Economic

Economists seek to explain and predict human behavior. We believe that people can change their behavior as they receive "new news". Other research fields implicitly assume that people do not change our behavior and thus they predict the future using naive statistical extrapolation methods. The recent swine flu epidemic offers an interesting case study. A new NBER Working paper titled "Public Avoidance and the Epidemiology of novel H1N1 Influenza A" by Byung-Kwang Yoo, Megumi Kasajima, and Jay Bhattacharya (NBER Working Paper No. 15752
February 2010
http://www.nber.org/papers/w15752.pdf) investigates this important issue.

"In June 2009, the World Health Organization declared that novel influenza A (nH1N1) had reached pandemic status worldwide. The response to the spread of this virus by the public and by the public health community was immediate and widespread. Among the responses included voluntary avoidance of public spaces, closure of schools, the ubiquitous placement of hand sanitizer, and the use of face masks in public places. Existing forecasting models of the epidemic spread of nH1N1, used by public
health officials to aid in making many decisions including vaccination policy, ignore avoidance responses in the formal modeling. In this paper, we build a forecasting model of the nH1N1 epidemic that explicitly accounts for avoidance behavior. We use data from the U.S. summer and the Australian winter nH1N1
epidemic of 2009 to estimate the parameters of our model and forecast the course of the epidemic in the U.S. in 2010. We find that accounting for avoidance responses results in a better fitting forecasting model. We also find that in models with avoidance, the marginal return in terms of saved lives and reduced infection rates of an early vaccination campaign are higher."

As individuals take costly actions (how costly?) to protect themselves (hand washing) their small mutinees against the public health threat help to protect us all from infection. A serious public health research question should investigate how different households (white, black, Hispanic, Asian of different ages and education levels) each respond to the common threat of epidemic. Who is most responsive? Do their local residential communities suffer less disease risk because of these individual responses? Which individuals and communities engage in the least epidemic "self defense"? How can we encourage such communities and individuals to be more pro-active?

In this age of air travel and globalization, there must be the variation in the data to explore the geography of contagion and the interesting aggregation patterns of which geographical areas suffered little from the epidemic versus which areas and demographic groups suffered greatly.