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http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/8623| Estimating the true (population) infection rate for COVID-19: A Backcasting Approach with Monte Carlo Methods | |
| Steven Phipps Quentin Grafton Tom Kompas | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| https://doi.org/10.1101/2020.05.12.20098889 | |
| https://www.medrxiv.org/content/10.1101/2020.05.12.20098889v1 | |
| Differences in COVID-19 testing and tracing across countries, as well as changes in testing within each country overtime, make it difficult to estimate the true (population) infection rate based on the confirmed number of cases obtained through RNA viral testing. We applied a backcasting approach, coupled with Monte Carlo methods, to estimate a distribution for the true (population) cumulative number of infections (infected and recovered) for 15 countries where reliable data are available. We find a positive relationship between the testing rate per 1,000 people and the implied true detection rate of COVID-19, and a negative relationship between the proportion who test positive and the implied true detection rate. Our estimates suggest that the true number of people infected across our sample of 15 developed countries is 18.2 (5-95% CI: 11.9-39.0) times greater than the reported number of cases. In individual countries, the true number of cases exceeds the reported figure by factors that range from 1.7 (5-95% CI: 1.1-3.6) for Australia to 35.6 (5-95% CI: 23.2-76.3) for Belgium. | |
| bioRxiv | |
| 18-05-2020 | |
| Preimpreso | |
| Inglés | |
| Público en general | |
| VIRUS RESPIRATORIOS | |
| Versión publicada | |
| publishedVersion - Versión publicada | |
| Aparece en las colecciones: | Materiales de Consulta y Comunicados Técnicos |
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| Estimating the true (population) infection rate for COVID-19 A Backcasting Approach with Monte Carlo Methods.pdf | 359.75 kB | Adobe PDF | Visualizar/Abrir |