994 resultados para Ross River virus


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Ross River virus (RRV) is the most common vector-borne disease in Australia. It is vitally important to make appropriate projections on the future spread of RRV under various climate change scenarios because such information is essential for policy-makers to identify vulnerable communities and to better manage RRV epidemics. However, there are many methodological challenges in projecting the impact of climate change on the transmission of RRV disease. This study critically examined the methodological issues and proposed possible solutions. A literature search was conducted between January and October 2012, using the electronic databases Medline, Web of Science and PubMed. Nineteen relevant papers were identified. These studies demonstrate that key challenges for projecting future climate change on RRV disease include: (1) a complex ecology (e.g. many mosquito vectors, immunity, heterogeneous in both time and space); (2) unclear interactions between social and environmental factors; and (3) uncertainty in climate change modelling and socioeconomic development scenarios. Future risk assessments of climate change will ultimately need to better understand the ecology of RRV disease and to integrate climate change scenarios with local socioeconomic and environmental factors, in order to develop effective adaptation strategies to prevent or reduce RRV transmission.

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Ross River virus (RRV) infection is a debilitating disease which has a significant impact on population health, economic productivity and tourism in Australia. This study examined epidemiological patterns of the RRV disease in Queensland, Australia between January 2001 and December 2011 at a statistical local area level. Spatial-temporal analyses were used to identify the patterns of the disease distribution over time stratified by age, sex and space. The results show that the mean annual incidence was 54 per 100,000 people, with a male: female ratio of 1:1.1. Two space-time clusters were identified: the areas adjacent to Townsville, on the eastern coast of Queensland; and the south east areas. Thus, although public health intervention should be considered across all areas in which RRV occurs, it should specifically focus on these high risk regions, particularly during the summer and autumn to reduce the social and economic impacts of RRV.

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Background Detection of outbreaks is an important part of disease surveillance. Although many algorithms have been designed for detecting outbreaks, few have been specifically assessed against diseases that have distinct seasonal incidence patterns, such as those caused by vector-borne pathogens. Methods We applied five previously reported outbreak detection algorithms to Ross River virus (RRV) disease data (1991-2007) for the four local government areas (LGAs) of Brisbane, Emerald, Redland and Townsville in Queensland, Australia. The methods used were the Early Aberration Reporting System (EARS) C1, C2 and C3 methods, negative binomial cusum (NBC), historical limits method (HLM), Poisson outbreak detection (POD) method and the purely temporal SaTScan analysis. Seasonally-adjusted variants of the NBC and SaTScan methods were developed. Some of the algorithms were applied using a range of parameter values, resulting in 17 variants of the five algorithms. Results The 9,188 RRV disease notifications that occurred in the four selected regions over the study period showed marked seasonality, which adversely affected the performance of some of the outbreak detection algorithms. Most of the methods examined were able to detect the same major events. The exception was the seasonally-adjusted NBC methods that detected an excess of short signals. The NBC, POD and temporal SaTScan algorithms were the only methods that consistently had high true positive rates and low false positive and false negative rates across the four study areas. The timeliness of outbreak signals generated by each method was also compared but there was no consistency across outbreaks and LGAs. Conclusions This study has highlighted several issues associated with applying outbreak detection algorithms to seasonal disease data. In lieu of a true gold standard, a quantitative comparison is difficult and caution should be taken when interpreting the true positives, false positives, sensitivity and specificity.

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Ross River virus (RRV) disease is the most common and widespread mosquito-borne disease in Australia, resulting in considerable health and economic cost to communities. While naturally occurring non-tidal flood events may enhance mosquito abundance, little is known about the impact of such events on RRV transmission. This paper critically reviews the existing evidence for an association between naturally occurring non-tidal flood events and RRV transmission. A systematic literature search was conducted on RRV transmission related to flooding and inundation from rain and riverine overflow. Overall, the evidence to support a positive association between flooding and RRV outbreaks is largely circumstantial, with the literature mostly reporting only coincidental occurrence between the two. However, for the Murray River, river flow and height (surrogates of flooding) were positively and significantly associated with RRV transmission. The association between non-tidal flooding and RRV transmission has not been studied comprehensively. More frequent flood events arising from climate change may result in increased outbreaks of RRV disease. Understanding the link between flood events and RRV transmission is necessary if resources for mosquito spraying and public health warnings are to be utilized more effectively and efficiently.

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Ross River virus (RRV) is the predominant cause of epidemic polyarthritis in Australia, yet the antigenic determinants are not well defined. We aimed to characterize epitope(s) on RRV-E2 for a panel of monoclonal antibodies (MAbs) that recognize overlapping conformational epitopes on the E2 envelope protein of RRV and that neutralize virus infection of cells in vitro. Phage-displayed random peptide libraries were probed with the MAbs T1E7, NB3C4, and T10C9 using solution-phase and solid-phase biopanning methods. The peptides VSIFPPA and KTAISPT were selected 15 and 6 times, respectively, by all three of the MAbs using solution-phase biopanning. The peptide LRLPPAP was selected 8 times by NB3C4 using solid-phase biopanning; this peptide shares a trio of amino acids with the peptide VSIFPPA. Phage that expressed the peptides VSIFPPA and LRLPPAP were reactive with T1E7 and/or NB3C4, and phage that expressed the peptides VSIFPPA, LRLPPAP, and KTAISPT partially inhibited the reactivity of T1E7 with RRV. The selected peptides resemble regions of RRV-E2 adjacent to sites mutated in neutralization escape variants of RRV derived by culture in the presence of these MAbs (E2 210-219 and 238-245) and an additional region of E2 172-182. Together these sites represent a conformational epitope of E2 that is informative of cellular contact sites on RRV.

