Validity and timeliness of syndromic influenza surveillance during the autumn/winter wave of A (H1N1) influenza 2009: results of emergency medical dispatch, ambulance and emergency department data from three European regions

Using ambulance surveillance data to characterise blood-borne viral infection histories among patients presenting with acute alcohol and other drug-related harms

OBJECTIVE

Preventable transmission of blood-borne viruses (BBV), including human immunodeficiency virus (HIV), hepatitis C virus (HCV) and hepatitis B virus (HBV), continue in at-risk populations, including people who use alcohol and drugs (AODs). To our knowledge, no studies have explored the use of ambulance data for surveillance of AOD harms in patients with BBV infections.

METHODS

We used electronic patient care records from the National Ambulance Surveillance System for people who were attended by an ambulance in Victoria, Australia between July 2015 and July 2016 for AOD-related harms, and with identified history of a BBV infection. Descriptive and geospatial analyses explored the epidemiological and psychosocial characteristics of patients for these attendances.

RESULTS

The present study included 1832 patients with a history of a BBV infection who required an ambulance for AOD-related harms. Amphetamines were reported in 24.7% of attendances where the patient identified HIV history, and heroin was reported more often for patients with viral hepatitis history (HCV: 19.2%; HBV: 12.7%). Higher proportions of attendances with a viral hepatitis history were observed in patients from the most socially disadvantaged areas. Geospatial analyses revealed higher concentrations of AOD attendances with a BBV history occurring in metropolitan Melbourne.

CONCLUSIONS

Our study describes the utility of ambulance data to identify a sub-population of patients with a BBV history and complex medical and social characteristics. Repeat attendances of BBV history patients to paramedics could present an opportunity for ongoing surveillance using ambulance data and possible paramedic intervention, with potential linkage to appropriate BBV services.

Use of Ambulance Dispatch Calls for Surveillance of Severe Acute Respiratory Infections

Ambulance dispatches for respiratory syndromes reflect incidence of influenza-like illness in primary care. Associations are highest in children (15%–34% of respiratory calls attributable to influenza), out-of-office hours (9%), and highest urgency-level calls (9%–11%). Ambulance dispatches might be an additional source of data for severe influenza surveillance.

Ambulance dispatch calls attributable to influenza A and other common respiratory viruses in the Netherlands (2014-2016)

BACKGROUND

Ambulance dispatches could be useful for syndromic surveillance of severe respiratory infections. We evaluated whether ambulance dispatch calls of highest urgency reflect the circulation of influenza A virus, influenza B virus, respiratory syncytial virus (RSV), rhinovirus, adenovirus, coronavirus, parainfluenzavirus and human metapneumovirus (hMPV).

METHODS

We analysed calls from four ambulance call centres serving 25% of the population in the Netherlands (2014-2016). The chief symptom and urgency level is recorded during triage; we restricted our analysis to calls with the highest urgency and identified those compatible with a respiratory syndrome. We modelled the relation between respiratory syndrome calls (RSC) and respiratory virus trends using binomial regression with identity link function.

RESULTS

We included 211 739 calls, of which 15 385 (7.3%) were RSC. Proportion of RSC showed periodicity with winter peaks and smaller interseasonal increases. Overall, 15% of RSC were attributable to respiratory viruses (20% in out-of-office hour calls). There was large variation by age group: in <15 years, only RSV was associated and explained 11% of RSC; in 15-64 years, only influenza A (explained 3% of RSC); and in ≥65 years adenovirus explained 9% of RSC, distributed throughout the year, and hMPV (4%) and influenza A (1%) mainly during the winter peaks. Additionally, rhinovirus was associated with total RSC.

CONCLUSION

High urgency ambulance dispatches reflect the burden of different respiratory viruses and might be useful to monitor the respiratory season overall. Influenza plays a smaller role than other viruses: RSV is important in children while adenovirus and hMPV are the biggest contributors to emergency calls in the elderly.

