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Exploring how ecological and epidemiological processes shape multi-host disease dynamics using global sensitivity

Kalpana Hanthanan Arachchilage1, Mohammed Y Hussaini1, N G Cogan1

  • 1Department of Mathematics, Florida State University, Tallahassee, Fl, 32306, USA.

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|May 8, 2023
PubMed
Summary
This summary is machine-generated.

Global sensitivity analysis reveals how ecological and epidemiological factors influence disease spread in two-host systems. Understanding these dynamics is key to predicting pathogen behavior and managing outbreaks.

Keywords:
DaphniaDilution effectEnvironmental transmissionGlobal sensitivity analysisPartial rank correlation coefficient

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Area of Science:

  • Ecology
  • Epidemiology
  • Mathematical Biology

Background:

  • Understanding disease dynamics in multi-host systems is complex.
  • Ecological interactions and pathogen transmission pathways significantly influence disease spread.
  • Sensitivity analysis offers a method to dissect these complex interactions.

Purpose of the Study:

  • To explore the roles of ecological and epidemiological processes in shaping disease dynamics.
  • To compute and interpret the sensitivities of disease prevalence to model parameters in a two-host system.
  • To contrast these sensitivities under different introduction scenarios (pathogen vs. host introduction).

Main Methods:

  • Utilized global sensitivity analysis, specifically Partial Rank Correlation Coefficients (PRCC).
  • Developed and parameterized a SIR-type model for two host species and an environmentally transmitted pathogen.
  • Calculated and biologically interpreted sensitivity rankings for disease prevalence in each host.

Main Results:

  • Sensitivity rankings varied depending on host species characteristics (competitive ability, disease competence) and system conditions (invader vs. resident).
  • When a pathogen is introduced, disease prevalence is more sensitive to the first host's burst size than the second.
  • Disease prevalence in each host is more sensitive to its own infection rate than the other host's infection rate.

Conclusions:

  • Global sensitivity analysis provides valuable insights into disease dynamics shaped by ecological and epidemiological processes.
  • The influence of these processes varies across time and system conditions.
  • Sensitivity analysis offers a quantitative approach to exploring and validating biological hypotheses in disease ecology.