This study examined coronavirus disease 2019 (COVID-19) prevention knowledge among community residents in Eastern Ethiopia to support public health interventions and vaccination coverage. A cross-sectional survey in August-September 2021 recruited 880 participants from households in a Health and Demographic Surveillance System (HDSS) in Harari and Oromia, Ethiopia. Participants were randomly selected and interviewed in person using tablets and a standardized questionnaire. Principal components analysis was used to create a score representing COVID-19 prevention knowledge. Quasi-Poisson regression was used to examine associations between demographic characteristics and COVID-19 prevention knowledge. The survey also assessed awareness of community/government COVID-19 prevention measures and healthcare services for under-5 children and pregnant women. The most cited COVID-19 prevention measures were handwashing with soap (91.5%) and wearing facemasks (89.2%); least mentioned were avoiding travel (22.2%) and wearing medical gloves (20.3%). Commonly recognized community/government measures included school closures (77.0%), avoiding gatherings (75.2%), and staying home (62.3%). Adjusted analyses demonstrated higher COVID-19 prevention knowledge among rural participants, those aged ≥65 years (reference: <25), with secondary education (reference: no education), with monthly income of ≥2,001 Birr (reference: 0–1,200), and were farmers, domestic/subsistence workers, or government employees (reference: unemployed). Knowledge was lower among households with ≥5 household members. Of households with under-5 children and pregnant women, 9.4% and 12.3% missed medical care visits since mid-March 2020 consequent to the pandemic. Public health interventions to reduce COVID-19 transmission rely on risk perception and knowledge. Understanding these factors can help Ethiopian authorities design effective health education programs to control community and household SARS-CoV-2 transmission. © The Author(s) 2024.

In resource-limited settings where vital registration and medical death certificates are unavailable or incomplete, verbal autopsy (VA) is often used to attribute causes of death (CoD) and prioritize resource allocation and interventions. We aimed to determine the CoD concordance between InterVA and CHAMPS's method. The causes of death (CoDs) of children <5 were determined by two methods using data from seven low- and middle-income countries (LMICs) enrolled in the Child Health and Mortality Prevention Surveillance (CHAMPS) network. The first CoD method was from the DeCoDe panel using data from Minimally Invasive Tissue Sampling (MITS), whereas the second method used Verbal Autopsy (VA), which utilizes the InterVA software. This analysis evaluated the agreement between the two using Lin's concordance correlation coefficient. The overall concordance of InterVA4 and DeCoDe in assigning causes of death across surveillance sites, age groups, and causes of death was poor (0.75 with 95% CI: 0.73-0.76) and lacked precision. We found substantial differences in agreement by surveillance site, with Mali showing the lowest and Mozambique and Ethiopia the highest concordance. The InterVA4 assigned CoD agrees poorly in assigning causes of death for U5s and stillbirths. Because VA methods are relatively easy to implement, such systems could be more useful if algorithms were improved to more accurately reflect causes of death, for example, by calibrating algorithms to information from programs that used detailed diagnostic testing to improve the accuracy of COD determination.

BACKGROUND: The COVID-19 pandemic was associated with widespread social disruptions, as governments implemented lockdowns to quell disease spread. To advance knowledge of consequences for households in resource-limited countries, we examine food insecurity during the pandemic period. METHODS: We conducted a cross-sectional study and used logistic regression to examine factors associated with food insecurity. Data were collected between August and September of 2021 through a Health and Demographic Surveillance System (HDSS) using a survey instrument focused on knowledge regarding the spread of COVID-19; food availability; COVID-19 related shocks/coping; under-five child healthcare services; and healthcare services for pregnant women. The study is set in two communities in Eastern Ethiopia, one rural (Kersa) and one urban (Harar), and included a random sample of 880 households. RESULTS: Roughly 16% of households reported not having enough food to eat during the pandemic, an increase of 6% since before the pandemic. After adjusting for other variables, households were more likely to report food insecurity if they were living in an urban area, were a larger household, had a family member lose employment, reported an increase in food prices, or were food insecure before the pandemic. Households were less likely to report food insecurity if they were wealthier or had higher household income. CONCLUSIONS: After taking individual and household level sociodemographic characteristics into consideration, households in urban areas were at higher risk for food insecurity. These findings suggest a need for expanding food assistance programs to more urban areas to help mitigate the impact of lockdowns on more vulnerable households.

