Delay in Diagnosis of Pulmonary Tuberculosis is Associated with Increased Risk of Transmission in Pastoralist Setting, Ethiopia

Delay in Diagnosis of Pulmonary Tuberculosis is Associated with Increased Risk of Transmission in Pastoralist Setting, Ethiopia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research article Delay in Diagnosis of Pulmonary Tuberculosis is Associated with Increased Risk of Transmission in Pastoralist Setting, Ethiopia Fentabil Getnet, Meaza Demissie, Alemayehu Worku, Tesfaye Gobena, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.2.10456/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background To comprehend the effect of delayed care on risk of tuberculosis (TB) transmission in a TB prevalent but low case detection area, this study examined the association of diagnosis delay with patient infectiousness (cavitation and smear positivity) and determined the threshold delay that optimizes infectiousness. It also assessed transmission drivers in Somali region of Ethiopia, an area with ample pastoralist population. Methods A cross-sectional study was conducted using 434 new pulmonary TB patients, aged ≥15 years, who were recruited prospectively in five major facilities between December 2017 and October 2018. Data were collected on delays in diagnosis, socio-demographics, clinical and epidemiological information using interview, record-review, anthropometry, sputum microscopy and chest radiography techniques. Log-binomial regression models were used to reveal predictors of cavitation and smear positivity at p<0.05 using Stata/SE®14. C-statistics was applied to determine predictive ability and threshold delay that classifies infectiousness. Results Median age of participants was 30 years. Majorities were male (62.9%), nearly half (46.5%) were pastoralist and 2.3% TB/HIV co-infected. Median delay from debut of illness to diagnosis was 49 days (IQR=37). Among all cases, 45.6% [95%CI: 40.9-50.4] had pulmonary cavity and 42.0% [95%CI: 37.3˗46.9] were smear positive. On multivariable analysis, cavitation was higher in patients delayed over a month [P49 days [p=0.02], ≤35 years [APR (95%CI) =1.4(1.1-1.8)], low BMI [APR (95%CI) =1.3(1.01-1.7)] and low MUAC [APR (95%CI) =1.5(1.2-1.9)]. Delay discriminates cavitation [AUC (95%CI) =0.67(0.62-0.72)] at 43 days optimal cutoff and 74.6% sensitivity. Conclusion This study highlights that delay in diagnosis of pulmonary TB remains high and is associated with increased risk of cavitation and smear positivity in pastoral setting in Ethiopia. In pastoral settings, this may call upon a socio-cultural tailored TB prevention and control strategies. Pulmonology delay tuberculosis cavity smear positivity pastoralist Ethiopia Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Background Tuberculosis (TB), caused by Mycobacterium Tuberculosis (MTB) , remains the leading killer of infectious diseases. Globally, it caused an estimated 10 million cases, 1.3 million deaths, and 300,000 deaths among HIV-positive people in 2017. In the same year, Ethiopia ranked 11 th among the 22 high burden, 4 th in Africa and one of 14 countries with triple burden of TB, MDR-TB and TB/HIV with an estimated 172, 000 new cases [ 1 ]. The prevalence was found to be higher in pastoral communities (316/100,000) than the national level (277/100,000) [ 2 ]. To curb the global epidemics of this deadliest disease, the End-TB strategy sets early diagnosis and treatment of cases as pillars to ending TB epidemics by 2030 [ 3 ]. For the most part, the national TB control program (NTP) of Ethiopia detects TB cases when people with presumptive symptoms present themselves to health facilities (passive case finding strategy) [ 4 ]. However, this passive approach struggles to achieve the required case detection rates in resource-limited settings, allowing millions of potentially infectious cases undiagnosed in communities [ 5 , 6 ]. Nearly one-third of TB cases in Ethiopia were not notified in 2017 [ 1 ]. Local-specific reports indicated the number of undetected infectious cases in community equals the number of notified cases [ 7 ], and another study reported up to two-thirds of active cases remained undetected by the passive system [ 6 ]. In Somali Regional State of Ethiopia (SRS), new case detection rate has not exceeded 50% in recent years [ 8 ]. This implies a high number of infectious cases exist in households and communities without obtaining proper diagnosis and treatments, which is likely influenced by patients’ healthcare seeking behavior and health system deficiencies [ 9 , 10 ]. Extreme delay in diagnosis and treatment of TB has been challenging in Ethiopia, and median delay exceeding two months was reported in pastoral settings [ 11 ]. Failures to timely detect cases and initiate treatment worsen the disease, increase risk of death, increase risk of treatment failure and drug resistance, and exacerbate ongoing transmission in households and congregate settings. Devastating damages occur in lung tissues as patients delay longer without proper treatment, the classical hallmark is cavity formation [ 12 , 13 ]. Cavities are sites of excessive TB bacilli accumulation and release higher bacilli load in aerosols [ 14 ]. Moreover, cavities slow smear conversion following treatment (prolongs contagious period), and are associated with high treatment failure and relapse, emergence of drug resistance, disease dissemination and permanent lung impairments [ 15 ]. Findings have indicated a call for extended treatment of Cavitary TB with a combination of new drugs and new treatment strategies [ 16 ], yet no special strategy is currently in place in Ethiopia. In addition to influencing infectiousness, delay prolongs contagious period and extends contact time between index case and close contacts [ 17 ]. This highlights the need for assessing the effect of delays on risk of TB transmission to assess the effectiveness of TB control programs in controlling the disease and interrupting its transmission. However, the effect of delays on risk of transmission, to the best of our knowledge, was not addressed in pastoral settings in Ethiopia. There is also limited data on cavitary TB and the acceptable delays from clinical and programmatic perspectives. Hence, this study was intended to assess the association of delay in diagnosis with infectiousness of patients and determine threshold delays that optimize cavitation and smear positivity as proxy measures of infectiousness. We have also assessed household drivers of transmission in Somali regional state of Ethiopia where majorities of the population lead pastoral life and households inhabit in cramped transitory huts [ 18 ]. Methods Study Setting Four hospitals (Kharamara, Dege-habour, Kebri-Daher and Gode) and one health center (Abilelie) in Somali Regional State of Ethiopia were selected purposefully based on their patient flow, presence of radiologic facility, and geographic location in the administration. Kharamara hospital and Abilelie health center are located in the regional capital, Jigjiga. The rest facilities are found in less-urbanized, pastoral-dominant and semi-arid zones of the region. Approximately 85% of the region’s population lead a nomadic or agro-pastoral way of life [ 18 ]. The nomads rear livestock, migrate seasonally while agro-pastoralists are relatively permanent, and carry out mixed herding and farming [ 11 ]. The hospitals and selected health centers provide TB services as per the National guideline, which involves two spot-spot smear microscopy examination spaced by 30 minutes (morning on demand), chest radiography, molecular (GeneXpert), pathology and clinical investigations [ 4 ]. Figure 1: Map of the study area Study Design and Population A facility-based cross-sectional study was conducted to determine the effect of delay in diagnosis and/or treatment on the infectiousness (pulmonary cavitation and sputum smear positivity) of patients diagnosed with pulmonary TB (PTB). All newly arriving clinically confirmed patients aged ≥15 years were included between December 1, 2017 and October 31, 2018 regardless of smear status and treatment category. Patients aged ≥15 years manifest similar pathological features and the same diagnosis approaches are used [ 4 ]. People in this age category are believed to acquire competent immunity that is key in cavity formation [ 19 ], cover 80% of all TB cases and account for almost 100% of disease transmissions [ 20 ]. Patients with lung co-morbidities (bronchitis, pneumonia and lung cyst) were excluded. Sample Size and Sampling Technique The minimum sample size estimated using OpenEpi303 for cross-sectional studies was 282. This assumed 95% CI, 80% power, 1:1 ratio of non-delayed/delayed, 27.5% of non-delayed and 45% of delayed patients had cavitation in related study [ 12 ], 5% precision and 10% non-response rate, and given delay above 30 days as critical point at which risk of transmission increases [ 21 ]. We included all the available samples in the analysis to increase the power of the test, which raised the final sample size to 434. Patients were recruited sequentially from the first date of data collection. As the patients arrived to the Directly Observed Therapy-Short Course (DOTS) facilities for treatment initiation, all upcoming eligible PTB patients were recruited for the study before initiating treatment. Data Collection: Questionnaire, Microscopy and Chest X-ray A mix of methods including interview, anthropometry, Acid-Fast Bacilli (AFB) microscopy and chest radiography were used in addition to the standard medical examination (record review). A structured and pre-tested questionnaire was employed to obtain data on delays in diagnosis, socio-demographics, self-reported medical conditions, and environmental drivers of transmission. Records were reviewed to substantiate co-morbidities. Mid-Upper Arm Circumference (MUAC) was measured using inelastic paper tapes, and Body Mass Index (BMI) was computed from weight (kilograms) and height (meter-square) measures. Nurses working in DOTS clinics carried out recruitment, interview, record review and anthropometry procedures. Training was provided on sampling and data collection procedures by the principal investigator and a local research assistant. AFB Examination Upon completion of interviews, the DOTS providers linked patients to radiology and laboratory units using request forms prepared for this purpose. Three sputum specimens from each patient were collected; morning sputum at home, and two spot specimens spaced by 30 minutes after the patient delivered the morning specimen. A pair of smears was prepared from each specimen, air dried and heat fixed. One slide of each pair was examined at hospital laboratories using Ziehl Neelsen (ZN) staining technique. The rest three smears were transported and examined blindly at Armaur Hansen Research Institute (AHRI) TB laboratory in Addis Ababa, Ethiopia. The results were interpreted as negative (no AFB), scanty (1-9 AFB/100 field), 1+ (10-99 AFB/100 field), 2+ (1-10 AFB/field), 3+(>10 AFB/field) [ 4 ]. Figure 2: Procedure of AFB examination Chest Radiography All patients underwent Chest X-ray examinations to identify lung cavitation, measure cavity size and count the number of cavities. A senior radiologist at Kharamara hospital examined all the X-ray films and digital imaging. The radiologist was blinded to radiologic and AFB results reported during the standard initial diagnosis. Sample of X-ray films (n=41) were randomly picked and blindly re-checked by another radiologist to ensure the reliability of X-ray readings. As of rechecking, we found levels of 95.1% [84.6-100%] kappa agreement for cavity identification, 0.84 [0.64, 0.93] Cohen’s kappa coefficient for cavity size, and 85.7% [63.7-96.9%] Cohen’s proportion of zero difference for cavity count. Data Processing and Analysis Data were double entered and validated using EpiData version 3.1; and analyzed using Stata/SE ® 14 ( StataCorp, College Station, Texas 77845 USA ). Descriptive statistics was performed to summarize delays in diagnosis, patient infectiousness, explanatory and environmental factors of transmission. Prevalence ratios along with 95% confidence intervals (CI) were used to compare cavitation and smear positivity between categories of predictors, and multivariable analyses were fitted using Log-binomial regression models. Statistical significances were determined at p-value ≤0.05; and p-value ≤ 0.2 in bivariate analysis was used as a cutoff point for inclusion in final models. C-statistics or Receiver Operating Characteristic (ROC) was employed to determine the discriminatory ability and threshold/optimal cutoff points of diagnosis delay that classify patient infectiousness at maximum sum of sensitivity and specificity, and positive likelihood ratio (LR+), given sensitivity (>70%). Operational/standard definition of terms Pulmonary Tuberculosis: is a patient with lung TB of either smear-positive or negative forms. A smear AFB positive patient is confirmed if at least one AFB positive smears; A smear negative patient is diagnosed if: at least two AFB smear negative results, no response to a course of broad-spectrum antibiotics, again two AFB negative smears and radiological abnormalities consistent with TB; Or two AFB smear negative results but culture positive for MTB [ 4 ]. New Case: is a patient who has never had treatment for TB before or has not yet initiated anti-TB treatment. Retreatment case: is a patient who was treated for any form of TB before but has developed the disease again following relapse or default or failure to cure during the 1 st regimen. Newly Diagnosed Patient: a patient who was prospectively diagnosed with Pulmonary TB during the study period. This excludes patients who were on treatment. Diagnosis delay: is defined as the period from debut of the first symptom(s) particularly cough or other (chest pain, haemoptysis, weight loss, night sweating) to the date of TB diagnosis. Infectiousness: is the capability of a PTB patient to transmit TB infection into a susceptible person, characterized by the existence of pulmonary cavity and/or AFB positive smear. Pulmonary cavity: is an air-containing lucent space within a consolidation or a mass or nodule surrounded by infiltrate or fibrotic wall identified upon radiological examination [ 19 , 22 ]. Figure 3: Photo of a patient with cavity on the right chest (arrow), [ captured by the radiologist ] Results Socio-demographic and Clinical Characteristics All the 434 pulmonary TB patients recruited in the study had complete chest radiography, and 421 of them had complete AFB results. The participants had a median age of 30 years, ranging from 15 to 82 years. The majority was male (62.9%; M:F ratio=1.7:1), illiterate (61.5%), new cases (90.3%) and smear negative (57.6%), presented with cough (94.9%) and chest pain (57.6%). Close to half (46.5%) were reliant on pastoralism (within, 36% nomadic) and 2.3% co-infected with HIV (Table 1). The median diagnosis delay from debut of respiratory symptoms