Assessment of ambulance dispatch data for surveillance of influenza-like illness in Melbourne, Australia
TL;DR: The ambulance dispatch data displayed seasonal trends that were similar to those observed in locum service surveillance and GP sentinel systems, and identified the years with higher-than-expected seasonal ILI activity.
About: This article is published in Public Health.The article was published on 2009-02-01 and is currently open access. It has received 25 citations till now. The article focuses on the topics: Influenza-like illness.
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TL;DR: The prevalence of antibodies reactive to the 2009 pandemic influenza A(H1N1) was determined in sera collected before the start of the pandemic, during the early phase, and after the main epidemic wave and nationwide vaccination campaign in Norway.
Abstract: The prevalence of antibodies reactive to the 2009 pandemic influenza A(H1N1) was determined in sera collected before the start of the pandemic, during the early phase, and after the main epidemic wave and nationwide vaccination campaign in Norway. A substantial rise in prevalence of antibodies at protective titres, from 3.2% to 44.9%, was observed between August 2009 and January 2010. The highest prevalence, 65.3%, was seen in the age group of 10-19 year-olds.
73 citations
TL;DR: The results further demonstrate the acute impact of short term air pollution episodes on public health and also illustrate the potential role of mass media reporting in escalating health care seeking behaviour.
43 citations
Cites background from "Assessment of ambulance dispatch da..."
...The meteorological driver behind these episodes was a high pressure system, which slowed the circulation of air across North West Europe (Dawson, 2014)....
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TL;DR: In this paper, the authors examined the validity and timeliness of the entire chain of EMS data sources from three European regions for common syndromic influenza surveillance during the A(H1N1) influenza pandemic in 2009.
Abstract: Emergency medical service (EMS) data, particularly from the emergency department (ED), is a common source of information for syndromic surveillance. However, the entire EMS chain, consists of both out-of-hospital and in-hospital services. Differences in validity and timeliness across these data sources so far have not been studied. Neither have the differences in validity and timeliness of this data from different European countries. In this paper we examine the validity and timeliness of the entire chain of EMS data sources from three European regions for common syndromic influenza surveillance during the A(H1N1) influenza pandemic in 2009. We gathered local, regional, or national information on influenza-like illness (ILI) or respiratory syndrome from an Austrian Emergency Medical Dispatch Service (EMD-AT), an Austrian and Belgian ambulance services (EP-AT, EP-BE) and from a Belgian and Spanish emergency department (ED-BE, ED-ES). We examined the timeliness of the EMS data in identifying the beginning of the autumn/winter wave of pandemic A(H1N1) influenza as compared to the reference data. Additionally, we determined the sensitivity and specificity of an aberration detection algorithm (Poisson CUSUM) in EMS data sources for detecting the autumn/winter wave of the A(H1N1) influenza pandemic. The ED-ES data demonstrated the most favourable validity, followed by the ED-BE data. The beginning of the autumn/winter wave of pandemic A(H1N1) influenza was identified eight days in advance in ED-BE data. The EP data performed stronger in data sets for large catchment areas (EP-BE) and identified the beginning of the autumn/winter wave almost at the same time as the reference data (time lag +2 days). EMD data exhibited timely identification of the autumn/winter wave of A(H1N1) but demonstrated weak validity measures. In this study ED data exhibited the most favourable performance in terms of validity and timeliness for syndromic influenza surveillance, along with EP data for large catchment areas. For the other data sources performance assessment delivered no clear results. The study shows that routinely collected data from EMS providers can augment and enhance public health surveillance of influenza by providing information during health crises in which such information must be both timely and readily obtainable.
20 citations
TL;DR: To enhance surveillance for influenza-like illness (ILI) in Denmark, a year-round electronic reporting system was established in collaboration with the Danish medical on-call service (DMOS) and a system for daily transfer of data to the national surveillance centre was implemented.
