62
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Advances and Limitations of Disease Biogeography Using Ecological Niche Modeling

      review-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Mapping disease transmission risk is crucial in public and animal health for evidence based decision-making. Ecology and epidemiology are highly related disciplines that may contribute to improvements in mapping disease, which can be used to answer health related questions. Ecological niche modeling is increasingly used for understanding the biogeography of diseases in plants, animals, and humans. However, epidemiological applications of niche modeling approaches for disease mapping can fail to generate robust study designs, producing incomplete or incorrect inferences. This manuscript is an overview of the history and conceptual bases behind ecological niche modeling, specifically as applied to epidemiology and public health; it does not pretend to be an exhaustive and detailed description of ecological niche modeling literature and methods. Instead, this review includes selected state-of-the-science approaches and tools, providing a short guide to designing studies incorporating information on the type and quality of the input data (i.e., occurrences and environmental variables), identification and justification of the extent of the study area, and encourages users to explore and test diverse algorithms for more informed conclusions. We provide a friendly introduction to the field of disease biogeography presenting an updated guide for researchers looking to use ecological niche modeling for disease mapping. We anticipate that ecological niche modeling will soon be a critical tool for epidemiologists aiming to map disease transmission risk, forecast disease distribution under climate change scenarios, and identify landscape factors triggering outbreaks.

          Related collections

          Most cited references114

          • Record: found
          • Abstract: not found
          • Article: not found

          Maximum entropy modeling of species geographic distributions

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            The global distribution and burden of dengue

            Dengue is a systemic viral infection transmitted between humans by Aedes mosquitoes 1 . For some patients dengue is a life-threatening illness 2 . There are currently no licensed vaccines or specific therapeutics, and substantial vector control efforts have not stopped its rapid emergence and global spread 3 . The contemporary worldwide distribution of the risk of dengue virus infection 4 and its public health burden are poorly known 2,5 . Here we undertake an exhaustive assembly of known records of dengue occurrence worldwide, and use a formal modelling framework to map the global distribution of dengue risk. We then pair the resulting risk map with detailed longitudinal information from dengue cohort studies and population surfaces to infer the public health burden of dengue in 2010. We predict dengue to be ubiquitous throughout the tropics, with local spatial variations in risk influenced strongly by rainfall, temperature and the degree of urbanisation. Using cartographic approaches, we estimate there to be 390 million (95 percent credible interval 284-528) dengue infections per year, of which 96 million (67-136) manifest apparently (any level of clinical or sub-clinical severity). This infection total is more than three times the dengue burden estimate of the World Health Organization 2 . Stratification of our estimates by country allows comparison with national dengue reporting, after taking into account the probability of an apparent infection being formally reported. The most notable differences are discussed. These new risk maps and infection estimates provide novel insights into the global, regional and national public health burden imposed by dengue. We anticipate that they will provide a starting point for a wider discussion about the global impact of this disease and will help guide improvements in disease control strategies using vaccine, drug and vector control methods and in their economic evaluation. [285]
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Very high resolution interpolated climate surfaces for global land areas

                Bookmark

                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                05 August 2016
                2016
                : 7
                : 1174
                Affiliations
                [1] 1Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul MN, USA
                [2] 2Minnesota Aquatic Invasive Species Research Center, University of Minnesota, St. Paul MN, USA
                Author notes

                Edited by: Yuji Morita, Aichi Gakuin University, Japan

                Reviewed by: Pelayo Acevedo, Instituto de Investigación en Recursos Cinegéticos (UCLM-CSIC-JCCM), Spain; Mike Taylor, University of Auckland, New Zealand

                *Correspondence: Luis E. Escobar, lescobar@ 123456umn.edu

                This article was submitted to Infectious Diseases, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2016.01174
                4974947
                27547199
                af6b3387-8ff0-4830-bfff-b95dac76e343
                Copyright © 2016 Escobar and Craft.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 31 January 2016
                : 15 July 2016
                Page count
                Figures: 14, Tables: 0, Equations: 0, References: 120, Pages: 21, Words: 0
                Funding
                Funded by: National Science Foundation 10.13039/100000001
                Award ID: DEB-1413925
                Funded by: U.S. Department of Agriculture 10.13039/100000199
                Categories
                Microbiology
                Review

                Microbiology & Virology
                spatial epidemiology,prediction,fundamental niche,infectious disease,risk map

                Comments

                Comment on this article