Risk estimation of infectious diseases determines the effectiveness of the control strategy

Usually, whether to take vaccination or not is a voluntary decision, which is determined by many factors, from societal factors (such as religious belief and human rights) to individual preferences (including psychology and altruism). Facing the outbreaks of infectious diseases, different people often have different estimations on the risk of infectious diseases. So, some persons are willing to vaccinate, but other persons are willing to take risks. In this paper, we establish two different risk assessment systems using the technique of dynamic programming, and then compare the effects of the two different systems on the prevention of diseases on complex networks. One is that the perceived probability of being infected for each individual is the same (uniform case). The other is that the perceived probability of being infected is positively correlated to individual degrees (preferential case). We show that these two risk assessment systems can yield completely different results, such as, the effectiveness of controlling diseases, the time evolution of the number of infections, and so on.

Research highlights
► On an outbreak of an infectious disease, individual decisions on vaccination depend on whether they can accurately estimate the risk of the disease.
► So, in this work, we establish two different risk assessment systems using the technique of dynamic programming. By comparing the two different risk assessment systems, we find that how individuals estimate the risk of infection determines the effectiveness of control strategy.
► Furthermore, many other interesting results are enclosed in this work.