Determinants of Dengue 2 Infection among Residents of Charters Towers, Queensland, Australia

McBride, William John Hannan; Mullner, Helen; Müller, Reinhold; LaBrooy, Justin T.; Wronski, Ian

doi:10.1093/oxfordjournals.aje.a009589

Cited by 22 publications

(23 citation statements)

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“…For dengue viruses, Koopman et al (1991) and McBride et al (1997) have demonstrated an association between water containers and the increased risk of infection, but both studies focused on surface breeding containers. This is not surprising because, before the advent of the funnel trap (Russell and Kay 1999), some subterranean habitats have been difÞcult to sample.…”

Section: Discussionmentioning

confidence: 99%

“…An epidemiological study of 10% of Charters Towers population revealed a dengue 2 seroprevalance of 24.6% (McBride et al 1997). A number of factors were identiÞed as major determinants of dengue 2 seropositivity and these included proximity to other dengue cases, household screening, and the presence of nearby water tank.…”

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confidence: 99%

“…The objective of our study was to reexamine data from the 1993 dengue epidemic (McBride et al 1997) in the light of new breeding site information to determine the epidemiological signiÞcance of subterranean mosquito breeding sites to the 1993 outbreak of dengue fever.…”

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confidence: 99%

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Epidemiological Significance of SubterraneanAedes aegypti(Diptera: Culicidae) Breeding Sites to Dengue Virus Infection in Charters Towers, 1993

et al. 2002

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The objective of this study wasto determine the epidemiological significance of subterranean mosquito breeding sites to the 1993 outbreak of dengue fever (type 2) in the northern Queensland town of Charters Towers, Australia. In recent studies on subterranean mosquito breeding, containers such as wells and service manholes have been shown to be important breeding sites to Australia's only dengue vector, Aedes aegypti (L.). This study demonstrates a direct epidemiological association between subterranean breeding sites and dengue virus infection. The mean distance between residents seropositive for dengue 2 and the nearest subterranean container (113 m) was significantly less than for a randomly selected control (191 m), (F = 81.9; df = 1, 478; P < 0.001). Residents positive for dengue 2 antibodies was 2.47 (95% confidence interval 1.88-3.24) times higher for those living within 160 m of a well or service manhole, compared with those residing further away. These findings emphasize the importance of incluuding subterranean water containers in Ae. aegypti surveillance and control programs.

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Section: Discussionmentioning

confidence: 99%

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Epidemiological Significance of SubterraneanAedes aegypti(Diptera: Culicidae) Breeding Sites to Dengue Virus Infection in Charters Towers, 1993

et al. 2002

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“…Furthermore they are easy to use and to interpretate, and thus provide a wide range of application fields. The use of CART procedure has been considered by others in a variety of medical problems [22,23] such as, for example, survival analysis [24-26], longitudinal analysis, diagnostic and prognostic studies or clinical trials [27-30]. …”

Section: Methodsmentioning

confidence: 99%

Oblique decision trees for spatial pattern detection: optimal algorithm and application to malaria risk

Gaudart

Poudiougou

Ranque

et al. 2005

BMC Med Res Methodol

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BackgroundIn order to detect potential disease clusters where a putative source cannot be specified, classical procedures scan the geographical area with circular windows through a specified grid imposed to the map. However, the choice of the windows' shapes, sizes and centers is critical and different choices may not provide exactly the same results.The aim of our work was to use an Oblique Decision Tree model (ODT) which provides potential clusters without pre-specifying shapes, sizes or centers. For this purpose, we have developed an ODT-algorithm to find an oblique partition of the space defined by the geographic coordinates.MethodsODT is based on the classification and regression tree (CART). As CART finds out rectangular partitions of the covariate space, ODT provides oblique partitions maximizing the interclass variance of the independent variable. Since it is a NP-Hard problem in RN, classical ODT-algorithms use evolutionary procedures or heuristics. We have developed an optimal ODT-algorithm in R2, based on the directions defined by each couple of point locations. This partition provided potential clusters which can be tested with Monte-Carlo inference.We applied the ODT-model to a dataset in order to identify potential high risk clusters of malaria in a village in Western Africa during the dry season. The ODT results were compared with those of the Kulldorff' s SaTScan™.ResultsThe ODT procedure provided four classes of risk of infection. In the first high risk class 60%, 95% confidence interval (CI95%) [52.22–67.55], of the children was infected. Monte-Carlo inference showed that the spatial pattern issued from the ODT-model was significant (p < 0.0001).Satscan results yielded one significant cluster where the risk of disease was high with an infectious rate of 54.21%, CI95% [47.51–60.75]. Obviously, his center was located within the first high risk ODT class. Both procedures provided similar results identifying a high risk cluster in the western part of the village where a mosquito breeding point was located.ConclusionODT-models improve the classical scanning procedures by detecting potential disease clusters independently of any specification of the shapes, sizes or centers of the clusters.

