Ross River Virus Transmission Research Articles

Bayesian Spatiotemporal Analysis of Ross River Virus Incidence in Relation to Variation in Socio-Ecologic Factors in Queensland, Australia

ISEE-0154 Background and Objective: Ross River virus (RRV) infection is the most common mosquito-borne disease in Australia and some Pacific island nations. This study aims to examine the potential impact of socio-ecologic factors on the transmission of RRV infection in Queensland, Australia. Methods: We obtained the computerised data set on the notified Ross River virus (RRV) cases by Local Government Area (LGA) in Queensland for the period of 1st January 1999-31st December 2001 from the Queensland Department of Health. Weather (maximum temperature and rainfall) and socio-economic index for areas (SEIFA) data were obtained for the same period from the Australian Bureau of Meteorology and the Australian Bureau of Statistics. We used a Bayesian spatiotemporal conditional autoregressive (CAR) model to explore the relationship between monthly variation of RRV incidence and socio-ecologic factors and determine areas prone to social and ecologic-driven epidemics after adjusting for spatiotemporal variation. Results: Our results show the average increase in monthly RRV incidence rates was 2.4% (95% Credible Interval (CrI): 0.08-4.8%) and 2.0% (95% CrI: 1.6-2.3%) for a 10C increase in monthly average maximum temperature and per 10 millilitre increase in monthly average rainfall, respectively. There appears an interactive effect between temperature and rainfall on the RRV transmission. However, there was no significant association of SEIFA with RRV. Conclusion: The results of spatiotemporal CAR models confirm the previous reports that climate variability may have played a significant role in the transmission of RRV in Queensland, Australia. The interaction between temperature and rainfall may be important in determining the dynamic pattern of RRV transmission.

Climate Variability, Social and Environmental Factors, and Ross River Virus Transmission: Research Development and Future Research Needs

BackgroundArbovirus diseases have emerged as a global public health concern. However, the impact of climatic, social, and environmental variability on the transmission of arbovirus diseases remains to be determined.ObjectiveOur goal for this study was to provide an overview of research development and future research directions about the interrelationship between climate variability, social and environmental factors, and the transmission of Ross River virus (RRV), the most common and widespread arbovirus disease in Australia.MethodsWe conducted a systematic literature search on climatic, social, and environmental factors and RRV disease. Potentially relevant studies were identified from a series of electronic searches.ResultsThe body of evidence revealed that the transmission cycles of RRV disease appear to be sensitive to climate and tidal variability. Rainfall, temperature, and high tides were among major determinants of the transmission of RRV disease at the macro level. However, the nature and magnitude of the interrelationship between climate variability, mosquito density, and the transmission of RRV disease varied with geographic area and socioenvironmental condition. Projected anthropogenic global climatic change may result in an increase in RRV infections, and the key determinants of RRV transmission we have identified here may be useful in the development of an early warning system.ConclusionsThe analysis indicates that there is a complex relationship between climate variability, social and environmental factors, and RRV transmission. Different strategies may be needed for the control and prevention of RRV disease at different levels. These research findings could be used as an additional tool to support decision making in disease control/surveillance and risk management.

The Impact of Climate Variability on Ross River Virus Transmission in Queensland, Australia

The Impact of Climate Variability on Ross River Virus Transmission in Queensland, Australia

EXPLORATORY SPATIAL ANALYSIS OF SOCIAL AND ENVIRONMENTAL FACTORS ASSOCIATED WITH THE INCIDENCE OF ROSS RIVER VIRUS IN BRISBANE, AUSTRALIA

We used geographic information systems and a spatial analysis approach to explore the pattern of Ross River virus (RRV) incidence in Brisbane, Australia. Climate, vegetation and socioeconomic data in 2001 were obtained from the Australian Bureau of Meteorology, the Brisbane City Council and the Australian Bureau of Statistics, respectively. Information on the RRV cases was obtained from the Queensland Department of Health. Spatial and multiple negative binomial regression models were used to identify the socioeconomic and environmental determinants of RRV transmission. The results show that RRV activity was primarily concentrated in the northeastern, northwestern, and southeastern regions in Brisbane. Multiple negative binomial regression models showed that the spatial pattern of RRV disease in Brisbane seemed to be determined by a combination of local ecologic, socioeconomic, and environmental factors.

