Environmental and entomological factors determining Ross River virus activity in the River Murray Valley of South Australia

Development of a regional climate change model for Aedes vigilax and Aedes camptorhynchus (Diptera: Culicidae) in Perth, Western Australia

Mosquito-borne disease is a significant public health issue and within Australia Ross River virus (RRV) is the most reported. This study combines a mechanistic model of mosquito development for two mosquito vectors; Aedes vigilax and Aedes camptorhynchus, with climate projections from three climate models for two Representative Concentration Pathways (RCPs), to examine the possible effects of climate change and sea-level rise on a temperate tidal saltmarsh habitat in Perth, Western Australia. The projections were run under no accretion and accretion scenarios using a known mosquito habitat as a case study. This improves our understanding of the possible implications of sea-level rise, accretion and climate change for mosquito control programmes for similar habitats across temperate tidal areas found in Southwest Western Australia. The output of the model indicate that the proportion of the year mosquitoes are active increases. Population abundances of the two Aedes species increase markedly. The main drivers of changes in mosquito population abundances are increases in the frequency of inundation of the tidal wetland and size of the area inundated, increased minimum water temperature, and decreased daily temperature fluctuations as water depth increases due to sea level changes, particularly under the model with no accretion. The effects on mosquito populations are more marked for RCP 8.5 when compared to RCP 4.5 but were consistent among the three climate change models. The results indicate that Ae. vigilax is likely to be the most abundant species in 2030 and 2050, but that by 2070 Aedes camptorhynchus may become the more abundant species. This increase would put considerable pressure on existing mosquito control programmes and increase the risk of mosquito-borne disease and nuisance biting to the local community, and planning to mitigate these potential impacts should commence now.

Prediction of Ross River Virus Incidence Using Mosquito Data in Three Cities of Queensland, Australia

Ross River virus (RRV) is the most common mosquito-borne disease in Australia, with Queensland recording high incidence rates (with an annual average incidence rate of 0.05% over the last 20 years). Accurate prediction of RRV incidence is critical for disease management and control. Many factors, including mosquito abundance, climate, weather, geographical factors, and socio-economic indices, can influence the RRV transmission cycle and thus have potential utility as predictors of RRV incidence. We collected mosquito data from the city councils of Brisbane, Redlands, and Mackay in Queensland, together with other meteorological and geographical data. Predictors were selected to build negative binomial generalised linear models for prediction. The models demonstrated excellent performance in Brisbane and Redlands but were less satisfactory in Mackay. Mosquito abundance was selected in the Brisbane model and can improve the predictive performance. Sufficient sample sizes of continuous mosquito data and RRV cases were essential for accurate and effective prediction, highlighting the importance of routine vector surveillance for disease management and control. Our results are consistent with variation in transmission cycles across different cities, and our study demonstrates the usefulness of mosquito surveillance data for predicting RRV incidence within small geographical areas.

A Multi-Species Simulation of Mosquito Disease Vector Development in Temperate Australian Tidal Wetlands Using Publicly Available Data

Worldwide, mosquito monitoring and control programs consume large amounts of resources in the effort to minimise mosquito-borne disease incidence. On-site larval monitoring is highly effective but time consuming. A number of mechanistic models of mosquito development have been developed to reduce the reliance on larval monitoring, but none for Ross River virus, the most commonly occurring mosquito-borne disease in Australia. This research modifies existing mechanistic models for malaria vectors and applies it to a wetland field site in Southwest, Western Australia. Environmental monitoring data were applied to an enzyme kinetic model of larval mosquito development to simulate timing of adult emergence and relative population abundance of three mosquito vectors of the Ross River virus for the period of 2018-2020. The model results were compared with field measured adult mosquitoes trapped using carbon dioxide light traps. The model showed different patterns of emergence for the three mosquito species, capturing inter-seasonal and inter-year variation, and correlated well with field adult trapping data. The model provides a useful tool to investigate the effects of different weather and environmental variables on larval and adult mosquito development and can be used to investigate the possible effects of changes to short-term and long-term sea level and climate changes.

Associations between temperature and Ross river virus infection: A systematic review and meta-analysis of epidemiological evidence

Ross River virus (RRV) infection is one of the emerging and prevalent arboviral diseases in Australia and the Pacific Islands. Although many studies have been conducted to establish the relationship between temperature and RRV infection, there has been no comprehensive review of the association so far. In this study, we performed a systematic review and meta-analysis to assess the effect of temperature on RRV transmission. We searched PubMed, Scopus, Embase, and Web of Science with additional lateral searches from references. The quality and strength of evidence from the included studies were evaluated following the Navigation Guide framework. We have qualitatively synthesized the evidence and conducted a meta-analysis to pool the relative risks (RRs) of RRV infection per 1 °C increase in temperature. Subgroup analyses were performed by climate zones, temperature metrics, and lag periods. A total of 17 studies met the inclusion criteria, of which six were included in the meta-analysis The meta-analysis revealed that the overall RR for the association between temperature and the risk of RRV infection was 1.09 (95% confidence interval (CI): 1.02, 1.17). Subgroup analyses by climate zones showed an increase in RRV infection per 1 °C increase in temperature in humid subtropical and cold semi-arid climate zones. The overall quality of evidence was "moderate" and we rated the strength of evidence to be "limited", warranting additional evidence to reduce uncertainty. The results showed that the risk of RRV infection is positively associated with temperature. However, the risk varies across different climate zones, temperature metrics and lag periods. These findings indicate that future studies on the association between temperature and RRV infection should consider local and regional climate, socio-demographic, and environmental factors to explore vulnerability at local and regional levels.

Using ecological variables to predict Ross River virus disease incidence in South Australia

BACKGROUND

Ross River virus (RRV) disease is Australia's most widespread vector-borne disease causing significant public health concern. The aim of this study was to identify the ecological covariates of RRV risk and to develop epidemic forecasting models in a disease hotspot region of South Australia.

METHODS

Seasonal autoregressive integrated moving average models were used to predict the incidence of RRV disease in the Riverland region of South Australia, an area known to have a high incidence of the disease. The model was developed using data from January 2000 to December 2012 then validated using disease notification data on reported cases for the following year.

RESULTS

Monthly numbers of the mosquito Culex annulirostris (β=0.033, p<0.001) and total rainfall (β=0.263, p=0.002) were significant predictors of RRV transmission in the study region. The forecasted RRV incidence in the predictive model was generally consistent with the actual number of cases in the study area.

CONCLUSIONS

A predictive model has been shown to be useful in forecasting the occurrence of RRV disease, with increased vector populations and rainfall being important factors associated with transmission. This approach may be useful in a public health context by providing early warning of vector-borne diseases in other settings.

Spatial and temporal patterns of Ross River virus in south east Queensland, Australia: identification of hot spots at the rural-urban interface

Background

Ross 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.

Methods

The 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.

Results

The 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.

Conclusions

Although 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.

Epidemiological models for predicting Ross River virus in Australia: A systematic review

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.

The geography of Ross River virus infection in South Australia, 2000-2013

Introduction

Ross River virus (RRV) disease is Australia's most common arthropod-borne disease which has an important impact on population health and productivity. The aim of this study was to identify the spatial and temporal distribution of RRV notifications during 2000-2013 in South Australia (SA).

Methods

The epidemiologic patterns of RRV notifications in SA from January 2000 to December 2013 were examined at a statistical local area (SLA) level. Spatial-temporal analyses were conducted using patient-reported place of exposure to characterise the recurrence of RRV infection stratified by age and sex.

Results

During the study period, a total of 3,687 RRV disease notifications were recorded in the state with state-wide mean annual rates of 16.8 cases per 100,000 persons and a 1:1.32 male:female ratio. The SLAs reporting cases of RRV disease exhibited spatial and temporal variation. Notified cases of RRV disease occurred more frequently in summer and autumn. A geographic expansion was observed of the area within which RRV cases occur. The comparison of age- and sex-standardised incidence rates, calculated by place of residence and patient-reported place of exposure, highlights the importance of using the latter to accurately display geospatial disease trends over time. Areas with the largest proportion of visitor cases and having the highest risk were mostly along the River Murray, which provides many vector mosquito habitats.

