Evaluation of alternative respiratory syndromes for specific syndromic surveillance of influenza and respiratory syncytial virus: a time series analysis

Assessing the Burden of Respiratory Syncytial Virus-related Bronchiolitis in Primary Care and at 15-Day and 6-Month Follow-up Before Prophylaxis in France: A Test-negative Study

OBJECTIVE

To assess the burden of respiratory syncytial virus (RSV)-related bronchiolitis in primary care and at 15 days and 6 months after a primary care visit.

STUDY DESIGN

In this test-negative study, children <2 years old with a first episode of bronchiolitis were prospectively enrolled by 45 ambulatory pediatricians in France from February 2021 to April 2023. RSV was assessed with a rapid antigen detection test. The burden of the disease was assessed with a questionnaire, including quality of life (PedsQL 1.0 Infant Scales), at 15-day and 6-month follow-up. Children with a positive RSV test result (RSV+) were compared to those with a negative test result (RSV-).

RESULTS

Among the 1591 children enrolled, 750 (47.1%) were RSV+. At 15 days follow-up (data availability: 69%), as compared with RSV- children, RSV+ children more frequently had fever (20.5% vs. 13.7%, P = 0.004) and decreased food intake (27.0% vs. 17.4%, P < 0.001) during the last 3 days. They had higher rates of hospitalization (11.8% vs. 5.8%, P < 0.001), childcare absenteeism (83.5% vs. 66.1%, P < 0.001) and parents who had to stop working to care for them (59.1% vs. 41.0%, P < 0.001) as well as lower quality of life (median PedsQL score 76.2 vs. 78.4, P = 0.03). At 6 months (data availability: 48.5%), the 2 groups did not differ in proportion of medical attendance, hospitalization, antibiotic treatment or quality of life.

CONCLUSION

RSV+ children experienced much more severe disease and follow-up family and societal burden than RSV- children. These data may be used as baseline data as RSV prophylaxis is about to be implemented.

The impact of undergoing elective pediatric lung resection during respiratory syncytial virus peak season on patient outcomes: A nationwide retrospective analysis

OBJECTIVES

Observational data to support delaying elective pediatric thoracic surgery during peak respiratory viral illness season is lacking. This study evaluated whether lung surgery during peak viral season is associated with differences in postoperative outcomes and resource utilization.

METHODS

A retrospective observational cohort study was performed using the Pediatric Health Information System (PHIS). Patients with a congenital lung malformation (CLM) who underwent elective lung resection between 1 January 2016 and 29 February 2020 were included. Respiratory syncytial virus (RSV) incidence was used as a proxy for respiratory viral illness circulation. Monthly hospital-specific RSV incidence was calculated from PHIS data, and peak RSV season was defined by Centers for Disease Control data. Multivariable regression models were built to identify predictors of postoperative mechanical ventilation, which was the main outcome measure, as well as secondary outcomes including 30-day readmission after lung resection, postoperative length of stay (LOS) and hospital billing charges.

RESULTS

Of 1542 CLM patients identified, 344 (22.3%) underwent lung resection during peak RSV season. 38% fewer operations were performed per month during peak RSV season than during off-peak months (p < .001). Children who underwent surgery during peak RSV season did not differ from the off-peak group in terms of age at operation, race, or comorbid conditions (i.e., congenital heart disease, newborn respiratory distress, and preoperative pneumonia). There was no association between hospital-specific RSV incidence at the time of surgery and postoperative mechanical ventilation, postoperative LOS, 30-day readmission rate or hospital billing charges.

DISCUSSION

Performing elective lung surgery in children with CLMs during peak viral season is not associated with adverse surgical outcomes or increased utilization of healthcare resources.

Respiratory Syncytial Virus in Outpatient Children with Bronchiolitis: Continuous Virus Circulation During the Nonepidemic Period

We aimed to estimate the respiratory syncytial virus positivity rate among ambulatory children with bronchiolitis according to the bronchiolitis epidemic period as defined by the French Public Health Institute. The positivity rate was 28.9% during the nonepidemic period and 50.6% during the epidemic period, which suggests continuous virus circulation between bronchiolitis annual peaks.