to the date of TB diagnosis was 49 days (IQR=37), ranging 8 to 362 days. Four rural patients received care longer than 254 days after the onset of the early respiratory illnesses. Figure 4: Box plot illustrating the distribution of diagnosis delay in days Cavitation and Smear Positivity Out of the 434 pulmonary TB cases, 45.6% [95%CI: 40.9-50.4%] had single-to-five cavities on chest X-ray (mean, 1.8±0.9 cavities) with mean diameter of 2.8±1.0 centimeters. Of the non-cavitary cases, 5.5% had consolidated lesions but not duly branded as cavity. Overall, 42.0% [95%CI: 37.3 ­ 46.9%] of patients were smear positive upon rechecking at AHRI TB laboratory. The AFB identification rate and loads were similar between the three sputum samples. Individual specimens produced equivalent smear positivity rates (i.e. morning=42%; first spot=41.8%; second spot=41.7%) and grading (correlation≥0.95) with the combined 42% smear positivity (Table 2). In hospital laboratories, 19.2% of smear positive patients were misidentified as smear negative and 2.9% of smear negative as smear positive. Smear positivity was multifold among patients with cavities (75.3%) compared to without cavities (13.7%) [APR (95%CI): 5.5 (3.9-7.7), p<0.001]. Conversely, 82.5% [95%CI: 76.1%, 87.8%] of smear positive patients had cavities. Smear examination truly identified 75.3% [95%CI: 68.6 ˗ 81.2%] of patients with cavitation (sensitivity) and 86.3% [95%CI: 81.2 ­ 90.5%] without cavitation (specificity) (Table 3). Risk Factors of Cavitation and Smear Positivity The rate of cavitation and smear positivity showed no difference between sex, diabetes, HIV, co-infection, history of TB, residence and pastoralism categories [p>0.05]. Cavitation was considerably higher in patients aged 35 years or younger [APR (95%CI) =1.3(1.01–1.6), p=0.04] and with chronic diseases (Hypertension/chronic Heart/Renal Disease) [APR (95%CI) =1.8 (1.2–2.6), p=0.006], and in female patients with low MUAC [APR (95%CI) =1.8 (1.2–2.8), p=0.01] (Table 4). Similarly, smear positivity was higher in patients aged 35 years or younger [APR (95%CI) =1.4 (1.1–1.8), p=0.007], with low BMI [APR (95%CI) =1.3 (1.01–1.7), p=0.04] and low MUAC [APR (95%CI) =1.5(1.2–1.9), p=0.003] (Table 5). Delay in diagnosis of patients is associated with the risk of cavitation [p<0.001]. Cavitation increased in patients who delayed 31-49 days [APR (95%CI) =1.8 (1.2–2.8), p=0.006], 50-70 days [APR (95%CI) =2.4 (1.6–3.7), p<0.001] and 71+ days [APR (95%CI) = 2.7 (1.8–4.1), p<0.001] compared to those who received care within 30 days. Ninety percent (90%) of patients with cavitation delayed more than 30 days (Table 4). Smear positivity was not associated at 30 days delay in diagnosis [p>0.05], but it was significantly higher in patients who delayed above median delay (49 days) [APR (95%CI) =1.3 (1.1–1.6), p=0.02] than their counterparts (Table 5). Discriminative Ability of Delay to Detect Thresholds of Infectiousness The ROC analysis indicated that diagnosis delay has significant predictive ability and detects optimal cutoff point as prognosis test of pulmonary cavitation (p<0.001). The area under curve (AUC) of the empirical ROC was 0.67 [95%CI: 0.62 - 0.72]. The optimal cutoff point was determined at 43 days when the resulting sensitivity, specificity and the likelihood ratio for positive test result were 74.6%, 52.1% and 1.6, respectively (Figure 5). Using this cutoff point, delay correctly classifies 62.4% of patients with or without cavitation, and 60.0% of patients delayed above this point. The predict test revealed that the probability of cavitation increases as a day in delay increases (Figure 6). The median diagnosis delay had also significant association with smear positivity (p=0.02). Nonetheless, it revealed poor discriminative ability to classify smear status [AUC (95%CI): 0.56 (0.51-0.62)] (Figure 7). Figure 5: Area under the ROC curve of diagnosis delay as a prognosis test of pulmonary cavitation Figure 6: The predicted probability of pulmonary cavitation at each value of the observed diagnosis delay Figure 7: Area under the ROC curve of diagnosis delay as a prognosis test of smear positivity Distribution of Environmental Catalysts of TB Transmission Two hundred three patients (46.8%) live in narrow, windowless and small dam-shaped huts. Of whom, 93.1% had evident cough. Out of the patients living in modern mud/cement-made homes, 34.5% live and 59.8% sleep in single rooms. Of the patients with recognized infectiousness, 77.8% of Cavitary and 76.8% of smear positive patients shared sleeping rooms with family members (mean, 6.6±2.8). Similarly, 73.7% of Cavitary and 76.3% of smear positive patients spit sputum everywhere. Regarding knowledge of TB transmission, 55.5% of patients thought TB is transmissible; of whom, 84.7% said via airborne droplets, 6.6% via contaminated food or drink, 5.8% via sexual intercourse and others (2.9%) (Table 6). Discussion The present finding reveals that close to half (45.6%) of all and 82.5% of smear positive patients with pulmonary TB had one or more cavities; 42% were sputum smear positive, and half of them delayed more than seven weeks and few nearly a year without medical care. Cavitation increased continuously as patients delayed longer than four weeks, and optimized at threshold delay of 43 days. Similarly, smear positivity was higher in patients who delayed above seven weeks. Cavitation and smear positivity were reciprocally illustrative, and the majority of patients had either cavitation or was smear positive. Cavities are the stockpiles of mycobacterial accumulation, and connected to airflow they release high bacillary load in sputum and nasal droplets, the channel for transmission [ 23 ]. This connotes the large majority of patients had intricate form of the disease and was capable of transmitting TB prior to diagnosis or treatment. This cavitation rate matches with the maximum assumption of 50% rate that happens if patients do not receive treatment during the entire course of the disease [ 24 , 25 ], and it surpassed the 34.0% [ 26 ] and 21% [ 23 ] rates elsewhere. It was also drastically higher in smear positive patients, almost twice to previous reports of 49.9% [ 23 ] and 38.3% [ 27 ] in other places. On the other hand, the smear positivity was comparable to other reports in Ethiopia [ 28-30 ]. Cavitation and smear positivity were notably higher in delayed patients. The median delay was higher than the threshold delay (43 days) that optimizes the risk of cavitation, and it was the significant delay at which smear positivity increases. To be precise, the majority of patients (60%) delayed above the threshold delay of cavitation without obtaining care. Delay in care does not only worsen cavitation and smear positivity as figured out [ 12 , 13 ], but it also prolongs the period of contagiousness and contact time between patients and contacts [ 17 ]. The majority of infectious patients (90% of cavitary and 84% of smear positive) delayed more than a month in poor housing, crowding and inadequate ventilation conditions implies higher prospect of transmission. Four out of five patients who delayed above the threshold and over three-fourth of patients with Cavitary- or smear positive-TB used to share sleeping rooms/beds with average six-plus household members. This signals an ongoing transmission and is an existing threat in a pastoral community bearing in mind the transitory huts with narrow and closed indoor spaces. In addition to delay, cavitation and smear positivity were also higher in younger (≤35) and undernourished patients as well as in those co-infected with chronic diseases after adjusting for potential confounders. Younger and immune competent patients are documented to have higher risk of cavitation than elders do [ 31 , 32 ]. Concomitant and weakening physical conditions in older people blunt inflammatory responses which then constrain cavitation [ 33 ]. The increased risk of cavitation and smear positivity in undernourished patients could be either way: under-nutrition led to immune-deficiency and enhanced disease progression [ 34 , 35 ] or the disease itself might lead to under-nutrition [ 36 ]. Moreover, other evidences revealed diabetes, smoking, low income and absence of HIV [ 37-39 ] as independent predictors of cavitation and smear positivity. The reason why it is not witnessed in the current study might be due to the small number of cases that cohabit these factors. Nonetheless, our data revealed that cavitation and smear positivity were not different between sex, treatment and livelihood categories. The impact of cavitation is not only limited to transmission but also associated with increased risks of treatment failure, relapse, emergence of drug resistance and permanent lung impairments upon complete treatments as well as dissemination of the disease to other organs [ 16 ]. Hence, evaluating the effects of cavitation on treatment outcomes and transmission will have strategic importance in the prevention and control of TB in places where cavitary TB is prevalent. Limitation: We can anticipate under-reporting of cavitation and smear-positivity. The reduced sensitivity of Chest X-ray might underestimate cavitation, and salivary sputum and missed smear examinations could underrate smear positivity. Recall bias might influence the precision of diagnosis delay. Moreover, the proportion of pastoralists seems less represented contrasted to their proportion in the general population. This might be due to the reduced case notification that was observed during dry seasons when pastoralists moved to remote areas for pasture. Conclusion This study highlights that delay in diagnosis and/or treatment and infectiousness of patients with pulmonary tuberculosis have remained high in pastoral settings in Ethiopia. The indices of infectiousness, cavitation and smear positivity, were extra-prevalent in patients with substantial delays, and in younger and undernourished patients. Excessive delay has strong association with infectiousness and a delay of 43 days looks the threshold delay that optimizes pulmonary cavitation. The majority of patients with remarkable infectiousness live in large families under deprived housings and hazardous conditions for extensive periods. Thus, the ongoing transmission would potentially be huge in pastoralist settings. To control the disease and interrupt the risk of transmission, strategies for pastoralist population need to be revisited, and socio-cultural tailored strategies are needed to address delay in detection and treatment of ill cases in the pastoralist areas of the country. Abbreviations AFB: Acid Fast Bacilli AHRI: Armaur Hansen Research Institute APR: Adjusted Prevalence Ratio AUC: Area Under the Curve BCG: Bacillus Calmette-Guerin BMI: Body Mass Index CI: Confidence Interval CM: Centimeters CT: Computed Tomography DOTS: Directly Observed Therapy-Short Course FMOH: Federal Ministry of Health HIV: Human Immunodeficiency Virus IQR: Inter-Quartile Range Kg: Kilogram M: Meter MDR: Multi-Drug Resistant MTB: Mycobacterium Tuberculosis MUAC: Mid-Upper Arm Circumference NTP: National TB Control Program PR: Prevalence Ratio PTB: Pulmonary Tuberculosis ROC: Receiver operating characteristic SRS: Somali Regional State TB: Tuberculosis WHO: World Health Organization Declarations Acknowledgement We are very grateful to Jigjiga University and Jigjiga One Health Initiative (JOHI) project for funding; Haramaya University, Swill Tropical and Public Health Institute and AHRI for their meticulous protocol evaluation, ethical approval and logistical support. Our special gratitude goes to Somali Regional Health Bureau and the respective study facilities for their support during data collection including permission, transport and logistic support, and permitting TB care providers’ active engagement in data collection. TB care providers, radiography and laboratory technologists deserve the utmost gratitude for their vigilant engagement in the data collection process that required good coordination between service units. Our sincere gratefulness also goes to Dr. Solomon Bishaw, Radiologist at Hiwot Fana Specialized Hospital, for his support during re-examination of sampled X-ray films, and Manendante Mulugeta (PhD in TEFL) for his language editing. Funding This study was funded by the Swiss Agency for Development and Cooperation (SDC) in the frame of Jigjiga One Health Initiative (JOHI) and Jigjiga University. Availability of Data and Materials The dataset supporting the conclusions of this article is included within the article. The collected data contain confidential information, and consent has not been obtained for public sharing of raw data with identifiers. However, the datasets used and/or analyzed are available at the hands of the corresponding author and can be shared upon reasonable requests. Authors’ Contributions FG conceived this research, developed draft protocol, coordinated fieldwork, led data analysis, and wrote draft manuscript. MD enriched the conception, revised and approved all drafts of the protocol and manuscript. AW directed data analysis, and revised and approved all drafts of protocol and manuscript. TG, BS and RT directed the fieldwork, and revised and approved all drafts of the protocol and manuscript. GA led laboratory examinations. MG led Chest X-ray imaging and examinations. All the authors read and approved the final manuscript version sent for publication. Ethical Approval and Consent to Participate Ethical clearance was obtained from Institutional Health Research Ethics Review Committee (IHRERC) of Haramaya University, College of Health and Medical Sciences (Ref.No: IHRERC/009/2016), and AHRI/ALERT Ethical Review Committee (Ref.No: P001/17). Written consent was obtained upon provision of information for participants and parents/guardians of 15-17 years old participants as well as assent from 15-17 years old participants. Participation was self-determined and discontinuation was guaranteed. Consent to publish Consent was obtained from all participants or parents/guardians of 15-17 years old participants to publish data without individual identifiers. Competing Interests None of the authors have any competing interests. References 1. WHO: Global tuberculosis report 2018: World Health Organization; 2018. 2. 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Palaci M, Dietze R, Hadad DJ, Ribeiro FKC, Peres RL, Vinhas SA et al : Cavitary disease and quantitative sputum bacillary load in cases of pulmonary tuberculosis. Journal of clinical microbiology 2007; 45(12):4064-4066. 23. Zhang L, Pang Y, Yu X, Wang Y, Lu J, Gao M et al : Risk factors for pulmonary cavitation in tuberculosis patients from China. Emerging microbes & infections 2016; 5(1):1-11. 24. Curvo-Semedo L, Teixeira L, Caseiro-Alves F: Tuberculosis of the chest. European journal of radiology 2005; 55(2):158-172. 25. Nachiappan AC, Rahbar K, Shi X, Guy ES, Mortani Barbosa EJ, Jr., Shroff GS et al : Pulmonary Tuberculosis: Role of Radiology in Diagnosis and Management. Radiographics : a review publication of the Radiological Society of North America, Inc 2017; 37(1):52-72. 