Magnitude of Tuberculosis, its associated risk factors, Rifampicin resistance, and multi- drug resistance rate among TB presumptive patients at five selected Public Hospitals, Somali Region, Eastern Ethiopia, 2025. Retrospective cross-sectional study

Magnitude of Tuberculosis, its associated risk factors, Rifampicin resistance, and multi- drug resistance rate among TB presumptive patients at five selected Public Hospitals, Somali Region, Eastern Ethiopia, 2025. 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Retrospective cross-sectional study Bawlah Tahir, Abdi Osman, Kalid Fuad, Hadis Mahamed, Niman Tayib This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6997913/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Mar, 2026 Read the published version in BMC Infectious Diseases → Version 1 posted 11 You are reading this latest preprint version Abstract Background Tuberculosis (TB) is a major public health problem worldwide. In 2022, an estimated 10.6 million people fell ill with TB worldwide. Emergency of Rifampicin and multi-Drug resistance (RR/MDR) has posed greater public health threat on control and prevention of TB. Ethiopia is among the top 30 high TB burden countries. Objective To assess the Magnitude of Tuberculosis, its associated risk factors, Rifampicin resistance (RR), and Multi-drug resistance (MDR) rate among TB suspected patients in Somali Region, Eastern Ethiopia, 2025. Methods Institution based retrospective cross-sectional study design was employed from May 10, to June 05, 2025. Total of 460 patient’s cards and registration logs from July - December 2024 were recruited. Systematic random sampling technique was employed. Retrospective card review and registers was done. Data were collected using pre-structured checklist. The data were entered into Epi-data version 4.6, exported to and analyzed in SPSS version 25. Bivariate and multi-variable logistic regression analysis was performed to measure the association between dependent and independent variables. P-value < 0.05 was considered statistically significant. Result The overall magnitude of TB among TB presumptive patients was 20.2%(95%CI:16–23%) (93/460). It was higher among male patients (24.3%), patients aged between 16–30 years (27.1%) and patients with history of TB contact (24.4%). Among the TB confirmed patients, 10.8% (95%CI: 7.9–13.6%), (10/93), were resistant to any first line anti-TB drugs. Rifampicin resistance rate was 10.8%( 95%CI: 7.9–13.6%) while MDR rate was 4.3%( 95%CI: 2.4–5.2%). RR/MDR rate was higher among previously treated TB patients; 12%(6/50). Being male, AOR (95%CI): 1.89(1.1–3.14, p = 0.012), and having history TB contact; AOR (95%CI):1.8(1.1–2.9, p = 0.02), were statistically associated with Tuberculosis Conclusion The magnitude of TB was 20.2% indicating higher TB incidence in the region. The overall drug resistance rate was 10.8%; of this, RR and MDR rates were 10.8%, and 4.3% respectively. Male sex and having history of TB contact were statistically associated with TB. Early laboratory diagnosis using WHO recommended rapid molecular tests, Improving and monitoring of early Treatment initiation, scaling up of TB specimen referral linkage to where rapid molecular diagnostics tests are accessible are recommended to limit the spread of the disease and an emergency of Drug resistance. Magnitude TB RR-TB MDR-TB Associated Risk factors Somali Region Ethiopia Figures Figure 1 Figure 2 Figure 3 Introduction Background Tuberculosis (TB) is a major public health problem worldwide and the World Health Organization (WHO) estimates that one third of the world’s population approximately 2 billion people are infected with Mycobacteria tuberculosis (MTB); the causative agent of TB(1). In 2023, an estimated 10.8 million people fell ill from TB worldwide including 6.0 million men, 3.6 million women and 1.3 million children(1). An emergence of drug resistant (DR)-TB poses a public health crisis and a health security threat and is the leading cause of death from antimicrobial resistance (2). Only about 2 in 5 people with multidrug resistant TB accessed treatment in 2023.(1) In 2019, an estimated 3.3% of new and 17.7% of previously treated TB cases have Rifampicin Resistance/Multi-Drug-resistant TB (RR-/MDR-TB)(3). Multi-drug resistant-TB is a form of TB caused by bacteria that do not respond to isoniazid and rifampicin, the two most effective first-line TB drugs and rifampicin resistant - TB (RR-TB) defined as TB resistant to rifampicin only detected using genotypic or phenotypic methods(1). Ethiopia is among the 30 high TB and TB/HIV burden countries globally with an estimated TB incidence rate of 140/100,000 populations (157,000 persons annually); and 21,000 (19/100,000 population) TB deaths in 2018 as per the WHO report 2019(2, 4). In addition, Drug resistant TB continues to pose a major threat in the national response to TB in Ethiopia. According to the last drug resistance survey conducted in 2019, the prevalence of RR-TB was 1.1% among new and 7.5% among previously treated TB cases. In addition, MDR prevalence was 1.03% among new and 6.52% among previously treated TB patients. Any Isoniazid (INH) resistance (6.16%) had highest detected prevalence of all first line drug resistance(2). According to the research findings, inadequate treatment regimen prescribed by health staff, poor patient adherence, previous history of exposure to anti-TB drugs, known TB contact, male sex, age, rural population, HIV co-infection, living in crowded areas, using congested transportation, smoking behavior, Alcohol use, family history of TB, family members greater than five, diabetes and history imprisonment were common associated risk factors of TB(5-15). There is no published data on Magnitude of TB, its associated factors, of RR and MDR rate in the region. Hence, this study is aimed to reflect the regional status of TB, factors associated, RR, and MDR rates. Objectives General Objective To assess the magnitude of Tuberculosis, its associated risk factors, Rifampicin resistance (RR), and Multi-drug resistance (MDR) rate among TB suspected patients in Somali Region, from May 10 – June 05, 2025 Eastern Ethiopia Specific Objective To determine the Magnitude of Tuberculosis To determine the of Rifampicin resistance rate To determine the Multidrug resistance rate To assess the associated risk factors Methods and Materials Study Area and period The study was conducted in five public Hospitals ( Karamara, Gode General Hospitals, Jigjiga Primary Hospita;, Siti general Hosptal, and JigJiga University-Sheik Hasan Yabare Specialized Comprehensive Hospital(JJU-SHYCSH) ), in Somali regional State from May 10 – June 10, 2025. Study design Institution based retrospective cross-sectional study design was employed Source and study population The source population was all TB presumptive patients living in Somali regional state. The study population was all TB presumptive patients ‘cards and register logs enrolled from July to December 2024 at the selected health institutions during the selected period. Inclusion and exclusion criteria All pulmonary and extra pulmonary presumptive TB patients’ cards/ registers with complete information and in all age groups were included. All pulmonary and extra pulmonary presumptive TB cases’ cards and registers with incomplete clinical information were excluded. Sample size determination and sampling technique The sample size was determined using single population proportion formula. By taking 5% margin of error, 95% confidence interval, expected prevalence of 50% as there is no published data on this problem in the study area and around. n = 384 plus 20% non-respondent rate making the final sample size 460 Systematic random sampling technique was deployed by calculating the k th value for each Hospital Proportional sample allocation This study employed a design with a two-stage sampling approach. First, all public Hospitals in the Somali Region offering GeneXpert diagnostic services were identified. From these comprehensive lists, five facilities were selected purposefully based on last six month patients follows. For the patient recruitment phase, all presumptive TB cases and screened at the selected health facilities from July – December 2024. The sample size was allocated proportionally based on each Hospital's average two quarter GeneXpert testing volume (derived from the last 6month surveillance data). The total TB suspects tested in the five Hospitals from July – December 2024 was 7066; where JJU-SHYCSH ranked first (2009), followed by Karamara General Hospital (1719), Jigjiga Primary hospital (1718), Gode General hospital with 895 TB suspected cases and Siti General Hospital with 725. Sample allocation was done using the following formula. A systematic random sampling approach was implemented where every k th patient’s card/register meeting the inclusion criteria was enrolled. The sampling interval (k) was calculated in real-time based on the available data to achieve the predetermined sample size for each Hospital. Data collection methods and laboratory procedures TB presumptive cases in all age groups with compete clinic information was included. Socio-demographic information such as age, sex, occupation, monthly income and educational status and other clinical- related factors (such as history of previous anti-TB, having contact with known TB case, comorbidities, HIV status, nutritional status etc.) was collected using pre-structured questionnaires/data extraction checklist prepared for this study (Supplementary file). Data collectors were trained on the proper card review and data extraction. Principal ad co-investigators fully took part the data collection and maintaining data accuracy. When RR-TB cases are identified, investigators tracked the patient linkage and followed patients’ cards in the selected MDR centers by looking at MDR status. Study variables Dependent variable Magnitude of TB Rifampicin. Multi-drug resistance Independent variables Age, sex, residence, sites of presumptive TB, HIV infection, History of TB contact, History of anti-TB, Diabetic mellitus comorbidity etc. Methods of Data analysis The laboratory analysis results and other data were registered on pre-structured data extraction checklist. The data were entered into Epi-data version 4.6, be exported to and analyzed in Statistical Package for Social Sciences (SPSS) version 25. Data were analyzed for normality and descriptive statistics were presented as a number and percentage (%) for categorical variables and mean ± standard deviation (SD) or median (interquartile range [IQR]) for continuous variables by using SPSS version 25. Bi-variable and multi-variable logistic regression analysis was performed to measure the association between outcome variable and independent variables based on Odds-ratio and level of statistical significance at P-value <0.05. Ethical consideration Ethical clearance was obtained from Somali Regional Health Bureau, Ethical Review Board. Official support letter was written to study sites. Any information about the data was kept confidential and result was only communicated to an authorized concerned body. Operational definitions Presumptive TB: person who presents with symptoms or signs suggestive of TB(16). Previously treated: People who have previously received 1 month or more of TB medicines(16). RR-TB: resistance to rifampicin detected using phenotypic or genotypic methods, with or without resistance to other anti-TB drugs(17) MDR-TB: resistance to at least both isoniazid and rifampicin(17) Results Socio-demographic characteristics The study enrolled 460 patients making 100% response rate. Of these, majority of them, 59.1 %(272/460) were male. The mean age was 33.45 years with a standard deviation of±18.09 years. Regarding age distribution, the