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Background Vaccination against influenza may reduce antibiotic use, but data are limited and imprecise. Methods We conducted a case-control study using deidentified data from a large national primary care database to evaluate antibiotic prescribing changes following influenza vaccination in children 1-4 years old attending primary care in the Australian 2018 and 2019 influenza seasons. Cases were prescribed β-lactam or macrolide antibiotics during the influenza season and controls were not. Influenza vaccination was documented in the medical records. Adjusted odds ratios for antibiotic prescribing according to influenza vaccination status were estimated using generalized estimating equations, controlling for age, asthma diagnosis, other vaccinations, practice visit frequency, and attendance week. Results In 2018, 11 282 cases and 32 020 controls were eligible, and in 2019, 12 705 cases and 36 858 controls. Antibiotic prescriptions were less likely in vaccinated participants in 2018 (aOR, 0.65; 95% CI, 0.62-0.69) and 2019 (aOR, 0.78; 95% CI, 0.73-0.82) and did not vary by age, the number of GP visits, or prior prescribing of antibiotics. In the subgroup of children vaccinated in the preceding season, influenza vaccination was not associated with a reduction in antibiotic use (2018—aOR, 1.12; 95% CI, 0.90-1.39; 2019—aOR, 1.30; 95% CI, 1.16-1.46). From our estimates, potentially 100 000 antibiotic prescriptions could be avoided annually in Australia if all children in this age range were vaccinated. Conclusions Influenza vaccination may substantially reduce antibiotic prescribing among young children. This effect should be considered in the overall assessment of the costs and benefits of childhood influenza vaccination programs.

Objectives The aim of this study was to estimate delay-adjusted case fatality rates (CFRs) for COVID-19 in South Korea, and evaluate how these estimates have evolved over time throughout the epidemic. Methods Public data from the Korea Centers for Disease Control and Prevention (KCDC) were used to estimate age- and sex-specific CFRs for COVID-19 in South Korea up to June 12, 2020. We applied statistical methods previously developed to adjust for the delay between diagnosis and death, and presented both delay-adjusted and crude (unadjusted) CFRs throughout the epidemic. Results The overall estimated delay-adjusted CFR was 2.39% (3.05% for males and 1.92% for females). Within each age strata where deaths were reported, males were found to have significantly higher CFRs than females. The estimated CFRs increased substantially from age 60 years in males and from 70 years in females. Both the delay-adjusted and crude CFRs were found to have evolved substantially, particularly early in the epidemic, converging only from mid-April 2020. Conclusions The CFRs for South Korea provide an estimate of mortality risk in a setting where case ascertainment is likely to be more complete. The evolution in CFRs throughout the epidemic highlights the need for caution when interpreting CFRs calculated at a given time point.

BackgroundThe presymptomatic transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been documented in limited clusters, and it is predicted through modelling. However, there is a lack of evidence from observations with a large sample size.MethodsWe used data from meticulous contact tracing of people exposed to cases of SARS-CoV-2 to estimate the proportion of cases that result from the presymptomatic transmission of the virus in Beijing during January 2020 and February 2020.ResultsThe results showed that presymptomatic transmission occurred in at least 15% of 100 secondary COVID-19 cases. The earliest presymptomatic contact event occurred 5 days prior to the index case’s onset of symptoms, and this occurred in two clusters.ConclusionsThe finding suggested that the contact tracing period should be earlier and highlighted the importance of preventing transmission opportunities well before the onset of symptoms.

We developed a model to predict the cyclic pattern of porcine reproductive and respiratory syndrome virus (PRRSV) RNA detection by reverse-transcription real-time PCR (RT-rtPCR) from 4 major swine-centric veterinary diagnostic laboratories (VDLs) in the United States and to use historical data to forecast the upcoming year’s weekly percentage of positive submissions and issue outbreak signals when the pattern of detection was not as expected. Standardized submission data and test results were used. Historical data (2015–2017) composed of the weekly percentage of PCR-positive submissions were used to fit a cyclic robust regression model. The findings were used to forecast the expected weekly percentage of PCR-positive submissions, with a 95% confidence interval (CI), for 2018. During 2018, the proportion of PRRSV-positive submissions crossed 95% CI boundaries at week 2, 14–25, and 48. The relatively higher detection on week 2 and 48 were mostly from submissions containing samples from wean-to-market pigs, and for week 14–25 originated mostly from samples from adult/sow farms. There was a recurring yearly pattern of detection, wherein an increased proportion of PRRSV RNA detection in submissions originating from wean-to-finish farms was followed by increased detection in samples from adult/sow farms. Results from the model described herein confirm the seasonal cyclic pattern of PRRSV detection using test results consolidated from 4 VDLs. Wave crests occurred consistently during winter, and wave troughs occurred consistently during the summer months. Our model was able to correctly identify statistically significant outbreak signals in PRRSV RNA detection at 3 instances during 2018.

OBJECTIVE This study aims to present overall survival rates to hospital discharge for out-of-hospital cardiac arrest (OHCA) in Tasmania and to identify predictors of survival. METHODS A retrospective observational cohort study was undertaken from 1 January 2010 to 31 December 2014. A probabilistically linked data set was created from paramedic electronic medical records and hospital patient records. Logistic regression was used to assess factors associated with survival of OHCA. RESULTS During the study, 2949 incidents of OHCA were reviewed and 1146 had emergency management provided, with an overall survival rate to hospital discharge of 135 (12%). A number of independent factors are associated with improved outcomes including if the initial presenting cardiac rhythm was either ventricular fibrillation or ventricular tachycardia (adjusted odds ratio [OR] 8.75, 95% confidence interval [CI] 5.15-14.89) (P

Background Benchmarks are needed for assessing the severity of the COVID-19 pandemic. However, comparisons can be misleading unless marked differences in age-specific mortality and differences in population age structure are considered. Methods Using COVID-19 death rates for New York City as at 2 June 2020, we used indirect age standardization to estimate standardized mortality ratios (SMR) for the first winter waves of the 1918 and 2009 influenza pandemics and the severe 2017-2018 influenza season in the United States (US). Data were obtained from published statistics. Results After adjusting for age, New York City’s death rate during the 1918 winter influenza pandemic wave was 6.7 times higher overall compared with the first wave of COVID-19 in 2020. New York City's first wave COVID-19 death rate was an estimated 59 times higher than that of the 2009 US influenza pandemic, and 14 times higher than that of the severe 2017-2018 influenza season. In Conclusions The 1918 pandemic was more deadly than COVID-19, which was, in turn, far more deadly than both the 2009 influenza pandemic and severe seasonal influenza. Age-specific mortality differences should be considered in decisions on COVID-19 vaccination strategies. Key messages Fundamental epidemiological methods remain valuable for modern epidemic risk assessment. COVID-19 is not just a ‘flu’.