26. Huang Q, Yin Y, Kuai S, Yan Y, Liu J, Zhang Y et al : The value of initial cavitation to predict re-treatment with pulmonary tuberculosis. European journal of medical research 2016; 21(1):20. 27. Manzano KR: Prevalence and Risk Factors of Cavitary Lung Lesions in a Metropolitan Hospital at San Juan Puerto Rico. Chest infections 2015; 148(4):143A. 28. Belay M, Bjune G, Ameni G, Abebe F: Diagnostic and treatment delay among Tuberculosis patients in Afar Region, Ethiopia: a cross-sectional study. BMC public health 2012; 12:369. 29. Gebreegziabher SB, Bjune GA, Yimer SA: Patients' and health system's delays in the diagnosis and treatment of new pulmonary tuberculosis patients in West Gojjam Zone, Northwest Ethiopia: a cross-sectional study. BMC Infect Dis 2016; 16(1):673. 30. Seid A, Metaferia Y: Factors associated with treatment delay among newly diagnosed tuberculosis patients in Dessie city and surroundings, Northern Central Ethiopia: a cross-sectional study. BMC public health 2018; 18(1):931. 31. Perez-Guzman C, Torres-Cruz A, Villarreal-Velarde H, Vargas MH: Progressive age-related changes in pulmonary tuberculosis images and the effect of diabetes. American journal of respiratory and critical care medicine 2000; 162(5):1738-1740. 32. Mathur M, Badhan RK, Kumari S, Kaur N, Gupta S: Radiological Manifestations of Pulmonary Tuberculosis - A Comparative Study between Immunocompromised and Immunocompetent Patients. Journal of clinical and diagnostic research : JCDR 2017; 11(9):Tc06-tc09. 33. Perez-Guzman C, Vargas MH, Torres-Cruz A, Villarreal-Velarde H: Does aging modify pulmonary tuberculosis?: A meta-analytical review. Chest 1999; 116(4):961-967. 34. Chandrasekaran P, Saravanan N, Bethunaickan R, Tripathy S: Malnutrition: Modulator of Immune Responses in Tuberculosis. Frontiers in immunology 2017; 8:1316. 35. Anuradha R, Munisankar S, Bhootra Y, Kumar NP, Dolla C, Kumaran P et al : Coexistent Malnutrition Is Associated with Perturbations in Systemic and Antigen-Specific Cytokine Responses in Latent Tuberculosis Infection. Clinical and vaccine immunology : CVI 2016; 23(4):339-345. 36. Kant S, Gupta H, Ahluwalia S: Significance of nutrition in pulmonary tuberculosis. Critical reviews in food science and nutrition 2015; 55(7):955-963. 37. de Albuquerque Mde F, Albuquerque SC, Campelo AR, Cruz M, de Souza WV, Ximenes RA et al : Radiographic features of pulmonary tuberculosis in patients infected by HIV: is there an objective indicator of co-infection? Revista da Sociedade Brasileira de Medicina Tropical 2001; 34(4):369-372. 38. Alkabab YM, Enani MA, Indarkiri NY, Heysell SK: Performance of computed tomography versus chest radiography in patients with pulmonary tuberculosis with and without diabetes at a tertiary hospital in Riyadh, Saudi Arabia. Infection and drug resistance 2018; 11:37-43. 39. Nijenbandring de Boer R, Oliveira e Souza Filho JB, Cobelens F, Ramalho Dde P, Campino Miranda PF, Logo K et al : Delayed culture conversion due to cigarette smoking in active pulmonary tuberculosis patients. Tuberculosis (Edinburgh, Scotland) 2014; 94(1):87-91. Tables Table 1: Socio-demographic and clinical characteristics of TB patients in Somali region, Ethiopia, December 2017 to October 2018 Characteristics of patients (N=434) Frequency (%) Sex Male 273 (62.9) Female 161 (37.1) Age group 15 to 23 115 (26.5) 24 to 30 112 (25.8) 31 to 50 123 (28.3) 51+ 84 (19.4) Literacy level Illiterate 267 (61.5) Primary 45 (10.4) Secondary 64 (14.7) Tertiary 58 (13.4) Marital status Single 131(30.2) Married 265 (61.1) Divorced/separated/widowed 38 (8.7) Residence Rural 215 (49.5) Urban 215 (49.5) Refugee/displaced 4 (1.0) Livelihood Pastoralism 202 (46.5) Other 232 (53.5) Income Saving 54(12.5) Income=expense 303 (69.8) Indebt 77 (17.7) Cough Yes 412 (94.9) No 22 (5.1) Haemoptysis Yes 33 (7.6) No 401 (92.4) Chest pain Yes 250 (57.6) No 184 (42.4) Breathing difficulty Yes 93 (21.4) No 341 (78.6) Functional status Good 60 (13.8) Ambulatory 360 (83.0) Bedridden 14 (3.2) Treatment category New 392 (90.3) Retreatment 42 (9.7) Prior History of tuberculosis Yes 65 (15.0) No 369 (85.0) Smear status Positive 184 (42.4) Negative 250 (57.6) HIV status Positive 10 (2.3) Negative 422 (97.2) Unknown 2 (0.5) Diabetes mellitus Yes 16 (3.7) No 412 (94.9) Unknown 6 (1.4) Smoking history Ever smoker 45 (10.4) Never smokers 389 (89.6) Khat chewing Ever chewer 58 (13.4) Never chewer 376 (86.6) Table 2: Sputum AFB grading of TB Patients in Somali region, Ethiopia, December 2017 to October 2018 AFB Grading (n=421) Sputum Specimens Morning Specimen 1st Spot Specimen 2nd Spot Specimen Negative 243 (58.0) 244 (58.2) 245 (58.3) Scanty 27 (6.4) 30 (7.2) 28 (6.7) 1+ 52 (12.4) 52 (12.4) 47 (11.2) 2+ 40 (9.6) 43 (10.3) 48 (11.4) 3+ 57 (13.6) 50 (11.9) 52 (12.4) Key: AFB: Acid-Fast Bacilli Table 3: sputum Smear positive versus cavitation matrix of TB patients Cavitary TB Yes (%) No (%) Total AFB result Positive 146 (75.3) 31 (13.7) 177 (42.04) Negative 48 (24.7) 196 (86.3) 244 (57.96) Total 194 227 421 Key : The percentages indicate the proportions of smear positive and negative patients among Cavitary and non-Cavitary cases Table 4: Predictors of Pulmonary cavitation in TB patients in Somali region, Ethiopia, December 2017 to October 2018 Characteristics (n=434) Total PTB cases n (%) Cavitary TB n (%) P- value PR (95%CI) P- value APR (95%CI) Sex Female 161 (37.1) 70 (43.5) 0.49* 1 -- -- Male 273 (62.9) 128 (46.9) 1.1 (0.9, 1.3) Age 15 to 35 251 (57.8) 125 (49.8) 0.04 1.3 (1.01, 1.6) 0.04 1.3 (1.01, 1.6) 36+ 183 (42.2) 73 (39.9) 1 1 Livelihood Pastoralism 202 (46.5) 96 (47.5) 0.45* 1.1 (0.9, 1.3) -- -- Non-pastoralism 232 (53.5) 102 (44.0) 1 Smoking Ever smoker 45 (10.4) 23 (51.1) 0.40* 1.1 (0.8, 1.5) -- -- Never smoker 389 (89.6) 175 (45.0) 1 BCG scar Yes 52 (12.0) 26 (50.0) 0.48* 1.1 (0.8, 1.5) -- -- No 382 (88.0) 172 (45.0) 1 Chronic diseases (HTP/CHD/CRD) Yes 20 (4.6) 12 (60) 0.13 1.3 (0.9, 1.9) 0.006 1.8 (1.2, 2.6) No 414 (95.4) 186 (44.9) 1 1 MUAC female (n=161) Low (≤23 cm) 93 (57.8) 51 (54.8) 0.002 2.0 (1.3, 3.0) 0.01 1.8 (1.13 , 2.8) High (>23 cm) 68 (42.2) 19 (27.9) 1 1 MUAC male (n=273) Low (≤23 cm) 154 (56.4) 74 (48.1) 0.63* 1.1 (0.8, 1.4) -- -- High (>23 cm) 119 (43.6) 54 (45.4) 1 BMI Low (<18.5) 304 (70.0) 149 (49.0) 0.04 1.3 (1.01, 1.7) 0.23 1.2 (0.9, 1.5) High (≥18.5) 130 (30.0) 49 (37.7) 1 1 Prior history of TB Yes 65 (15.0) 31 (47.7) 0.71* 1.1 (0.8, 1.4) -- -- No 369 (85.0) 167 (45.3) 1 Delay in medical care (days) 30 or less 90 (20.7) 20 (22.2) 1 1 -- 1 31 to 49 138 (31.8) 58 (42.0) 0.004 1.9 (1.2, 2.9) 0.006 1.8 (1.2, 2.8) 50 to 70 98 (22.6) 54 (55.1) <0.001 2.5 (1.6, 3.8) <0.001 2.4 (1.6, 3.7) 71 or more 108 (24.9) 66 (61.1) <0.001 2.8 (1.8, 4.2) <0.001 2.7 (1.8, 4.1) Table 5: Predictors of smear positivity in TB patients in Somali region, Ethiopia, December 2017 to October 2018 Characteristics (n=434) Total PTB cases n (%) Smear positive TB n (%) P- value PR (95%CI) P- value APR (95%CI) Sex Female 157 (37.3) 58 (36.9) 0.11 1 0.17 1 Male 264 (62.7) 119 (45.1) 1.2 (0.9, 1.5) 1.2 (0.9, 1.5) Age 15 to 35 245 (58.2) 119 (48.6) 0.002 1.5 (1.2, 1.9) 0.007 1.4 (1.1, 1.8) 36+ 176 (41.8) 58 (33.0) 1 1 Livelihood Pastoralism 194 (46.1) 81 (41.8) 0.91 0.98 (0.79, 1.24) - -- Non-pastoralism 227 (53.9) 96 (42.3) 1 Smoking Ever smoker 43 (10.2) 22 (51.2) 0.17 1.2 (0.9, 1.7) 0.28 1.2 (0.8, 1.6) Never smoker 378 (89.8) 155 (41.0) 1 1 BCG scar Yes 52 (12.4) 23 (44.2) 0.61 1.01 (0.7, 1.4) - -- No 369 (87.6) 154 (41.7) 1 Chronic diseases (HTP/CHD/CRD) Yes 20 (4.8) 8 (40.0) 0.85 0.95 (0.5, 1.6) - -- No 401 (95.2) 169 (42.1) 1 MUAC Low (≤23 cm) 235 (55.8) 119 (50.6) 23 cm) 186 (44.2) 58 (31.2) 1 1 BMI Low (<18.5) 294 (69.8) 135 (45.9) 0.02 1.4 (1.1, 1.8) 0.04 1.3 (1.01, 1.7) High (≥18.5) 127 (30.2) 42 (33.1) 1 1 Prior history of TB Yes 65 (15.4) 22 (33.8) 0.17 0.8 (0.5, 1.1) 0.25 0.8 (0.6, 1.2) No 356 (84.6) 155 (43.5) 1 1 Delay in medical care (days) 49 or less 222 (52.7) 83 (37.4) 0.04 1 0.02 1 50 or more 199 (47.3) 94 (47.2) 1.3 (1.01, 1.6) 1.3 (1.1, 1.6) Key: MUAC and BMI Cutoffs were 23 cm and 18.5 Kg/M2 (FANTA’s finding for developing countries) ; 1 indicates reference category; *indicates the variable not included in multivariable regression analysis; BCG: Bacillus Calmette-Guerin; AFB: Acid-Fast Bacilli; PR prevalence ratio; APR Adjusted prevalence ratio; HTP/CHD/CRD Hypertension/Chronic Heart Disease/Chronic Renal Disease Table 6: Transmission catalysts among delayed, Cavitary and smear-positive patients in Somali region, Ethiopia, December 2017 to October 2018 Environmental catalysis Total PTB cases (= 434) n (%) Delayed above optimal cutoff (=256) n (%) Cavitary TB (=198) n (%) Smear positive (=177) n (%) House type Traditional hut 203 (46.8) 136 (53.1) 93 (47.0) 82 (46.3) Wood & metal roof 173 (39.9) 93 (36.3) 82 (41.4) 70 (39.6) Cement/concrete 58 (13.3) 27 (10.6) 23 (11.6) 25 (14.1) Shares sleeping room with family Yes 350 (80.6) 212 (82.8) 154 (77.8) 136 (76.8) No 84 (19.4) 44 (17.2) 44 (22.2) 41 (23.2) Where do spit Sputum Spit anywhere 320 (73.7) 187 (73.1) 146 (73.7) 135 (76.3) Prepared container 107 (24.7) 66 (25.8) 50 (25.3) 40 (22.6) Other 7 (1.6) 3 (1.2) 2 (1.0) 2 (1.1) Thought TB is transmissible Yes 241 (55.5) 139 (54.3) 122 (61.6) 104 (58.7) No 112 (25.8) 62 (24.2) 44 (22.2) 49 (27.7) I don’t know 81 (18.7) 55 (21.5) 32 (16.2) 24 (13.6) Action to prevent transmission Mouth cover (cough) 164 (37.8) 95 (37.1) 80 (40.4) 72 (40.7) Separate sleep 25 (5.8) 14 (5.5) 11 (5.6) 11 (6.2) Separate meal utensil 4 (0.9) 2 (0.8) 2 (1.0) 1 (0.6) Nothing to prevent 241 (55.5) 145 (56.6) 105 (53.0) 93 (52.5) Key: Delayed case: patients delayed above optimal cut-off point for augmented infectiousness (43 days). 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20:54:21","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":49433,"visible":true,"origin":"","legend":"Procedure of AFB examination","description":"","filename":"figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1442/v1/figure_2.jpg"},{"id":2614596,"identity":"da8211a8-f845-4afb-98a0-0bf928e19e62","added_by":"b0e95e7b-bbe0-4bfd-bf12-a325b7db0c3e","created_at":"2020-09-25 20:54:21","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":30930,"visible":true,"origin":"","legend":"Photo of a patient with cavity on the right chest (arrow), [captured by the radiologist]","description":"","filename":"figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1442/v1/figure_3.jpg"},{"id":2614595,"identity":"e10938b7-1c89-4ba3-b19f-dd50f0d3abfc","added_by":"b0e95e7b-bbe0-4bfd-bf12-a325b7db0c3e","created_at":"2020-09-25 20:54:21","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":14814,"visible":true,"origin":"","legend":"Box plot illustrating the distribution of diagnosis delay in days","description":"","filename":"figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1442/v1/figure_4.jpg"},{"id":2614601,"identity":"8f83aa07-5ae9-4b21-8491-e8da10ee4e13","added_by":"b0e95e7b-bbe0-4bfd-bf12-a325b7db0c3e","created_at":"2020-09-25 20:54:21","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":29567,"visible":true,"origin":"","legend":"Area under the ROC curve of diagnosis delay as a prognosis test of pulmonary cavitation","description":"","filename":"figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1442/v1/figure_5.jpg"},{"id":2614598,"identity":"1bf56862-0198-4e75-9410-35086dc0bd54","added_by":"b0e95e7b-bbe0-4bfd-bf12-a325b7db0c3e","created_at":"2020-09-25 20:54:21","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":18315,"visible":true,"origin":"","legend":"The predicted probability of pulmonary cavitation at each value of the observed diagnosis delay","description":"","filename":"figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1442/v1/figure_6.jpg"},{"id":2614599,"identity":"76a72374-cfe5-4f53-a47b-9026bc0f3cb1","added_by":"b0e95e7b-bbe0-4bfd-bf12-a325b7db0c3e","created_at":"2020-09-25 20:54:21","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":25213,"visible":true,"origin":"","legend":"Area under the ROC curve of diagnosis delay as a prognosis test of smear positivity","description":"","filename":"figure7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1442/v1/figure_7.jpg"},{"id":13467439,"identity":"7e893eff-6d96-48cd-a465-e851009f9ba5","added_by":"auto","created_at":"2021-09-16 20:55:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":848144,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1442/v1/580c8a63-c9ef-4f99-8395-ff44f71bd401.pdf"}],"financialInterests":"","formattedTitle":"Delay in Diagnosis of Pulmonary Tuberculosis is Associated with Increased Risk of Transmission in Pastoralist Setting, Ethiopia","fulltext":[{"header":"Background","content":"\u003cp\u003eTuberculosis (TB), caused by \u003cem\u003eMycobacterium Tuberculosis\u003c/em\u003e \u003cem\u003e(MTB)\u003c/em\u003e, remains the leading killer of infectious diseases. Globally, it caused an estimated\n 10 million cases, 1.3 million deaths, and 300,000 deaths among HIV-positive people\n in 2017. In the same year, Ethiopia ranked 11\u003csup\u003eth\u003c/sup\u003e among the 22 high burden, 4\u003csup\u003eth\u003c/sup\u003e in Africa and one of 14 countries with triple burden of TB, MDR-TB and TB/HIV with\n an estimated 172, 000 new cases [\u003ca href=\"#_ENREF_1\"\u003e\n 1\u003c/a\u003e]. The prevalence was found to be higher in pastoral communities (316/100,000) than\n the national level (277/100,000) [\u003ca href=\"#_ENREF_2\"\u003e\n 2\u003c/a\u003e]. To curb the global epidemics of this deadliest disease, the End-TB strategy sets\n early diagnosis and treatment of cases as pillars to ending TB epidemics by 2030 [\u003ca href=\"#_ENREF_3\"\u003e\n 3\u003c/a\u003e]. For the most part, the national TB control program (NTP) of Ethiopia detects TB\n cases when people with presumptive symptoms present themselves to health facilities\n (passive case finding strategy) [\u003ca href=\"#_ENREF_4\"\u003e\n 4\u003c/a\u003e]. \u003c/p\u003e\n \n\u003cp\u003eHowever, this passive approach struggles to achieve the required case detection rates\n in resource-limited settings, allowing millions of potentially infectious cases undiagnosed\n in communities [\u003ca href=\"#_ENREF_5\"\u003e\n 5\u003c/a\u003e, \u003ca href=\"#_ENREF_6\"\u003e\n 6\u003c/a\u003e]. Nearly one-third of TB cases in Ethiopia were not notified in 2017 [\u003ca href=\"#_ENREF_1\"\u003e\n 1\u003c/a\u003e]. Local-specific reports indicated the number of undetected infectious cases in community\n equals the number of notified cases [\u003ca href=\"#_ENREF_7\"\u003e\n 7\u003c/a\u003e], and another study reported up to two-thirds of active cases remained undetected\n by the passive system [\u003ca href=\"#_ENREF_6\"\u003e\n 6\u003c/a\u003e]. In Somali Regional State of Ethiopia (SRS), new case detection rate has not exceeded\n 50% in recent years [\u003ca href=\"#_ENREF_8\"\u003e\n 8\u003c/a\u003e]. This implies a high number of infectious cases exist in households and communities\n without obtaining proper diagnosis and treatments, which is likely influenced by patients’\n healthcare seeking behavior and health system deficiencies [\u003ca href=\"#_ENREF_9\"\u003e\n 9\u003c/a\u003e, \u003ca href=\"#_ENREF_10\"\u003e\n 10\u003c/a\u003e]. Extreme delay in diagnosis and treatment of TB has been challenging in Ethiopia,\n and median delay exceeding two months was reported in pastoral settings [\u003ca href=\"#_ENREF_11\"\u003e\n 11\u003c/a\u003e].