Estimating the number of probable new SARS-CoV-2 infections among tested subjects from the number of confirmed cases
- PMID: 37978439
- PMCID: PMC10655282
- DOI: 10.1186/s12874-023-02077-2
Estimating the number of probable new SARS-CoV-2 infections among tested subjects from the number of confirmed cases
Abstract
Objectives: In most African countries, confirmed COVID-19 case counts underestimate the number of new SARS-CoV-2 infection cases. We propose a multiplying factor to approximate the number of biologically probable new infections from the number of confirmed cases.
Methods: Each of the first thousand suspect (or alert) cases recorded in South Kivu (DRC) between 29 March and 29 November 2020 underwent a RT-PCR test and an IgM and IgG serology. A latent class model and a Bayesian inference method were used to estimate (i) the incidence proportion of SARS-CoV-2 infection using RT-PCR and IgM test results, (ii) the prevalence using RT-PCR, IgM and IgG test results; and, (iii) the multiplying factor (ratio of the incidence proportion on the proportion of confirmed -RT-PCR+- cases).
Results: Among 933 alert cases with complete data, 218 (23%) were RT-PCR+; 434 (47%) IgM+; 464 (~ 50%) RT-PCR+, IgM+, or both; and 647 (69%) either IgG + or IgM+. The incidence proportion of SARS-CoV-2 infection was estimated at 58% (95% credibility interval: 51.8-64), its prevalence at 72.83% (65.68-77.89), and the multiplying factor at 2.42 (1.95-3.01).
Conclusions: In monitoring the pandemic dynamics, the number of biologically probable cases is also useful. The multiplying factor helps approximating it.
Keywords: Africa.; COVID-19 testing; Reverse transcriptase polymerase chain reaction; SARS-CoV-2; Serology.
© 2023. The Author(s).
Conflict of interest statement
None
References
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- WHO COVID-19 Case definition. https://www.who.int/publications-detail-redirect/WHO-2019-nCoV-Surveillance_Case_Definition-2020.2. Last accessed: Sept. 2021.
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