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

Author:

Han Qing12ORCID,Bragazzi Nicola2,Asgary Ali3,Orbinski James4,Wu Jianhong2ORCID,Kong Jude Dzevela12ORCID

Affiliation:

1. Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), York University, Keele Campus, 4700 Keele Street, Toronto, Ontario, Canada M3J 1P3

2. Department of Mathematics and Statistics, Laboratory for Industrial and Applied Mathematics (LIAM), York University, Keele Campus, 4700 Keele Street, Toronto, Ontario, Canada M3J 1P3

3. Disaster and Emergency Management, School of Administrative Studies, Faculty of Liberal Arts and Professional Studies, York University, Keele Campus, 4700 Keele Street, Toronto, Ontario, Canada M3J 1P3

4. Dahdaleh Institute for Global Health Research, York University, Keele Campus, 4700 Keele Street, Toronto, Ontario, Canada M3J 1P3

Abstract

Country reported case counts suggested a slow spread of SARS-CoV-2 in the initial phase of the COVID-19 pandemic in Africa. Owing to inadequate public awareness, unestablished monitoring practices, limited testing and stigmas, there might exist extensive under-ascertainment of the true number of cases, especially at the beginning of the novel epidemic. We developed a compartmentalized epidemiological 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 (s.d. 0.7), with a range between 1.12 (Zambia) and 3.64 (Nigeria). The mean overall report rate was estimated to be 5.37% (s.d. 5.71%), with the highest 30.41% in Libya and the lowest 0.02% in São Tomé and Príncipe. An average of 5.46% (s.d. 6.4%) of all infected cases were severe cases and 66.74% (s.d. 17.28%) were asymptomatic ones. The estimated low reporting rates in Africa suggested a clear need for improved reporting and surveillance systems in these countries.

Funder

Swedish International Development Cooperation Agency

International Development Research Centre

Publisher

The Royal Society

Subject

Multidisciplinary

Reference57 articles.

1. The proximal origin of SARS-CoV-2

2. WHO. 2022 Timeline: WHO’s COVID-19 response. See https://www.who.int/emergencies/diseases/novel-coronavirus-2019/interactive-timeline.

3. WHO. 2020 Statement on the second meeting of the International Health Regulations (2005) Emergency Committee regarding the outbreak of novel coronavirus (2019-nCoV). See https://www.who.int/news/item/30-01-2020-statement-on-the-second-meeting-of-the-international-health-regulations-(2005)-emergency-committee-regarding-the-outbreak-of-novel-coronavirus-(2019-ncov).

4. WHO. 2020 WHO Director-General’s opening remarks at the media briefing on COVID-19. See https://www.who.int/director-general/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19-11-march-2020.

5. WHO. 2022 WHO Coronavirus (COVID-19) dashboard. See https://covid19.who.int.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3