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Coupling between infectious diseases leads to synchronization of their dynamics

Jorge P Rodríguez1, Víctor M Eguíluz2

  • 1Instituto Mediterráneo de Estudios Avanzados (IMEDEA), CSIC-UIB, 07190 Esporles, Spain.

Chaos (Woodbury, N.Y.)
|March 1, 2023
PubMed

Insights

Disease interactions create modeling uncertainty. This study shows cooperative or competitive interactions synchronize infections, like COVID-19 and influenza, impacting disease dynamics.

Area of Science:

  • Epidemiology
  • Mathematical Modeling
  • Infectious Disease Dynamics

Background:

  • Interactions between diseases can alter individual disease trajectories.
  • Distinguishing symptoms of co-occurring infections complicates epidemiological modeling.
  • Existing models often simplify disease interactions, necessitating more comprehensive frameworks.

Purpose of the Study:

  • To generalize existing models of interacting infections to non-symmetric scenarios.
  • To investigate the impact of cooperative and competitive interactions on disease dynamics.
  • To model the coupled dynamics of COVID-19 and seasonal influenza.

Main Methods:

  • Developed a generalized mathematical model for interacting infections, accommodating non-symmetric interactions.
  • Simulated scenarios of cooperation, competition, and asymmetric coupling between disease dynamics.
  • Applied the framework to model the interaction between COVID-19 and seasonal influenza.

Main Results:

  • Both cooperative and competitive interactions lead to the synchronization of the maximum fraction of infected individuals.
  • The coupling of disease dynamics synchronizes both COVID-19 and influenza.
  • Influenza dynamics exhibit a stronger influence from the interaction compared to COVID-19.

Conclusions:

  • Disease interactions, even non-symmetric ones, tend to synchronize infection peaks.
  • Modeling coupled disease dynamics is crucial for understanding and predicting epidemiological outcomes.
  • The interaction between COVID-19 and influenza demonstrates significant synchronization effects, particularly on influenza patterns.

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