Abstract
Although influenza is a common disease, the determinants of each season's onset, magnitude, and duration remain poorly understood. Marked seasonality in temperate regions suggests that environmental variables affect transmission. Using deterministic compartmental transmission modeling, we assessed the potential for estimating climatic effects on influenza A epidemic patterns. Two versions of a susceptible-exposed-infectious-removed-susceptible (SEIRS) model were created with multiple immunity levels to represent viral drift. In the first model, seasonal transmission was approximated via a regular sine wave for the probability of transmission ( β). In the second model, β varied based on actual values of the Multivariate El Niño Southern Oscillation Index (MEI), an index comprising six weather variables associated with global climate variability. The SEIRS models were each used to generate epidemic patterns, some of which were regular and others irregular, depending on the parameter values used. However, MEI had a notable effect on the epidemic patterns by allowing susceptibles to accumulate, leading to larger seasonal epidemics. This approach allows us to explore how relaxing certain model assumptions affects results, and provides a foundation for detecting climate effects in actual influenza data. Our ultimate goal is to promote interepidemic preparedness by elucidating the contribution of environmental variables to influenza transmission.
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