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Computing R 0 of dynamic models by a definition-based method.

Xiaohao Guo1, Yichao Guo1, Zeyu Zhao1,2

  • 1State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, 361102, Fujian Province, People's Republic of China.

Infectious Disease Modelling
|June 15, 2022
PubMed
Summary
This summary is machine-generated.

A new definition-based method (DBM) offers a more interpretable way to calculate the basic reproduction number (R0) in epidemiological models compared to the next-generation matrix (NGM). DBM provides a better understanding of disease transmission dynamics, especially in complex models.

Keywords:
Basic reproduction numberDefinition-based methodDynamics modelNext-generation method

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Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Public Health

Background:

  • Calculating the basic reproduction number (R0) is crucial for understanding disease spread in public health.
  • The widely used next-generation methods (NGM) often yield a threshold quantity lacking clear epidemiological interpretation.
  • There is a need for methods that provide a more interpretable R0.

Purpose of the Study:

  • To propose a definition-based method (DBM) for computing the basic reproduction number (R0).
  • To compare the DBM with the existing next-generation methods (NGM).
  • To provide a more interpretable R0 for deterministic dynamical models.

Main Methods:

  • The study defines R0 based on its fundamental epidemiological meaning.
  • It considers various states of an infected individual and calculates expectations.
  • Numerical verification was performed using COVID-19 data from Hunan Province, comparing DBM and NGM.

Main Results:

  • DBM and NGM produced identical results for simple single-host models.
  • Differences emerged in models partitioned into subgroups, where DBM offered clearer interpretations.
  • Numerical verification confirmed consistencies and differences, supporting DBM's superior interpretability.

Conclusions:

  • The definition-based method (DBM) is more suitable for single-host epidemiological models, particularly those with subgroups.
  • DBM provides a more accurate and interpretable basic reproduction number (R0).
  • For multi-host models where R0 is difficult to define, NGM can still serve as a useful threshold indicator.