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      Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus

      research-article
      1 , 2 , 3 , , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 4 , 11 , 4 , 4 , 4 , 4 , 4 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 26 , 27 , 28 , 29 , 17 , 30 , 17 , 31 , 16 , 17 , 2 , 3 ,   4 , 32 , 33 , 9 , 34 , 1 , 1 , 35 , 36 , 37 , 38 , 39 , 15 , 1 , 40 , 4 , , 41 ,
      Nature Microbiology
      Nature Publishing Group UK
      Microbiology, Infectious diseases

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          Abstract

          The global population at risk from mosquito-borne diseases—including dengue, yellow fever, chikungunya and Zika—is expanding in concert with changes in the distribution of two key vectors: Aedes aegypti and Aedes albopictus. The distribution of these species is largely driven by both human movement and the presence of suitable climate. Using statistical mapping techniques, we show that human movement patterns explain the spread of both species in Europe and the United States following their introduction. We find that the spread of Ae. aegypti is characterized by long distance importations, while Ae. albopictus has expanded more along the fringes of its distribution. We describe these processes and predict the future distributions of both species in response to accelerating urbanization, connectivity and climate change. Global surveillance and control efforts that aim to mitigate the spread of chikungunya, dengue, yellow fever and Zika viruses must consider the so far unabated spread of these mosquitos. Our maps and predictions offer an opportunity to strategically target surveillance and control programmes and thereby augment efforts to reduce arbovirus burden in human populations globally.

          Abstract

          Statistical mapping techniques provide insights into the spread of two key arbovirus vectors in Europe and the United States, and predict the future distributions of both mosquitoes in response to accelerating urbanization, connectivity and climate change.

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          Most cited references44

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          A new scenario framework for climate change research: the concept of shared socioeconomic pathways

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            Spread of the tiger: global risk of invasion by the mosquito Aedes albopictus.

            Aedes albopictus, commonly known as the Asian tiger mosquito, is currently the most invasive mosquito in the world. It is of medical importance due to its aggressive daytime human-biting behavior and ability to vector many viruses, including dengue, LaCrosse, and West Nile. Invasions into new areas of its potential range are often initiated through the transportation of eggs via the international trade in used tires. We use a genetic algorithm, Genetic Algorithm for Rule Set Production (GARP), to determine the ecological niche of Ae. albopictus and predict a global ecological risk map for the continued spread of the species. We combine this analysis with risk due to importation of tires from infested countries and their proximity to countries that have already been invaded to develop a list of countries most at risk for future introductions and establishments. Methods used here have potential for predicting risks of future invasions of vectors or pathogens.
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              A universal model for mobility and migration patterns.

              Introduced in its contemporary form in 1946 (ref. 1), but with roots that go back to the eighteenth century, the gravity law is the prevailing framework with which to predict population movement, cargo shipping volume and inter-city phone calls, as well as bilateral trade flows between nations. Despite its widespread use, it relies on adjustable parameters that vary from region to region and suffers from known analytic inconsistencies. Here we introduce a stochastic process capturing local mobility decisions that helps us analytically derive commuting and mobility fluxes that require as input only information on the population distribution. The resulting radiation model predicts mobility patterns in good agreement with mobility and transport patterns observed in a wide range of phenomena, from long-term migration patterns to communication volume between different regions. Given its parameter-free nature, the model can be applied in areas where we lack previous mobility measurements, significantly improving the predictive accuracy of most of the phenomena affected by mobility and transport processes.
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                Author and article information

