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Background: Meningococcal infection causes severe, rapidly progressing illness and reporting of cases is mandatory in New South Wales (NSW), Australia. The NSW Department of Health operates near real-time Emergency Department (ED) surveillance that includes capture and statistical analysis of clinical preliminary diagnoses. The system can provide alerts in response to specific diagnoses entered in the ED computer system. This study assessed whether once daily reporting of clinical diagnoses of meningococcal infection using the ED surveillance system provides an opportunity for timelier public health response for this disease. Methods: The study involved a prospective and retrospective component. First, reporting of ED diagnoses of meningococcal infection from the ED surveillance system prospectively operated in parallel with conventional surveillance which requires direct telephone reporting of this scheduled medical condition to local public health authorities by hospitals and laboratories when a meningococcal infection diagnosis is made. Follow-up of the ED diagnoses determined whether meningococcal infection was confirmed, and the time difference between ED surveillance report and notification by conventional means. Second, cases of meningococcal infection reported by conventional surveillance during 2004 were retrospectively matched to ED visits to determine the sensitivity and positive predictive value (PPV) of ED surveillance. Results: During the prospective evaluation, 31 patients were diagnosed with meningococcal infection in participating EDs. Of these, 12 had confirmed meningococcal disease, resulting in a PPV of 38.7%. All confirmed cases were notified earlier to public health authorities by conventional reporting. Of 149 cases of notified meningococcal disease identified retrospectively, 130 were linked to an ED visit. The sensitivity and PPV of the ED diagnosis for meningococcal infection was 36.2% and 36.7%, respectively. Conclusions: Based on prospective evaluation, it is reassuring that existing mechanisms for reporting meningococcal infection perform well and are timely. The retrospective evaluation found low sensitivity and PPV of ED diagnoses for meningococcal disease. Even if more rapid forwarding of ED meningococcal diagnoses to public health authorities were possible, the low sensitivity and PPV do not justify this. In this study, use of an ED surveillance system to augment conventional surveillance of this scheduled medical condition did not demonstrate a benefit. [ABSTRACT FROM AUTHOR]

Background: In April 2005, syndromic surveillance based on statistical control chart methods in Sydney, Australia, signalled increasing incidence of urgent emergency department visits for cardiovascular and chest pain syndromes compared to the preceding twelve months. This paper aimed to determine whether environmental factors could have been responsible for this 'outbreak'. Methods: The outcome studied was daily counts of emergency department visits for cardiovascular or chest pain syndromes that were considered immediately or imminently life threatening on arrival at hospital. The outbreak had a mean daily count of 5.7 visits sustained for eight weeks, compared with 4.0 in the same months in previous years. Poisson regression was used to systematically assess the emergency department visits in relation to available daily weather and pollution variables by first finding the best model that explained short-term variation in the outcome over the period 25 January 2002 to 31 May 2005, and then assessing interactions of all available variables with the 'outbreak' period, April-May 2005. Rate ratios were estimated for an interquartile increase in each variable meaning that the ratio measures the relative increase (or decrease) in the emergency department visits for an interquartile increase in the weather or pollution variable. The rate ratios for the outbreak period measure the relative increase (or decrease) in the emergency department visits for an interquartile increase in the weather or pollution variable during the outbreak period only. Results: The best fitting model over the whole study period included minimum temperature with a rate ratio (RR) of 0.86 (95% confidence interval (CI), 0.77-0.96), maximum relative humidity of 1.09 (95% CI 1.05-1.14) and minimum daily particulate matter less than 10 microns (PM10) of 1.05 (95% CI, 1.01-1.09). During the outbreak period, maximum temperature (RR 1.27, 95% CI 1.03-1.57), solar radiation (RR 1.44, 95% CI, 1.00-2.07) and ozone (RR 1.13, 95% CI 1.01-1.26) were associated with the outcome. Conclusion: The increase may have been associated with photochemical pollution. Syndromic surveillance can identify outbreaks of non-communicable diseases associated with environmental factors. [ABSTRACT FROM AUTHOR]

Background: In a climate of concern over bioterrorism threats and emergent diseases, public health authorities are trialling more timely surveillance systems. The 2003 Rugby World Cup (RWC) provided an opportunity to test the viability of a near real-time syndromic surveillance system in metropolitan Sydney, Australia. We describe the development and early results of this largely automated system that used data routinely collected in Emergency Departments (EDs). Methods: Twelve of 49 EDs in the Sydney metropolitan area automatically transmitted surveillance data from their existing information systems to a central database in near real-time. Information captured for each ED visit included patient demographic details, presenting problem and nursing assessment entered as free-text at triage time, physician-assigned provisional diagnosis codes, and status at departure from the ED. Both diagnoses from the EDs and triage text were used to assign syndrome categories. The text information was automatically classified into one or more of 26 syndrome categories using automated "naïve Bayes" text categorisation techniques. Automated processes were used to analyse both diagnosis and free text-based syndrome data and to produce web-based statistical summaries for daily review. An adjusted cumulative sum (cusum) was used to assess the statistical significance of trends. Results: During the RWC the system did not identify any major public health threats associated with the tournament, mass gatherings or the influx of visitors. This was consistent with evidence from other sources, although two known outbreaks were already in progress before the tournament. Limited baseline in early monitoring prevented the system from automatically identifying these ongoing outbreaks. Data capture was invisible to clinical staff in EDs and did not add to their workload. Conclusion: We have demonstrated the feasibility and potential utility of syndromic surveillance using routinely collected data from ED information systems. Key features of our system are its nil impact on clinical staff, and its use of statistical methods to assign syndrome categories based on clinical free text information. The system is ongoing, and has expanded to cover 30 EDs. Results of formal evaluations of both the technical efficiency and the public health impacts of the system will be described subsequently. [ABSTRACT FROM AUTHOR]