Spatial Distribution Of Dengue Research Articles

A tale of 141 municipalities: the spatial distribution of dengue in Mato Grosso, Brazil.

In recent years, the state of Mato Grosso has presented one of the highest dengue incidence rates in Brazil. The meeting of the Amazon, Cerrado and Pantanal biomes results in a large variation of rainfall and temperature across different regions of the state. In addition, Mato Grosso has been undergoing intense urban growth since the 1970s, mainly due to the colonization of the Mid-North and North regions. We analyzed factors involved in dengue incidence in Mato Grosso from 2008 to 2019. The Moran Global Index was used to assess spatial autocorrelation of dengue incidence using explanatory variables such as temperature, precipitation, deforestation, population density and municipal development index. Areas at risk of dengue were grouped by the Local Moran Indicator. We noticed that areas at risk of dengue expanded from the Mid-North region to the North; the same pattern occurred from the Southeast to the Northeast; the South region remained at low-risk levels. The increase in incidence was influenced by precipitation, deforestation and the municipal development index. The identification of risk areas for dengue in space and time enables public health authorities to focus their control and prevention efforts, reducing infestation and the potential impact of dengue in the human population.

Spatial Distribution of Dengue and Forecasting in South Denpasar, Bali Province, Indonesia

Background and purpose: The incidence of dengue hemorrhagic fever (DHF) in Bali continues to increase. A new strategy is required to control dengue in Bali. The purpose of the study is to conduct spatial mapping with a geographic information system to help determine the distribution pattern and areas at risk of DHF and to predict increasing vector density and dengue cases.
 Methods: A cross-sectional study was conducted in the South Denpasar Public Health Center service area from January to June 2020. It was conducted in 3 villages, including Kelurahan Sesetan (3,446 households), Sidakarya Village (2,859 households), and Kelurahan Panjer (2,907 households). A total of 191 cases of DHF were recorded during the study period. Results: Calculation of the spatial analysis of the Average Nearest Neighbor (AAN) with the value of Z score=-8.03 show a spatial pattern of the distribution of DHF cases. AAN value of 0.69 (<1) means that the pattern of spread of DHF incidence is clustered. Time series forecasting by modeling using the Autoregressive Moving Average (ARIMA) and Double Exponential Smoothing Method Routine shows that larva control efforts are predicted to affect the number of dengue cases. The pattern of the spatial distribution of cases occurs in clusters.
 Conclusion: There is a spatial relationship with population density. It is predicted that routine larvae control will reduce dengue cases.

Periodic synchronisation of dengue epidemics in Thailand over the last 5 decades driven by temperature and immunity.

The spatial distribution of dengue and its vectors (spp. Aedes) may be the widest it has ever been, and projections suggest that climate change may allow the expansion to continue. However, less work has been done to understand how climate variability and change affects dengue in regions where the pathogen is already endemic. In these areas, the waxing and waning of immunity has a large impact on temporal dynamics of cases of dengue haemorrhagic fever. Here, we use 51 years of data across 72 provinces and characterise spatiotemporal patterns of dengue in Thailand, where dengue has caused almost 1.5 million cases over the last 30 years, and examine the roles played by temperature and dynamics of immunity in giving rise to those patterns. We find that timescales of multiannual oscillations in dengue vary in space and time and uncover an interesting spatial phenomenon: Thailand has experienced multiple, periodic synchronisation events. We show that although patterns in synchrony of dengue are similar to those observed in temperature, the relationship between the two is most consistent during synchronous periods, while during asynchronous periods, temperature plays a less prominent role. With simulations from temperature-driven models, we explore how dynamics of immunity interact with temperature to produce the observed patterns in synchrony. The simulations produced patterns in synchrony that were similar to observations, supporting an important role of immunity. We demonstrate that multiannual oscillations produced by immunity can lead to asynchronous dynamics and that synchrony in temperature can then synchronise these dengue dynamics. At higher mean temperatures, immune dynamics can be more predominant, and dengue dynamics more insensitive to multiannual fluctuations in temperature, suggesting that with rising mean temperatures, dengue dynamics may become increasingly asynchronous. These findings can help underpin predictions of disease patterns as global temperatures rise.

Spatial distribution of dengue in Ecuador during 1994–2018 using geographic information systems (GIS) – Implications public health and travel medicine

Spatial distribution of dengue in Ecuador during 1994–2018 using geographic information systems (GIS) – Implications public health and travel medicine

A Perspective on Inhabited Urban Space: Land Use and Occupation, Heat Islands, and Precarious Urbanization as Determinants of Territorial Receptivity to Dengue in the City of Rio De Janeiro.