largest proportion of participants aged 16–30 years, accounting for 40.9% followed by 31–50 years (28.7%). Most of the patients, (72.8%)(335/460) were from urban areas( Table 1 ). Table 1 : socio-demographic features for magnitude of Tuberculosis, its associated risk factors, Rifampicin resistance, and multi-drug resistance rate among TB presumptive patients at Somali Region, Eastern Ethiopia Variable Category Frequency(n) Percentage (%) Sex Male 272 59.1 Female 188 40.9 Age Categories ≤15 years 65 14.1 16-30 years 188 40.9 31-50 years 132 28.7 >50 years 75 16.3 Residence Urban 335 72.8 Rural 125 27.2 Clinical characteristics The study showed that majority (85%) of participants was presumptive TB cases. Regarding treatment history, most (89.1%), of the patients was treatment naïve. With respect to TB contact history, about 53.5% of participants reported having contact with a TB case. The majority of TB cases were pulmonary (78.5%). Based on patient group classification, 90.4% were new cases, followed by relapse cases (5.4%). Regarding HIV status, 2.2 %(10/460) of patients were HIV-positive. In terms of diabetes status, 17.6% were diabetic ( Table 2 ). Table 2 : Clinical characteristics for magnitude of Tuberculosis, its associated risk factors, Rifampicin resistance, and multi-drug resistance rate among TB presumptive patients at Somali Region, Eastern Ethiopia Variable Category Frequency(n) Percentage (%) Reason for Diagnosis Presumptive TB 391 85 Presumptive DR- TB 69 15 Treatment History New cases 410 89.1 Previously treated 50 10.9 TB Contact History Yes 246 53.5 No 214 46.5 Patient Registration group New 416 90.4 Failure 5 1.1 Relapse 26 5.7 Default 13 2.8 HIV co-infection Positive 10 2.2 Negative 270 58.7 DM status Diabetic 81 17.6 Non-diabetic 378 82.4 Type of TB Pulmonary 361 78.5 Extra-pulmonary 99 21.5 Magnitude of Tuberculosis The overall magnitude of Tuberculosis among Tuberculosis presumptive patients was 20.2%(95%CI:16- 23%) (93/460)( Figure 1 ). The magnitude of TB was higher among male patients (24.3%), patients aged between 16 – 30 years(27.1%) and patients with history of TB contact(24.4%)( Table 1 ). Drug resistance pattern Among the Tuberculosis confirmed patients, 10.8% (95%CI: 7.9 – 13.6%), (10/93), were resistant to any first line anti-TB drugs. Among TB confirmed patients, 10.8%(95%CI: 7.9 – 13.6%), were resistant to Rifampicin while 4.3%(95%CI: 2.4 – 5.2%) were found to be Multi-drug resistant ( Figure 2 ). Drug resistance regarding TB treatment History. The prevalence of any drug resistance (either RR or MDR or both) was higher among previously treated TB patients; 12%(6/50). Among anti-TB naïve patients, drug resistance level was 1%(4/410)( Table 3 ). Table 3 : Drug resistance difference regarding TB treatment history for magnitude of Tuberculosis, its associated risk factors, Rifampicin resistance, and multi-drug resistance rate among TB presumptive patients at Somali Region, Eastern Ethiopia Variable Category Drug resistance pattern(any) Resistant, n(%) Susceptible, n(%) TB treatment History Naïve 4(1) 406(99) Previously treated 6(12) 44(88) Bivariate and multivariable regression for associated factors. Bivariate regression In bivariate regression analysis, sex, TB contact history, age of the patients, and HIV co-infection were candidates for multivariable regression analysis at p-value <0.25( Table 4 ). Table 4 : Bivariate regression for magnitude of Tuberculosis, its associated risk factors, Rifampicin resistance, and multi-drug resistance rate among TB presumptive patients at Somali Region, Eastern Ethiopia Variable Category Tuberculosis AOR (95% CI) P value -ve N (%) +ve N (%) Sex Male 206(75.7) 66(24.3) 1.9(1.2 – 3.12) 0.01 Female 161(85.6) 27(14.4) Ref Age(in years) ≤15 55(84.6) 10(15.4) 1.06(0.42 – 2.7) 0.9 16 -30 137(72.9) 51(27.1) 2.2(1.06 – 4.4) 0.03 31 – 50 111(84.1) 21(15.9) 1.1(0.5 – 2.4) 0.8 Above 50 64(85.3) 11(14.7) Ref Residence Urban 264(78.8) 71(21.2) 1.3(0.7 – 2.14) 0.4 Rural 103(82.4) 22(17.6) Ref TB treatment history New 331(79.8) 84(20.2) 1.01(0.48 – 2.2) 0.97 Previously treated 36(80) 9(20) Ref TB contact history Yes 186(75.6) 60(24.4) 1.5(0.97 – 2.5) 0.018 No 181(84.6) 33(15.4) Ref HIV co-infection Positive 6(60) 4(40) 2.97(0.8 – 11.1) 0.11 Negative 214(79.3) 56(20.7) 1.2(0.7 – 1.9) 0.53 Unknown 147(81.7) 33(18.3) Ref Diabetic Mellitus Yes 66(81.5) 15(18.5) 0.88(0.47 – 1.6) 0.7 No 300(79.4) 78(20.6) Ref Type of TB Pulmonary 290(80.3) 71(19.7) 0.86(0.5 – 1.5) 0.6 Extra-pulmonary 77(77.8) 22(22.2) Ref Abbreviation : -ve: negative, +ve: positive, COR: Crude Odds Ratio, CI: Confidence Interval, N: Number Multivariable Logistic regression In multivariable regression analysis, patients’ sex and having history of TB contact were found statistically associated with Tuberculosis. Male patients were 1.89 times more likely to develop Tuberculosis compared to female patients; AOR (95%CI): 1.89(1.1 – 3.14, p=0.012). In addition, patients with history of contact with TB case were 1.8 times more likely to have infected with Tuberculosis compared with their counterparts; AOR (95%CI):1.8(1.1 – 2.9, p=0.02)( Table 5 ). Table 5 : Multivariable regression for magnitude of Tuberculosis, its associated risk factors, Rifampicin resistance, and multi-drug resistance rate among TB presumptive patients at Somali Region, Eastern Ethiopia Variable Category Tuberculosis AOR (95% CI) P value -ve N (%) +ve N (%) Sex Male 206(75.7) 66(24.3) 1.89(1.1 – 3.14) 0.012 Female 161(85.6) 27(14.4) Ref Age(in years) ≤15 55(84.6) 10(15.4) 1.06(0.4 – 2.7) 0.9 16 -30 137(72.9) 51(27.1) 2.0(0.98 – 4.2) 0.06 31 – 50 111(84.1) 21(15.9) 1.02(0.5 – 2.3) 0.96 Above 50 64(85.3) 11(14.7) Ref TB contact history Yes 186(75.6) 60(24.4) 1.8(1.1 – 2.9) 0.02 No 181(84.6) 33(15.4) Ref HIV co-infection Positive 6(60) 4(40) 2.5(0.6 – 10) 0.2 Negative 214(79.3) 56(20.7) 1.1(0.7 – 1.85) 0.6 Unknown 147(81.7) 33(18.3) Ref Abbreviation : -ve: negative, +ve: positive, AOR: Adjusted Odds Ratio, CI: Confidence Interval, N: Number Discussion TB is public health threat leading to greater mortality and morbidity, especially; developing world. And emergency of drug resistance to the first and 2 nd line anti-TB drugs is posing public health crisis diminishing prevention and control approaches against TB. Producing local epidemiological data on the TB burden, predisposing factors and drug resistance rate would be essential in prevention, control and intervention approaches against the disease(5). In the present study, the overall magnitude of Tuberculosis among Tuberculosis presumptive patients was 20.2 %( 95%CI: 16- 23%). This finding was is in agreement with studies conducted in Debre Markos (23.2%)(18), Gambella (20%)(19), Dessie (23.4%)(20), Gambo Hospital (22.4%)(21), Yirgalem Hospital (16.5%)(22), Ethiopia, South Asian General Hospital(21.3%)(23), Western Oromia (21.3%)(24), Nigeria (23%)(25), Northeastern Nigeria (19.1%)(26), and southwest Nigeria (18.8%)(27). However, this finding was higher than studies done in St. Peter TB specialized Hospital, Addis-Ababa (13.5%), Amhara Region(11%)(28), selected public Hospitals in Addis Ababa (15.11%)(29), Uganda (14%)(30), South Africa (13%)(31), Hiwot Fana Hospital (15.7%)(32), Metehara (14.2%)(33), Motta (8.4%)(34), northwest Ethiopia, Nepal (13.8%)(35), Zimbabwe (11%)(36). This difference would be due to difference in laboratory diagnostic methods, study population inclusion, sample size, geographical locations and living style. In other way, the current study finding was lower than studies carried out in East Gojjam (32.2%)(37), Tigray (37%)(38), Ethiopia, Congo (79.1%)(39), Togo (57%)(40). The disagreement could be due to differences in diagnostic modalities, study participants, sample size, geographical, and TB control practices(5). In the current study, the magnitude of TB was higher among male patients (24.3%) compared to their counterparts. This finding was consistent with study conducted in Debre Markos indicating higher TB incidence among males (27.9%) compared to females and studies done in Addis Ababa(41), Southern Ethiopia(42), Gondar(43), Nigeria(11) and Malaysia(44). In addition, this finding was supported by WHO 2025 report where 10.8 million TB victims, 6 million of them were men(45) and Ethiopian TB national guideline, 2021, reporting that Males account for 56% of the notified TB cases(2). Although, TB affects all sex, but high burden is seen in men. This could be due to men are commonly exposed to variety of risk behavior such as having contact with variety of people, access to prisons, smoking cigarrete and other outreach activities(46). In addition, in the current study, the TB prevalence was higher in patients aged between 16 – 30 years (27.1%) compared to their counterpart indicating circulation of TB infection in the community. This finding was supported by studies conducted in Yirgalem Hospital, Ethiopia(22), Refugee camps, Ethiopia(47). In the current study, male sex was found to be significantly associated with Tuberculosis (1.89 times more likely to develop Tuberculosis compared to female patients). This is in line with studies conducted in selected refugee camps, Ethiopia(47), Addis Ababa(48), India(49), Nigeria(11), Thailand(50) Uganda(10) and Hong Kong(51). In addition to this, this finding was supported by study carried out in Nigeria reporting that female sex were less likely to have TB compared to male(52). In addition, in the present study, history of contact with TB case was statistically associated with the magnitude of TB (1.8 times more likely to have infected with TB). This finding is consistent with studies done in St. Paul’s Hospital, Addis Ababa(53), north Wollo(9), Debre Markos(54), Gedo Zone, Ethiopia(55) Oromia region(56) South Africa(57), Uganda(10), Nigeria(58) and India(59). In the present study, the overall drug resistance rate was 10.8% (95%CI: 7.9 – 13.6%). Level of RR – rate was 10.8% (95%CI: 7.9 – 13.6%). This finding was supported by studies conducted in Debre-Markos (10.3%)(18), India (10.5%)(60), Addis Ababa (9.8%)(41), Thailand (11%)(50), Nigeria (13.5%)(61), Addis-Ababa (9.9%)(29) and Kenya (9.9%)(62). However, it was lower than studies carried out in Addis-Ababa(39.4%)(63), Gondar(15.8%)(43), and Lagos, Nigeria (23.4%)(7). On the other hand, the current finding was higher than reports of studies conducted in Gambella (4.9%)(19), Dubti, Afar region (4.3%)(64), in Eastern Ethiopia (1.7%)(65), East Gojjam (2.59%)(37) and in Nigeria (6.9%)(66). This discrepancies might be due to difference in patient selection, TB case management, diagnosis, geographical locations, and treatment compliance(29). In the current study, drug resistance rate (either RR or MDR or both) was higher among previously treated TB patients compared to treatment naïve (12% vs 1%). This finding is in line with studies conducted in East Gojam, Ethiopia(37), Addis-Ababa(29), Uttar pradesh(67) and Nairobi Kenya(68). This finding was also supported by Ethiopian TB/HIV guideline 2021 indicating that prevalence of RR-TB is 1.1% among new and 7.5% among previously treated TB cases(2) In the present study, the prevalence of MDR was 4.3 %( 95%CI: 2.4 – 5.2%). This finding was supported by studies conducted in East Gojjam, Northwest Ethiopia(3.37%)(37), Dire-dawa(5.1%)(69), Addis Ababa(5.3%)(70) China (5.6%)(71), Germany (4%)(72). However, it was lower than studies done in Amhara Region (15.3%)(73), Addis Ababa (11.54%)(74), St. Peter TB specialized Hospital, Addis Ababa(46.3%)(75) and Iran (12.2%)(76). The disagreement could be due to difference in study population and diagnostic modalities used, for instance these studies deploy MDR-Presumptive TB patients while the current study included all presumptive TB and MDR-presumptive patients and presumptive TB cases dominated. Conclusion and Recommendation The