Dataset Information

Dengue fever occurrence and vector detection by larval survey, ovitrap and MosquiTRAP: a space-time clusters analysis.

ABSTRACT: The use of vector surveillance tools for preventing dengue disease requires fine assessment of risk, in order to improve vector control activities. Nevertheless, the thresholds between vector detection and dengue fever occurrence are currently not well established. In Belo Horizonte (Minas Gerais, Brazil), dengue has been endemic for several years. From January 2007 to June 2008, the dengue vector Aedes (Stegomyia) aegypti was monitored by ovitrap, the sticky-trap MosquiTRAP™ and larval surveys in an study area in Belo Horizonte. Using a space-time scan for clusters detection implemented in SaTScan software, the vector presence recorded by the different monitoring methods was evaluated. Clusters of vectors and dengue fever were detected. It was verified that ovitrap and MosquiTRAP vector detection methods predicted dengue occurrence better than larval survey, both spatially and temporally. MosquiTRAP and ovitrap presented similar results of space-time intersections to dengue fever clusters. Nevertheless ovitrap clusters presented longer duration periods than MosquiTRAP ones, less acuratelly signalizing the dengue risk areas, since the detection of vector clusters during most of the study period was not necessarily correlated to dengue fever occurrence. It was verified that ovitrap clusters occurred more than 200 days (values ranged from 97.0±35.35 to 283.0±168.4 days) before dengue fever clusters, whereas MosquiTRAP clusters preceded dengue fever clusters by approximately 80 days (values ranged from 65.5±58.7 to 94.0±14. 3 days), the former showing to be more temporally precise. Thus, in the present cluster analysis study MosquiTRAP presented superior results for signaling dengue transmission risks both geographically and temporally. Since early detection is crucial for planning and deploying effective preventions, MosquiTRAP showed to be a reliable tool and this method provides groundwork for the development of even more precise tools.

SUBMITTER: de Melo DP

PROVIDER: S-EPMC3405049 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Dengue fever occurrence and vector detection by larval survey, ovitrap and MosquiTRAP: a space-time clusters analysis.

de Melo Diogo Portella Ornelas DP Scherrer Luciano Rios LR Eiras Álvaro Eduardo ÁE

PloS one 20120725 7

The use of vector surveillance tools for preventing dengue disease requires fine assessment of risk, in order to improve vector control activities. Nevertheless, the thresholds between vector detection and dengue fever occurrence are currently not well established. In Belo Horizonte (Minas Gerais, Brazil), dengue has been endemic for several years. From January 2007 to June 2008, the dengue vector Aedes (Stegomyia) aegypti was monitored by ovitrap, the sticky-trap MosquiTRAP™ and larval surveys ...[more]

PMID: 22848729

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Project description:Larval surveillance is the central approach for monitoring dengue vector populations in Indonesia. However, traditional larval indices are ineffective for measuring mosquito population dynamics and predicting the dengue transmission risk. We conducted a 14-month ovitrap surveillance. Eggs and immature mosquitoes were collected on a weekly basis from an urban village of Bandung, namely Sekejati. Ovitrap-related indices, namely positive house index (PHI), ovitrap index (OI), and ovitrap density index (ODI), were generated and correlated with environmental variables, housing type (terraced or high-density housing), ovitrap placement location (indoor or outdoor; household or public place), and local dengue cases. Our results demonstrated that Aedes aegypti was significantly predominant compared with Aedes albopictus at each housing type and ovitrap placement location. Ovitrap placement locations and rainfall were the major factors contributing to variations in PHI, OI, and ODI, whereas the influences of housing type and temperature were subtle. Indoor site values were significantly positively correlated to outdoor sites' values for both OI and ODI. OI and ODI values from households were best predicted with those from public places at 1- and 0-week lags, respectively. Weekly rainfall values at 4- and 3-week lags were the best predictors of OI and ODI for households and public places, respectively. Monthly mean PHI, OI, and ODI were significantly associated with local dengue cases. In conclusion, ovitrap may be an effective tool for monitoring the population dynamics of Aedes mosquitoes, predicting dengue outbreaks, and serving as an early indicator to initiate environmental clean-up. Ovitrap surveillance is easy for surveyors if they are tasked with a certain number of ovitraps at a designated area, unlike the existing larval surveillance methodology, which entails identifying potential breeding sites largely at the surveyors' discretion. Ovitrap surveillance may reduce the influence of individual effort in larval surveillance that likely causes inconsistency in results.

