Symptom propagation in respiratory pathogens of public health concern: a review of the evidence

Phoebe Asplin*, Rebecca Mancy, Thomas Finnie, Fergus Cumming, Matt J. Keeling, Edward M. Hill

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

2 Citations (Scopus)

Abstract

Symptom propagation occurs when the symptom set an individual experiences is correlated with the symptom set of the individual who infected them. Symptom propagation may dramatically affect epidemiological outcomes, potentially causing clusters of severe disease. Conversely, it could result in chains of mild infection, generating widespread immunity with minimal cost to public health. Despite accumulating evidence that symptom propagation occurs for many respiratory pathogens, the underlying mechanisms are not well understood. Here, we conducted a scoping literature review for 14 respiratory pathogens to ascertain the extent of evidence for symptom propagation by two mechanisms: dose-severity relationships and route-severity relationships. We identify considerable heterogeneity between pathogens in the relative importance of the two mechanisms, highlighting the importance of pathogen-specific investigations. For almost all pathogens, including influenza and SARS-CoV-2, we found support for at least one of the two mechanisms. For some pathogens, including influenza, we found convincing evidence that both mechanisms contribute to symptom propagation. Furthermore, infectious disease models traditionally do not include symptom propagation. We summarize the present state of modelling advancements to address the methodological gap. We then investigate a simplified disease outbreak scenario, finding that under strong symptom propagation, isolating mildly infected individuals can have negative epidemiological implications.

Original languageEnglish
Article number20240009
JournalJournal of the Royal Society Interface
Volume21
Issue number216
DOIs
Publication statusPublished - 2024

Bibliographical note

Publisher Copyright:
© 2024 The Authors.

Keywords

  • SARS-CoV-2
  • influenza
  • mathematical modelling
  • respiratory pathogens
  • symptom propagation
  • symptom severity

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