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Various authors have suggested a general predictive value of climatic indices of El Nino/Southem Oscillation events as indicators of outbreaks of arbovirus disease, particularly Ross River virus in Australia. By analyzing over 100 years of historical outbreak data on Ross River virus disease, our data indicate that, although high Southern Oscillation Index and La Nina conditions are potentially important predictors for the Murray Darling River region, this is not the case for the other four ecological zones in Australia. Our study, therefore, cautions against overgeneralization and suggests that, since climate and weather exert different influences and have different biological implications for the multiplicity of vectors involved, it is logical that predictors should be heterogeneous.

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Ross River virus (RE) is a mosquito-borne arbovirus responsible for outbreaks of polyarthritic disease throughout Australia. To better understand human and environmental factors driving such events, 57 historical reports oil RR Outbreaks between 1896 and 1998 were examined collectively. The magnitude, regularity, seasonality, and locality of outbreaks were found to be wide ranging; however, analysis of climatic and tidal data highlighted that environmental conditions let differently ill tropical, arid, and temperate regions. Overall, rainfall seems to be the single most important risk factor, with over 90% of major outbreak locations receiving higher than average rainfall in preceding mouths. Many temperatures were close to average, particularly in tropical populations; however, in arid regions, below average maximum temperatures predominated, and ill southeast temperate regions, above average minimum temperatures predominated. High spring tides preceded coastal Outbreaks, both in the presence and absence of rainfall, and the relationship between rainfall and the Southern Oscillation Index and Lit Nina episodes suggest they may be useful predictive tools, but only ill southeast temperate regions. Such heterogeneity predisposing outbreaks supports the notion that there are different RE epidemiologies throughout Australia but also Suggests that generic parameters for the prediction and control of outbreaks are of limited use at a local level.

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Ross River virus is a common mosquito-borne arbovirus responsible for outbreaks of polyarthritic disease throughout Australia. To better understand climatic factors preceding outbreaks, we compared seasonal and monthly rainfall and temperature trends in outbreak and nonoutbreak years at four epidemic-prone locations. Our analyses showed that rainfall in outbreak years tended to be above average and higher than rainfall in nonoutbreak years. Overall temperatures were warmer during outbreak years. However, there were a number of distinct deviations in temperature, which seem to play a role in either promoting or inhibiting outbreaks. These preliminary findings show that climatic differences occur between outbreak and nonoutbreak years; however, seasonal and monthly trends differed across geo-climatic regions of the country. More detailed research is imperative if we are to optimize the surveillance and control of epidemic polyarthritic disease in Australia.

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Background There are no analytical studies of individual risks for Ross River virus (RRV) disease. Therefore, we set out to determine individual risk and protective factors for RRV disease in a high incidence area and to assess the utility of the case-control design applied for this purpose to an arbovirus disease. Methods We used a prospective matched case-control study of new community cases of RRV disease in the local government areas of Cairns, Mareeba, Douglas, and Atherton, in tropical Queensland, from January I to May 31, 1998. Results Protective measures against mosquitoes reduced the risk for disease. Mosquito coils, repellents, and citronella candles each decreased risk by at least 2-fold, with a dose-response for the number of protective measures used. Light-coloured clothing decreased risk 3-fold. Camping increased the risk 8-fold. Conclusions These risks were substantial and statistically significant, and provide a basis for educational programs on individual protection against RRV disease in Australia. Our study demonstrates the utility of the case-control method for investigating arbovirus risks. Such a risk analysis has not been done before for RRV infection, and is infrequently reported for other arbovirus infections.

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We describe the development of an epitope-blocking enzyme-linked immunosorbent assay (ELISA) for the sensitive and rapid detection of antibodies to Ross River virus (RRV) in human sera and known vertebrate host species. This ELISA provides an alternative method for the serodiagnosis of RRV infections.

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The spatial heterogeneity in the risk of Ross River virus (family Togaviridae, genus Alphavirus, RRV) disease, the most common mosquito-borne disease in Australia, was examined in Redland Shire in southern Queensland, Australia. Disease cases, complaints from residents of intense mosquito biting exposure, and human population data were mapped using a geographic information system. Surface maps of RRV disease age-sex standardized morbidity ratios and mosquito biting complaint morbidity ratios were created. To determine whether there was significant spatial variation in disease and complaint patterns, a spatial scan analysis method was used to test whether the number of cases and complaints was distributed according to underlying population at risk. Several noncontiguous areas in proximity to productive saline water habitats of Aedes vigilax (Skuse), a recognized vector of RRV, had higher than expected numbers of RRV disease cases and complaints. Disease rates in human populations in areas which had high numbers of adult Ae. vigilax in carbon dioxide- and octenol-baited light traps were up to 2.9 times those in areas that rarely had high numbers of mosquitoes. It was estimated that targeted control of adult Ae. vigilax in these high-risk areas could potentially reduce the RRV disease incidence by an average of 13.6%. Spatial correlation was found between RRV disease risk and complaints from residents of mosquito biting. Based on historical patterns of RRV transmission throughout Redland Shire and estimated future human population growth in areas with higher than average RRV disease incidence, it was estimated that RRV incidence rates will increase by 8% between 2001 and 2021. The use of arbitrary administrative areas that ranged in size from 4.6 to 318.3 km2, has the potential to mask any small scale heterogeneity in disease patterns. With the availability of georeferenced data sets and high-resolution imagery, it is becoming more feasible to undertake spatial analyses at relatively small scales.

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In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (β = 0.15, p-value < 0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (β = −1.03, p-value = 0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention.