1000 resultados para Aracatuba virus
Resumo:
We describe a vaccinialike virus, Aragatuba virus, associated with a cowpoxlike outbreak in a dairy herd and a related case of human infection. Diagnosis was based on virus growth characteristics, electron microscopy, and molecular biology techniques. Molecular characterization of the virus was done by using polymerase chain reaction amplification, cloning, an DNA sequencing of conserved orthopoxvirus genes such as the vaccinia growth factor (VGF), thymidine kinase (TK), and hemagglutinin. We used VGF-homologous and TK gene nucleoticle sequences to construct a phylogenetic tree for comparison with other poxviruses. Gene sequences showed 99% homology with vaccinia virus genes and were clustered together with the isolated virus in the phylogenetic tree. Aragatuba virus is very similar to Cantagalo virus, showing the same signature deletion in the gene. Aragatuba virus could be a novel vaccinialike virus or could represent the spread of Cantagalo virus.
Resumo:
We describe a vaccinialike virus, Araçatuba virus, associated with a cowpoxlike outbreak in a dairy herd and a related case of human infection. Diagnosis was based on virus growth characteristics, electron microscopy, and molecular biology techniques. Molecular characterization of the virus was done by using polymerase chain reaction amplification, cloning, and DNA sequencing of conserved orthopoxvirus genes such as the vaccinia growth factor (VGF), thymidine kinase (TK), and hemagglutinin. We used VGF-homologous and TK gene nucleotide sequences to construct a phylogenetic tree for comparison with other poxviruses. Gene sequences showed 99% homology with vaccinia virus genes and were clustered together with the isolated virus in the phylogenetic tree. Araçatuba virus is very similar to Cantagalo virus, showing the same signature deletion in the gene. Araçatuba virus could be a novel vaccinialike virus or could represent the spread of Cantagalo virus.
Resumo:
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.
Rainfall, Mosquito Density and the Transmission of Ross River Virus: A Time-Series Forecasting Model
Resumo:
The spatial and temporal variations of Ross River virus infections reported in Queensland, Australia, between 1985 and 1996 were studied by using the Geographic Information System. The notified cases of Ross River virus infection came from 489 localities between 1985 and 1988, 805 between 1989 and 1992, and 1,157 between 1993 and 1996 (chi2(df = 2) = 680.9; P < 0.001). There was a marked increase in the number of localities where the cases were reported by 65 percent for the period of 1989-1992 and 137 percent for 1993-1996, compared with that for 1985-1988. The geographic distribution of the notified Ross River virus cases has expanded in Queensland over recent years. As Ross River virus disease has impacted considerably on tourism and industry, as well as on residents of affected areas, more research is required to explore the causes of the geographic expansion of the notified Ross River virus infections.
Resumo:
Australian mosquitoes from which Japanese encephalitis virus (JEV) has been recovered (Culex annulirostris, Culex gelidus, and Aedes vigilax) were assessed for their ability to be infected with the ChimeriVax-JE vaccine, with yellow fever vaccine virus 17D (YF 17D) from which the backbone of ChimeriVax-JE vaccine is derived and with JEV-Nakayama. None of the mosquitoes became infected after being fed orally with 6.1 log(10) plaque-forming units (PFU)/mL of ChimeriVax-JE vaccine, which is greater than the peak viremia in vaccinees (mean peak viremia = 4.8 PFU/mL, range = 0-30 PFU/mL of 0.9 days mean duration, range = 0-11 days). Some members of all three species of mosquito became infected when fed on JEV-Nakayama, but only Ae. vigilax was infected when fed on YF 17D. The results suggest that none of these three species of mosquito are likely to set up secondary cycles of transmission of ChimeriVax-JE in Australia after feeding on a viremic vaccinee.
Resumo:
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.