RESUMO
Ethiopia has made significant progress in the last two decades in improving the availability and coverage of essential maternal and child health services including childhood immunizations. As Ethiopia keeps momentum towards achieving national immunization goals, methods must be developed to analyze routinely collected health facility data and generate localized coverage estimates. This study leverages the District Health Information Software (DHIS2) platform to estimate immunization coverage for the first dose of measles vaccine (MCV1) and the third dose of diphtheria-pertussis-tetanus-Hib-HepB vaccine (Penta3) across Ethiopian districts ("woredas"). Monthly reported numbers of administered MCV1 and Penta3 immunizations were extracted from public facilities from DHIS2 for 2017/2018-2021/2022 and corrected for quality based on completeness and consistency across time and districts. We then utilized three sources for the target population (infants) to compute administrative coverage estimates: Central Statistical Agency, DHIS2, and WorldPop. The Ethiopian Demographic and Health Surveys were used as benchmarks to which administrative estimates were adjusted at the regional level. Administrative vaccine coverage was estimated for all woredas, and, after adjustments, was bounded within 0-100%. In regions with the highest immunization coverage, MCV1 coverage would range from 83 to 100% and Penta3 coverage from 88 to 100% (Addis Ababa, 2021/2022); MCV1 from 8 to 100% and Penta3 from 4 to 100% (Tigray, 2019/2020). Nationally, the Gini index for MCV1 was 0.37, from 0.13 (Harari) to 0.37 (Somali); for Penta3, it was 0.36, from 0.16 (Harari) to 0.36 (Somali). The use of routine health information systems, such as DHIS2, combined with household surveys permits the generation of local health services coverage estimates. This enables the design of tailored health policies with the capacity to measure progress towards achieving national targets, especially in terms of inequality reductions.
RESUMO
Tuberculosis (TB) is a major public health concern in low- and middle-income countries including Ethiopia. This study aimed to assess the spatiotemporal distribution of TB and identify TB risk factors in Ethiopia's Oromia region. Descriptive and spatiotemporal analyses were conducted. Bayesian spatiotemporal modeling was used to identify covariates that accounted for variability in TB and its spatiotemporal distribution. A total of 206,278 new pulmonary TB cases were reported in the Oromia region between 2018 and 2022, with the lowest annual TB case notification (96.93 per 100,000 population) reported in 2020 (i.e., during the COVID-19 pandemic) and the highest TB case notification (106.19 per 100,000 population) reported in 2019. Substantial spatiotemporal variations in the distribution of notified TB case notifications were observed at zonal and district levels with most of the hotspot areas detected in the northern and southern parts of the region. The spatiotemporal distribution of notified TB incidence was positively associated with different ecological variables including temperature (ß = 0.142; 95% credible interval (CrI): 0.070, 0.215), wind speed (ß = -0.140; 95% CrI: -0.212, -0.068), health service coverage (ß = 0.426; 95% CrI: 0.347, 0.505), and population density (ß = 0.491; 95% CrI: 0.390, 0.594). The findings of this study indicated that preventive measures considering socio-demographic and health system factors can be targeted to high-risk areas for effective control of TB in the Oromia region. Further studies are needed to develop effective strategies for reducing the burden of TB in hotspot areas.
RESUMO
Background: Despite large investments in the public health care system, disparities in health outcomes persist between lower- and upper-income individuals, as well as rural vs urban dwellers in Ethiopia. Evidence from Ethiopia and other low- and middle-income countries suggests that challenges in health care access may contribute to poverty in these settings. Methods: We employed a two-step floating catchment area to estimate variations in spatial access to health care and in staffing levels at health care facilities. We estimated the average travel time from the population centers of administrative areas and adjusted them with provider-to-population ratios. To test hypotheses about the role of travel time vs staffing, we applied Spearman's rank tests to these two variables against the access score to assess the significance of observed variations. Results: Among Ethiopia's 11 first-level administrative units, Addis Ababa, Dire Dawa, and Harari had the best access scores. Regions with the lowest access scores were generally poorer and more rural/pastoral. Approximately 18% of the country did not have access to a public health care facility within a two-hour walk. Our results suggest that spatial access and staffing issues both contribute to access challenges. Conclusion: Investments both in new health facilities and staffing in existing facilities will be necessary to improve health care access within Ethiopia. Because rural and low-income areas are more likely to have poor access, future strategies for expanding and strengthening the health care system should strongly emphasize equity and the role of improved access in reducing poverty.
