A model of behavioural response to risk accurately predicts the statistical distribution of COVID-19 infection and reproduction numbers.
Sci Rep
; 13(1): 2435, 2023 02 10.
Article
in En
| MEDLINE
| ID: mdl-36765110
ABSTRACT
One clear aspect of behaviour in the COVID-19 pandemic has been people's focus on, and response to, reported or observed infection numbers in their community. We describe a simple model of infectious disease spread in a pandemic situation where people's behaviour is influenced by the current risk of infection and where this behavioural response acts homeostatically to return infection risk to a certain preferred level. This homeostatic response is active until approximate herd immunity is reached in this domain the model predicts that the reproduction rate R will be centred around a median of 1, that proportional change in infection numbers will follow the standard Cauchy distribution with location and scale parameters 0 and 1, and that high infection numbers will follow a power-law frequency distribution with exponent 2. To test these predictions we used worldwide COVID-19 data from 1st February 2020 to 30th June 2022 to calculate [Formula see text] confidence interval estimates across countries for these R, location, scale and exponent parameters. The resulting median R estimate was [Formula see text] (predicted value 1) the proportional change location estimate was [Formula see text] (predicted value 0), the proportional change scale estimate was [Formula see text] (predicted value 1), and the frequency distribution exponent estimate was [Formula see text] (predicted value 2); in each case the observed estimate agreed with model predictions.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
COVID-19
Type of study:
Etiology_studies
/
Prognostic_studies
/
Risk_factors_studies
Limits:
Humans
Language:
En
Journal:
Sci Rep
Year:
2023
Document type:
Article
Affiliation country:
Irlanda