Trends in pediatric ambulatory community acquired infections before and during COVID-19 pandemic: A prospective multicentric surveillance study in France

Background

Covid-19 pandemic control has imposed several non-pharmaceutical interventions (NPIs). Strict application of these measures has had a dramatic reduction on the epidemiology of several infectious diseases. As the pandemic is ongoing for more than 2 years, some of these measures have been removed, mitigated, or less well applied. The aim of this study is to investigate the trends of pediatric ambulatory infectious diseases before and up to two years after the onset of the pandemic.

Methods

We conducted a prospective surveillance study in France with 107 pediatricians specifically trained in pediatric infectious diseases. From January 2018 to April 2022, the electronic medical records of children with an infectious disease were automatically extracted. The annual number of infectious diseases in 2020 and 2021 was compared to 2018-2019 and their frequency was compared by logistic regression.

Findings

From 2018 to 2021, 185,368 infectious diseases were recorded. Compared to 2018 (n=47,116) and 2019 (n=51,667), the annual number of cases decreased in 2020 (n=35,432) by about a third. Frequency of scarlet fever, tonsillopharyngitis, enteroviral infections, bronchiolitis, and gastroenteritis decreased with OR varying from 0·6 (CI95% [0·5;0·7]) to 0·9 (CI95% [0·8;0·9]), p<0·001. In 2021, among the 52,153 infectious diagnoses, an off-season rebound was observed with increased frequency of enteroviral infections, bronchiolitis, gastroenteritis and otitis with OR varying from 1·1 (CI95% [1·0;1·1]) to 1·5 (CI95% [1·4;1·5]), p<0·001.

Interpretation

While during NPIs strict application, the overall frequency of community-acquired infections was reduced, after relaxation of these measures, a rebound of some of them (enteroviral infections, bronchiolitis, gastroenteritis, otitis) occurred beyond the pre-pandemic level. These findings highlight the need for continuous surveillance of infectious diseases, especially insofar as future epidemics are largely unpredictable.

Funding

ACTIV, AFPA, GSK, MSD, Pfizer and Sanofi.

Examining the Correlation of Google Influenza Trend with Hospital Data: Retrospective Study

Introduction

Many studies have explored social media and users search activities such as Google Trends to predict and detect influenza activities. Studies that examined Google Trends correlation with the actual hospital influenza cases were conducted in non-tropical regions that have clearly defined seasons. Tropical areas are known for having less-defined seasonality and the extent of Google Trends concordance with actual influenza cases is unknown for these areas. The goal of this study is to compare Google Trends with hospital cases in tropical regions.

Methods

We analyzed 48,263 influenza cases in the time period of 2010 to 2019. The cases were retrieved from central hospital medical records in tropical regions using the corresponding codes for influenza ICD-10 AM. Cases from the medical records were compared with Google Trends to determine trends, seasonality, and correlation.

Results

Graphically, there were some similar areas of the trend, but cross-correlation analysis did not show any significant correlation between hospital and Google Trends with a maximum correlation rate of 0.300. Seasonality analysis showed a clear pattern that peaked around November in Google Trends while hospital data showed less defined seasonality with a smaller peak occurring at the end of December and beginning of January.

Conclusion

Based on the results, there is a weak correlation between Google Trends and hospital data. More innovative methods are emerging to predict influenza activity using social media and user search data and further study is needed to examine the concurrent trends derived using these methods across regions that have different humidity levels and temperatures.

Syndromic Surveillance of Respiratory Disease in Free-Living Chimpanzees

Disease surveillance in wildlife is rapidly expanding in scope and methodology, emphasizing the need for formal evaluations of system performance. We examined a syndromic surveillance system for respiratory disease detection in Gombe National Park, Tanzania, from 2004 to 2012, with respect to data quality, disease trends, and respiratory disease detection. Data quality was assessed by examining community coverage, completeness, and consistency. The data were examined for baseline trends; signs of respiratory disease occurred at a mean frequency of less than 1 case per week, with most weeks containing zero observations of abnormalities. Seasonal and secular (i.e., over a period of years) trends in respiratory disease frequency were not identified. These baselines were used to develop algorithms for outbreak detection using both weekly counts and weekly prevalence thresholds and then compared retrospectively on the detection of 13 respiratory disease clusters from 2005 to 2012. Prospective application of outbreak detection algorithms to real-time syndromic data would be useful in triggering a rapid outbreak response, such as targeted diagnostic sampling, enhanced surveillance, or mitigation.

