Estimating the Size of the Hidden Population of COVID-19
- Авторлар: Mehraeen E.1, Akhtaran F.2, Faridrohani M.2, Afzalian A.3, Mojdeganlou H.4, Ghanbari Z.5, Fathzadeh Y.6, Gholizadeh M.6, SeyedAlinaghi S.7, Hackett D.8
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Мекемелер:
- Department of Health Information Technology, Khalkhal University of Medical Sciences
- Faculty of Mathematical Sciences, Shahid Beheshti University
- School of medicine, Tehran University of Medical Sciences
- Department of Pathology, The Johns Hopkins University, School of Medicine
- Student Research Committee, Khalkhal University of medical science
- Student Research Committee, Khalkhal University of medical sciences
- Iranian Research Center for HIV/AIDS, Iranian Institute for Reduction of High-Risk Behaviors, Tehran University of Medical Science
- Physical Activity, Lifestyle, Ageing and Wellbeing Faculty Research Group, School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney
- Шығарылым: Том 24, № 2 (2024)
- Бөлім: Medicine
- URL: https://gynecology.orscience.ru/1871-5265/article/view/645497
- DOI: https://doi.org/10.2174/0118715265255039231018113634
- ID: 645497
Дәйексөз келтіру
Толық мәтін
Аннотация
Introduction:An asymptomatic population has the same infection as symptomatic individuals, so these individuals can unknowingly spread the virus. It is not possible to predict the rate of epidemic growth by considering only the identified isolated or hospitalized population. In this study, we want to estimate the size of the COVID-19 population, based on information derived from patients visiting medical centers. So, individuals who do not receive a formal diagnosis in those medical centers can be considered as hidden.
Methodology:To estimate the Bayesian size of the hidden population of COVID-19 a respondentdriven sampling (RDS) method was used. Twenty-three people infected with COVID-19 seeds and who had positive PCR test results were selected as seeds. These participants were asked whether any of their friends and acquaintances who had COVID-19 did not visit a medical center or hid their illness. Access to other patients was gained through friendship and kinship, hence allowing the sampling process to proceed.
Results:Out of 23 selected seeds, only 15 seeds remained in the sample and the rest were excluded due to not participating in the further sampling process. After 5 waves, 50 people with COVID-19 who had hidden their disease and were not registered in the official statistics were included in the sample. It was estimated that 12,198 people were infected with COVID-19 in Khalkhal city in 2022. This estimate was much higher than recorded in the official COVID-19 statistics.
Conclusions:The study findings indicate that the estimated 'true' numbers of COVID-19 patients in one town in Iran were significantly higher compared to the official numbers. The RDS method can help capture the potential size of infections in further pandemics or outbreaks globally.
Негізгі сөздер
Авторлар туралы
Esmaeil Mehraeen
Department of Health Information Technology, Khalkhal University of Medical Sciences
Email: info@benthamscience.net
Fatemeh Akhtaran
Faculty of Mathematical Sciences, Shahid Beheshti University
Email: info@benthamscience.net
Mohammad Faridrohani
Faculty of Mathematical Sciences, Shahid Beheshti University
Email: info@benthamscience.net
Arian Afzalian
School of medicine, Tehran University of Medical Sciences
Email: info@benthamscience.net
Hengameh Mojdeganlou
Department of Pathology, The Johns Hopkins University, School of Medicine
Email: info@benthamscience.net
Zeinab Ghanbari
Student Research Committee, Khalkhal University of medical science
Email: info@benthamscience.net
Yasamin Fathzadeh
Student Research Committee, Khalkhal University of medical sciences
Email: info@benthamscience.net
Mohadeseh Gholizadeh
Student Research Committee, Khalkhal University of medical sciences
Email: info@benthamscience.net
SeyedAhmad SeyedAlinaghi
Iranian Research Center for HIV/AIDS, Iranian Institute for Reduction of High-Risk Behaviors, Tehran University of Medical Science
Хат алмасуға жауапты Автор.
Email: info@benthamscience.net
Daniel Hackett
Physical Activity, Lifestyle, Ageing and Wellbeing Faculty Research Group, School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney
Email: info@benthamscience.net
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