Spatial point analysis based on dengue surveys at household level in central Brazil

Siqueira-Junior, João B; Maciel, Ivan José; Barcellos, Christovam; Souza, Wayner Vieira de; Carvalho, Marília Sá; Nascimento, Nazareth E; Oliveira, Reinaldo Cunha de; Morais-Neto, Otaliba L.; Martelli, C. M. T.

doi:10.1186/1471-2458-8-361

Cited by 62 publications

(50 citation statements)

References 32 publications

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“…Since the 1990s, the analysis techniques have been improved to generate identifi cation maps of risk areas, resulting in differentiated attention being given by the health services. 6,21,22 Examples are the Brazilian studies that have used different spatial analysis techniques based on individual and aggregated data to identify areas that present higher risk of dengue. 5,11,16,23,27 The present study aimed to analyze the dengue epidemic in relation to the socioeconomic context.…”

Section: Introductionmentioning

confidence: 99%

Análise espacial da dengue e o contexto socioeconômico no município do Rio de Janeiro, RJ

2009

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OBJECTIVE:To analyze the dengue epidemic in relation to the socioeconomic context according to geographical areas. METHODS:An ecological study was conducted in the municipality of Rio de Janeiro (Southeastern Brazil), in areas delimited as neighborhoods, based on information about notifi ed dengue cases concerning residents in the municipality. The average incidence rate of dengue was calculated between the epidemiological weeks: 48 th of 2001 and 20 th of 2002. The occurrence of dengue was correlated with socioeconomic variables through Pearsons' correlation coeffi cient. Moran's global and local indexes were used to assess the spatial auto-correlation between dengue and the variables that signifi cantly correlated with the disease. The multiple linear regression model and the conditional auto-regression spatial model were used to analyze the relationship between dengue and socioeconomic context. RESULTS:The neighborhoods located in the west zone of the municipality presented high rates of average dengue incidence. The variables presenting signifi cant correlation were: percentage of households connected with the general sanitary network, households with washing machines, and population density per urban area. Moran's spatial auto-correlation index revealed spatial dependence between dengue and the selected variables. The utilized models indicated percentage of households connected with the general sanitary network as the sole variable signifi cantly associated with the disease. The residual fi gures in both models revealed signifi cant spatial auto-correlation, with a positive Moran Index (p<0.001) for linear regression model, and a negative one (p=0.005) for the conditional auto-regression one. CONCLUSIONS:Problems related to basic sanitation contribute decisively to increase the risk of the disease.

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Section: Introductionmentioning

confidence: 99%

Análise espacial da dengue e o contexto socioeconômico no município do Rio de Janeiro, RJ

2009

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“…4), where there is limited access to water, high population density high building density, and low neighbourhood quality. Several studies (Honório et al, 2003;Lagrotta et al, 2008;Siqueira-Junior et al, 2008;, found that Aedes mosquitoes and DF risk cases increase in areas with high human population density and high concentrations of dwellings. Similar results were also found by da Costa and Natal (1998), who stated that people from low socioeconomic backgrounds are more affected and at a greater risk of contracting DF.…”

Section: Discussionmentioning

confidence: 99%

“…Siqueira-Junior et al, 2008), using household surveys, spatial point pattern analysis and risk factor assessments, demonstrating that lowprevalence areas can easily shift to high-risk areas from one year to the next. GIS and statistical methods can play an important role in formulating control activities, assessing changes in transmission over time and determining resources to control prevalence, particularly in areas of high or persistent transmission (Allen and Wong, 2006;Bautista et al, 2006;Achu, 2008;Bhandari et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

Assessing the risk for dengue fever based on socioeconomic and environmental variables in a geographical information system environment

Khormi

Kumar

2012

Geospat Health

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Abstract. An important option in preventing the spread of dengue fever (DF) is to control and monitor its vector (Aedes aegypti) as well as to locate and destroy suitable mosquito breeding environments. The aim of the present study was to use a combination of environmental and socioeconomic variables to model areas at risk of DF. These variables include clinically confirmed DF cases, mosquito counts, population density in inhabited areas, total populations per district, water access, neighbourhood quality and the spatio-temporal risk of DF based on the average, weekly frequency of DF incidence. Out of 111 districts investigated, 17 (15%), covering a total area of 121 km², were identified as of high risk, 25 (22%), covering 133 km², were identified as of medium risk, 18 (16%), covering 180 km², were identified as of low risk and 51 (46%), covering 726 km², were identified as of very low risk. The resultant model shows that most areas at risk of DF were concentrated in the central part of Jeddah county, Saudi Arabia. The methods used can be implemented as routine procedures for control and prevention. A concerted intervention in the medium-and high-risk level districts identified in this study could be highly effective in reducing transmission of DF in the area as a whole.

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“…In addition, the lack of a relationship between precipitation and number of breeding sites found in Puerto Iguazú City (Rotela, 2012) highlights the importance of the use of water storage containers and the increase of mosquito breeding sites independently of this weather variable. Therefore, a chain is created resulting in an increase in vector density leading to an increase in vector-human contact that finally produces a higher viral transmission rates among the human population during epidemic events (Siqueira-Junior et al, 2008;Eisen and Lozano-Fuentes, 2009). This converts the detection of vector density changes into an important factor in the epidemiology of the disease (Niño, 2011).…”

Section: Discussionmentioning

confidence: 99%

Spatial pattern evolution of Aedes aegypti breeding sites in an Argentinean city without a dengue vector control programme

et al. 2016

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The main objective of this study was to obtain and analyse the space-time dynamics of Aedes aegypti breeding sites in Clorinda City, Formosa Province, Argentina coupled with landscape analysis using the maximum entropy approach in order to generate a dengue vector niche model. In urban areas, without vector control activities, 12 entomologic (larval) samplings were performed during three years (October 2011 to October 2014). The entomologic surveillance area represented 16,511 houses. Predictive models for Aedes distribution were developed using vector breeding abundance data, density analysis, clustering and geoprocessing techniques coupled with Earth observation satellite data. The spatial analysis showed a vector spatial distribution pattern with clusters of high density in the central region of Clorinda with a well-defined high-risk area in the western part of the city. It also showed a differential temporal behaviour among different areas, which could have implications for risk models and control strategies at the urban scale. The niche model obtained for Ae. aegypti, based on only one year of field data, showed that 85.8% of the distribution of breeding sites is explained by the percentage of water supply (48.2%), urban distribution (33.2%), and the percentage of urban coverage (4.4%). The consequences for the development of control strategies are discussed with reference to the results obtained using distribution maps based on environmental variables.

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Spatial point analysis based on dengue surveys at household level in central Brazil

Cited by 62 publications

References 32 publications

Análise espacial da dengue e o contexto socioeconômico no município do Rio de Janeiro, RJ

Análise espacial da dengue e o contexto socioeconômico no município do Rio de Janeiro, RJ

Assessing the risk for dengue fever based on socioeconomic and environmental variables in a geographical information system environment

Spatial pattern evolution of Aedes aegypti breeding sites in an Argentinean city without a dengue vector control programme

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