Background Asthma affects approximately 11% of Australia’s population and allergic rhinitis 19%. Grass pollen is associated with asthma and allergic rhinitis exacerbations. This study tested the hypothesis that days with extreme numbers of general practice (GP) encounters for asthma and allergic rhinitis aligned with grass pollen season. Methods The MedicineInsight GP database contains longitudinal data on persons attending a sample of Australian GPs. We created time series of daily counts of asthma and allergic rhinitis encounters by state and territory to identify extreme encounter days; days with counts above the 99th percentile. Results Of 3,036,678 attendances during the study period, 2.4% were for asthma. There were 83 extreme encounter days during April to December, across Australia. Victoria and South Australia had the highest increase in attendances on extreme days. Allergic rhinitis encounters represented 0.9% of attendances. Of the 69 extreme allergic rhinitis encounter days across Australia, Victoria and Australian Capital Territory had the highest increase in attendances. Allergic rhinitis extreme days were clustered between mid-October and early December (72%), compared to 22% of the asthma extreme days. Conclusions Extreme asthma GP encounters were not as strongly associated with grass pollen season compared to allergic rhinitis encounters. Victoria had a high number of encounters on asthma and allergic rhinitis extreme days, many associated with thunderstorm asthma. Key messages Extreme asthma encounter days can be associated with cooler months, grass pollen season and school holidays. Extremes allergic rhinitis presentation days were aligned with grass pollen season.

INTRODUCTION In Australia, the 2017 and 2019 influenza seasons were severe. High-dose or adjuvanted vaccines were introduced for ≥65 year-olds in 2018. AIM To compare influenza-associated mortality in 2017 and 2019 with the average for 2010-2019. METHODS We used time series modelling to obtain estimates of influenza-associated death rates for influenza A(H1N1)pdm09, A(H3N2) and B in Australia, in persons of all ages and

Objective Programmes that reduce the time to defibrillation are likely to improve overall survival rates from out-of-hospital cardiac arrests (OHCAs). This research sought to identify human factors common among community responders taking an automated external defibrillator (AED) to a victim of an OHCA that are either barriers or enablers of desired behaviour. Methods A qualitative methodology was used. Community members who had access to an AED and who had been notified of an incident of OHCA near them were approached to participate in the research. Participants completed a written survey and undertook a semi-structured interview. A thematic analysis was undertaken using NVivo software and triangulated against findings from an automated data-mining package, Leximancer. Results The study found that 100% of people who were notified of the need for an AED responded. Twelve participants subsequently identified during interviews that they held some form of leadership role in their community. First aid training and previous experience of, and competency in managing emergencies were the strongest motivations for their response. Personal risk was not a concern when responding to victims in immediately life-threatening situations. Conclusion Prospective programmes may be able to be designed to increase the likelihood that community members with AEDs will respond in advance of emergency medical services by targeting common human factors, such as leadership behaviour, training, competency and experience in managing emergencies, leading to better overall survival rates from OHCA.

Purpose: The burden of influenza on primary health-care services is not well established in tropical countries, where there are no clearly defined influenza seasons. We aimed to estimate the association between influenza infection activity and polyclinic attendance rates for upper respiratory tract infections (URTIs) in the Singapore population. Methods: We used generalized additive time series models to estimate the association between the proportion of respiratory tests positive for influenza infection in Singapore reported to the World Health Organization every week, and the population rate of polyclinic attendances in Singapore for physician-diagnosed URTI, which includes influenza-like illness (ILI), for six years from 2012 through 2017. Where data were available, we controlled for other infections that can cause fever or respiratory symptoms. Results: Influenza, dengue fever and chickenpox (varicella) were positively associated with acute URTI polyclinic attendances. The estimated URTI polyclinic attendance rates attributable to influenza, dengue fever and chickenpox were 618.9 (95% confidence interval [CI]: 501.6–736.3), 153.3 (95% CI: 16.5–290.2) and 1751.5 (95% CI: 1246.3–2256.8) per 100 000 population per year, respectively. Conclusions: Influenza poses a considerable burden on primary health-care services in Singapore. However, a substantial number of polyclinic attendances due to febrile infections such as dengue fever and chickenpox appear to be recorded as URTI in the polyclinic database. These associations require further investigation.

Objective To examine the impact of parental international migration on health care seeking for common childhood illnesses (diarrhoea, fever, and acute respiratory infections) and nutritional status (stunting, underweight and wasting) in young children in Nepal using the most recent nationally representative Multiple Indicator Cluster Survey. Study design Nationally representative cross-sectional survey. Methods We used multiple logistic regression models to examine the association between parental international migration and the study outcomes adjusting for a range of potential confounders. Results Of 5310 children, 23.5% had at least one parent living abroad. Health care for common childhood illnesses was sought for 52.1% (95% confidence interval [CI]: 45.0%–59.2%) and 47.0% (95% CI: 42.7%–51.1%) of children from migrant and non-migrant families, respectively. The prevalence of stunting, underweight and wasting among left-behind children were 35.3% (95% CI: 31.5%–39.1%), 28.3% (95% CI: 24.2%–32.2%) and 11.8% (95% CI: 8.8%–14.7%), respectively. In adjusted analyses, there were no statistically significant differences in health care seeking or nutritional status by parent's migration status. Conclusions Despite large economic benefits to Nepal due to international labour migration, we did not observe any apparent differences in young left-behind children in terms of seeking health care for common childhood illnesses or prevalence of under-nutrition. Longitudinal studies are needed to accurately measure whether migration has any substantial temporal effect on the nutritional status of young children or seeking for health care.

Background Influenza continues to cause seasonal epidemics and pandemics in humans. The burden of influenza is underestimated by traditional laboratory-based surveillance, and modelled estimates are required for influenza-attributable morbidity and mortality. We aimed to estimate the influenza-attributable hospitalisation in Australia, by influenza type. Methods A generalised-additive regression model was used to estimate type- and age-specific influenza-attributable hospitalisation rates per 100,000 population by principal diagnosis in Australia, from 2001 through 2013. Weekly counts of laboratory-confirmed influenza notifications and by type, influenza A and B were used as covariates in the model. Main principal diagnosis categories of interest were influenza and pneumonia and respiratory admissions. A smoothing spline was used to control for unmeasured time varying factors. Results for 2009, in which the pandemic influenza A(H1N1)pdm09 virus circulated, were not included in annual averages and are reported separately. Results During the study period, the estimated annual average, all-age, annual respiratory hospitalisation rates attributable to seasonal influenza type A, B and total influenza were 45.4 (95% CI: 34.9, 55.9), 32.6 (95% CI: 22.8, 42.4), and 76.9 (95% CI: 73.6, 80.2) per 100,000 population, respectively. During 2009, the estimated total pandemic influenza-attributable, all-age, respiratory hospitalisation rate was 56.1 (95% CI: 47.4, 64.9) per 100,000. Older adults (≥85 years of age) experienced the highest influenza-attributable hospitalisation rates for both seasonal and 2009 pandemic influenza. Collinearity between influenza A and B time series in some years limited the ability of the model to resolve differences in influenza attribution between the two virus types. Conclusion Both seasonal and pandemic influenza caused considerable morbidity in Australia during the years studied, particularly among older adults. The pandemic hospitalisation rate in 2009 was lower than the average overall annual rate for seasonal influenza, but young to middle aged adults experience a hospitalisation rate similar to that of severe seasonal influenza.

