Data relating to acute post-streptococcal glomerulonephritis (APSGN) from the notifiable diseases surveillance system in the Northern Territory of Australia was extracted and analyzed. Isolates of Streptococcus pyogenes from confirmed cases were emm sequence typed. From 1991 to July 2008, there were 415 confirmed cases and 23 probable cases of APSGN notified. Four hundred fifteen (94.7%) of these were Indigenous Australians and 428 (97.7%) were people living in remote or very remote locations. The median age of cases was 7 years (range 0–54). The incidence of confirmed cases was 12.5/100,000 person-years, with an incidence in Indigenous Australian children younger than 15 years of age of 94.3 cases/100,000 person-years. The overall rate ratio of confirmed cases in Indigenous Australians to non-Indigenous Australians was 53.6 (95% confidence interval 32.6–94.8). Outbreaks of disease across multiple communities occurred in 1995 (N = 68), 2000 (N = 55), and 2005 (N = 87 [confirmed cases]). Various emm types of S. pyogenes were isolated from cases of APSGN including some types not previously recognized to be nephritogenic. The widespread outbreak in 2005 was caused by emm55.0 S. pyogenes. Acute post-streptococcal glomerulonephritis continues to occur in remote Indigenous communities in Australia at rates comparable to or higher than those estimated in developing countries. Improvements in preventative and outbreak control strategies are needed.
Summaryobjectives To describe the epidemiology of Ross River virus (RRV) infection in the endemic Darwin region of tropical northern Australia and to develop a predictive model for RRV infections.methods Analysis of laboratory confirmed cases of RRV infection between 01 January 1991 and 30 June 2006, together with climate, tidal and mosquito data collected weekly over the study period from 11 trap sites around Darwin. The epidemiology was described, correlations with various lag times were performed, followed by Poisson modelling to determine the best main effects model to predict RRV infection.results Ross River virus infection was reported equally in males and females in 1256 people over the 15.5 years. Average annual incidence was 113 ⁄ 100 000 people. Infections peaked in the 30-34 agegroup for both sexes. Correlations revealed strong associations between monthly RRV infections and climatic variables and also each of the four implicated mosquito species populations. Three models were created to identify the best predictors of RRV infections for the Darwin area. The climate-only model included total rainfall, average daily minimum temperature and maximum tide. This model explained 44.3% deviance. Using vector-only variables, the best fit was obtained with average monthly trap numbers of Culex annulirostris, Aedes phaecasiatus, Aedes notoscriptus and Aedes vigilax. This model explained 59.5% deviance. The best global model included rainfall, minimum temperature and three mosquito species. This model explained 63.5% deviance, and predicted disease accurately.conclusions We have produced a model that accurately predicts RRV infections throughout the year, in the Darwin region. Our model also indicates that predicted anthropogenic global climatic changes may result in an increase in RRV infections. Further research needs to target other high-risk areas elsewhere in tropical Australia to ascertain the best local climatic and vector predictive RRV infection models for each region. This methodology can also be tested for assessing utility of predictive models for other mosquito-borne diseases endemic to locations outside Australia.
Murray Valley encephalitis virus (MVEV) is the most serious of the endemic arboviruses in Australia. It was responsible for six known large outbreaks of encephalitis in south-eastern Australia in the 1900s, with the last comprising 58 cases in 1974. Since then MVEV clinical cases have been largely confined to the western and central parts of northern Australia.In 2011, high-level MVEV activity occurred in south-eastern Australia for the first time since 1974, accompanied by unusually heavy seasonal MVEV activity in northern Australia. This resulted in 17 confirmed cases of MVEV disease across Australia. Record wet season rainfall was recorded in many areas of Australia in the summer and autumn of 2011. This was associated with significant flooding and increased numbers of the mosquito vector and subsequent MVEV activity. This paper documents the outbreak and adds to our knowledge about disease outcomes, epidemiology of disease and the link between the MVEV activity and environmental factors.Clinical and demographic information from the 17 reported cases was obtained. Cases or family members were interviewed about their activities and location during the incubation period.In contrast to outbreaks prior to 2000, the majority of cases were non-Aboriginal adults, and almost half (40%) of the cases acquired MVEV outside their area of residence. All but two cases occurred in areas of known MVEV activity.This outbreak continues to reflect a change in the demographic pattern of human cases of encephalitic MVEV over the last 20 years. In northern Australia, this is associated with the increasing numbers of non-Aboriginal workers and tourists living and travelling in endemic and epidemic areas, and also identifies an association with activities that lead to high mosquito exposure. This outbreak demonstrates that there is an ongoing risk of MVEV encephalitis to the heavily populated areas of south-eastern Australia.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.