Conclusion

Although public health interventions should be considered in all SLAs where RRV occurs, we suggest that priority should be given to the Riverland areas identified as highest risk.

Flooding and Arboviral Disease: Predicting Ross River Virus Disease Outbreaks Across Inland Regions of South-Eastern Australia

Flood frequency is expected to increase across the globe with climate change. Understanding the relationship between flooding and arboviral disease can reduce disease risk and associated costs. South-eastern Australia is dominated by the flood-prone Murray-Darling River system where the incidence of Australia's most common arboviral disease, Ross River virus (RRV), is high. This study aimed to determine the relationship between riverine flooding and RRV disease outbreaks in inland south-eastern Australia, specifically New South Wales (NSW). Each study month from 1991 to 2013, for each of 37 local government areas (LGAs) was assigned 'outbreak/non-outbreak' status based on long-term trimmed-average age-standardized RRV notification rates and 'flood/non-flood' status based on riverine overflow. LGAs were grouped into eight climate zones with the relationship between flood and RRV outbreak modeled using generalized estimating equations. Modeling adjusted for rainfall in the previous 1-3 mo. Spring-summer flooding increased the odds of summer RRV outbreaks in three climate zones before and after adjusting for rainfall 1, 2, and 3 mo prior to the outbreak. Flooding at any time of the year was not predictive of RRV outbreaks in the remaining five climate zones. Predicting RRV disease outbreaks with flood events can assist with more targeted mosquito spraying programs, thereby reducing disease transmission and mosquito resistance.

The forecasting of dynamical Ross River virus outbreaks: Victoria, Australia

Ross River virus (RRV) is Australia's most epidemiologically important mosquito-borne disease. During RRV epidemics in the State of Victoria (such as 2010/11 and 2016/17) notifications can account for up to 30% of national RRV notifications. However, little is known about factors which can forecast RRV transmission in Victoria. We aimed to understand factors associated with RRV transmission in epidemiologically important regions of Victoria and establish an early warning forecast system. We developed negative binomial regression models to forecast human RRV notifications across 11 Local Government Areas (LGAs) using climatic, environmental, and oceanographic variables. Data were collected from July 2008 to June 2018. Data from July 2008 to June 2012 were used as a training data set, while July 2012 to June 2018 were used as a testing data set. Evapotranspiration and precipitation were found to be common factors for forecasting RRV notifications across sites. Several site-specific factors were also important in forecasting RRV notifications which varied between LGA. From the 11 LGAs examined, nine experienced an outbreak in 2011/12 of which the models for these sites were a good fit. All 11 LGAs experienced an outbreak in 2016/17, however only six LGAs could predict the outbreak using the same model. We document similarities and differences in factors useful for forecasting RRV notifications across Victoria and demonstrate that readily available and inexpensive climate and environmental data can be used to predict epidemic periods in some areas. Furthermore, we highlight in certain regions the complexity of RRV transmission where additional epidemiological information is needed to accurately predict RRV activity. Our findings have been applied to produce a Ross River virus Outbreak Surveillance System (ROSS) to aid in public health decision making in Victoria.

The Role of Temperature in Transmission of Zoonotic Arboviruses

We reviewed the literature on the role of temperature in transmission of zoonotic arboviruses. Vector competence is affected by both direct and indirect effects of temperature, and generally increases with increasing temperature, but results may vary by vector species, population, and viral strain. Temperature additionally has a significant influence on life history traits of vectors at both immature and adult life stages, and for important behaviors such as blood-feeding and mating. Similar to vector competence, temperature effects on life history traits can vary by species and population. Vector, host, and viral distributions are all affected by temperature, and are generally expected to change with increased temperatures predicted under climate change. Arboviruses are generally expected to shift poleward and to higher elevations under climate change, yet significant variability on fine geographic scales is likely. Temperature effects are generally unimodal, with increases in abundance up to an optimum, and then decreases at high temperatures. Improved vector distribution information could facilitate future distribution modeling. A wide variety of approaches have been used to model viral distributions, although most research has focused on the West Nile virus. Direct temperature effects are frequently observed, as are indirect effects, such as through droughts, where temperature interacts with rainfall. Thermal biology approaches hold much promise for syntheses across viruses, vectors, and hosts, yet future studies must consider the specificity of interactions and the dynamic nature of evolving biological systems.