magnitude of TB was 20.2% indicating higher TB incidence in the region. It was higher among male. The overall drug resistance rate was 10.8%; of this, RR and MDR rates were 10.8%, and 4.3% respectively. Drug resistance was higher among previously treated patients. Male sex and having history of TB contact were statistically associated with TB. Early laboratory diagnosis using WHO recommended rapid molecular tests, Improving and monitoring of early Treatment initiation, scaling up of TB specimen referral linkage to where rapid molecular diagnostics tests are accessible are recommended to limit the spread of the disease and an emergency of Drug resistance. Abbreviations AOR Adjusted Odds Ratio CI Confidence interval COR Crude Odds Ratio HIV Human Immuno-deficiency Virus INH Isoniazid IQR Inter-Quartile Range JJU-SHYCSH Jigjiga University Sheik Hassan Yabare Comprehensive Specialized Hospital MDR Multi-Drug Resistance MTB Mycobacterium Tuberculosis RR Rifampicin resistance SD Standard Deviation SPSS Statistical Package for Social Science TB Tuberculosis WHO World Health Organization Declarations Ethical Approval and consent Ethical clearance was obtained from Institutional Health Research Ethics Review Committee (IHRERC), Somali Regional Health Bureau. Official support letter was written to the selected Hospitals (the study area). Informed voluntary written and signed consent was obtained from the chief executive officers of the study Hospitals, and signed consent and assent could not obtained from the patients since the study was retrospective and only patients’ cards and registers were used. Any information about the data was kept confidential. The study also adhered to the Declaration of Helsinki. Clinical trial Not applicable Consent for Publication Not applicable Availability of data and material All data generated or analyzed during this study are available and can be received from the corresponding author upon request Competing Interest Authors declare no competing interest Funding This study was funded by Somali Regional Health Bureau Authors’ contributions BT, AO, KF, HM contributed in designing the study, conducted data collection, analyzed the data and drafted the paper. BT, AO, NT, KF, HM played a great role in the conception of the study, analysis and interpretation of the data and revised subsequent drafts of the paper. BT, KF, NT conducted data analysis, drafted and finalized the manuscript for publication. All authors read and approved the final manuscript for submission. 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Mycobacterium tuberculosis burden, multidrug resistance pattern, and associated risk factors among presumptive extrapulmonary tuberculosis cases at Dessie Referral Hospital, Northeast Ethiopia. The Egyptian Journal of Chest Diseases and Tuberculosis. 2020;69(3):449-54. Ramos JM, Fernández-Muñoz M, Tisiano G, Fano H, Yohannes T, Gosa A, et al. Use of Xpert MTB/RIF assay in rural health facilities in southern Ethiopia. Arch Clin Microbiol. 2017;8:2. Hordofa MW, Adela TB. Prevalence of Refampcin mono resistant Mycobacterium tuberculosis among suspected cases attending at Yirgalem hospital. Clin Med Res. 2015;4(3):75-8. Shrestha P, Arjyal A, Caws M, Prajapati KG, Karkey A, Dongol S, et al. The Application of GeneXpert MTB/RIF for Smear‐Negative TB Diagnosis as a Fee‐Paying Service at a South Asian General Hospital. Tuberculosis research and treatment. 2015;2015(1):102430. Zewdie O, Dabsu R, Kifle E, Befikadu D. Rifampicin-resistant multidrug-resistant tuberculosis cases in selected hospitals in Western Oromia, Ethiopia: cross-sectional retrospective study. Infection and Drug Resistance. 2020:3699-705. Aliyu G, El-Kamary SS, Abimiku Al, Ezati N, Mosunmola I, Hungerford L, et al. Mycobacterial etiology of pulmonary tuberculosis and association with HIV infection and multidrug resistance in Northern Nigeria. Tuberculosis Research and Treatment. 2013;2013(1):650561. Denue BA, Miyanacha WJ, Wudiri Z, Alkali MB, Goni BW, Akawu CB. Molecular detection of sputum Mycobacterium tuberculosis/rifampicin resistance among presumptive pulmonary tuberculosis cases in Borno state, North-Eastern Nigeria. Port Harcourt Medical Journal. 2018;12(2):64-9. Bello LA, Shittu MO, Shittu BT, Oluremi AS, Akinnuroju ON, Adekola SA. Rifampicin-monoresistant Mycobacterium tuberculosis among the patients visiting chest clinic, state specialist hospital, Akure, Nigeria. Int J Res Med Sci. 2014;2:1134-7. Hailu AGWGG. 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Trend analysis and seasonality of tuberculosis among patients at the Hiwot Fana Specialized University Hospital, Eastern Ethiopia: a Retrospective Study. Risk management and healthcare policy. 2019:297-305. Yohanes A, Abera S, Ali S. Smear positive pulmonary tuberculosis among suspected patients attending metehara sugar factory hospital; eastern Ethiopia. African health sciences. 2012;12(3):325-30. Demissie TA, Belayneh D. Magnitude of Mycobacterium tuberculosis infection and its resistance to rifampicin using Xpert-MTB/RIF assay among presumptive tuberculosis patients at Motta General Hospital, Northwest Ethiopia. Infection and Drug Resistance. 2021:1335-41. Sah SK, Bhattarai PR, Shrestha A, Dhami D, Guruwacharya D, Shrestha R. Rifampicin-resistant Mycobacterium tuberculosis by GeneXpert MTB/RIF and associated factors among presumptive pulmonary tuberculosis patients in Nepal. Infection and Drug Resistance. 2020:2911-9. Charambira K, Ade S, Harries A, Ncube R, Zishiri C, Sandy C, et al. Diagnosis and treatment of TB patients with rifampicin resistance detected using Xpert® MTB/RIF in Zimbabwe. Public health action. 2016;6(2):122-8. Adane K, Ameni G, Bekele S, Abebe M, Aseffa A. Prevalence and drug resistance profile of Mycobacterium tuberculosis isolated from pulmonary tuberculosis patients attending two public hospitals in East Gojjam zone, northwest Ethiopia. BMC public health. 2015;15:1-8. Mehari K, Asmelash T, Hailekiros H, Wubayehu T, Godefay H, Araya T, et al. Prevalence and factors associated with multidrug‐resistant tuberculosis (MDR‐TB) among presumptive MDR‐TB patients in Tigray Region, Northern Ethiopia. Canadian Journal of Infectious Diseases and Medical Microbiology. 2019;2019(1):2923549. Farra A, Manirakiza A, Yambiyo BM, Zandanga G, Lokoti B, Berlioz-Arthaud A, et al., editors. Surveillance of rifampicin resistance with GeneXpert MTB/RIF in the National Reference Laboratory for tuberculosis at the Institut Pasteur in Bangui, 2015–2017. Open forum infectious diseases; 2019: Oxford University Press US. Dagnra AY, Mlaga KD, Adjoh K, Kadanga E, Disse K, Adekambi T. Prevalence of multidrug-resistant tuberculosis cases among HIV-positive and HIV-negative patients eligible for retreatment regimen in Togo using GeneXpert MTB/RIF. New microbes and new infections. 2015;8:24-7. Araya S, Negesso AE, Tamir Z. Rifampicin-resistant Mycobacterium tuberculosis among patients with presumptive tuberculosis in Addis Ababa, Ethiopia. Infection and Drug Resistance. 2020:3451-9. Datiko DG, Lindtjørn B. Tuberculosis recurrence in smear-positive patients cured under DOTS in southern Ethiopia: retrospective cohort study. BMC Public Health. 2009;9:1-5. Jaleta KN, Gizachew M, Gelaw B, Tesfa H, Getaneh A, Biadgo B. Rifampicin-resistant Mycobacterium tuberculosis among tuberculosis-presumptive cases at University of Gondar Hospital, northwest Ethiopia. Infection and drug resistance. 2017:185-92. Ahmad N, Baharom M, Aizuddin AN, Ramli R. Sex-related differences in smear-positive pulmonary tuberculosis patients in Kuala Lumpur, Malaysia: prevalence and associated factors. PloS One. 2021;16(1):e0245304. WHO WHO. Tuberculosis 2025 [Available from: https://www.who.int/news-room/fact-sheets/detail/tuberculosis. Borgdorff MW, Nagelkerke N, Dye C, Nunn P. Gender and tuberculosis: a comparison of prevalence surveys with notification data to explore sex differences in case detection. The International Journal of Tuberculosis and Lung Disease. 2000;4(2):123-32. Meaza A, Yenew B, Amare M, Alemu A, Hailu M, Gamtesa DF, et al. Prevalence of tuberculosis and associated factors among presumptive TB refugees residing in refugee camps in Ethiopia. BMC infectious diseases. 2023;23(1):498. Hirpa S, Medhin G, Girma B, Melese M, Mekonen A, Suarez P, et al. Determinants of multidrug-resistant tuberculosis in patients who underwent first-line treatment in Addis Ababa: a case control study. BMC public health. 2013;13:1-9. Dhanaraj B, Papanna MK, Adinarayanan S, Vedachalam C, Sundaram V, Shanmugam S, et al. Prevalence and risk factors for adult pulmonary tuberculosis in a metropolitan city of South India. PloS one. 2015;10(4):e0124260. Klayut W, Rudeeaneksin J, Srisungngam S, Bunchoo S, Bhakdeenuan P, Phetsuksiri B, et al. Detection and factors associated with tuberculosis and rifampicin resistance among presumptive patients at the Thailand-Myanmar border. 2022. Law W, Yew W, Chiu Leung C, Kam K, Tam C, Chan C, et al. Risk factors for multidrug-resistant tuberculosis in Hong Kong. The international journal of tuberculosis and lung disease. 2008;12(9):1065-70. Famuyiwa MK. Risk factors and prevalence of tuberculosis among presumptive cases of a general hospital in Nigeria. Researchgate; 2018. Kassa M, Desta K, Ambachew R, Gebreyohannes Z, Gebreyohanns A, Zena N, et al. Magnitude of Mycobacterium tuberculosis, drug resistance and associated factors among presumptive tuberculosis patients at St. Paul’s Hospital Millennium Medical College, Addis Ababa, Ethiopia. Plos one. 2022;17(8):e0272459. Liyew Ayalew M, Birhan Yigzaw W, Tigabu A, Gelaw Tarekegn B. Prevalence, associated risk factors and rifampicin resistance pattern of pulmonary tuberculosis among children at Debre Markos Referral Hospital, Northwest, Ethiopia. Infection and Drug Resistance. 2020:3863-72. Diriba K, Awulachew E. Associated risk factor of tuberculosis infection among adult patients in Gedeo Zone, Southern Ethiopia. SAGE Open Medicine. 2022;10:20503121221086725. Mulisa G, Workneh T, Hordofa N, Suaudi M, Abebe G, Jarso G. Multidrug-resistant Mycobacterium tuberculosis and associated risk factors in Oromia Region of Ethiopia. International Journal of Infectious Diseases. 2015;39:57-61. Marais BJ, Obihara CC, Gie RP, Schaaf HS, Hesseling AC, Lombard C, et al. The prevalence of symptoms associated with pulmonary tuberculosis in randomly selected children from a high burden community. Archives of Disease in Childhood. 2005;90(11):1166-70. Egbe NE, Olatunji A, Vantsawa PA. Prevalence of Tuberculosis, Rifampicin Resistant Tuberculosis and Associated Risk Factors in Presumptive Tuberculosis Patients Attending Some Hospitals in Kaduna, Nigeria. The FASEB Journal. 2022;36. Singh M, Mynak M, Kumar L, Mathew J, Jindal S. Prevalence and risk factors for transmission of infection among children in household contact with adults having pulmonary tuberculosis. Archives of disease in childhood. 2005;90(6):624-8. Gupta A, Mathuria JP, Singh SK, Gulati AK, Anupurba S. Antitubercular drug resistance in four healthcare facilities in North India. Journal of health, population, and nutrition. 2011;29(6):583. Nwadioha S, Nwokedi E, Ezema G, Eronini N, Anikwe A, Audu F, et al. Drug Resistant Mycobacterium tuberculosis in Benue, Nigeria. 2014. Ng'ang'a ZW, Nyang’au LO, Amukoye E. Determining first line anti-tuberculosis drug resistance among new and re-treatment tuberculosis/human immunodeficiency virus infected patients, Nairobi Kenya. 2015. Mesfin EA, Beyene D, Tesfaye A, Admasu A, Addise D, Amare M, et al. Drug-resistance patterns of Mycobacterium tuberculosis strains and associated risk factors among multi drug-resistant tuberculosis suspected patients from Ethiopia. PloS one. 2018;13(6):e0197737. Gebrehiwet GB, Kahsay AG, Welekidan LN, Hagos AK, Abay GK, Hagos DG. Rifampicin resistant tuberculosis in presumptive pulmonary tuberculosis cases in Dubti Hospital, Afar, Ethiopia. The Journal of Infection in Developing Countries. 