We aimed to examine the available evidence on the impact of overseas parental migration on healthcare seeking for common childhood illnesses and the nutritional status of children left-behind under five years of age. A systematic review of English language articles was conducted on PubMed, MEDLINE and EMBASE, supplemented by a manual search of grey literature and reference lists. There were no studies examining the association between overseas parental migration and healthcare seeking for common childhood illnesses. We found three cross-sectional surveys examining the association with an indicator of nutritional status. We observed mixed findings from the available studies. The results indicated that children left-behind may have positive, negative or null effects on their nutritional status. There was insufficient information available to draw conclusions on the magnitude and direction of the association between overseas parental migration and its effect on either healthcare seeking for common childhood illnesses or the nutritional status of left-behind children. The association, if any, may be context or country dependent. Prospective studies are needed to address this important knowledge gap.

BACKGROUND Seasonal influenza is responsible for a large disease and economic burden. Despite the expanding recommendation of influenza vaccination, influenza has continued to be a major public health concern in the United States (U.S.). To evaluate influenza prevention strategies it is important that policy makers have current estimates of the economic burden of influenza. OBJECTIVE To provide an updated estimate of the average annual economic burden of seasonal influenza in the U.S. population in the presence of vaccination efforts. METHODS We evaluated estimates of age-specific influenza-attributable outcomes (ill-non medically attended, office-based outpatient visit, emergency department visits, hospitalizations and death) and associated productivity loss. Health outcome rates were applied to the 2015 U.S. population and multiplied by the relevant estimated unit costs for each outcome. We evaluated both direct healthcare costs and indirect costs (absenteeism from paid employment) reporting results from both a healthcare system and societal perspective. Results were presented in five age groups (

Studies conducted during the 2009 influenza A (H1N1) pandemic found that obesity increases the risk of severe influenza including hospitalization and death. In this study, we examined the relationship of BMI with having laboratory-confirmed seasonal influenza and influenza-related respiratory hospitalization. We linked a cohort of 246,494 adults aged ≥45 years with data on BMI to subsequent laboratory-confirmed influenza notifications and cause-specific hospitalizations from 2006 to 2015. Cox-proportional hazard models were used to estimate the risk of incident laboratory-confirmed influenza and influenza-related respiratory hospitalizations according to BMI, adjusting for age, sex and other covariates. After 1,840,408 person-years of follow-up, 1891 participants had laboratory-confirmed influenza notifications (crude rate 10.3/10,000 person-years) of whom 623 were hospitalized for a respiratory illness. Compared to those with healthy BMI (22.5 to

Objectives Alcohol misuse is a complex systemic problem. The aim of this study was to explore the feasibility of using a transparent and participatory agent-based modelling approach to develop a robust decision support tool to test alcohol policy scenarios before they are implemented in the real world. Methods A consortium of Australia’s leading alcohol experts was engaged to collaboratively develop an agent-based model of alcohol consumption behaviour and related harms. As a case study, four policy scenarios were examined. Results A 19.5 ± 2.5% reduction in acute alcohol-related harms was estimated with the implementation of a 3 a.m. licensed venue closing time plus 1 a.m. lockout; and a 9 ± 2.6% reduction in incidence was estimated with expansion of treatment services to reach 20% of heavy drinkers. Combining the two scenarios produced a 33.3 ± 2.7% reduction in the incidence of acute alcohol-related harms, suggesting a synergistic effect. Conclusions This study demonstrates the feasibility of participatory development of a contextually relevant computer simulation model of alcohol-related harms and highlights the value of the approach in identifying potential policy responses that best leverage limited resources. Electronic supplementary material The online version of this article (doi:10.1007/s00038-017-1041-y) contains supplementary material, which is available to authorized users.

Objectives: Influenza’s impact on health and health care is under-estimated by influenza diagnoses recorded in health care databases. We aimed to estimate total and non-admitted influenza-attributable hospital Emergency Department demand in New South Wales (NSW), Australia. Methods: We used time series analysis of ~11 million presentations recorded in the NSW Emergency Department Data Collection to estimate rates, numbers and proportions of total and non-admitted Emergency Department presentations demand in New South Wales (NSW), Australia during 2010 through 2014. Laboratory confirmed influenza infections notified in NSW was used as a marker of influenza activity in the model. Results: The average estimated annual influenza-attributable respiratory presentation rate was 120.6 (99.9% confidence interval [CI] 102.3-138.8)/100,000 population, representing 8,887 (99.9% CI 7,548 – 10,227) presentations per year. For infection presentations, the annual average was 79.7 (99.9% CI 70.6-88.9)/100,000 (5,856 [99.9% CI 5,192-6,519] presentations). For cardiovascular presentations, the relationship with influenza was unclear. For all-cause presentations, the annual average was 309.0 (99.9% CI 208.0 – 410.1)/100,000 (22,619 [99.9% CI 15,268 – 29,969] presentations). Around 1 in 100 total presentations and more than 1 in 10 respiratory or infection presentations were associated with influenza. Conclusion: Influenza places a substantial and annually varying burden of hospital-attended illness on Emergency Departments. The greatest demand occurs among young children, and in the oldest population in some years. Influenza surveillance may assist in preparing for and managing influenza-associated peaks in Emergency Department demand, and improved control of influenza may substantially reduce surges in Emergency Department demand.