Temperature explains broad patterns of Ross River virus transmission

Thermal biology predicts that vector-borne disease transmission peaks at intermediate temperatures and declines at high and low temperatures. However, thermal optima and limits remain unknown for most vector-borne pathogens. We built a mechanistic model for the thermal response of Ross River virus, an important mosquito-borne pathogen in Australia, Pacific Islands, and potentially at risk of emerging worldwide. Transmission peaks at moderate temperatures (26.4°C) and declines to zero at thermal limits (17.0 and 31.5°C). The model accurately predicts that transmission is year-round endemic in the tropics but seasonal in temperate areas, resulting in the nationwide seasonal peak in human cases. Climate warming will likely increase transmission in temperate areas (where most Australians live) but decrease transmission in tropical areas where mean temperatures are already near the thermal optimum. These results illustrate the importance of nonlinear models for inferring the role of temperature in disease dynamics and predicting responses to climate change.

Mosquitoes cannot control their body temperature, so their survival and performance depend on the temperature where they live. As a result, outside temperatures can also affect the spread of diseases transmitted by mosquitoes. This has left scientists wondering how climate change may affect the spread of mosquito-borne diseases. Predicting the effects of climate change on such diseases is tricky, because many interacting factors, including temperatures and rainfall, affect mosquito populations. Also, rising temperatures do not always have a positive effect on mosquitoes – they may help mosquitoes initially, but it can get too warm even for these animals.

Climate change could affect the Ross River virus, the most common mosquito-borne disease in Australia. The virus infects 2,000 to 9,000 people each year and can cause long-term joint pain and disability. Currently, the virus spreads year-round in tropical, northern Australia and seasonally in temperate, southern Australia. Large outbreaks have occurred outside of Australia, and scientists are worried it could spread worldwide.

Now, Shocket et al. have built a model that predicts how the spread of Ross River virus changes with temperature. Shocket et al. used data from laboratory experiments that measured mosquito and virus performance across a broad range of temperatures. The experiments showed that ~26°C (80°F) is the optimal temperature for mosquitoes to spread the Ross River virus. Temperatures below 17°C (63°F) and above 32°C (89°F) hamper the spread of the virus. These temperature ranges match the current disease patterns in Australia where human cases peak in March. This is two months after the country’s average temperature reaches the optimal level and about how long it takes mosquito populations to grow, infect people, and for symptoms to develop.

Because northern Australia is already near the optimal temperature for mosquitos to spread the Ross River virus, any climate warming should decrease transmission there. But warming temperatures could increase the disease’s transmission in the southern part of the country, where most people live. The model Shocket et al. created may help the Australian government and mosquito control agencies better plan for the future.

Hydrological features and the ecological niches of mammalian hosts delineate elevated risk for Ross River virus epidemics in anthropogenic landscapes in Australia

Background

The current understanding of the landscape epidemiology of Ross River virus (RRV), Australia’s most common arthropod-borne pathogen, is fragmented due to gaps in surveillance programs and the relatively narrow focus of the research conducted to date. This leaves public health agencies with an incomplete understanding of the spectrum of infection risk across the diverse geography of the Australian continent. The current investigation sought to assess the risk of RRV epidemics based on abiotic and biotic landscape features in anthropogenic landscapes, with a particular focus on the influence of water and wildlife hosts.

Methods

Abiotic features, including hydrology, land cover and altitude, and biotic features, including the distribution of wild mammalian hosts, were interrogated using a Maxent model to discern the landscape suitability to RRV epidemics in anthropogenically impacted environments across Australia.

