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Spatial Analysis of Mosquito-Borne Diseases in Europe: A Scoping Review

Author

Listed:
  • Sandra Moutinho

    (Departamento de Geografia, Faculdade de Letras e Centro de Estudos de Geografia e Ordenamento do Território, Universidade do Porto, 4150-564 Porto, Portugal)

  • Jorge Rocha

    (Instituto de Geografia e Ordenamento do Território, Universidade de Lisboa e Laboratório Associado Terra, 1600-276 Lisboa, Portugal)

  • Alberto Gomes

    (Departamento de Geografia, Faculdade de Letras e Centro de Estudos de Geografia e Ordenamento do Território, Universidade do Porto, 4150-564 Porto, Portugal)

  • Bernardo Gomes

    (EPIUnit–Instituto de Saúde Pública, Universidade do Porto, 4050-600 Porto, Portugal
    Unidade de Saúde Pública Entre Douro e Vouga I. Administração Regional de Saúde do Norte, 4520-244 Porto, Portugal)

  • Ana Isabel Ribeiro

    (EPIUnit–Instituto de Saúde Pública, Universidade do Porto, 4050-600 Porto, Portugal
    Departamento de Ciências da Saúde Pública e Forenses e Educação Médica, Faculdade de Medicina, Universidade do Porto, 4200-319 Porto, Portugal
    Laboratório para a Investigação Integrativa e Translacional em Saúde Populacional (ITR), Rua das Taipas 135, 4050-600 Porto, Portugal)

Abstract

Mosquito-borne infections are increasing in endemic areas and previously unaffected regions. In 2020, the notification rate for Dengue was 0.5 cases per 100,000 population, and for Chikungunya <0.1/100,000. In 2019, the rate for Malaria was 1.3/100,000, and for West Nile Virus, 0.1/100,000. Spatial analysis is increasingly used in surveillance and epidemiological investigation, but reviews about their use in this research topic are scarce. We identify and describe the methodological approaches used to investigate the distribution and ecological determinants of mosquito-borne infections in Europe. Relevant literature was extracted from PubMed, Scopus, and Web of Science from inception until October 2021 and analysed according to PRISMA-ScR protocol. We identified 110 studies. Most used geographical correlation analysis ( n = 50), mainly applying generalised linear models, and the remaining used spatial cluster detection ( n = 30) and disease mapping ( n = 30), mainly conducted using frequentist approaches. The most studied infections were Dengue ( n = 32), Malaria ( n = 26), Chikungunya ( n = 26), and West Nile Virus ( n = 24), and the most studied ecological determinants were temperature ( n = 39), precipitation ( n = 24), water bodies ( n = 14), and vegetation ( n = 11). Results from this review may support public health programs for mosquito-borne disease prevention and may help guide future research, as we recommended various good practices for spatial epidemiological studies.

Suggested Citation

  • Sandra Moutinho & Jorge Rocha & Alberto Gomes & Bernardo Gomes & Ana Isabel Ribeiro, 2022. "Spatial Analysis of Mosquito-Borne Diseases in Europe: A Scoping Review," Sustainability, MDPI, vol. 14(15), pages 1-20, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:8975-:d:868768
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    References listed on IDEAS

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    1. Eduardo Gomes & César Capinha & Jorge Rocha & Carla Sousa, 2016. "Mapping Risk of Malaria Transmission in Mainland Portugal Using a Mathematical Modelling Approach," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-17, November.
    2. Stephanie Margarete Thomas & Nils Benjamin Tjaden & Christina Frank & Anja Jaeschke & Lukas Zipfel & Christiane Wagner-Wiening & Mirko Faber & Carl Beierkuhnlein & Klaus Stark, 2018. "Areas with High Hazard Potential for Autochthonous Transmission of Aedes albopictus -Associated Arboviruses in Germany," IJERPH, MDPI, vol. 15(6), pages 1-12, June.
    3. David Moher & Alessandro Liberati & Jennifer Tetzlaff & Douglas G Altman & The PRISMA Group, 2009. "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-6, July.
    4. Andrew J Tatem & Abdisalan M Noor & Craig von Hagen & Antonio Di Gregorio & Simon I Hay, 2007. "High Resolution Population Maps for Low Income Nations: Combining Land Cover and Census in East Africa," PLOS ONE, Public Library of Science, vol. 2(12), pages 1-8, December.
    5. Carla Ippoliti & Luca Candeloro & Marius Gilbert & Maria Goffredo & Giuseppe Mancini & Gabriele Curci & Serena Falasca & Susanna Tora & Alessio Di Lorenzo & Michela Quaglia & Annamaria Conte, 2019. "Defining ecological regions in Italy based on a multivariate clustering approach: A first step towards a targeted vector borne disease surveillance," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-21, July.
    6. Beniamino Caputo & Mattia Manica & Federico Filipponi & Marta Blangiardo & Pietro Cobre & Luca Delucchi & Carlo Maria De Marco & Luca Iesu & Paola Morano & Valeria Petrella & Marco Salvemini & Cesare , 2020. "ZanzaMapp: A Scalable Citizen Science Tool to Monitor Perception of Mosquito Abundance and Nuisance in Italy and Beyond," IJERPH, MDPI, vol. 17(21), pages 1-19, October.
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    1. Adivânia Cardoso da Silva & Paulo Sérgio Scalize, 2023. "Environmental Variables Related to Aedes aegypti Breeding Spots and the Occurrence of Arbovirus Diseases," Sustainability, MDPI, vol. 15(10), pages 1-21, May.

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