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Background Corona Virus Disease 2019 is a novel respiratory disease commonly transmitted through respiratory droplets. The disease has currently expanded all over the world with differing epidemiologic trajectories. This investigation was conducted to determine the basic clinical and epidemiological characteristics of the disease in Ethiopia. Methods A prospective case-ascertained study of laboratory-confirmed COVID-19 cases and their close contacts were conducted. The study included 100 COVID-19 laboratory-confirmed cases reported from May 15, 2020 to June 15, 2020 and 300 close contacts. Epidemiological and clinical information were collected using the WHO standard data collection tool developed first-few cases and contacts investigation. Nasopharyngeal and Oropharyngeal samples were collected by using polystyrene tipped swab and transported to the laboratory by viral transport media maintaining an optimal temperature. Clinical and epidemiological parameters were calculated in terms of ratios, proportions, and rates with 95% CI. Result A total of 400 participants were investigated, 100 confirmed COVID-19 cases and 300 close contacts of the cases. The symptomatic proportion of cases was 23% (23) (95% CI: 15.2%-32.5%), the proportion of cases required hospitalization were 8% (8) (95%CI: 3.5%-15.2%) and 2% (95%CI: 0.24% - 7.04%) required mechanical ventilation. The secondary infection rate, secondary clinical attack rate, median incubation period and median serial interval were 42% (126) (95% CI: 36.4%-47.8%), 11.7% (35) (95% CI: 8.3%-15.9%), 7 days (IQR: 4–13.8) and 11 days (IQR: 8–11.8) respectively. The basic reproduction number (RO) was 1.26 (95% CI: 1.0–1.5). Conclusion The proportion of asymptomatic infection, as well as secondary infection rate among close contacts, are higher compared to other studies. The long serial interval and low basic reproduction number might contribute to the observed slow progression of the pandemic, which gives a wide window of opportunities and time to control the spread. Testing, prevention, and control measures should be intensified.

Health information systems (HIS) performance in Ethiopia is currently insufficient, and improvements are required to ensure that decision making is data driven. We share our experiences from the early-stage implementation of a package of HIS capacity-strengthening interventions as part of an innovative academic-government collaboration that addresses challenges in HIS performance.We used routine program data to assess HIS performance using the Performance of Routine Information System Management (PRISM) assessment tools. The assessment employed a pre-post design and was conducted in a total of 24 selected health facilities (6 hospitals and 18 health centers) from 11 districts in Ethiopia at project baseline (2018) and midline (2020).Source document completeness rate reached less than 80% for the majority of the assessed data elements. Improvements were observed in quarterly report completeness (26% vs. 83%) and timeliness (17% vs. 48%). Though data inaccuracies are noted for all assessed data elements in 2020, the majority (83%) of skilled birth attendance and HIV reports (68%) fall within the acceptable range of reporting accuracy. The identification of performance-related problems, using performance monitoring team (PMT) meetings, improved between 2018 and 2020 (67% vs 89%). Similar improvements were also observed in developing action plans to solve identified problems via the PMT (52% in 2018 vs. 89% in 2020). Data use for planning and target setting (65% in 2018 vs. 90% in 2020), reviewing performance (58% in 2018 vs. 60% in 2020), and supervision (51% in 2018 vs. 53% in 2020) all improved among assessed health facilities.This study showed that a capacity-building and mentorship program that engages experts from multiple disciplines and sectors can improve the quality and use of health data. This partnership enabled engagement between government and academic stakeholders and allowed for a more robust exchange of resources and expertise toward HIS improvement.