Results

Water-soil balance, proximity to controlled water reservoirs, and the ecological niches of four species (Perameles nasuta, Wallabia bicolor, Pseudomys novaehollandiae and Trichosurus vulpecula) were important features identifying high risk landscapes suitable for the occurrence of RRV epidemics.

Conclusions

These results help to delineate human infection risk and thus provide an important perspective for geographically targeted vector, wildlife, and syndromic surveillance within and across the boundaries of local health authorities. Importantly, our analysis highlights the importance of the hydrology, and the potential role of mammalian host species in shaping RRV epidemic risk in peri-urban space. This study offers novel insight into wildlife hosts and RRV infection ecology and identifies those species that may be beneficial to future targeted field surveillance particularly in ecosystems undergoing rapid change.

Electronic supplementary material

The online version of this article (10.1186/s13071-018-2776-x) contains supplementary material, which is available to authorized users.

Fine-temporal forecasting of outbreak probability and severity: Ross River virus in Western Australia

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 (r2 = 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.

Converting Mosquito Surveillance to Arbovirus Surveillance with Honey-Baited Nucleic Acid Preservation Cards

Spatially and temporally accurate information about infectious mosquito distribution allows for pre-emptive public health interventions that can reduce the burden of mosquito-borne infections on human populations. However, the labile nature of arboviruses, the low prevalence of infection in mosquitoes, the expensive labor costs for mosquito identification and sorting, and the specialized equipment required for arbovirus testing can obstruct arbovirus surveillance efforts. The recently developed techniques of testing mosquito expectorate using honey-baited nucleic acid preservation cards or sugar bait stations allows a sensitive method of testing for infectious, rather than infected, mosquito vectors. Here we report the results from the first large-scale incorporation of honey-baited cards into an existing mosquito surveillance program. During 4 months of the peak virus season (January-April, 2014) for a total of 577 trap nights, we set CO2-baited encephalitis vector survey (EVS) light traps at 88 locations in South Australia. The collection container for the EVS trap was modified to allow for the placement of a honey-baited nucleic acid preservation card (FTA™ card) inside. After collection, mosquitoes were maintained in a humid environment and allowed access to the cards for 1 week. Cards were then analyzed for common endemic Australian arboviruses using a nested RT-PCR. Eighteen virus detections, including 11 Ross River virus, four Barmah Forest virus, and three Stratford virus (not previously reported from South Australia) were obtained. Our findings suggest that adding FTA cards to an existing mosquito surveillance program is a rapid and efficient way of detecting infectious mosquitoes with high spatial resolution.

Predictive modelling of Ross River virus notifications in southeastern Australia

Ross River virus (RRV) is a mosquito-borne virus endemic to Australia. The disease, marked by arthritis, myalgia and rash, has a complex epidemiology involving several mosquito species and wildlife reservoirs. Outbreak years coincide with climatic conditions conducive to mosquito population growth. We developed regression models for human RRV notifications in the Mildura Local Government Area, Victoria, Australia with the objective of increasing understanding of the relationships in this complex system, providing trigger points for intervention and developing a forecast model. Surveillance, climatic, environmental and entomological data for the period July 2000-June 2011 were used for model training then forecasts were validated for July 2011-June 2015. Rainfall and vapour pressure were the key factors for forecasting RRV notifications. Validation of models showed they predicted RRV counts with an accuracy of 81%. Two major RRV mosquito vectors (Culex annulirostris and Aedes camptorhynchus) were important in the final estimation model at proximal lags. The findings of this analysis advance understanding of the drivers of RRV in temperate climatic zones and the models will inform public health agencies of periods of increased risk.

