Using a real-world network to model the tradeoff between stay-at-home restriction, vaccination, social distancing and working hours on COVID-19 dynamics.
Nashebi, R.; Sari, M.; Kotil, S.
Show abstract
BackgroundHuman behavior, 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. MethodsTo achieve this, we 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 graphs edges have been categorized into three categories: home, workplaces, and social environment. The conditions needed to mitigate the spread of wild-type (WT) 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, work hours, vaccination, and stay at home restrictions. ResultsFor the WT, it has been found that a 13% increase in vaccination impacts the reproduction number, like the magnitude of decreasing nine hours of work to four and a single day of stay-at-home order. For the delta, 16% 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 COVID-19s specifications, the Re depends on the non-household transmissions rate. ConclusionsAll measures are worth considering. Vaccination and transmission reduction are almost interchangeable. Without vaccination or teaching people how to lower their transmission probability significantly, changing work hours or weekend restrictions will only make people more frustrated
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Analysis of mitigation of Covid-19 outbreaks in workplaces and schools by hybrid telecommuting 98%
- Novel travel time aware metapopulation models and multi-layer waning immunity for late-phase epidemic and endemic scenarios 97%
- An integrated framework for building trustworthy data-driven epidemiological models: Application to the COVID-19 outbreak in New York City 97%
Similar papers in this journal
- Beyond six feet: The collective behavior of social distancing 98%
- Countering the potential re-emergence of a deadly infectious disease - information warfare, identifying strategic threats, launching countermeasures 98%
- Dynamical SPQEIR model assesses the effectiveness of non-pharmaceutical interventions against COVID-19 epidemic outbreaks 98%
Similar papers in this journal
- Modeling the Effect of Lockdown Timing as a COVID-19 Control Measure in Countries with Differing Social Contacts 97%
- Tracing contacts to evaluate the transmission of COVID-19 from highly exposed individuals in public transportation 97%
- Ranking the Effectiveness of Non-Pharmaceutical Interventions to Counter COVID-19 in UK Universities with Vaccinated Population 96%
Similar papers in this journal
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.