Rainfall, mosquito density and the transmission of Ross River virus: A time-series forecasting model

This paper attempted to develop an epidemic forecasting model using local data on rainfall and mosquito density to predict outbreaks of Ross River virus (RRV) disease in Brisbane, Australia. We obtained monthly data on the counts of RRV cases, monthly total rainfall, human population size and mosquito density (i.e., average number of mosquitoes trapped in all mosquito monitoring stations per month) between 1 November 1998 and 31 December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Australia Bureau of Statistics and Brisbane City Council, respectively. Both polynomial distributed lag (PDL) time-series regression and seasonal auto-regressive integrated moving average (SARIMA) models were used to examine associations of RRV transmission with rainfall and mosquito density after adjustment for seasonality and auto-correlation. The results show that 85% and 95% of the variance in the RRV transmission was accounted for by rainfall and mosquito density, respectively. Both rainfall and mosquito density were strong predictors of the RRV transmission in simple models. However, multivariate PDL models show that only mosquito density at lags of 0 and 1 month was significantly associated with the transmission of RRV disease. The SARIMA models show similar results. The findings of this study may facilitate the development of early warning systems for the control and prevention of this disease and other similar vector-borne diseases using local rainfall and/or vector data.

RAINFALL, MOSQUITO DENSITY AND THE TRANSMISSION OF ROSS RIVER VIRUS: A TIME SERIES FORECASTING MODEL

This paper attempted to develop an epidemic forecasting model using local data on rainfall and mosquito density to predict outbreaks of Ross River virus (RRV) disease in Brisbane, Australia. We obtained monthly data on the counts of RRV cases, monthly total rainfall, human population size and mosquito density (i.e., average number of mosquitoes trapped in all mosquito monitoring stations per month) between 1 November 1998 and 31 December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Australia Bureau of Statistics and Brisbane City Council, respectively. Both polynomial distributed lag (PDL) time-series regression and seasonal auto-regressive integrated moving average (SARIMA) models were used to examine associations of RRV transmission with rainfall and mosquito density after adjustment for seasonality and auto-correlation. The results show that 85% and 95% of the variance in the RRV transmission was accounted for by rainfall and mosquito density, respectively. Both rainfall and mosquito density were strong predictors of the RRV transmission in simple models. However, multivariate PDL models show that only mosquito density at lags of 0 and 1 month was significantly associated with the transmission of RRV disease. The SARIMA models show similar results. The findings of this study may facilitate the development of early warning systems for the control and prevention of this disease and other similar vector-borne diseases using local rainfall and/or vector data.

Ecological mechanisms that promote arbovirus survival: a mathematical model of Ross River virus transmission

Many assessments of host and vector competence for arboviruses focus on level and length of infectivity and ignore ecological mechanisms that contribute to virus survival. In this paper, mathematical models are used to compare local survival mechanisms for a range of scenarios, using Ross River virus as a case study. Ross River virus is an Australian arbovirus with many mosquito vectors and reservoir hosts. The mechanisms for maintaining long-term transmission of the virus vary between salt and freshwater mosquito vectors, and according to the availability of susceptible hosts. The models demonstrate that overwintering of virus in adult freshwater mosquitoes requires a large host population, while overwintering of virus in infected eggs of saltwater mosquitoes is an effective survival strategy when filial infection rates are high. The virus survives longer when both salt and freshwater mosquito species are included in the model than when only one mosquito species is present. When the marsupial host is replaced by a host with higher birth rate and shorter infectious period, the virus survived longer under all models. This suggests that birth rate can be a key factor when assessing the competence of reservoir hosts to maintain virus transmission.

DEVELOPMENT OF A PREDICTIVE MODEL FOR ROSS RIVER VIRUS DISEASE IN BRISBANE, AUSTRALIA

This paper describes the development of an empirical model to forecast epidemics of Ross River virus (RRV) disease using the multivariate seasonal auto-regressive integrated moving average (SARIMA) technique in Brisbane, Australia. We obtained computerized data on notified RRV disease cases, climate, high tide, and population sizes in Brisbane for the period 1985-2001 from the Queensland Department of Health, the Australian Bureau of Meteorology, the Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model was developed and validated by dividing the data file into two data sets: the data between January 1985 and December 2000 were used to construct a model, and those between January and December 2001 to validate it. The SARIMA models show that monthly precipitation (beta = 0.004, P = 0.031) was significantly associated with RRV transmission. However, there was no significant association between other climate variables (e.g., temperature, relative humidity, and high tides) and RRV transmission. The predictive values in the model were generally consistent with actual values (root mean square percentage error = 0.94%). Therefore, this model may have applications as a decision supportive tool in disease control and risk-management planning programs.

