Open AccessPrevalence and transmission of COVID‐19 in community and household levels of Bangladesh: Longini and Koopman epidemic modelling approach
Author(s) -
Rahman Atikur,
Marjan Nahyatul,
Afroz Nahida,
Afroz Nilima,
Hossain Zakir
Publication year - 2021
Publication title -
international journal of clinical practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.756
H-Index - 98
eISSN - 1742-1241
pISSN - 1368-5031
DOI - 10.1111/ijcp.14921
Subject(s) - pandemic , transmission (telecommunications) , context (archaeology) , medicine , covid-19 , markov chain monte carlo , demography , environmental health , bayesian probability , geography , statistics , computer science , disease , mathematics , telecommunications , archaeology , pathology , sociology , infectious disease (medical specialty)
Aim To estimate the prevalence of COVID‐19 pandemic and its transmission rates among people in both community and household levels of Bangladesh. Methods We use the cross‐sectional online survey data of 2080 individuals, collected from 442 households during June to September 2020 in Bangladesh. The Longini and Koopman stochastic epidemic modelling approach was adapted for analysing the data. To validate the results, a simulation study was conducted using the Markov Chain Monte Carlo (MCMC) method via the Metropolis‐Hastings algorithm in the context of the Bayesian framework. Results Overall, the prevalence of COVID‐19 pandemic was 15.1% (315 out of 2080) among people in Bangladesh. This proportion was higher in smaller households (size one: 40.0%, two: 35.7% and three: 25.9%) than larger (four: 15.8%, five: 13.3%, six: 14.1%, seven: 12.5% eight: 8.7%, nine: 14.8% and ten or eleven: 5.7%). The transmission rate of COVID‐19 in community people was higher (12.0%, 95% CI: 10.0% to 13.0%) than household members (9.0%, 95% CI: 6.0% to 11.0%). Conclusion The susceptible individuals have a higher risk of community infection than the household and the community transmission is more responsible than the household for COVID‐19 pandemic in Bangladesh.