Project description:Background Mozambique, same as many other tropical countries, is at high risk of arthropod-borne virus (arbovirus) diseases and recently two dengue virus (DENV) outbreaks occurred in the northern part of the country. The occurrence of some important vector species, such as Aedes (Stegomyia) aegypti (Linnaeus) and Ae. (Stg.) albopictus (Skuse), besides several other sylvatic vectors, have been reported in the country, which may indicate that the transmission of some arboviruses of public health importance may involve multiple-vector systems. Therefore, knowing the occurrence and distribution of existing and the new important vectors species, is crucial for devising systematic transmission surveillance and vector control approaches. The aim of this study was to map the occurrence and distribution of mosquito species with potential for transmitting arboviruses of human and veterinary relevance in Niassa Province, Northern Mozambique. Methods Field entomological surveys were undertaken in April 2016 in Lago District, Niassa Province, northern Mozambique. Breeding sites of mosquitoes were inspected and immature stages were collected and reared into adult. Mosquitoes in the adult stages were morphologically identified using taxonomic keys. Morphological identification of Aedes (Stegomyia) luteocephalus (Newstead) were later confirmed using dissected male genitalia and molecular based on the phylogenetic analyses of the sequenced barcode (cox1 mtDNA) gene. Results A total of 92 mosquito larvae collected developed into adults. Of these, 16 (17.39%) were morphologically identified as Ae. luteocephalus. The remaining specimens belonged to Ae. (Stg.) aegypti (n?=?4, 4.35%), Ae. (Aedimorphus) vittatus (n?=?24, 26.09%), Anopheles garnhami (n?=?1, 1.09%), Culex (Culiciomyia) nebulosus (n?=?28, 30.43%), Eretmapodites subsimplicipes (n?=?18, 19.57%) and Toxorhynchites brevipalpis (n?=?1, 1.09%), taxa already known to the country. Male genitalia and phylogenetic analyses confirmed the identity of Ae. luteocephalus specimens collected in this study. Conclusions To our knowledge, this is the first detection of Ae. luteocephalus in Mozambican territory, a vector species of yellow fever virus (YFV), Zika virus (ZIKV) and dengue virus (DENV) in Africa. Further studies are encouraged to investigate the role of Ae. luteocephalus in the transmission of arboviral diseases in Mozambique.

Project description:Accurate detection and classification of predation events is important to determine predation and consumption rates by predators. However, obtaining this information for large predators is constrained by the speed at which carcasses disappear and the cost of field data collection. To accurately detect predation events, researchers have used GPS collar technology combined with targeted site visits. However, kill sites are often investigated well after the predation event due to limited data retrieval options on GPS collars (VHF or UHF downloading) and to ensure crew safety when working with large predators. This can lead to missing information from small-prey (including young ungulates) kill sites due to scavenging and general site deterioration (e.g., vegetation growth). We used a space-time permutation scan statistic (STPSS) clustering method (SaTScan) to detect predation events of grizzly bears (Ursus arctos) fitted with satellite transmitting GPS collars. We used generalized linear mixed models to verify predation events and the size of carcasses using spatiotemporal characteristics as predictors. STPSS uses a probability model to compare expected cluster size (space and time) with the observed size. We applied this method retrospectively to data from 2006 to 2007 to compare our method to random GPS site selection. In 2013-2014, we applied our detection method to visit sites one week after their occupation. Both datasets were collected in the same study area. Our approach detected 23 of 27 predation sites verified by visiting 464 random grizzly bear locations in 2006-2007, 187 of which were within space-time clusters and 277 outside. Predation site detection increased by 2.75 times (54 predation events of 335 visited clusters) using 2013-2014 data. Our GLMMs showed that cluster size and duration predicted predation events and carcass size with high sensitivity (0.72 and 0.94, respectively). Coupling GPS satellite technology with clusters using a program based on space-time probability models allows for prompt visits to predation sites. This enables accurate identification of the carcass size and increases fieldwork efficiency in predation studies.

Project description:BackgroundThe Prospective Space-Time scan statistic (PST) is widely used for the evaluation of space-time clusters of point event data. Usually a window of cylindrical shape is employed, with a circular or elliptical base in the space domain. Recently, the concept of Minimum Spanning Tree (MST) was applied to specify the set of potential clusters, through the Density-Equalizing Euclidean MST (DEEMST) method, for the detection of arbitrarily shaped clusters. The original map is cartogram transformed, such that the control points are spread uniformly. That method is quite effective, but the cartogram construction is computationally expensive and complicated.ResultsA fast method for the detection and inference of point data set space-time disease clusters is presented, the Voronoi Based Scan (VBScan). A Voronoi diagram is built for points representing population individuals (cases and controls). The number of Voronoi cells boundaries intercepted by the line segment joining two cases points defines the Voronoi distance between those points. That distance is used to approximate the density of the heterogeneous population and build the Voronoi distance MST linking the cases. The successive removal of edges from the Voronoi distance MST generates sub-trees which are the potential space-time clusters. Finally, those clusters are evaluated through the scan statistic. Monte Carlo replications of the original data are used to evaluate the significance of the clusters. An application for dengue fever in a small Brazilian city is presented.ConclusionsThe ability to promptly detect space-time clusters of disease outbreaks, when the number of individuals is large, was shown to be feasible, due to the reduced computational load of VBScan. Instead of changing the map, VBScan modifies the metric used to define the distance between cases, without requiring the cartogram construction. Numerical simulations showed that VBScan has higher power of detection, sensitivity and positive predicted value than the Elliptic PST. Furthermore, as VBScan also incorporates topological information from the point neighborhood structure, in addition to the usual geometric information, it is more robust than purely geometric methods such as the elliptic scan. Those advantages were illustrated in a real setting for dengue fever space-time clusters.

Project description:BackgroundDengue is a widely spread vector-borne disease. Dengue cases in the Americas have increased over the last few decades, affecting various urban spaces throughout these continents, including the tourism-oriented city of Girardot, Colombia. Interactions among mosquitoes, pathogens and humans have recently been examined using different temporal and spatial scales in attempts to determine the roles that social and ecological systems play in dengue transmission. The current work characterizes the spatial and temporal behaviours of dengue in Girardot and discusses the potential territorial dynamics related to the distribution of this disease.MethodsBased on officially reported dengue cases (2012-2015) corresponding to epidemic (2013) and inter-epidemic years (2012, 2014, 2015), space (Getis-Ord index) and space-time (Kulldorff's scan statistics) analyses were performed.ResultsGeocoded dengue cases (n = 2027) were slightly overrepresented by men (52.1%). As expected, the cases were concentrated in the 0- to 15-year-old age group according to the actual trends of Colombia. The incidence rates of dengue during the rainy and dry seasons as well as those for individual years (2012, 2013 and 2014) were significant using the global Getis-Ord index. Local clusters shifted across seasons and years; nevertheless, the incidence rates clustered towards the southwest region of the city under different residential conditions. Space-time clusters shifted from the northeast to the southwest of the city (2012-2014). These clusters represented only 4.25% of the total cases over the same period (n = 1623). A general trend was observed, in which dengue cases increased during the dry seasons, especially between December and February.ConclusionsDespite study limitations related to official dengue records and available fine-scale demographic information, the spatial analysis results were promising from a geography of health perspective. Dengue did not show linear association with poverty or with vulnerable peripheral spaces in intra-urban settings, supporting the idea that the pathogenic complex of dengue is driven by different factors. A coordinated collaboration of epidemiological, public health and social science expertise is needed to assess the effect of "place" from a relational perspective in which geography has an important role to play.

Dataset Information

Dengue fever occurrence and vector detection by larval survey, ovitrap and MosquiTRAP: a space-time clusters analysis.

Publications

Dengue fever occurrence and vector detection by larval survey, ovitrap and MosquiTRAP: a space-time clusters analysis.

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