategies that would improve men access to tuberculosis care [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. TB detection rate was high in people without HIV 71.7% (4596) and 0.23% (15/6414) cases were tuberculosis rifampicin resistance (RR) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e We argue that this is due to strengthened HIV prevention and control response and enhanced TB/HIV collaborative activities. Countries and regions with high burdens of HIV and TB should strengthen and sustain efforts in order to achieve the goal of ending both HIV and TB epidemics in line with the Sustainable \"Development Goals.[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur finding on MDR-TB of 0.23% in Mwanza region were below the pooled prevalence of MDR-TB reported by a systematic review that synthesized evidence on the prevalence of MDR-TB in East Africa. The results of this meta-analysis survey reported the pooled prevalence of newly diagnosed MDR-TB to 4% (95% CI 2\u0026ndash;5%)[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Ethiopia reported rifampicin-resistance of 8.73%, almost doubling that of Uganda.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStudy Limitation\u003c/h2\u003e \u003cp\u003eThe data analyzed were from the TB date base and were retrospectively collected. We encountered missing critical information that could have added more value to our publication. Variables including treatment success rates and their associated factors were missing.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe TB case detection rate decreased in Mwanza region from 2017 to 2021. Other parameters were missing in the data base which highlight remarkable gaps in established database to monitor tuberculosis managements in the region. The program require to investigate and make continuous improvement barriers hindering fully documentation of cases information\u0026rsquo;s which are very necessary for the program to attain its goals.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by DAHW Deutsche Lepra-und Tuberkulosehilfe e.V, Wurzburg, Germany grant number 7.18.20.19.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData of this study is available and can be shared once requested.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors has no competing interest\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMB Conceptualization, methodology, formal analysis, visualization, Writing-review and editing, manuscript writing. NNC Conceptualization, methodology, formal analysis, visualization, writing-review \u0026amp;editing and supervision. GW conceptualization, methodology, writing-review \u0026amp;editing and supervision. SM conceptualization, methodology, formal analysis, writing and reviewing \u0026amp; editing and supervision. KC conceptualization, methodology, writing-reviewing \u0026amp; editing supervision and resources\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eMwanza Regional Chief medical Officer and and Districts TB coordinators,\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDing C et al. \u003cem\u003eEpidemic trends in high tuberculosis burden countries during the last three decades and feasibility of achieving the global targets at the country level.\u003c/em\u003e 2022. 9: p. 798465.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBagcchi S. \u003cem\u003eWHO's global tuberculosis report 2022.\u003c/em\u003e 2023. 4(1): p. e20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChakaya J et al. \u003cem\u003eThe WHO Global Tuberculosis 2021 Report\u0026ndash;not so good news and turning the tide back to End TB.\u003c/em\u003e 2022. 124: pp. S26-S29.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShah HD, et al. Gaps and interventions across the diagnostic care cascade of TB patients at the level of patient. community health system: qualitative Rev literature. 2022;7(7):136.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNgabonziza JCS, et al. Diagn Perform smear microscopy Increm yield Xpert Detect pulmonary tuberculosis Rwanda. 2016;16:1\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMukasa E et al. Challenges and strategies for standardizing information systems for integrated TB/HIV services in Tanzania: a case study of Kinondoni municipality. 2017. 79(1): p. 1\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStosic M et al. \u003cem\u003eTrends in tuberculosis notification and mortality and factors associated with treatment outcomes in Serbia, 2005 to 2015.\u003c/em\u003e 2020. 25(1): p. 1900322.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStatistics TNBo. \u003cem\u003ePopulation and Housing Census Administrative units Population Distribution and Age and Sex Distribution Report\u003c/em\u003e. 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRegion M. \u003cem\u003eMwanza region size\u003c/em\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGraham SM et al. \u003cem\u003eClinical case definitions for classification of intrathoracic tuberculosis in children: an update.\u003c/em\u003e 2015. 61(suppl_3): pp. S179-S187.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaluku JB et al. Trends of notification rates and treatment outcomes of tuberculosis cases with and without HIV co-infection in eight rural districts of Uganda (2015\u0026ndash;2019). 2022. 22(1): p. 651.