Impact of weekday social contact patterns on the modeling of influenza transmission, and determination of the influenza latent period.

Human social contact patterns show marked day-of-week variations, with a higher frequency of contacts occurring during weekdays when children are in school, and adults are in contact with co-workers, than typically occur on weekends. Using epidemic modeling, we show that using the average of social contacts during the week in the model yields virtually identical predictions of epidemic final size and the timing of the epidemic incidence peak as a model that incorporates weekday social contact patterns. This is true of models with a constant weekly average contact rate throughout the year, and also of models that assume seasonality of transmission. Our modeling studies reveal, however, that weekday social contact patterns can produce substantial weekday variations in an influenza incidence curve, and the pattern of variation is sensitive to the influenza latent period. The possible observability of weekday patterns in daily influenza incidence data opens up an interesting avenue of further inquiry that can shed light on the latent period of pandemic influenza. The duration of the latent period must be known with precision in order to design effective disease intervention strategies, such as use of antivirals. For a hypothetical influenza pandemic, we thus perform a simulation study to determine the number of cases needed to observe the weekday variation pattern in influenza epidemic incidence data. Our studies suggest that these patterns should be observable at 95% confidence in daily influenza hospitalization data from large cities over 75% of the time. Using 2009 A(H1N1) daily case data recorded by a large hospital in Santiago, Chile, we show that significant weekday incidence patterns are evident. From these weekday incidence patterns, we estimate the latent period of influenza to be [0.04, 0.60] days (95% CI). This method for determination of the influenza latent period in a community setting is novel, and unique in its approach.