Abstract: To enhance surveillance for influenza-like illness (ILI)in Denmark, a year-round electronic reporting system was established in collaboration with the Danish medical on-call service (DMOS). In order to achieve real-time surveillance of ILI, a checkbox for ILI was inserted in the electronic health record and a system for daily transfer of data to the national surveillance centre was implemented. The weekly number of all consultations in DMOS was around 60,000, and activity of ILI peaked in week 46 of 2009 when 9.5% of 73,723 consultations were classified as ILI. The incidence of ILI reached a maximum on 16 November 2009 for individuals between five and 24 years of age, followed by peaks in children under five years, adults aged between 25 and 64 years and on 27 November in senior citizens(65 years old or older). In addition to the established influenza surveillance system, this novel system was useful because it was timelier than the sentinel surveillance system and allowed for a detailed situational analysis including subgroup analysis on a daily basis.
18 citations
Cites background from "Assessment of ambulance dispatch da..."
...Other systems for influenza surveillance, including traditional surveillance for consultation of general practitioners for ILI or acute respiratory infections within their working hours, ambulance dispatches [5,6] and hospital admissions [7,8], may in emergencies or in times of lack of resources become ‘saturated’....
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TL;DR: There was an increase in the number of studies using forecasting methods and studies applying machine learning methods, hidden Markov models, and Bayesian framework to multivariate datasets, but these methods do not appear to be used widely in public health practice.
17 citations
References
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4,805 citations
TL;DR: In this article, it was shown that Page's stopping time is optimal for the detection of changes in distributions, in a well defined sense, which is a generalization of an existing result where it was proved that Page stopping time was optimal asymptotically.
Abstract: It is shown that Page's stopping time is optimal for the detection of changes in distributions, in a well defined sense This work is a generalization of an existing result where it was shown that Page's stopping time is optimal asymptotically
1,032 citations
"Assessment of ambulance dispatch da..." refers methods in this paper
...16 To generate signals for the ambulance data, the log likelihood ratio (LLR) form of the CUSUM was used, which is optimal, in a statistical sense, for detecting abrupt shifts from the baseline.(17) For a binomial process (i....
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TL;DR: There are many applications of control charts in health-care monitoring and in public-health surveillance as mentioned in this paper, and these applications to industrial practitioners and discuss some of the ideas that arise that may be applicable in industrial monitoring.
Abstract: There are many applications of control charts in health-care monitoring and in public-health surveillance. We introduce these applications to industrial practitioners and discuss some of the ideas that arise that may be applicable in industrial monitoring. The advantages and disadvantages of the charting methods proposed in the health-care and public-health areas are considered. Some additional contributions in the industrial statistical process control literature relevant to this area are given. There are many application and research opportunities available in the use of control charts for health-related monitoring.
497 citations
Journal Article•
TL;DR: There are many applications of control charts in health-care monitoring and in public-health surveillance as mentioned in this paper, and these applications to industrial practitioners and discuss some of the ideas that arise that may be applicable in industrial monitoring.
Abstract: There are many applications of control charts in health-care monitoring and in public-health surveillance. We introduce these applications to industrial practitioners and discuss some of the ideas that arise that may be applicable in industrial monitoring. The advantages and disadvantages of the charting methods proposed in the health-care and public-health areas are considered. Some additional contributions in the industrial statistical process control literature relevant to this area are given. There are many application and research opportunities available in the use of control charts for health-related monitoring.
481 citations
TL;DR: A new CUSUM procedure is described that adjusts for each patient's pre-operative risk of surgical failure through the use of a likelihood-based scoring method that is ideally suited for settings where there is a variable mix of patients over time.
Abstract: The cumulative sum (CUSUM) procedure is a graphical method that is widely used for quality monitoring in industrial settings. More recently it has been used to monitor surgical outcomes whereby it 'signals' if sufficient evidence has accumulated that there has been a change in the surgical failure rate. A limitation of the standard CUSUM procedure in this context is that since it is simply based on the observed surgical outcomes, it may signal as a result of changes in the referral pattern, such as an increased proportion of high-risk patients, rather than due to a change in the actual surgical performance. We describe a new CUSUM procedure that adjusts for each patient's pre-operative risk of surgical failure through the use of a likelihood-based scoring method. The procedure is therefore ideally suited for settings where there is a variable mix of patients over time.
418 citations