Construction and evaluation of two computational models for predicting the incidence of influenza in Nagasaki Prefecture, Japan

It remains challenging to forecast local, seasonal outbreaks of influenza. The goal of this study was to construct a computational model for predicting influenza incidence. We built two computational models including an Autoregressive Distributed Lag (ARDL) model and a hybrid model integrating ARDL with a Generalized Regression Neural Network (GRNN), to assess meteorological factors associated with temporal trends in influenza incidence. The modelling and forecasting performance of these two models were compared using observations collected between 2006 and 2015 in Nagasaki Prefecture, Japan. In both the training and forecasting stages, the hybrid model showed lower error rates, including a lower residual mean square error (RMSE) and mean absolute error (MAE) than the ARDL model. The lag of log-incidence, weekly average barometric pressure, and weekly average of air temperature were 4, 1, and 3, respectively in the ARDL model. The ARDL-GRNN hybrid model can serve as a tool to better understand the characteristics of influenza epidemic, and facilitate their prevention and control.

The burden of seasonal respiratory infections on a national telehealth service in England

Seasonal respiratory illnesses present a major burden on primary care services. We assessed the burden of respiratory illness on a national telehealth system in England and investigated the potential for providing early warning of respiratory infection. We compared weekly laboratory reports for respiratory pathogens with telehealth calls (NHS 111) between week 40 in 2013 and week 29 in 2015. Multiple linear regression was used to identify which pathogens had a significant association with respiratory calls. Children aged <5 and 5-14 years, and adults over 65 years were modelled separately as were time lags of up to 4 weeks between calls and laboratory specimen dates. Associations with respiratory pathogens explained over 83% of the variation in cold/flu, cough and difficulty breathing calls. Based on the first two seasons available, the greatest burden was associated with respiratory syncytial virus (RSV) and influenza, with associations found in all age bands. The most sensitive signal for influenza was calls for 'cold/flu', whilst for RSV it was calls for cough. The best-fitting models showed calls increasing a week before laboratory specimen dates. Daily surveillance of these calls can provide early warning of seasonal rises in influenza and RSV, contributing to the national respiratory surveillance programme.

High burden of RSV hospitalization in very young children: a data linkage study

Linked administrative population data were used to estimate the burden of childhood respiratory syncytial virus (RSV) hospitalization in an Australian cohort aged <5 years. RSV-coded hospitalizations data were extracted for all children aged <5 years born in New South Wales (NSW), Australia between 2001 and 2010. Incidence was calculated as the total number of new episodes of RSV hospitalization divided by the child-years at risk. Mean cost per episode of RSV hospitalization was estimated using public hospital cost weights. The cohort comprised of 870 314 children. The population-based incidence/1000 child-years of RSV hospitalization for children aged <5 years was 4·9 with a rate of 25·6 in children aged <3 months. The incidence of RSV hospitalization (per 1000 child-years) was 11·0 for Indigenous children, 81·5 for children with bronchopulmonary dysplasia (BPD), 10·2 for preterm children with gestational age (GA) 32-36 weeks, 27·0 for children with GA 28-31 weeks, 39·0 for children with GA <28 weeks and 6·7 for term children with low birthweight. RSV hospitalization was associated with an average annual cost of more than AUD 9 million in NSW. RSV was associated with a substantial burden of childhood hospitalization specifically in children aged <3 months and in Indigenous children and children born preterm or with BPD.

Inaccurate ascertainment of morbidity and mortality due to influenza in administrative databases: a population-based record linkage study

BACKGROUND

Historically, counting influenza recorded in administrative health outcome databases has been considered insufficient to estimate influenza attributable morbidity and mortality in populations. We used database record linkage to evaluate whether modern databases have similar limitations.

