Spatial patterns of dengue cases in Brazil.
Ontology highlight
ABSTRACT:
SUBMITTER: Antonio FJ
PROVIDER: S-EPMC5513438 | biostudies-literature | 2017
REPOSITORIES: biostudies-literature
Publications
Spatial patterns of dengue cases in Brazil.
Antonio Fernando Jose FJ Itami Andreia Silva AS de Picoli Sergio S Teixeira Jorge Juarez Vieira JJV Mendes Renio Dos Santos RDS
PloS one 20170717 7
Dengue infection plays a central role in our society, since it is the most prevalent vector-borne viral disease affecting humans. We statistically investigated patterns concerning the spatial spreading of dengue epidemics in Brazil, as well as their temporal evolution in all Brazilian municipalities for a period of 12 years. We showed that the distributions of cases in municipalities follow power laws persistent in time and that the infection scales linearly with the population of the municipali ...[more]
Similar Datasets
Project description:Dengue is a viral disease caused by an arbovirus of the genus Flavivirus transmitted in Brazil by the mosquito Aedes aegypti (Linnaeus, 1762). Simultaneous circulation of the four viral serotypes (DENV1, 2, 3 and 4) has been occurring since 2010 and determines a scenario of hyperendemicity of the disease in the country. This study aimed to describe the epidemiological situation of dengue in Brazil in the last three decades. This is a descriptive, observational study that used data of dengue notifications of the National Surveillance System from 1990 to 2017, available in the Epidemiological Bulletins and publications of the Ministry of Health. Dengue incidence increased in all Brazilian regions and the interepidemic periods are distinct in the different regions. The greatest epidemics was recorded in 2015 (1,688,688 cases), with an incidence of 826.0 cases per 100,000 inhabitants, which illustrates the occurrence of dengue in the last decade with increasingly higher epidemic peaks and shortening of the interepidemic periods. The incidence and mortality indices point to the need to improve the organization of response to dengue epidemics. This study provides information on the epidemiology of dengue in the country and can be used in the formulation of public health policies to reduce the impacts of viral transmission.
| S-EPMC7018131 | biostudies-literature
Project description:We evaluated the sensitivity of the dengue surveillance system in detecting hospitalized cases in ten capital cities in Brazil from 2008 to 2013 using a probabilistic record linkage of two independent information systems hospitalization (SIH-SUS) adopted as the gold standard and surveillance (SINAN). Sensitivity was defined as the proportion of cases reported to the surveillance system amid the suspected hospitalized cases registered in SIH-SUS. Of the 48,174 hospitalizations registered in SIH-SUS, 24,469 (50.7%) were reported and registered in SINAN, indicating an overall sensitivity of 50.8% (95%CI 50.3-51.2). The observed sensitivity for each of the municipalities included in the study ranged from 22.0% to 99.1%. The combination of the two data sources identified 71,161 hospitalizations, an increase of 97.0% over SINAN itself. Our results allowed establishing the proportion of underreported dengue hospitalizations in the public health system in Brazil, highlighting the use of probabilistic record linkage as a valuable tool for evaluating surveillance systems.
| S-EPMC4871568 | biostudies-literature
Project description:BackgroundDengue is a public health problem, and noncompliance with World Health Organization (WHO) recommendations for blood transfusion components is frequently reported. Moreover, economic impact studies of the WHO recommendations on the use of blood transfusion are scarce.MethodsWe compared the cost and hospitalization time in a prospective observational study, by following hospitalised patients and analysing their medical records from 2010 and March 2016 to December 2017. We divided the patients into two groups: transfused (with or without WHO criteria for transfusion) and not transfused (with or without WHO criteria for transfusion). Generalised linear modelling was performed to identify the variable that could increase the costs and hospital stay.ResultsAmong 323 patients, 52 were transfused, of whom 52% without criteria (n = 27), and 271 were not transfused, of which 4.4% (n = 12) with criteria. Hospitalisation costs were 41% higher in the transfused group without criteria than in those with criteria (median US$ 674.3 vs US$ 478 p = 0.293). Patients who were not transfused but met the WHO criteria for transfusion (n = 12) had longer mean hospitalisation time than did those who were not transfused (3.8±3.4 days versus 3.6±3.1 days; p = 0.022). The GLM analysis using hospital stay and costs as the dependent variable explained approximately 33.4% (R2 = 0.334) of the hospitalisation time and 79.3% (R2 = 0.793) of costs. Receiving a transfusion increased the hospitalization time by 1.29 days (p = 0.0007; IRR = 1.29), and the costs were 5.1 times higher than those without receiving blood components (IRR = 5.1; p< 0.001; median US$ 504.4 vs US$ 170.7). In contrast, patients who were transfused according to WHO criteria had a reduction in costs of approximately 96% (IRR = 0.044; p<0.001; ? = -3.12) compared to that for those who were not transfused according to WHO criteria (without criteria).ConclusionTransfusion without following WHO recommendations increased the time and cost of hospitalisation.
