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The spatial and temporal scales of local dengue virus transmission in natural settings: a retrospective analysis.

ABSTRACT: BACKGROUND:Dengue is a vector-borne disease caused by the dengue virus (DENV). Despite the crucial role of Aedes mosquitoes in DENV transmission, pure vector indices poorly correlate with human infections. Therefore there is great need for a better understanding of the spatial and temporal scales of DENV transmission between mosquitoes and humans. Here, we have systematically monitored the circulation of DENV in individual Aedes spp. mosquitoes and human patients from Caratinga, a dengue endemic city in the state of Minas Gerais, in Southeast Brazil. From these data, we have developed a novel stochastic point process pattern algorithm to identify the spatial and temporal association between DENV infected mosquitoes and human patients. METHODS:The algorithm comprises of: (i) parameterization of the variogram for the incidence of each DENV serotype in mosquitoes; (ii) identification of the spatial and temporal ranges and variances of DENV incidence in mosquitoes in the proximity of humans infected with dengue; and (iii) analysis of the association between a set of environmental variables and DENV incidence in mosquitoes in the proximity of humans infected with dengue using a spatio-temporal additive, geostatistical linear model. RESULTS:DENV serotypes 1 and 3 were the most common virus serotypes detected in both mosquitoes and humans. Using the data on each virus serotype separately, our spatio-temporal analyses indicated that infected humans were located in areas with the highest DENV incidence in mosquitoes, when incidence is calculated within 2.5-3 km and 50 days (credible interval 30-70 days) before onset of symptoms in humans. These measurements are in agreement with expected distances covered by mosquitoes and humans and the time for virus incubation. Finally, DENV incidence in mosquitoes found in the vicinity of infected humans correlated well with the low wind speed, higher air temperature and northerly winds that were more likely to favor vector survival and dispersal in Caratinga. CONCLUSIONS:We have proposed a new way of modeling bivariate point pattern on the transmission of arthropod-borne pathogens between vector and host when the location of infection in the latter is known. This strategy avoids some of the strong and unrealistic assumptions made by other point-process models. Regarding virus transmission in Caratinga, our model showed a strong and significant association between high DENV incidence in mosquitoes and the onset of symptoms in humans at specific spatial and temporal windows. Together, our results indicate that vector surveillance must be a priority for dengue control. Nevertheless, localized vector control at distances lower than 2.5 km around premises with infected vectors in densely populated areas are not likely to be effective.

SUBMITTER: Sedda L

PROVIDER: S-EPMC5797342 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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The spatial and temporal scales of local dengue virus transmission in natural settings: a retrospective analysis.

Sedda Luigi L Vilela Ana Paula Pessoa APP Aguiar Eric Roberto Guimarães Rocha ERGR Gaspar Caio Henrique Pessoa CHP Gonçalves André Nicolau Aquime ANA Olmo Roenick Proveti RP Silva Ana Teresa Saraiva ATS de Cássia da Silveira Lízia L Eiras Álvaro Eduardo ÁE Drumond Betânia Paiva BP Kroon Erna Geessien EG Marques João Trindade JT

Parasites & vectors 20180202 1

<h4>Background</h4>Dengue is a vector-borne disease caused by the dengue virus (DENV). Despite the crucial role of Aedes mosquitoes in DENV transmission, pure vector indices poorly correlate with human infections. Therefore there is great need for a better understanding of the spatial and temporal scales of DENV transmission between mosquitoes and humans. Here, we have systematically monitored the circulation of DENV in individual Aedes spp. mosquitoes and human patients from Caratinga, a dengue ...[more]

PMID: 29394906

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Project description:Dengue virus serotype 4 (DENV-4) circulated in Aedes aegypti in 2016 and 2017 in Florida in the absence of human index cases, compelling a full assessment of local mosquito vector competence and DENV-4 risk. To better understand DENV-4 transmission risk in Florida, we used an expanded suite of tests to measure and compare the vector competencies of both an established colony of A. aegypti (Orlando strain [ORL]) and a field-derived colony from Collier County, FL, in 2018 (COL) for a Haitian DENV-4 human field isolate and a DENV-4 laboratory strain (Philippines H241). We immediately noted that ORL saliva positivity was higher for the field than for laboratory DENV-4 strains. In a subsequent comparison with the recent COL mosquito colony, we also observed significantly higher midgut infection of COL and ORL by the Haitian DENV-4 field strain and a significantly higher saliva positivity rate for COL, although overall saliva virus titers were similar between the two. These data point to a potential midgut infection barrier for the DENV-4 laboratory strain for both mosquito colonies and indicate that the marked differences in transmission potential estimates hinge on virus-vector combinations. Our study highlights the importance of leveraging an expanded suite of testing methods with emphasis on utilizing local mosquito populations and field-relevant dengue virus serotypes and strains to accurately estimate transmission risk in a given setting. IMPORTANCE DENV-4 was found circulating in Florida (FL) A. aegypti mosquitoes in the absence of human index cases in the state (2016 to 2017). How DENV-4 was maintained locally is unclear, presenting a major gap in our understanding of DENV-4 public health risk. We determined the baseline arbovirus transmission potential of laboratory and field colonies of A. aegypti for both laboratory and field isolates of DENV-4. We observed a high transmission potential of field populations of A. aegypti and evidence of higher vertical transmission of the DENV-4 field isolate, providing clues to the possible mechanism of undetected DENV-4 maintenance in the state. Our findings also move the field forward in the development of best practices for evaluating arbovirus vector competence, with evidence that transmission potential estimates vary depending on the mosquito-virus combinations. These data emphasize the poor suitability of laboratory-established virus strains and the high relevance of field-derived mosquito populations in estimating transmission risk.

Project description:Human and many other animals can detect, recognize, and classify natural actions in a very short time. How this is achieved by the visual system and how to make machines understand natural actions have been the focus of neurobiological studies and computational modeling in the last several decades. A key issue is what spatial-temporal features should be encoded and what the characteristics of their occurrences are in natural actions. Current global encoding schemes depend heavily on segmenting while local encoding schemes lack descriptive power. Here, we propose natural action structures, i.e., multi-size, multi-scale, spatial-temporal concatenations of local features, as the basic features for representing natural actions. In this concept, any action is a spatial-temporal concatenation of a set of natural action structures, which convey a full range of information about natural actions. We took several steps to extract these structures. First, we sampled a large number of sequences of patches at multiple spatial-temporal scales. Second, we performed independent component analysis on the patch sequences and classified the independent components into clusters. Finally, we compiled a large set of natural action structures, with each corresponding to a unique combination of the clusters at the selected spatial-temporal scales. To classify human actions, we used a set of informative natural action structures as inputs to two widely used models. We found that the natural action structures obtained here achieved a significantly better recognition performance than low-level features and that the performance was better than or comparable to the best current models. We also found that the classification performance with natural action structures as features was slightly affected by changes of scale and artificially added noise. We concluded that the natural action structures proposed here can be used as the basic encoding units of actions and may hold the key to natural action understanding.

Dataset Information

The spatial and temporal scales of local dengue virus transmission in natural settings: a retrospective analysis.

Publications

The spatial and temporal scales of local dengue virus transmission in natural settings: a retrospective analysis.

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