Gebremedhin Berhe Gebregergs

The incidence of tuberculosis (TB) has increased in Tigray, Ethiopia due to war and a crippled healthcare system. Although early detection and treatment are critical for TB control, over 30% of TB cases are missed using current diagnostic techniques. Thus, we developed and validated a risk prediction model for pulmonary TB in presumptive cases. In this multicenter cross-sectional study, we consecutively enrolled 907 respondents from primary healthcare facilities in Tigray, northern Ethiopia. We used least absolute shrinkage and selection operator regression to identify variables for the model. Risk scores were generated from the coefficients of multivariable logistic regression. We evaluated the model performance using the area under the curve and calibration plots, and clinical utility using decision curves. Among all respondents, 155 (17%) had GeneXpert-confirmed pulmonary TB. At an optimal cutoff value of 8.5, the model demonstrated a discrimination accuracy of 0.82 (95% CI: 0.78–0.85), a sensitivity of 82.6%, and a specificity of 68.9%. The model had a calibration slope of 0.98 and an intercept of 0.001. The model exhibits acceptable discrimination and calibration performance. Thus, it can be used for screening patients for pulmonary TB in primary healthcare settings where accurate diagnostic resources are limited.

Tuberculosis (TB) is Ethiopia’s leading infectious killer disease. The war in the Tigray region of Ethiopia has resulted in the disruption of TB care services. Prediction models are recommended to aid the diagnosis of TB in resource-limited settings. However, the development of such decision-support tools without the participation of end users may not be successful. To inform the tool development, we described barriers to diagnosing TB and identified applicable and desirable parameters for the proposed tool. We conducted a qualitative study between February and June 2023 in two cities in Tigray, Northern Ethiopia. We conducted 12 in-depth interviews and four focus group discussions with healthcare workers (HCWs). Interviews were translated, coded, and analyzed to identify predefined and emergent themes during the thematic analysis. Healthcare workers used symptoms, risk factors, signs, and investigations to diagnose TB. However, failure to ask about antibiotic use, the absence and non-affordability of investigations, and patient load were barriers affecting the diagnosis of TB. Most of the classic TB symptoms and their duration were sorted as very important, simple, reliable, generalizable, and desirable indices. In addition, a trial of antibiotics, being chronically sick-looking, having HIV, having a contact history with a TB patient, and an erythrocyte sedimentation rate fulfilled the above criteria. In the TB diagnostic process, HCWs account for a variety of data, but they prefer the classic symptoms of TB to heighten their clinical suspicion. Antibiotic trials and some risk factors were also considered reasonable. However, when HCWs have a heavy workload and a shortage of investigations, they experience a suboptimal TB diagnostic process. Hence, appropriate context consideration and care providers’ preferences for parameters will inform tool development.

Background: The Tigray region of Ethiopia, which has been affected by civil war from 2020 to 2022, is facing an increase in tuberculosis in the damaged health system. Our study employed mathematical modeling to predict the incidence of tuberculosis and its trends during the war and in the post-conflict setting of Tigray, Northern Ethiopia. Methods: We predicted the incidence of tuberculosis from 2020 to 2025 in Tigray using the SEIRD model in the context of the recent war and compared it with its counterfactual trend in the absence of war. The counterfactual trend was forecasted using an autoregressive integrated moving average (ARIMA) model for stationary time-series data. We performed rolling origin cross-validation for ARIMA and sensitivity analysis for the SEIRD model. The initial tuberculosis data and model parameters were obtained from the Institute for Health Metrics and Evaluation and the literature, respectively. Results: Between 2000 and 2017, the incidence of tuberculosis in Tigray decreased at an annual rate of 3.0%. Shortly before the war, the incidence of tuberculosis in the region was 178 per 100,000 people. In a counterfactual scenario where there was no war, the incidence was projected to decrease to 144.3 in 2022 and 126.3 in 2025. However, owing to the war and siege, the SEIRD-projected incidence of tuberculosis would have increased to 965.5 (95% CI: 958.5– 972.7) in 2022 and 372.4 (95% CI: 367.7– 376.6) in 2025. Over 800 cases of tuberculosis per 100,000 people were attributed to the war in 2022. In the postwar period, the incidence is projected to decrease by 30% by 2023. Conclusion: The Tigray War reversed a two-decade decline in tuberculosis cases, causing a five-fold increase compared to the no-war scenario. Urgent interventions are needed to support tuberculosis prevention, testing, and treatment, particularly in key and vulnerable populations.

