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COVID-19 is a respiratory disease caused by a recently discovered, novel coronavirus, SARS-COV2. The disease has led to over 41 million cases, with over 1 million deaths, and over 28 million recovered individuals world wide. In the current social and political climate, the risk of COVID-19 infection is driven by people’s perception of the risk of infection. A number of factors drive public perception of disease risk, these include people's beliefs, knowledge, and information about a disease. In this seminar, I will present two different models for COVID-19 looking at peoples’ behavior and their sentiments about the disease. One model uses game theory and appropriate payoff functions relating to the perception of risk measured using disease incidence and severity of infection to account for a series of human behaviors. This leads to a complex interplay between the epidemiological model, that affects the success of different strategies, and the game-theoretic behavioral model, which in turn affects the spread of the disease. The second model uses tweets from twitter to account for people's sentiments about the disease. It also takes into account negative sentiments driven by misinformation. The results from these models show that the rational behavior of susceptible individuals can lead to a second wave of the pandemic; these multiple waves of the pandemic are possible if the rate of social learning of infected individuals is sufficiently high. To reduce the burden of the disease in the community, it is necessary to ensure positive sentiments and feelings and to incentivize such altruistic behavior by infected individuals as voluntary self-isolation.

Contact Mariel Vazquez for any questions mrlvazquez@ucdavis.edu