Related Experiment Video
Updated: Jan 19, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Incorporating calendar effects to predict influenza seasonality in Milwaukee, Wisconsin
Ryan B Simpson1, Tania M Alarcon Falconi1, Aishwarya Venkat1
1Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA.
Abstract:
Social outings can trigger influenza transmission, especially in children and elderly. In contrast, school closures are associated with reduced influenza incidence in school-aged children. While influenza surveillance modelling studies typically account for holidays and mass gatherings, age-specific effects of school breaks, sporting events and commonly celebrated observances are not fully explored. We examined the impact of school holidays, social events and religious observances for six age groups (all ages, ⩽4, 5-24, 25-44, 45-64, ⩾65 years) on four influenza outcomes (tests, positives, influenza A and influenza B) as reported by the City of Milwaukee Health Department Laboratory, Milwaukee, Wisconsin from 2004 to 2009. We characterised holiday effects by analysing average weekly counts in negative binomial regression models controlling for weather and seasonal incidence fluctuations. We estimated age-specific annual peak timing and compared influenza outcomes before, during and after school breaks. During the 118 university holiday weeks, average weekly tests were lower than in 140 school term weeks (5.93 vs. 11.99 cases/week, P < 0.005). The dampening of tests during Winter Break was evident in all ages and in those 5-24 years (RR = 0.31; 95% CI 0.22-0.41 vs. RR = 0.14; 95% CI 0.09-0.22, respectively). A significant increase in tests was observed during Spring Break in 45-64 years old adults (RR = 2.12; 95% CI 1.14-3.96). Milwaukee Public Schools holiday breaks showed similar amplification and dampening effects. Overall, calendar effects depend on the proximity and alignment of an individual holiday to age-specific and influenza outcome-specific peak timing. Better quantification of individual holiday effects, tailored to specific age groups, should improve influenza prevention measures.
More Related Videos
20:36Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
Published on: July 4, 2007
12:09Measuring Influenza Neutralizing Antibody Responses to AH3N2 Viruses in Human Sera by Microneutralization Assays Using MDCK-SIAT1 Cells
Published on: November 22, 2017
Related Concept Videos
10:46A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
20:36Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
Seasoning of Wood
Achieving equilibrium moisture content is the goal of seasoning; this is the point where the wood's moisture content stabilizes to align with the moisture levels of the surrounding environment. Proper...
12:09Measuring Influenza Neutralizing Antibody Responses to A(H3N2) Viruses in Human Sera by Microneutralization Assays Using MDCK-SIAT1 Cells
08:20Cell Block Preparation from Cytology Specimen with Predominance of Individually Scattered Cells
Biological Clocks and Seasonal Responses