title: Seasonality and comparative dynamics of six childhood infections in pre-vaccination Copenhagen.
abstract: Seasonal variation in infection transmission is a key determinant of epidemic dynamics of acute infections. For measles, the best-understood strongly immunizing directly transmitted childhood infection, the perception is that term-time forcing is the main driver of seasonality in developed countries. The degree to which this holds true across other acute immunizing childhood infections is not clear. Here, we identify seasonal transmission patterns using a unique long-term dataset with weekly incidence of six infections including measles. Data on age-incidence allow us to quantify the mean age of infection. Results indicate correspondence between dips in transmission and school holidays for some infections, but there are puzzling discrepancies, despite close correspondence between average age of infection and age of schooling. Theoretical predictions of the relationship between amplitude of seasonality and basic reproductive rate of infections that should result from term-time forcing are also not upheld. We conclude that where yearly trajectories of susceptible numbers are perturbed, e.g. via waning of immunity, seasonality is unlikely to be entirely driven by term-time forcing. For the three bacterial infections, pertussis, scarlet fever and diphtheria, there is additionally a strong increase in transmission during the late summer before the end of school vacations.
authors.affiliation: Centre for Infectious Disease Dynamics, The Pennsylvania State University, 208 Mueller Laboratory, University Park, PA 16802, USA. cjm53@psu.edu
authors.forename: C Jessica E
authors.initials: CJ
authors.lastname: Metcalf
authors.forename: Ottar N
authors.initials: ON
authors.lastname: Bjørnstad
authors.forename: Bryan T
authors.initials: BT
authors.lastname: Grenfell
authors.forename: Viggo
authors.initials: V
authors.lastname: Andreasen
mesh_terms: D000367:Age Factors; D002648:Child; D002947:Cities / Q000453:epidemiology*; D003718:Denmark / Q000453:epidemiology; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D049673:History, 20th Century; D006801:Humans; D007239:Infections / Q000453:epidemiology* / Q000266:history / Q000635:transmission*; D016015:Logistic Models; D008954:Models, Biological; D012621:Seasons