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The basic reproduction number and prediction of the epidemic size of the novel coronavirus (COVID-19) in Shahroud, Iran
The aim of this study was to estimate the basic reproduction number (R(0)) of COVID-19 in the early stage of the epidemic and predict the expected number of new cases in Shahroud in Northeastern Iran. The R(0) of COVID-19 was estimated using the serial interval distribution and the number of inciden...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7322167/ https://www.ncbi.nlm.nih.gov/pubmed/32517845 http://dx.doi.org/10.1017/S0950268820001247 |
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author | Khosravi, A. Chaman, R. Rohani-Rasaf, M. Zare, F. Mehravaran, S. Emamian, M. H. |
author_facet | Khosravi, A. Chaman, R. Rohani-Rasaf, M. Zare, F. Mehravaran, S. Emamian, M. H. |
author_sort | Khosravi, A. |
collection | PubMed |
description | The aim of this study was to estimate the basic reproduction number (R(0)) of COVID-19 in the early stage of the epidemic and predict the expected number of new cases in Shahroud in Northeastern Iran. The R(0) of COVID-19 was estimated using the serial interval distribution and the number of incidence cases. The 30-day probable incidence and cumulative incidence were predicted using the assumption that daily incidence follows a Poisson distribution determined by daily infectiousness. Data analysis was done using ‘earlyR’ and ‘projections’ packages in R software. The maximum-likelihood value of R(0) was 2.7 (95% confidence interval (CI): 2.1−3.4) for the COVID-19 epidemic in the early 14 days and decreased to 1.13 (95% CI 1.03–1.25) by the end of day 42. The expected average number of new cases in Shahroud was 9.0 ± 3.8 cases/day, which means an estimated total of 271 (95% CI: 178–383) new cases for the period between 02 April to 03 May 2020. By day 67 (27 April), the effective reproduction number (R(t)), which had a descending trend and was around 1, reduced to 0.70. Based on the R(t) for the last 21 days (days 46–67 of the epidemic), the prediction for 27 April to 26 May is a mean daily cases of 2.9 ± 2.0 with 87 (48–136) new cases. In order to maintain R below 1, we strongly recommend enforcing and continuing the current preventive measures, restricting travel and providing screening tests for a larger proportion of the population. |
format | Online Article Text |
id | pubmed-7322167 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-73221672020-06-29 The basic reproduction number and prediction of the epidemic size of the novel coronavirus (COVID-19) in Shahroud, Iran Khosravi, A. Chaman, R. Rohani-Rasaf, M. Zare, F. Mehravaran, S. Emamian, M. H. Epidemiol Infect Original Paper The aim of this study was to estimate the basic reproduction number (R(0)) of COVID-19 in the early stage of the epidemic and predict the expected number of new cases in Shahroud in Northeastern Iran. The R(0) of COVID-19 was estimated using the serial interval distribution and the number of incidence cases. The 30-day probable incidence and cumulative incidence were predicted using the assumption that daily incidence follows a Poisson distribution determined by daily infectiousness. Data analysis was done using ‘earlyR’ and ‘projections’ packages in R software. The maximum-likelihood value of R(0) was 2.7 (95% confidence interval (CI): 2.1−3.4) for the COVID-19 epidemic in the early 14 days and decreased to 1.13 (95% CI 1.03–1.25) by the end of day 42. The expected average number of new cases in Shahroud was 9.0 ± 3.8 cases/day, which means an estimated total of 271 (95% CI: 178–383) new cases for the period between 02 April to 03 May 2020. By day 67 (27 April), the effective reproduction number (R(t)), which had a descending trend and was around 1, reduced to 0.70. Based on the R(t) for the last 21 days (days 46–67 of the epidemic), the prediction for 27 April to 26 May is a mean daily cases of 2.9 ± 2.0 with 87 (48–136) new cases. In order to maintain R below 1, we strongly recommend enforcing and continuing the current preventive measures, restricting travel and providing screening tests for a larger proportion of the population. Cambridge University Press 2020-06-10 /pmc/articles/PMC7322167/ /pubmed/32517845 http://dx.doi.org/10.1017/S0950268820001247 Text en © The Author(s) 2020 http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Paper Khosravi, A. Chaman, R. Rohani-Rasaf, M. Zare, F. Mehravaran, S. Emamian, M. H. The basic reproduction number and prediction of the epidemic size of the novel coronavirus (COVID-19) in Shahroud, Iran |
title | The basic reproduction number and prediction of the epidemic size of the novel coronavirus (COVID-19) in Shahroud, Iran |
title_full | The basic reproduction number and prediction of the epidemic size of the novel coronavirus (COVID-19) in Shahroud, Iran |
title_fullStr | The basic reproduction number and prediction of the epidemic size of the novel coronavirus (COVID-19) in Shahroud, Iran |
title_full_unstemmed | The basic reproduction number and prediction of the epidemic size of the novel coronavirus (COVID-19) in Shahroud, Iran |
title_short | The basic reproduction number and prediction of the epidemic size of the novel coronavirus (COVID-19) in Shahroud, Iran |
title_sort | basic reproduction number and prediction of the epidemic size of the novel coronavirus (covid-19) in shahroud, iran |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7322167/ https://www.ncbi.nlm.nih.gov/pubmed/32517845 http://dx.doi.org/10.1017/S0950268820001247 |
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