Preparing for the Next Pandemic: Learning Lessons from the Recent Past

Bret D. Elderd (), Tad Dallas (), Grant Foster () and Robert L. Richards ()
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Bret D. Elderd: Louisiana State University, Department of Biological Sciences
Tad Dallas: University of South Carolina, Department of Biological Sciences
Grant Foster: University of South Carolina, Department of Biological Sciences
Robert L. Richards: Georgia Institute of Technology, School of Biological Sciences

A chapter in Handbook of Visual, Experimental and Computational Mathematics, 2026, pp 1587-1601 from Springer

Abstract: Abstract While the initial waves of the COVID-19 pandemic have long come to a close, the pandemic presents an opportunity to learn from the recent past in order to prepare for the next one. Throughout the COVID-19 pandemic, vaccination rates were high in some parts of the world and stalled in others as new variants emerged. Non-pharmaceutical interventions (NPIs) played an important role in limiting COVID-19 spread. But, how important of a role? Using a Susceptible-Exposed-Asymptomatic-Infected-Recovered (SEAIR) model, the proportion of the population that followed NPI guidelines (e.g., wearing a mask) were varied while changing the ratio of vaccinations that were given to individuals that follow NPI guidelines to those individuals that do not follow established guidelines. For each of the scenarios, the peak number of infections and overall number of infections during the outbreak were tracked. Both metrics can be considered gauges of hospital and societal burden associated with the disease. The simulations show NPIs are effective at controlling outbreaks. However, when relatively few individuals comply with NPI guidelines, the most effective strategy to decrease burden becomes prioritizing the vaccination of the non-compliers – those not conforming to NPI guidelines. With that in mind, vaccination campaigns focused on specific groups such as individuals not following suggested NPI guidelines may be the best way to increase vaccination uptake, help stop the spread of the disease, and decrease overall societal burden. The results lend insight into potential mitigation strategies that should be considered during the next pandemic, which is surely closer than one thinks.

Keywords: SEAIR model; Pandemic; COVID-19; Stochastic dynamics; Hospital burden; Societal burden (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-3-032-16368-4_49

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