Background: Although tuberculosis is highly prevalent in low- and middle-income countries, millions of cases remain undetected using current diagnostic methods. To address this problem, researchers have proposed prediction rules. Objective: We analyzed existing prediction rules for the diagnosis of pulmonary tuberculosis and identified factors with a moderate to high strength of association with the disease. Methods: We conducted a comprehensive search of relevant databases (MEDLINE/PubMed, Cochrane Library, Science Direct, Global Health for Reports, and Google Scholar) up to 14 November 2022. Studies that developed diagnostic algorithms for pulmonary tuberculosis in adults from low and middle-income countries were included. Two reviewers performed study screening, data extraction, and quality assessment. The study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2. We performed a narrative synthesis. Results: Of the 26 articles selected, only half included human immune deficiency virus-positive patients. In symptomatic human immune deficiency virus patients, radiographic findings and body mass index were strong predictors of pulmonary tuberculosis, with an odds ratio of >4. However, in human immune deficiency virus-negative individuals, the biomarkers showed a moderate association with the disease. In symptomatic human immune deficiency virus patients, a C-reactive protein level ⩾10 mg/L had a sensitivity and specificity of 93% and 40%, respectively, whereas a trial of antibiotics had a specificity of 86% and a sensitivity of 43%. In smear-negative patients, anti-tuberculosis treatment showed a sensitivity of 52% and a specificity of 63%. Conclusions: The performance of predictors and diagnostic algorithms differs among patient subgroups, such as in human immune deficiency virus-positive patients, radiographic findings, and body mass index were strong predictors of pulmonary tuberculosis. However, in human immune deficiency virus-negative individuals, the biomarkers showed a moderate association with the disease. A few models have reached the World Health Organization’s recommendation. Therefore, more work should be done to strengthen the predictive models for tuberculosis screening in the future, and they should be developed rigorously, considering the heterogeneity of the population in clinical work.

The study aimed to assess willingness to pay for community-based health insurance and its correlates among households in Wukro and Setit-humera towns, Tigray, Northern Ethiopia for the year 2016. A community-based survey was conducted in Wukro and Setit-humera towns of the Tigray region from August 30 to October 05, 2016. A total of 823 households were enrolled using a two-stage sampling. A structured, pre-tested, and interviewer-administered questionnaire was used. Data were entered and analyzed using SPSS version 20. Frequencies, mean, and median were calculated. Bivariate and multiple variable logistic regressions were fitted. Odds Ratio with 95% CI was used to see the associations between selected independent variables and the outcome variable. Willingness to pay for community-based health insurance (CBHI) in the two towns was 93.4% with a 95% CI (91.6-95.0). The median amount of money that households are willingness-to-pay (WTP) was 11.1 USD. The mean amount of money an individual household is willing to pay was significantly higher in Setit-humera than in Wukro town. Participants who knew their monthly income were two times more likely to be willing to pay for CBHI [Adjusted odds ratio (AOR) =2.6, 95% CI; 1.1, 8.1]; and willingness was higher among households who perceived that the cost of care is affordable in health facilities [AOR=2.6, 95% CI; 1.02, 7.1]. The study has shown a high level of willingness to pay for health insurance. Perceived affordability and knowledge of monthly income were significant factors that affect willingness to pay for community-based health insurance. Therefore, it can be operationalized in urban settings provided that the community is aware and sensitized focusing on the benefits of health insurance. Besides, the premium needs to be carefully set to consider the community’s ability to pay.

Background. Rehospitalization, treatment resistance, and impairment are all possible outcomes of a schizophrenia relapse, which has a severe impact on patients, families, and the healthcare system. However, little is known regarding the time to relapse and relapse predictors in Ethiopia and in the study settings. Therefore, the aim of this study was to determine the time to relapse and relapse predictors in patients with schizophrenia at Ayder Comprehensive Specialized Hospital, Northern Ethiopia. Methods. A retrospective cohort study was carried out among 273 schizophrenia patients discharged from Ayder Comprehensive and Specialty Hospital between January 2015 and January 2019. The data was taken from the patient’s medical record and was chosen using a systematic random sampling procedure. A standardized data collection checklist was employed. The survival experiences of participants were compiled using a life table. Both univariate and multivariate Cox regression models were used for variable selection. Finally, after confirming the model’s diagnosis and assumptions, factors with a value of less than 0.05 were declared to be statistically significant predictors of schizophrenia relapse. Results. In this study, the incidence of relapse was 2.9 per 100 person-months (PMs) and the median time to relapse of 13 months (interquartile range: 6–23 months). Being divorced ( , 95% CI: 1.18-5.28), not adhering to treatment ( , 95% CI: 3.03-10.74), and substance abuse ( , 95% CI: 1.01-3.22) were risk factors for increasing schizophrenia relapse. Age ( , 95% CI: 0.34-0.88) and length of first hospitalization ( , 95% CI: 0.57-0.86) were factors that decreased schizophrenia relapse. Conclusion and Recommendation. In this study, out of 100 patients with schizophrenia followed up for a month, three had a relapse, and the highest risk factor for relapse was treatment nonadherence, followed by being divorced and substance misuse. As a result, it is advised that all parties involved focus on early detection and taking preventive measures against schizophrenia relapse, as well as providing regular psychoeducation about the significance of treatment adherence and connecting patients with substance misuse to substance rehabilitation centers.