Introduction: Rio de Janeiro is the second-largest city in Brazil, with strong socio-spatial segregation, and diverse and heterogeneous land use, occupation, and landscapes. The complexity of dengue requires the construction of surveillance and control tools that take into account the historical, social, economic, and environmental processes mediated in the territory as a central axis of public policy. In this context, this study aimed to stratify the city into areas of receptivity to dengue, using innovative “territorial indicators” because they are built based on the actual occupation of the territory. Methods: We designed and constructed 17 indicators that sought to characterize the transformed and inhabited space according to receptivity to dengue. We used data on land use and occupation, connectivity, climate, and landscape. We developed the dengue receptivity through principal component analysis (PCA), using multiple criteria analysis and map algebra integrated in a GIS platform. Results: The most receptive areas were concentrated in the transition between the north and west zones of the city, a region of unconsolidated urban sprawl. The areas of greatest receptivity had the highest incidence and density of Aedes eggs during the study period. The correlation between receptivity index and incidence rate was positive in the epidemic years. Conclusion: The proposed set of indicators was able to identify areas of greater receptivity, such as regions of disorderly urban sprawl, with a concentration of social and environmental processes that are related to the occurrence of dengue outbreaks and high vector density. On the other hand, population immunity plays an important role in the spatial distribution of dengue during non-epidemic years.

Spatial distribution of dengue in Honduras during 2016-2019 using a geographic information systems (GIS)-Dengue epidemic implications for public health and travel medicine.

After serious epidemics of chikungunya (CHIKV) and Zika (ZIKV) in the Americas, dengue (DENV) have reemerged in most countries. We analyzed the incidence, incidence rates, and evolution of DENV cases in Honduras from 2015 to 2018 and the ongoing 2019 epidemic. Using epidemiological weeks (EW) surveillance data on the DENV in Honduras, we estimated incidence rates (cases/100,000 population), and developed maps at national, departmental, and municipal levels. From January 1, 2016 to July 21, 2019, a total of 109,557 cases of DENV were reported, 28,603 in 2019, with an incidence rate of 312.32 cases/100,000 population this year; 0.13% laboratory-confirmed. The highest peak was reached on the EW 28°, 2019 (5299 cases; 57.89 cases/100,000 population). The department with the highest number of cases and incidence rate was Cortes (8404 cases, 479.68 cases/100,000 population in 2019). The pattern and evolution of DENV epidemic in 2019 in Honduras has been similar to that which occurred for in 2015. As previously reported, this epidemic involved the north and central areas of the country predominantly, reaching municipality incidences there >1000 cases/100,000 population (or 1%). Studies using geographical information systems linked with clinical disease characteristics are necessary to obtain accurate epidemiological data for public health systems. Such information is also useful for assessment of risk for travelers who visit specific areas in a destination country.

Socio-demographic inequalities in the clinical characteristics of dengue haemorrhagic fever in the city of Rio de Janeiro, Brazil, 2007-2008.

In 2007-2008, the city of Rio de Janeiro underwent an epidemiological change, with increases in the incidence in children and in severe forms of dengue. To describe the clinical profile and spatial distribution of dengue we performed an ecological study based on dengue surveillance data using the Brazilian classification (2005): dengue fever, dengue haemorrhagic fever (DHF) and dengue with complications. χ 2 test was used to describe the clinical and socio-demographic variables (P < 0.05). Spatial distribution of incidence and case-fatality was explored with thematic maps, Moran and Geary indices (P < 0.05). Of the total of 151 527 dengue cases, 38 808 met the inclusion criteria; 42.4% <18 years; 22.9% dengue with complications and 2.7% DHF. Case-fatality was higher in infants (1.4%) and in DHF (7.7%). Bleeding was more frequent in adolescents and adults while plasma leakage was more common in preschoolers and schoolchildren. The highest incidence was found in the West Zone of the city, in a different area from that of the worst case-fatality (P < 0.05). Although the incidence of DHF was higher in schoolchildren, infants showed higher case-fatality. The area with the highest case-fatality did not present the highest incidence, which suggests problems in the organization of health services.

