The ghost of infections past: Accounting for heterogeneity in individual infection history improves accuracy in epidemic forecasting

Variation in infection history is an important but often underappreciated driver of individual variability in responses to infections. Such individual heterogeneity in immune responses, stemming from variable previous exposure to pathogens, subsequently influences epidemiological outcomes. By comparing research on innate immune priming in invertebrates, which lack adaptive immune memory but demonstrate enhanced responses to re-infections, to patterns seen in vertebrates, this Essay reveals broad implications for disease dynamics. Insights from mathematical modelling and experimental data highlight the critical need to integrate evolutionary disease ecology into public health initiatives to better predict and manage infectious diseases.

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Publication Details

Journal
PLoS Biology
Published
2025-08-11
DOI
https://doi.org/10.1371/journal.pbio.3003311
Primary Topic
Evolution and Genetic Dynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

The ghost of infections past: Accounting for heterogeneity in individual infection history improves accuracy in epidemic forecasting

Mike Boots, Pedro F. Vale, Chadi M. Saad-Roy
PLoS Biology
Evolution and Genetic Dynamics
article

The ghost of infections past: Accounting for heterogeneity in individual infection history improves accuracy in epidemic forecasting

Mike Boots, Pedro F. Vale, Chadi M. Saad-Roy
article en

Abstract

Variation in infection history is an important but often underappreciated driver of individual variability in responses to infections. Such individual heterogeneity in immune responses, stemming from variable previous exposure to pathogens, subsequently influences epidemiological outcomes. By comparing research on innate immune priming in invertebrates, which lack adaptive immune memory but demonstrate enhanced responses to re-infections, to patterns seen in vertebrates, this Essay reveals broad implications for disease dynamics. Insights from mathematical modelling and experimental data highlight the critical need to integrate evolutionary disease ecology into public health initiatives to better predict and manage infectious diseases.

PLoS BiologyVol. 23(8)
Miller College (US), University of California, Berkeley (US), University of Edinburgh (GB)
National Science Foundation, Adolph C. and Mary Sprague Miller Institute for Basic Research in Science, University of California Berkeley, Natural Environment Research Council
Good health and well-being
Openalex Percentile: Top 77%
Evolution and Genetic Dynamics
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