METHODS

Person-level records were linked across databases of laboratory notified influenza, emergency department (ED) presentations, hospital admissions and death registrations, from the population (∼6.9 million) of New South Wales (NSW), Australia, 2005 to 2008.

RESULTS

There were 2568 virologically diagnosed influenza infections notified. Among those, 25% of 40 who died, 49% of 1451 with a hospital admission and 7% of 1742 with an ED presentation had influenza recorded on the respective database record. Compared with persons aged ≥65 years and residents of regional and remote areas, respectively, children and residents of major cities were more likely to have influenza coded on their admission record. Compared with older persons and admitted patients, respectively, working age persons and non-admitted persons were more likely to have influenza coded on their ED record. On both ED and admission records, persons with influenza type A infection were more likely than those with type B infection to have influenza coded. Among death registrations, hospital admissions and ED presentations with influenza recorded as a cause of illness, 15%, 28% and 1.4%, respectively, also had laboratory notified influenza. Time trends in counts of influenza recorded on the ED, admission and death databases reflected the trend in counts of virologically diagnosed influenza.

CONCLUSIONS

A minority of the death, hospital admission and ED records for persons with a virologically diagnosed influenza infection identified influenza as a cause of illness. Few database records with influenza recorded as a cause had laboratory confirmation. The databases have limited value for estimating incidence of influenza outcomes, but can be used for monitoring variation in incidence over time.

The effect of statin therapy on the incidence of infections: a retrospective cohort analysis

BACKGROUND

Statins have been postulated to prevent infection through immunomodulatory effects.

OBJECTIVES

To compare the incidence of infections in statin users to that in nonusers within the same health care system.

METHODS

This was a retrospective cohort study of patients enrolled as Tricare Prime or Plus in the San Antonio military multimarket. Statin users were patients who received a statin for at least 3 months between October 1, 2004 and September 30, 2005. Nonusers were patients who did not receive a statin within the study period (October 1, 2003-September 30, 2009). Inpatient and outpatient International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes were used to determine the incidence of infections during the follow-up period (October 1, 2005-September 30, 2009) via multivariable regression analysis and time to infection via Cox regression analysis.

RESULTS

Of 45,247 patients who met the study criteria, 12,981 (29%) were statin users and 32,266 were nonusers. After adjustments for age, gender, Charlson Comorbidity Score, tobacco use, alcohol abuse/dependence, health care utilization and use of specific medication classes, statin use was associated with an increased incidence of common infections (odds ratio [OR]: 1.13; 95% confidence interval [CI]: 1.06-1.19) but not influenza or fungal infections (OR: 1.06, 95% CI: 0.80-1.39; OR: 0.97; 95% CI: 0.91-1.04, respectively). Time-to-first infection was similar in statin users and nonusers in all infection categories examined.

CONCLUSIONS

Statin use was associated with an increased incidence of common infections but not influenza or fungal infections. This study does not support a protective role of statins in infection prevention; however, the influence of potential confounders cannot be excluded.

Syndromic surveillance for influenza in the emergency department-A systematic review

The science of surveillance is rapidly evolving due to changes in public health information and preparedness as national security issues, new information technologies and health reform. As the Emergency Department has become a much more utilized venue for acute care, it has also become a more attractive data source for disease surveillance. In recent years, influenza surveillance from the Emergency Department has increased in scope and breadth and has resulted in innovative and increasingly accepted methods of surveillance for influenza and influenza-like-illness (ILI). We undertook a systematic review of published Emergency Department-based influenza and ILI syndromic surveillance systems. A PubMed search using the keywords "syndromic", "surveillance", "influenza" and "emergency" was performed. Manuscripts were included in the analysis if they described (1) data from an Emergency Department (2) surveillance of influenza or ILI and (3) syndromic or clinical data. Meeting abstracts were excluded. The references of included manuscripts were examined for additional studies. A total of 38 manuscripts met the inclusion criteria, describing 24 discrete syndromic surveillance systems. Emergency Department-based influenza syndromic surveillance has been described worldwide. A wide variety of clinical data was used for surveillance, including chief complaint/presentation, preliminary or discharge diagnosis, free text analysis of the entire medical record, Google flu trends, calls to teletriage and help lines, ambulance dispatch calls, case reports of H1N1 in the media, markers of ED crowding, admission and Left Without Being Seen rates. Syndromes used to capture influenza rates were nearly always related to ILI (i.e. fever +/- a respiratory or constitutional complaint), however, other syndromes used for surveillance included fever alone, "respiratory complaint" and seizure. Two very large surveillance networks, the North American DiSTRIBuTE network and the European Triple S system have collected large-scale Emergency Department-based influenza and ILI syndromic surveillance data. Syndromic surveillance for influenza and ILI from the Emergency Department is becoming more prevalent as a measure of yearly influenza outbreaks.