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“…A solid understanding of the epidemiology of emerging arboviral diseases is crucial for the development and operation of functional control/surveillance systems [2], [4]. However, except for dengue virus (e.g., [5]–[7]) and a few other arboviruses (e.g., [8]–[10]), risk factors for infection remain poorly understood.…”

Section: Introductionmentioning

confidence: 99%

Mayaro Virus Infection in Amazonia: A Multimodel Inference Approach to Risk Factor Assessment

Abad‐Franch¹,

Grimmer²,

Paula

et al. 2012

PLoS Negl Trop Dis

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BackgroundArboviral diseases are major global public health threats. Yet, our understanding of infection risk factors is, with a few exceptions, considerably limited. A crucial shortcoming is the widespread use of analytical methods generally not suited for observational data – particularly null hypothesis-testing (NHT) and step-wise regression (SWR). Using Mayaro virus (MAYV) as a case study, here we compare information theory-based multimodel inference (MMI) with conventional analyses for arboviral infection risk factor assessment.Methodology/Principal FindingsA cross-sectional survey of anti-MAYV antibodies revealed 44% prevalence (n = 270 subjects) in a central Amazon rural settlement. NHT suggested that residents of village-like household clusters and those using closed toilet/latrines were at higher risk, while living in non-village-like areas, using bednets, and owning fowl, pigs or dogs were protective. The “minimum adequate” SWR model retained only residence area and bednet use. Using MMI, we identified relevant covariates, quantified their relative importance, and estimated effect-sizes (β±SE) on which to base inference. Residence area (β Village = 2.93±0.41; β Upland = −0.56±0.33, β Riverbanks = −2.37±0.55) and bednet use (β = −0.95±0.28) were the most important factors, followed by crop-plot ownership (β = 0.39±0.22) and regular use of a closed toilet/latrine (β = 0.19±0.13); domestic animals had insignificant protective effects and were relatively unimportant. The SWR model ranked fifth among the 128 models in the final MMI set.Conclusions/SignificanceOur analyses illustrate how MMI can enhance inference on infection risk factors when compared with NHT or SWR. MMI indicates that forest crop-plot workers are likely exposed to typical MAYV cycles maintained by diurnal, forest dwelling vectors; however, MAYV might also be circulating in nocturnal, domestic-peridomestic cycles in village-like areas. This suggests either a vector shift (synanthropic mosquitoes vectoring MAYV) or a habitat/habits shift (classical MAYV vectors adapting to densely populated landscapes and nocturnal biting); any such ecological/adaptive novelty could increase the likelihood of MAYV emergence in Amazonia.

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Determinants of Dengue 2 Infection among Residents of Charters Towers, Queensland, Australia

Cited by 22 publications

References 13 publications

Epidemiological Significance of SubterraneanAedes aegypti(Diptera: Culicidae) Breeding Sites to Dengue Virus Infection in Charters Towers, 1993

Epidemiological Significance of SubterraneanAedes aegypti(Diptera: Culicidae) Breeding Sites to Dengue Virus Infection in Charters Towers, 1993

Oblique decision trees for spatial pattern detection: optimal algorithm and application to malaria risk

Mayaro Virus Infection in Amazonia: A Multimodel Inference Approach to Risk Factor Assessment

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