Syndromic surveillance using ambulance transfer data in Tokyo, Japan

Bioterrorism attacks become more probable when important high-profile international or political events are held, such as G7 summit meetings or mass gathering events including Olympic and Paralympic games and FIFA World Cup tournaments. Outbreaks of infectious disease and widespread incidents of food poisoning are also public health concerns at such times. In Japan, the Tokyo Metropolitan Government operates Ambulance Transfer Syndromic Surveillance (ATSS), which can help monitor such incidents. The present study presents and assesses the ATSS framework. During the study period of October 2017 through November 2018, we monitored 33 areas for symptoms of 9 categories: vomiting/nausea, dizziness, palpitation, unconsciousness, breathing disorder, fever, spasm/paralysis, collapse/weakness, and bloody emesis/nasal hemorrhage. Among all symptoms, we found 9929 low-level aberrations, 2537 medium-level aberrations, and 577 high-level aberrations, with respective frequencies of 9.2%, 2.3%, and 0.5%. Of those, Tokyo Metropolitan Institute of Public Health reported the information to Tokyo Metropolitan Government 28 times during the period. Of the 28 identified clusters, Tokyo Metropolitan Government judged the necessity for investigating 7. All of those were investigated at hospitals by the jurisdictional public health center. Because ATSS covers almost the entire Tokyo metropolitan area, with about 13.8 million residents, it is definitely the largest syndromic surveillance in the world.

Methods for detecting seasonal influenza epidemics using a school absenteeism surveillance system

Background

School absenteeism data have been collected daily by the public health unit in Wellington-Dufferin-Guelph, Ontario since 2008. To date, a threshold-based approach has been implemented to raise alerts for community-wide and within-school illness outbreaks. We investigate several statistical modelling approaches to using school absenteeism for influenza surveillance at the regional level, and compare their performances using two metrics.

Methods

Daily absenteeism percentages from elementary and secondary schools, and report dates for influenza cases, were obtained from Wellington-Dufferin-Guelph Public Health. Several absenteeism data aggregations were explored, including using the average across all schools or only using schools of one type. A 10% absence threshold, exponentially weighted moving average model, logistic regression with and without seasonality terms, day of week indicators, and random intercepts for school year, and generalized estimating equations were used as epidemic detection methods for seasonal influenza. In the regression models, absenteeism data with various lags were used as predictor variables, and missing values in the datasets used for parameter estimation were handled either by deletion or linear interpolation. The epidemic detection methods were compared using a false alarm rate (FAR) as well as a metric for alarm timeliness.

Results

All model-based epidemic detection methods were found to decrease the FAR when compared to the 10% absence threshold. Regression models outperformed the exponentially weighted moving average model and including seasonality terms and a random intercept for school year generally resulted in fewer false alarms. The best-performing model, a seasonal logistic regression model with random intercept for school year and a day of week indicator where parameters were estimated using absenteeism data that had missing values linearly interpolated, produced a FAR of 0.299, compared to the pre-existing threshold method which at best gave a FAR of 0.827.

Conclusions

School absenteeism can be a useful tool for alerting public health to upcoming influenza epidemics in Wellington-Dufferin-Guelph. Logistic regression with seasonality terms and a random intercept for school year was effective at maximizing true alarms while minimizing false alarms on historical data from this region.

Potential added value of the new emergency care dataset to ED-based public health surveillance in England: an initial concept analysis

INTRODUCTION

For the London Olympic and Paralympic Games in 2012, a sentinel ED syndromic surveillance system was established to enhance public health surveillance by obtaining data from a selected network of EDs, focusing on London. In 2017, a new national standard Emergency Care Dataset was introduced, which enabled Public Health England (PHE) to initiate the expansion of their sentinel system to national coverage. Prior to this initiative, we estimated the added value, and potential additional resource use, of an expansion of the sentinel surveillance system.

METHODS

The detection capabilities of the sentinel and national systems were compared using the aberration detection methods currently used by PHE. Different scenarios were used to measure the impact on health at a local, subnational and national level, including improvements to sensitivity and timeliness, along with changes in specificity.

RESULTS

The biggest added value was found to be for detecting local impacts, with an increase in sensitivity of over 80%. There were also improvements found at a national level with outbreaks being detected earlier and smaller impacts being detectable. However, the increased number of local sites will also increase the number of false alarms likely to be generated.

CONCLUSION

We have quantified the added value of national ED syndromic surveillance systems, showing how they will enable detection of more localised events. Furthermore, national systems add value in enabling timelier public health interventions. Finally, we have highlighted areas where extra resource may be required to manage improvements in detection coverage.

Potential role of Emergency Medical System call centres in epidemiological surveillance of seasonal influenza

OBJECTIVES

Seasonal influenza causes high morbidity worldwide and high mortality in developing countries. As a result, the development of systems for seasonal influenza surveillance has been of great interest. The aim of this study is to explore the potential role of an Emergency Medical System (EMS) call centre to complement traditional surveillance systems of seasonal influenza.