Studies in Ethiopia show an increasing trend in maternal health service use, such as having at least 4 visits of antenatal care (ANC4+) and skilled birth attendance (SBA). Improving the health information system (HIS) is an intervention that can improve service uptake and quality. We conducted a baseline study to measure current maternal service coverage, HIS performance status, and their relationship.We conducted a linked health facility-level and population-based survey from September 2020 to October 2020. The study covers all regions of Ethiopia. For the population-based survey, 3,016 mothers were included. Overall, 81 health posts, 71 health centers, and 15 hospitals were selected for the facility survey. A two-stage sampling procedure was applied to select target households. The study used modified Performance of Routine Information System Management tools for the facility survey and a structured questionnaire for the household survey. Multilevel logistic regression was employed to account for clustering and control for likely confounders.Maternal service indicators, ANC4+ visits (54.0%), SBA (75.8%), postnatal care (70.6%), and cesarean delivery (9%) showed good service uptake. All data quality and use indicators showed lower performance compared to the national target of 90%. Maternal education and higher levels of wealth index were significantly and positively associated with all selected maternal service indicators. Longer distance from health facilities was significantly and negatively associated with SBA and the maternal care composite indicator. Among HIS-related indicators, availability of electronic HIS tools was significantly associated with maternal care composite indicator and ANC4+.Maternal service indicators showed promising performance. However, current HIS performance is suboptimal. Both service user and HIS-related factors were associated with maternal service uptake. Conducting similar research outside of the project sites will be helpful to have a wider understanding and better coverage.

Background The Coronavirus Disease 2019 (COVID-19) pandemic has had wide-reaching direct and indirect impacts on population health. In low- and middle-income countries, these impacts can halt progress toward reducing maternal and child mortality. This study estimates changes in health services utilization during the pandemic and the associated consequences for maternal, neonatal, and child mortality. Methods and findings Data on service utilization from January 2018 to June 2021 were extracted from health management information systems of 18 low- and lower-middle-income countries (Afghanistan, Bangladesh, Cameroon, Democratic Republic of the Congo (DRC), Ethiopia, Ghana, Guinea, Haiti, Kenya, Liberia, Madagascar, Malawi, Mali, Nigeria, Senegal, Sierra Leone, Somalia, and Uganda). An interrupted time-series design was used to estimate the percent change in the volumes of outpatient consultations and maternal and child health services delivered during the pandemic compared to projected volumes based on prepandemic trends. The Lives Saved Tool mathematical model was used to project the impact of the service utilization disruptions on child and maternal mortality. In addition, the estimated monthly disruptions were also correlated to the monthly number of COVID-19 deaths officially reported, time since the start of the pandemic, and relative severity of mobility restrictions. Across the 18 countries, we estimate an average decline in OPD volume of 13.1% and average declines of 2.6% to 4.6% for maternal and child services. We projected that decreases in essential health service utilization between March 2020 and June 2021 were associated with 113,962 excess deaths (110,686 children under 5, and 3,276 mothers), representing 3.6% and 1.5% increases in child and maternal mortality, respectively. This excess mortality is associated with the decline in utilization of the essential health services included in the analysis, but the utilization shortfalls vary substantially between countries, health services, and over time. The largest disruptions, associated with 27.5% of the excess deaths, occurred during the second quarter of 2020, regardless of whether countries reported the highest rate of COVID-19-related mortality during the same months. There is a significant relationship between the magnitude of service disruptions and the stringency of mobility restrictions. The study is limited by the extent to which administrative data, which varies in quality across countries, can accurately capture the changes in service coverage in the population. Conclusions Declines in healthcare utilization during the COVID-19 pandemic amplified the pandemic’s harmful impacts on health outcomes and threaten to reverse gains in reducing maternal and child mortality. As efforts and resource allocation toward prevention and treatment of COVID-19 continue, essential health services must be maintained, particularly in low- and middle-income countries.