Objectives Influenza outbreaks cause overcrowding in EDs. We aimed to quantify the impact of influenza on the National Emergency Access Targets and premature patient departure in New South Wales, Australia. Methods This was a retrospective observational study of 11 million presentations to 115 hospitals during 2010–2014, using routinely collected administrative records. A time series generalised additive regression model was used to assess the correlation between weekly influenza activity and the weekly proportion of patients leaving the ED in >4 h and the proportion that departed before commencing or completing treatment (‘did not wait’), after controlling for background winter and holiday effects. Results During 2011–2014, peak annual circulating influenza was associated with the peak weekly proportion of presentations that left in >4 h. The maximum estimated absolute weekly change in that proportion was 3.88 (95% confidence interval 3.02–4.74) percentage points in 2014. For presentations that did not wait, influenza circulation was associated with statistically significant increases in all years, with a maximum weekly value of 2.68 (95% confidence interval 2.31–3.06) percentage points in 2012. Conclusions Circulating influenza was associated with sustained increases and peaks in delayed patient throughput and premature patient departures. Influenza surveillance information may assist with development of health system and hospital workforce planning and bed management activities.

Vaccination is the best available way to prevent influenza infections and related complications. Little information is available on vaccination policy in the world's most populous country, China. In China, influenza vaccine is not included in the national immunization programme. Citizens seek the vaccine on their own. Since 2007, Beijing, ahead of most cities in China, has offered free influenza vaccine for seniors aged at least 60 years and for primary and middle school students. There has been limited evaluation of the policy. We introduce and evaluate the government-funded influenza immunization policy in Beijing. Available data showed that the policy greatly increased the vaccine uptake rate in the population qualifying for free vaccination. Evidence of impact in a single influenza season on all high-risk populations was unclear. We suggest that further evaluation over multiple influenza seasons and in each high-risk group are required to inform future policy development in Beijing.

Background Vaccination is recommended to prevent influenza virus infection and associated complications. This study aimed to estimate the influenza vaccine effectiveness (VE) against hospitalization in the 2015/16 season in Beijing. Methods Patients who were hospitalized in the 5 study hospitals between 1 Oct 2015 and 15 May 2016 were recruited. Influenza vaccination status was obtained for PCR-confirmed influenza patients and the selected controls who tested negative for the virus. Conditional logistic regression was used to estimate the influenza VE matching by calendar week, and adjusting for age, study sites, underlying medical conditions, smoking status, and hospital admissions over the past 12 months. Results The overall VE was −37.9% (95% CI: −103.3, 6.5) against laboratory-confirmed influenza-associated hospitalization. The 2015–16 seasonal vaccine was had −61.9% (95% CI: −211.9, 15.9), −5.4% (95% CI: −108.1, 46.6) and −45.2% (95% CI: −152.6, 16.5) effectiveness to prevent infection from A(H1N1)pdm09, A(H3N2) and influenza B, respectively. Conclusions Influenza vaccination did not show effective protection against hospitalization with influenza in 2015/16 season in Beijing.

Objectives To describe population based trends and clinical characteristics of injury related presentations to Emergency Departments (EDs). Design and setting A retrospective, descriptive analysis of de-identified linked ED data across New South Wales, Australia over five calendar years, from 2010 to 2014. Participants Patients were included in this analysis if they presented to an Emergency Department and had an injury related diagnosis. Injury severity was categorised into critical (triage category 1–2 and admitted to ICU or operating theatre, or died in ED), serious (admitted as an in-patient, excluding above critical injuries) and minor injuries (discharged from ED). Main outcome measures The outcomes of interest were rates of injury related presentations to EDs by age groups and injury severity. Results A total of 2.09 million injury related ED presentations were analysed. Minor injuries comprised 85.0%, and 14.1% and 1.0% were serious and critical injuries respectively. There was a 15.8% per annum increase in the rate of critical injuries per 1000 population in those 80 years and over, with the most common diagnosis being head injuries. Around 40% of those with critical injuries presented directly to a major trauma centre. Conclusion Critical injuries in the elderly have risen dramatically in recent years. A minority of critical injuries present directly to major trauma centres. Trauma service provision models need revision to ensure appropriate patient care. Injury surveillance is needed to understand the external causes of injury presenting to hospital.

We report 1,327 probable cases of dengue in Burkina Faso in 2016. Of 35 serum samples tested by a trioplex test, 19 were confirmed dengue virus (DENV)‒positive: 11 DENV-2, 6 DENV-3, 2 nontypeable, and 1 DENV-2/DENV-3 co-infection. Molecular testing should be conducted to correctly identify causative agents in this complex infectious disease landscape.

Objective Using the epidemic of influenza type A in 2016 in Australia, we demonstrated a simple but statistically sound adaptive method of automatically representing the spatial intensity and evolution of an influenza epidemic that could be applied to a laboratory surveillance count data stream that does not have a denominator. Introduction Surveillance of influenza epidemics is a priority for risk assessment and pandemic preparedness. Mapping epidemics can be challenging because influenza infections are incompletely ascertained, ascertainment can vary spatially, and often a denominator is not available. Rapid, more refined geographic or spatial intelligence could facilitate better preparedness and response. Methods Weekly counts of persons with laboratory confirmed influenza type A infections in Australia in 2016 were analysed by 86 sub-state geographical areas. Weekly standardised epidemic intensity was represented by a z-score calculated using the standard deviation of below-median counts in the previous 52 weeks. A geographic information system was used to present the epidemic progression. Results There were 79,628 notifications of influenza A infections included. Of these, 79,218 (99.5%) were allocated to a geographical area. The maps indicated areas of elevated epidemic intensity across Australia by week and area, that were consistent with the observed start, peak and decline of the epidemic when compared with weekly counts aggregated at the state and territory level. An example is shown in Figure 1. Conclusions The methods could be automated to rapidly generate spatially varying epidemic intensity maps using a surveillance data stream. This could improve local level epidemic intelligence in a variety of settings and for other diseases. It may also increase our understanding of geographic epidemic dynamics.

BACKGROUND Although oil-in-water adjuvants improve pandemic influenza vaccine efficacy, AS03 versus MF59 adjuvant comparisons in A(H1N1)pdm09 pandemic vaccines are lacking. METHODS We conducted an indirect-comparison meta-analysis extracting published data from randomised controlled trials in literature databases (01/01/2009-09/09/2018), evaluating immunogenicity and safety of AS03- or MF59-adjuvanted vaccines. We conducted comparisons of log-transformed haemagglutination inhibition geometric mean titre ratio (GMTR; primary outcome) of different regimens of each adjuvant versus unadjuvanted counterparts. Then via test of subgroup differences, we indirectly compared different AS03 versus MF59 regimens. RESULTS We identified 22 publications with 10,734 participants. In adults, AS03-adjuvanted vaccines (3.75 µg haemagglutinin) achieved superior GMTR versus unadjuvanted vaccines (all four comparisons); MD = 0.56 (95%CI 0.33 to 0.80, p

Surveillance of influenza epidemics is a priority for risk assessment and pandemic preparedness, yet representation of their spatiotemporal intensity remains limited. Using the epidemic of influenza type A in 2016 in Australia, we demonstrated a simple but statistically sound adaptive method of mapping epidemic evolution over space and time. Weekly counts of persons with laboratory confirmed influenza type A infections in Australia in 2016 were analysed by official national statistical region. Weekly standardised epidemic intensity was represented by a standard score (z-score) calculated using the standard deviation of below-median counts in the previous 52 weeks. A geographic information system (GIS) was used to present the epidemic progression. There were 79,628 notifications of influenza A infections included. Of these, 79,218 (99.5%) were allocated to a geographical area. The GIS maps indicated areas of elevated epidemic intensity across Australia by week and area that were consistent with the observed start, peak and decline of the epidemic when compared with counts aggregated at the state and territory level. This simple, adaptable approach could improve local level epidemic intelligence in a variety of settings and for other diseases. It may also facilitate increased understanding of geographic epidemic dynamics.

