Estimation of epidemiological parameters and ascertainment rate from early transmission of COVID-19 across Africa

Estimation of epidemiological parameters and ascertainment rate from early transmission of COVID-19 across Africa | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Estimation of epidemiological parameters and ascertainment rate from early transmission of COVID-19 across Africa Qing Han, Nicola Bragazzi, Ali Asgary, James Orbinski, Jianhong Wu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1708820/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Country reported case counts suggested a slow spread of SARS-CoV-2 in the initial phase of the COVID-19 pandemic in Africa. However, due to inadequate public awareness, unestablished monitoring practices, limited testing, ineffective diagnosis, stigmas attached to being infected with SARS-CoV-2, self-medication, and the use of complementary/alternative medicine that are common among Africans for social, economic, and psychological reasons, there might exist extensive under-ascertainment and therefore an underestimation of the true number of cases, especially at the beginning of the novel epidemic. We developed a compartmentalized epidemiological model based on an augmented susceptible-exposed-infectious-recovered (SEIR) model to track the early epidemics in 54 African countries. Data on the reported cumulative number of cases and daily confirmed cases were used to fit the model for the time period with no or little massive national interventions yet in each country. We estimated that the mean basic reproduction number is 2.02 (SD 0.7), with a range between 1.12 (Zambia) and 3.64 (Nigeria), whereas the mean basic reproduction number for observed cases was estimated to be 0.17 (SD 0.17), with a range between 0 (Sao Tomé and Príncipe, Seychelles, Tanzania, South Sudan, Mozambique, Liberia, Togo) and 0.68 (South Africa). It was estimated that the mean overall report rate is 5.37% (SD 5.71%), with the highest 30.41% in Libya and the lowest 0.02% in Sao Tomé and Príncipe. An average of 5.46% (SD 6.4%) of all infected cases were severe cases and 66.74% (SD 17.28%) were asymptomatic ones, with Libya having the most (39.45%) fraction of severe cases and Togo the most (97.38%) fraction of asymptomatic cases. The estimated low reporting rates in Africa suggested a clear need for improved reporting and surveillance system in these countries. Full Text Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterials.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1708820","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":116793996,"identity":"fd796ac3-84a7-4426-99d9-8539b2d97982","order_by":0,"name":"Qing Han","email":"","orcid":"","institution":"York University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qing","middleName":"","lastName":"Han","suffix":""},{"id":116793997,"identity":"4aa53948-c3f8-497d-8be9-bf0fbcc34eb6","order_by":1,"name":"Nicola Bragazzi","email":"","orcid":"","institution":"York 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