Evaluation of modelling study shows limits of COVID-19 importing risk simulations in sub-Saharan Africa
- PMID: 32513346
- PMCID: PMC7303472
- DOI: 10.1017/S095026882000120X
Evaluation of modelling study shows limits of COVID-19 importing risk simulations in sub-Saharan Africa
Abstract
Mathematical modelling studies predicting the spread of the coronavirus disease 2019 (COVID-19) have been used worldwide, but precisions are limited. Thus, continuous evaluation of the modelling studies is crucial. We investigated situations of virus importation in sub-Saharan Africa (SSA) to assess effectiveness of a modelling study by Haider N et al. titled 'Passengers' destinations from China: low risk of novel coronavirus (2019-nCoV) transmission into Africa and South America'. We obtained epidemiological data of 2417 COVID-19 cases reported by 40 countries in SSA within 30 days of the first case confirmed in Nigeria on 27 February. Out of 442 cases which had travel history available, only one (0.2%) had a travel history to China. These findings underline the result of the model. However, the fact that there were numbers of imported cases from other regions shows the limits of the model. The limits could be attributed to the characteristics of the COVID-19 which is infectious even when the patients do not express any symptoms. Therefore, there is a profound need for all modelling researchers to take asymptomatic cases into account when they establish modelling studies.
Keywords: COVID-19; mathematical modelling.
Comment in
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Response to 'Evaluation of modelling study shows limits of COVID-19 importing risk simulations in sub-Saharan Africa' (Epidemiology and Infection - HYG-LE-10513-May-20).Epidemiol Infect. 2020 Jun 10;148:e112. doi: 10.1017/S0950268820001211. Epidemiol Infect. 2020. PMID: 32517820 Free PMC article. No abstract available.
Comment on
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Passengers' destinations from China: low risk of Novel Coronavirus (2019-nCoV) transmission into Africa and South America.Epidemiol Infect. 2020 Feb 26;148:e41. doi: 10.1017/S0950268820000424. Epidemiol Infect. 2020. PMID: 32100667 Free PMC article.
References
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- Adam D (2020) The simulations driving the world's response to COVID-19. Nature 580, 316–318. - PubMed
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