2019;13(01):21-7. Seyoum B, Demissie M, Worku A, Bekele S, Aseffa A. Prevalence and drug resistance patterns of Mycobacterium tuberculosis among new smear positive pulmonary tuberculosis patients in eastern Ethiopia. Tuberculosis research and treatment. 2014;2014(1):753492. Okonkwo R, Onwunzo M, Chukwuka C, Ele P, Anyabolu A, Onwurah C, et al. The use of the Gene Xpert mycobacterium tuberculosis/Rifampicin (MTB/Rif) assay in detection of multi-drug resistant tuberculosis (MDRTB) in Nnamdi Azikiwe University Teaching Hospital, Nnewi, Nigeria. J HIV Retrovirus. 2017;3:1. Gautam PB, Mishra A, Kumar S. Prevalence of rifampicin resistant mycobacterium tuberculosis and associated factors among presumptive tuberculosis patients in eastern Uttar Pradesh: a cross sectional study. Int J Community Med Public Health. 2018;5(6):2271-6. Ogaro T, Githui W, Kikuvi G, Okari J, Wangui E, Asiko V. Anti-tuberculosis drug resistance in Nairobi, Kenya. African Journal of Health Sciences. 2012;20(1-2):21-7. Zewdie B, Mohammed H. Prevalence and associated factors of multi drug resistance tuberculosis among presumptive tuberculosis patients at public health facilities in Dire Dawa City, Eastern Ethiopia. Harla Journal of Health and Medical Science. 2022;1(1):31-43. Eyob G, Guebrexabher H, Lemma E, Wolday D, Gebeyehu M, Abate G, et al. Drug susceptibility of Mycobacterium tuberculosis in HIV-infected and-uninfected Ethiopians and its impact on outcome after 24 months of follow-up. The International Journal of Tuberculosis and Lung Disease. 2004;8(11):1388-91. Zhao M, Li X, Xu P, Shen X, Gui X, Wang L, et al. Transmission of MDR and XDR tuberculosis in Shanghai, China. PLoS One. 2009;4(2):e4370. Eker B, Ortmann J, Migliori GB, Sotgiu G, Muetterlein R, Centis R, et al. Multidrug- and extensively drug-resistant tuberculosis, Germany. Emerging infectious diseases. 2008;14(11):1700-6. Nigus DM, Lingerew W, Beyene B, Tamiru A, Lemma M, Melaku MY. Prevalence of multi drug resistant tuberculosis among presumptive multi drug resistant tuberculosis cases in Amhara National Regional State, Ethiopia. J Mycobac Dis. 2014;4(152):2161-1068.1000152. Sinshaw W, Kebede A, Bitew A, Tesfaye E, Tadesse M, Mehamed Z, et al. Prevalence of tuberculosis, multidrug resistant tuberculosis and associated risk factors among smear negative presumptive pulmonary tuberculosis patients in Addis Ababa, Ethiopia. BMC infectious diseases. 2019;19:1-15. Abate D, Taye B, Abseno M, Biadgilign S. Epidemiology of anti-tuberculosis drug resistance patterns and trends in tuberculosis referral hospital in Addis Ababa, Ethiopia. BMC Res Notes. 2012;5:462. Metanat M, Sharifi-Mood B, Shahreki S, Dawoudi SH. Prevalence of multidrug-resistant and extensively drug-resistant tuberculosis in patients with pulmonary tuberculosis in zahedan, southeastern iran. Iranian Red Crescent medical journal. 2012;14(1):53-5. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6997913","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":498529900,"identity":"606b5919-5a46-48d5-9443-3266bfa8e390","order_by":0,"name":"Bawlah 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12:53:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6997913/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6997913/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12879-026-13150-8","type":"published","date":"2026-03-25T16:13:16+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":89232313,"identity":"bbf7a3e1-4215-427a-9169-9c11996e3c99","added_by":"auto","created_at":"2025-08-17 14:24:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":61051,"visible":true,"origin":"","legend":"\u003cp\u003eMagnitude of TB for magnitude of Tuberculosis, its associated risk factors, Rifampicin resistance, and multi-drug resistance rate among TB presumptive patients at Somali Region, Eastern Ethiopia\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-6997913/v1/f9e62439f21b967df35fd65d.png"},{"id":89233272,"identity":"e326de85-e94f-4f0e-8fa9-124f220d3fc3","added_by":"auto","created_at":"2025-08-17 14:32:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":64499,"visible":true,"origin":"","legend":"\u003cp\u003eDrug resistance patterns for magnitude of Tuberculosis, its associated risk factors, Rifampicin resistance, and multi-drug resistance rate among TB presumptive patients at Somali Region, Eastern Ethiopia\u003c/p\u003e","description":"","filename":"22.png","url":"https://assets-eu.researchsquare.com/files/rs-6997913/v1/466580029a40f322b5c7d2f0.png"},{"id":89233274,"identity":"b59e13aa-d28f-483d-b90f-9b1ca498395e","added_by":"auto","created_at":"2025-08-17 14:32:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":51988,"visible":true,"origin":"","legend":"\u003cp\u003eUnnumbered image in the Methods and Materials section.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6997913/v1/a49e998bddcaea3877577b0e.png"},{"id":105755052,"identity":"56bfea8c-898f-4150-a81f-2b2de1421be3","added_by":"auto","created_at":"2026-03-30 16:24:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1388146,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6997913/v1/e9e6fddf-59ee-4833-a1e9-934536a53963.pdf"},{"id":89232315,"identity":"bfeefc5f-7a06-45b6-8b8c-d7d53c794e33","added_by":"auto","created_at":"2025-08-17 14:24:28","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":19909,"visible":true,"origin":"","legend":"","description":"","filename":"QuestionariesforTBmagnitudeandDrugresistance.docx","url":"https://assets-eu.researchsquare.com/files/rs-6997913/v1/6870958d76bf272ab78af439.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Magnitude of Tuberculosis, its associated risk factors, Rifampicin resistance, and multi- drug resistance rate among TB presumptive patients at five selected Public Hospitals, Somali Region, Eastern Ethiopia, 2025. Retrospective cross-sectional study","fulltext":[{"header":"Introduction","content":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTuberculosis (TB) is a major public health problem worldwide and the World Health Organization (WHO) estimates that one third of the world\u0026rsquo;s population approximately 2 billion people are infected with \u003cem\u003eMycobacteria tuberculosis\u003c/em\u003e (MTB); the causative agent of TB(1). In 2023, an estimated 10.8 million people fell ill from TB worldwide including 6.0\u0026nbsp;million men, 3.6\u0026nbsp;million women and 1.3\u0026nbsp;million children(1).\u0026nbsp;An emergence of drug resistant (DR)-TB poses a public health crisis and a health security threat and is the leading cause of death from antimicrobial resistance (2). Only about 2 in 5 people with multidrug resistant TB accessed treatment in 2023.(1)\u0026nbsp;In 2019, an estimated 3.3% of new and 17.7% of previously treated TB cases have Rifampicin Resistance/Multi-Drug-resistant TB (RR-/MDR-TB)(3). Multi-drug resistant-TB is a form of TB caused by bacteria that do not respond to isoniazid and rifampicin, the two most effective first-line TB drugs and rifampicin resistant - TB (RR-TB) defined as TB resistant to rifampicin only detected using genotypic or phenotypic methods(1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEthiopia is among the 30 high TB and TB/HIV burden countries globally with an estimated TB incidence rate of 140/100,000 populations (157,000 persons annually); and 21,000 (19/100,000 population) TB deaths in 2018 as per the WHO report 2019(2, 4). In addition, Drug resistant TB continues to pose a major threat in the national response to TB in Ethiopia. According to the last drug resistance survey conducted in 2019, the prevalence of RR-TB was 1.1% among new and 7.5% among previously treated TB cases. In addition, MDR prevalence was 1.03% among new and 6.52% among previously treated TB patients. Any Isoniazid (INH) resistance (6.16%) had highest detected prevalence of all first line drug resistance(2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAccording to the research findings, inadequate treatment regimen prescribed by health staff, poor patient adherence, previous history of exposure to anti-TB drugs, known TB contact, male sex, age, rural population, HIV co-infection, living in crowded areas, using congested transportation, smoking behavior, Alcohol use, family history of TB, family members greater than five, diabetes and history imprisonment were common associated risk factors of TB(5-15). There is no published data on Magnitude of TB, its associated factors, of RR and MDR rate in the region. Hence, this study is aimed to reflect the regional status of TB, factors associated, RR, and MDR rates.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGeneral Objective\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eTo assess the magnitude of Tuberculosis, its associated risk factors, \u0026nbsp;Rifampicin resistance (RR), and Multi-drug resistance (MDR) rate among TB suspected patients in Somali Region, from May 10 \u0026ndash; June 05, 2025 Eastern Ethiopia\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eSpecific Objective\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eTo determine the Magnitude of Tuberculosis\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eTo determine the of Rifampicin resistance rate\u003c/li\u003e\n \u003cli\u003eTo determine the Multidrug resistance rate\u003c/li\u003e\n \u003cli\u003eTo assess the associated risk factors\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Methods and Materials ","content":"\u003cp\u003e\u003cstrong\u003eStudy Area and period\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in five public Hospitals (\u003cem\u003eKaramara, Gode General Hospitals, Jigjiga Primary Hospita;, Siti general Hosptal, and JigJiga University-Sheik Hasan Yabare Specialized Comprehensive Hospital(JJU-SHYCSH)\u003c/em\u003e), in Somali regional State from May 10 \u0026ndash; June 10, 2025. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInstitution based retrospective cross-sectional study design was employed\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSource and study population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe source population was all TB presumptive patients living in Somali regional state. The study population was all TB presumptive patients \u0026lsquo;cards and register logs enrolled from July to December 2024 at the selected health institutions during the selected period.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion and exclusion criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll pulmonary and extra pulmonary presumptive TB patients\u0026rsquo; cards/ registers with complete information and in all age groups were included. All pulmonary and extra pulmonary presumptive TB cases\u0026rsquo; cards and registers with incomplete clinical information were excluded.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample size determination and sampling technique\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sample size was determined using single population proportion formula. By taking 5% margin of error, 95% confidence interval, expected prevalence of 50% as there is no published data on this problem in the study area and around.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"285\" height=\"102\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e= 384 plus 20% non-respondent rate making the final sample size 460\u003c/p\u003e\n\u003cp\u003eSystematic random sampling technique was deployed by calculating the k\u003csup\u003eth\u003c/sup\u003e value for each Hospital \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProportional sample allocation\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study employed a design with a two-stage sampling approach. First, all public Hospitals in the Somali Region offering GeneXpert diagnostic services were identified. From these comprehensive lists, five facilities were selected purposefully based on last six month patients follows.