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An Introductory Framework for Choosing Spatiotemporal Analytical Tools in Population-Level Eco-Epidemiological Research

Frontiers in veterinary science publish this investigation article

July 7th, 2020

Spatiotemporal visualization and analytical tools (SATs) are increasingly being applied to risk-based surveillance/monitoring of adverse health events affecting humans, animals, and ecosystems. Different disciplines use diverse SATs to address similar research questions. The juxtaposition of these diverse techniques provides a list of options for researchers who are new to population-level spatial eco-epidemiology. Here, we are conducting a narrative review to provide an overview of the multiple available SATs, and introducing a framework for choosing among them when addressing common research questions across disciplines. The framework is comprised of three stages: (a) pre-hypothesis testing stage, in which hypotheses regarding the spatial dependence of events are generated; (b) primary hypothesis testing stage, in which the existence of spatial dependence and patterns are tested; and (c) secondary-hypothesis testing and spatial modeling stage, in which predictions and inferences were made based on the identified spatial dependences and associated covariates. In this step-wise process, six key research questions are formulated, and the answers to those questions should lead researchers to select one or more methods from four broad categories of SATs: (T1) visualization and descriptive analysis; (T2) spatial/spatiotemporal dependence and pattern recognition; (T3) spatial smoothing and interpolation; and (T4) geographic correlation studies (i.e., spatial modeling and regression). The SATs described here include both those used for decades and also other relatively new tools. Through this framework review, we intend to facilitate the choice among available SATs and promote their interdisciplinary use to support improving human, animal, and ecosystem health




Kanankege K., Alvarez J., Zhang L. and Perez AM.




See this article
An Introductory Framework for Choosing Spatiotemporal Analytical Tools in Population-Level Eco-Epidemiological Research




Participants:

University of MinnesotaDepartment of Veterinary Population Medicine. College of Veterinary Medicine. University of Minnesota (UMM).

Universidad ComplutenseCentro de Vigilancia Sanitaria Veterinaria (VISAVET). Universidad Complutense (UCM).

Universidad ComplutenseDepartamento de Sanidad Animal. Facultad de Veterinaria. Universidad Complutense (UCM).

University of MinnesotaDivision of Biostatistics. School of Public Health. University of Minnesota (UMM).







Frontiers in veterinary science
FACTOR YEAR Q
2.245 2019

NLMID: 101666658

ISSN: 2297-1769



TITLE: An Introductory Framework for Choosing Spatiotemporal Analytical Tools in Population-Level Eco-Epidemiological Research


JOURNAL: Front Vet Sci


NUMERACIÓN: 7:339


AÑO: 2020


PUBLISHER: Lausanne : Frontiers Media S.A


AUTHORS: Kanankege K., Alvarez J., Zhang L. and Perez AM.


VISAVET PARTICIPANTS


Julio Álvarez Sánchez

DOI: https://doi.org/ 10.3389/fvets.2020.00339


CITE THIS PUBLICATION:

Kanankege K., Alvarez J., Zhang L. and Perez AM. An Introductory Framework for Choosing Spatiotemporal Analytical Tools in Population-Level Eco-Epidemiological Research. Frontiers in veterinary science. 7:339. 2020. (A). ISSN: 2297-1769. DOI: 10.3389/fvets.2020.00339