\u003c/p\u003e\n \n\u003cp\u003eFailures to timely detect cases and initiate treatment worsen the disease, increase\n risk of death, increase risk of treatment failure and drug resistance, and exacerbate\n ongoing transmission in households and congregate settings. Devastating damages occur\n in lung tissues as patients delay longer without proper treatment, the classical hallmark\n is cavity formation [\u003ca href=\"#_ENREF_12\"\u003e\n 12\u003c/a\u003e, \u003ca href=\"#_ENREF_13\"\u003e\n 13\u003c/a\u003e]. Cavities are sites of excessive TB bacilli accumulation and release higher bacilli\n load in aerosols [\u003ca href=\"#_ENREF_14\"\u003e\n 14\u003c/a\u003e]. Moreover, cavities slow smear conversion following treatment (prolongs contagious period), and\n are associated with high treatment failure and relapse, emergence of drug resistance,\n disease dissemination and permanent lung impairments [\u003ca href=\"#_ENREF_15\"\u003e\n 15\u003c/a\u003e]. Findings have indicated a call for extended treatment of Cavitary TB with a combination\n of new drugs and new treatment strategies [\u003ca href=\"#_ENREF_16\"\u003e\n 16\u003c/a\u003e], yet no special strategy is currently in place in Ethiopia. \u003c/p\u003e\n \n\u003cp\u003eIn addition to influencing infectiousness, delay prolongs contagious period and extends\n contact time between index case and close contacts [\u003ca href=\"#_ENREF_17\"\u003e\n 17\u003c/a\u003e]. This highlights the need for assessing the effect of delays on risk of TB transmission\n to assess the effectiveness of TB control programs in controlling the disease and\n interrupting its transmission. However, the effect of delays on risk of transmission,\n to the best of our knowledge, was not addressed in pastoral settings in Ethiopia.\n There is also limited data on cavitary TB and the acceptable delays from clinical\n and programmatic perspectives. Hence, this study was intended to assess the association\n of delay in diagnosis with infectiousness of patients and determine threshold delays\n that optimize cavitation and smear positivity as proxy measures of infectiousness.\n We have also assessed household drivers of transmission in Somali regional state of\n Ethiopia where majorities of the population lead pastoral life and households inhabit\n in cramped transitory huts [\u003ca href=\"#_ENREF_18\"\u003e\n 18\u003c/a\u003e]. \u003c/p\u003e"},{"header":"Methods","content":"\u003ch2 data-xsweet-outline-level=\"1\"\u003eStudy Setting\u003c/h2\u003e\n \n\u003cp\u003eFour hospitals (Kharamara, Dege-habour, Kebri-Daher and Gode) and one health center\n (Abilelie) in Somali Regional State of Ethiopia were selected purposefully based on their patient flow, presence of radiologic facility, and geographic\n location in the administration. Kharamara hospital and Abilelie health center are\n located in the regional capital, Jigjiga. The rest facilities are found in less-urbanized,\n pastoral-dominant and semi-arid zones of the region. Approximately 85% of the region’s population lead a nomadic or agro-pastoral way of\n life [\u003ca href=\"#_ENREF_18\"\u003e\n 18\u003c/a\u003e]. The nomads rear livestock, migrate seasonally while agro-pastoralists are relatively\n permanent, and carry out mixed herding and farming [\u003ca href=\"#_ENREF_11\"\u003e\n 11\u003c/a\u003e]. The hospitals and selected health centers provide TB services as per the National\n guideline, which involves two spot-spot smear microscopy examination spaced by 30\n minutes (morning on demand), chest radiography, molecular (GeneXpert), pathology and\n clinical investigations [\u003ca href=\"#_ENREF_4\"\u003e\n 4\u003c/a\u003e]. \u003c/p\u003e\n \n\u003cp\u003eFigure 1: Map of the study area\u003c/p\u003e\n \n\u003ch2 data-xsweet-outline-level=\"1\"\u003eStudy Design and Population \u003c/h2\u003e\n \n\u003cp\u003eA facility-based cross-sectional study was conducted to determine the effect of delay\n in diagnosis and/or treatment on the infectiousness (pulmonary cavitation and sputum\n smear positivity) of patients diagnosed with pulmonary TB (PTB). All newly arriving\n clinically confirmed patients aged ≥15 years were included between December 1, 2017\n and October 31, 2018 regardless of smear status and treatment category. Patients aged\n ≥15 years manifest similar pathological features and the same diagnosis approaches\n are used [\u003ca href=\"#_ENREF_4\"\u003e\n 4\u003c/a\u003e]. People in this age category are believed to acquire competent immunity that is\n key in cavity formation [\u003ca href=\"#_ENREF_19\"\u003e\n 19\u003c/a\u003e], cover 80% of all TB cases and account for almost 100% of disease transmissions\n [\u003ca href=\"#_ENREF_20\"\u003e\n 20\u003c/a\u003e]. Patients with lung co-morbidities (bronchitis, pneumonia and lung cyst) were excluded.\u003c/p\u003e\n \n\u003ch2 data-xsweet-outline-level=\"1\"\u003eSample Size and Sampling Technique \u003c/h2\u003e\n \n\u003cp\u003eThe minimum sample size estimated using OpenEpi303 for cross-sectional studies was\n 282. This assumed 95% CI, 80% power, 1:1 ratio of non-delayed/delayed, 27.5% of non-delayed\n and 45% of delayed patients had cavitation in related study [\u003ca href=\"#_ENREF_12\"\u003e\n 12\u003c/a\u003e], 5% precision and 10% non-response rate, and given delay above 30 days as critical\n point at which risk of transmission increases [\u003ca href=\"#_ENREF_21\"\u003e\n 21\u003c/a\u003e]. We included all the available samples in the analysis to increase the power of\n the test, which raised the final sample size to 434. Patients were recruited sequentially\n from the first date of data collection. As the patients arrived to the Directly Observed\n Therapy-Short Course (DOTS) facilities for treatment initiation, all upcoming eligible\n PTB patients were recruited for the study before initiating treatment. \u003c/p\u003e\n \n\u003ch2 data-xsweet-outline-level=\"1\"\u003eData Collection: Questionnaire, Microscopy and Chest X-ray\u003c/h2\u003e\n \n\u003cp\u003eA mix of methods including interview, anthropometry, Acid-Fast Bacilli (AFB) microscopy\n and chest radiography were used in addition to the standard medical examination (record\n review). A structured and pre-tested questionnaire was employed to obtain data on\n delays in diagnosis, socio-demographics, self-reported medical conditions, and environmental\n drivers of transmission. Records were reviewed to substantiate co-morbidities. Mid-Upper\n Arm Circumference (MUAC) was measured using inelastic paper tapes, and Body Mass Index\n (BMI) was computed from weight (kilograms) and height (meter-square) measures. Nurses\n working in DOTS clinics carried out recruitment, interview, record review and anthropometry\n procedures. Training was provided on sampling and data collection procedures by the\n principal investigator and a local research assistant. \u003c/p\u003e\n \n\u003ch2\u003eAFB Examination \u003c/h2\u003e\n \n\u003cp\u003eUpon completion of interviews, the DOTS providers linked patients to radiology and\n laboratory units using request forms prepared for this purpose. Three sputum specimens\n from each patient were collected; morning sputum at home, and two spot specimens spaced\n by 30 minutes after the patient delivered the morning specimen. A pair of smears was\n prepared from each specimen, air dried and heat fixed. One slide of each pair was\n examined at hospital laboratories using Ziehl Neelsen (ZN) staining technique. The\n rest three smears were transported and examined blindly at Armaur Hansen Research\n Institute (AHRI) TB laboratory in Addis Ababa, Ethiopia. The results were interpreted\n as negative (no AFB), scanty (1-9 AFB/100 field), 1+ (10-99 AFB/100 field), 2+ (1-10\n AFB/field), 3+(\u0026gt;10 AFB/field) [\u003ca href=\"#_ENREF_4\"\u003e\n 4\u003c/a\u003e]. \u003c/p\u003e\n \n\u003cp\u003eFigure 2: Procedure of AFB examination\u003c/p\u003e\n \n\u003ch2\u003eChest Radiography\u003c/h2\u003e\n \n\u003cp\u003eAll patients underwent Chest X-ray examinations to identify lung cavitation, measure\n cavity size and count the number of cavities. A senior radiologist at Kharamara hospital\n examined all the X-ray films and digital imaging. The radiologist was blinded to radiologic\n and AFB results reported during the standard initial diagnosis. Sample of X-ray films\n (n=41) were randomly picked and blindly re-checked by another radiologist to ensure\n the reliability of X-ray readings. As of rechecking, we found levels of 95.1% [84.6-100%]\n kappa agreement for cavity identification, 0.84 [0.64, 0.93] Cohen’s kappa coefficient\n for cavity size, and 85.7% [63.7-96.9%] Cohen’s proportion of zero difference for\n cavity count. \u003c/p\u003e\n \n\u003ch2 data-xsweet-outline-level=\"1\"\u003eData Processing and Analysis\u003c/h2\u003e\n \n\u003cp\u003eData were double entered and validated using EpiData version 3.1; and analyzed using\n Stata/SE\u003csup\u003e®\u003c/sup\u003e14 (\u003cem\u003eStataCorp, College Station, Texas 77845 USA\u003c/em\u003e). Descriptive statistics was performed to summarize delays in diagnosis, patient\n infectiousness, explanatory and environmental factors of transmission. Prevalence\n ratios along with 95% confidence intervals (CI) were used to compare cavitation and\n smear positivity between categories of predictors, and multivariable analyses were\n fitted using Log-binomial regression models. Statistical significances were determined\n at p-value ≤0.05; and p-value ≤ 0.2 in bivariate analysis was used as a cutoff point\n for inclusion in final models. C-statistics or Receiver Operating Characteristic (ROC)\n was employed to determine the discriminatory ability and threshold/optimal cutoff points of diagnosis delay that classify patient\n infectiousness at maximum sum of sensitivity and specificity, and positive likelihood\n ratio (LR+), given sensitivity (\u0026gt;70%). \u003c/p\u003e\n \n\u003ch2 data-xsweet-outline-level=\"1\"\u003eOperational/standard definition of terms\u003c/h2\u003e\n \n\u003cp\u003ePulmonary Tuberculosis: is a patient with lung TB of either smear-positive or negative forms. A smear AFB positive\n patient is confirmed if at least one AFB positive smears; A smear negative patient\n is diagnosed if: at least two AFB smear negative results, no response to a course\n of broad-spectrum antibiotics, again two AFB negative smears and radiological abnormalities\n consistent with TB; Or two AFB smear negative results but culture positive for \u003cem\u003eMTB \u003c/em\u003e[\u003ca href=\"#_ENREF_4\"\u003e\n 4\u003c/a\u003e]. \u003c/p\u003e\n \n\u003cp\u003eNew Case: is a patient who has never had treatment for TB before or has not yet initiated\n anti-TB treatment.\u003c/p\u003e\n \n\u003cp\u003eRetreatment case: is a patient who was treated for any form of TB before but has developed the disease\n again following relapse or default or failure to cure during the 1\u003csup\u003est\u003c/sup\u003e regimen.\u003c/p\u003e\n \n\u003cp\u003eNewly Diagnosed Patient: a patient who was prospectively diagnosed with Pulmonary TB during the study period.\n This excludes patients who were on treatment.\u003c/p\u003e\n \n\u003cp\u003eDiagnosis delay: is defined as the period from debut of the first symptom(s) particularly cough or\n other (chest pain, haemoptysis, weight loss, night sweating) to the date of TB diagnosis.\n \u003c/p\u003e\n \n\u003cp\u003eInfectiousness: is the capability of a PTB patient to transmit TB infection into a susceptible person,\n characterized by the existence of pulmonary cavity and/or AFB positive smear.\u003c/p\u003e\n \n\u003cp\u003ePulmonary cavity: is an air-containing lucent space within a consolidation or a mass or nodule surrounded\n by infiltrate or fibrotic wall identified upon radiological examination [\u003ca href=\"#_ENREF_19\"\u003e\n 19\u003c/a\u003e, \u003ca href=\"#_ENREF_22\"\u003e\n 22\u003c/a\u003e].\u003c/p\u003e\n \n\u003cp\u003eFigure 3: Photo of a patient with cavity on the right chest (arrow), [\u003cem\u003ecaptured by the radiologist\u003c/em\u003e]\u003c/p\u003e"},{"header":"Results","content":"\u003ch3 data-xsweet-outline-level=\"1\"\u003eSocio-demographic and Clinical Characteristics\u003c/h3\u003e\n \n\u003cp\u003eAll the 434 pulmonary TB patients recruited in the study had complete chest radiography,\n and 421 of them had complete AFB results. The participants had a median age of 30\n years, ranging from 15 to 82 years. The majority was male (62.9%; M:F ratio=1.7:1),\n illiterate (61.5%), new cases (90.3%) and smear negative (57.6%), presented with cough\n (94.9%) and chest pain (57.6%). Close to half (46.5%) were reliant on pastoralism\n (within, 36% nomadic) and 2.3% co-infected with HIV (Table 1). \u003c/p\u003e\n \n\u003cp\u003eThe median diagnosis delay from debut of respiratory symptoms to the date of TB diagnosis\n was 49 days (IQR=37), ranging 8 to 362 days. Four rural patients received care longer\n than 254 days after the onset of the early respiratory illnesses. \u003c/p\u003e\n \n\u003cp\u003eFigure 4: Box plot illustrating the distribution of diagnosis delay in days\u003c/p\u003e\n \n\u003ch3 data-xsweet-outline-level=\"1\"\u003eCavitation and Smear Positivity\u003c/h3\u003e\n \n\u003cp\u003eOut of the 434 pulmonary TB cases, 45.6% [95%CI: 40.9-50.4%] had single-to-five cavities\n on chest X-ray (mean, 1.8±0.9 cavities) with mean diameter of 2.8±1.0 centimeters.\n Of the non-cavitary cases, 5.5% had consolidated lesions but not duly branded as cavity.\n Overall, 42.0% [95%CI: 37.3 ­ 46.9%] of patients were smear positive upon rechecking\n at AHRI TB laboratory. The AFB identification rate and loads were similar between\n the three sputum samples. Individual specimens produced equivalent smear positivity\n rates (i.e. morning=42%; first spot=41.8%; second spot=41.7%) and grading (correlation≥0.95)\n with the combined 42% smear positivity (Table 2). In hospital laboratories, 19.2%\n of smear positive patients were misidentified as smear negative and 2.9% of smear\n negative as smear positive. Smear positivity was multifold among patients with cavities\n (75.3%) compared to without cavities (13.7%) [APR (95%CI): 5.5 (3.9-7.7), p\u0026lt;0.001].