Introduction and Aims Acute harm from heavy drinking episodes is an increasing focus of public health policy, but capturing timely data on acute harms in the population is challenging. This study aimed to evaluate the precision of readily available administrative emergency department (ED) data in public health surveillance of acute alcohol harms. Design and Methods We selected a random sample of 1000 ED presentations assigned an ED diagnosis code for alcohol harms (the ‘alcohol syndrome’) in the New South Wales, Australia, automatic syndromic surveillance system. The sample was selected from 68 public hospitals during 2014. Nursing triage free-text fields were independently reviewed to confirm alcohol consumption and classify each presentation into either an ‘acute’ or ‘chronic’ harm. Positive predictive value (PPV) for acute harm was calculated, and predictors of acute harm presentations were estimated using logistic regression. Results The PPV of the alcohol syndrome for acute alcohol harm was 53.5%. Independent predictors of acute harm were ambulance arrival [adjusted odds ratio (aOR) = 3.4, 95% confidence interval (CI) 2.4–4.7], younger age (12–24 vs. 25–39 years: aOR = 3.4, 95% CI 2.2–5.3), not being admitted (aOR 2.2, 95% CI 1.5–3.2) and arriving between 10 pm and 5.59 am (aOR 2.1, 95% CI 1.5–2.8). PPV among 12 to 24-year-olds was 82%. Discussion and Conclusions The alcohol syndrome provides moderate precision as an indicator of acute alcohol harms presenting to the ED. Precision for monitoring acute harm in the population is improved by filtering the syndrome by the strongest independent predictors of acute alcohol harm presentations. [Whitlam G, Dinh M, Rodgers C, Muscatello DJ, McGuire R, Ryan T, Thackway S. Diagnosis-based emergency department alcohol harm surveillance: What can it tell us about acute alcohol harms at the population level? Drug Alcohol Rev 2016;35:693–701]

Background Influenza B is characterised by two antigenic lineages; B/Victoria and B/Yamagata. These lineages circulate together with influenza A during influenza seasons, with varying incidence from year to year and by geographic region. Objective To determine the epidemiology of influenza B relative to influenza A in Australia. Methods Laboratory-confirmed influenza notifications between 2001 and 2014 in Australia were obtained from the Australian National Notifiable Diseases Surveillance System. Results A total of 278,485 laboratory-confirmed influenza cases were notified during the study period; comprising influenza A (82.2%), B (17.1%), and ‘other and untyped’ (0.7%). The proportion of notifications that were influenza B was highest in 5-9 year-olds (27.5%) and lowest in persons aged 85 years and over (11.5%). Of all B notifications with lineage determined, 77.1% were B/Victoria and 22.9% were B/Yamagata infections. Mismatches between the dominant B lineage in a season and the trivalent vaccine B lineage occurred in over one-third of seasons during the study years. In general, influenza B notifications peaked later than influenza A notifications. Conclusion The proportion of circulating influenza B in Australia during 2001 to 2014 was slightly lower than the global average and was dominated by B Victoria. Compared with influenza A, influenza B infection was more common among older children and young adults and less common in the very elderly. Influenza B lineage mismatch with the trivalent vaccine occurred about one third of the time. This article is protected by copyright. All rights reserved.

The study aimed to analyze ambulance transportations to Emergency Departments (EDs) in New South Wales (NSW) and to identify temporal changes in demographics, acuity, and clinical diagnoses.This was a retrospective analysis of a population based registry of ED presentations in New South Wales. The NSW Emergency Department data collection (EDCC) collects patient level data on presentations to designated EDs across NSW. Patients that presented to EDs by ambulance between January 2010 and December 2014 were included. Patients dead on arrival, transferred from another hospital, or planned ED presentations were excluded.A total of 10.8 million ED attendances were identified of which 2.6 million (23%) were transported to ED by ambulance. The crude rate of ambulance transportations to EDs across all ages increased by 3.0% per annum over the five years with the highest rate observed in those 85 years and over (620.5 presentations per 1,000 population). There was an increase in the proportion of category 1 and 2 (life-threatening or potentially life-threatening) cases from 18.1% to 24.0%.Demand for ambulance services appears to be driven by older patients presenting with higher acuity problems. Alternative models of acute care for elderly patients need to be planned and implemented to address these changes.

Objective The objective of this study is to describe the trends and characteristics of short-term and frequent representations to EDs in New South Wales, Australia. Methods This was a retrospective analysis of a linked population-based registry of ED representations in New South Wales, conducted as part of the Demand for Emergency Services in Years 2010–2014 project. Trend analysis of unplanned representations to ED within 3 days of discharge from ED, readmission to an in-patient unit within 30 days of index in-patient admission from ED and demographic data and trends for frequent and very frequent ED presenters is discussed. Results A total of 10 798 797 ED presentations were identified from 4 188 283 individual patients. Within 1 year, 48.9% of ED presentations had a previous presentation, and 4.9% had represented within 3 days of a previous presentation. The readmission rate within 30 days was 2.8%, the proportion of frequent (representing 5212 [0.1%] individual patients) and very frequent representations (representing 1186 [0.03%] individual patients) were 1.7% and 1.0%, respectively. The overall rate of representations within 3 days has decreased from 5.1% in 2010 to 4.7% in 2014 (P

