Cargando…
Time-discrete SIR model for COVID-19 in Fiji
Using the data provided by Fiji's ministry of health and medical services, we apply an implicit time-discrete SIR (susceptible people–infectious people–removed people) model that tracks the transmission and recovering rate at time, t to predict the trend of the coronavirus disease 2019 (COVID-1...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9043634/ https://www.ncbi.nlm.nih.gov/pubmed/35387697 http://dx.doi.org/10.1017/S0950268822000590 |
_version_ | 1784694925407813632 |
---|---|
author | Singh, Rishal Amar Lal, Rajnesh Kotti, Ramanuja Rao |
author_facet | Singh, Rishal Amar Lal, Rajnesh Kotti, Ramanuja Rao |
author_sort | Singh, Rishal Amar |
collection | PubMed |
description | Using the data provided by Fiji's ministry of health and medical services, we apply an implicit time-discrete SIR (susceptible people–infectious people–removed people) model that tracks the transmission and recovering rate at time, t to predict the trend of the coronavirus disease 2019 (COVID-19) pandemic in Fiji. The model implied time-varying transmission and recovery rates were calculated from 4 May 2021 to 9 October 2021. The estimator functions for these rates were determined, and a short-term (30 days) forecast was done. The model was validated with observed values of the active and recovered cases from 11 October 2021 to 9 December 2021. Statistical results reveal a good fit of profiles between model simulated and the reported COVID-19 data. The gradual decrease of the time-varying basic reproduction number with values below one towards the end of the study period suggest the government's success in controlling the epidemic. The mean reproduction number for the second wave of COVID-19 in Fiji was estimated as 2.7818. The results from this study can be used by researchers, the Fijian government, and the relevant health policy makers in making informed decisions should a third COVID-19 wave occur. |
format | Online Article Text |
id | pubmed-9043634 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-90436342022-04-28 Time-discrete SIR model for COVID-19 in Fiji Singh, Rishal Amar Lal, Rajnesh Kotti, Ramanuja Rao Epidemiol Infect Original Paper Using the data provided by Fiji's ministry of health and medical services, we apply an implicit time-discrete SIR (susceptible people–infectious people–removed people) model that tracks the transmission and recovering rate at time, t to predict the trend of the coronavirus disease 2019 (COVID-19) pandemic in Fiji. The model implied time-varying transmission and recovery rates were calculated from 4 May 2021 to 9 October 2021. The estimator functions for these rates were determined, and a short-term (30 days) forecast was done. The model was validated with observed values of the active and recovered cases from 11 October 2021 to 9 December 2021. Statistical results reveal a good fit of profiles between model simulated and the reported COVID-19 data. The gradual decrease of the time-varying basic reproduction number with values below one towards the end of the study period suggest the government's success in controlling the epidemic. The mean reproduction number for the second wave of COVID-19 in Fiji was estimated as 2.7818. The results from this study can be used by researchers, the Fijian government, and the relevant health policy makers in making informed decisions should a third COVID-19 wave occur. Cambridge University Press 2022-04-07 /pmc/articles/PMC9043634/ /pubmed/35387697 http://dx.doi.org/10.1017/S0950268822000590 Text en © The Author(s) 2022 https://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, provided the original article is properly cited. |
spellingShingle | Original Paper Singh, Rishal Amar Lal, Rajnesh Kotti, Ramanuja Rao Time-discrete SIR model for COVID-19 in Fiji |
title | Time-discrete SIR model for COVID-19 in Fiji |
title_full | Time-discrete SIR model for COVID-19 in Fiji |
title_fullStr | Time-discrete SIR model for COVID-19 in Fiji |
title_full_unstemmed | Time-discrete SIR model for COVID-19 in Fiji |
title_short | Time-discrete SIR model for COVID-19 in Fiji |
title_sort | time-discrete sir model for covid-19 in fiji |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9043634/ https://www.ncbi.nlm.nih.gov/pubmed/35387697 http://dx.doi.org/10.1017/S0950268822000590 |
work_keys_str_mv | AT singhrishalamar timediscretesirmodelforcovid19infiji AT lalrajnesh timediscretesirmodelforcovid19infiji AT kottiramanujarao timediscretesirmodelforcovid19infiji |