| S-EPMC6613682 | biostudies-literature
Project description:To identify the spatial distribution patterns and areas of higher risk of preventable perinatal mortality in the city of Salvador, State of Bahia, Brazil.We carried out a spatial aggregated study in 2007, considering the weighting areas (census tracts contiguous sets) of Salvador, of which the center and north present low life conditions. Data were obtained from national vital statistics systems and the 2010 Census. Addresses of live births and stillbirths were geocoded by weighting area. The spatial distribution of the perinatal mortality rate was analyzed from thematic maps. Spatial dependence was evaluated by the Global and Local Geary's and Moran's Indexes.Crude and smoothed perinatal mortality rates were high in areas situated to the north, west, and in center of Salvador. The smoothed rates in weighting areas ranged from 4.9/1,000 to 22.3/1,000 births. Of all perinatal deaths, 92.1% could have been prevented. We identified spatial dependence for preventable perinatal mortality for care in pregnancy, with neighboring areas with high risk in the north of the city.The preventability potential of perinatal mortality was high in Salvador, in 2007. The spatial distribution pattern with higher rates in disadvantaged areas of the city suggests the existence of social inequalities in health. The characteristics of the process of urban development of Salvador, which has inadequate prenatal care, possibly influenced the magnitude and spatial distribution pattern of this mortality.
| S-EPMC5559215 | biostudies-other
Project description:BackgroundDengue fever is the most common arboviral infection in humans, with viral transmissions occurring in more than 100 countries in tropical regions. A global strategy for dengue prevention and control was established more than 10 years ago. However, the factors that drive the transmission of the dengue virus and subsequent viral infection continue unabated. The largest dengue outbreaks in Taiwan since World War II occurred in two recent successive years: 2014 and 2015.MethodsWe performed a systematic analysis to detect and recognize spatial and temporal clustering patterns of dengue incidence in geographical areas of Taiwan, using the map-based pattern recognition procedure and scan test. Our aim was to recognize geographical heterogeneity patterns of varying dengue incidence intensity and detect hierarchical incidence intensity clusters.ResultsUsing the map-based pattern recognition procedure, we identified and delineated two separate hierarchical dengue incidence intensity clusters that comprise multiple mutually adjacent geographical units with high dengue incidence rates. We also found that that dengue incidence tends to peak simultaneously and homogeneously among the neighboring geographic units with high rates in the same cluster.ConclusionBeyond significance testing, this study is particularly desired by and useful for health authorities who require optimal characteristics of disease incidence patterns on maps and over time. Among the integrated components for effective prevention and control of dengue and dengue hemorrhagic fever are active surveillance and community-based integrated mosquito control, for which this study provides valuable inferences. Effective dengue prevention and control programs in Taiwan are critical, and have the added benefit of controlling the potential emergence of Zika.