METHODS

Retrospective observational study in which data on influenza from the system of Notifiable Diseases List (Spanish acronym EDO) and Sentinel Physicians Network (Spanish acronym RMC) were compared with information on calls made to the Principality of Asturias EMS call centre that covers all the region population (1,027,659 inhabitants) based on a set of specific criteria to determine differences and explore this emergency call system as a complementary epidemiological surveillance system. Cases registered by different systems have been compared to the same 68 weeks period, from week 45 of 2011 to week 8 of 2013.

RESULTS

RMC reported a total of 2,354 cases of influenza, EDO 43,071 cases and EMS call centre 4,360 "case calls" out of 180,720 total emergency calls. Case series of EDO and EMS call centre have shown a positive correlation (R = 0.42, p = 0.003). Case series from EMS call centre and RMC were correlated (R = 0.38, p = 0.007). Case series from EDO and RMC have shown a strong positive correlation (R = 0.91, p < 0.001). Correlation analysis of the cases reported by the three systems have shown a significant positive correlation between them (p < 0.001). The spike of EMS calls related to the studied influenza syndrome occurs one week in advance compared to traditional epidemiological surveillance systems.

CONCLUSIONS

EMS call centre data on influenza could be potentially used as a complementary surveillance system to the traditional epidemiological surveillance systems for influenza.

Outbreak detection and evaluation of a school-based influenza-like-illness syndromic surveillance in Tianjin, China

School-based influenza-like-illness (ILI) syndromic surveillance can be an important part of influenza community surveillance by providing early warnings for outbreaks and leading to a fast response. From September 2012 to December 2014, syndromic surveillance of ILI was carried out in 4 county-level schools. The cumulative sum methods(CUSUM) was used to detect abnormal signals. A susceptible-exposed-infectious/asymptomatic-recovered (SEIAR) model was fit to the influenza outbreak without control measures and compared with the actual influenza outbreak to evaluate the effectiveness of early control efforts. The ILI incidence rates in 2014 (14.51%) was higher than the incidence in 2013 (5.27%) and 2012 (3.59%). Ten school influenza outbreaks were detected by CUSUM. Each outbreak had high transmissibility with a median R_unc of 4.62. The interventions in each outbreak had high effectiveness and all R_con were 0. The early intervention had high effectiveness within the school-based ILI syndromic surveillance. Syndromic surveillance within schools can play an important role in controlling influenza outbreaks.

Heroin and pharmaceutical opioid overdose events: Emergency medical response characteristics

BACKGROUND

Emergency Medical Services (EMS) data may provide insight into opioid overdose incidence, clinical characteristics, and medical response. This analysis describes patient characteristics, clinical features, and EMS response to opioid overdoses, comparing heroin and pharmaceutical opioid (PO) overdoses, using a structured opioid overdose case criteria definition.

METHODS

A case series study was conducted. EMS medical staff screened cases for possible overdoses and study staff categorized the likelihood of opioid overdose. Medical form data were abstracted. Patient characteristics, clinical presentation, and medical response to heroin and PO-involved overdoses were compared with bi-variate test statistics.

RESULTS

We identified 229 definite or probable opioid overdose cases over six months: heroin in 98 (43%) cases (10 also involved PO), PO without heroin in 85 (37%) cases, and 46 (20%) that could not be categorized and were excluded from analyses. Heroin overdose patients were younger than PO (median age 33 v 41 (p<0.05)), more often male (80% v 61% (p=<0.01)), intubated less (8% v 22%, p<0.01) and more likely to be administered naloxone (72% v 51%, p<0.01). No significant differences were found between heroin and PO overdoses for initial respiratory rate, Glasgow Coma Scale score, or co-ingestants, but heroin users were more likely to have miotic pupils (p<0.01).

CONCLUSIONS

While heroin and PO events presented similarly, heroin-involved cases were more likely to receive naloxone and less likely to be intubated. Standardized case definitions and data documentation could aid opioid overdose surveillance as well as provide data for measuring the impact of professional and lay interventions.

Daily volume of cases in emergency call centers: construction and validation of a predictive model

Background

Variations in the activity of emergency dispatch centers are an obstacle to the rationalization of resource allocation. Many explanatory factors are well known, available in advance and could predict the volume of emergency cases. Our objective was to develop and evaluate the performance of a predictive model of daily call center activity.

Methods

A retrospective survey was conducted on all cases from 2005 to 2011 in a large medical emergency call center (1,296,153 cases). A generalized additive model of daily cases was calibrated on data from 2005 to 2008 (1461 days, development sample) and applied to the prediction of days from 2009 to 2011 (1095 days, validation sample). Seventeen calendar and epidemiological variables and a periodic function for seasonality were included in the model.

