Background: Female sex workers (FSWs) are marginalized groups of the population who have limited access to healthcare and a higher risk of HIV infection due to biobehavioral and structural risk factors. Although it is known that the Eastern and Southern African region is affected by the highest HIV incidence and prevalence, understanding the burden among FSWs in the region remains limited. We aimed to assess the pooled prevalence and associated factors of HIV in this vulnerable population. Methods: Relevant studies were searched on PubMed, Embase, Scopus, ScienceDirect, Hinari, African Journals Online (AJOL), Google, and Google Scholar. The searching mechanism was constructed using keywords identified by CoCoPop (Condition, Context, and Population) framework and medical subject heading terms to recruit studies published between January 1, 2015 and March 30, 2024. Observational studies that estimate the prevalence or incidence or associated factors of HIV among FSWs, even if FSWs were not the main focus of the study, were included. The quality of included studies was assessed using Joana Brigg’s Institute checklist. Data were extracted and analyzed using STATA 17 software. To estimate the pooled effect sizes with their 95% confidence intervals, a random effect model was fitted. The I² statistic was used to evaluate heterogeneity. Funnel plot and Egger’s regression test were utilized to assess the small study effect. Publication bias was managed using trim-and-fill analysis. Subgroup and sensitivity analysis were considered to handle heterogeneity among studies. Results: A total of 54 articles with 78,747 FSWs who had successful HIV biological test were included in the analysis. The pooled prevalence of HIV among FSWs in Eastern and Southern Africa was 36.0% (95% CI: 31.0%–41.0%). Regionally, the pooled prevalence was 59.0% (95% CI: 53.0%–64.0%) and 29.0% (95% CI: 25.0%–34.0%) in Southern and Eastern Africa, respectively. Age above 35 (POR = 7.35; 95% CI: 5.26, 10.28) and 25–34 years (POR = 2.91; 95% CI: 2.02, 4.21), being married (POR = 1.33; 95% CI: 1.07, 1.66), divorced (POR = 1.72; 95% CI: 1.39, 2.13), and widowed (POR = 2.70; 95% CI: 2.09, 3.49), primary education (POR = 1.29; 95% CI:1.08, 1.55), history of sexually transmitted infection (POR = 1.51; 95% CI: 1.20, 1.90), syphilis (POR = 2.57; 95% CI: 1.66, 3.98), Hepatitis B infection (POR = 2.60; 95% CI: 1.07,6.32), drinking alcohol (POR = 1.21; 95% CI: 1.01, 1.45) and injectable drug use before sex (POR = 1.75; 95% CI: 1.24, 2.47) were found significantly associated with the increased risk of HIV infection among FSWs. Conclusion: These data suggest an urgent need to improve access to HIV prevention programs for FSWs. Providing behavioral interventions including reduction of alcohol and injectable drug use before sex, initiating tailored healthcare services, strengthening the psychosocial and legal support network, and fostering partnership might reduce the burden in the region. Clinicians could facilitate early detection and treatment of STIs, and Hepatitis B virus infection. Trial registration: Protocol registration: The protocol for this systematic review and meta-analysis was registered in the PROSPERO with registration number CRD42024509200.

Introduction: Hepatitis B virus (HBV) is one of the major public health problems globally and needs an urgent response. It is one of the most responsible causes of mortality among the five hepatitis viruses, and it affects almost every class of individuals. Different studies were conducted on the prevalence of HBV among pregnant women in East African countries, but none of them showed the pooled prevalence of HBV among the pregnant women. Thus, the main objective of this study was to determine the pooled prevalence and its determinants among pregnant women in East Africa. Methods: We searched studies using PubMed, Scopus, Embase, ScienceDirect, Google Scholar and grey literature that were published between January 01/2020 to January 30/2024. The studies were assessed using the Newcastle Ottawa Scale (NOS) quality assessment scale. The random-effect (DerSimonian) model was used to determine the pooled prevalence and associated factors of HBV among pregnant women. Heterogeneity were assessed by I² statistic, sub-group analysis, and sensitivity analysis. Publication bias was assessed by Egger test, and the analysis was done using STATA version 17. Result: A total of 45 studies with 35639 pregnant women were included in this systematic review and meta-analysis. The overall pooled prevalence of HBV among pregnant women in East Africa was 6.0% (95% CI: 6.0%−7.0%, I² = 89.7%). The highest prevalence of 8% ((95% CI: 6%, 10%), I² = 91.08%) was seen in 2021, and the lowest prevalence 5% ((95% CI: 4%, 6%) I² = 52.52%) was observed in 2022. A pooled meta-analysis showed that history of surgical procedure (OR = 2.14 (95% CI: 1.27, 3.61)), having multiple sexual partners (OR = 3.87 (95% CI: 2.52, 5.95), history of body tattooing (OR = 2.55 (95% CI: 1.62, 4.01)), history of tooth extraction (OR = 2.09 (95% CI: 1.29, 3.39)), abortion history(OR = 2.20(95% CI: 1.38, 3.50)), history of sharing sharp material (OR = 1.88 (95% CI: 1.07, 3.31)), blood transfusion (OR = 2.41 (95% CI: 1.62, 3.57)), family history of HBV (OR = 4.87 (95% CI: 2.95, 8.05)) and history needle injury (OR = 2.62 (95% CI: 1.20, 5.72)) were significant risk factors associated with HBV infection among pregnant women. Conclusions: The pooled prevalence of HBV infection among pregnant women in East Africa was an intermediate level and different across countries ranging from 1.5% to 22.2%. The result of this pooled prevalence was an indication of the need for screening, prevention, and control of HBV infection among pregnant women in the region. Therefore, early identification of risk factors, awareness creation on the mode of transmission HBV and implementation of preventive measures are essential in reducing the burden of HBV infection among pregnant women.

