Epidemiologic, Entomologic, and Virologic Factors of the 2014-15 Ross River Virus Outbreak, Queensland, Australia.
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ABSTRACT:
SUBMITTER: Jansen CC
PROVIDER: S-EPMC6874252 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Ross River virus (RRV) infection is a debilitating disease that has a significant impact on population health, economic productivity, and tourism in Australia. This study examined epidemiologic patterns of RRV disease in Queensland, Australia, during January 2001-December 2011 at a statistical local area level. Spatio-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 persons, 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 southeast areas. Thus, although public health intervention should be considered across all areas in which RRV occurs, it should specifically focus on high-risk regions, particularly during summer and autumn to reduce the social and economic impacts of RRV infection.
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Project description:We investigated a dengue outbreak in Dar es Salaam, Tanzania, in 2014, that was caused by dengue virus (DENV) serotype 2. DENV infection was present in 101 (20.9%) of 483 patients. Patient age and location of residence were associated with infection. Seven (4.0%) of 176 patients were co-infected with malaria and DENV.
| S-EPMC4861515 | biostudies-literature
Project description:Health warnings of mosquito-borne disease risk require forecasts that are accurate at fine-temporal resolutions (weekly scales); however, most forecasting is coarse (monthly). We use environmental and Ross River virus (RRV) surveillance to predict weekly outbreak probabilities and incidence spanning tropical, semi-arid, and Mediterranean regions of Western Australia (1991-2014). Hurdle and linear models were used to predict outbreak probabilities and incidence respectively, using time-lagged environmental variables. Forecast accuracy was assessed by model fit and cross-validation. Residual RRV notification data were also examined against mitigation expenditure for one site, Mandurah 2007-2014. Models were predictive of RRV activity, except at one site (Capel). Minimum temperature was an important predictor of RRV outbreaks and incidence at all predicted sites. Precipitation was more likely to cause outbreaks and greater incidence among tropical and semi-arid sites. While variable, mitigation expenditure coincided positively with increased RRV incidence (r 2 = 0·21). Our research demonstrates capacity to accurately predict mosquito-borne disease outbreaks and incidence at fine-temporal resolutions. We apply our findings, developing a user-friendly tool enabling managers to easily adopt this research to forecast region-specific RRV outbreaks and incidence. Approaches here may be of value to fine-scale forecasting of RRV in other areas of Australia, and other mosquito-borne diseases.
| S-EPMC9152751 | biostudies-literature
Project description:Ross River virus (RRV), the most common human arbovirus infection in Australia, causes significant morbidity and substantial medical costs. About half of Australian cases occur in Queensland. We describe the spatial and temporal patterns of RRV disease in Queensland over the past two decades. RRV notifications, human population data, and weather data from 2001 to 2020 were analysed by the Statistical Area Level 2 (SA2) area. Spatial interpolation or linear extrapolation were used for missing weather values and the estimated population in 2020, respectively. Notifications and incidence rates were analysed through space and time. During the study period, there were 43,699 notifications in Queensland. The highest annual number of notifications was recorded in 2015 (6182), followed by 2020 (3160). The average annual incidence rate was 5 per 10,000 people and the peak period for RRV notifications was March to May. Generally, SA2 areas in northern Queensland had higher numbers of notifications and higher incidence rates than SA2 areas in southern Queensland. The SA2 areas with high incidence rates were in east coastal areas and western Queensland. The timely prediction may aid disease prevention and routine vector control programs, and RRV management plans are important for these areas.
| S-EPMC8396220 | biostudies-literature
Project description:BackgroundRoss River virus (RRV) is responsible for the most common vector-borne disease of humans reported in Australia. The virus circulates in enzootic cycles between multiple species of mosquitoes, wildlife reservoir hosts and humans. Public health concern about RRV is increasing due to rising incidence rates in Australian urban centres, along with increased circulation in Pacific Island countries. Australia experienced its largest recorded outbreak of 9544 cases in 2015, with the majority reported from south east Queensland (SEQ). This study examined potential links between disease patterns and transmission pathways of RRV.MethodsThe spatial and temporal distribution of notified RRV cases, and associated epidemiological features in SEQ, were analysed for the period 2001-2016. This included fine-scale analysis of disease patterns across the suburbs of the capital city of Brisbane, and those of 8 adjacent Local Government Areas, and host spot analyses to identify locations with significantly high incidence.ResultsThe mean annual incidence rate for the region was 41/100,000 with a consistent seasonal peak in cases between February and May. The highest RRV incidence was in adults aged from 30 to 64 years (mean incidence rate: 59/100,000), and females had higher incidence rates than males (mean incidence rates: 44/100,000 and 34/100,000, respectively). Spatial patterns of disease were heterogeneous between years, and there was a wide distribution of disease across both urban and rural areas of SEQ. Overall, the highest incidence rates were reported from predominantly rural suburbs to the north of Brisbane City, with significant hot spots located in peri-urban suburbs where residential, agricultural and conserved natural land use types intersect.ConclusionsAlthough RRV is endemic across all of SEQ, transmission is most concentrated in areas where urban and peri-urban environments intersect. The drivers of RRV transmission across rural-urban landscapes should be prioritised for further investigation, including identification of specific vectors and hosts that mediate human spillover.