Results

The average number of cases per day was 507 (95% confidence interval: 500 to 514) (range, 286 to 1251). Factors significantly associated with increased case volume were the annual increase, weekend days, public holidays, regional incidence of influenza in the previous week and regional incidence of gastroenteritis in the previous week. The adjusted R for the model was 0.89 in the calibration sample. The model predicted the actual number of cases within ± 100 for 90.5% of the days, with an average error of −13 cases (95% CI: -17 to 8).

Conclusions

A large proportion of the variability of the medical emergency call center’s case volume can be predicted using readily available covariates.

Electronic supplementary material

The online version of this article (10.1186/s13049-017-0430-9) contains supplementary material, which is available to authorized users.

Success Factors of European Syndromic Surveillance Systems: A Worked Example of Applying Qualitative Comparative Analysis

INTRODUCTION

Syndromic surveillance aims at augmenting traditional public health surveillance with timely information. To gain a head start, it mainly analyses existing data such as from web searches or patient records. Despite the setup of many syndromic surveillance systems, there is still much doubt about the benefit of the approach. There are diverse interactions between performance indicators such as timeliness and various system characteristics. This makes the performance assessment of syndromic surveillance systems a complex endeavour. We assessed if the comparison of several syndromic surveillance systems through Qualitative Comparative Analysis helps to evaluate performance and identify key success factors.

MATERIALS AND METHODS

We compiled case-based, mixed data on performance and characteristics of 19 syndromic surveillance systems in Europe from scientific and grey literature and from site visits. We identified success factors by applying crisp-set Qualitative Comparative Analysis. We focused on two main areas of syndromic surveillance application: seasonal influenza surveillance and situational awareness during different types of potentially health threatening events.

RESULTS

We found that syndromic surveillance systems might detect the onset or peak of seasonal influenza earlier if they analyse non-clinical data sources. Timely situational awareness during different types of events is supported by an automated syndromic surveillance system capable of analysing multiple syndromes. To our surprise, the analysis of multiple data sources was no key success factor for situational awareness.

CONCLUSIONS

We suggest to consider these key success factors when designing or further developing syndromic surveillance systems. Qualitative Comparative Analysis helped interpreting complex, mixed data on small-N cases and resulted in concrete and practically relevant findings.

Human temperatures for syndromic surveillance in the emergency department: data from the autumn wave of the 2009 swine flu (H1N1) pandemic and a seasonal influenza outbreak

Background

The emergency department (ED) increasingly acts as a gateway to the evaluation and treatment of acute illnesses. Consequently, it has also become a key testing ground for systems that monitor and identify outbreaks of disease. Here, we describe a new technology that automatically collects body temperatures during triage. The technology was tested in an ED as an approach to monitoring diseases that cause fever, such as seasonal flu and some pandemics.

Methods

Temporal artery thermometers that log temperature measurements were placed in a Boston ED and used for initial triage vital signs. Time-stamped measurements were collected from the thermometers to investigate the performance a real-time system would offer. The data were summarized in terms of rates of fever (temperatures ≥100.4 °F [≥38.0 °C]) and were qualitatively compared with regional disease surveillance programs in Massachusetts.

Results

From September 2009 through August 2011, 71,865 body temperatures were collected and included in our analysis, 2073 (2.6 %) of which were fevers. The period of study included the autumn–winter wave of the 2009–2010 H1N1 (swine flu) pandemic, during which the weekly incidence of fever reached a maximum of 5.6 %, as well as the 2010–2011 seasonal flu outbreak, during which the maximum weekly incidence of fever was 6.6 %. The periods of peak fever rates corresponded with the periods of regionally elevated flu activity.

Conclusions

Temperature measurements were monitored at triage in the ED over a period of 2 years. The resulting data showed promise as a potential surveillance tool for febrile disease that could complement current disease surveillance systems. Because temperature can easily be measured by non-experts, it might also be suitable for monitoring febrile disease activity in schools, workplaces, and transportation hubs, where many traditional syndromic indicators are impractical. However, the system’s validity and generalizability should be evaluated in additional years and settings.

Electronic supplementary material

The online version of this article (doi:10.1186/s12873-016-0080-7) contains supplementary material, which is available to authorized users.

Performance assessment of communicable disease surveillance in disasters: a systematic review

BACKGROUND

This study aimed to identify the indices and frameworks that have been used to assess the performance of communicable disease surveillance (CDS) in response to disasters and other emergencies, including infectious disease outbreaks.

