School of Life Sciences and ecoSERVICES Group, Arizona State University, Tempe, AZ 85287-4501, USA.
Proc Natl Acad Sci U S A. 2011 Apr 12;108(15):6306-11. doi: 10.1073/pnas.1011250108. Epub 2011 Mar 28.
The science and management of infectious disease are entering a new stage. Increasingly public policy to manage epidemics focuses on motivating people, through social distancing policies, to alter their behavior to reduce contacts and reduce public disease risk. Person-to-person contacts drive human disease dynamics. People value such contacts and are willing to accept some disease risk to gain contact-related benefits. The cost-benefit trade-offs that shape contact behavior, and hence the course of epidemics, are often only implicitly incorporated in epidemiological models. This approach creates difficulty in parsing out the effects of adaptive behavior. We use an epidemiological-economic model of disease dynamics to explicitly model the trade-offs that drive person-to-person contact decisions. Results indicate that including adaptive human behavior significantly changes the predicted course of epidemics and that this inclusion has implications for parameter estimation and interpretation and for the development of social distancing policies. Acknowledging adaptive behavior requires a shift in thinking about epidemiological processes and parameters.
传染病的科学和管理正在进入一个新阶段。越来越多的传染病管理公共政策侧重于通过社会隔离政策激励人们改变行为，以减少接触并降低公共疾病风险。人际接触推动了人类疾病的动态变化。人们重视这种接触，并愿意接受一定的疾病风险以获得与接触相关的好处。塑造接触行为（进而影响传染病的进程）的成本效益权衡通常只是在流行病学模型中隐含地考虑。这种方法在解析适应性行为的影响方面存在困难。我们使用疾病动态的流行病学 - 经济学模型来明确建模驱动人际接触决策的权衡。结果表明，包含适应性人类行为会显著改变预测的传染病进程，并且这种包含对参数估计和解释以及社会隔离政策的制定具有影响。承认适应性行为需要转变对流行病学过程和参数的思考方式。
