%0 Journal Article %1 Castillo-Chavez201614582 %A Castillo-Chavez, C. %A Bichara, D. %A Morin, B.R. %D 2016 %I National Academy of Sciences %J Proceedings of the National Academy of Sciences of the United States of America %K Review; aspect; conceptual economic epidemic; epidemiological framework; human; infection; journal; monitoring; priority time %N 51 %P 14582-14588 %R http://dx.doi.org/10.1073/pnas.1604994113 %T Perspectives on the role of mobility, behavior, and time scales in the spread of diseases %U http://dx.doi.org/10.1073/pnas.1604994113 %V 113 %X The dynamics, control, and evolution of communicable and vector-borne diseases are intimately connected to the joint dynamics of epidemiological, behavioral, and mobility processes that operate across multiple spatial, temporal, and organizational scales. The identification of a theoretical explanatory framework that accounts for the pattern regularity exhibited by a large number of host-parasite systems, including those sustained by host-vector epidemiological dynamics, is but one of the challenges facing the coevolving fields of computational, evolutionary, and theoretical epidemiology. Host-parasite epidemiological patterns, including epidemic outbreaks and endemic recurrent dynamics, are characteristic to well-identified regions of the world; the result of processes and constraints such as strain competition, host and vector mobility, and population structure operating over multiple scales in response to recurrent disturbances (like El NiÃ$\pm$o) and climatological and environmental perturbations over thousands of years. It is therefore important to identify and quantify the processes responsible for observed epidemiological macroscopic patterns: the result of individual interactions in changing social and ecological landscapes. In this perspective, we touch on some of the issues calling for the identification of an encompassing theoretical explanatory framework by identifying some of the limitations of existing theory, in the context of particular epidemiological systems. Fostering the reenergizing of research that aims at disentangling the role of epidemiological and socioeconomic forces on disease dynamics, better understood as complex adaptive systems, is a key aim of this perspective. Â\copyright 2016, National Academy of Sciences. All rights reserved.

@article{Castillo-Chavez201614582, abstract = {The dynamics, control, and evolution of communicable and vector-borne diseases are intimately connected to the joint dynamics of epidemiological, behavioral, and mobility processes that operate across multiple spatial, temporal, and organizational scales. The identification of a theoretical explanatory framework that accounts for the pattern regularity exhibited by a large number of host-parasite systems, including those sustained by host-vector epidemiological dynamics, is but one of the challenges facing the coevolving fields of computational, evolutionary, and theoretical epidemiology. Host-parasite epidemiological patterns, including epidemic outbreaks and endemic recurrent dynamics, are characteristic to well-identified regions of the world; the result of processes and constraints such as strain competition, host and vector mobility, and population structure operating over multiple scales in response to recurrent disturbances (like El Ni{\~A}$\pm$o) and climatological and environmental perturbations over thousands of years. It is therefore important to identify and quantify the processes responsible for observed epidemiological macroscopic patterns: the result of individual interactions in changing social and ecological landscapes. In this perspective, we touch on some of the issues calling for the identification of an encompassing theoretical explanatory framework by identifying some of the limitations of existing theory, in the context of particular epidemiological systems. Fostering the reenergizing of research that aims at disentangling the role of epidemiological and socioeconomic forces on disease dynamics, better understood as complex adaptive systems, is a key aim of this perspective. {\^A}{\copyright} 2016, National Academy of Sciences. All rights reserved.}, added-at = {2017-11-10T22:48:29.000+0100}, affiliation = {Simon A. Levin Mathematical and Computational Modeling Sciences Center, Arizona State University, Tempe, AZ, United States; Departamento de Ingenier{\~A}-a Biom{\~A}{\copyright}dica, Universidad de Los Andes, Bogota, Colombia; Yachay Tech. University, Office of the Rector, Urcuqui, Ecuador; Department of Mathematics, California State University, Fullerton, CA, United States; Center for Computational and Applied Mathematics, California State University, Fullerton, CA, United States; School of Life Sciences, Arizona State University, Tempe, AZ, United States; Department of Mathematics and Statistics, Vassar College, Poughkeepsie, NY, United States}, author = {Castillo-Chavez, C. and Bichara, D. and Morin, B.R.}, author_keywords = {Behavior; Complex adaptive systems; Infectious disease; Mobility; Risk}, biburl = {https://www.bibsonomy.org/bibtex/202b17173d128eb1190821a8e4d731254/ccchavez}, coden = {PNASA}, correspondence_address1 = {Castillo-Chavez, C.; Simon A. Levin Mathematical and Computational Modeling Sciences Center, Arizona State UniversityUnited States; email: ccchavez@asu.edu}, date-added = {2017-11-10 21:45:26 +0000}, date-modified = {2017-11-10 21:45:26 +0000}, document_type = {Review}, doi = {http://dx.doi.org/10.1073/pnas.1604994113}, interhash = {f513ebd5df91a8d85c62392a9aa749b0}, intrahash = {02b17173d128eb1190821a8e4d731254}, issn = {00278424}, journal = {Proceedings of the National Academy of Sciences of the United States of America}, keywords = {Review; aspect; conceptual economic epidemic; epidemiological framework; human; infection; journal; monitoring; priority time}, language = {English}, number = 51, pages = {14582-14588}, publisher = {National Academy of Sciences}, timestamp = {2017-11-10T22:48:29.000+0100}, title = {Perspectives on the role of mobility, behavior, and time scales in the spread of diseases}, url = {http://dx.doi.org/10.1073/pnas.1604994113}, volume = 113, year = 2016 }