Increased frequency of travel in the presence of cross-immunity may act to decrease the chance of a global pandemic

Philos Trans R Soc Lond B Biol Sci. 2019 Jun 24;374(1775):20180274. doi: 10.1098/rstb.2018.0274.

Abstract

The high frequency of modern travel has led to concerns about a devastating pandemic since a lethal pathogen strain could spread worldwide quickly. Many historical pandemics have arisen following pathogen evolution to a more virulent form. However, some pathogen strains invoke immune responses that provide partial cross-immunity against infection with related strains. Here, we consider a mathematical model of successive outbreaks of two strains-a low virulence (LV) strain outbreak followed by a high virulence (HV) strain outbreak. Under these circumstances, we investigate the impacts of varying travel rates and cross-immunity on the probability that a major epidemic of the HV strain occurs, and the size of that outbreak. Frequent travel between subpopulations can lead to widespread immunity to the HV strain, driven by exposure to the LV strain. As a result, major epidemics of the HV strain are less likely, and can potentially be smaller, with more connected subpopulations. Cross-immunity may be a factor contributing to the absence of a global pandemic as severe as the 1918 influenza pandemic in the century since. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'.

Keywords: antigenic variation; cross-immunity; major epidemic; mathematical modelling; pathogen diversity.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cross Protection
  • Disease Outbreaks
  • Global Health
  • Humans
  • Influenza A virus / immunology
  • Influenza A virus / pathogenicity
  • Influenza A virus / physiology
  • Influenza, Human / epidemiology
  • Influenza, Human / immunology*
  • Influenza, Human / transmission*
  • Models, Theoretical
  • Pandemics
  • Probability
  • Travel* / statistics & numerical data
  • Virulence

Associated data

  • figshare/10.6084/m9.figshare.c.4438796