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Influenza-Like-Illness (ILI)

Description

Syndromic surveillance of health care data such as the International Classification of Diseases, Ninth Revision (ICD-9), codes related to Influenza-Like-Illness (ILI), was used to track the progression of the 2009 Fall Novel H1N1 Outbreak in the Madison area. Early studies focused on prediction of an outbreak, however further investigation of patient resource utilization would be helpful in developing an action plan for addressing community and patient needs during future outbreaks. There is a paucity of research comparing emergency department (ED) and urgent care utilization rates during the 2009 Novel H1N1 Pandemic, though there is regional data suggesting that urgent care centers bore a larger portion of the burden of H1N1 influenza than emergency departments. Furthermore, one group found that ILI related phone calls to urgent care centers predicted influenza outbreak at least one week ahead of peaks in the ILI hospital care consultation rates. ED data on its own has proven useful for public health disease surveillance and many studies group urgent care and ED care together. The literature is lacking subgroup analysis of these two very different care environments. Understanding the correlation between urgent care and ED utilization rates will provide a more in depth understanding of the stress that the 2009 Fall Novel H1N1 placed on community resources in our geographic region.

 

Objective

To compare the proportion of patients presenting with ILI to urgent care centers versus the ED during the 2009 Fall Novel H1N1 Outbreak.

Submitted by elamb on
Description

Using an electronic health record (EHR) system, we tracked an outpatient population from a series of primary care providers to identify influenza-like illness (ILI) as part of a multi-state effort directed by the Centers for Disease Control and Prevention. From these patients, we also collected de-identified project-specific information and symptoms using an electronic template to evaluate possible differences among patient groupings as well as longitudinal population patterns.

 

Objective

Evaluate the use of an EHR network to track ILI incidence in an outpatient population and using laboratory testing, identify influenza cases by subtype as well as other respiratory viruses.

Submitted by elamb on
Description

Outbreaks of Avian influenza (AI) in poultry were first reported in Nigeria in 2006 (1). The only human case was reported in 2007 (1). The epizootics of AI among poultry and wild birds and subsequent risk to human health highlighted the need to detect influenza viruses with pandemic potential and for establishment of Influenza Sentinel Surveillance (ISS) System. This is to aid the description of the the epidemiology and burden of seasonal human influenza, to provide information for public health decision making, for program planning and preparedness and to serve as an early warning for outbreaks of Avian or pandemic flu. Also, to characterize and monitor trends in illnesses and deaths attributable to SARI (2). Lagos State University Teaching Hospital (LASUTH) is one of the 4 sites for ISS in Nigeria and started functioning in 2009.

Objective

To analyze the Lagos site of the National Influenza Sentinel Surveillance (NISS) system and to determine the viruses responsible for Influenza-like illnesses (ILI) and Severe Acute Respiratory Infection (SARI).

Submitted by knowledge_repo… on
Description

MOH's national sentinel surveillance programme for influenza is part of the WHO international laboratory-based surveillance network to detect the emergence and spread of new antigenic variants of influenza viruses. Virological sample collection is on-going and is carried out during both outbreak and non-outbreak periods.In 2011 and 2012, the sentinel surveillance programme involved a total of 169 sites (18 government primary care clinics and 151 private/general practitioner [GP] clinics).

Objective

 We evaluated the Singapore Ministry of Health's sentinel surveillance system for influenza virus, which included the monitoring of virological samples from patients with influenza-like illness (ILI) seen at government primary care clinics and private general practitioner clinics in 2011-12.

Submitted by knowledge_repo… on
Description

The objective of this report is to describe the variation of symptoms being detected as respiratory or influenza-like illness (ILI) syndrome using nurse advice call center (NACC) data and emergency department (ED) chief complaint data compared to laboratory data from one hospital.

Submitted by elamb on
Description

To determine sensitivity and specificity of syndromic surveillance of influenza based on data from SOS Medecins, a healthcare network of emergency general practitioners (GP) in Bordeaux, France.

