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Theory suggests that individual behavioral responses impact the spread of flu-like illnesses, but this has been difficult to empirically characterize. Social distancing is an important component of behavioral response, though analyses have been limited by a lack of behavioral data. Springborn, et al. (2015) sought to use media data to characterize social distancing behavior in order to empirically inform explanatory and predictive epidemiological models.
The researchers used data on variation in home television viewing as a proxy for variation in time spent in the home and, by extension, contact. This behavioral proxy is imperfect but appealing since information on a rich and representative sample is collected using consistent techniques across time and most major cities. They studied the April-May 2009 outbreak of A/H1N1 in Central Mexico and examine the dynamic behavioral response in aggregate and contrast the observed patterns of various demographic subgroups. They developed and calibrated a dynamic behavioral model of disease transmission informed by the proxy data on daily variation in contact rates and compared it to a standard (non-adaptive) model and a fixed effects model that crudely captures behavior.
Springborn, et al. (2015) found that after a demonstrable initial behavioral response (consistent with social distancing) at the onset of the outbreak, there was attenuation in the response before the conclusion of the public health intervention. They also found substantial differences in the behavioral response across age subgroups and socioeconomic levels, and that the dynamic behavioral and fixed effects transmission models better account for variation in new confirmed cases, generate more stable estimates of the baseline rate of transmission over time and predict the number of new cases over a short horizon with substantially less error.
The researchers add that their results suggest that A/H1N1 had an innate transmission potential greater than previously thought but this was masked by behavioral responses. They say that observed differences in behavioral response across demographic groups indicate a potential benefit from targeting social distancing outreach efforts. Their research was published in BMC Infectious Diseases.
Reference: Springborn M, Chowell G, MacLachlan M and Fenichel EP. Accounting for behavioral responses during a flu epidemic using home television viewing. BMC Infectious Diseases 2015, 15:21 doi:10.1186/s12879-014-0691-0