| S-EPMC5987425 | biostudies-literature
Project description:Dengue fever, a disease caused by a vector-borne flavivirus, is endemic to tropical countries, but its occurrence has been reported worldwide. This study aimed to understand important factors contributing to the spatial and temporal patterns of dengue occurrence in São Paulo, the largest municipality of Brazil. The temporal assessment of dengue occurrence covered the 2011-2016 time period and was based on climatological data, such as the El Niño indices and time series statistical tools such as the continuous wavelet transformation. The spatial assessment used Landsat 8 data for years 2014-2016 to estimate land surface temperature and normalized indices for vegetation, urban areas, and leaf water. Results from a cross correlation for the temporal analysis found a relationship between the sea surface temperature anomalies index and the number of reported dengue cases in São Paulo (r = 0.5) with a lag of +29 (weeks) between the climatic event and the response on the dengue incidence. This relationship, initially nonlinear, became linear after correcting for the lag period. For the spatial assessment, the linear stepwise regression model detected a low relationship between dengue incidence and minimum surface temperature (r = 0.357) and no relationship with other environmental parameters. The poor relationship might be due to confounding effects of socioeconomic factors as these seem to influence the spatial dynamics of dengue incidence. More testing is needed to validate these methods in other locations. Nevertheless, we presented possible tools to be used for the improvement of dengue control programs.
| S-EPMC7007072 | biostudies-literature
Project description:BackgroundRio de Janeiro, Brazil, experienced a severe dengue fever epidemic in 2008. This was the worst epidemic ever, characterized by a sharp increase in case-fatality rate, mainly among younger individuals. A combination of factors, such as climate, mosquito abundance, buildup of the susceptible population, or viral evolution, could explain the severity of this epidemic. The main objective of this study is to model the spatial patterns of dengue seroprevalence in three neighborhoods with different socioeconomic profiles in Rio de Janeiro. As blood sampling coincided with the peak of dengue transmission, we were also able to identify recent dengue infections and visually relate them to Aedes aegypti spatial distribution abundance. We analyzed individual and spatial factors associated with seroprevalence using Generalized Additive Model (GAM).Methodology/principal findingsThree neighborhoods were investigated: a central urban neighborhood, and two isolated areas characterized as a slum and a suburban area. Weekly mosquito collections started in September 2006 and continued until March 2008. In each study area, 40 adult traps and 40 egg traps were installed in a random sample of premises, and two infestation indexes calculated: mean adult density and mean egg density. Sera from individuals living in the three neighborhoods were collected before the 2008 epidemic (July through November 2007) and during the epidemic (February through April 2008). Sera were tested for DENV-reactive IgM, IgG, Nested RT-PCR, and Real Time RT-PCR. From the before-after epidemics paired data, we described seroprevalence, recent dengue infections (asymptomatic or not), and seroconversion. Recent dengue infection varied from 1.3% to 14.1% among study areas. The highest IgM seropositivity occurred in the slum, where mosquito abundance was the lowest, but household conditions were the best for promoting contact between hosts and vectors. By fitting spatial GAM we found dengue seroprevalence hotspots located at the entrances of the two isolated communities, which are commercial activity areas with high human movement. No association between recent dengue infection and household's high mosquito abundance was observed in this sample.Conclusions/significanceThis study contributes to better understanding the dynamics of dengue in Rio de Janeiro by assessing the relationship between dengue seroprevalence, recent dengue infection, and vector density. In conclusion, the variation in spatial seroprevalence patterns inside the neighborhoods, with significantly higher risk patches close to the areas with large human movement, suggests that humans may be responsible for virus inflow to small neighborhoods in Rio de Janeiro. Surveillance guidelines should be further discussed, considering these findings, particularly the spatial patterns for both human and mosquito populations.