| S-EPMC7530966 | biostudies-literature
Project description:Local transmission of chikungunya, a debilitating mosquito-borne viral disease, was first reported in Singapore in January 2008. After 3 months of absence, locally acquired Chikungunya cases resurfaced in May 2008, causing an outbreak that resulted in a total of 231 cases by September 2008. The circulating viruses were related to East, Central, and South African genotypes that emerged in the Indian Ocean region in 2005. The first local outbreak was due to a wild-type virus (alanine at codon 226 of the envelope 1 gene) and occurred in an area where Aedes aegypti mosquitoes were the primary vector. Strains isolated during subsequent outbreaks showed alanine to valine substitution (A226V) and largely spread in areas predominated by Ae. albopictus mosquitoes. These findings led to a revision of the current vector control strategy in Singapore. This report highlights the use of entomologic and virologic data to assist in the control of chikungunya in disease-endemic areas.
| S-EPMC2815960 | biostudies-literature
Project description:Ross River virus (RRV), an alphavirus of the Togaviridae family, is the most medically significant mosquito-borne virus of Australia. Past RRV phylogenetic and evolutionary analyses have been based on partial genome analyses only. Three geographically distinct RRV lineages, the Eastern, the Western, and the supposedly extinct North-Eastern lineage, were classified previously. We sought to expand on past phylogenies through robust genome-scale phylogeny to better understand RRV genetic diversity and evolutionary dynamics. We analyzed 106 RRV complete coding sequences, which included 13 genomes available on NCBI and 94 novel sequences derived for this study, sampled throughout Western Australia (1977-2014) and during the substantial Pacific Islands RRV epidemic (1979-1980). Our final data set comprised isolates sampled over 59 years (1959-2018) from a range of locations. Four distinct genotypes were defined, with the newly described genotype 4 (G4) found to be the contemporary lineage circulating in Western Australia. The prior geographical classification of RRV lineages was not supported by our findings, with evidence of geographical and temporal cocirculation of distinct genetic groups. Bayesian Markov chain Monte Carlo (MCMC) analysis revealed that RRV lineages diverged from a common ancestor approximately 94 years ago, with distinct lineages emerging roughly every 10 years over the past 50 years in periodic bursts of genetic diversity. Our study has enabled a more robust analysis of RRV evolutionary history and resolved greater genetic diversity that had been previously defined by partial E2 gene analysis.IMPORTANCE Ross River virus (RRV) causes the most common mosquito-borne infection in Australia and causes a significant burden of suffering to infected individuals as well as being a large burden to the Australian economy. The genetic diversity of RRV and its evolutionary history have so far only been studied using partial E2 gene analysis with a limited number of isolates. Robust whole-genome analysis has not yet been conducted. This study generated 94 novel near-whole-genome sequences to investigate the evolutionary history of RRV to better understand its genetic diversity through comprehensive whole-genome phylogeny. A better understanding of RRV genetic diversity will enable better diagnostics, surveillance, and potential future vaccine design.