BACKGROUND: COVID-19 resulted in enormous disruption to life around the world. To quell disease spread, governments implemented lockdowns that likely created hardships for households. To improve knowledge of consequences, we examine how the pandemic period was associated with household hardships and assess factors associated with these hardships. METHODS: We conducted a cross-sectional study using quasi-Poisson regression to examine factors associated with household hardships. Data were collected between August and September of 2021 from a random sample of 880 households living within a Health and Demographic Surveillance System (HDSS) located in the Harari Region and the District of Kersa, both in Eastern Ethiopia. RESULTS: Having a head of household with no education, residing in a rural area, larger household size, lower income and/or wealth, and community responses to COVID-19, including lockdowns and travel restrictions, were independently associated with experiencing household hardships. CONCLUSIONS: Our results identify characteristics of groups at-risk for household hardships during the pandemic; these findings may inform efforts to mitigate the consequences of COVID-19 and future disease outbreaks.

Data were collected as part of the Child Health and Mortality Prevention Surveillance (CHAMPS) network to learn about the effects of COVID-19 lockdowns on child health and access to care. Data were collected between August and September 2021 through a Health and Demographic Surveillance System (HDSS) operating in Eastern Ethiopia using a survey instrument focused on knowledge about COVID-19 and changes in food availability and healthcare services during the COVID-19 related lockdown. The data are representative of two communities in Eastern Ethiopia, one rural (Kersa) and one urban (Harar), and consist of a random sample of 880 households.

Objective The COVID-19 pandemic was associated with widespread social disruptions, as governments implemented lockdowns to quell disease spread. To advance knowledge of consequences for households in lower-income countries, we examine food insecurity during the pandemic period. Design Cross-sectional study using logistic regression to examine factors associated with food insecurity. Data were collected between August and September of 2021 through a Health and Demographic Surveillance System (HDSS) using a survey instrument focused on knowledge regarding the spread of COVID-19; food availability; COVID-19 related shocks/coping; under-five child healthcare services; and healthcare services for pregnant women. Setting The study is set in two communities in Eastern Ethiopia, one rural and one urban. Participants A random sample of 880 households residing in Kersa and Harar. Results Roughly 16% of households reported not having enough food to eat during the pandemic, an increase of 6% since before the pandemic. After adjusting for other variables, households were more likely to report food insecurity if they were living in an urban area, were a larger household, had a family member lose employment, reported an increase in food prices, or were food insecure before the pandemic. Households were less likely to report food insecurity if they were wealthier or had higher household income. Discussion After taking other characteristics into consideration, households in urban areas were at higher risk for food insecurity. These findings point to the need for expanding food assistance programs to more urban areas to help mitigate the impact of lockdowns on more vulnerable households. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.

Background: COVID-19 caused enormous disruption to life in the 21st century. To quell disease spread, governments implemented lockdowns that likely created hardships for households. To improve knowledge of consequences, we examine how the pandemic period was associated with household hardships and assess factors associated with these hardships. Method(s): We conducted a cross-sectional study using quasi-Poisson regression to examine factors associated with household hardships. Data were collected between August and September of 2021 from a random sample of 880 households living within a Health and Demographic Surveillance System (HDSS) located in the Harari Region and the District of Kersa, both in Eastern Ethiopia. Result(s): Having a head of household with no education, residing in a rural area, larger household size, lower income and/or wealth, and community responses to COVID-19, including lockdowns and travel restrictions, were independently associated with experiencing household hardships. Conclusion(s): Our results identify characteristics of groups at-risk for household hardships during the pandemic; these findings may inform efforts to mitigate the consequences of COVID-19 and future disease outbreaks. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.

Point of care (POC) tests for antiretroviral drugs (ARVs) could help improve individual adherence. This study sought to define the utility of urine, blood, and buccal swabs as minimally invasive specimens amenable to development of POC tests for ARVs. Urine, dried blood spots (DBS) and buccal swabs were collected from 35 HIV-negative men between 2 and 96 hours following a single dose of tenofovir alafenamide (TAF)/emtricitabine (FTC)/elvitegravir (EVG)/cobicistat and darunavir (DRV). ARV concentrations were measured by high performance liquid chromatography-mass spectrometry. High concentrations of FTC, DRV and TFV were detectable in urine at least 24 hours after dosing. FTC, DRV and EVG remained detectable in DBS at least 24 hours post dose. FTC and DRV were detectable on buccal swabs up to 2- and 24-hours post dose, respectively. TFV was not detectable in DBS or buccal swabs collected between 2 and 96 hours after dosing. Variable distribution of ARVs in minimally invasive specimens highlights the challenge of developing POC assays for recent ARV exposure.

