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      Mapping infectious disease landscapes: unmanned aerial vehicles and epidemiology.

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          Abstract

          The potential applications of unmanned aerial vehicles (UAVs), or drones, have generated intense interest across many fields. UAVs offer the potential to collect detailed spatial information in real time at relatively low cost and are being used increasingly in conservation and ecological research. Within infectious disease epidemiology and public health research, UAVs can provide spatially and temporally accurate data critical to understanding the linkages between disease transmission and environmental factors. Using UAVs avoids many of the limitations associated with satellite data (e.g., long repeat times, cloud contamination, low spatial resolution). However, the practicalities of using UAVs for field research limit their use to specific applications and settings. UAVs fill a niche but do not replace existing remote-sensing methods.

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          Author and article information

          Journal
          Trends Parasitol.
          Trends in parasitology
          1471-5007
          1471-4922
          Nov 2014
          : 30
          : 11
          Affiliations
          [1 ] Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK. Electronic address: Kimberly.Fornace@lshtm.ac.uk.
          [2 ] Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK.
          [3 ] Infectious Diseases Society Sabah, Menzies School of Health Research Clinical Research Unit, Kota Kinabalu, Sabah, Malaysia; Infectious Diseases Unit, Clinical Research Centre, Queen Elizabeth Hospital, Kota Kinabalu, Sabah, Malaysia; Sabah Department of Health, Kota Kinabalu, Sabah, Malaysia.
          [4 ] Research Institute for Tropical Medicine, Department of Health, Filinvest, Alabang, Muntinlupa City, Philippines.
          Article
          S1471-4922(14)00146-9
          10.1016/j.pt.2014.09.001
          25443854
          1e94cc97-6ce7-4d19-a02c-11083d163bbc
          Copyright © 2014 Elsevier Ltd. All rights reserved.
          History

          Plasmodium knowlesi,drone,geographic information system,malaria,spatial epidemiology,unmanned aerial vehicle

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