ArticleParasites & vectors2020
Spatial modelling of the infestation indices of Aedes aegypti: an innovative strategy for vector control actions in developing countries.
Article in Parasites & vectors, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 27 citations in OpenAlex.
- Influence of climatic and land use factors on post-monsoon distribution of Aedes mosquito vectors in Udupi taluk.Scientific reports · 2025Observational
- Effects of the El Niño-Southern Oscillation and seasonal weather conditions on Aedes aegypti infestation in the State of São Paulo (Brazil): A Bayesian spatio-temporal study.PLoS neglected tropical diseases · 2024Article
- Cancer survival analysis and spatial distribution during 2014-2016 in Shandong Province, China.Scientific reports · 2023Article
- Identification of risk areas for arboviruses transmitted byOne health (Amsterdam, Netherlands) · 2023Article
- Spatiotemporal dynamics and recurrence of chikungunya virus in Brazil: an epidemiological study.The Lancet. Microbe · 2023Article
- Spatial patterns associated with the distribution of immature stages ofGigaByte (Hong Kong, China) · 2023Article
- Prevention and control of mosquito-borne arboviral diseases: lessons learned from a school-based intervention in Brazil (Zikamob).BMC public health · 2022Article
- Dengue Risk Forecast with Mosquito Vector: A Multicomponent Fusion Approach Based on Spatiotemporal Analysis.Computational and mathematical methods in medicine · 2022Article
- Spatial Distribution of Road Traffic Accident at Hawassa City Administration, Ethiopia.Ethiopian journal of health sciences · 2021Article
- Identification of high-risk and low-risk clusters and estimation of the relative risk of acute lymphoblastic leukemia in provinces of Iran during 2006-2014 period: A geo-epidemiological study.Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences · 2021Article
- MEWAR: Development of a Cross-Platform Mobile Application and Web Dashboard System for Real-Time Mosquito Surveillance in Northeast Brazil.Frontiers in public health · 2021Article
- Larval Indices of Vector Mosquitoes as Predictors of Dengue Epidemics: An Approach to Manage Dengue Outbreaks Based on Entomological Parameters in the Districts of Colombo and Kandy, Sri Lanka.BioMed research international · 2020Article
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundLarval indices such as the house index (HI), Breteau index (BI) and container index (CI) are widely used to interpret arbovirus vector density in surveillance programmes. However, the use of such data as an alarm signal is rarely considered consciously when planning programmes. The present study aims to investigate the spatial distribution pattern of the infestation of Aedes aegypti, considering the data available in the Ae. aegypti Infestation Index Rapid Survey (LIRAa) for the city of Campina Grande, Paraíba State in Brazil.
methodsThe global and local Moran's indices were used in spatial analysis to measure the effects of spatial dependencies between neighbourhoods, using secondary data related to HI and BI gathered from surveillance service.
resultsOur analysis shows that there is a predominance of high rates of mosquito infestation, placing Campina Grande at a near-constant risk of arbovirus outbreaks and epidemics. A highly significant Moran's index value (P < 0.001) was observed, indicating a positive spatial dependency between the neighbourhoods in Campina Grande. Using the Moran mapping and LISA mapping, the autocorrelation patterns of Ae. aegypti infestation rates among neighbourhoods have revealed hotpots that should be considered a priority to preventive actions of the entomological surveillance services. Predominance of high infestation rates and clearer relationships of these between neighbourhoods were observed between the months of May and July, the period with the highest rainfall in the city.
conclusionsThis analysis is an innovative strategy capable of providing detailed information on infestation locations to the relevant public health authorities, which will enable a more efficient allocation of resources, particularly for arbovirus prevention.
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