Climate variability and Ross River virus transmission in Townsville Region, Australia, 1985-1996.

How climate variability affects the transmission of infectious diseases at a regional level remains unclear. We assess the impact of climate variation on the Ross River virus (RRv) transmission in the Townsville region, Queensland, north-east Australia. We obtained population-based information on monthly variations in RRv cases, climatic factors, sea level, and population growth between 1985 and 1996. Cross-correlations were computed for a series of associations between climate variables (rainfall, maximum temperature, minimum temperature, relative humidity and high tide) and the monthly incidence of RRv disease over a range of time lags. We assessed the impact of climate variability on RRv transmission using the seasonal auto-regressive integrated moving average (SARIMA) model. There were significant correlations of the monthly incidence of RRv to rainfall, maximum temperature, minimum temperature and relative humidity, all at a lag of 2 months, and high tide in the current month. The results of SARIMA models show that monthly average rainfall (beta = 0.0007, P = 0.01) and high tide (beta = 0.0089, P = 0.04) were significantly associated with RRv transmission and maximum temperature was also marginally significantly associated with monthly incidence of RRv (beta = 0.0412, P = 0.07), although relative humidity did not seem to have played an important role in the Townsville region. Rainfall, high tide and maximum temperature were likely to be key determinants of RRv transmission in the Townsville region.

ROSS RIVER VIRUS TRANSMISSION AND EL NIÑO-SOUTHERN-SOUTHERN OSCILLATION IN AUSTRALIA

This paper analyses the relationship between El Niño-Southern Osicillation (ENSO) events and Ross River virus (RRv) disease in different spatial scales (eg, local government areas, Queensland state and Australia). Information on RRv cases was supplied by the Queensland Department of Health (for the period of 1 January 1985–31 December 2001) and the Commonwealth Department of Health and Ageing (for the period of 1 January 1992–31 December 2001). Data on the ENSO were supplied by the Australian Bureau of Meteorology. Spearman's rank correlation analysis was conducted on the monthly ENSO and monthly incidence of RRv disease. The function of cross-correlation was used to show the correlation between ENSO and RRv disease at different time lags. No statistically significant relationship was found between the monthly index of ENSO and monthly incidence of RRv disease in whole Queensland (rs = −0.06; p = 0.40) and Australia (rs = −0.004; p = 0.69). However, there were significant relationships between ENSO and RRv disease in mid coastal areas, especially Mackay (rs = −0.20, p < 0.01) and Rockhampton (rs = −0.18, p < 0.05) in Queensland. The results of this study show that the ENSO was associated with RRv transmission in specific areas but not large geographic regions. The reasons for this will be explored in the paper.

Different responses of Ross River virus to climate variability between coastline and inland cities in Queensland, Australia

Aims: To examine the potential impact of climate variability on the transmission of Ross River virus (RRv) infection, and to assess the difference in the potential predictors of RRv incidence...

Climate Variation and Incidence of Ross River Virus in Cairns, Australia: A Time-Series Analysis

In this study we assessed the impact of climate variability on the Ross River virus (RRv) transmission and validated an epidemic-forecasting model in Cairns, Australia. Data on the RRv cases recorded between 1985 and 1996 were obtained from the Queensland Department of Health. Climate and population data were supplied by the Australian Bureau of Meteorology and the Australian Bureau of Statistics, respectively. The cross-correlation function (CCF) showed that maximum temperature in the current month and rainfall and relative humidity at a lag of 2 months were positively and significantly associated with the monthly incidence of RRv, whereas relative humidity at a lag of 5 months was inversely associated with the RRv transmission. We developed autoregressive integrated moving average (ARIMA) models on the data collected between 1985 to 1994, and then validated the models using the data collected between 1995 and 1996. The results show that the relative humidity at a lag of 5 months (p < 0.001) and the rainfall at a lag of 2 months (p < 0.05) appeared to play significant roles in the transmission of RRv disease in Cairns. Furthermore, the regressive forecast curves were consistent with the pattern of actual values.

