Predicting the progress of COVID-19 : the case for Turkey
| Autor: | Selcen Ozturkcan, Ahmet Akgül, Kerem Şenel, Mesut Ozdinc |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Coronavirus disease 2019 (COVID-19)
Turkey Reproduction (economics) coronavirus COVID-19 Public Health Global Health Social Medicine and Epidemiology General Medicine 01 natural sciences 010104 statistics & probability 03 medical and health sciences Folkhälsovetenskap global hälsa socialmedicin och epidemiologi 0302 clinical medicine Geography Pandemic SIR 030212 general & internal medicine epidemic models 0101 mathematics Epidemic model Demography |
| Popis: | The SIR model is applied to a dataset of 43 days from the beginning of the COVID-19 pandemic in Turkey. Model outputs regarding the estimates of effective reproduction number and peak date of the maximum number of actively infected are presented. Favorable impact of social distancing measures are observed in comparing model outputs on progressive days. Findings are valuable for policy and decision makers in shedding light on the next phases of the pandemic. |
| Databáze: | OpenAIRE |
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