Objective: To quantify the initial spread of COVID-19 in the WHO African region, and to investigate the possible drivers responsible for variation in the epidemic among member states. Design: A cross-sectional study. Setting: COVID-19 daily case and death data from the initial case through 29 November 2020. Participants: 46 countries comprising the WHO African region. Main outcome measures: We used five pandemic response indicators for each country: speed at which the pandemic reached the country, speed at which the first 50 cases accumulated, maximum monthly attack rate, cumulative attack rate, and crude case fatality ratio (CFR). We studied the effect of 13 predictor variables on the country-level variation in them using a principal component analysis, followed by regression. Results: Countries with higher tourism activities, GDP per capita, and proportion of older people had higher monthly (p < 0.001) and cumulative attack rates (p < 0.001) and lower CFRs (p = 0.052). Countries having more stringent early COVID-19 response policies experienced greater delay in arrival of the first case (p < 0.001). The speed at which the first 50 cases occurred was slower in countries whose neighbors had higher cumulative attack rates (p = 0.06). Conclusions: While global connectivity and tourism could facilitate the spread of airborne infectious agents, the observed differences in attack rates between African countries might also be due to differences in testing capacities or age distribution. Wealthy countries managed to minimize adverse outcomes. Further, careful and early implementation of strict government policies, such as restricting tourism, could be pivotal to controlling the COVID-19 pandemic. Evidently, good quality data and sufficient testing capacities are essential to unravel the epidemiology of an outbreak. We thus urge decision-makers to reduce these barriers to ensure rapid responses to future threats to public health and economic stability.
Emerging infectious diseases are a growing threat in sub-Saharan African countries, but the human and technical capacity to quickly respond to outbreaks remains limited. Here, we describe the experience and lessons learned from a joint project with the WHO Regional Office for Africa (WHO AFRO) to support the sub-Saharan African COVID-19 response.In June 2020, WHO AFRO contracted a number of consultants to reinforce the COVID-19 response in member states by providing actionable epidemiological analysis. Given the urgency of the situation and the magnitude of work required, we recruited a worldwide network of field experts, academics and students in the areas of public health, data science and social science to support the effort. Most analyses were performed on a merged line list of COVID-19 cases using a reverse engineering model (line listing built using data extracted from national situation reports shared by countries with the Regional Office for Africa as per the IHR (2005) obligations). The data analysis platform The Renku Project (https://renkulab.io) provided secure data storage and permitted collaborative coding.Over a period of 6 months, 63 contributors from 32 nations (including 17 African countries) participated in the project. A total of 45 in-depth country-specific epidemiological reports and data quality reports were prepared for 28 countries. Spatial transmission and mortality risk indices were developed for 23 countries. Text and video-based training modules were developed to integrate and mentor new members. The team also began to develop EpiGraph Hub, a web application that automates the generation of reports similar to those we created, and includes more advanced data analyses features (e.g. mathematical models, geospatial analyses) to deliver real-time, actionable results to decision-makers.Within a short period, we implemented a global collaborative approach to health data management and analyses to advance national responses to health emergencies and outbreaks. The interdisciplinary team, the hands-on training and mentoring, and the participation of local researchers were key to the success of this initiative.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.