Modelo de risco tempo-espacial para identificação de áreas de risco para ocorrência de dengue

Galli, Bruno; Neto, Francisco Chiaravalloti

doi:10.1590/s0034-89102008005000032

Cited by 11 publications

(11 citation statements)

References 12 publications

(9 reference statements)

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“…Moreover, a higher transmission in poor areas of SJRP has been shown, especially in the north zones of the city [47]. Therefore, it is relevant to further evaluate if the occurrence of transmission in poor areas facilitates a higher dispersion of the virus to other areas of the city.…”

Section: Discussionmentioning

confidence: 99%

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Spatio-Temporal Tracking and Phylodynamics of an Urban Dengue 3 Outbreak in São Paulo, Brazil

et al. 2009

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The dengue virus has a single-stranded positive-sense RNA genome of ∼10.700 nucleotides with a single open reading frame that encodes three structural (C, prM, and E) and seven nonstructural (NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5) proteins. It possesses four antigenically distinct serotypes (DENV 1–4). Many phylogenetic studies address particularities of the different serotypes using convenience samples that are not conducive to a spatio-temporal analysis in a single urban setting. We describe the pattern of spread of distinct lineages of DENV-3 circulating in São José do Rio Preto, Brazil, during 2006. Blood samples from patients presenting dengue-like symptoms were collected for DENV testing. We performed M-N-PCR using primers based on NS5 for virus detection and identification. The fragments were purified from PCR mixtures and sequenced. The positive dengue cases were geo-coded. To type the sequenced samples, 52 reference sequences were aligned. The dataset generated was used for iterative phylogenetic reconstruction with the maximum likelihood criterion. The best demographic model, the rate of growth, rate of evolutionary change, and Time to Most Recent Common Ancestor (TMRCA) were estimated. The basic reproductive rate during the epidemics was estimated. We obtained sequences from 82 patients among 174 blood samples. We were able to geo-code 46 sequences. The alignment generated a 399-nucleotide-long dataset with 134 taxa. The phylogenetic analysis indicated that all samples were of DENV-3 and related to strains circulating on the isle of Martinique in 2000–2001. Sixty DENV-3 from São José do Rio Preto formed a monophyletic group (lineage 1), closely related to the remaining 22 isolates (lineage 2). We assumed that these lineages appeared before 2006 in different occasions. By transforming the inferred exponential growth rates into the basic reproductive rate, we obtained values for lineage 1 of R0 = 1.53 and values for lineage 2 of R0 = 1.13. Under the exponential model, TMRCA of lineage 1 dated 1 year and lineage 2 dated 3.4 years before the last sampling. The possibility of inferring the spatio-temporal dynamics from genetic data has been generally little explored, and it may shed light on DENV circulation. The use of both geographic and temporally structured phylogenetic data provided a detailed view on the spread of at least two dengue viral strains in a populated urban area.

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Section: Discussionmentioning

confidence: 99%

“…The socioeconomic features lost its explanatory power as the years passed and the spatial characteristic of the areas was more relevant [54]. A higher transmission of dengue in poor areas of the north zone was observed again in 2005–2006 [47].…”

Section: Discussionmentioning

confidence: 99%

Spatio-Temporal Tracking and Phylodynamics of an Urban Dengue 3 Outbreak in São Paulo, Brazil

et al. 2009

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“…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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“…Also authors agree that transmission depends on the environmental context and on variables that were not taken into consideration in this study, e.g., populational immunity, circulating serotypes, and control measures [14]–[16], [27], [47], [51]. Furthermore, underreporting of cases is also assumed because some patients were either asymptomatic or had mild symptoms, which were not reported to the health services, as mentioned in various studies [20], [31], [52], [53].…”

Section: Discussionmentioning

confidence: 82%

“…These techniques allow the development of models to predict the risk of disease and territorial infestation, mapping environmental and social conditions associated to such patterns [26]. A number of studies using these techniques have analyzed the spatial and temporal distribution of A. aegypti [27], [28] and dengue transmission [29]–[32], as well as their relationships between each other [33], [34].…”

Section: Introductionmentioning

confidence: 99%

Spatial Distribution of the Risk of Dengue and the Entomological Indicators in Sumaré, State of São Paulo, Brazil

et al. 2014

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Dengue fever is a major public health problem worldwide, caused by any of four virus (DENV-1, DENV-2, DENV-3 and DENV-4; Flaviviridae: Flavivirus), transmitted by Aedes aegypti mosquito. Reducing the levels of infestation by A. aegypti is one of the few current strategies to control dengue fever. Entomological indicators are used by dengue national control program to measure the infestation of A. aegypti, but little is known about predictive power of these indicators to measure dengue risk. In this spatial case-control study, we analyzed the spatial distribution of the risk of dengue and the influence of entomological indicators of A. aegypti in its egg, larva-pupa and adult stages occurring in a mid-size city in the state of São Paulo. The dengue cases were those confirmed by the city's epidemiological surveillance system and the controls were obtained through random selection of points within the perimeter of the inhabited area. The values of the entomological indicators were extrapolated for the entire study area through the geostatistical ordinary kriging technique. For each case and control, the respective indicator values were obtained, according with its geographical coordinates and analyzed by using a generalized additive model. Dengue incidence demonstrated a seasonal behavior, as well as the entomological indicators of all mosquito's evolutionary stages. The infestation did not present a significant variation in intensity and was not a limiting or determining factor of the occurrence of cases in the municipality. The risk maps of the disease from crude and adjusted generalized additive models did not present differences, suggesting that areas with the highest values of entomological indicators were not associated with the incidence of dengue. The inclusion of other variables in the generalized additive models may reveal the modulatory effect for the risk of the disease, which is not found in this study.

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Modelo de risco tempo-espacial para identificação de áreas de risco para ocorrência de dengue

Cited by 11 publications

References 12 publications

Spatio-Temporal Tracking and Phylodynamics of an Urban Dengue 3 Outbreak in São Paulo, Brazil

Spatio-Temporal Tracking and Phylodynamics of an Urban Dengue 3 Outbreak in São Paulo, Brazil

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

Spatial Distribution of the Risk of Dengue and the Entomological Indicators in Sumaré, State of São Paulo, Brazil

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