\n Conversely, 82.5% [95%CI: 76.1%, 87.8%] of smear positive patients had cavities. Smear\n examination truly identified 75.3% [95%CI: 68.6 ˗ 81.2%] of patients with cavitation\n (sensitivity) and 86.3% [95%CI: 81.2 ­ 90.5%] without cavitation (specificity) (Table\n 3). \u003c/p\u003e\n \n\u003ch3 data-xsweet-outline-level=\"1\"\u003eRisk Factors of Cavitation and Smear Positivity\u003c/h3\u003e\n \n\u003cp\u003eThe rate of cavitation and smear positivity showed no difference between sex, diabetes,\n HIV, co-infection, history of TB, residence and pastoralism categories [p\u0026gt;0.05]. Cavitation\n was considerably higher in patients aged 35 years or younger [APR (95%CI) =1.3(1.01–1.6),\n p=0.04] and with chronic diseases \u003cem\u003e(Hypertension/chronic Heart/Renal Disease)\u003c/em\u003e [APR (95%CI) =1.8 (1.2–2.6), p=0.006], and in female patients with low MUAC [APR\n (95%CI) =1.8 (1.2–2.8), p=0.01] (Table 4). Similarly, smear positivity was higher\n in patients aged 35 years or younger [APR (95%CI) =1.4 (1.1–1.8), p=0.007], with low\n BMI [APR (95%CI) =1.3 (1.01–1.7), p=0.04] and low MUAC [APR (95%CI) =1.5(1.2–1.9),\n p=0.003] (Table 5). \u003c/p\u003e\n \n\u003cp\u003eDelay in diagnosis of patients is associated with the risk of cavitation [p\u0026lt;0.001].\n Cavitation increased in patients who delayed 31-49 days [APR (95%CI) =1.8 (1.2–2.8),\n p=0.006], 50-70 days [APR (95%CI) =2.4 (1.6–3.7), p\u0026lt;0.001] and 71+ days [APR (95%CI)\n = 2.7 (1.8–4.1), p\u0026lt;0.001] compared to those who received care within 30 days. Ninety\n percent (90%) of patients with cavitation delayed more than 30 days (Table 4). Smear\n positivity was not associated at 30 days delay in diagnosis [p\u0026gt;0.05], but it was significantly\n higher in patients who delayed above median delay (49 days) [APR (95%CI) =1.3 (1.1–1.6),\n p=0.02] than their counterparts (Table 5).\u003c/p\u003e\n \n\u003ch3 data-xsweet-outline-level=\"1\"\u003eDiscriminative Ability of Delay to Detect Thresholds of Infectiousness\u003c/h3\u003e\n \n\u003cp\u003eThe ROC analysis indicated that diagnosis delay has significant predictive ability\n and detects optimal cutoff point as prognosis test of pulmonary cavitation (p\u0026lt;0.001).\n The area under curve (AUC) of the empirical ROC was 0.67 [95%CI: 0.62 - 0.72]. The\n optimal cutoff point was determined at 43 days when the resulting sensitivity, specificity\n and the likelihood ratio for positive test result were 74.6%, 52.1% and 1.6, respectively\n (Figure 5). Using this cutoff point, delay correctly classifies 62.4% of patients\n with or without cavitation, and 60.0% of patients delayed above this point. The predict\n test revealed that the probability of cavitation increases as a day in delay increases\n (Figure 6). The median diagnosis delay had also significant association with smear\n positivity (p=0.02). Nonetheless, it revealed poor discriminative ability to classify\n smear status [AUC (95%CI): 0.56 (0.51-0.62)] (Figure 7). \u003c/p\u003e\n \n\u003cp\u003eFigure 5: Area under the ROC curve of diagnosis delay as a prognosis test of pulmonary\n cavitation\u003c/p\u003e\n \n\u003cp\u003eFigure 6: The predicted probability of pulmonary cavitation at each value of the observed\n diagnosis delay\u003c/p\u003e\n \n\u003cp\u003eFigure 7: Area under the ROC curve of diagnosis delay as a prognosis test of smear\n positivity\u003c/p\u003e\n \n\u003ch3 data-xsweet-outline-level=\"1\"\u003eDistribution of Environmental Catalysts of TB Transmission\u003c/h3\u003e\n \n\u003cp\u003eTwo hundred three patients (46.8%) live in narrow, windowless and small dam-shaped\n huts. Of whom, 93.1% had evident cough. Out of the patients living in modern mud/cement-made\n homes, 34.5% live and 59.8% sleep in single rooms. Of the patients with recognized\n infectiousness, 77.8% of Cavitary and 76.8% of smear positive patients shared sleeping\n rooms with family members (mean, 6.6±2.8). Similarly, 73.7% of Cavitary and 76.3%\n of smear positive patients spit sputum everywhere. Regarding knowledge of TB transmission,\n 55.5% of patients thought TB is transmissible; of whom, 84.7% said via airborne droplets,\n 6.6% via contaminated food or drink, 5.8% via sexual intercourse and others (2.9%)\n (Table 6). \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present finding reveals that close to half (45.6%) of all and 82.5% of smear positive\n patients with pulmonary TB had one or more cavities; 42% were sputum smear positive,\n and half of them delayed more than seven weeks and few nearly a year without medical\n care. Cavitation increased continuously as patients delayed longer than four weeks,\n and optimized at threshold delay of 43 days. Similarly, smear positivity was higher\n in patients who delayed above seven weeks. \u003c/p\u003e\n \n\u003cp\u003eCavitation and smear positivity were reciprocally illustrative, and the majority of\n patients had either cavitation or was smear positive. Cavities are the stockpiles\n of mycobacterial accumulation, and connected to airflow they release high bacillary\n load in sputum and nasal droplets, the channel for transmission [\u003ca href=\"#_ENREF_23\"\u003e\n 23\u003c/a\u003e]. This connotes the large majority of patients had intricate form of the disease\n and was capable of transmitting TB prior to diagnosis or treatment. This cavitation\n rate matches with the maximum assumption of 50% rate that happens if patients do not\n receive treatment during the entire course of the disease [\u003ca href=\"#_ENREF_24\"\u003e\n 24\u003c/a\u003e, \u003ca href=\"#_ENREF_25\"\u003e\n 25\u003c/a\u003e], and it surpassed the 34.0% [\u003ca href=\"#_ENREF_26\"\u003e\n 26\u003c/a\u003e] and 21% [\u003ca href=\"#_ENREF_23\"\u003e\n 23\u003c/a\u003e] rates elsewhere. It was also drastically higher in smear positive patients, almost\n twice to previous reports of 49.9% [\u003ca href=\"#_ENREF_23\"\u003e\n 23\u003c/a\u003e] and 38.3% [\u003ca href=\"#_ENREF_27\"\u003e\n 27\u003c/a\u003e] in other places. On the other hand, the smear positivity was comparable to other\n reports in Ethiopia [\u003ca href=\"#_ENREF_28\"\u003e\n 28-30\u003c/a\u003e]. \u003c/p\u003e\n \n\u003cp\u003eCavitation and smear positivity were notably higher in delayed patients. The median\n delay was higher than the threshold delay (43 days) that optimizes the risk of cavitation,\n and it was the significant delay at which smear positivity increases. To be precise,\n the majority of patients (60%) delayed above the threshold delay of cavitation without\n obtaining care. Delay in care does not only worsen cavitation and smear positivity\n as figured out [\u003ca href=\"#_ENREF_12\"\u003e\n 12\u003c/a\u003e, \u003ca href=\"#_ENREF_13\"\u003e\n 13\u003c/a\u003e], but it also prolongs the period of contagiousness and contact time between patients\n and contacts [\u003ca href=\"#_ENREF_17\"\u003e\n 17\u003c/a\u003e]. The majority of infectious patients (90% of cavitary and 84% of smear positive)\n delayed more than a month in poor housing, crowding and inadequate ventilation conditions\n implies higher prospect of transmission. Four out of five patients who delayed above\n the threshold and over three-fourth of patients with Cavitary- or smear positive-TB\n used to share sleeping rooms/beds with average six-plus household members. This signals\n an ongoing transmission and is an existing threat in a pastoral community bearing\n in mind the transitory huts with narrow and closed indoor spaces. \u003c/p\u003e\n \n\u003cp\u003eIn addition to delay, cavitation and smear positivity were also higher in younger\n (≤35) and undernourished patients as well as in those co-infected with chronic diseases\n after adjusting for potential confounders. Younger and immune competent patients are\n documented to have higher risk of cavitation than elders do [\u003ca href=\"#_ENREF_31\"\u003e\n 31\u003c/a\u003e, \u003ca href=\"#_ENREF_32\"\u003e\n 32\u003c/a\u003e]. Concomitant and weakening physical conditions in older people blunt inflammatory\n responses which then constrain cavitation [\u003ca href=\"#_ENREF_33\"\u003e\n 33\u003c/a\u003e]. The increased risk of cavitation and smear positivity in undernourished patients\n could be either way: under-nutrition led to immune-deficiency and enhanced disease\n progression [\u003ca href=\"#_ENREF_34\"\u003e\n 34\u003c/a\u003e, \u003ca href=\"#_ENREF_35\"\u003e\n 35\u003c/a\u003e] or the disease itself might lead to under-nutrition [\u003ca href=\"#_ENREF_36\"\u003e\n 36\u003c/a\u003e]. Moreover, other evidences revealed diabetes, smoking, low income and absence of\n HIV [\u003ca href=\"#_ENREF_37\"\u003e\n 37-39\u003c/a\u003e] as independent predictors of cavitation and smear positivity. The reason why it\n is not witnessed in the current study might be due to the small number of cases that\n cohabit these factors. Nonetheless, our data revealed that cavitation and smear positivity\n were not different between sex, treatment and livelihood categories. \u003c/p\u003e\n \n\u003cp\u003eThe impact of cavitation is not only limited to transmission but also associated with\n increased risks of treatment failure, relapse, emergence of drug resistance and permanent\n lung impairments upon complete treatments as well as dissemination of the disease\n to other organs [\u003ca href=\"#_ENREF_16\"\u003e\n 16\u003c/a\u003e]. Hence, evaluating the effects of cavitation on treatment outcomes and transmission\n will have strategic importance in the prevention and control of TB in places where\n cavitary TB is prevalent. \u003c/p\u003e\n \n\u003cp\u003eLimitation: We can anticipate under-reporting of cavitation and smear-positivity. The reduced\n sensitivity of Chest X-ray might underestimate cavitation, and salivary sputum and\n missed smear examinations could underrate smear positivity. Recall bias might influence\n the precision of diagnosis delay. Moreover, the proportion of pastoralists seems less\n represented contrasted to their proportion in the general population. This might be\n due to the reduced case notification that was observed during dry seasons when pastoralists\n moved to remote areas for pasture. \u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study highlights that delay in diagnosis and/or treatment and infectiousness\n of patients with pulmonary tuberculosis have remained high in pastoral settings in\n Ethiopia. The indices of infectiousness, cavitation and smear positivity, were extra-prevalent\n in patients with substantial delays, and in younger and undernourished patients. Excessive\n delay has strong association with infectiousness and a delay of 43 days looks the\n threshold delay that optimizes pulmonary cavitation. The majority of patients with\n remarkable infectiousness live in large families under deprived housings and hazardous\n conditions for extensive periods. Thus, the ongoing transmission would potentially\n be huge in pastoralist settings. To control the disease and interrupt the risk of\n transmission, strategies for pastoralist population need to be revisited, and socio-cultural\n tailored strategies are needed to address delay in detection and treatment of ill\n cases in the pastoralist areas of the country. \u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ch4\u003eAFB:\n Acid Fast Bacilli\u003c/h4\u003e\n \n\u003ch4\u003eAHRI:\n Armaur Hansen Research Institute\u003c/h4\u003e\n \n\u003ch4\u003eAPR:\n Adjusted Prevalence Ratio\u003c/h4\u003e\n \n\u003ch4\u003eAUC:\n Area Under the Curve\u003c/h4\u003e\n \n\u003ch4\u003eBCG:\n Bacillus Calmette-Guerin\u003c/h4\u003e\n \n\u003ch4\u003eBMI:\n Body Mass Index\u003c/h4\u003e\n \n\u003ch4\u003eCI:\n Confidence Interval \u003c/h4\u003e\n \n\u003ch4\u003eCM:\n Centimeters \u003c/h4\u003e\n \n\u003ch4\u003eCT:\n Computed Tomography\u003c/h4\u003e\n \n\u003ch4\u003eDOTS:\n Directly Observed Therapy-Short Course\n \u003c/h4\u003e\n \n\u003ch4\u003eFMOH:\n Federal Ministry of Health\n \u003c/h4\u003e\n \n\u003ch4\u003eHIV:\n Human Immunodeficiency Virus\u003c/h4\u003e\n \n\u003ch4\u003eIQR:\n Inter-Quartile Range\u003c/h4\u003e\n \n\u003ch4\u003eKg:\n Kilogram \u003c/h4\u003e\n \n\u003ch4\u003eM:\n Meter \u003c/h4\u003e\n \n\u003ch4\u003eMDR:\n Multi-Drug Resistant\u003c/h4\u003e\n \n\u003ch4\u003eMTB:\n Mycobacterium Tuberculosis\u003c/h4\u003e\n \n\u003ch4\u003eMUAC:\n Mid-Upper Arm Circumference \u003c/h4\u003e\n \n\u003ch4\u003eNTP:\n National TB Control Program\u003c/h4\u003e\n \n\u003ch4\u003ePR:\n Prevalence Ratio\u003c/h4\u003e\n \n\u003ch4\u003ePTB:\n Pulmonary Tuberculosis\u003c/h4\u003e\n \n\u003ch4\u003eROC: \n Receiver operating characteristic\u003c/h4\u003e\n \n\u003ch4\u003eSRS:\n Somali Regional State\u003c/h4\u003e\n \n\u003ch4\u003eTB:\n Tuberculosis\u003c/h4\u003e\n \n\u003ch4\u003eWHO:\n World Health Organization \u003c/h4\u003e"},{"header":"Declarations","content":"\u003ch3 data-xsweet-outline-level=\"0\"\u003eAcknowledgement \u003c/h3\u003e\n \n\u003cp\u003eWe are very grateful to Jigjiga University and Jigjiga One Health Initiative (JOHI) project for funding; Haramaya University, Swill Tropical and Public Health Institute and AHRI for their\n meticulous protocol evaluation, ethical approval and logistical support. Our special\n gratitude goes to Somali Regional Health Bureau and the respective study facilities\n for their support during data collection including permission, transport and logistic\n support, and permitting TB care providers’ active engagement in data collection. TB\n care providers, radiography and laboratory technologists deserve the utmost gratitude\n for their vigilant engagement in the data collection process that required good coordination\n between service units. Our sincere gratefulness also goes to Dr. Solomon Bishaw, Radiologist\n at Hiwot Fana Specialized Hospital, for his support during re-examination of sampled\n X-ray films, and Manendante Mulugeta (PhD in TEFL) for his language editing. \u003c/p\u003e\n \n\u003ch3 data-xsweet-outline-level=\"0\"\u003eFunding \u003c/h3\u003e\n \n\u003cp\u003eThis study was funded by the Swiss Agency for Development and Cooperation (SDC) in\n the frame of Jigjiga One Health Initiative (JOHI) and Jigjiga University. \u003c/p\u003e\n \n\u003ch3 data-xsweet-outline-level=\"0\"\u003eAvailability of Data and Materials \u003c/h3\u003e\n \n\u003cp\u003eThe dataset supporting the conclusions of this article is included within the article.\n The collected data contain confidential information, and consent has not been obtained\n for public sharing of raw data with identifiers. However, the datasets used and/or\n analyzed are available at the hands of the corresponding author and can be shared\n upon reasonable requests.\u003c/p\u003e\n \n\u003ch3 data-xsweet-outline-level=\"0\"\u003eAuthors’ Contributions\u003c/h3\u003e\n \n\u003cp\u003eFG conceived this research, developed draft protocol, coordinated fieldwork, led data\n analysis, and wrote draft manuscript. MD enriched the conception, revised and approved\n all drafts of the protocol and manuscript. AW directed data analysis, and revised\n and approved all drafts of protocol and manuscript. TG, BS and RT directed the fieldwork,\n and revised and approved all drafts of the protocol and manuscript. GA led laboratory\n examinations. MG led Chest X-ray imaging and examinations. All the authors read and\n approved the final manuscript version sent for publication.