Submitted by elamb on
Description

Influenza affects millions of people and causes about 36,000 deaths in the United States each winter. Pandemics of influenza emerge at irregular intervals. National influenza surveillance is used to detect the emergence and spread of influenza virus variants and to monitor influenza-related morbidity and mortality. Existing surveillance consists of seven data types, which are reported weekly. Newly available national electronic data sources created as part of the routine delivery of medical care might supplement current data sources. Nurse call data offer national coverage, are timely, and do not require any extra manual data entry. Using such data for influenza-like illness (ILI) surveillance may lead to earlier detection of ILI in the community, both because people with ILI may call a nurse line before seeking care at a health-care facility and because the data are more timely than existing weekly data.

 

Objective

Our purpose was to compare nurse call data for respiratory and ILI against CDC national influenza surveillance data from the 2004-2005 season by region to determine if the call data were informative and might allow earlier detection of influenza activity.

Submitted by elamb on
Description

The New York State (NYS) Medicaid Program provides healthcare for 34% of the population in New York City (NYC) and 4%-20% in each of the 57 county populations up-state. Prescription data are collected through the sub-mission of claims forms to the Medicaid Program and transmitted daily to the NYS Syndromic Surveillance Program as summary counts by drug category and patient’s ZIP Code, age category, and sex. One of the 18 drug categories is influenza agents, which in-cludes rimantadine, oseltamivir, and zanamivir.

For surveillance of influenza-like illness (ILI) activity, the NYS and NYC Sentinel Physician Influenza Surveillance Program collects from sentinel physicians weekly reports of the total number of patients seen and the number of patients presenting with ILI (defined as temperature > 100 degrees F, presence of cough or sore throat, and absence of other known cause of these symptoms). Not all counties in NYS have sentinel physicians: in the 2003-2004 flu surveillance season (Week 40, in early October, 2003, to Week 20, in late May, 2004), 37 of 57 upstate counties and all 5 counties of NYC had sentinel physicians.

 

Objective

To evaluate the usefulness of daily counts of prescriptions for influenza agents charged to Medicaid insurance, by county of residence of the recipient, for detection of elevated ILI in NYS, currently monitored through physicians participating in the CDC Influenza Surveillance Program.

Submitted by elamb on
Description

Previous reports from participating facilities in North Dakota illustrated that ILI syndrome data from syndromic surveillance data, which is based on chief complaints logs, had a close correlation to the traditional ILI surveillance and that frequency slope of the ILI syndrome was also closely correlated to that of the cases that tested positive for influenza. The facility used in this report submits ICD-9 codes to the North Dakota Department of Health (NDDoH). By comparing the NDDoH ILI syndrome to influenza laboratory testing data and ICD-9 code specific to influenza (487) we found that syndromic surveillance data for ILI closely followed the influenza testing trend as well as the ICD-9 code trend.

Objective

The objective of this report is to evaluate the correlation between influenza-like illness (ILI) syndrome classification using chief complaint data and discharge diagnosis International Classification of Disease, Ninth Revision (ICD-9) code for influenza with the laboratory data from one hospital in North Dakota over a period of three influenza seasons.

Submitted by elamb on
Description

One of the significant challenges that multi-user biosurveillance systems have is alarm management. Currently deployed syndromic surveillance systems [1–3] have a single user interface. However, different users have different objectives; the alarms that are important for one category of user are irrelevant to the objectives of another category of user. For example, a physician wants to identify disease on an individual-patient level, a county health authority is interested in identifying disease outbreak as early as possible within his local region, while an epidemiologist at the national level is interested in global situational awareness. The objective of a multi-agent decision support system is not only to recognize patterns of epidemiologically significant events but also to indicate their relevance to particular user groups’ objectives. Thus, instead of simply providing alerts of anomaly detections, the system architecture needs to provide analyzed information supporting multiple users’ decisions.

Submitted by elamb on