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Systematic Review: Land Cover, Meteorological, and Socioeconomic Determinants of Aedes Mosquito Habitat for Risk Mapping

Author

Listed:
  • Mohamed F. Sallam

    (Resilient Environment and Health, Agriculture and Water Solutions, National Exposure Research laboratory/System Exposure Division, Oak Ridge Institute for Science and Education, 109 T.W. Alexander Dr., Research Triangle Park, NC 27711, USA)

  • Chelsea Fizer

    (Oak Ridge Associated Universities, Contractor to US EPA, Office of Research and Development, National Exposure Research Laboratory, Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA)

  • Andrew N. Pilant

    (Office of Research and Development, National Exposure Research Laboratory, Environmental Protection Agency, 109 T.W, Oak Ridge Associated Universities, Alexander Drive, Research Triangle Park, Oak Ridge, NC 27711, USA)

  • Pai-Yei Whung

    (Office of Research and Development, National Exposure Research Laboratory, Environmental Protection Agency, 109 T.W, Oak Ridge Associated Universities, Alexander Drive, Research Triangle Park, Oak Ridge, NC 27711, USA)

Abstract

Asian tiger and yellow fever mosquitoes ( Aedes albopictus and Ae. aegypti ) are global nuisances and are competent vectors for viruses such as Chikungunya (CHIKV), Dengue (DV), and Zika (ZIKV). This review aims to analyze available spatiotemporal distribution models of Aedes mosquitoes and their influential factors. A combination of five sets of 3–5 keywords were used to retrieve all relevant published models. Five electronic search databases were used: PubMed, MEDLINE, EMBASE, Scopus, and Google Scholar through 17 May 2017. We generated a hierarchical decision tree for article selection. We identified 21 relevant published studies that highlight different combinations of methodologies, models and influential factors. Only a few studies adopted a comprehensive approach highlighting the interaction between environmental, socioeconomic, meteorological and topographic systems. The selected articles showed inconsistent findings in terms of number and type of influential factors affecting the distribution of Aedes vectors, which is most likely attributed to: (i) limited availability of high-resolution data for physical variables, (ii) variation in sampling methods; Aedes feeding and oviposition behavior; (iii) data collinearity and statistical distribution of observed data. This review highlights the need and sets the stage for a rigorous multi-system modeling approach to improve our knowledge about Aedes presence/abundance within their flight range in response to the interaction between environmental, socioeconomic, and meteorological systems.

Suggested Citation

  • Mohamed F. Sallam & Chelsea Fizer & Andrew N. Pilant & Pai-Yei Whung, 2017. "Systematic Review: Land Cover, Meteorological, and Socioeconomic Determinants of Aedes Mosquito Habitat for Risk Mapping," IJERPH, MDPI, vol. 14(10), pages 1-15, October.
    • Handle: RePEc:gam:jijerp:v:14:y:2017:i:10:p:1230-:d:115162
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    References listed on IDEAS

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    1. Mohamed F. Sallam & Sarah R. Michaels & Claudia Riegel & Roberto M. Pereira & Wayne Zipperer & B. Graeme Lockaby & Philip G. Koehler, 2017. "Spatio-Temporal Distribution of Vector-Host Contact (VHC) Ratios and Ecological Niche Modeling of the West Nile Virus Mosquito Vector, Culex quinquefasciatus, in the City of New Orleans, LA, USA," IJERPH, MDPI, vol. 14(8), pages 1-20, August.
    2. Cyril Caminade & Jacques A. Ndione & Mawlouth Diallo & Dave A. MacLeod & Ousmane Faye & Yamar Ba & Ibrahima Dia & Andrew P. Morse, 2014. "Rift Valley Fever Outbreaks in Mauritania and Related Environmental Conditions," IJERPH, MDPI, vol. 11(1), pages 1-16, January.
    3. Pickard, Brian R. & Daniel, Jessica & Mehaffey, Megan & Jackson, Laura E. & Neale, Anne, 2015. "EnviroAtlas: A new geospatial tool to foster ecosystem services science and resource management," Ecosystem Services, Elsevier, vol. 14(C), pages 45-55.
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    1. Thomas C. McHale & Claudia M. Romero-Vivas & Claudio Fronterre & Pedro Arango-Padilla & Naomi R. Waterlow & Chad D. Nix & Andrew K. Falconar & Jorge Cano, 2019. "Spatiotemporal Heterogeneity in the Distribution of Chikungunya and Zika Virus Case Incidences during their 2014 to 2016 Epidemics in Barranquilla, Colombia," IJERPH, MDPI, vol. 16(10), pages 1-21, May.
    2. Shi Yin & Chao Ren & Yuan Shi & Junyi Hua & Hsiang-Yu Yuan & Lin-Wei Tian, 2022. "A Systematic Review on Modeling Methods and Influential Factors for Mapping Dengue-Related Risk in Urban Settings," IJERPH, MDPI, vol. 19(22), pages 1-20, November.
    3. Zhichao Li & Helen Gurgel & Nadine Dessay & Luojia Hu & Lei Xu & Peng Gong, 2020. "Semi-Supervised Text Classification Framework: An Overview of Dengue Landscape Factors and Satellite Earth Observation," IJERPH, MDPI, vol. 17(12), pages 1-29, June.
    4. Daniel Adyro Martínez-Bello & Antonio López-Quílez & Alexander Torres Prieto, 2018. "Spatio-Temporal Modeling of Zika and Dengue Infections within Colombia," IJERPH, MDPI, vol. 15(7), pages 1-18, June.
    5. Johnny A. Uelmen & Charles Brokopp & Jonathan Patz, 2020. "A 15 Year Evaluation of West Nile Virus in Wisconsin: Effects on Wildlife and Human Health," IJERPH, MDPI, vol. 17(5), pages 1-24, March.

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