Using an Emergency Department Syndromic Surveillance System to investigate the impact of extreme cold weather events.

This report describes the development of novel syndromic cold weather public health surveillance indicators for use in monitoring the impact of extreme cold weather on attendances at EDs, using data from the 2010-11 and 2011-12 winters. A number of new surveillance indicators were created specifically for the identification and monitoring of cold weather related ED attendances, using the diagnosis codes provided for each attendance in the Emergency Department Syndromic Surveillance System (EDSSS), the first national syndromic surveillance system of its kind in the UK. Using daily weather data for the local area, a time series analysis to test the sensitivity of each indicator to cold weather was undertaken. Diagnosis codes relating to a health outcome with a potential direct link to cold weather were identified and assigned to a number of 'cold weather surveillance indicators'. The time series analyses indicated strong correlations between low temperatures and cold indicators in nearly every case. The strongest fit with temperature was cold related fractures in females, and that of snowfall was cold related fractures in both sexes. Though currently limited to a small number of sentinel EDs, the EDSSS has the ability to give near real-time detail on the magnitude of the impact of weather events. EDSSS cold weather surveillance fits well with the aims of the Cold Weather Plan for England, providing information on those particularly vulnerable to cold related health outcomes severe enough to require emergency care. This timely information aids those responding to and managing the effects on human health, both within the EDs themselves and in the community as a whole.

The impact of thunderstorm asthma on emergency department attendances across London during July 2013.

BACKGROUND: This study illustrates the potential of using emergency department attendance data, routinely accessed as part of a national syndromic surveillance system, to monitor the impact of thunderstorm asthma. METHODS: The Emergency Department Syndromic Surveillance System (EDSSS) routinely monitors anonymised attendance data on a daily basis across a sentinel network of 35 emergency departments. Attendance data for asthma, wheeze and difficulty breathing are analysed on a daily basis. RESULTS: A statistically significant spike in asthma attendances in two EDSSS emergency departments in London was detected on 23 July 2013, coinciding with a series of large violent thunderstorms across southern England. There was also an increase in the reported severity of these attendances. CONCLUSIONS: This preliminary report illustrates the potential of the EDSSS to monitor the impact of thunderstorms on emergency department asthma attendances. Further work will focus on how this system can be used to quantify the impact on emergency departments, thus potentially improving resource planning and also adding to the thunderstorm asthma evidence-base.

Using public health scenarios to predict the utility of a national syndromic surveillance programme during the 2012 London Olympic and Paralympic Games.

During 2012 real-time syndromic surveillance formed a key part of the daily public health surveillance for the London Olympic and Paralympic Games. It was vital that these systems were evaluated prior to the Games; in particular what types and scales of incidents could and could not be detected. Different public health scenarios were created covering a range of potential incidents that the Health Protection Agency would require syndromic surveillance to rapidly detect and monitor. For the scenarios considered it is now possible to determine what is likely to be detectable and how incidents are likely to present using the different syndromic systems. Small localized incidents involving food poisoning are most likely to be detected the next day via emergency department surveillance, while a new strain of influenza is more likely to be detected via GP or telephone helpline surveillance, several weeks after the first seed case is introduced.

Evaluation of a national microbiological surveillance system to inform automated outbreak detection.

OBJECTIVES: Evaluate data available from a national voluntary reporting system and describe the data processing necessary to enable the development and application of outbreak detection methods in healthcare settings. METHODS: Evaluation was performed on an extract of data reported between March 2007 and May 2012. Reporting delays were calculated and analysed at the trust, regional and national levels. Negative binomial regression analysis was performed to detect any changes in laboratory reporting within this time. RESULTS: 167 hospital laboratories have reported to the voluntary reporting system. 1,705,126 reports were made in the five-year study period. There is large variation in how laboratories report to the system. Under half (44.9%) report in a timely manner, with >90% of infections reported within three weeks of the specimen date. Overall, there was a significant increase of 17.5% in reporting after October 2010 (95% CI 13.8-21.4%, p < 0.001) and an improvement in reporting delay, when new statutory reporting regulations were introduced. CONCLUSIONS: The outbreak detection algorithm used at the national and regional level requires further modification to optimise outbreak detection for individual hospitals. For any prospective outbreak detection system to perform optimally it is imperative that laboratories ensure that the data they submit is complete, consistent and timely.

The United Kingdom public health response to an imported laboratory confirmed case of a novel coronavirus in September 2012.

On 22 September 2012, a novel coronavirus, very closely related to that from a fatal case in Saudi Arabia three months previously, was detected in a previously well adult transferred to intensive care in London from Qatar with severe respiratory illness. Strict respiratory isolation was instituted. Ten days after last exposure, none of 64 close contacts had developed severe disease, with 13 of 64 reporting mild respiratory symptoms. The novel coronavirus was not detected in 10 of 10 symptomatic contacts tested.

