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http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/8272| A model for COVID-19 prediction in Iran based on China parameters | |
| Bushra Zareie amin roshani Mohammad Ali Mansournia Mohammad Aziz Rasouli Ghobad Moradi | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| https://doi.org/10.1101/2020.03.19.20038950 | |
| https://www.medrxiv.org/content/10.1101/2020.03.19.20038950v1 | |
| Abstract Background The rapid spread of COVID-19 virus from China to other countries and outbreaks of disease require an epidemiological analysis of the disease in the shortest time and an increased awareness of effective interventions. The purpose of this study was to estimate the COVID-19 epidemic in Iran based on the SIR model. The results of the analysis of the epidemiological data of Iran from January 22 to March 8, 2020 were investigated and the prediction was made until March 29, 2020. Methods By estimating the three parameters of time-dependent transmission rate, time-dependent recovery rate, and time-dependent mortality rate from Covid-19 outbreak in China, and using the number of Covid-19 infections in Iran, we predicted the number of patients for the next month in Iran. Each of these parameters was estimated using GAM models. All analyses were conducted in R software using the mgcv package. Findings On average, 925 people with COVID-19 are expected to be infected daily in Iran. The epidemic peaks within one week (15.03.2020 to 03.21.2020) and reaches its highest point on 03.18.2020 with 1126 infected cases. Conclusion The most important point is to emphasize the timing of the epidemic peak, hospital readiness, government measures and public readiness to reduce social contact. Competing Interest Statement The authors have declared no competing interest. Funding Statement This study was funded by Vice Chancellor for Research and Technology of Kurdistan University of Medical Sciences, Sanandaj, Iran. The funding body played no role in the design of the study, collection, analysis, or interpretation of data or in writing the manuscript. | |
| bioRxiv | |
| 23-03-2020 | |
| Preimpreso | |
| Inglés | |
| Público en general | |
| VIRUS RESPIRATORIOS | |
| Aparece en las colecciones: | Materiales de Consulta y Comunicados Técnicos |
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