Background: Acute respiratory infections (ARIs) are the leading cause of death in children under the age of 5 globally. Maternal healthcare-seeking behavior may help minimize mortality associated with ARIs since they make decisions about the kind and frequency of healthcare services for their children. Therefore, this study aimed to predict the absence of maternal healthcare-seeking behavior and identify its associated factors among children under the age 5 in sub-Saharan Africa (SSA) using machine learning models.Methods: The sub-Saharan African countries’ demographic health survey was the source of the dataset. We used a weighted sample of 16,832 under-five children in this study. The data were processed using Python (version 3.9), and machine learning models such as extreme gradient boosting (XGB), random forest, decision tree, logistic regression, and Naïve Bayes were applied. In this study, we used evaluation metrics, including the AUC ROC curve, accuracy, precision, recall, and F-measure, to assess the performance of the predictive models.Result: In this study, a weighted sample of 16,832 under-five children was used in the final analysis. Among the proposed machine learning models, the random forest (RF) was the best-predicted model with an accuracy of 88.89%, a precision of 89.5%, an F-measure of 83%, an AUC ROC curve of 95.8%, and a recall of 77.6% in predicting the absence of mothers’ healthcare-seeking behavior for ARIs. The accuracy for Naïve Bayes was the lowest (66.41%) when compared to other proposed models. No media exposure, living in rural areas, not breastfeeding, poor wealth status, home delivery, no ANC visit, no maternal education, mothers’ age group of 35–49 years, and distance to health facilities were significant predictors for the absence of mothers’ healthcare-seeking behaviors for ARIs. On the other hand, undernourished children with stunting, underweight, and wasting status, diarrhea, birth size, married women, being a male or female sex child, and having a maternal occupation were significantly associated with good maternal healthcare-seeking behaviors for ARIs among under-five children.Conclusion: The RF model provides greater predictive power for estimating mothers’ healthcare-seeking behaviors based on ARI risk factors. Machine learning could help achieve early prediction and intervention in children with high-risk ARIs. This leads to a recommendation for policy direction to reduce child mortality due to ARIs in sub-Saharan countries.

Background Exclusive breastfeeding (EBF) is a major public health problem in Ethiopia. However, the spatial variation of EBF and the associated factors have not been studied as much as we have searched. This study aimed at assessing geospatial variation and the predictors of EBF using geographically weighted regression. Methods A cross-sectional study was conducted using the 2019 Mini-Ethiopian Demographic and Health Survey data set. The study used a total weighted sample of 548 infants. Hotspot spatial analysis showed the hotspot and cold spot areas of EBF. The spatial distribution of EBF was interpolated for the target population using spatial interpolation analysis. SaTScan V.9.6 software was used to detect significant clusters. Ordinary least squares regression analysis identified significant spatial predictors. In geographically weighted regression analysis, the effect of predictor variables on the spatial variation of EBF was detected using local coefficients. Results The weighted prevalence of EBF in Ethiopia was 58.97% (95% CI 52.67% to 64.99%), and its spatial distribution was found to be clustered (global Moran’s I=0.56, p<0.001). Significant hotspot areas were located in Amhara, Tigray, Southern Nations, Nationalities, and Peoples’ Region, and Somali regions, while significant cold spots were located in Dire Dawa, Addis Ababa and Oromia regions. Kulldorff’s SaTScan V.9.6 was used to detect significant clusters of EBF using a 50% maximum cluster size per population. The geographically weighted regression model explained 35.75% of the spatial variation in EBF. The proportions of households with middle wealth index and married women were significant spatial predictors of EBF. Conclusion Middle wealth index and married women were significant spatial predictors of EBF. Our detailed map of EBF hotspot areas will help policymakers and health programmers encourage the practice of EBF in hotspot areas and set national and regional programmes focused on improving EBF in cold spots by considering significant predictor variables.