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor the patient recruitment phase, all presumptive TB cases and screened at the selected health facilities from July \u0026ndash; December 2024. The sample size was allocated proportionally based on each Hospital\u0026apos;s average two quarter GeneXpert testing volume (derived from the last 6month surveillance data). The total TB suspects tested in the five Hospitals from July \u0026ndash; December 2024 was 7066; where JJU-SHYCSH ranked first (2009), followed by Karamara General Hospital (1719), Jigjiga Primary hospital (1718), Gode General hospital with 895 TB suspected cases and Siti General Hospital with 725. Sample allocation was done using the following formula.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAARsAAABSCAYAAABkDXAxAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAAFiUAABYlAUlSJPAAAAqFSURBVHhe7d2/b9NMGAfwp+8fgOR2ZUB1BxCgIDAUlQipDKSqWBgg6caaiBGQaOcOyQ5tJQa2psy0tFSiEgkIaEGJAIFEnQEhJocO/AF+h7d373MXO3YgvRjz/UiWXN+FvPHZj++n3yHf930CADhg/+gHAAAOAoINABiBYAMARiDYAIARCDYAYASCDQAYgWADAEYg2ACAEQg2AGAEgg0AGIFgAwBGINgAgBEINgBgBIINABiBYAMARiDYAIARCDYAYASCDQAYgWADAEakNtg0m00aGhqSW6vV0rPAH6BQKMgyLJVKejL8QVIbbD59+iT3Lcui0dFRJR16U6/XleAttuHhYT1rh7Nnz3Z8bmhoiAqFgp61w87OjtzPZDJKWpro50ZszWZTz6qYm5vr+EzccjEttcHm/fv3cv/y5ctKGvQum82S67rkOI5yfG9vj9bW1pRjuvX1dSqXy8qxxcVFqlaryjFdu90m13Xl3+fPn1fS08TzPCoWi/phevTokX5IMT8/T6urq8qxYrFIX758UY4lgp9SjuP4ROQTkV8ul/Vk+EXlclmeV7EVi0U9WwfP82T+XC6nJwdaXV1VviftarVax7m1bVvPFkhc75Zl+Z7n6cmJkNqazfb2Nvm+T77v0507d/Rk6KOoGgoR0bdv3+T+jRs3lLQw09PTsgz/1v+9meu6kU0p2s9H+31cIyMjenIipDbYwMF49+4dERHNzs7KY3GaUj9//pT7586dU9LgPx8/fiQiolwupzRXo5pStF8GREQXL17UkxIDwQZ6IjpsT548SblcTh5//Pgxy9Xp5cuXROis70rUYEZHR+natWvy+MrKCsvVqV6vy/1jx44paUmCYAOx8Q7bw4cP09WrV2VaVFNK1IjQWR9ue3ubiIiOHDmiBPKoppSoEVmWlegRO+PBpt1uU6VSobGxMRoaGqKxsbHAE1mtVuWQ6fDwMJVKJWq323o2SZ9XI7alpSU9ayrp5yvo5q/X68q8lUKhEHjuw7x+/VruZ7NZZXQoqiklakSnT5/WkxT8v8/0MG6z2ZTX5dzcnJ58oNrttjxHExMTlMlkyLIsmd6tKSXKMPHNU73H+CA1Gg3fsqzIHvdisdiRh2KMYnie5+fzeeUztVpNz5YqnucpI298c11X5lteXu5Ipx5HL8RIlOM48pht2/LfChuVcl23p/LQR2Wiyr1f9Gun0WjoWQ4M/82iPPh9oN8jnCiDpI+6GqvZVKtVmpycJNu2yXVd8jxPRm4+l6JUKtHCwgL75P82Nja6zgQeGRmhmzdvKsey2azyd5o0m00aHx8n13WpVquR7/tK9fv79+9E++d+ZmaGffJ/e3t7tLm5qR8O9OzZM6L9SXpCPp+X+0G1KSKiz58/y/04fQrZbFb5HZcuXVLS00j0adm2LUeTrly5ItPDmlK8aXvixAk9OVGMBRvab6+vr6/T6OgojYyMdFT7KpUKLSwsUD6fJ9d1yff9jslg4gYKw4dY9Qlov6NSqXRU7/u1VSoV/etiGxsbo62tLRlU9RuzXq/TzMwMOY4jA1KtVlPyfP36Vfk7zJs3b4i0mbzXr1+X+2FNqRcvXhDtl0fcYdnd3V25b+omunv3Ltm2TbQ/2may/0P0afFrdnp6OrIpxZu24+PjSlri6FUdk0T133EcWY0Mqorzqm1UNZxPOpudndWTf1nQZLZ+bf2s/s7Ozsp/13Vd37Is33GcjqZSLpfr6fsbjYbMr5dBVFNKfFdQWhh+fvT/9jQS3Qt6WUQ1pcR1GZSWNAMNNuIkOo7j27bt5/N5PYvvaxdeVDua30TLy8t6curx35/P533btgNvVp5vcXFRT+7A+3x0PMBZlqUn9/Q9vtZ/8SfcRL+rW5+WPotav/5FOYbdO0litBnF8fbnzs4O/fjxg+7du6fkCRJVtRVVfYrZP5A2/PevrKzQw4cPI5sux48f1w91EGvNgpqm3ZpSvJzjrm0SQ7kU8n1p061PK6opJcp7cnJSOZ5EAws2r169Uv6+f/9+4E3BL1beaRik2WzKmZQUIzCljf77i8ViaAc5D0phebinT58ShcyTyWQysq+DtAl+vJzjlsfW1pbcjxoqjyNsxXo/tqmpKf3rehbVp8VXx/MJfry84zwwBm1gwYYHEdu2Q183wC9WvfNTx18rERWY0oj/fiKiW7duKX8L/CKNe574zOEgYaNSopzjfg9pr5WYmJhQ0tLo7du3RNooHxc2KsXLO84DY9AGFmzEbEkiotu3bytpHH/KRY1KPH/+XO5HBaY04q/VyOfzocsCeAA/c+aMkhaET4fXRxAFvSklbggxVSFuebRaLWUqRD9uomw2qyzo7Oe2vr6uf13PNjY2iLqsa9KbUqL8xChiL4F8kAYSbPhsSYpoy4vqO8UY2uMBLCowpRE/V93a8DyAX7hwQUkLEmddk96UEn0L4kaKWx68/+Jv6K+Ju66J1/wfPHhAxOY9xXlgJMFAgo3+Fr2wtjyv7oe1ZzkewI4ePaqk/a6kzrPhDiKAE5sDElarEXhTamVlRWkqxy2PDx8+yP2wZkWa8M7wsPuAtKbUzs4OtVot2e8W1rRNmoEEG/GkpIgLmFf3gzomOf6EsG079AmcVvz3U5cLt9cATiyIRTWFeFPKdV1Zfr2Uh3haU5dmxUFpDmBtVNw+Lb0ptbm5Kcux2z2UKPpYuAlxJ5TxtSpRc2b4pDtTa2mSJO7vX1xclPniTLLrNgckCJ/gJyaq9TIHRHw27vf10yDWRvWyrolP8BPnNmheU1INpGbDh127jTbwZkG39qwu6gmcRqKpQxG/nzdtwmo/XLc5IEF4U0o8eX91+LofncNJ1uu6Jt6U+uNqNYNoRrVaLWUuSLcLmI9K8BujWq12/G89ePWbazabNDU11fX1FGnAA3O3C5cvZOVzM8LOk5gDQvsLXaPwppTQ7YHC6U1BrlQqhS707BfTa6P4uqZDhw4paUH0phRFPFiSxniw4bUavsI1ytraGrXbbSqVSoErmHmPvHjKi5Xm7XZbWaCZNvpwcdzO2CdPnhAR0dLSEp06daoj0FCMt8Tp9FEp6qGGoj94ms0mtVotKhQKtLCwEHvB6K/KZDK0u7tLvu/T/Py8ntx3UW83DKLPR4sbyBNBb1cdNL6OJqrPQG9Diy1ojY3+DhSx5XK5wLVBacLXz0StJeJ9NnwrFovKefI8r+O9QkHnPQgvY/7umzh4f57YLMuK7LP70+jloJ//MPpaqTifSQrjwaaXBYCe58n8lmX5+Xy+a6dduVyWHWeO46TuAg3DO4fjdMbyYJDL5fzV1VU9i9LRq98UUfgK8Tj5uUajoZR5sVhUXgKWBnoQF1vUg0IQ13jc/Ekx5P83AgAAcKCM99kAwN8JwQYAjECwAQAjEGwAwAgEGwAwAsEGAIxAsAEAIxBsAMAIBBsAMALBBgCMQLABACMQbADACAQbADACwQYAjECwAQAjEGwAwAgEGwAwAsEGAIxAsAEAIxBsAMAIBBsAMALBBgCMQLABACMQbADACAQbADACwQYAjECwAQAjEGwAwAgEGwAwAsEGAIxAsAEAIxBsAMAIBBsAMALBBgCM+Bc2fd6bj/LbrwAAAABJRU5ErkJggg==\" width=\"283\" height=\"82\"\u003e\u003c/p\u003e\n\u003cp\u003eA systematic random sampling approach was implemented where every k\u003csup\u003eth\u003c/sup\u003e patient\u0026rsquo;s card/register meeting the inclusion criteria was enrolled. The sampling interval (k) was calculated in real-time based on the available data to achieve the predetermined sample size for each Hospital.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection methods and laboratory procedures\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTB presumptive cases in all age groups with compete clinic information was included. Socio-demographic information such as age, sex, occupation, monthly income and educational status and other clinical- related factors (such as history of previous anti-TB, having contact with known TB case, comorbidities, HIV status, nutritional status etc.) was collected using pre-structured questionnaires/data extraction checklist prepared for this study \u003cstrong\u003e(Supplementary file).\u003c/strong\u003e Data collectors were trained on the proper card review and data extraction. Principal ad co-investigators fully took part the data collection and maintaining data accuracy. When RR-TB cases are identified, investigators tracked the patient linkage and followed patients\u0026rsquo; cards in the selected MDR centers by looking at MDR status.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy variables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDependent variable\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eMagnitude of TB\u003c/li\u003e\n \u003cli\u003eRifampicin.\u003c/li\u003e\n \u003cli\u003eMulti-drug resistance\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eIndependent variables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eAge, sex, residence, sites of presumptive TB, HIV infection, History of TB contact, History of anti-TB, Diabetic mellitus comorbidity etc.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eMethods of Data analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe laboratory analysis results and other data were registered on pre-structured data extraction checklist. The data were entered into Epi-data version 4.6, be exported to and analyzed in Statistical Package for Social Sciences (SPSS) version 25. Data were analyzed for normality and descriptive statistics were presented as a number and percentage (%) for categorical variables and mean \u0026plusmn; standard deviation (SD) or median (interquartile range [IQR]) for continuous variables by using SPSS version 25. \u0026nbsp;Bi-variable and multi-variable logistic regression analysis was performed to measure the association between outcome variable and independent variables based on Odds-ratio and level of statistical significance at P-value \u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical consideration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical clearance was obtained from Somali Regional Health Bureau, Ethical Review Board. \u0026nbsp;Official support letter was written to study sites. \u0026nbsp;Any information about the data was kept confidential and result was only communicated to an authorized concerned body.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOperational definitions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003ePresumptive TB: person who presents with symptoms or signs suggestive of TB(16).\u003c/li\u003e\n \u003cli\u003ePreviously treated:\u0026nbsp;People who have previously received 1 month or more of TB medicines(16).\u003c/li\u003e\n \u003cli\u003eRR-TB: resistance to rifampicin detected using phenotypic or genotypic methods, with or without resistance to other anti-TB drugs(17)\u003c/li\u003e\n \u003cli\u003eMDR-TB: resistance to at least both isoniazid and rifampicin(17)\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eSocio-demographic characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe\u0026nbsp;study\u0026nbsp;enrolled 460 patients making 100% response rate. Of these, majority of them, 59.1 %(272/460) were male.\u0026nbsp;The mean age was\u0026nbsp;33.45\u0026nbsp;years\u0026nbsp;with\u0026nbsp;a\u0026nbsp;standard\u0026nbsp;deviation of\u0026plusmn;18.09 years. Regarding age distribution, the largest proportion of\u0026nbsp;participants aged 16\u0026ndash;30 years, accounting for 40.9% followed by\u0026nbsp;31\u0026ndash;50 years (28.7%). Most of the patients, (72.8%)(335/460) were from urban areas(\u003cstrong\u003e\u003cem\u003eTable 1\u003c/em\u003e\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e socio-demographic features for magnitude of Tuberculosis, its associated risk factors, Rifampicin resistance, and multi-drug resistance rate among TB presumptive patients at Somali Region, Eastern Ethiopia\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"679\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency(n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e59.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e40.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAge Categories\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003e\u0026le;15 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e14.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003e16-30 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e40.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003e31-50 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e28.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003e\u0026gt;50 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e16.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eResidence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e72.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e27.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eClinical characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study showed that majority (85%) of participants was presumptive TB cases. Regarding treatment history, most (89.1%), of the patients was treatment na\u0026iuml;ve. With respect to TB contact history, about 53.5% of participants reported having contact with a TB case. The majority of TB cases were pulmonary (78.5%). Based on patient group classification, 90.4% were new cases, followed by relapse cases (5.4%). Regarding HIV status, 2.2 %(10/460) of patients were HIV-positive.\u0026nbsp;In\u0026nbsp;terms\u0026nbsp;of\u0026nbsp;diabetes\u0026nbsp;status,\u0026nbsp;17.6%\u0026nbsp;were\u0026nbsp;diabetic (\u003cstrong\u003e\u003cem\u003eTable 2\u003c/em\u003e\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Clinical characteristics for magnitude of Tuberculosis, its associated risk factors, Rifampicin resistance, and multi-drug resistance rate among TB presumptive patients at Somali Region, Eastern Ethiopia\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency(n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eReason\u0026nbsp;for Diagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003ePresumptive TB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e391\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003ePresumptive\u0026nbsp;DR- TB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp; 69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp;15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eTreatment History\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eNew cases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e410\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e89.