Nonparametric Models for Identifying Gaps in Message Feeds

Timely and accurate syndromic surveillance depends on continuous data feeds from healthcare facilities. Typical outlier detection methodologies in syndromic surveillance compare predictions of counts for an interval to observed event counts, either to detect increases in volume associated with public health incidents or decreases in volume associated with compromised data transmission.

January 25, 2018

A pilot project to identify individuals who died from suicide and visited an ED before death

In 2015, suicide was the 8th leading cause of death in Salt Lake County, Utah, and has recently been identified as a priority public health issue. For suicide, suicide ideation and suicide attempts surveillance, Salt Lake County Health Department staff use National Violent Death Reporting System (NVDRS) mortality data to monitor historical trends and vital records mortality data and ESSENCE ED encounter morbidity data to monitor trends and populations in real time.

January 25, 2018

Wearable Sensor Application for Integrated Early Warning and Health Surveillance

Wearable devices are a low cost, minimally invasive way to monitor health. Sensor data provides real-time physiological indictors of an individual’s health status without the requirement of health care professionals or facilities. Information gleamed from wearable sensors can be used to better understand physiological stressors and prodromal symptoms. In addition, this data can be used to monitor individuals that are in high risk of health-related problems.

January 25, 2018

Detecting Public Health Impacts Associated with Air Pollution Events in the UK Using Syndromic Surveillance

Air pollution is well documented to cause adverse health effects in the population. Epidemiological/toxicological studies have demonstrated that air pollution is associated with various adverse health outcomes, ranging from mortality to subclinical respiratory symptoms. Classical epidemiological studies of the health effects of air pollution are typically retrospective. In order to assess the effectiveness of any public health messages or interventions in a timely manner there is a need to be able to systematically detect any health effects occurring in real-time.

August 22, 2018

Surveillance of Overdose-related Emergency Department Visits in Rhode Island

During March-May 2013, 14 overdose deaths occurred in RI that were caused by acetyl fentanyl, a novel synthetic opioid about five times more potent than heroin1. Ten of these deaths were clustered in March, causing a significant increase over baseline of monthly illicit drug overdose deaths in RI1. Overdose deaths are well described in RI by forensic toxicology testing results. However, the overall number of ED visits associated with this event was unknown. We used RODS data retrospectively to characterize overdose related ED visits in RI and to analyze trends.

May 02, 2019

Monitoring the Impact of Heat Waves with Emergency Service Utilization Data in Los Angeles County

Los Angeles County’s (LAC) early event detection system captures over 60% of total ED visits, as well as 800 to 1,000 emergency dispatch calls from Los Angeles City Fire (LACF) daily. Both ED visits and EDC calls are classified into syndrome categories, and then analyzed for aberrations in count and spatial distribution. During periods of high temperatures, a heat report is generated and sent to stakeholders upon request.

June 25, 2018

Real-time estimation and prediction for pandemic A/H1N1 (2009) in Japan

Unfortunately, confirmation and notification of all A/H1N1 (2009) patients in Japan was ceased on 24 July when the cumulative number of patients was about 5000. After that, as all suspected patients are not necessarily confirmed or reported, the only official surveillance was the sentinel surveillance for influenza-like-illness (ILI) patients from 5000 clinics accounting for almost 10% of all clinics and hospitals in Japan. However, because the surveillance results are reported weekly, it tends to lack timeliness.

June 21, 2019

Real-time, reusable, dynamic public health surveillance

The resources available in most public health departments are limited. Access to trained technical personnel and stateof-the-art computing resources are also lacking. Customizable off-the-shelf systems contribute only to creation of information silos, are expensive, and not affordable by the limited budget available to the departments of health (only growing worse with the recession). The one thing that has increased is the need for surveillance in more areas, from diseases to environmental exposures to unexpected disasters.

June 24, 2019

Real Time Syndromic Surveillance Response to UK Flooding Incident 2007

Wetter and stormier weather is predicted in the UK as global temperatures rise. It is likely there will be increases in river and coastal flooding. The known short and medium term health effects of flooding are drowning, injury, acute asthma, skin rashes and outbreaks of gastrointestinal and respiratory disease. Longer term health effects of flooding are thought to be psychological stress and increased rates of mental illness. Reacher et al. conducted a retrospective study of illness in a population affected by flooding in Lewes, South-East England during 2000 [1].

July 30, 2018

GUARDIAN: Geographic Utilization of Artificial Intelligence in Real-Time for Disease Identification and Notification

Real-time disease surveillance is critical for early detection of the covert release of a biological threat agent (BTA). Numerous software applications have been developed to detect emerging disease clusters resulting from either naturally occurring phenomena or from occult acts of bioterrorism. However, these do not focus adequately on the diagnosis of BTA infection in proportion to the potential risk to public health.

July 30, 2018

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National Syndromic
Surveillance Program

Email:nssp@cdc.gov

The National Syndromic Surveillance Program (NSSP) is a collaboration among states and public health jurisdictions that contribute data to the BioSense Platform, public health practitioners who use local syndromic surveillance systems, Center for Disease Control and Prevention programs, other federal agencies, partner organizations, hospitals, healthcare professionals, and academic institutions.

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