| S-EPMC6955267 | biostudies-literature
Project description:Ross River virus (RRV) is the most common and widespread arbovirus in Australia. Epidemiological models of RRV increase understanding of RRV transmission and help provide early warning of outbreaks to reduce incidence. However, RRV predictive models have not been systematically reviewed, analysed, and compared. The hypothesis of this systematic review was that summarising the epidemiological models applied to predict RRV disease and analysing model performance could elucidate drivers of RRV incidence and transmission patterns. We performed a systematic literature search in PubMed, EMBASE, Web of Science, Cochrane Library, and Scopus for studies of RRV using population-based data, incorporating at least one epidemiological model and analysing the association between exposures and RRV disease. Forty-three articles, all of high or medium quality, were included. Twenty-two (51.2%) used generalised linear models and 11 (25.6%) used time-series models. Climate and weather data were used in 27 (62.8%) and mosquito abundance or related data were used in 14 (32.6%) articles as model covariates. A total of 140 models were included across the articles. Rainfall (69 models, 49.3%), temperature (66, 47.1%) and tide height (45, 32.1%) were the three most commonly used exposures. Ten (23.3%) studies published data related to model performance. This review summarises current knowledge of RRV modelling and reveals a research gap in comparing predictive methods. To improve predictive accuracy, new methods for forecasting, such as non-linear mixed models and machine learning approaches, warrant investigation.
| S-EPMC7537878 | biostudies-literature
Project description:The mechanisms driving dynamics of many epidemiologically important mosquito-borne pathogens are complex, involving combinations of vector and host factors (e.g., species composition and life-history traits), and factors associated with transmission and reporting. Understanding which intrinsic mechanisms contribute most to observed disease dynamics is important, yet often poorly understood. Ross River virus (RRV) is Australia's most important mosquito-borne disease, with variable transmission dynamics across geographic regions. We used deterministic ordinary differential equation models to test mechanisms driving RRV dynamics across major epidemic centers in Brisbane, Darwin, Mandurah, Mildura, Gippsland, Renmark, Murray Bridge, and Coorong. We considered models with up to two vector species (Aedes vigilax, Culex annulirostris, Aedes camptorhynchus, Culex globocoxitus), two reservoir hosts (macropods, possums), seasonal transmission effects, and transmission parameters. We fit models against long-term RRV surveillance data (1991-2017) and used Akaike Information Criterion to select important mechanisms. The combination of two vector species, two reservoir hosts, and seasonal transmission effects explained RRV dynamics best across sites. Estimated vector-human transmission rate (average β = 8.04x10-4per vector per day) was similar despite different dynamics. Models estimate 43% underreporting of RRV infections. Findings enhance understanding of RRV transmission mechanisms, provide disease parameter estimates which can be used to guide future research into public health improvements and offer a basis to evaluate mitigation practices.
| S-EPMC10868856 | biostudies-literature
Project description:BACKGROUND:Australian bat lyssavirus (ABLV) belongs to the genus Lyssavirus which also includes classic rabies virus and the European lyssaviruses. To date, the only three known human ABLV cases, all fatal, have been reported from Queensland, Australia. ABLV is widely distributed in Australian bats, and any bite or scratch from an Australian bat is considered a potential exposure to ABLV. METHODOLOGY/PRINCIPAL FINDINGS:Potential exposure to ABLV has been a notifiable condition in Queensland since 2005. We analysed notification data for potential exposures occurring between 2009 and 2014. There were 1,515 potential exposures to ABLV notified in Queensland, with an average annual notification rate of 5.6 per 100,000 population per year. The majority of notified individuals (96%) were potentially exposed to ABLV via bats, with a small number of cases potentially exposed via two ABLV infected horses and an ABLV infected human. The most common routes of potential exposure were through bat scratches (47%) or bites (37%), with less common routes being mucous membrane/broken skin exposure to bat saliva/brain tissue (2.2%). Intentional handling of bats by the general public was the major cause of potential exposures (56% of notifications). Examples of these potential exposures included people attempting to rescue bats caught in barbed wire fences/fruit tree netting, or attempting to remove bats from a home. Following potential exposures, 1,399 cases (92%) were recorded as having appropriate post-exposure prophylaxis (PEP) as defined in national guidelines, with the remainder having documentation of refusal or incomplete PEP. Up to a quarter of notifications occurred after two days from the potential exposure, but with some delays being more than three weeks. Of 393 bats available for testing during the reporting period, 20 (5.1%) had ABLV detected, including four species of megabats (all flying foxes) and one species of microbats (yellow-bellied sheathtail bat). CONCLUSIONS/SIGNIFICANCE:Public health strategies should address the strong motivation of some members of the public to help injured bats or bats in distress, by emphasising that their action may harm the bat and put themselves at risk of the fatal ABLV infection. Alternative messaging should include seeking advice from professional animal rescue groups, or in the event of human contact, public health units. Further efforts are required to ensure that when potential exposure occurs, timely reporting and appropriate post-exposure prophylaxis occur.
| S-EPMC5199083 | biostudies-literature