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003ePreviously treated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eTB Contact History\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e53.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e46.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003ePatient Registration group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eNew\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e416\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e90.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eFailure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eRelapse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eDefault\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eHIV co-infection\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e58.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eDM status\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eDiabetic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e17.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eNon-diabetic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e378\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e82.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eType of TB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003ePulmonary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e361\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e78.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eExtra-pulmonary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e21.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eMagnitude of Tuberculosis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe overall magnitude of Tuberculosis among Tuberculosis presumptive patients was 20.2%(95%CI:16- 23%) (93/460)(\u003cstrong\u003e\u003cem\u003eFigure 1\u003c/em\u003e\u003c/strong\u003e). The magnitude of TB was higher among male patients (24.3%), patients aged between 16 \u0026ndash; 30 years(27.1%) and patients with history of TB contact(24.4%)(\u003cstrong\u003e\u003cem\u003eTable 1\u003c/em\u003e\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDrug resistance pattern\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong the Tuberculosis confirmed patients, 10.8% (95%CI: 7.9 \u0026ndash; 13.6%), (10/93), were resistant to any first line anti-TB drugs. Among TB confirmed patients, 10.8%(95%CI: 7.9 \u0026ndash; 13.6%), \u0026nbsp;were resistant to Rifampicin while 4.3%(95%CI: 2.4 \u0026ndash; 5.2%) were found to be Multi-drug resistant (\u003cstrong\u003e\u003cem\u003eFigure 2\u003c/em\u003e\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDrug resistance regarding TB treatment History.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe prevalence of any drug resistance (either RR or MDR or both) was higher among previously treated TB patients; 12%(6/50). Among anti-TB na\u0026iuml;ve patients, drug resistance level was 1%(4/410)(\u003cstrong\u003e\u003cem\u003eTable 3\u003c/em\u003e\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e3\u003c/strong\u003e: Drug resistance difference regarding TB treatment history for magnitude of Tuberculosis, its associated risk factors, Rifampicin resistance, and multi-drug resistance rate among TB presumptive patients at Somali Region, Eastern Ethiopia\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 282px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrug resistance pattern(any)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResistant, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSusceptible, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eTB treatment History\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eNa\u0026iuml;ve\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e4(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e406(99)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003ePreviously treated\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e6(12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e44(88)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eBivariate and multivariable regression for associated factors.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBivariate regression\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn bivariate regression analysis, sex, TB contact history, age of the patients, and HIV co-infection were candidates for multivariable regression analysis at p-value \u0026lt;0.25(\u003cstrong\u003e\u003cem\u003eTable 4\u003c/em\u003e\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Bivariate regression for magnitude of Tuberculosis, its associated risk factors, Rifampicin resistance, and multi-drug resistance rate among TB presumptive patients at Somali Region, Eastern Ethiopia\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"648\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTuberculosis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAOR\u0026nbsp;(95%\u0026nbsp;CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-ve\u0026nbsp;N (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e+ve\u0026nbsp;N (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eSex\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e206(75.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e66(24.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e1.9(1.2 \u0026ndash; 3.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e161(85.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e27(14.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eAge(in years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026le;15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e55(84.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e10(15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e1.06(0.42 \u0026ndash; 2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e16 -30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e137(72.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e51(27.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e2.2(1.06 \u0026ndash; 4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.03\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e31 \u0026ndash; 50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e111(84.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e21(15.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e1.1(0.5 \u0026ndash; 2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eAbove 50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e64(85.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e11(14.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eResidence\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eUrban\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e264(78.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e71(21.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e1.3(0.7 \u0026ndash; 2.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e103(82.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e22(17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eTB treatment history\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eNew\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e331(79.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e84(20.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e1.01(0.48 \u0026ndash; 2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003ePreviously treated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e36(80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e9(20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eTB contact history\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eYes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e186(75.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e60(24.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e1.5(0.97 \u0026ndash; 2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eNo\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e181(84.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e33(15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eHIV co-infection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003ePositive\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e6(60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e4(40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e2.97(0.8 \u0026ndash; 11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e214(79.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e56(20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e1.2(0.7 \u0026ndash; 1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e147(81.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e33(18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eRef\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eDiabetic Mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eYes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e66(81.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e15(18.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e0.88(0.47 \u0026ndash; 1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eNo\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e300(79.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e78(20.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eRef\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eType of TB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003ePulmonary\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e290(80.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e71(19.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e0.86(0.5 \u0026ndash; 1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eExtra-pulmonary\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e77(77.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e22(22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eAbbreviation\u003c/em\u003e: -ve: negative, +ve: positive, COR: Crude Odds Ratio, CI: Confidence Interval, N: Number\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMultivariable Logistic regression\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn multivariable regression analysis, patients\u0026rsquo; sex and having history of TB contact were found statistically associated with Tuberculosis. Male patients were 1.89 times more likely to develop Tuberculosis compared to female patients; AOR (95%CI): 1.89(1.1 \u0026ndash; 3.14, p=0.012). In addition, patients with history of contact with TB case were 1.8 times more likely to have infected with Tuberculosis compared with their counterparts; AOR (95%CI):1.8(1.1 \u0026ndash; 2.9, p=0.02)(\u003cstrong\u003e\u003cem\u003eTable 5\u003c/em\u003e\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e5\u003c/strong\u003e: Multivariable regression for magnitude of Tuberculosis, its associated risk factors, Rifampicin resistance, and multi-drug resistance rate among TB presumptive patients at Somali Region, Eastern Ethiopia\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"648\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTuberculosis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAOR\u0026nbsp;(95%\u0026nbsp;CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-ve\u0026nbsp;N (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e+ve\u0026nbsp;N (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eSex\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e206(75.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e66(24.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e1.89(1.1 \u0026ndash; 3.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.012\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e161(85.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e27(14.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eAge(in years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026le;15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e55(84.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e10(15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e1.06(0.4 \u0026ndash; 2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e16 -30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e137(72.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e51(27.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e2.0(0.98 \u0026ndash; 4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e31 \u0026ndash; 50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e111(84.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e21(15.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e1.02(0.5 \u0026ndash; 2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eAbove 50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e64(85.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e11(14.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eTB contact history\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eYes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e186(75.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e60(24.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e1.8(1.1 \u0026ndash; 2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eNo\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e181(84.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e33(15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eHIV co-infection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003ePositive\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e6(60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e4(40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e2.5(0.6 \u0026ndash; 10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e214(79.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e56(20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e1.1(0.7 \u0026ndash; 1.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e147(81.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e33(18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eRef\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eAbbreviation\u003c/em\u003e: -ve: negative, +ve: positive, AOR: Adjusted Odds Ratio, CI: Confidence Interval, N: Number\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTB is public health threat leading to greater mortality and morbidity, especially; developing world. And emergency of drug resistance to the first and 2\u003csup\u003end\u003c/sup\u003e line anti-TB drugs is posing public health crisis diminishing prevention and control approaches against TB. Producing local epidemiological data on the TB burden, predisposing factors and drug resistance rate would be essential in prevention, control and intervention approaches against the disease(5).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the present study, the overall magnitude of Tuberculosis among Tuberculosis presumptive patients was 20.2 %( 95%CI: 16- 23%). This finding was is in agreement with studies conducted in Debre Markos (23.2%)(18), Gambella (20%)(19), Dessie (23.4%)(20), Gambo Hospital (22.4%)(21), Yirgalem Hospital (16.5%)(22), Ethiopia, South Asian General Hospital(21.3%)(23), Western Oromia (21.3%)(24), Nigeria (23%)(25), Northeastern Nigeria (19.1%)(26), and southwest Nigeria (18.8%)(27). However, this finding was higher than studies done in St. Peter TB specialized Hospital, Addis-Ababa (13.5%), Amhara Region(11%)(28), selected public Hospitals in Addis Ababa (15.11%)(29), Uganda (14%)(30), South Africa (13%)(31), Hiwot Fana Hospital (15.7%)(32), Metehara (14.2%)(33), Motta (8.4%)(34), northwest Ethiopia, Nepal (13.8%)(35), Zimbabwe (11%)(36). This difference would be due to difference in laboratory diagnostic methods, study population inclusion, sample size, geographical locations and living style.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn other way, the current study finding was lower than studies carried out in East Gojjam (32.2%)(37), Tigray (37%)(38), Ethiopia, Congo (79.1%)(39), Togo (57%)(40). The disagreement could be due to differences in diagnostic modalities, study participants, sample size, geographical, and TB control practices(5).\u003c/p\u003e\n\u003cp\u003eIn the current study,\u0026nbsp;the magnitude of TB was higher among male patients (24.3%) compared to their counterparts. This finding was consistent with study conducted in Debre Markos indicating higher TB incidence among males (27.9%) compared to females and studies done in Addis Ababa(41), Southern Ethiopia(42), Gondar(43), Nigeria(11) and Malaysia(44). In addition, this finding was supported by WHO 2025 report where 10.8 million TB victims, 6 million of them were men(45) and Ethiopian TB national guideline, 2021, reporting that Males account for 56% of the notified TB cases(2). Although, TB affects all sex, but high burden is seen in men. This could be due to men are commonly exposed to variety of risk behavior such as having contact with variety of people, access to prisons, smoking cigarrete and other outreach activities(46).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;In addition, in the current study, the TB prevalence was higher in patients aged between 16 \u0026ndash; 30 years (27.1%) compared to their counterpart indicating circulation of TB infection in the community. This finding was supported by studies conducted in Yirgalem Hospital, Ethiopia(22), Refugee camps, Ethiopia(47).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the current study, male sex was found to be significantly associated with Tuberculosis (1.89 times more likely to develop Tuberculosis compared to female patients). This is in line with studies conducted in selected refugee camps, Ethiopia(47), Addis Ababa(48), India(49), Nigeria(11), Thailand(50) Uganda(10) and Hong Kong(51). In addition to this, this finding was supported by study carried out in Nigeria reporting that female sex were less likely to have TB compared to male(52).\u003c/p\u003e\n\u003cp\u003eIn addition, in the present study, history of contact with TB case was statistically associated with the magnitude of TB (1.8 times more likely to have infected with TB). This finding is consistent with studies done in St. Paul\u0026rsquo;s Hospital, Addis Ababa(53), north Wollo(9), Debre Markos(54), Gedo Zone, Ethiopia(55) Oromia region(56) South Africa(57), Uganda(10), Nigeria(58) and India(59).\u003c/p\u003e\n\u003cp\u003eIn the present study, the overall drug resistance rate was 10.8% (95%CI: 7.9 \u0026ndash; 13.6%). Level of RR \u0026ndash; rate was 10.8% (95%CI: 7.9 \u0026ndash; 13.6%). This finding was supported by studies conducted in Debre-Markos (10.3%)(18), India (10.5%)(60), Addis Ababa (9.8%)(41), Thailand (11%)(50), Nigeria (13.5%)(61), Addis-Ababa (9.9%)(29) and Kenya (9.9%)(62). However, it was lower than studies carried out in Addis-Ababa(39.4%)(63), Gondar(15.8%)(43), and Lagos, Nigeria (23.4%)(7). On the other hand, the current finding was higher than reports of studies conducted in Gambella (4.9%)(19), Dubti, Afar region (4.3%)(64),\u0026nbsp;in Eastern Ethiopia (1.7%)(65), East Gojjam (2.59%)(37)\u003cu\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/u\u003eand in Nigeria (6.9%)(66). This discrepancies might be due to difference in patient selection, TB case management, diagnosis, geographical locations, and treatment compliance(29). In the current study, drug resistance rate (either RR or MDR or both) was higher among previously treated TB patients compared to treatment na\u0026iuml;ve (12% vs 1%). This finding is in line with studies conducted in East Gojam, Ethiopia(37), Addis-Ababa(29), Uttar pradesh(67) and Nairobi Kenya(68). This finding was also supported by Ethiopian TB/HIV guideline 2021 indicating that prevalence of RR-TB is 1.1% among new and 7.5% among previously treated TB cases(2)\u003c/p\u003e\n\u003cp\u003eIn the present study, the prevalence of MDR was 4.3 %( 95%CI: 2.4 \u0026ndash; 5.2%). This finding was supported by studies conducted in East Gojjam, Northwest Ethiopia(3.37%)(37), Dire-dawa(5.1%)(69), Addis Ababa(5.3%)(70) China (5.6%)(71), Germany (4%)(72). However, it was lower than studies done in Amhara Region (15.3%)(73), Addis Ababa (11.54%)(74), St. Peter TB specialized Hospital, Addis Ababa(46.3%)(75) and Iran (12.2%)(76). The disagreement could be due to difference in study population and diagnostic modalities used, for instance these studies deploy MDR-Presumptive TB patients while the current study included all presumptive TB and MDR-presumptive patients and presumptive TB cases dominated.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion and Recommendation","content":"\u003cp\u003eThe magnitude of TB was 20.2% indicating higher TB incidence in the region. It was higher among male. The overall drug resistance rate was 10.8%; of this, RR and MDR rates were 10.8%, and 4.3% respectively. Drug resistance was higher among previously treated patients. Male sex and having history of TB contact were statistically associated with TB. Early laboratory diagnosis using WHO recommended rapid molecular tests, Improving and monitoring of early Treatment initiation, scaling up of TB specimen referral linkage to where rapid molecular diagnostics tests are accessible are recommended to limit the spread of the disease and an emergency of Drug resistance.\u0026nbsp;\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"655\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eAOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 488px;\"\u003e\n \u003cp\u003eAdjusted Odds Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 488px;\"\u003e\n \u003cp\u003eConfidence interval\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eCOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 488px;\"\u003e\n \u003cp\u003eCrude Odds Ratio\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eHIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 488px;\"\u003e\n \u003cp\u003eHuman Immuno-deficiency Virus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eINH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 488px;\"\u003e\n \u003cp\u003eIsoniazid\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eIQR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 488px;\"\u003e\n \u003cp\u003eInter-Quartile Range\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eJJU-SHYCSH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 488px;\"\u003e\n \u003cp\u003eJigjiga University Sheik Hassan Yabare Comprehensive Specialized Hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eMDR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 488px;\"\u003e\n \u003cp\u003eMulti-Drug Resistance\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eMTB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 488px;\"\u003e\n \u003cp\u003e\u003cem\u003eMycobacterium Tuberculosis\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eRR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 488px;\"\u003e\n \u003cp\u003eRifampicin resistance\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 488px;\"\u003e\n \u003cp\u003eStandard Deviation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eSPSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 488px;\"\u003e\n \u003cp\u003eStatistical Package for Social Science\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eTB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 488px;\"\u003e\n \u003cp\u003eTuberculosis\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eWHO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 488px;\"\u003e\n \u003cp\u003eWorld Health Organization\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval and consent\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical clearance was obtained from Institutional Health Research Ethics Review Committee (IHRERC), Somali Regional Health Bureau. Official support letter was written to the selected Hospitals (the study area). Informed voluntary written and signed consent was obtained from the chief executive officers of the study Hospitals, and signed consent and assent could not obtained from the patients since the study was retrospective and only patients\u0026rsquo; cards and registers were used. Any information about the data was kept confidential. The study also adhered to the Declaration of Helsinki.