Novel coronavirus associated with severe respiratory disease: case definition and public health measures.

Two cases of rapidly progressive acute respiratory infection in adults associated with a novel coronavirus have generated an international public health response. The two infections were acquired three months apart, probably in Saudi Arabia and Qatar. An interim case definition has been elaborated and was published on the World Health Organization website on 25 September 2012.

Infectious disease surveillance for the London 2012 Olympic and Paralympic Games.

The London 2012 Olympic and Paralympic Games will be one of the largest mass gathering events in British history. In order to minimise potential infectious disease threats related to the event, the Health Protection Agency (HPA) has set up a suite of robust and multisource surveillance systems. These include enhancements of already established systems (notification of infectious diseases, local and regional reporting,laboratory surveillance, mortality surveillance, international surveillance, and syndromic surveillance in primary care), as well as new systems created for the Games (syndromic surveillance in emergency departments and out-of-hours/unscheduled care,undiagnosed serious infectious illness surveillance).Enhanced existing and newly established surveillance systems will continue after the Games or will be ready for future reactivation should the need arise. In addition to the direct improvements to surveillance, the strengthening of relationships with national and international stakeholders will constitute a major post-Games legacy for the HPA.

Data linkage between existing healthcare databases to support hospital epidemiology.

Enhancing the use of existing datasets within acute hospitals will greatly facilitate hospital epidemiology, surveillance, the monitoring of a variety of processes, outcomes and risk factors, and the provision of alert systems. Multiple overlapping data systems exist within National Health Service (NHS) hospitals in the UK, and many duplicate data recordings take place because of the lack of linkage and interfaces. This results in hospital-collected data not being used efficiently. The objective was to create an inventory of all existing systems, including administrative, management, human resources, microbiology, patient care and other platforms, to describe the data architecture that could contribute valuable information for a hospital epidemiology unit. These datasets were investigated as to how they could be used to generate surveillance data, key performance indicators and risk information that could be shared at board, clinical programme group, specialty and ward level. An example of an output of this integrated data platform and its application in influenza resilience planning and responsiveness is described. The development of metrics for staff absence and staffing levels may also be used as key indicators for risk-monitoring for infection prevention. This work demonstrates the value of such a data inventory and linkage and the importance of more sophisticated uses of existing NHS data, and innovative collaborative approaches to support clinical care, quality improvement, surveillance, emergency planning and research.

Estimating time to onset of swine influenza symptoms after initial novel A(H1N1v) viral infection.

Characterization of the incubation time from infection to onset is important for understanding the natural history of infectious diseases. Attempts to estimate the incubation time distribution for novel A(H1N1v) have been, up to now, based on limited data or peculiar samples. We characterized this distribution for a generic group of symptomatic cases using laboratory-confirmed swine influenza case-information. Estimates of the incubation distribution for the pandemic influenza were derived through parametric time-to-event analyses of data on onset of symptoms and exposure dates, accounting for interval censoring. We estimated a mean of about 1·6-1·7 days with a standard deviation of 2 days for the incubation time distribution in those who became symptomatic after infection with the A(H1N1v) virus strain. Separate analyses for the <15 years and ≥ 15 years age groups showed a significant (P<0·02) difference with a longer mean incubation time in the older age group.

Hospitalization in two waves of pandemic influenza A(H1N1) in England.

Uncertainties exist regarding the population risks of hospitalization due to pandemic influenza A(H1N1). Understanding these risks is important for patients, clinicians and policy makers. This study aimed to clarify these uncertainties. A national surveillance system was established for patients hospitalized with laboratory-confirmed pandemic influenza A(H1N1) in England. Information was captured on demographics, pre-existing conditions, treatment and outcomes. The relative risks of hospitalization associated with pre-existing conditions were estimated by combining the captured data with population prevalence estimates. A total of 2416 hospitalizations were reported up to 6 January 2010. Within the population, 4·7 people/100,000 were hospitalized with pandemic influenza A(H1N1). The estimated hospitalization rate of cases showed a U-shaped distribution with age. Chronic kidney disease, chronic neurological disease, chronic respiratory disease and immunosuppression were each associated with a 10- to 20-fold increased risk of hospitalization. Patients who received antiviral medication within 48 h of symptom onset were less likely to be admitted to critical care than those who received them after this time (adjusted odds ratio 0·64, 95% confidence interval 0·44-0·94, P=0·024). In England the risk of hospitalization with pandemic influenza A(H1N1) has been concentrated in the young and those with pre-existing conditions. By quantifying these risks, this study will prove useful in planning for the next winter in the northern and southern hemispheres, and for future pandemics.

Syndromic surveillance to assess the potential public health impact of the Icelandic volcanic ash plume across the United Kingdom, April 2010.

The Health Protection Agency and Health Protection Scotland used existing syndromic surveillance systems to monitor community health in the UK following the volcanic eruption in Iceland in April 2010.