Relationship between the population incidence of pertussis in children in New South Wales, Australia and emergency department visits with cough: a time series analysis

Background

Little is known about the potential of syndromic surveillance to provide early warning of pertussis outbreaks. We conducted a time series analysis to assess whether an emergency department (ED) cough syndrome would respond to changes in the incidence of pertussis in children aged under 10 years in New South Wales (NSW), Australia, and to evaluate the timing of any association. A further aim was to assess the lag between the onset of pertussis symptoms and case notification in the infectious diseases surveillance system in NSW.

Methods

Using routinely collected data, we prepared a daily count time series of visits to NSW EDs assigned a provisional diagnosis of cough. Separate daily series were prepared for three independent variables: notifications of cases of pertussis and influenza and ED visits with bronchiolitis (a proxy measure of respiratory syncytial virus (RSV) infection). The study period was 1/1/2007-31/12/2010. A negative binomial multivariate model was used to assess associations between the outcome and independent variables. We also evaluated the median delay in days between the estimated onset of a case of pertussis and the date the local public health authority was notified of that case.

Results

When notified pertussis increased by 10 cases in one day, ED visits with cough increased by 5.2% (95% confidence interval (CI): 0.5%-10.0%) seven days later. Daily increases in the other independent variables had a smaller impact on cough visits. When notified influenza increased by 10 cases in one day, ED visits with cough increased by 0.8% (95% CI: 0%-1.7%) seven days later. When ED visits with bronchiolitis increased by 10 visits in one day, ED visits with cough increased by 4.8% (95% CI: 1.2%-8.6%) one day earlier. The median interval between estimated onset of pertussis and case notification was seven days.

Conclusions

Pertussis appears to be an important driver of ED visits with cough in children aged under 10 years. However, the median delay in notification of cases of pertussis was similar to the lag in the pertussis-associated short-term increases in ED visits with cough. Elevations in RSV and influenza activity may also explain increases in the ED cough syndrome. Real time monitoring of ED visits with cough in children is therefore unlikely to consistently detect a potential outbreak of pertussis before passive surveillance.

Prescription surveillance and polymerase chain reaction testing to identify pathogens during outbreaks of infection

Syndromic surveillance, including prescription surveillance, offers a rapid method for the early detection of agents of bioterrorism and emerging infectious diseases. However, it has the disadvantage of not considering definitive diagnoses. Here, we attempted to definitively diagnose pathogens using polymerase chain reaction (PCR) immediately after the prescription surveillance system detected an outbreak. Specimens were collected from 50 patients with respiratory infections. PCR was used to identify the pathogens, which included 14 types of common respiratory viruses and Mycoplasma pneumoniae. Infectious agents including M. pneumoniae, respiratory syncytial virus (RSV), rhinovirus, enterovirus, and parainfluenza virus were detected in 54% of patients. For the rapid RSV diagnosis kit, sensitivity was 80% and specificity was 85%. For the rapid adenovirus diagnosis kit, no positive results were obtained; therefore, sensitivity could not be calculated and specificity was 100%. Many patients were found to be treated for upper respiratory tract infections without the diagnosis of a specific pathogen. In Japan, an outbreak of M. pneumoniae infection began in 2011, and our results suggested that this outbreak may have included false-positive cases. By combining syndromic surveillance and PCR, we were able to rapidly and accurately identify causative pathogens during a recent respiratory infection outbreak.