OBJECTIVE: This study aims to describe the general characteristics and data definitions used in a population-based data set of ED presentations in New South Wales (NSW), used to form the basis of future-trend analyses. METHODS: Retrospective analysis of the Emergency Department Data Collection registry, which provided clinical and demographic information of ED presentations across all EDs in NSW between 2010 and 2014. Presenting problems and ED diagnoses were classified using broad clinical categories including injury/musculoskeletal, respiratory, cardiovascular, ear nose and throat, and mental health. Presentations were linked by patient to allow for analysis of representations, and population data were obtained from the Australian Bureau of Statistics. RESULTS: There were 11.8 million presentations that were analysed from 150 EDs (80.6% of all EDs). The rate of ED presentations was highest in those aged 85 years and older and appears to increase across all age groups between 2010 and 2014. The most common ED diagnosis categories were injury/musculoskeletal (27.5%) followed by abdominal/gastrointestinal (12.3%), respiratory (9%) and cardiovascular (8%). Both the Systematised Nomenclature of Medicine Clinical Terms (66%) and the International Classification of Diseases (24%) were used to code ED diagnoses. CONCLUSIONS: The elderly population had the highest rate of ED attendances. The use of diverse diagnosis classifications and source information systems may present problems with further analysis. Patterns and characteristics of ED presentations in NSW were broadly consistent with those reported in other states in Australia. Language: en

Background: The Early Warning and Response System (EWARS) is Indonesia’s national syndromic and early warning surveillance system for the rapid detection of infectious diseases and outbreaks. We evaluated EWARS in the remote West Papua province of Indonesia. Methods: Structured telephone interviews were conducted with 11 key informants from West Papuan health services. EWARS data were analysed for usefulness of reporting. Results: Most respondents reported that EWARS is important and useful in improving early detection of outbreaks. The system has led to increased disease control coordination among health jurisdictional levels in the province. However, respondents noted that the limited number of districts involved in the system affected representativeness, and some stated that only about 30–35% of districts in each regency were involved and trained in EWARS reporting, partly owing to lack of a mobile telephone network. Barriers to complete reporting and response to alerts included limited human and funding resources for surveillance, lack of epidemiological training, and technical limitations imposed by limited internet and mobile communication infrastructure in this remote region. Conclusion: Great progress has been made in integrating West Papua into a nationally consistent disease and outbreak detection system. Strategies for addressing barriers resulting from remoteness, constrained human, funding and laboratory resources, lack of training, and limited internet and communications infrastructure are needed if EWARS in West Papua is to advance.

We analyzed surveillance data for 2 sentinel hospitals to estimate the influenza-associated severe acute respiratory infection hospitalization rate in Beijing, China. The rate was 39 and 37 per 100,000 persons during the 2014–15 and 2015–16 influenza seasons, respectively. Rates were highest for children

Background: Influenza causes serious illness requiring annual health system surge capacity, yet annual seasonal variation makes it difficult to forecast and plan for the severity of an upcoming season. Research shows that hospital and health system stakeholders indicate a preference for forecasting tools that are easy to use and understand to assist with surge capacity planning for influenza. Objective: This study aimed to develop a simple risk prediction tool, Flucast, to predict the severity of an emerging influenza season. Methods: Study data were obtained from the National Notifiable Diseases Surveillance System and Australian Influenza Surveillance Reports from the Department of Health, Australia. We tested Flucast using retrospective seasonal data for 11 Australian influenza seasons. We compared five different models using parameters known early in the season that may be associated with the severity of the season. To calibrate the tool, the resulting estimates of seasonal severity were validated against independent reports of influenza-attributable morbidity and mortality. The model with the highest predictive accuracy against retrospective seasonal activity was chosen as a best-fit model to develop the Flucast tool. The tool was prospectively tested against the 2018 and the emerging 2019 influenza season. Results: The Flucast tool predicted the severity of all retrospectively studied years correctly for influenza seasonal activity in Australia. With the use of real-time data, the tool provided a reasonable early prediction of a low to moderate season for the 2018 and severe seasonal activity for the upcoming 2019 season. The tool meets stakeholder preferences for simplicity and ease of use to assist with surge capacity planning. Conclusions: The Flucast tool may be useful to inform future health system influenza preparedness planning, surge capacity, and intervention programs in real time, and can be adapted for different settings and geographic locations.

BACKGROUND Influenza causes serious illness requiring annual health system surge capacity, yet annual seasonal variation makes it difficult to forecast and plan for the severity of an upcoming season. Research shows that hospital and health system stakeholders indicated a preference of forecasting tools that are easy to use and understand, to assist with surge capacity planning for influenza. OBJECTIVE This study aimed to develop a simple risk prediction tool, Flucast, to predict the severity of an emerging influenza season. METHODS Study data were obtained from the National Notifiable Diseases Surveillance System and Australian Influenza Surveillance Reports, Department of Health, Australia. We tested Flucast using retrospective seasonal data for eleven Australian influenza seasons. We compared five different models, using parameters known early in the season and which may be associated with the severity of the season. To calibrate the tool, the resulting estimates of seasonal severity were validated against independent reports of influenza-attributable morbidity and mortality. A model with highest predictive accuracy against retrospective seasonal activity was chosen as a best fit model to develop the Flucast tool. The tool was prospectively tested against the emerging 2018 influenza season. RESULTS The Flucast tool predicted the severity of all retrospectively studied years correctly for influenza seasonal activity in Australia. For 2018, the tool provided a reliable early prediction of severe seasonal influenza with the use of real-time data. The tool meets stakeholder preferences for simplicity and ease of use to assist with surge capacity planning. CONCLUSIONS The Flucast tool may be useful to inform future health system influenza preparedness planning, surge capacity and intervention programs in real time and can be adapted for different settings and geographic locations. CLINICALTRIAL NA

Annual seasonal influenza vaccine manufacturing cycles align with temperate country seasonality in each hemisphere, yet influenza seasonality is poorly defined for many countries. The study introduces a novel and universal approach to defining and classifying seasonality that can be used to classify any country's influenza vaccine cycle alignment.Countries reporting to the World Health Organization's FluNet influenza virology database in 90% of weeks during 2011 through 2017 were included. A smoothed, standardised, average proportion of influenza occurring in each week of the year was used to determine degree of seasonality based on the range of average weekly variation. The proportion of activity occurring May through October was used to align influenza activity with a hemisphere's vaccine manufacturing cycle.From 84 included countries, there were 2,239,208 positive influenza results, of which 26% were influenza type B. Degree of seasonality was moderately positively correlated with absolute value of latitude (r = 0.69, p 0.0001). Latitude was strongly negatively correlated with the proportion of influenza occurring during May through October (r = -0.83, p 0.0001). Thirteen countries (12% of the included global population), mainly in tropical zones, had influenza occurrence aligned with the opposite hemisphere's influenza vaccine manufacturing cycle. In tropical zones, concordance in the degree of seasonality and vaccine cycle alignment within regions and between adjacent countries was limited. In temperate zones, on average, influenza B peaked four weeks later than A.Influenza activity in many countries aligns with the vaccine manufacturing cycle of the opposite hemisphere. In tropical regions, there is limited scope for grouping countries for vaccine distribution and administration.