\u003c/p\u003e\n \n\u003ch3 data-xsweet-outline-level=\"0\"\u003eEthical Approval and Consent to Participate\u003c/h3\u003e\n \n\u003cp\u003eEthical clearance was obtained from Institutional Health Research Ethics Review Committee\n (IHRERC) of Haramaya University, College of Health and Medical Sciences (Ref.No: IHRERC/009/2016),\n and AHRI/ALERT Ethical Review Committee (Ref.No: P001/17). Written consent was obtained\n upon provision of information for participants and parents/guardians of 15-17 years\n old participants as well as assent from 15-17 years old participants. Participation\n was self-determined and discontinuation was guaranteed. \u003c/p\u003e\n \n\u003ch3 data-xsweet-outline-level=\"0\"\u003eConsent to publish\u003c/h3\u003e\n \n\u003cp\u003eConsent was obtained from all participants or parents/guardians of 15-17 years old\n participants to publish data without individual identifiers.\u003c/p\u003e\n \n\u003ch3 data-xsweet-outline-level=\"0\"\u003eCompeting Interests \u003c/h3\u003e\n \n\u003cp\u003eNone of the authors have any competing interests. \u003c/p\u003e"},{"header":"References","content":"\u003cp\u003e1.\n WHO: Global tuberculosis report 2018: World Health Organization; 2018.\u003c/p\u003e\n \n\u003cp\u003e2.\n Kebede AH, Alebachew, Tsegaye ZF, Lemma E, Abebe A, Agonafir M\u003cem\u003e et al\u003c/em\u003e: The first population-based national tuberculosis prevalence survey in Ethiopia,\n 2010-2011. 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In\u003cem\u003e.\u003c/em\u003e Addis Ababa: Central Statistical Agency of Federal Democratic Republic of Ethiopia;\n 2013.\u003c/p\u003e\n \n\u003cp\u003e19.\n Gadkowski LB, Stout JE: Cavitary pulmonary disease. \u003cem\u003eClinical microbiology reviews \u003c/em\u003e2008; 21(2):305-333.\u003c/p\u003e\n \n\u003cp\u003e20.\n Hunter RL: Pathology of post primary tuberculosis of the lung: an illustrated critical\n review. \u003cem\u003eTuberculosis (Edinburgh, Scotland) \u003c/em\u003e2011; 91(6):497-509.\u003c/p\u003e\n \n\u003cp\u003e21.\n Lin X, Chongsuvivatwong V, Lin L, Geater A, Lijuan R: Dose-response relationship between\n treatment delay of smear-positive tuberculosis patients and intra-household transmission:\n a cross-sectional study. \u003cem\u003eTrans R Soc Trop Med Hyg \u003c/em\u003e2008; 102(8):797-804.\u003c/p\u003e\n \n\u003cp\u003e22.\n Palaci M, Dietze R, Hadad DJ, Ribeiro FKC, Peres RL, Vinhas SA\u003cem\u003e et al\u003c/em\u003e: Cavitary disease and quantitative sputum bacillary load in cases of pulmonary tuberculosis.\n \u003cem\u003eJournal of clinical microbiology \u003c/em\u003e2007; 45(12):4064-4066.\u003c/p\u003e\n \n\u003cp\u003e23.\n Zhang L, Pang Y, Yu X, Wang Y, Lu J, Gao M\u003cem\u003e et al\u003c/em\u003e: Risk factors for pulmonary cavitation in tuberculosis patients from China. \u003cem\u003eEmerging microbes \u0026amp; infections \u003c/em\u003e2016; 5(1):1-11.\u003c/p\u003e\n \n\u003cp\u003e24.\n Curvo-Semedo L, Teixeira L, Caseiro-Alves F: Tuberculosis of the chest. \u003cem\u003eEuropean journal of radiology \u003c/em\u003e2005; 55(2):158-172.\u003c/p\u003e\n \n\u003cp\u003e25.\n Nachiappan AC, Rahbar K, Shi X, Guy ES, Mortani Barbosa EJ, Jr., Shroff GS\u003cem\u003e et al\u003c/em\u003e: Pulmonary Tuberculosis: Role of Radiology in Diagnosis and Management. \u003cem\u003eRadiographics : a review publication of the Radiological Society of North America,\n Inc \u003c/em\u003e2017; 37(1):52-72.\u003c/p\u003e\n \n\u003cp\u003e26.\n Huang Q, Yin Y, Kuai S, Yan Y, Liu J, Zhang Y\u003cem\u003e et al\u003c/em\u003e: The value of initial cavitation to predict re-treatment with pulmonary tuberculosis.\n \u003cem\u003eEuropean journal of medical research \u003c/em\u003e2016; 21(1):20.\u003c/p\u003e\n \n\u003cp\u003e27.\n Manzano KR: Prevalence and Risk Factors of Cavitary Lung Lesions in a Metropolitan\n Hospital at San Juan Puerto Rico. \u003cem\u003eChest infections \u003c/em\u003e2015; 148(4):143A.\u003c/p\u003e\n \n\u003cp\u003e28.\n Belay M, Bjune G, Ameni G, Abebe F: Diagnostic and treatment delay among Tuberculosis\n patients in Afar Region, Ethiopia: a cross-sectional study. \u003cem\u003eBMC public health \u003c/em\u003e2012; 12:369.\u003c/p\u003e\n \n\u003cp\u003e29.\n Gebreegziabher SB, Bjune GA, Yimer SA: Patients' and health system's delays in the\n diagnosis and treatment of new pulmonary tuberculosis patients in West Gojjam Zone,\n Northwest Ethiopia: a cross-sectional study. \u003cem\u003eBMC Infect Dis \u003c/em\u003e2016; 16(1):673.\u003c/p\u003e\n \n\u003cp\u003e30.\n Seid A, Metaferia Y: Factors associated with treatment delay among newly diagnosed\n tuberculosis patients in Dessie city and surroundings, Northern Central Ethiopia:\n a cross-sectional study. \u003cem\u003eBMC public health \u003c/em\u003e2018; 18(1):931.\u003c/p\u003e\n \n\u003cp\u003e31.\n Perez-Guzman C, Torres-Cruz A, Villarreal-Velarde H, Vargas MH: Progressive age-related\n changes in pulmonary tuberculosis images and the effect of diabetes. \u003cem\u003eAmerican journal of respiratory and critical care medicine \u003c/em\u003e2000; 162(5):1738-1740.\u003c/p\u003e\n \n\u003cp\u003e32.\n Mathur M, Badhan RK, Kumari S, Kaur N, Gupta S: Radiological Manifestations of Pulmonary\n Tuberculosis - A Comparative Study between Immunocompromised and Immunocompetent Patients.\n \u003cem\u003eJournal of clinical and diagnostic research : JCDR \u003c/em\u003e2017; 11(9):Tc06-tc09.\u003c/p\u003e\n \n\u003cp\u003e33.\n Perez-Guzman C, Vargas MH, Torres-Cruz A, Villarreal-Velarde H: Does aging modify\n pulmonary tuberculosis?: A meta-analytical review. \u003cem\u003eChest \u003c/em\u003e1999; 116(4):961-967.\u003c/p\u003e\n \n\u003cp\u003e34.\n Chandrasekaran P, Saravanan N, Bethunaickan R, Tripathy S: Malnutrition: Modulator\n of Immune Responses in Tuberculosis. \u003cem\u003eFrontiers in immunology \u003c/em\u003e2017; 8:1316.\u003c/p\u003e\n \n\u003cp\u003e35.\n Anuradha R, Munisankar S, Bhootra Y, Kumar NP, Dolla C, Kumaran P\u003cem\u003e et al\u003c/em\u003e: Coexistent Malnutrition Is Associated with Perturbations in Systemic and Antigen-Specific\n Cytokine Responses in Latent Tuberculosis Infection. \u003cem\u003eClinical and vaccine immunology : CVI \u003c/em\u003e2016; 23(4):339-345.\u003c/p\u003e\n \n\u003cp\u003e36.\n Kant S, Gupta H, Ahluwalia S: Significance of nutrition in pulmonary tuberculosis.\n \u003cem\u003eCritical reviews in food science and nutrition \u003c/em\u003e2015; 55(7):955-963.\u003c/p\u003e\n \n\u003cp\u003e37.\n de Albuquerque Mde F, Albuquerque SC, Campelo AR, Cruz M, de Souza WV, Ximenes RA\u003cem\u003e et al\u003c/em\u003e: Radiographic features of pulmonary tuberculosis in patients infected by HIV: is\n there an objective indicator of co-infection? \u003cem\u003eRevista da Sociedade Brasileira de Medicina Tropical \u003c/em\u003e2001; 34(4):369-372.\u003c/p\u003e\n \n\u003cp\u003e38.\n Alkabab YM, Enani MA, Indarkiri NY, Heysell SK: Performance of computed tomography\n versus chest radiography in patients with pulmonary tuberculosis with and without\n diabetes at a tertiary hospital in Riyadh, Saudi Arabia. \u003cem\u003eInfection and drug resistance \u003c/em\u003e2018; 11:37-43.\u003c/p\u003e\n \n\u003cp\u003e39.\n Nijenbandring de Boer R, Oliveira e Souza Filho JB, Cobelens F, Ramalho Dde P, Campino\n Miranda PF, Logo K\u003cem\u003e et al\u003c/em\u003e: Delayed culture conversion due to cigarette smoking in active pulmonary tuberculosis\n patients. \u003cem\u003eTuberculosis (Edinburgh, Scotland) \u003c/em\u003e2014; 94(1):87-91. \u003c/p\u003e"},{"header":"Tables","content":"\u003cp class=\"caption\"\u003eTable 1: Socio-demographic and clinical characteristics of TB patients in Somali region, Ethiopia, December 2017 to October 2018\u003c/p\u003e\n\u003ctable class=table\u003e\u003ctbody\u003e\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003eCharacteristics of patients (N=434)\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003c/td\u003e\u003ctd\u003e\u003cp\u003e\u003cb\u003eFrequency (%)\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eSex \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eMale \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e273 (62.9)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eFemale \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e161 (37.1)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003cp\u003eAge group \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e15 to 23\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e115 (26.5)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e24 to 30\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e112 (25.8)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e31 to 50\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e123 (28.3)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e51+\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e84 (19.4)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003cp\u003eLiteracy level\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eIlliterate \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e267 (61.5)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003ePrimary \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e45 (10.4)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eSecondary \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e64 (14.7)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eTertiary \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e58 (13.4)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eMarital status \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eSingle \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e131(30.2)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eMarried \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e265 (61.1)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eDivorced/separated/widowed \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e38 (8.7)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eResidence \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eRural \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e215 (49.5)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eUrban \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e215 (49.5)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eRefugee/displaced \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e4 (1.0)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eLivelihood \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003ePastoralism \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e202 (46.5)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eOther \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e232 (53.5)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eIncome \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eSaving \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e54(12.5)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eIncome=expense\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e303 (69.8)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eIndebt \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e77 (17.7)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eCough \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eYes \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e412 (94.9)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNo \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e22 (5.1)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eHaemoptysis \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eYes \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e33 (7.6)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNo \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e401 (92.4)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eChest pain\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eYes \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e250 (57.6)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNo \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e184 (42.4)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eBreathing difficulty \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eYes \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e93 (21.4)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNo \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e341 (78.6)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eFunctional status \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eGood \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e60 (13.8)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eAmbulatory \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e360 (83.0)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eBedridden \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e14 (3.2)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eTreatment category \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNew \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e392 (90.3)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eRetreatment \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e42 (9.7)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003ePrior History of tuberculosis \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eYes \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e65 (15.0)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNo \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e369 (85.0)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eSmear status \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003ePositive \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e184 (42.4)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNegative \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e250 (57.6)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eHIV status\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003ePositive \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e10 (2.3)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNegative \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e422 (97.2)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eUnknown \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e2 (0.5)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eDiabetes mellitus \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eYes \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e16 (3.7)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNo \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e412 (94.9)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eUnknown \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e6 (1.4)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eSmoking history \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eEver smoker \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e45 (10.4)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNever smokers\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e389 (89.6)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eKhat chewing \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eEver chewer\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e58 (13.4)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNever chewer\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e376 (86.6)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003c/tbody\u003e\u003c/table\u003e\n\u003cp class=\"caption\"\u003e Table 2: Sputum AFB grading of TB Patients in Somali region, Ethiopia, December 2017 to October 2018 \u003c/p\u003e\n\u003ctable class=table\u003e\u003ctbody\u003e\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eAFB Grading (n=421)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eSputum Specimens\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eMorning Specimen \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1st Spot Specimen\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e2nd Spot Specimen \u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eNegative \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e243 (58.0)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e244 (58.2)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e245 (58.3)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eScanty \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e27 (6.4)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e30 (7.2)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e28 (6.7)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003e1+\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e52 (12.4)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e52 (12.4)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e47 (11.2)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003e2+\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e40 (9.6)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e43 (10.3)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e48 (11.4)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003e3+\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e57 (13.6)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e50 (11.9)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e52 (12.4)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003c/tbody\u003e\u003c/table\u003e\n\u003cp\u003e\u003cb\u003e\u003ci\u003eKey:\u003c/i\u003e\u003c/b\u003e\u003ci\u003e AFB: Acid-Fast Bacilli\u003c/i\u003e\u003c/p\u003e\n\u003cp class=\"caption\"\u003eTable 3: sputum Smear positive versus cavitation matrix of TB patients \u003c/p\u003e\n\u003ctable class=table\u003e\u003ctbody\u003e\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003c/td\u003e\u003ctd\u003e\u003cp\u003e\u003cb\u003eCavitary TB\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003c/td\u003e\u003ctd\u003e\u003cp\u003e\u003cb\u003eYes (%)\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003eNo (%)\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003eAFB result\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e146 (75.3)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e31 (13.7)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e177 (42.04)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003eNegative\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e48 (24.7)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e196 (86.3)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e244 (57.96)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003c/td\u003e\u003ctd\u003e\u003cp\u003e\u003cb\u003e Total\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e194\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e227\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e421\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003c/tbody\u003e\u003c/table\u003e\n\u003cp\u003e\u003cb\u003e\u003ci\u003eKey\u003c/i\u003e\u003c/b\u003e\u003ci\u003e: The percentages indicate the proportions of smear positive and negative patients among Cavitary and non-Cavitary cases\u003c/i\u003e\u003c/p\u003e\n\u003cbody\u003e\u003cp class=\"caption\"\u003eTable 4: Predictors of Pulmonary cavitation in TB patients in Somali region, Ethiopia, December 2017 to October 2018\u003c/p\u003e\n\u003ctable class=table\u003e\u003ctbody\u003e\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003eCharacteristics (n=434)\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003c/td\u003e\u003ctd\u003e\u003cp\u003e\u003cb\u003eTotal PTB cases n (%)\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003eCavitary TB n (%)\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003e\u003ci\u003eP-\u003c/i\u003evalue\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003ePR (95%CI)\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003e\u003ci\u003eP-\u003c/i\u003evalue\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003eAPR (95%CI)\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eSex \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eFemale \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e161 (37.1)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e70 (43.5)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.49*\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eMale \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e273 (62.9)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e128 (46.9)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.1 (0.9, 1.3)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eAge \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e15 to 35 \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e251 (57.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e125 (49.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.04\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.3 (1.01, 1.6)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.04\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.3 (1.01, 1.6)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e36+\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e183 (42.2)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e73 (39.9)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eLivelihood \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003ePastoralism \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e202 (46.5)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e96 (47.5)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.45*\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.1 (0.9, 1.3)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNon-pastoralism \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e232 (53.5)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e102 (44.0)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eSmoking \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eEver smoker \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e45 (10.4)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e23 (51.1)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.40*\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.1 (0.8, 1.5)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNever smoker\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e389 (89.6)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e175 (45.0)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eBCG scar \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eYes \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e52 (12.0)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e26 (50.0)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.48*\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.1 (0.8, 1.5)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNo \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e382 (88.0)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e172 (45.0)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eChronic diseases (HTP/CHD/CRD)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eYes \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e20 (4.6)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e12 (60)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.13\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.3 (0.9, 1.9)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.006\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.8 (1.2, 2.6)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNo \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e414 (95.4)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e186 (44.9)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eMUAC female (n=161)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eLow (≤23 cm)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e93 (57.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e51 (54.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.002\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e2.0 (1.3, 3.0)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.01\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.8 (1.13 , 2.8)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eHigh (\u0026gt;23 cm)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e68 (42.2)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e19 (27.9)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eMUAC male (n=273)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eLow (≤23 cm)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e154 (56.4)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e74 (48.1)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.63*\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.1 (0.8, 1.4)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eHigh (\u0026gt;23 cm)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e119 (43.6)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e54 (45.4)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eBMI\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eLow (\u0026lt;18.5)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e304 (70.0)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e149 (49.0)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.04\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.3 (1.01, 1.7)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.23 \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.2 (0.9, 1.5)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eHigh (≥18.5)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e130 (30.0)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e49 (37.7)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003ePrior history of TB\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eYes \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e65 (15.0)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e31 (47.7)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.71*\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.1 (0.8, 1.4)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNo \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e369 (85.0)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e167 (45.3)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eDelay in medical care (days)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e30 or less\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e90 (20.7)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e20 (22.2)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e31 to 49\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e138 (31.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e58 (42.0)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.004\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.9 (1.2, 2.9)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.006\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.8 (1.2, 2.8)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e50 to 70\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e98 (22.6)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e54 (55.1)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e2.5 (1.6, 3.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e2.4 (1.6, 3.7)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e71 or more\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e108 (24.9)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e66 (61.1)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e2.8 (1.8, 4.2)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e2.7 (1.8, 4.1)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003c/tbody\u003e\u003c/table\u003e\n\u003cp class=\"caption\"\u003eTable 5: Predictors of smear positivity in TB patients in Somali region, Ethiopia, December 2017 to October 2018\u003c/p\u003e\n\u003ctable class=table\u003e\u003ctbody\u003e\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003eCharacteristics (n=434)\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003c/td\u003e\u003ctd\u003e\u003cp\u003e\u003cb\u003eTotal PTB cases n (%)\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003eSmear positive TB n (%)\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003e\u003ci\u003eP-\u003c/i\u003evalue\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003ePR (95%CI)\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003e\u003ci\u003eP-\u003c/i\u003evalue\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003eAPR (95%CI)\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eSex \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eFemale \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e157 (37.3)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e58 (36.9)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.11\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.17\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eMale \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e264 (62.7)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e119 (45.1)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.2 (0.9, 1.5)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.2 (0.9, 1.5)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eAge \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e15 to 35 \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e245 (58.2)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e119 (48.6)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.002\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.5 (1.2, 1.9)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.007\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.4 (1.1, 1.8)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e36+\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e176 (41.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e58 (33.0)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eLivelihood \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003ePastoralism \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e194 (46.1)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e81 (41.