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Estimating the Number of COVID-19 Cases and Impact of New COVID-19 Variants and Vaccination on the Population in Kerman, Iran: A Mathematical Modeling Study

COVID-19 is spreading all over Iran, and Kerman is one of the most affected cities. We conducted this study to predict COVID-19-related deaths, hospitalization, and infected cases under different scenarios (scenarios A, B, and C) by 31 December 2021 in Kerman. We also aimed to assess the impact of n...

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Autores principales: Nakhaeizadeh, Mehran, Chegeni, Maryam, Adhami, Masoumeh, Sharifi, Hamid, Gohari, Milad Ahmadi, Iranpour, Abedin, Azizian, Mahdieh, Mashinchi, Mashaallah, Baneshi, Mohammad Reza, Karamouzian, Mohammad, Haghdoost, Ali Akbar, Jahani, Yunes
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9039779/
https://www.ncbi.nlm.nih.gov/pubmed/35495892
http://dx.doi.org/10.1155/2022/6624471
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author Nakhaeizadeh, Mehran
Chegeni, Maryam
Adhami, Masoumeh
Sharifi, Hamid
Gohari, Milad Ahmadi
Iranpour, Abedin
Azizian, Mahdieh
Mashinchi, Mashaallah
Baneshi, Mohammad Reza
Karamouzian, Mohammad
Haghdoost, Ali Akbar
Jahani, Yunes
author_facet Nakhaeizadeh, Mehran
Chegeni, Maryam
Adhami, Masoumeh
Sharifi, Hamid
Gohari, Milad Ahmadi
Iranpour, Abedin
Azizian, Mahdieh
Mashinchi, Mashaallah
Baneshi, Mohammad Reza
Karamouzian, Mohammad
Haghdoost, Ali Akbar
Jahani, Yunes
author_sort Nakhaeizadeh, Mehran
collection PubMed
description COVID-19 is spreading all over Iran, and Kerman is one of the most affected cities. We conducted this study to predict COVID-19-related deaths, hospitalization, and infected cases under different scenarios (scenarios A, B, and C) by 31 December 2021 in Kerman. We also aimed to assess the impact of new COVID-19 variants and vaccination on the total number of COVID-19 cases, deaths, and hospitalizations (scenarios D, E, and F) using the modified susceptible-exposed-infected-removed (SEIR) model. We calibrated the model using deaths reported from the start of the epidemic to August 30, 2021. A Monte Carlo Markov Chain (MCMC) uncertainty analysis was used to estimate 95% uncertainty intervals (UI). We also calculated the time-varying reproductive number (R(t)) following time-dependent methods. Under the worst-case scenario (scenario A; contact rate = 10, self‐isolation rate = 30%, and average vaccination shots per day = 5,000), the total number of infections by December 31, 2021, would be 1,625,000 (95% UI: 1,112,000–1,898,000) with 6,700 deaths (95% UI: 5,200–8,700). With the presence of alpha and delta variants without vaccine (scenario D), the total number of infected cases and the death toll were estimated to be 957,000 (95% UI: 208,000–1,463,000) and 4,500 (95% UI: 1,500–7,000), respectively. If 70% of the population were vaccinated when the alpha variant was dominant (scenario E), the total number of infected cases and deaths would be 608,000 (95% UI: 122,000–743,000) and 2,700 (95% UI: 700–4,000), respectively. The R(t) was ≥1 almost every day during the epidemic. Our results suggest that policymakers should concentrate on improving vaccination and interventions, such as reducing social contacts, stricter limitations for gathering, public education to promote social distancing, incensing case finding and contact tracing, effective isolation, and quarantine to prevent more COVID-19 cases, hospitalizations, and deaths in Kerman.