Background: In Ethiopia, specimens of presumptive drug resistant tuberculosis cases are transported by courier system from district sample collection centers to reference laboratories. It is essential to track the effectiveness of the referral system and identify challenges in order to take timely and appropriate actions. We assessed turnaround time and quality of speci- mens, and explored challenges of the specimen referral system in Amhara region, Ethiopia, 2017. Methods: With mixed methods, we retrospectively examined 385 randomly selected presumptive drug resistance TB speci- mens, and interviewed 53 purposively selected key informants from laboratories and post offices. We calculated median TAT and proportion of acceptable quality. We analyzed qualitative data thematically. Results: Of the 385 specimens, 94.5% (364/385) had acceptable quality at arrival in the reference laboratories. All the 364 specimens had result. Three - fourth (76.1%) of results were dispatched to the referring health facilities within the recom- mended turnaround time. Ineffective communication and lack of feedback among institutions were mentioned as challenges. Conclusion: The postal service was effective in keeping quality and majority of test results were timely delivered. Yet, there were operational challenges. Therefore, effective communication, using dedicated vehicle for specimen shipment and aware- ness creation on specimen collection and handling are recommended. Keywords: Postal service; specimen referral; turnaround time; drug resistance tuberculosis.

Determinants of delay in seeking treatment among malaria patients in Dera district, NorthWest Ethiopia: a case control study

The antibiotic treatment of people with trachoma helps to prevent transmission the disease in a community. Currently, Zithromax is the drug recommended for mass drug administration (MDA). MDA should be carried out annually for three to five years in trachoma endemic areas. Coverage survey is essential to track progress towards program goals and to identify communities with poor coverage in order to permit timely and appropriate actions. We assessed mass Zithromax administration coverage, social mobilization and campaign challenges in south and southeast zones of Tigray, Ethiopia. We conducted a survey in community in Southern and South East zones of Tigray region from August 15 to August 31, 2016. The survey included nine Woredas. It was supported by qualitative methods. A total of 3741 individuals were enrolled from 933 households using multistage sampling. We used structured questionnaire. In-depth interview and focus group discussion were also applied. Descriptive statistics was performed using SPSS version 20.We thematically analyzed the qualitative data using Atlas 7. The overall coverage of Zithromax MDA was 93.3%. It ranges from 90.0% in Seharti Samre to 97.9% in Endamokoni. The coverage was 93.4% for males and 93.1% for females. A higher proportion (98.3%) of children aged 5 to 15 years and 409 (87.8%) under five children took Zithromax. The coverage was 94% in rural and 91.2% in urban. Women development army (43.3%) and health extension workers (32.5%) were the main source of information. Frequent occurrence of drug side effects, rumors, lack of community and leaders’ engagement in the campaign, fasting, shortage of human power and short term unavailability of supplies were barriers during the campaign. The Zithromax MDA coverage in the study zones was higher than the minimum WHO set criteria of 80%. There was a wide difference in coverage among Woredas and Kebeles. The MDA coverage was lower in urban than rural. Misconceptions and poor mobilization were common challenges. Thus, proper planning, community mobilization and uniform training will need to be done ahead of the campaign in the future. Ethiopia has the world's highest burden of trachoma. The disease causes significant blindness and visual impairment, particularly in poorer communities. To prevent the transmission of active trachoma, mass administration of Zithromax is given every year, which is implemented for consecutive three to five years in endemic and hyper endemic areas of the country. We have shown that the mass administration coverage of Zithromax, in 2016, was greater than 90% in the South and Southeastern zones of Tigray, Ethiopia. However, it was accompanied by a number of program challenges and social barriers.Women development armies and health extension workers were key players in community mobilization and drug provision, respectively.

Factors associated with institutional delivery in Dangila district, North West Ethiopia: a cross-sectional study