Background The benefit of school-based influenza vaccination policy has not been fully addressed in Beijing. Objectives To evaluate the benefit of school-based influenza vaccination policy launched in Beijing. Methods Using existing surveillance and immunization data, we developed a dynamic transmission model to assess the impact of influenza vaccination in school-going children. The outcome was defined as the averted number of medically attended influenza illnesses and the prevented disease fraction to all children aged 5-14 years for the 2013/14, 2014/15, and 2015/16 seasons. Results We estimated that during the three consecutive influenza seasons, the averted number of medically attended influenza illnesses among children aged 5-14 years was around 104 000 (95% CI: 101 000-106 000), 23 000 (95% CI: 22 000-23 000), and 21 000 (95% CI: 21 000-22 000), respectively. Corresponding prevented fractions to all children aged 5-14 years were 76.3%, 38.5%, and 43.9%. Conclusions In Beijing, school-based vaccinations reduced a substantial number of medically attended influenza illnesses despite seasonal variation in the prevented fraction. This is strong supportive evidence for the continuation of school-based vaccination programs to reduce the influenza burden in this age group.

Background In 2010, influenza, influenza-like illness (ILI) and acute respiratory infection (ARI) surveillance was established by the government of Burkina Faso. We provide preliminary descriptive results from this surveillance activity. Methods The study period was 2013 through 2015. Two primary healthcare facilities in Bobo-Dioulasso district reported ILI in outpatients. Influenza virology, using reverse transcription-polymerase chain reaction (rRT-PCR), was available for a proportion of ILI patients. One hospital, in the capital Ouagadougou, reported ARI in both outpatients and inpatients (hospitalized). Inpatients admitted with ARI were considered severe ARI (SARI). We estimated the proportion of primary care outpatient visits that were ILI, and the proportion of those that were due to influenza, by age. We estimated the proportion of hospital outpatient visits that were ARI and the proportion of those that were SARI, by age. Results Among combined outpatient visits in the Bobo-Dioulasso facilities, 19.6% were for ILI. One half (49.9%) of outpatient visits in infants and 30.9% in 1–4 year-olds were ILI. Among ILI outpatient visits 14.8% were due to influenza virus and, of these, 58.5% were type A and 41.5% type B. At the Ouagadougou hospital, 6.7% of outpatient visits were ARI, and 22.3% of those were SARI. The highest proportions of ARI were among infants (19.8%) and 1–4 year-olds (16.0%). The proportion of ARI that was SARI was highest among ≥15 year-olds (31.5%) followed by 1–4 year-olds (22.4%). Overall, 4.1% of SARI patients died. Conclusions These preliminary data indicate the importance of respiratory infections among health care attendances in Burkina Faso, and influenza may be an important contributor to these.

Australia was one of the first countries to introduce nationally funded rotavirus vaccination. The program has had a substantial impact on both rotavirus and all-cause acute gastroenteritis (AGE) hospitalisations and rotavirus laboratory tests. Evidence for an impact on Emergency Department (ED) presentations is limited. This study assessed changes in ED presentations for rotavirus in children aged5 years in New South Wales, Australia, following introduction of monovalent human rotavirus vaccine (RV1, Rotarix(®), GlaxoSmithKline Australia Pty Ltd., Victoria, Australia).A time series analysis to examine trends in total non-admitted ED presentations for all-cause AGE and in the rotavirus-attributable fraction using data on rotavirus positive laboratory tests.A decline in the rate of non-admitted ED presentations for all-cause AGE was observed for all ages, being most notable in 1 year old children. Compared with the pre-vaccination period, we estimated the average weekly rate was lower across the first 4.5 years of the program for both all-cause AGE (18.3%; 70.5 versus 57.5 per 100,000 population) and rotavirus attributable (55.4%; 17.3 versus 7.7 per 100,000 population) presentations. In the fourth year of the program, estimated annual rotavirus attributable presentations were 77% lower than the pre-vaccination annual mean (996 versus 4300 per year).The program was associated with a substantial decline in rotavirus attributable non-admitted AGE presentations to ED among children aged5 years.

To contrast long-term population-based trends in general practice (GP) presentations and acute inpatient admissions from the emergency department (ED) in the elderly population within the Greater Sydney Area.This was a retrospective analysis of population-based ED presentation data over 11 years, between January 2001 and December 2011, conducted within the Greater Sydney Area in Australia. De-identified data were obtained from the New South Wales Emergency Department Data Collection database on all patients presenting to 30 public hospital EDs located within the Greater Sydney Area. The outcomes of interest were GP presentations to ED (triage category 4 or 5, self-referred and discharged from ED) and of acute inpatient admissions from ED per 1000 population.Over 11 million presentations were identified. Around 40% of presentations were classified as a GP presentation and 23% were classified as acute inpatient admissions. There was a 2.9% per annum increase in acute inpatient admissions per 1000 population in those ≥80 years of age and no appreciable change in other age groups. Rates of GP presentations were higher in those65 years of age. GP presentations increased 1.9% per annum in those aged65 years of age.The increase in ED demand appears to be driven by the elderly presenting with acute problems requiring inpatient admission. There has been a modest increase in the rate of GP presentations to ED.

Background Regression modeling methods are commonly used to estimate influenza-associated mortality using covariates such as laboratory-confirmed influenza activity in the population as a proxy of influenza incidence. Objective We examined the choices of influenza proxies that can be used from influenza laboratory surveillance data and their impact on influenza-associated mortality estimates. Method Semiparametric generalized additive models with a smoothing spline were applied on national mortality data from South Africa and influenza surveillance data as covariates to obtain influenza-associated mortality estimates from respiratory causes from 2009 to 2013. Proxies examined included alternative ways of expressing influenza laboratory surveillance data such as weekly or yearly proportion or rate of positive samples, using influenza subtypes, or total influenza data and expressing the data as influenza season-specific or across all seasons. Result Based on model fit, weekly proportion and influenza subtype-specific proxy formulation provided the best fit. The choice of proxies used gave large differences to mortality estimates, but the 95% confidence interval of these estimates overlaps. Conclusion Regardless of proxy chosen, mortality estimates produced may be broadly consistent and not statistically significant for public health practice.