Can linked emergency department data help assess the out-of-hospital burden of acute lower respiratory infections? A population-based cohort study

Background

There is a lack of data on the out-of-hospital burden of acute lower respiratory infections (ALRI) in developed countries. Administrative datasets from emergency departments (ED) may assist in addressing this.

Methods

We undertook a retrospective population-based study of ED presentations for respiratory-related reasons linked to birth data from 245,249 singleton live births in Western Australia. ED presentation rates <9 years of age were calculated for different diagnoses and predictors of ED presentation <5 years were assessed by multiple logistic regression.

Results

ED data from metropolitan WA, representing 178,810 births were available for analysis. From 35,136 presentations, 18,582 (52.9%) had an International Classification of Diseases (ICD) code for ALRI and 434 had a symptom code directly relating to an ALRI ICD code. A further 9600 presentations had a non-specific diagnosis. From the combined 19,016 ALRI presentations, the highest rates were in non-Aboriginal children aged 6–11 months (81.1/1000 child-years) and Aboriginal children aged 1–5 months (314.8/1000). Croup and bronchiolitis accounted for the majority of ALRI ED presentations. Of Aboriginal births, 14.2% presented at least once to ED before age 5 years compared to 6.5% of non-Aboriginal births. Male sex and maternal age <20 years for Aboriginal children and 20–29 years for non-Aboriginal children were the strongest predictors of presentation to ED with ALRI.

Conclusions

ED data can give an insight into the out-of-hospital burden of ALRI. Presentation rates to ED for ALRI were high, but are minimum estimates due to current limitations of the ED datasets. Recommendations for improvement of these data are provided. Despite these limitations, ALRI, in particular bronchiolitis and croup are important causes of presentation to paediatric EDs.

Relationship between the population incidence of febrile convulsions in young children in Sydney, Australia and seasonal epidemics of influenza and respiratory syncytial virus, 2003-2010: a time series analysis

Background

In 2010, intense focus was brought to bear on febrile convulsions in Australian children particularly in relation to influenza vaccination. Febrile convulsions are relatively common in infants and can lead to hospital admission and severe outcomes. We aimed to examine the relationships between the population incidence of febrile convulsions and influenza and respiratory syncytial virus (RSV) seasonal epidemics in children less than six years of age in Sydney Australia using routinely collected syndromic surveillance data and to assess the feasibility of using this data to predict increases in population rates of febrile convulsions.

Methods

Using two readily available sources of routinely collected administrative data; the NSW Emergency Department (ED) patient management database (1 January 2003 - 30 April 2010) and the Ambulance NSW dispatch database (1 July 2006 - 30 April 2010), we used semi-parametric generalized additive models (GAM) to determine the association between the population incidence rate of ED presentations and urgent ambulance dispatches for 'convulsions', and the population incidence rate of ED presentations for 'influenza-like illness' (ILI) and 'bronchiolitis' - proxy measures of influenza and RSV circulation, respectively.

Results

During the study period, when the weekly all-age population incidence of ED presentations for ILI increased by 1/100,000, the 0 to 6 year-old population incidence of ED presentations for convulsions increased by 6.7/100,000 (P < 0.0001) and that of ambulance calls for convulsions increased by 3.2/100,000 (P < 0.0001). The increase in convulsions occurred one week earlier relative to the ED increase in ILI. The relationship was weaker during the epidemic of pandemic (H1N1) 2009 influenza virus.

When the 0 to 3 year-old population incidence of ED presentations for bronchiolitis increased by 1/100,000, the 0 to 6 year-old population incidence of ED presentations for convulsions increased by 0.01/100,000 (P < 0.01). We did not find a meaningful and statistically significant association between bronchiolitis and ambulance calls for convulsions.

Conclusions

Influenza seasonal epidemics are associated with a substantial and statistically significant increase in the population incidence of hospital attendances and ambulance dispatches for reported febrile convulsions in young children. Monitoring syndromic ED and ambulance data facilitates rapid surveillance of reported febrile convulsions at a population level.

Prediction and surveillance of influenza epidemics

OBJECTIVE

To describe the use of surveillance and forecasting models to predict and track epidemics (and, potentially, pandemics) of influenza.