Background: In Ethiopia, recent evidence revealed that over a quarter (27%) of households (HHs) defecated openly in bush or fields, which play a central role as the source of many water-borne infectious diseases, including cholera. Ethiopia is not on the best track to achieve the SDG of being open-defecation-free by 2030. Therefore, this study aimed to explore the spatial variation and geographical inequalities of open defecation (OD) among HHs in Ethiopia. Methods: This was a country-wide community-based cross-sectional study among a weighted sample of 8663 HHs in Ethiopia. The global spatial autocorrelation was explored using the global Moran’s-I, and the local spatial autocorrelation was presented by Anselin Local Moran’s-I to evaluate the spatial patterns of OD practice in Ethiopia. Hot spot and cold spot areas of OD were detected using ArcGIS 10.8. The most likely high and low rates of clusters with OD were explored using SaTScan 10.1. Geographical weighted regression analysis (GWR) was fitted to explore the geographically varying coefficients of factors associated with OD. Results: The prevalence of OD in Ethiopia was 27.10% (95% CI: 22.85–31.79). It was clustered across enumeration areas (Global Moran’s I = 0.45, Z-score = 9.88, P-value ≤ 0.001). Anselin Local Moran’s I analysis showed that there was high-high clustering of OD at Tigray, Afar, Northern Amhara, Somali, and Gambela regions, while low-low clustering of OD was observed at Addis Ababa, Dire-Dawa, Harari, SNNPR, and Southwest Oromia. Hotspot areas of OD were detected in the Tigray, Afar, eastern Amhara, Gambela, and Somali regions. Tigray, Afar, northern Amhara, eastern Oromia, and Somali regions were explored as having high rates of OD. The GWR model explained 75.20% of the geographical variation of OD among HHs in Ethiopia. It revealed that as the coefficients of being rural residents, female HH heads, having no educational attainment, having no radio, and being the poorest HHs increased, the prevalence of OD also increased. Conclusion: The prevalence of OD in Ethiopia was higher than the pooled prevalence in sub-Saharan Africa. Tigray, Afar, northern Amhara, eastern Oromia, and Somali regions had high rates of OD. Rural residents, being female HH heads, HHs with no educational attainment, HHs with no radio, and the poorest HHs were spatially varying determinants that affected OD. Therefore, the government of Ethiopia and stakeholders need to design interventions in hot spots and high-risk clusters. The program managers should plan interventions and strategies like encouraging health extension programs, which aid in facilitating basic sanitation facilities in rural areas and the poorest HHs, including female HHs, as well as community mobilization with awareness creation, especially for those who are uneducated and who do not have radios.

Introduction: Diabetes mellitus (DM) is one of the most significant public health problems. Globally, one in ten adults has diabetes, and it results in macro- or microvascular complications, such as diabetic retinopathy (DR). It is one of the most prevalent eye complications associated with DM, and it is the main cause of vision loss. Even though East African countries face a growing burden of diabetes and DR, no study depicts the regional prevalence and its associated factors. Therefore, this study aimed to estimate the pooled prevalence of DR and its associated factors among adults in East African countries. Methods: We extensively searched PubMed, Embase, Scopus, Google Scholar, and Google for relevant studies. A forest plot was used to estimate the pooled prevalence of diabetic retinopathy using DerSimonian and Laird’s random-effects model. We checked publication bias using funnel plots and Egger’s regression test. Potential heterogeneity was tested using the I-squared statistic. Subgroup analysis, sensitivity analysis, and meta-regression analysis were also performed. Furthermore, the pooled odds ratios for the associated factors were estimated. The research protocol was registered in PROSPER. Results: Among the 29 included studies, the estimated pooled prevalence of DR in East African countries was 28% (95% CI 23.0, 33.0). Besides, age ≥60 (OR = 2.88, 95% CI: 1.55, 5.32), body mass index ≥ 25 (AOR = 2.85; 95% CI: 1.69, 4.81; I2 = 85.4%, p < 0.001), and hemoglobin A1c levels ≥7 (OR = 2.48, 95% CI: 1.46, 4.23) were significantly associated with the prevalence of DR. Conclusions: The prevalence of DR in East Africa was high, with more than one in four individuals with diabetes developing DR. Besides, advanced age, higher body mass index, and elevated hemoglobin A1c levels were significant factors associated with increased DR prevalence. Therefore, comprehensive diabetes management focusing on optimal glycemic control and healthy weight maintenance is essential to mitigate the problems. Also, the Ministries of Health and policymakers should prioritize and implement targeted strategies to address the identified modifiable risk factors, aiming to reduce the prevalence of DR in the region. Trial registration: Systematic review registration: PROSPERO (2024: ID = CRD42024511437 ). https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024511437.