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are available and can be received from the corresponding author upon request\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors declare no competing interest\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by Somali Regional Health Bureau\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBT, AO, KF, HM contributed in designing the study, conducted data collection, analyzed the data and drafted the paper. BT, AO, NT, KF, HM played a great role in the conception of the study, analysis and interpretation of the data and revised subsequent drafts of the paper. BT, KF, NT conducted data analysis, drafted and finalized the manuscript for publication. All authors read and approved the final manuscript for submission.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirst, our heartfelt gratitude goes to Somali Regional Health Bureau, Regional Public Health Laboratory and Research Center Directorate for funding. Second, we are indebted to the selected Hospitals\u0026rsquo; administration and staffs for their support. \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWHO WHO. Tuberculosis 2025 [Available from: https://www.who.int/news-room/fact-sheets/detail/tuberculosis \u003c/li\u003e\n\u003cli\u003eFederal Ministry of Health E. 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Smear positive pulmonary tuberculosis among suspected patients attending metehara sugar factory hospital; eastern Ethiopia. African health sciences. 2012;12(3):325-30.\u003c/li\u003e\n\u003cli\u003eDemissie TA, Belayneh D. Magnitude of Mycobacterium tuberculosis infection and its resistance to rifampicin using Xpert-MTB/RIF assay among presumptive tuberculosis patients at Motta General Hospital, Northwest Ethiopia. Infection and Drug Resistance. 2021:1335-41.\u003c/li\u003e\n\u003cli\u003eSah SK, Bhattarai PR, Shrestha A, Dhami D, Guruwacharya D, Shrestha R. Rifampicin-resistant Mycobacterium tuberculosis by GeneXpert MTB/RIF and associated factors among presumptive pulmonary tuberculosis patients in Nepal. Infection and Drug Resistance. 2020:2911-9.\u003c/li\u003e\n\u003cli\u003eCharambira K, Ade S, Harries A, Ncube R, Zishiri C, Sandy C, et al. Diagnosis and treatment of TB patients with rifampicin resistance detected using Xpert\u0026reg; MTB/RIF in Zimbabwe. 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Detection and factors associated with tuberculosis and rifampicin resistance among presumptive patients at the Thailand-Myanmar border. 2022.\u003c/li\u003e\n\u003cli\u003eLaw W, Yew W, Chiu Leung C, Kam K, Tam C, Chan C, et al. Risk factors for multidrug-resistant tuberculosis in Hong Kong. The international journal of tuberculosis and lung disease. 2008;12(9):1065-70.\u003c/li\u003e\n\u003cli\u003eFamuyiwa MK. Risk factors and prevalence of tuberculosis among presumptive cases of a general hospital in Nigeria. Researchgate; 2018.\u003c/li\u003e\n\u003cli\u003eKassa M, Desta K, Ambachew R, Gebreyohannes Z, Gebreyohanns A, Zena N, et al. Magnitude of Mycobacterium tuberculosis, drug resistance and associated factors among presumptive tuberculosis patients at St. Paul\u0026rsquo;s Hospital Millennium Medical College, Addis Ababa, Ethiopia. Plos one. 2022;17(8):e0272459.\u003c/li\u003e\n\u003cli\u003eLiyew Ayalew M, Birhan Yigzaw W, Tigabu A, Gelaw Tarekegn B. Prevalence, associated risk factors and rifampicin resistance pattern of pulmonary tuberculosis among children at Debre Markos Referral Hospital, Northwest, Ethiopia. Infection and Drug Resistance. 2020:3863-72.\u003c/li\u003e\n\u003cli\u003eDiriba K, Awulachew E. Associated risk factor of tuberculosis infection among adult patients in Gedeo Zone, Southern Ethiopia. SAGE Open Medicine. 2022;10:20503121221086725.\u003c/li\u003e\n\u003cli\u003eMulisa G, Workneh T, Hordofa N, Suaudi M, Abebe G, Jarso G. Multidrug-resistant Mycobacterium tuberculosis and associated risk factors in Oromia Region of Ethiopia. International Journal of Infectious Diseases. 2015;39:57-61.\u003c/li\u003e\n\u003cli\u003eMarais BJ, Obihara CC, Gie RP, Schaaf HS, Hesseling AC, Lombard C, et al. The prevalence of symptoms associated with pulmonary tuberculosis in randomly selected children from a high burden community. 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Drug Resistant Mycobacterium tuberculosis in Benue, Nigeria. 2014.\u003c/li\u003e\n\u003cli\u003eNg\u0026apos;ang\u0026apos;a ZW, Nyang\u0026rsquo;au LO, Amukoye E. Determining first line anti-tuberculosis drug resistance among new and re-treatment tuberculosis/human immunodeficiency virus infected patients, Nairobi Kenya. 2015.\u003c/li\u003e\n\u003cli\u003eMesfin EA, Beyene D, Tesfaye A, Admasu A, Addise D, Amare M, et al. Drug-resistance patterns of Mycobacterium tuberculosis strains and associated risk factors among multi drug-resistant tuberculosis suspected patients from Ethiopia. PloS one. 2018;13(6):e0197737.\u003c/li\u003e\n\u003cli\u003eGebrehiwet GB, Kahsay AG, Welekidan LN, Hagos AK, Abay GK, Hagos DG. Rifampicin resistant tuberculosis in presumptive pulmonary tuberculosis cases in Dubti Hospital, Afar, Ethiopia. The Journal of Infection in Developing Countries. 2019;13(01):21-7.\u003c/li\u003e\n\u003cli\u003eSeyoum B, Demissie M, Worku A, Bekele S, Aseffa A. Prevalence and drug resistance patterns of Mycobacterium tuberculosis among new smear positive pulmonary tuberculosis patients in eastern Ethiopia. Tuberculosis research and treatment. 2014;2014(1):753492.\u003c/li\u003e\n\u003cli\u003eOkonkwo R, Onwunzo M, Chukwuka C, Ele P, Anyabolu A, Onwurah C, et al. The use of the Gene Xpert mycobacterium tuberculosis/Rifampicin (MTB/Rif) assay in detection of multi-drug resistant tuberculosis (MDRTB) in Nnamdi Azikiwe University Teaching Hospital, Nnewi, Nigeria. J HIV Retrovirus. 2017;3:1.\u003c/li\u003e\n\u003cli\u003eGautam PB, Mishra A, Kumar S. Prevalence of rifampicin resistant mycobacterium tuberculosis and associated factors among presumptive tuberculosis patients in eastern Uttar Pradesh: a cross sectional study. Int J Community Med Public Health. 2018;5(6):2271-6.\u003c/li\u003e\n\u003cli\u003eOgaro T, Githui W, Kikuvi G, Okari J, Wangui E, Asiko V. Anti-tuberculosis drug resistance in Nairobi, Kenya. 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Multidrug- and extensively drug-resistant tuberculosis, Germany. Emerging infectious diseases. 2008;14(11):1700-6.\u003c/li\u003e\n\u003cli\u003eNigus DM, Lingerew W, Beyene B, Tamiru A, Lemma M, Melaku MY. Prevalence of multi drug resistant tuberculosis among presumptive multi drug resistant tuberculosis cases in Amhara National Regional State, Ethiopia. J Mycobac Dis. 2014;4(152):2161-1068.1000152.\u003c/li\u003e\n\u003cli\u003eSinshaw W, Kebede A, Bitew A, Tesfaye E, Tadesse M, Mehamed Z, et al. Prevalence of tuberculosis, multidrug resistant tuberculosis and associated risk factors among smear negative presumptive pulmonary tuberculosis patients in Addis Ababa, Ethiopia. BMC infectious diseases. 2019;19:1-15.\u003c/li\u003e\n\u003cli\u003eAbate D, Taye B, Abseno M, Biadgilign S. Epidemiology of anti-tuberculosis drug resistance patterns and trends in tuberculosis referral hospital in Addis Ababa, Ethiopia. BMC Res Notes. 2012;5:462.\u003c/li\u003e\n\u003cli\u003eMetanat M, Sharifi-Mood B, Shahreki S, Dawoudi SH. Prevalence of multidrug-resistant and extensively drug-resistant tuberculosis in patients with pulmonary tuberculosis in zahedan, southeastern iran. Iranian Red Crescent medical journal. 2012;14(1):53-5.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Magnitude, TB, RR-TB, MDR-TB, Associated Risk factors, Somali Region, Ethiopia","lastPublishedDoi":"10.21203/rs.3.rs-6997913/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6997913/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eTuberculosis (TB) is a major public health problem worldwide. In 2022, an estimated 10.6\u0026nbsp;million people fell ill with TB worldwide. Emergency of Rifampicin and multi-Drug resistance (RR/MDR) has posed greater public health threat on control and prevention of TB. Ethiopia is among the top 30 high TB burden countries.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eTo assess the Magnitude of Tuberculosis, its associated risk factors, Rifampicin resistance (RR), and Multi-drug resistance (MDR) rate among TB suspected patients in Somali Region, Eastern Ethiopia, 2025.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eInstitution based retrospective cross-sectional study design was employed from May 10, to June 05, 2025. Total of 460 patient\u0026rsquo;s cards and registration logs from July - December 2024 were recruited. Systematic random sampling technique was employed. Retrospective card review and registers was done. Data were collected using pre-structured checklist. The data were entered into Epi-data version 4.6, exported to and analyzed in SPSS version 25. Bivariate and multi-variable logistic regression analysis was performed to measure the association between dependent and independent variables. P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e\u003cp\u003eThe overall magnitude of TB among TB presumptive patients was 20.2%(95%CI:16\u0026ndash;23%) (93/460). It was higher among male patients (24.3%), patients aged between 16\u0026ndash;30 years (27.1%) and patients with history of TB contact (24.4%). Among the TB confirmed patients, 10.8% (95%CI: 7.9\u0026ndash;13.6%), (10/93), were resistant to any first line anti-TB drugs. Rifampicin resistance rate was 10.8%( 95%CI: 7.9\u0026ndash;13.6%) while MDR rate was 4.3%( 95%CI: 2.4\u0026ndash;5.2%). RR/MDR rate was higher among previously treated TB patients; 12%(6/50). Being male, AOR (95%CI): 1.89(1.1\u0026ndash;3.14, p\u0026thinsp;=\u0026thinsp;0.012), and having history TB contact; AOR (95%CI):1.8(1.1\u0026ndash;2.9, p\u0026thinsp;=\u0026thinsp;0.02), were statistically associated with Tuberculosis\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThe magnitude of TB was 20.2% indicating higher TB incidence in the region. The overall drug resistance rate was 10.8%; of this, RR and MDR rates were 10.8%, and 4.3% respectively. Male sex and having history of TB contact were statistically associated with TB. Early laboratory diagnosis using WHO recommended rapid molecular tests, Improving and monitoring of early Treatment initiation, scaling up of TB specimen referral linkage to where rapid molecular diagnostics tests are accessible are recommended to limit the spread of the disease and an emergency of Drug resistance.\u003c/p\u003e","manuscriptTitle":"Magnitude of Tuberculosis, its associated risk factors, Rifampicin resistance, and multi- drug resistance rate among TB presumptive patients at five selected Public Hospitals, Somali Region, Eastern Ethiopia, 2025. 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