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spelling pubmed-90397792022-04-27 Estimating the Number of COVID-19 Cases and Impact of New COVID-19 Variants and Vaccination on the Population in Kerman, Iran: A Mathematical Modeling Study Nakhaeizadeh, Mehran Chegeni, Maryam Adhami, Masoumeh Sharifi, Hamid Gohari, Milad Ahmadi Iranpour, Abedin Azizian, Mahdieh Mashinchi, Mashaallah Baneshi, Mohammad Reza Karamouzian, Mohammad Haghdoost, Ali Akbar Jahani, Yunes Comput Math Methods Med Research Article COVID-19 is spreading all over Iran, and Kerman is one of the most affected cities. We conducted this study to predict COVID-19-related deaths, hospitalization, and infected cases under different scenarios (scenarios A, B, and C) by 31 December 2021 in Kerman. We also aimed to assess the impact of new COVID-19 variants and vaccination on the total number of COVID-19 cases, deaths, and hospitalizations (scenarios D, E, and F) using the modified susceptible-exposed-infected-removed (SEIR) model. We calibrated the model using deaths reported from the start of the epidemic to August 30, 2021. A Monte Carlo Markov Chain (MCMC) uncertainty analysis was used to estimate 95% uncertainty intervals (UI). We also calculated the time-varying reproductive number (R(t)) following time-dependent methods. Under the worst-case scenario (scenario A; contact rate = 10, self‐isolation rate = 30%, and average vaccination shots per day = 5,000), the total number of infections by December 31, 2021, would be 1,625,000 (95% UI: 1,112,000–1,898,000) with 6,700 deaths (95% UI: 5,200–8,700). With the presence of alpha and delta variants without vaccine (scenario D), the total number of infected cases and the death toll were estimated to be 957,000 (95% UI: 208,000–1,463,000) and 4,500 (95% UI: 1,500–7,000), respectively. If 70% of the population were vaccinated when the alpha variant was dominant (scenario E), the total number of infected cases and deaths would be 608,000 (95% UI: 122,000–743,000) and 2,700 (95% UI: 700–4,000), respectively. The R(t) was ≥1 almost every day during the epidemic. Our results suggest that policymakers should concentrate on improving vaccination and interventions, such as reducing social contacts, stricter limitations for gathering, public education to promote social distancing, incensing case finding and contact tracing, effective isolation, and quarantine to prevent more COVID-19 cases, hospitalizations, and deaths in Kerman. Hindawi 2022-04-26 /pmc/articles/PMC9039779/ /pubmed/35495892 http://dx.doi.org/10.1155/2022/6624471 Text en Copyright © 2022 Mehran Nakhaeizadeh et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Nakhaeizadeh, Mehran
Chegeni, Maryam
Adhami, Masoumeh
Sharifi, Hamid
Gohari, Milad Ahmadi
Iranpour, Abedin
Azizian, Mahdieh
Mashinchi, Mashaallah
Baneshi, Mohammad Reza
Karamouzian, Mohammad
Haghdoost, Ali Akbar
Jahani, Yunes
Estimating the Number of COVID-19 Cases and Impact of New COVID-19 Variants and Vaccination on the Population in Kerman, Iran: A Mathematical Modeling Study
title Estimating the Number of COVID-19 Cases and Impact of New COVID-19 Variants and Vaccination on the Population in Kerman, Iran: A Mathematical Modeling Study
title_full Estimating the Number of COVID-19 Cases and Impact of New COVID-19 Variants and Vaccination on the Population in Kerman, Iran: A Mathematical Modeling Study
title_fullStr Estimating the Number of COVID-19 Cases and Impact of New COVID-19 Variants and Vaccination on the Population in Kerman, Iran: A Mathematical Modeling Study
title_full_unstemmed Estimating the Number of COVID-19 Cases and Impact of New COVID-19 Variants and Vaccination on the Population in Kerman, Iran: A Mathematical Modeling Study
title_short Estimating the Number of COVID-19 Cases and Impact of New COVID-19 Variants and Vaccination on the Population in Kerman, Iran: A Mathematical Modeling Study
title_sort estimating the number of covid-19 cases and impact of new covid-19 variants and vaccination on the population in kerman, iran: a mathematical modeling study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9039779/
https://www.ncbi.nlm.nih.gov/pubmed/35495892
http://dx.doi.org/10.1155/2022/6624471
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