About: Spatial modelling of the infestation indices of Aedes aegypti: an innovative strategy for vector control actions in developing countries

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About: Spatial modelling of the infestation indices of Aedes aegypti: an innovative strategy for vector control actions in developing countries Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Spatial modelling of the infestation indices of Aedes aegypti: an innovative strategy for vector control actions in developing countries
Creator	Carolina, Ana Traxler, John Gomes, Alexandrino Santos, Silvana Smith, Matt Alves De Olinda, Ricardo Cavalcante, Policarpo
Source	PMC
abstract	BACKGROUND: Larval 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. METHODS: The global and local Moranʼs 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. RESULTS: Our 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 Moranʼs 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. CONCLUSIONS: This 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. [Image: see text]
has issue date	2020-04-16(xsd:dateTime)
bibo:doi	10.1186/s13071-020-04070-w
bibo:pmid	32299496
has license	cc-by
sha1sum (hex)	4e3aeec6bb6ea379bb97845dccfbbc832808264c
schema:url	https://doi.org/10.1186/s13071-020-04070-w
resource representing a document's title	Spatial modelling of the infestation indices of Aedes aegypti: an innovative strategy for vector control actions in developing countries
has PubMed Central identifier	PMC7164210
has PubMed identifier	32299496
schema:publication	Parasit Vectors
resource representing a document's body	covid:4e3aeec6bb6ea379bb97845dccfbbc832808264c#body_text
is schema:about of	named entity 'data' named entity 'Larval' named entity 'However' named entity 'strategy' named entity 'Spatial' named entity 'house' named entity 'arbovirus' named entity 'vector' named entity 'Brazil' named entity 'arbovirus' named entity 'Campina Grande' named entity 'mosquito' named entity 'dengue' named entity 'Ae. aegypti' named entity 'autocorrelation' named entity 'socioeconomic' named entity 'Breteau' named entity 'Ae. aegypti' named entity 'spatial autocorrelation' named entity 'insecticides' named entity 'Campina Grande' named entity 'scientific research' named entity 'spatial autocorrelation' named entity 'Maranhão' named entity 'natural history of disease' named entity 'Monte Castelo' named entity 'spatial autocorrelation' named entity 'epidemics' named entity 'relative humidity' named entity 'wet season' named entity 'vector' named entity 'east zone' named entity 'autocorrelation' named entity 'mosquito' named entity 'northeast Brazil' named entity 'climate change' named entity 'socioeconomic conditions' named entity 'mosquito breeding' named entity 'South America' named entity 'dengue fever' named entity 'disease vectors' named entity 'ith' named entity 'endemic disease' named entity 'domestic water' named entity 'Cruzeiro' named entity 'dengue' named entity 'cross-reactivity' named entity 'Taiwan' named entity 'Vila Cabral' named entity 'arbovirus' named entity 'demographic' named entity 'Kenya' named entity 'Zika virus' named entity 'spatial dependence' named entity 'Brazil' named entity 'Greater São Paulo' named entity 'mosquito' named entity 'dengue' named entity 'Thailand' named entity 'vector' named entity 'congenital' named entity 'Taiwan' named entity 'LISA' named entity 'José Pinheiro' named entity 'Ae. aegypti' named entity 'vector' named entity 'socioeconomic conditions' named entity 'Campina Grande' named entity 'Epidemiological studies' named entity 'population density' named entity 'Spatial correlation' named entity 'dengue' named entity 'dengue' named entity 'Brazil' named entity 'vector'

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