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http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/8950| Predictive Accuracy of a Hierarchical Logistic Model of Cumulative SARS-CoV-2 Case Growth | |
| Levente Kriston | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| https://doi.org/10.1101/2020.06.15.20130989 | |
| https://www.medrxiv.org/content/10.1101/2020.06.15.20130989v1 | |
| Background Infectious disease predictions models, including virtually all epidemiological models describing the spread of the SARS-CoV-2 pandemic up to June 2020, are rarely evaluated. The aim of the present study was to investigate the predictive accuracy of a prognostic model for forecasting the development of the cumulative number of reported SARS-CoV-2 cases in countries and administrative regions worldwide. Methods The cumulative number of reported SARS-CoV-2 cases was forecasted in 251 regions with a horizon of two weeks, one month, and two months using a previously described hierarchical logistic model at the end of March 2020. Forecasts were compared to actual observations by using a series of evaluation metrics. Results On average, predictive accuracy was very high in nearly all regions at the two weeks forecast, high in most regions at the one month forecast, and notable in the majority of the regions at the two months forecast. Higher accuracy was associated with the availability of more data for estimation and with a more pronounced cumulative case growth from the first case to the date of estimation. In some strongly affected regions, cumulative case counts were considerably underestimated. Conclusions With keeping its limitations in mind, the investigated model can be used for the preparation and distribution of resources during the SARS-CoV-2 pandemic. Future research should primarily address the model’s assumptions and its scope of applicability. In addition, establishing a relationship with known mechanisms and traditional epidemiological models of disease transmission would be desirable. | |
| bioRxiv | |
| 16-06-2020 | |
| Preimpreso | |
| Inglés | |
| Público en general | |
| VIRUS RESPIRATORIOS | |
| Aparece en las colecciones: | Materiales de Consulta y Comunicados Técnicos |
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| Predictive Accuracy of a Hierarchical Logistic Model of Cumulative SARS-CoV-2 Case Growth.pdf | 1.72 MB | Adobe PDF | Visualizar/Abrir |