Estimating the Size of the Hidden Population of COVID-19


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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.

Sobre autores

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

Autor responsável pela correspondência
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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