Background The objective of the study was to describe an m-health initiative to strengthen malaria surveillance in a 184-health facility, multi-province, project aimed at strengthening the National Health Information System (NHIS) in a country with fragmented malaria surveillance, striving towards enhanced control, pre-elimination. Methods A remote-loading mobile application and secure online platform for health professionals was created to interface with the new system (eNHIS). A case-based malaria testing register was developed and integrated geo-coded households, villages and health facilities. A malaria programme management dashboard was created, with village-level malaria mapping tools, and statistical algorithms to identify malaria outbreaks. Results Since its inception in 2015, 160,750 malaria testing records, including village of residence, have been reported to the eNHIS. These case-based, geo-coded malaria data are 100% complete, with a median data entry delay of 9 days from the date of testing. The system maps malaria to the village level in near real-time as well as the availability of treatment and diagnostics to health facility level. Data aggregation, analysis, outbreak detection, and reporting are automated. Conclusions The study demonstrates that using mobile technologies and GIS in the capture and reporting of NHIS data in Papua New Guinea provides timely, high quality, geo-coded, case-based malaria data required for malaria elimination. The health systems strengthening approach of integrating malaria information management into the eNHIS optimizes sustainability and provides enormous flexibility to cater for future malaria programme needs.

Infectious disease dynamic modeling can support outbreak emergency responses. We conducted a workshop to canvas the needs of stakeholders in Australia for practical, real-time modeling tools for infectious disease emergencies. The workshop was attended by 29 participants who represented government, defense, general practice, and academia stakeholders. We found that modeling is underused in Australia and its potential is poorly understood by practitioners involved in epidemic responses. The development of better modeling tools is desired. Ideal modeling tools for operational use would be easy to use, clearly indicate underlying parameterization and assumptions, and assist with policy and decision making.

Objective To describe trends in population-based rates of ED presentations in the Greater Sydney Area (GSA) and compare these between the elderly and non-elderly age groups. Methods This was a retrospective study using ED presentation data from all public hospitals in the GSA and population data from the Australian Bureau of Statistics between 2001 and 2011. Age-specific ED presentation rates stratified by age group (

BACKGROUND: Disposition decisions are critical to the functioning of Emergency Departments. The objectives of the present study were to derive and internally validate a prediction model for inpatient admission from the Emergency Department to assist with triage, patient flow and clinical decision making. METHODS: This was a retrospective analysis of State-wide Emergency Department data in New South Wales, Australia. Adult patients (age ≥ 16 years) were included if they presented to a Level five or six (tertiary level) Emergency Department in New South Wales, Australia between 2013 and 2014. The outcome of interest was in-patient admission from the Emergency Department. This included all admissions to short stay and medical assessment units and being transferred out to another hospital. Analyses were performed using logistic regression. Discrimination was assessed using area under curve and derived risk scores were plotted to assess calibration. RESULTS: 1,721,294 presentations from twenty three Level five or six hospitals were analysed. Of these 49.38% were male and the mean (sd) age was 49.85 years (22.13). Level 6 hospitals accounted for 47.70% of cases and 40.74% of cases were classified as an in-patient admission based on their mode of separation. The final multivariable model including age, arrival by ambulance, triage category, previous admission and presenting problem had an AUC of 0.82 (95% CI 0.81, 0.82). CONCLUSION: By deriving and internally validating a risk score model to predict the need for in-patient admission based on basic demographic and triage characteristics, patient flow in ED, clinical decision making and overall quality of care may be improved. Further studies are now required to establish clinical effectiveness of this risk score model.

OBJECTIVE The objective of the present study is to demonstrate a novel method of mapping ED activity to analyse patterns presentations, occupancy and performance trends. METHODS This was a retrospective, descriptive analysis of de-identified and linked ED presentations across NSW, Australia, over five calendar years, 2010-2014. It was undertaken as part of the Demand for Emergency Services Trend in Years 2010-2014 (DESTINY) study. The DESTINY project analysed 10.8 million presentations during 2010-2014. Hourly Emergency Activity Tracking (HEAT) maps were generated to visually represent and analyse the number of emergency arrivals to ED occupancy and proportion of patients leaving the ED within 4 h per hour of day across consecutive months of the year. RESULTS HEAT maps provided a means of visually representing ED activity to demonstrate hour-to-hour trends in presentations, occupancy and performance between 2010 and 2014. This analysis has shown that the most marked increase in presentations per hour has occurred during the 10.00-14.00 hour period, associated with an improvement in ED performance during the same period. CONCLUSION HEAT maps may be used to facilitate further analyses of ED demand, patterns of patient presentations and patient flow and future health system redesign.

Background This study aims to examine factors associated with variation in crash-related hospitalization costs for young adults in New South Wales (NSW), Australia with a particular focus on types of vehicle occupant, rurality of residence and socioeconomic status (SES). Methods Data on patients aged 17–25 years, admitted to public hospitals due to a crash during July 2000–June 2007 were extracted from the NSW Health Admission Collection database. The hospitalization cost of each admission was calculated based on published charges for specific Australian Refined-Diagnosis Related Groups (AR-DRG). Multivariable analyses using generalized estimating equations were used to estimate costs by vehicle occupant type (driver, passenger and other occupants), rurality of residence (urban, regional and rural areas) and SES (low, moderate and high SES areas). Results During 2000–2007, there were 11,892 crash-related hospitalizations involving young adults, aged 17–25 years, in NSW. These cost the health sector about A$87.6 million or on average, A$7363 per hospitalization (mean length of stay (LOS) 5.3 days). Compared to drivers, passengers had significantly longer LOS (

Outbreaks of known and novel pathogens causing very severe illness increase the risk to public health in a globalised community and alarm the public Intensive care units (ICUs) may be an underused setting for public health surveillance. This study investigates the electronic Record for Intensive Care (eRIC), an electronic clinical information and management system being developed for New South Wales ICUs, and its surveillance opportunity offerings. The surveillance benefits being introduced by the eRIC were evaluated through consultation with stakeholders and the eRIC program team. The consultation process involved providing stakeholders with background information about the eRIC system. Based on the consultation, a draft data and information model for surveillance was developed. The model was evaluated using guidelines from the US Centers for Disease Control and Prevention. Population health stakeholders confirmed that the eRIC offers an appealing surveillance data source for pathogens and other hazards causing severe illness, the study found. Suggested application of the surveillance included, for known hazards, seasonal and pandemic influenza, enterovirus 71, Murray Valley encephalitis virus, enterohaemorrhagic Escherichia coli 0104:H4 and parechovirus. The proposed surveillance model uses syndromic rather than specific-cause surveillance. It may offer greater timeliness and sensitivity than relying on reporting of diagnoses of specific pathogens. Five syndromes derived from clinical pathways in the eRIC are proposed: severe acute respiratory disease, severe acute neurological disease, sepsis or septicaemia, jaundice or hepatitis, and acute renal failure. This paper concludes that the new intensive care clinical information systems offer a largely untapped resource for continuous, mainstream, rapid ICU surveillance of severe illness. A continuous, mainstream, rapid ICU surveillance facility that will readily adapt to emergency situations would be a valuable resource for protecting population health. The study establishes a firm basis on which ICU surveillance can be developed.