Abstract
Background. Human behaviour, economic activity, vaccination, and social distancing are inseparably entangled in epidemic management. This study aims to investigate the effects of various parameters such as stay-at-home restrictions, work hours, vaccination, and social distance on the containment of pandemics such as COVID-19. Methods. To achieve this, we have developed an agent based model based on a time-dynamic graph with stochastic transmission events. The graph is constructed from a real-world social network. The edges of graph have been categorized into three categories: home, workplaces, and social environment. The conditions needed to mitigate the spread of wild-type COVID-19 and the delta variant have been analyzed. Our purposeful agent based model has carefully executed tens of thousands of individual-based simulations. We propose simple relationships for the trade-offs between effective reproduction number (Re), transmission rate, working hours, vaccination, and stay-at-home restrictions. Results. We have found that the effect of a 13.6% increase in vaccination for wild-type (WT) COVID-19 is equivalent to reducing four hours of work or a one-day stay-at-home restriction. For the delta, 20.2% vaccination has the same effect. Also, since we can keep track of household and non-household infections, we observed that the change in household transmission rate does not significantly alter the Re. Household infections are not limited by transmission rate due to the high frequency of connections. For the specifications of COVID-19, the Re depends on the non-household transmissions rate. Conclusions. Our findings highlight that decreasing working hours is the least effective among the non-pharmaceutical interventions. Our results suggest that policymakers decrease work-related activities as a last resort and should probably not do so when the effects are minimal, as shown. Furthermore, the enforcement of stay-at-home restrictions is moderately effective and can be used in conjunction with other measures if absolutely necessary.
Original language | English |
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Article number | 14353 |
Journal | PeerJ |
Volume | 10 |
DOIs | |
Publication status | Published - Dec 2022 |
Bibliographical note
Publisher Copyright:Copyright 2022 Nashebi et al.
Funding
This work was supported by TUBITAK, 2232 - International Fellowship for Outstanding Researchers, Project number 118C244. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Funders | Funder number |
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Türkiye Bilimsel ve Teknolojik Araştırma Kurumu | 118C244 |
Keywords
- Agent-based model
- COVID-19
- Household transmission
- Pandemic
- Social network
- Stay-at-home policy
- Working hours