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

## TL;DR

This paper argues that individual differences in past infections affect immune responses and should be considered to improve epidemic predictions.

## Contribution

It highlights the importance of integrating evolutionary disease ecology into public health for better infectious disease forecasting.

## Key findings

- Individual immune responses vary due to differing past pathogen exposures.
- Innate immune priming in invertebrates shows parallels to vertebrate immune memory.
- Mathematical models and experiments support the need for improved forecasting methods.

## 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.

Variable pathogen exposure history contributes to individual immune differences, complicating epidemic forecasting. This Essay argues that experimental disease ecology can offer powerful tools and approaches to better understand and predict the epidemiological consequences of variable infection history.