Contact, travel, and transmission: The impact of winter holidays on influenza dynamics in the United States

Abstract

Winter holidays delay seasonal influenza epidemic peaks and shift disease risk toward adults because of changes in contact patterns. These findings may inform targeted influenza information and vaccination campaigns during holiday periods.

The impact of regular school closure on seasonal influenza epidemics: a data-driven spatial transmission model for Belgium

“…The simulated incidence profile clearly shows a slowing down in the growth of the number of new infections during the Christmas break, as reported by sentinel surveillance in the country, suggesting that holiday is associated to temporary reductions in influenza transmission. This was also found in previous empirical studies [23,45]. To identify the mechanisms behind this effect, we isolated the changes in mixing and those in travel behavior during school closure, comparing different experimental scenarios, similar to Ewing et al [45].…”

“…The model calibrated on a single district (i.e. a subset of patches, ∼ 3% of the country total) is able to reproduce with fairly good agreement the empirical pattern observed in the country for that season, suggesting that data-driven mixing and mobility are crucial ingredients to capture influenza spatial dynamics [94,18,36,10,79,39,4,26,45]. The result is a spatially heterogeneous propagation where the two ingredients act at different levels.…”

“…Travel is known to be responsible for the spatial dissemination of influenza [57,94,32,46,44,47,9,10,7,4]. In addition to extraordinary travel drops in reaction to epidemics [2,7,84], mobility changes regularly occur during school holidays compared to term-time [75,45]. Moreover, important differences were highlighted in the mobility of children vs. adults and their associated variations, so that their coupling with social mixing changes occurring during holidays may have a considerable impact on the epidemic outcome [4,45].…”

“…The contexts are however considered independently (no full school calendar can be considered) and the epidemic impact is evaluated only in terms of conditions for spatial dissemination. Going beyond these limitations, more recently Ewing et al introduced an age-specific spatial metapopulation model to evaluate how behavioral changes associated to winter holiday impact the flu season [45]. The model is applied to the United States and it integrates data on travel behavior, whereas mixing is assumed from estimates available from Europe and adapted to summer holiday changes measured in the UK during the 2009 pandemic [39].…”

“…Given the central role of mixing patterns largely supported by evidence [22,69,4,45], the heterogeneous country-specific contact variations measured in Europe [80,61], and the marked difference expected in individual behavior during a seasonal flu epidemic vs. a pandemic, here we extend prior approaches to introduce a data-driven spatially explicit model fully parameterized on Belgium. The aim is to reduce assumptions in favor of input data, and to exclusively focus on seasonal influenza and associated parameterization.…”