Regional Comparison of Mosquito Bloodmeals in South Australia: Implications for Ross River Virus Ecology

Ross River virus (RRV) is responsible for the most notifications of human arboviral infection in Australia. Seroprevalence and experimental infection studies have implicated macropods (e.g., kangaroos) as the major reservoir hosts. However, transmission ecology varies spatially, and infections in urban areas have prompted the question of what animals serve as reservoirs in regions where macropods are scarce. In South Australia (SA), human infection rates for RRV vary greatly by region as do vector and reservoir abundance. We hypothesized that mosquito abundance and feeding patterns would vary among ecoregions of SA and could help explain divergent human case rates. To test our hypothesis, we amplified and sequenced a 457 base pair region of the cytochrome B segment of mitochondrial DNA from blood fed mosquitoes collected in three main ecoregions of SA and identified sequences using a BLAST search in NCBI. Domestic livestock made up the vast majority of bloodmeals from the region with the highest human infection rate. Livestock are generally not considered to be important reservoir hosts for RRV, but our results suggest they may have a role in transmission ecology in some places. Surprisingly, none of the 199 bloodmeal samples were identified as macropod in origin. In the context of these findings, we consider the possible RRV vectors and reservoir hosts in these regions and propose that diverse spatial and temporal transmission ecologies occur in SA, depending on vector and reservoir availability.

Improving public health intervention for mosquito-borne disease: the value of geovisualization using source of infection and LandScan data

Epidemiological studies use georeferenced health data to identify disease clusters but the accuracy of this georeferencing is obfuscated by incorrectly assigning the source of infection and by aggregating case data to larger geographical areas. Often, place of residence (residence) is used as a proxy for the source of infection (source) which may not be accurate. Using a 21-year dataset from South Australia of human infections with the mosquito-borne Ross River virus, we found that 37% of cases were believed to have been acquired away from home. We constructed two risk maps using age-standardized morbidity ratios (SMRs) calculated using residence and patient-reported source. Both maps confirm significant inter-suburb variation in SMRs. Areas frequently named as the source (but not residence) and the highest-risk suburbs both tend to be tourist locations with vector mosquito habitat, and camping or outdoor recreational opportunities. We suggest the highest-risk suburbs as places to focus on for disease control measures. We also use a novel application of ambient population data (LandScan) to improve the interpretation of these risk maps and propose how this approach can aid in implementing disease abatement measures on a smaller scale than for which disease data are available.

Ross River Virus (RRV) infection in horses and humans: a review

A fascinating and important arbovirus is Ross River Virus (RRV) which is endemic and epizootic in nature in certain parts of the world. RRV is a member of the genus Alphavirus within the Semliki Forest complex of the family Togaviridae, which also includes the Getah virus. The virus is responsible for causing disease both in humans as well as horses. Mosquito species (Aedes camptorhynchus and Aedes vigilax; Culex annulirostris) are the most important vector for this virus. In places of low temperature as well as low rainfall or where there is lack of habitat of mosquito there is also limitation in the transmission of the virus. Such probability is higher especially in temperate regions bordering endemic regions having sub-tropical climate. There is involvement of articular as well as non-articular cells in the replication of RRV. Levels of pro-inflammatory factors viz., tumor necrosis factor-alpha (TNF-α); interferon-gamma (IFN-γ); and macrophage chemo-attractant protein-1 (MAC-1) during disease pathogenesis have been found to be reduced. Reverse transcription-polymerase chain reaction (RT-PCR) is the most advanced molecular diagnostic tool along with epitope-blocking enzyme-linked immunosorbent assay (ELISA) for detecting RRV infection. Treatment for RRV infection is only supportive. Vaccination is not a fruitful approach. Precise data collection will help the researchers to understand the RRV disease dynamics and thereby designing effective prevention and control strategy. Advances in diagnosis, vaccine development and emerging/novel therapeutic regimens need to be explored to their full potential to tackle RRV infection and the disease it causes.

West nile virus and equine encephalitis viruses: new perspectives

Mosquito-borne diseases affect horses worldwide. Mosquito-borne diseases generally cause encephalomyelitis in the horse and can be difficult to diagnose antemortem. In addition to general disease, and diagnostic and treatment aspects, this review article summarizes the latest information on these diseases, covering approximately the past 5 years, with a focus on new equine disease encroachments, diagnostic and vaccination aspects, and possible therapeutics on the horizon.