METHODS

We collected 5 years of historical data (2005-2009) on emergency department presentations and hospital admissions for influenza-like illnesses (International Classification of Diseases [ICD-10-AM] coding) from the Emergency Department Information System (EDIS) database of 27 Queensland public hospitals. The historical data were used to generate prediction and surveillance models, which were assessed across the 2009 southern hemisphere influenza season (June-September) for their potential usefulness in informing response policy. Three models are described: (i) surveillance monitoring of influenza presentations using adaptive cumulative sum (CUSUM) plan analysis to signal unusual activity; (ii) generating forecasts of expected numbers of presentations for influenza, based on historical data; and (iii) using Google search data as outbreak notification among a population.

RESULTS

All hospitals, apart from one, had more than the expected number of presentations for influenza starting in late 2008 and continuing into 2009. (i) The CUSUM plan signalled an unusual outbreak in December 2008, which continued in early 2009 before the winter influenza season commenced. (ii) Predictions based on historical data alone underestimated the actual influenza presentations, with 2009 differing significantly from previous years, but represent a baseline for normal ED influenza presentations. (iii) The correlation coefficients between internet search data for Queensland and statewide ED influenza presentations indicated an increase in correlation since 2006 when weekly influenza search data became available.

CONCLUSION

This analysis highlights the value of health departments performing surveillance monitoring to forewarn of disease outbreaks. The best system among the three assessed was a combination of routine forecasting methods coupled with an adaptive CUSUM method.

Effects of air pollution on neonatal prematurity in Guangzhou of China: a time-series study

BACKGROUND

Over the last decade, a few studies have investigated the possible adverse effects of ambient air pollution on preterm birth. However, the correlation between them still remains unclear, due to insufficient evidences.

METHODS

The correlation between air pollution and preterm birth in Guangzhou city was examined by using the Generalized Additive Model (GAM) extended Poisson regression model in which we controlled the confounding factors such as meteorological factors, time trends, weather and day of the week (DOW). We also adjusted the co linearity of air pollutants by using Principal Component Analysis. The meteorological data and air pollution data were obtained from the Meteorological Bureau and the Environmental Monitoring Centre, while the medical records of newborns were collected from the perinatal health database of all obstetric institutions in Guangzhou, China in 2007.

RESULTS

In 2007, the average daily concentrations of NO₂, PM₁₀ and SO₂ in Guangzhou, were 61.04, 82.51 and 51.67 μg/m³ respectively, where each day an average of 21.47 preterm babies were delivered. Pearson correlation analysis suggested a negative correlation between the concentrations of NO₂, PM₁₀, SO₂, and temperature as well as relative humidity. As for the time-series GAM analysis, the results of single air pollutant model suggested that the cumulative effects of NO₂, PM₁₀ and SO₂ reached its peak on day 3, day 4 and day 3 respectively. An increase of 100 μg/m³ of air pollutants corresponded to relative risks (RRs) of 1.0542 (95%CI: 1.0080 ~1.1003), 1.0688 (95%CI: 1.0074 ~1.1301) and 1.1298 (95%CI: 1.0480 ~1.2116) respectively. After adjusting co linearity by using the Principal Component Analysis, the GAM model of the three air pollutants suggested that an increase of 100 μg/m³ of air pollutants corresponded to RRs of 1.0185 (95%CI: 1.0056~1.0313), 1.0215 (95%CI: 1.0066 ~1.0365) and 1.0326 (95%CI: 1.0101 ~1.0552) on day 0; and RRs of the three air pollutants, at their strongest cumulative effects, were 1.0219 (95%CI: 1.0053~1.0386), 1.0274 (95%CI: 1.0066~1.0482) and 1.0388 (95%CI: 1.0096 ~1.0681) respectively.

CONCLUSIONS

This study indicates that the daily concentrations of air pollutants such as NO₂, PM₁₀ and SO₂ have a positive correlation with the preterm births in Guangzhou, China.

Can near real-time monitoring of emergency department diagnoses facilitate early response to sporadic meningococcal infection?--prospective and retrospective evaluations

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.