| S-EPMC2768822 | biostudies-literature
Project description:BackgroundDengue, a viral disease transmitted by Aedes mosquitoes, is an important public health concern throughout Thailand. Climate variables are potential predictors of dengue transmission. Associations between climate variables and dengue have usually been performed on large-scale first-level national administrative divisions, i.e. provinces. Here we analyze data on a finer spatial resolution in one province, which is often more relevant for effective disease control design. The objective of this study was to investigate the effect of seasonal variations, monthly climate variability, and to identify local clusters of symptomatic disease at the sub-district level based on reported dengue cases.MethodsData on dengue cases were retrieved from the national communicable disease surveillance system in Thailand. Between 2006 and 2016, 15,167 cases were recorded in 199 sub-districts of Khon Kaen Province, northeastern Thailand. Descriptive analyses included demographic characteristics and temporal patterns of disease and climate variables. The association between monthly disease incidence and climate variations was analyzed at the sub-district level using Bayesian Poisson spatial regression. A hotspot analysis was used to assess the spatial patterns (clustered/dispersed/random) of dengue incidence.ResultsDengue was predominant in the 5-14?year-old age group (51.1%). However, over time, dengue incidence in the older age groups (>?15?years) gradually increased and was the most affected group in 2013. Dengue outbreaks coincide with the rainy season. In the spatial regression model, maximum temperature was associated with higher incidence. The hotspot analysis showed clustering of cases around the urbanized area of Khon Kaen city and in rural areas in the southwestern portion of the province.ConclusionsThere was an increase in the number of reported dengue cases in older age groups over the study period. Dengue incidence was highly seasonal and positively associated with maximum ambient temperature. However, climatic variables did not explain all the spatial variation of dengue in the province. Further analyses are needed to clarify the detailed effects of urbanization and other potential environmental risk factors. These results provide useful information for ongoing prediction modeling and developing of dengue early warning systems to guide vector control operations.
| S-EPMC6708185 | biostudies-literature
Project description:Dengue remains an important public health problem in Timor-Leste, with several major epidemics occurring over the last 10 years. The aim of this study was to identify dengue clusters at high geographical resolution and to determine the association between local environmental characteristics and the distribution and transmission of the disease.Notifications of dengue cases that occurred from January 2005 to December 2013 were obtained from the Ministry of Health, Timor-Leste. The population of each suco (the third-level administrative subdivision) was obtained from the Population and Housing Census 2010. Spatial autocorrelation in dengue incidence was explored using Moran's I statistic, Local Indicators of Spatial Association (LISA), and the Getis-Ord statistics. A multivariate, Zero-Inflated, Poisson (ZIP) regression model was developed with a conditional autoregressive (CAR) prior structure, and with posterior parameters estimated using Bayesian Markov chain Monte Carlo (MCMC) simulation with Gibbs sampling.The analysis used data from 3206 cases. Dengue incidence was highly seasonal with a large peak in January. Patients ? 14 years were found to be 74% [95% credible interval (CrI): 72-76%] less likely to be infected than those < 14 years, and females were 12% (95% CrI: 4-21%) more likely to suffer from dengue as compared to males. Dengue incidence increased by 0.7% (95% CrI: 0.6-0.8%) for a 1 °C increase in mean temperature; and 47% (95% CrI: 29-59%) for a 1 mm increase in precipitation. There was no significant residual spatial clustering after accounting for climate and demographic variables.Dengue incidence was highly seasonal and spatially clustered, with positive associations with temperature, precipitation and demographic factors. These factors explained the observed spatial heterogeneity of infection.
| S-EPMC5755460 | biostudies-literature
Project description:We analysed nationwide trends and spatial distribution of NTD-related mortality in Brazil. We included all death certificates in Brazil from 2000 to 2011, in which NTDs were recorded as any causes of death. A total of 100,814/12,491,280 (0.81%) death certificates were identified, which mentioned at least one NTD. Age-adjusted NTD-related mortality rates showed a significant decrease over time (annual percent change [APC]: - 2.1%; 95% CI: - 2.8 to - 1.3), with decreasing mortality rates in the Southeast, South, and Central-West regions, stability in the Northeast region, and increase in the North region. We identified spatial and spatiotemporal high-risk clusters for NTD-related mortality in all regions, with a major cluster covering a wide geographic range in central Brazil. Despite nationwide decrease of NTD-related mortality in the observation period, regional differences remain, with increasing mortality trends especially in the socioeconomically disadvantaged regions of the country. The existence of clearly defined high-risk areas for NTD-related deaths reinforces the need for integrated prevention and control measures in areas with highest disease burden.
| S-EPMC5991825 | biostudies-literature