Seasonality, Environment, and Infectious Diseases

Hospital For Sick Chldrn (Toronto), Toronto ON

Investigators

Linked publications & trials

Abstract

[unreadable] DESCRIPTION (provided by applicant): Objectives: The seasonality of infectious disease occurrence has been recognized since ancient times, but mechanisms underlying seasonality remain poorly defined. While environmental exposures (e.g., changes in weather or environmental pollutants) could contribute to seasonality, other mechanisms (e.g., seasonal changes in population behavior or co-occurrence of infectious diseases) might also result in seasonal disease occurrence. Current efforts to define the role of environmental exposures in infectious disease occurrence are limited by the sparse nature of public health surveillance data, and confounding of associations when aggregated exposure or outcome data are used. The case-crossover study design is a novel epidemiologic technique useful for defining causal relationships between repeated transient exposures and rare outcomes. It has proven useful in the study of environmental influences on non-infectious disease, but has not been used previously in the study of infectious diseases of public health importance. Our objectives are to: 1. better elucidate the epidemiologic relationship between acute changes in the physical environment (e.g., weather, environmental pollutants) and the occurrence of infectious diseases of public health importance. 2. define the role of case-crossover study design as a tool for study of the role of environment in communicable disease occurrence. Our specific aims include use of the case-crossover study design to determine the extent to which the seasonality of occurrence of selected infectious diseases in Philadelphia County, PA, is a result of seasonal variation in acute environmental exposures (weather patterns and air quality), and the identification of optimal control selection strategies when case-crossover design is used to study infectious diseases. The latter aim will be achieved using mathematical modeling. [unreadable] [unreadable] [unreadable]