Spatial distribution and cluster analysis of dengue using self organizing maps in Andhra Pradesh, India, 2011–2013

Background and objectivesDengue is an emerging and re-emerging infectious disease, transmitted by mosquitoes. It is mostly prevalent in tropical and sub-tropical regions of the world, particularly, in Asia-Pacific region. To understand the epidemiology and spatial distribution of dengue, a retrospective surveillance study was conducted in the state of Andhra Pradesh, India during 2011–2013. Material and methodsDistrict-wise disease endemicity levels were mapped through geographical information system (GIS) tools. Spatial statistical analysis such as Getis-Ord Gi* was performed to identify hot spots and cold spots of dengue disease. Similarly self organizing maps (SOM), a datamining tool was also applied to understand the endemicity patterns in study areas. ResultsThe analysis shows that districts of Warangal, Karimnagar, Khammam and Vizianagaram are reported as hot spot regions whereas Adilabad and Nizamabad reported as cold spots for dengue. The SOM classify 23 districts in 03 major (07 sub) clusters. These SOM clusters were projected in the geographical space and based on the disease/cases intensity the districts were characterized into low, medium and high endemic areas. ConclusionThis visualization approach, SOM-GIS helps the public health officials to identify the disease endemic zones and take real time decisions for disease management.

Spatial Distribution of Dengue in a Brazilian Urban Slum Setting: Role of Socioeconomic Gradient in Disease Risk.

BackgroundFew studies of dengue have shown group-level associations between demographic, socioeconomic, or geographic characteristics and the spatial distribution of dengue within small urban areas. This study aimed to examine whether specific characteristics of an urban slum community were associated with the risk of dengue disease.Methodology/Principal FindingsFrom 01/2009 to 12/2010, we conducted enhanced, community-based surveillance in the only public emergency unit in a slum in Salvador, Brazil to identify acute febrile illness (AFI) patients with laboratory evidence of dengue infection. Patient households were geocoded within census tracts (CTs). Demographic, socioeconomic, and geographical data were obtained from the 2010 national census. Associations between CTs characteristics and the spatial risk of both dengue and non-dengue AFI were assessed by Poisson log-normal and conditional auto-regressive models (CAR). We identified 651 (22.0%) dengue cases among 2,962 AFI patients. Estimated risk of symptomatic dengue was 21.3 and 70.2 cases per 10,000 inhabitants in 2009 and 2010, respectively. All the four dengue serotypes were identified, but DENV2 predominated (DENV1: 8.1%; DENV2: 90.7%; DENV3: 0.4%; DENV4: 0.8%). Multivariable CAR regression analysis showed increased dengue risk in CTs with poorer inhabitants (RR: 1.02 for each percent increase in the frequency of families earning ≤1 times the minimum wage; 95% CI: 1.01-1.04), and decreased risk in CTs located farther from the health unit (RR: 0.87 for each 100 meter increase; 95% CI: 0.80-0.94). The same CTs characteristics were also associated with non-dengue AFI risk.Conclusions/SignificanceThis study highlights the large burden of symptomatic dengue on individuals living in urban slums in Brazil. Lower neighborhood socioeconomic status was independently associated with increased risk of dengue, indicating that within slum communities with high levels of absolute poverty, factors associated with the social gradient influence dengue transmission. In addition, poor geographic access to health services may be a barrier to identifying both dengue and non-dengue AFI cases. Therefore, further spatial studies should account for this potential source of bias.

Spatial distribution of dengue in the city of Cruzeiro, São Paulo State, Brazil: use of geoprocessing tools

The aim of this article is to identify patterns in spatial distribution of cases of dengue fever that occurred in the municipality of Cruzeiro, State of São Paulo, in 2006. This is an ecological and exploratory study using the tools of spatial analysis in the preparation of thematic maps with data from Sinan-Net. An analysis was made by area, taking as unit the IBGE census, the analysis included four months in 2006 which show the occurrence of the disease in the city. The thematic maps were constructed by TerraView 3.3.1 software, the same software provided the values of the indicators of Global Moran (I M) every month and the Kernel estimation. In the year 2006, 691 cases of dengue were georeferenced (with a rate of 864.2 cases/100,000 inhabitants); the indicators of Moran and p-values obtained were I M = 0.080 (March) p = 0.11; I M = 0.285 (April) p = 0.01; I M = 0.201 (May) p = 0.01 and I M = 0.002 (June) p = 0.57. The first cases were identified in the Northeast and Central areas of Cruzeiro and the recent cases, in the North, Northeast and Central. It was possible to identify census tracts where the epidemic began and how it occurred temporally and spatially in the city.