UNDERSTANDING GLOBAL SEASONAL SYNCHRONIZATION OF INFECTIOUS DISEASES USING REMOTE SENSING

Seasonality is a common phenomenon for many infectious diseases with a strong environment component and drives the probability of exposure and transmission. The global synchronization of spatio-temporal patterns has been noted for respiratory and water-borne infections worldwide. The tools offered by remote sensing have a great potential in developing a unifying approach to comprehensively study seasonal patterns across various climatic zones and vulnerable populations. This presentation introduces the notion of seasonality by outlining several of its essential terms and factors, provides comparisons of current methods for assessing seasonality, illustrates synchronization of non-specific and laboratory-confirmed hospitalizations due to enteric infection, and demonstrates seasonal oscillations using dynamic mapping. The use of remote sensing data will be illustrated with examples of meta-analysis applied to the seasonality of water-borne infections. The topic of disease seasonality covers all aspects of data-rich applications: description, quantifications, modeling, study design, near-term prediction and long-term forecast.