A game dynamic model for delayer strategies in vaccinating behaviour for pediatric infectious diseases.
Several studies have found that some parents delay the age at which their children receive pediatric vaccines due to perception of higher vaccine risk at the recommended age of vaccination. This has been particularly apparently during the Measles-Mumps-Rubella scare in the United Kingdom. Under a voluntary vaccination policy, vaccine coverage in certain age groups is a potentially complex interplay between vaccinating behaviour, disease dynamics, and age-specific risk factors. Here, we construct an age-structured game dynamic model, where individuals decide whether to vaccinate according to imitation dynamics depending on age-dependent disease prevalence and perceived risk of vaccination. Individuals may be timely vaccinators, delayers, or non-vaccinators. The model exhibits multiple equilibria and a broad range of possible dynamics. For certain parameter regimes, the proportion of timely vaccinators and delayers oscillate in an anti-phase fashion in response to oscillations in infection prevalence. Under an exogenous change to the perceived risk of vaccination as might occur during a vaccine scare, the model can also capture an increase in delayer strategists similar in magnitude to that observed during the Measles-Mumps-Rubella vaccine scare in the United Kingdom. Our model also shows that number of delayers steadily increases with increasing severity of the scare, whereas it saturates to specific value with increases in duration of the scare. Finally, by comparing the model dynamics with and without the option of a delayer strategy, we show that adding a third delayer strategy can have a stabilizing effect on model dynamics. In an era where individual choice--rather than accessibility--is becoming an increasingly important determinant of vaccine uptake, more infectious disease models may need to use game theory or related techniques to determine vaccine uptake.
Bhattacharyya
Samit
S
Department of Mathematics and Statistics, University of Guelph, Guelph, ON, Canada. sbhattac@uoguelph.ca
Bauch
C T
CT
D000367:Age Factors; D000465:Algorithms; D002648:Child; D002675:Child, Preschool; D003141:Communicable Diseases / Q000453:epidemiology*; D003198:Computer Simulation; D005716:Game Theory; D007722:Health Knowledge, Attitudes, Practice; D006801:Humans; D007115:Immunization Schedule; D007223:Infant; D032541:Mass Vaccination / Q000009:adverse effects / Q000523:psychology*; D008954:Models, Biological; D010507:Periodicity; D015995:Prevalence; D013997:Time Factors