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHogan AB et al. Potential impact of the COVID-19 pandemic on HIV, tuberculosis, and malaria in low-income and middle-income countries: a modelling study. 2020. 8(9): p. e1132\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlemu T, H.J.B.R N, Gutema. \u003cem\u003eTrend in magnitude of tuberculosis in Awi Zone, Northwest Ethiopia: a five-year tuberculosis surveillance data analysis.\u003c/em\u003e 2019. 12: pp. 1\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDurovni B et al. Impact of replacing smear microscopy with Xpert MTB/RIF for diagnosing tuberculosis in Brazil: a stepped-wedge cluster-randomized trial. 2014. 11(12): p. e1001766.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHorton KC et al. \u003cem\u003eSex differences in tuberculosis burden and notifications in low-and middle-income countries: a systematic review and meta-analysis.\u003c/em\u003e 2016. 13(9): p. e1002119.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNeyrolles O, Quintana-Murci LJPm. Sex Inequal tuberculosis. 2009;6(12):e1000199.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcQuaid CF et al. The risk of multidrug-or rifampicin-resistance in males versus females with tuberculosis. 2020. 56(3).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGelaw YA et al. \u003cem\u003eHIV prevalence among tuberculosis patients in sub-Saharan Africa: a systematic review and meta-analysis.\u003c/em\u003e 2019. 23: pp. 1561\u0026ndash;1575.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMolla KA, Reta MA, Ayene YYJPo. Prevalence of multidrug-resistant tuberculosis in East Africa: a systematic review and meta-analysis. 2022. 17(6): p. e0270272.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Tuberculosis, trends, detection, rate","lastPublishedDoi":"10.21203/rs.3.rs-4226350/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4226350/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground.\u003c/h2\u003e \u003cp\u003eIn Tanzania like other developing countries, TB detection is hindered by totally missed, late notification and delayed diagnosis of active cases. Apart from having TB control strategies and interventions to detect patients and put them on treatment to cut down the chain of transmission, we are unaware of the existing burden and trends of tuberculosis for the previous five years in the Mwanza region. This study aimed at determining trends of tuberculosis in Mwanza region Tanzania for a period of five years, from 2017 to 2021.\u003c/p\u003e\u003ch2\u003eMethods.\u003c/h2\u003e \u003cp\u003eWe extracted routine TB diagnostic data from 2017 to 2021 from eight districts of the Mwanza region of Tanzania from the electronic TB database. Data were captured in Microsoft office Excel 2007 in collaboration with district TB and leprosy coordinators and then imported into STATA 13 (Stata corp LLC, College Station, TX, USA) for analysis. We estimated TB case detection rate per 100,000 population.\u003c/p\u003e\u003ch2\u003eResults.\u003c/h2\u003e \u003cp\u003eA total of 6,414 laboratory confirmed tuberculosis cases were detected in eight districts of Mwanza region in Tanzania during the year 2017 to 2021. Average tuberculosis detection rate in five years was 34.7 per 100,000 population. Overall, TB the detection rate was two times higher in people without HIV (30.5) compared to those infected with HIV; 13.4 per 100,000 population. Of the 15 rifampicin resistant TB cases detected, 66.7% (10/15) were uninfected with HIV compared to 33.3% (5/15) that were detected in year 2018.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe TB case detection rate decreased in Mwanza region from 43.9 in 2017 to 21.4 per 100,000 population in 2021. Other parameters were missing in the data base which highlight remarkable gaps in the established database to monitor TB management in the region. The program require to investigate and improve on barriers hindering fully documentation of cases information\u0026rsquo;s which are very necessary for the program to attain its goals.\u003c/p\u003e","manuscriptTitle":"Five-year tuberculosis trends analysis in eight districts of Mwanza region, Tanzania; (2017- 2021)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-19 18:37:48","doi":"10.21203/rs.3.rs-4226350/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-04-16T08:20:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-11T20:43:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-11T20:43:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2024-04-06T07:55:47+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"32369b46-516f-49e0-bbf7-1ced90548862","owner":[],"postedDate":"April 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-11-25T16:02:54+00:00","versionOfRecord":{"articleIdentity":"rs-4226350","link":"https://doi.org/10.1186/s12889-024-20684-6","journal":{"identity":"bmc-public-health","isVorOnly":false,"title":"BMC Public Health"},"publishedOn":"2024-11-19 15:57:48","publishedOnDateReadable":"November 19th, 2024"},"versionCreatedAt":"2024-04-19 18:37:48","video":"","vorDoi":"10.1186/s12889-024-20684-6","vorDoiUrl":"https://doi.org/10.1186/s12889-024-20684-6","workflowStages":[]},"version":"v1","identity":"rs-4226350","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4226350","identity":"rs-4226350","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}