PLoS Computational Biology (Aug 2024)

Quantifying the risk of spillover reduction programs for human health.

  • Scott L Nuismer,
  • Andrew J Basinski,
  • Courtney L Schreiner,
  • Evan A Eskew,
  • Elisabeth Fichet-Calvet,
  • Christopher H Remien

DOI
https://doi.org/10.1371/journal.pcbi.1012358
Journal volume & issue
Vol. 20, no. 8
p. e1012358

Abstract

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Reducing spillover of zoonotic pathogens is an appealing approach to preventing human disease and minimizing the risk of future epidemics and pandemics. Although the immediate human health benefit of reducing spillover is clear, over time, spillover reduction could lead to counterintuitive negative consequences for human health. Here, we use mathematical models and computer simulations to explore the conditions under which unanticipated consequences of spillover reduction can occur in systems where the severity of disease increases with age at infection. Our results demonstrate that, because the average age at infection increases as spillover is reduced, programs that reduce spillover can actually increase population-level disease burden if the clinical severity of infection increases sufficiently rapidly with age. If, however, immunity wanes over time and reinfection is possible, our results reveal that negative health impacts of spillover reduction become substantially less likely. When our model is parameterized using published data on Lassa virus in West Africa, it predicts that negative health outcomes are possible, but likely to be restricted to a small subset of populations where spillover is unusually intense. Together, our results suggest that adverse consequences of spillover reduction programs are unlikely but that the public health gains observed immediately after spillover reduction may fade over time as the age structure of immunity gradually re-equilibrates to a reduced force of infection.