Analysis and prediction of Ross River virus transmission in New South Wales, Australia

BACKGROUND

Ross River virus (RRV) disease is the most widespread mosquito-borne disease in Australia. The disease is maintained in enzootic cycles between mosquitoes and reservoir hosts. During outbreaks and in endemic regions, RRV transmission can be sustained between vectors and reservoir hosts in zoonotic cycles with spillover to humans. Symptoms include arthritis, rash, fever and fatigue and can persist for several months. The prevalence and associated morbidity make this disease a medically and economically important mosquito-borne disease in Australia.

METHODS

Climate, environment, and RRV vector and reservoir host information were used to develop predictive models in four regions in NSW over a 13-year period (1991-2004). Polynomial distributed lag (PDL) models were used to explore long-term influences of up to 2 years ago that could be related to RRV activity.

RESULTS

Each regional model consisted of a unique combination of predictors for RRV disease highlighting the differences in the disease ecology and epidemiology in New South Wales (NSW). Events up to 2 years before were found to influence RRV activity. The shorter-term associations may reflect conditions that promote virus amplification in RRV vectors whereas long-term associations may reflect RRV reservoir host breeding and herd immunity. The models indicate an association between host populations and RRV disease, lagged by 24 months, suggesting two or more generations of susceptible juveniles may be necessary for an outbreak. Model sensitivities ranged from 60.4% to 73.1%, and model specificities ranged from 57.9% to 90.7%. This was the first study to include reservoir host data into statistical RRV models; the inclusion of host parameters was found to improve model fit significantly.

CONCLUSION

The research presents the novel use of a combination of climate, environment, and RRV vector and reservoir host information in statistical predictive models. The models have potential for public health decision-making.

Projecting the impact of climate change on the transmission of Ross River virus: methodological challenges and research needs

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.

Eggs of the Australian saltmarsh mosquito, Aedes camptorhynchus, survive for long periods and hatch in instalments: implications for biosecurity in New Zealand

The Australian saltmarsh mosquito, Aedes camptorhynchus (Diptera: Culicidae), is a significant biting pest and disease vector and is the subject of an eradication programme in New Zealand (NZ), where it has been resident for more than 10 years. To better understand the ecology of this common and widespread pest, we studied egg longevity and hatching patterns in the laboratory. By regularly testing for the presence of viable embryos, we found that eggs may last more than 15 months when stored dry (13% viable at this time). Eggs display instalment hatching, with no more than 56% of a batch hatching upon first inundation. Further hatching may occur for at least six inundations and some unhatched eggs may remain viable even after this. Variation in hatching rates can be observed using different water types, with weaker hatching media stimulating lower hatching rates spread over more inundations. By applying average hatching rates to a non-linear model of natural egg attrition, we showed that egg batches exposed to three inundations should be exhausted (zero live eggs present) in approximately 11 months at the conditions tested here. These findings have implications for the current eradication programme for Ae. camptorhynchus in NZ and for our understanding of the ecology of a widespread and common disease vector in Australia.

Arbovirus models to provide practical management tools for mosquito control and disease prevention in the Northern Territory, Australia

Ross River virus (RRV) causes the most common human arbovirus disease in Australia. Although the disease is nonfatal, the associated arthritis and postinfection fatigue can be debilitating for many months, impacting on workforce participation. We sought to create an early-warning system to notify of approaching RRV disease outbreak conditions for major townships in the Northern Territory. By applying a logistic regression model to meteorologic factors, including rainfall, a postestimation analysis of sensitivity and specificity can create rainfall cut-points. These rainfall cut-points indicate the rainfall level above which previous epidemic conditions have occurred. Furthermore, rainfall cut-points indirectly adjust for vertebrate host data from the agile wallaby (Macropus agilis) as the life cycle of the agile wallaby is intricately meshed with the wet season. Once generated, cut-points can thus be used prospectively to allow timely implementation of larval survey and control measures and public health warnings to preemptively reduce RRV disease incidence. Cut-points are location specific and have the capacity to replace previously used models, which require data management and input, and rarely provide timely notification for vector control requirements and public health warnings. These methods can be adapted for use elsewhere.