Although seasonality is a well-known phenomenon in the epidemiology of enteric infections, analytical tools for examination, evaluation, and comparison of seasonal patterns are insufficient limiting analysis of factors associated with variations. We offer a framework for seasonality assessment, and a parametric approach for evaluating peak timing and intensity. We will discuss the importance of proper aggregation for the time series and determination of the calendar year for each health outcome. We contrast our approach with non-parametric modeling and demonstrate this methodology on hospitalization data for environmentally driven diseases using examples related to the effect of extreme temperature and precipitation. This requires an appropriate definition of seasonality and analytic tools suitable for routine use. An understanding of how environmental factors influence human disease can improve disease forecasting, improve the design of integrated warning systems, and advance development of efficient outbreak detection algorithms.
Learning Objectives:
1. Describe waterborne diseases demonstrate a seasonal pattern which may be driven by climatic characteristics.
Qualified on the content I am responsible for because: I have conceptualized and conducted this work on my own.
Any relevant financial relationships? No
I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.
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