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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.
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.
  • Nakhaeizadeh M; Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
  • Chegeni M; Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran.
  • Adhami M; Department of Basic and Medical Laboratory Sciences, Khomein University of Medical Sciences, Khomein, Iran.
  • Sharifi H; Molecular and Medicine Research Center, Khomein University of Medical Sciences, Khomein, Iran.
  • Gohari MA; Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
  • Iranpour A; HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
  • Azizian M; Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
  • Mashinchi M; Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran.
  • Baneshi MR; HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
  • Karamouzian M; Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
  • Haghdoost AA; Department of General Educations, Afzalipour School of Medicine, Kerman University of Medical Sciences, Kerman, Iran.
  • Jahani Y; Department of Statistics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran.
Comput Math Methods Med ; 2022: 6624471, 2022.
Article in English | MEDLINE | ID: covidwho-1816854
ABSTRACT
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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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Topics: Vaccines / Variants Limits: Humans Country/Region as subject: Asia Language: English Journal: Comput Math Methods Med Journal subject: Medical Informatics Year: 2022 Document Type: Article Affiliation country: 2022

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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Topics: Vaccines / Variants Limits: Humans Country/Region as subject: Asia Language: English Journal: Comput Math Methods Med Journal subject: Medical Informatics Year: 2022 Document Type: Article Affiliation country: 2022