Behaviour quantification of public health policy adoption - the case of non-pharmaceutical measures during COVID-19

Rhiannon Loster; Sarah Smook; Lia Humphrey; David Lyver; Zahra Mohammadi; Edward W. Thommes; Monica G. Cojocaru; Rhiannon Loster; Sarah Smook; Lia Humphrey; David Lyver; Zahra Mohammadi; Edward W. Thommes; Monica G. Cojocaru

doi:10.3934/mbe.2025033

Mathematical Biosciences and Engineering

2025, Volume 22, Issue 4: 920-942. doi: 10.3934/mbe.2025033

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Behaviour quantification of public health policy adoption - the case of non-pharmaceutical measures during COVID-19

1.
Department of Mathematics, University of Guelph, 50 Stone Rd E, Guelph, ON N1G 2W1, Canada
2.
Sanofi, 1755 Steeles Ave W, North York, ON M2R 3T4, Canada

Received: 05 September 2024 Revised: 19 November 2024 Accepted: 05 December 2024 Published: 10 March 2025

In this work, we provide estimates of non-pharmaceutical interventions (NPIs) adoption and its effects on the COVID-19 disease transmission across the province of Ontario, Canada, in 2020. Using freely available data, we estimate perceived risks of infection and a personal discomfort with complying with NPIs for Ontarians across 34 public health units. With the use of game theory, we model a time series of decision making processes in each public health region to extract an estimate of the adoption level of NPIs from March to December 2020. In conjunction with a susceptible-exposed-recovered-isolated compartmental model for Ontario, we are able to estimate a province-wide effectiveness level of NPIs. Last but not least, we show the model's versatility by applying it to Pennsylvania and Georgia in the United States.
- non-pharmaceutical interventions,
- game theory and decision making models,
- Nash equilibrium,
- behavioural epidemiology,
- COVID-19,
- infectious disease
Citation: Rhiannon Loster, Sarah Smook, Lia Humphrey, David Lyver, Zahra Mohammadi, Edward W. Thommes, Monica G. Cojocaru. Behaviour quantification of public health policy adoption - the case of non-pharmaceutical measures during COVID-19[J]. Mathematical Biosciences and Engineering, 2025, 22(4): 920-942. doi: 10.3934/mbe.2025033

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Abstract

In this work, we provide estimates of non-pharmaceutical interventions (NPIs) adoption and its effects on the COVID-19 disease transmission across the province of Ontario, Canada, in 2020. Using freely available data, we estimate perceived risks of infection and a personal discomfort with complying with NPIs for Ontarians across 34 public health units. With the use of game theory, we model a time series of decision making processes in each public health region to extract an estimate of the adoption level of NPIs from March to December 2020. In conjunction with a susceptible-exposed-recovered-isolated compartmental model for Ontario, we are able to estimate a province-wide effectiveness level of NPIs. Last but not least, we show the model's versatility by applying it to Pennsylvania and Georgia in the United States.

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