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Projeto de investigação
Modelação estocástica e espaciotemporal da incidência de doenças transmitidas por vetores em Portugal
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Spatiotemporal analysis of mosquito-borne infections and mosquito vectors in mainland Portugal
Publication . Moutinho, Sandra; Rocha, Jorge; Gomes, Alberto; Gomes, Bernardo; Ribeiro, Ana Isabel
Background The incidence of mosquito-borne infections has increased worldwide. Mainland Portugal’s
characteristics might favour the (re)emergence of mosquito-borne diseases. This study aimed to characterize the spatial distribution of vectors and notification rates of imported cases of mosquito-borne infections in mainland Portugal and demarcate the areas where these geographies overlap.
Methods We used data from imported cases of malaria, dengue and Zika from 2009 to 2019, alongside data on the presence of mosquitoes capable of potentially transmitting these diseases at the municipality level (2009–2018). This data was provided by the National Epidemiological Surveillance System and Regional Health Administrations, based on reports from the Vector Surveillance Network. While the mosquitoes in question do not currently transmit these diseases, they have the potential to do so if there is a significant increase in pathogen circulation. A spatial cluster analysis was performed using the univariate Local Moran Index, the Bivariate Moran Local Index and the MannKendall method.
Results We found significant spatial variability in both notification rates of imported mosquito-borne infections
and the distribution of competent mosquito species. We identified clusters of simultaneous high concentrations
of vectors and imported cases of malaria in Condeixa-a-Nova (Coimbra), Cuba (Beja), Santiago do Cacém (Setúbal), Albufeira and São Brás de Alportel (Faro), most located on the Southern coast of Portugal. For dengue, we detected clusters of simultaneous high concentrations of vectors and imported cases in Paredes, in the Northern region, and Faro, on the southern coast. For Zika, no clusters were identified.
Conclusion This study identified areas with high notification rates of imported cases and the presence of competent vectors. Surveillance, control, and awareness efforts are essential, as these areas may present higher risks for local transmission in the future if ecological conditions remain or become suitable, potentially evolving into foci for disease transmission.
Spatial Analysis of Mosquito-Borne Diseases in Europe: A Scoping Review
Publication . Moutinho, Sandra; Rocha, Jorge; Gomes, Alberto; Gomes, Bernardo; Ribeiro, Ana Isabel
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.
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Entidade financiadora
Fundação para a Ciência e a Tecnologia
Programa de financiamento
POR_CENTRO
Número da atribuição
2020.07201.BD