METHOD

In this systematic review, PubMed, Google Scholar, Scopus, ScienceDirect, ProQuest databases and grey literature were searched until the end of 2013. All retrieved titles were examined in accordance with inclusion criteria. Abstracts of the relevant titles were reviewed and eligible abstracts were included in a list for data abstraction. Finally, the study variables were extracted.

RESULTS

Sixteen articles and one book were found relevant to our study objectives. In these articles, 31 criteria and 35 indicators were used or suggested for the assessment/evaluation of the performance of surveillance systems in disasters. The Centers for Disease Control (CDC) updated guidelines for the evaluation of public health surveillance systems were the most widely used.

CONCLUSION

Despite the importance of performance assessment in improving CDS in response to disasters, there is a lack of clear and accepted frameworks. There is also no agreement on the use of existing criteria and indices. The only relevant framework is the CDC guideline, which is a common framework for assessing public health surveillance systems as a whole. There is an urgent need to develop appropriate frameworks, criteria, and indices for specifically assessing the performance of CDS in response to disasters and other emergencies, including infectious diseases outbreaks. Key words: Disasters, Emergencies, Communicable Diseases, Surveillance System, Performance Assessment.

Meeting the International Health Regulations (2005) surveillance core capacity requirements at the subnational level in Europe: the added value of syndromic surveillance

Background

The revised World Health Organization’s International Health Regulations (2005) request a timely and all-hazard approach towards surveillance, especially at the subnational level. We discuss three questions of syndromic surveillance application in the European context for assessing public health emergencies of international concern: (i) can syndromic surveillance support countries, especially the subnational level, to meet the International Health Regulations (2005) core surveillance capacity requirements, (ii) are European syndromic surveillance systems comparable to enable cross-border surveillance, and (iii) at which administrative level should syndromic surveillance best be applied?

Discussion

Despite the ongoing criticism on the usefulness of syndromic surveillance which is related to its clinically nonspecific output, we demonstrate that it was a suitable supplement for timely assessment of the impact of three different public health emergencies affecting Europe. Subnational syndromic surveillance analysis in some cases proved to be of advantage for detecting an event earlier compared to national level analysis. However, in many cases, syndromic surveillance did not detect local events with only a small number of cases.

The European Commission envisions comparability of surveillance output to enable cross-border surveillance. Evaluated against European infectious disease case definitions, syndromic surveillance can contribute to identify cases that might fulfil the clinical case definition but the approach is too unspecific to comply to complete clinical definitions. Syndromic surveillance results still seem feasible for comparable cross-border surveillance as similarly defined syndromes are analysed.

We suggest a new model of implementing syndromic surveillance at the subnational level. In this model, syndromic surveillance systems are fine-tuned to their local context and integrated into the existing subnational surveillance and reporting structure. By enhancing population coverage, events covering several jurisdictions can be identified at higher levels. However, the setup of decentralised and locally adjusted syndromic surveillance systems is more complex compared to the setup of one national or local system.

Summary

We conclude that syndromic surveillance if implemented with large population coverage at the subnational level can help detect and assess the local and regional effect of different types of public health emergencies in a timely manner as required by the International Health Regulations (2005).

Using real-time syndromic surveillance to assess the health impact of the 2013 heatwave in England

Heatwaves are a seasonal threat to public health. During July 2013 England experienced a heatwave; we used a suite of syndromic surveillance systems to monitor the impact of the heatwave. Significant increases in heatstroke and sunstroke were observed during 7-10 July 2013. Syndromic surveillance provided an innovative and effective service, supporting heatwave planning and providing early warning of the impact of extreme heat thereby improving the public health response to heatwaves.

A concept for routine emergency-care data-based syndromic surveillance in Europe

We developed a syndromic surveillance (SyS) concept using emergency dispatch, ambulance and emergency-department data from different European countries. Based on an inventory of sub-national emergency data availability in 12 countries, we propose framework definitions for specific syndromes and a SyS system design. We tested the concept by retrospectively applying cumulative sum and spatio-temporal cluster analyses for the detection of local gastrointestinal outbreaks in four countries and comparing the results with notifiable disease reporting. Routine emergency data was available daily and electronically in 11 regions, following a common structure. We identified two gastrointestinal outbreaks in two countries; one was confirmed as a norovirus outbreak. We detected 1/147 notified outbreaks. Emergency-care data-based SyS can supplement local surveillance with near real-time information on gastrointestinal patients, especially in special circumstances, e.g. foreign tourists. It most likely cannot detect the majority of local gastrointestinal outbreaks with few, mild or dispersed cases.