Spatiotemporal Modeling of Preterm Birth

Authored by: Joshua L. Warren , Montserrat Fuentes , Amy H. Herring , Peter H. Langlois

Handbook of Spatial Epidemiology

Print publication date:  April  2016
Online publication date:  April  2016

Print ISBN: 9781482253016
eBook ISBN: 9781482253023
Adobe ISBN:

10.1201/b19470-40

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Abstract

The analysis of spatiotemporal data has received increasing amounts of attention in recent years. This is due to the rising availability of spatially and temporally referenced data, mainly as a result of advancements in technology that allow researchers to more easily obtain location- and date-specific data records. A number of areas now regularly collect and analyze spatiotemporal data. Pollution monitors across a geographic domain collect information at fixed spatial locations during various times of the day. Public health studies often attempt to investigate the spread and severity of a disease outbreak using spatially referenced data. With census data, it is common to have access to information aggregated at the county or state level during discrete points in time. The ability to properly analyze spatiotemporal data is crucial in order to fully understand the data generating process and to ensure that the appropriate statistical inference is conducted. Failing to account for the spatiotemporal behavior of the process could lead to poor decisions regarding questions of interest in a particular study. This is especially important in the public health setting where researchers attempt to analyze spatiotemporally referenced data with the goal of improving the overall health of the population through informed lifestyle choices.

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