Climate variation and incidence of Ross river virus in Cairns, Australia: a time-series analysis.

In this study we assessed the impact of climate variability on the Ross River virus (RRv) transmission and validated an epidemic-forecasting model in Cairns, Australia. Data on the RRv cases recorded between 1985 and 1996 were obtained from the Queensland Department of Health. Climate and population data were supplied by the Australian Bureau of Meteorology and the Australian Bureau of Statistics, respectively. The cross-correlation function (CCF) showed that maximum temperature in the current month and rainfall and relative humidity at a lag of 2 months were positively and significantly associated with the monthly incidence of RRv, whereas relative humidity at a lag of 5 months was inversely associated with the RRv transmission. We developed autoregressive integrated moving average (ARIMA) models on the data collected between 1985 to 1994, and then validated the models using the data collected between 1995 and 1996. The results show that the relative humidity at a lag of 5 months (p < 0.001) and the rainfall at a lag of 2 months (p < 0.05) appeared to play significant roles in the transmission of RRv disease in Cairns. Furthermore, the regressive forecast curves were consistent with the pattern of actual values.

Ross River virus transmission, infection, and disease: a cross-disciplinary review.

Ross River virus (RRV) is a fascinating, important arbovirus that is endemic and enzootic in Australia and Papua New Guinea and was epidemic in the South Pacific in 1979 and 1980. Infection with RRV may cause disease in humans, typically presenting as peripheral polyarthralgia or arthritis, sometimes with fever and rash. RRV disease notifications in Australia average 5,000 per year. The first well-described outbreak occurred in 1928. During World War II there were more outbreaks, and the name epidemic polyarthritis was applied. During a 1956 outbreak, epidemic polyarthritis was linked serologically to a group A arbovirus (Alphavirus). The virus was subsequently isolated from Aedes vigilax mosquitoes in 1963 and then from epidemic polyarthritis patients. We review the literature on the evolutionary biology of RRV, immune response to infection, pathogenesis, serologic diagnosis, disease manifestations, the extraordinary variety of vertebrate hosts, mosquito vectors, and transmission cycles, antibody prevalence, epidemiology of asymptomatic and symptomatic human infection, infection risks, and public health impact. RRV arthritis is due to joint infection, and treatment is currently based on empirical anti-inflammatory regimens. Further research on pathogenesis may improve understanding of the natural history of this disease and lead to new treatment strategies. The burden of morbidity is considerable, and the virus could spread to other countries. To justify and design preventive programs, we need accurate data on economic costs and better understanding of transmission and behavioral and environmental risks.

Investigation of gray-headed flying foxes (Pteropus poliocephalus) (Megachiroptera: Pteropodidae) and mosquitoes in the ecology of Ross River virus in Australia.

Entomologic and virologic factors were investigated to determine whether gray-headed flying foxes (Pteropus poliocephalus) from Indooroopilly Island, Brisbane, Australia could be vertebrate hosts of Ross River (RR) virus. Aedes funereus was the most abundant mosquito species with 6,300-38,700 females per light trap night in the flying fox camp containing gray-headed, black (P. alecto), and little red (P. scapulatus) flying foxes. Sixteen Ae. funereus blood meals from this collection were analyzed by hemoglobin electrophoresis and were found to be from P. alecto. From pledget feeding with RR virus, the infectious dose required to infect 50% of wild caught Ae. funereus was log10 4.2 50% tissue culture infectious doses per mosquito, with a transmission rate to mice of 17% at 9-10 days post infection. Experimental infection of 10 juvenile P. poliocephalus produced viremias of low titer in five animals, with a duration of 1-4 days and a mean of two days. Three percent of colonized Ae. vigilax that fed on the 10 animals during this period became infected. One of the five viremic flying foxes and two of the five aviremic animals produced a detectable immune response by either neutralization or hemagglutination-inhibition tests. Based on the low to moderate vector competence of Ae. funereus for RR virus, and evidence that P. poliocephalus is a poor vertebrate host of RR virus, it is unlikely that RR virus transmission would be maintained between these two species, but it could be maintained by other more competent vector/host pairs.