Individual vaccination decisions based on local information can lead to optimal public health outcomes [MCB seminar series]
Vaccinations have played a significant role in containing the spread of infectious diseases worldwide. A major factor underlying the success of large-scale voluntary vaccination schemes in combating epidemic resurgence is public perception of the necessity of vaccination. From the point of view of an individual, the optimal outcome will be that in which everybody else gets vaccinated so that she enjoys the benefit of herd immunity, without incurring any of the costs (real or perceived) associated with being vaccinated herself. However, if everyone argues in this manner, the vaccination drive will fail and the population will be vulnerable to a large-scale epidemic. Thus, the effectiveness of such schemes could engender their own undoing. In this talk, I will discuss a model of epidemic spreading in a social network of individuals who take strategic decisions on whether to get vaccinated, and where vaccination behaviour consequently co-evolves with the spread of the epidemic. Our model reveals important factors, such as the heterogeneity in information, and hence risk perception over the population, that can crucially affect the efficacy of public health intervention schemes involving voluntary vaccination. In particular, we observe that vaccination choices made on the basis of local information (such as word-of-mouth) may lead to better public health outcomes than those driven by global information (such as that disseminated through mass media).
This work is in collaboration with: Anupama Sharma, V. Sasidevan and Sitabhra Sinha Reference: https://protect-au.mimecast.com/s/f5z5CGvmpxhX1yV0iKc7_4?domain=arxiv.org
Dr Shakti Menon, The Institute of Mathematical Sciences, CIT Campus, Taramani, Chennai 600113, India.