Health and demographic surveillance systems (HDSSs) provide a foundation for characterizing and defining priorities and strategies for improving population health. The Child Health and Mortality Prevention Surveillance (CHAMPS) project aims to inform policy to prevent child deaths through generating causes of death from surveillance data combined with innovative diagnostic and laboratory methods. Six of the 7 sites that constitute the CHAMPS network have active HDSSs: Mozambique, Mali, Ethiopia, Kenya, Bangladesh, and South Africa; the seventh, in Sierra Leone, is in the early planning stages. This article describes the network of CHAMPS HDSSs and their role in the CHAMPS project. To generate actionable health and demographic data to prevent child deaths, the network depends on reliable demographic surveillance, and the HDSSs play this crucial role.

BACKGROUND: Influenza is an acute viral disease of the respiratory tract which is characterized by fever, headache, myalgia, prostration, coryza, sore throat and cough. Globally, an estimated 3 to 5 million cases of severe influenza illness and 291 243-645 832 seasonal influenza-associated respiratory deaths occur annually. Although recent efforts from some African countries to describe burden of influenza disease and seasonality, these data are missing for the vast majority, including Ethiopia. Ethiopia established influenza sentinel surveillance in 2008 aiming to determine influenza strains circulating in the country and know characteristics, trend and burden of influenza viruses. METHODS: We used influenza data from sentinel surveillance sites and respiratory disease outbreak investigations from 2009 to 2015 for this analysis. We obtained the data by monitoring patients with influenza-like illness (ILI) at three health-centers, severe acute respiratory infection (SARI) at five hospitals and investigating patients during different respiratory infection outbreaks. Throat-swab specimens in viral transport media were transported to the national reference laboratory within 72 h of collection using a cold-chain system. We extracted viral RNA from throat-swabs and subjected to real-time PCR amplification. We further subtyped and characterized Influenza A-positive specimens using CDC real-time reverse transcription PCR protocol. RESULTS: A total of 4962 throat-swab samples were collected and 4799 (96.7%) of them were tested. Among them 988 (20.6%) were influenza-positive and of which 349 (35.3%) were seasonal influenza A(H3N2), 321 (32.5%) influenza A(H1N1)pdm2009 and 318 (32.0%) influenza B. Positivity rate was 29.5% in persons 5-14 years followed by 26.4% in 15-44 years, 21.2% in > 44 years and 6.4% in under five children. The highest positivity rate observed in November (37.5%) followed by March (27.6%), December (26.4%), October (24.4%) and January (24.3%) while the lowest positivity rate was in August (7.7%). CONCLUSION: In Ethiopia, seasonal Influenza A(H3N2), Influenza A(H1N1)pdm2009 and Influenza B viruses were circulating during 2009-2015. Positivity rate and number of cases peaked in November and December. Influenza is one of public health problems in Ethiopia and the need to introduce influenza vaccine and antivirus is important to prevent and treat the disease in future.

BACKGROUND: Yellow fever (YF) is a viral hemorrhagic fever, endemic in the tropical forests of Africa and Central and South America. The disease is transmitted by mosquitoes infected with the yellow fever virus (YFV). Ethiopia was affected by the largest YF outbreak since the vaccination era during 1960-1962. The recent YF outbreak occurred in 2013 in Southern part of the country. The current survey of was carried out to determine the YF seroprevalence so as to make recommendations from YF prevention and control in Ethiopia. METHODOLOGY: A multistage cluster design was utilized. Consequently, the country was divided into 5 ecological zones and two sampling towns were picked per zone randomly. A total of 1643 serum samples were collected from human participants. The serum samples were tested for IgG antibody against YFV using ELISA. Any serum sample testing positive by ELISA was confirmed by plaque reduction neutralization test (PRNT). In addition, differential testing was performed for other flaviviruses, namely dengue, Zika and West Nile viruses. RESULT: Of the total samples tested, 10 (0.61%) were confirmed to be IgG positive against YFV and confirmed with PRNT. Nine (0.5%) samples were antibody positive for dengue virus, 15(0.9%) forWest Nile virus and 7 (0.4%) for Zika virus by PRNT. Three out of the five ecological zones namely zones 1, 3 and 5 showed low levels (< 2%) of IgG positivity against YFV. A total of 41(2.5%) cases were confirmed to be positive for one of flaviviruses tested. CONCLUSION: Based on the seroprevalence data, the level of YFV activity and the risk of a YF epidemic in Ethiopia are low. However additional factors that could impact the likelihood of such an epidemic occurring should be considered before making final recommendations for YF prevention and control in Ethiopia. Based on the results of the serosurvey and other YF epidemic risk factors considered, a preventive mass vaccination campaign is not recommended, however the introduction of YF vaccine in routine EPI is proposed nationwide, along with strong laboratory based YF surveillance.