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.91\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.98 (0.79, 1.24)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNon-pastoralism \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e227 (53.9)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e96 (42.3)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eSmoking \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eEver smoker \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e43 (10.2)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e22 (51.2)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.17 \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.2 (0.9, 1.7)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.28\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.2 (0.8, 1.6)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNever smoker\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e378 (89.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e155 (41.0)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eBCG scar \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eYes \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e52 (12.4)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e23 (44.2)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.61\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.01 (0.7, 1.4)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNo \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e369 (87.6)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e154 (41.7)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eChronic diseases (HTP/CHD/CRD)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eYes \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e20 (4.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e8 (40.0)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.85\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.95 (0.5, 1.6)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNo \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e401 (95.2)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e169 (42.1)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eMUAC\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eLow (≤23 cm)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e235 (55.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e119 (50.6)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.6 (1.3, 2.1)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.003\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.5 (1.2, 1.9)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eHigh (\u0026gt;23 cm)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e186 (44.2)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e58 (31.2)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eBMI\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eLow (\u0026lt;18.5)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e294 (69.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e135 (45.9)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.02\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.4 (1.1, 1.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.04\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.3 (1.01, 1.7)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eHigh (≥18.5)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e127 (30.2)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e42 (33.1)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003ePrior history of TB\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eYes \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e65 (15.4)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e22 (33.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.17\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.8 (0.5, 1.1)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.25\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.8 (0.6, 1.2)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNo \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e356 (84.6)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e155 (43.5)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eDelay in medical care (days)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e49 or less\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e222 (52.7)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e83 (37.4)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.04\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e0.02\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e50 or more\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e199 (47.3)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e94 (47.2)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.3 (1.01, 1.6)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1.3 (1.1, 1.6)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003c/tbody\u003e\u003c/table\u003e\n\u003cp\u003e\u003cb\u003e\u003ci\u003eKey:\u003c/i\u003e\u003c/b\u003e\u003c/p\u003e\n\u003cp\u003e\u003ci\u003eMUAC and BMI Cutoffs were 23 cm and 18.5 Kg/M2 (FANTA’s finding for developing countries) ; 1 indicates reference category; *indicates the variable not included in multivariable regression analysis; BCG: Bacillus Calmette-Guerin; AFB: Acid-Fast Bacilli; PR prevalence ratio; APR Adjusted prevalence ratio; HTP/CHD/CRD Hypertension/Chronic Heart Disease/Chronic Renal Disease\u003c/i\u003e\u003c/p\u003e\n\n\u003cp class=\"caption\"\u003eTable 6: Transmission catalysts among delayed, Cavitary and smear-positive patients in Somali region, Ethiopia, December 2017 to October 2018\u003c/p\u003e\n\u003ctable class=table\u003e\u003ctbody\u003e\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003eEnvironmental catalysis \u003c/b\u003e\u003c/p\u003e\n\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003c/td\u003e\u003ctd\u003e\u003cp\u003e\u003cb\u003eTotal PTB cases (= 434) n (%) \u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003eDelayed above optimal cutoff (=256) n (%) \u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003eCavitary TB (=198) \u003c/b\u003e\u003c/p\u003e\n\u003cp\u003e\u003cb\u003en (%)\u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e\u003cb\u003eSmear positive (=177) \u003c/b\u003e\u003c/p\u003e\n\u003cp\u003e\u003cb\u003en (%) \u003c/b\u003e\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eHouse type \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eTraditional hut\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e203 (46.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e136 (53.1)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e93 (47.0)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e82 (46.3)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eWood \u0026amp; metal roof\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e173 (39.9)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e93 (36.3)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e82 (41.4)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e70 (39.6)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eCement/concrete\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e58 (13.3)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e27 (10.6)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e23 (11.6)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e25 (14.1)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eShares sleeping room with family \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eYes \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e350 (80.6)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e212 (82.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e154 (77.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e136 (76.8)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNo \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e84 (19.4)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e44 (17.2)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e44 (22.2)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e41 (23.2)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eWhere do spit Sputum \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eSpit anywhere \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e320 (73.7)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e187 (73.1)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e146 (73.7)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e135 (76.3)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003ePrepared container\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e107 (24.7)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e66 (25.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e50 (25.3)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e40 (22.6)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eOther \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e7 (1.6)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e3 (1.2)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e2 (1.0)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e2 (1.1)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eThought TB is transmissible \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eYes \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e241 (55.5)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e139 (54.3)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e122 (61.6)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e104 (58.7)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNo \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e112 (25.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e62 (24.2)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e44 (22.2)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e49 (27.7)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eI don’t know \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e81 (18.7)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e55 (21.5)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e32 (16.2)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e24 (13.6)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp\u003eAction to prevent transmission \u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eMouth cover (cough)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e164 (37.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e95 (37.1)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e80 (40.4)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e72 (40.7)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eSeparate sleep\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e25 (5.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e14 (5.5)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e11 (5.6)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e11 (6.2)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eSeparate meal utensil\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e4 (0.9)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e2 (0.8)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e2 (1.0)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e1 (0.6)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003cp/\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003eNothing to prevent\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e241 (55.5)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e145 (56.6)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e105 (53.0)\u003c/p\u003e\n\u003c/td\u003e\t\u003ctd\u003e\u003cp\u003e93 (52.5)\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\n\u003ctr\u003e\t\u003ctd\u003e\u003c/tbody\u003e\u003c/table\u003e\u003cp\u003e\u003ci\u003eKey:\u003c/i\u003e\u003c/p\u003e\n\u003cp\u003e\u003ci\u003eDelayed case: patients delayed above optimal cut-off point for augmented infectiousness (43 days).\u003c/i\u003e\u003c/p\u003e\n\u003cp\u003e\u003ci\u003eMean family size= 6.6±2.8 household members\u003c/i\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"delay, tuberculosis, cavity, smear positivity, pastoralist, Ethiopia","lastPublishedDoi":"10.21203/rs.2.10456/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.2.10456/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Background\n\nTo comprehend the effect of delayed care on risk of tuberculosis (TB) transmission in a TB prevalent but low case detection area, this study examined the association of diagnosis delay with patient infectiousness (cavitation and smear positivity) and determined the threshold delay that optimizes infectiousness. It also assessed transmission drivers in Somali region of Ethiopia, an area with ample pastoralist population.\n\nMethods\n\nA cross-sectional study was conducted using 434 new pulmonary TB patients, aged ≥15 years, who were recruited prospectively in five major facilities between December 2017 and October 2018. Data were collected on delays in diagnosis, socio-demographics, clinical and epidemiological information using interview, record-review, anthropometry, sputum microscopy and chest radiography techniques. Log-binomial regression models were used to reveal predictors of cavitation and smear positivity at p\u003c0.05 using Stata/SE®14. C-statistics was applied to determine predictive ability and threshold delay that classifies infectiousness.\n\nResults\n\nMedian age of participants was 30 years. Majorities were male (62.9%), nearly half (46.5%) were pastoralist and 2.3% TB/HIV co-infected. Median delay from debut of illness to diagnosis was 49 days (IQR=37). Among all cases, 45.6% [95%CI: 40.9-50.4] had pulmonary cavity and 42.0% [95%CI: 37.3˗46.9] were smear positive. On multivariable analysis, cavitation was higher in patients delayed over a month [P\u003c0.001], ≤35 years [APR (95%CI) =1.3(1.01-1.6)], with chronic diseases [APR (95%CI) =1.8(1.2-2.6)] and low MUAC*female [APR (95%CI) =1.8(1.2-2.8)]. Smear positivity was higher in patients delayed \u003e49 days [p=0.02], ≤35 years [APR (95%CI) =1.4(1.1-1.8)], low BMI [APR (95%CI) =1.3(1.01-1.7)] and low MUAC [APR (95%CI) =1.5(1.2-1.9)]. Delay discriminates cavitation [AUC (95%CI) =0.67(0.62-0.72)] at 43 days optimal cutoff and 74.6% sensitivity.\n\nConclusion\n\nThis study highlights that delay in diagnosis of pulmonary TB remains high and is associated with increased risk of cavitation and smear positivity in pastoral setting in Ethiopia. In pastoral settings, this may call upon a socio-cultural tailored TB prevention and control strategies.","manuscriptTitle":"Delay in Diagnosis of Pulmonary Tuberculosis is Associated with Increased Risk of Transmission in Pastoralist Setting, Ethiopia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2019-06-19 23:07:08","doi":"10.21203/rs.2.10456/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"26fe5557-0179-4d0c-b62b-a434beccb097","owner":[],"postedDate":"June 19th, 2019","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":13834,"name":"Pulmonology"}],"tags":[],"updatedAt":"","versionOfRecord":[],"versionCreatedAt":"2019-06-19 23:07:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1442","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"identity":"rs-1442","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}