Seasonal variation in acute hospital admissions and emergency room presentations among children in the Australian Capital Territory.

AIM: To examine seasonal variation in hospital use for five paediatric conditions of the Australian Capital Territory residents. METHODS: Hospital admissions (1993-2004) and emergency room (ER) presentations (1999-2004) for asthma, croup, bronchiolitis, other respiratory conditions and diarrhoea of children aged <5 years were compared by month and season. RESULTS: The five conditions comprised 14% of admissions and 24% of ER presentations of children aged <5 years. Bronchiolitis (both admissions and ER presentations) were the highest in the 0-1 year age group (>80%) and the other four conditions peaked at 1-2 years. Children aged 0-2 years contributed 66% of diarrhoea, 62% of croup and 44% of other respiratory admissions whereas ER presentations were higher for other respiratory conditions (57%) and lower for croup (47%). Boys showed higher rates of admissions and ER presentations for all conditions except diarrhoea. Strong seasonal associations were apparent. Incident rate ratios of admissions were significantly higher in autumn compared with summer for asthma and croup whereas bronchiolitis and other respiratory conditions admissions were the highest in winter. Diarrhoea admissions were the highest in spring. ER presentations of the five conditions also showed similar associations with season. CONCLUSION: Hospital admissions and ER presentations of these five conditions showed strong seasonal patterns, knowledge of which could contribute to improved resource planning (staffing) to meet expected increases in demand for services and scheduling of elective admissions. These findings could be extended to develop a model for forecasting hospital use and to explore the causes of these diseases to ameliorate seasonal effects.

Early warning of Ross River virus epidemics: combining surveillance data on climate and mosquitoes.

BACKGROUND: Ross River virus disease is spread by mosquitoes, and an average of 5000 people are infected each year in Australia. It is one of the few infectious diseases for which climate-based early warning systems could be developed. The aim of this study was to test whether supplementing routinely collected climate data with mosquito surveillance data could increase the accuracy of disease prediction models. METHODS: We focused on a temperate region of Western Australia between July 1991 and June 1999. We developed "early" and "later" warning logistic regression models to test the sensitivity of data on climate (tide height, rainfall, sea surface temperature) and mosquito counts for predicting epidemics of disease. RESULTS: Climate data on their own were moderately sensitive (64%) for predicting epidemics during the early warning period. Addition of mosquito surveillance data increased the sensitivity of the early warning model to 90%. The later warning model had a sensitivity of 85%. CONCLUSIONS: We found that climate data are inexpensive and easy to collect and allow the prediction of Ross River virus disease epidemics within the time necessary to improve the effectiveness of public health responses. Mosquito surveillance data provide a more expensive early warning but add substantial predictive value.

An outbreak of Legionnaires' disease at the Melbourne Aquarium, April 2000: investigation and case-control studies.

OBJECTIVE: To investigate the source and risk factors associated with Australia's largest outbreak of Legionnaires' disease. DESIGN AND SETTING: Epidemiological and environmental investigation of cases of Legionnaires' disease associated with visits to the Melbourne Aquarium; two case-control studies to confirm the outbreak source and to investigate risk factors for infection, respectively. PARTICIPANTS: Patients with confirmed Legionnaires' disease who visited the Melbourne Aquarium between 11 and 27 April 2000 were compared (i) with control participants from the community, and (ii) with control participants selected from other visitors to the Aquarium during this period. MAIN OUTCOME MEASURES: Risk factors for acquiring Legionnaires' disease. RESULTS: There were 125 confirmed cases of Legionnaires' disease caused by Legionella pneumophila serogroup 1 associated with the Aquarium; 76% of patients were hospitalised, and four (3.2%) died. The Aquarium cooling towers were contaminated with this organism. Visiting the Aquarium was significantly associated with disease (odds ratio [OR], 207; 95% CI, 73-630). The case-control study indicated that current smoking was a dose-dependent risk (multivariable OR for currently smoking > 70 cigarettes/week, 13.5; 95% CI, 5-36), but chronic illness and duration of exposure at the site were not significant risks. CONCLUSIONS: This study showed an association between poorly disinfected cooling towers at the Aquarium and Legionnaires' disease in visitors, and confirmed current smoking as a critical risk factor. The rapid response, publicity, and widespread urinary antigen testing may have resulted in detection of milder cases and contributed to the relatively low apparent morbidity and mortality rates. The urinary antigen test allows rapid identification of cases and may be changing the severity of illness recognised as Legionnaires' disease and altering who is considered at risk.

Predicting Ross River virus epidemics from regional weather data.

BACKGROUND: Diseases caused by arboviruses cause extensive mortality and morbidity throughout the world. Weather directly affects the breeding, abundance, and survival of mosquitoes, the principal vector of many arboviruses. The goal of this study was to test whether climate variables could predict with high levels of accuracy (more than 70%) epidemics of one arbovirus, Ross River virus disease. METHODS: Weather data from two regions in southeastern Australia were matched with Ross River virus disease data for the period 1991 to 1999. Our aim was to develop simple models for the probability of the occurrence of an epidemic in an area in a given year. RESULTS: Two predictable epidemic patterns emerged, after either high summer rainfalls or high winter rainfalls. A prerequisite relating to host-virus dynamics was lower than average spring rainfall in the preepidemic year. The sensitivity of the model was 96% for Region 1 and 73% for Region 2. CONCLUSIONS: Early warning of weather conditions conducive to outbreaks of Ross River virus disease is possible at the regional level with a high degree of accuracy. Our models may have application as a decision tool for health authorities to use in risk-management planning.