Background: The COVID-19 pandemic has had wide-reaching direct and indirect impacts on population health. We describe one of the most critical of these secondary consequences, the decrease in the utilization of health services and the resulting consequences for mortality. In low- and middle-income countries, these disruptions can halt progress towards reducing maternal and child mortality. Methods: Data on service utilization from January 2018 to June 2021 is extracted from health management information systems of 18 low- and lower-middle-income countries. Interrupted time series design is used to estimate percent change in the volumes of essential health services delivered during the pandemic compared to projected volumes based on pre-pandemic trends. The Lives Saved Tool mathematical model is used to estimate the impact of the service utilization disruptions on child and maternal mortality. In addition, the estimated monthly disruptions are also correlated to the COVID-19 burden, time since the start of the pandemic, and relative severity of mobility restrictions. Findings: We estimate that decreases in essential health service utilization between March 2020 and June 2021 led to 113,873 additional deaths in the 18 countries, representing 3.8% and 1.4% increases in child and maternal mortality, respectively. This corresponds to an average of 2.6 indirect deaths per COVID-19 death officially reported in the same period. This excess mortality results from the decline in utilization of the RMNCH services included in the analysis, but the utilization shortfalls vary substantially between countries, health services, and over time. The largest disruptions, resulting in 27.5% of the excess death, occurred during the second quarter of 2020, regardless of whether countries experienced the highest rate of COVID-19-related deaths during the same months. There is a significant relationship between the magnitude of service disruptions and the stringency of mobility restrictions. Interpretation: Large declines in health care utilization during the COVID-19 pandemic amplify the pandemic's harmful impacts on health outcomes. As efforts and resource allocation towards prevention and treatment of COVID-19 continue, essential health services must be maintained, particularly in low and middle-income countries. Funding: The Global Financing Facility for Women, Children, and Adolescents. Declaration of Interests: We declare no competing interests.

Background As part of a partnership between the Institute for Healthcare Improvement and Ethiopian Federal Ministry of Health (FMoH), a Maternal and Neonatal Health (MNH) Collaborative took place between November 2016 and December 2017 aiming to accelerate reduction of maternal and neonatal mortality in Lemu Bilbilu, Tanqua Abergele and Duguna Fango districts. Before starting the MNH Collaborative, assessments found inaccuracies in core process and outcome data obtained from Health Management Information System (HMIS) reports. Objectives We aimed to assess the effect of an initiative to improve data quality in the MNH Collaborative. Methods Building on the core MNH Collaborative design, data quality improvement activities were added. We used the WHO review methodology to derive a verification factor (VF) for the core measures of number of pregnant women that received antenatal care first visit, number of pregnant women that received antenatal care on at least four visits, number of pregnant women tested for syphilis and number of births attended by skilled health personnel. Impact was assessed using interrupted time series. Results Data quality improved across all measures, for example, in Duguna Fango, the VF for number of pregnant women that received antenatal care first visit improved from 0.79 (quartiles 0.73, 0.85) pre-intervention to 0.99 (0.93, 1.00) post intervention, p Conclusions A data quality improvement initiative significantly improved accuracy of data used to monitor maternal progress of this MNH Collaborative in Ethiopia.

Background As part of a partnership between the Institute for Healthcare Improvement and the Ethiopian Federal Ministry of Health, woreda-based quality improvement collaboratives took place between November 2016 and December 2017 aiming to accelerate reduction of maternal and neonatal mortality in Lemu Bilbilu, Tanqua Abergele and Duguna Fango woredas. Before starting the collaboratives, assessments found inaccuracies in core measures obtained from Health Management Information System reports. Methods and results Building on the quality improvement collaborative design, data quality improvement activities were added and we used the World Health Organization review methodology to drive a verification factor for the core measures of number of pregnant women that received their first antenatal care visit, number of pregnant women that received antenatal care on at least four visits, number of pregnant women tested for syphilis and number of births attended by skilled health personnel. Impact of the data quality improvement was assessed using interrupted time series analysis. We found accurate data across all time periods for Tanqua Abergele. In Lemu Bilbilu and Duguna Fango, data quality improved for all core metrics over time. In Duguna Fango, the verification factor for number of pregnant women that received their first antenatal care visit improved from 0.794 (95%CI 0.753, 0.836; p