Extreme mortality during a historical measles outbreak on Rotuma is consistent with measles immunosuppression

Susie Cant1,2, G Dennis Shanks3, Matt J Keeling1,2,4

  • 1Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Coventry, UK.

PubMed

Insights

Measles epidemics devastated Pacific Island populations. This study models the 1911 Rotuma measles epidemic, showing immunosuppression significantly impacted mortality patterns and disease spread.

Area of Science:

  • Epidemiology
  • Immunology
  • Mathematical Modeling

Background:

  • Measles introduction to previously unexposed Pacific Island populations caused severe mortality.
  • The 1911 Rotuma, Fiji measles epidemic resulted in a 13% population loss.
  • Mortality data revealed two peaks, suggesting secondary causes of death following measles.

Purpose of the Study:

  • To investigate the role of measles-induced immunosuppression in the observed mortality patterns during the 1911 Rotuma epidemic.
  • To determine if secondary infections or dysregulated immune responses contributed to the second mortality peak.
  • To assess the impact of including immunosuppression in epidemiological models for measles.

Main Methods:

  • Utilized a compartmental model to simulate measles infection dynamics.
  • Incorporated the concept of immunosuppression following measles infection.
  • Modeled vulnerability to secondary infectious agents or pre-existing microbial imbalances during immunosuppression.

Main Results:

  • Both models, considering a new pathogen or existing microbes during immunosuppression, plausibly fit the observed mortality data.
  • Including immunosuppression in the model provided more realistic estimates of measles epidemiological parameters.
  • The findings support the hypothesis that measles-induced immune dysfunction contributed to the epidemic's mortality profile.

Conclusions:

  • Measles-induced immunosuppression is a critical factor in understanding severe measles epidemics.
  • Mathematical modeling incorporating immunosuppression enhances the accuracy of epidemiological parameter estimation.
  • This approach offers a more comprehensive understanding of measles' impact on vulnerable populations.

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