Pandemic Influenza A (H1N1) 2009 and mortality in the United Kingdom: risk factors for death, April 2009 to March 2010.

This paper describes the epidemiology of fatal pandemic influenza A(H1N1) cases in the United Kingdom (UK) since April 2009 and in particular risk factors associated with death. A fatal case was defined as a UK resident who died between 27 April 2009 and 12 March 2010, in whom pandemic influenza A(H1N1) infection was confirmed by laboratory or recorded on death certificate. Case fatality ratios (CFR) were calculated using the estimated cumulative number of clinical cases as the denominator. The relative risk of death was estimated by comparing the population mortality rate in each risk group, with those not in a risk group. Across the UK, 440 fatal cases were identified. In England, fatal cases were mainly seen in young adults (median age 43 years, 85% under 65 years), unlike for seasonal influenza. The majority (77%) of cases for whom data were available (n=308) had underlying risk factors for severe disease. The CFR in those aged 65 years or over was nine per 1,000 (range 3 - 26) compared to 0.4 (range 0.2 to 0.9) for those aged six months to 64 years. In the age group between six month and 64 years, the relative risk for fatal illness for those in a risk group was 18. The population attributable fractions in this age group were highest for chronic neurological disease (24%), immunosuppression (16%) and respiratory disease (15%). The results highlight the importance of early targeted effective intervention programmes.

Pandemic (H1N1) 2009 virus outbreak in a school in London, April-May 2009: an observational study.

On 29 April 2009, an imported case of pandemic (H1N1) 2009 virus infection was detected in a London school. As further cases, pupils and staff members were identified, school closure and mass prophylaxis were implemented. An observational descriptive study was conducted to provide an insight into the clinical presentation and transmission dynamics in this setting. Between 15 April and 15 May 2009, 91 symptomatic cases were identified: 33 were confirmed positive for pandemic (H1N1) 2009 virus infection; 57 were tested negative; in one the results were unavailable. Transmission occurred first within the school, and subsequently outside. Attack rates were 2% in pupils (15% in the 11-12 years age group) and 17% in household contacts. The predominant symptoms were fever (97%), respiratory symptoms (91%), and sore throat (79%). Limited spread in the school may have been due to a combination of school closure and mass prophylaxis. However, transmission continued through household contacts to other schools.

Using chlamydia positivity to estimate prevalence: evidence from the Chlamydia Screening Pilot in England.

Studies have suggested that positivity can be used to estimate the prevalence of Chlamydia trachomatis in large-scale chlamydia screening programmes. A recent pilot of opportunistic screening in England estimated that the prevalence among 16-24-year-old women in Portsmouth and Wirral was 9.8% and 11.2%, respectively. This study assessed the continued validity of positivity as an approximate for prevalence. We re-analysed data from the Chlamydia Screening Pilot to estimate positivity,calculated as total positive tests divided by total tests, and compared these estimates with the previously reported prevalence, measured as the number of women testing positive divided by the total number of women screened. Overall positivity was 9.4% in Portsmouth and 11.0% in the Wirral; these estimates were not statistically different from prevalence, regardless of health-care setting, age group or symptoms. We conclude that positivity can be used as a proxy for prevalence.

Opportunistic screening for genital chlamydial infection. I: acceptability of urine testing in primary and secondary healthcare settings.

OBJECTIVES: To determine the acceptability of opportunistic screening for Chlamydia trachomatis in young people in a range of healthcare settings. DESIGN: An opportunistic screening programme (1 September 1999 to 31 August 2000) using urine samples tested by ligase chain reaction (LCR). Data on uptake and testing were collected and in-depth interviews were used for programme evaluation. SETTING: General practice, family planning, genitourinary medicine clinics, adolescent sexual health clinics, termination of pregnancy clinics, and women's services in hospitals (antenatal, colposcopy, gynaecology and infertility clinics) in two health authorities (Wirral and Portsmouth and South East Hampshire). Main participants: Sexually active women aged between 16 and 24 years attending healthcare settings for any reason. MAIN OUTCOME MEASURES: Uptake data: proportion of women accepting a test by area, healthcare setting, and age; overall population coverage achieved in 1 year. Evaluation data: participants' attitudes and views towards opportunistic screening and urine testing. RESULTS: Acceptance of testing by women (16-24 years) was 76% in Portsmouth and 84% in Wirral. Acceptance was lower in younger women (Portsmouth only) and varied by healthcare setting within each site. 50% of the target female population were screened in Portsmouth and 39% in Wirral. Both the opportunistic offer of screening and the method of screening were universally acceptable. Major factors influencing a decision to accept screening were the non-invasive nature of testing and treatment, desire to protect future fertility, and the experimental nature of the screening programme. CONCLUSIONS: An opportunistic model of urine screening for chlamydial infection is a practical, universally acceptable method of screening.