                Contributors
                moritz.kraemer@zoo.ox.ac.uk
                sihay@uw.edu
                nick.golding.research@gmail.com
                Journal
                Nat Microbiol
                Nat Microbiol
                Nature Microbiology
                Nature Publishing Group UK (London )
                2058-5276
                4 March 2019
                4 March 2019
                2019
                : 4
                : 5
                : 854-863
                Affiliations
                [1 ]ISNI 0000 0004 1936 8948, GRID grid.4991.5, Department of Zoology, , University of Oxford, ; Oxford, UK
                [2 ]ISNI 000000041936754X, GRID grid.38142.3c, Harvard Medical School, , Harvard University, ; Boston, MA USA
                [3 ]ISNI 0000 0004 0378 8438, GRID grid.2515.3, Boston Children’s Hospital, ; Boston, MA USA
                [4 ]ISNI 0000000122986657, GRID grid.34477.33, Institute for Health Metrics and Evaluation, , University of Washington, ; Seattle, WA USA
                [5 ]ISNI 0000 0004 0425 469X, GRID grid.8991.9, Centre for Mathematical Modelling of Infectious Diseases, , London School of Hygiene and Tropical Medicine, ; London, UK
                [6 ]ISNI 0000 0004 0425 469X, GRID grid.8991.9, Department of Infectious Disease Epidemiology, , London School of Hygiene and Tropical Medicine, ; London, UK
                [7 ]ISNI 0000 0004 1936 8948, GRID grid.4991.5, School of Geography and the Environment, , University of Oxford, ; Oxford, UK
                [8 ]ISNI 0000 0004 1936 8948, GRID grid.4991.5, Oxford School of Global and Area Studies, , University of Oxford, ; Oxford, UK
                [9 ]ISNI 0000 0001 2348 0746, GRID grid.4989.c, Spatial Epidemiology Lab (SpELL), Universite Libre de Bruxelles, ; Brussels, Belgium
                [10 ]ISNI 0000 0004 0647 2148, GRID grid.424470.1, Fonds National de la Recherche Scientifique, ; Brussels, Belgium
                [11 ]ISNI 000000041936754X, GRID grid.38142.3c, Department of Statistics, , Harvard University, ; Cambridge, MA USA
                [12 ]ISNI 0000000100301493, GRID grid.62562.35, RTI International, ; Washington, DC USA
                [13 ]ISNI 0000 0004 1936 8868, GRID grid.4563.4, Epidemiology and Public Health Division, School of Medicine, , University of Nottingham, ; Nottingham, UK
                [14 ]ISNI 0000 0001 2168 0066, GRID grid.131063.6, Department of Biological Sciences and Eck Institute for Global Health, , University of Notre Dame, ; Notre Dame, IN USA
                [15 ]ISNI 0000 0004 0369 313X, GRID grid.419897.a, School of Health, Fudan University, Key Laboratory of Public Health Safety, , Ministry of Education, ; Shanghai, China
                [16 ]ISNI 0000 0004 1936 9297, GRID grid.5491.9, Department of Geography and Environment, , University of Southampton, ; Southampton, UK
                [17 ]GRID grid.475139.d, Flowminder Foundation, ; Stockholm, Sweden
                [18 ]ISNI 0000 0001 0379 7164, GRID grid.216417.7, School of Business, , Central South University, ; Changsha, China
                [19 ]ISNI 0000 0000 9548 2110, GRID grid.412110.7, College of Systems Engineering, , National University of Defense Technology, ; Changsha, China
                [20 ]GRID grid.443347.3, School of Business Administration, , Southwestern University of Finance and Economics, ; Chengdu, China
                [21 ]Waen Associates Ltd, Y Waen, Islaw’r Dref, Dolgellau, Gwynedd, UK
                [22 ]ISNI 0000 0001 0505 4321, GRID grid.4437.4, Pan American Health Organization (PAHO), ; Washington, DC USA
                [23 ]ISNI 0000 0004 0602 9808, GRID grid.414596.b, National Dengue Control Program, , Ministry of Health, ; Brasilia, Brazil
                [24 ]ISNI 0000 0004 1791 8889, GRID grid.418914.1, European Centre for Disease Prevention and Control, ; Stockholm, Sweden
                [25 ]ISNI 0000 0001 2153 5088, GRID grid.11505.30, Institute of Tropical Medicine, ; Antwerp, Belgium
                [26 ]GRID grid.423833.d, Avia-GIS, ; Zoersel, Belgium
                [27 ]Francis Schaffner Consultancy, Riehen, Switzerland
                [28 ]ISNI 0000 0004 1936 8083, GRID grid.47894.36, Department of Microbiology, Immunology, and Pathology, , Colorado State University, ; Fort Collins, CO USA
                [29 ]ISNI 0000 0001 2156 2780, GRID grid.5801.c, Computational Social Science, , ETH Zurich, ; Zurich, Switzerland
                [30 ]ISNI 0000 0004 1937 0626, GRID grid.4714.6, Department of Public Health Sciences, , Karolinska Institutet, ; Stockholm, Sweden
                [31 ]ISNI 0000 0001 1214 1861, GRID grid.419684.6, Stockholm School of Economics, ; Stockholm, Sweden
                [32 ]ISNI 0000 0001 2353 6535, GRID grid.428999.7, Insect–Virus Interactions Unit, , Institut Pasteur, CNRS, ; UMR2000 Paris, France
                [33 ]ISNI 0000 0001 2353 6535, GRID grid.428999.7, Mathematical Modelling of Infectious Diseases Unit, , Institut Pasteur, CNRS, ; UMR2000 Paris, France
                [34 ]ISNI 0000 0001 2242 8479, GRID grid.6520.1, Department of Geography, , Universite de Namur, ; Namur, Belgium
                [35 ]ISNI 0000 0004 1936 9684, GRID grid.27860.3b, Department of Entomology and Nematology, , University of California, Davis, ; Davis, CA USA
                [36 ]ISNI 0000 0000 8803 2373, GRID grid.198530.6, State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, , Chinese Center for Disease Control and Prevention, Changping, ; Beijing, China
                [37 ]ISNI 0000 0004 1761 1174, GRID grid.27255.37, Shandong University Climate Change and Health Center, School of Public Health, , Shandong University, Jinan, ; Shandong, China
                [38 ]WHO Collaborating Centre for Vector Surveillance and Management, Beijing, China
                [39 ]Chongqing Centre for Disease Control and Prevention, Chongqing, China
                [40 ]ISNI 0000 0004 1936 8948, GRID grid.4991.5, Environmental Research Group Oxford (ERGO), Department of Zoology, , Oxford University, ; Oxford, UK
                [41 ]ISNI 0000 0001 2179 088X, GRID grid.1008.9, School of BioSciences, , University of Melbourne, ; Parkville, Victoria Australia
                Author information
                http://orcid.org/0000-0001-8838-7147
                http://orcid.org/0000-0002-7205-9621
                http://orcid.org/0000-0002-6644-518X
                http://orcid.org/0000-0002-5821-6651
                http://orcid.org/0000-0003-4367-3849
                http://orcid.org/0000-0001-5958-2138
                http://orcid.org/0000-0002-0819-7755
                http://orcid.org/0000-0002-9747-8822
                http://orcid.org/0000-0002-0611-7272
                http://orcid.org/0000-0001-8916-5570
                Article
                376
                10.1038/s41564-019-0376-y
                6522366
                30833735
                de5d3124-2c3c-40be-8b28-f35c57ff7762
                © The Author(s), under exclusive licence to Springer Nature Limited 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 20 November 2018
                : 18 January 2019
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                © The Author(s), under exclusive licence to Springer Nature Limited 2019

                microbiology,infectious diseases
                microbiology, infectious diseases

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