Outbreak Detection

Nontyphoidal Salmonella, consisting of >2,500 distinct serotypes, is the leading bacterial agent of foodborne illness in the U.S., causing an estimated 1 million infections per year. In NYC, interviews of all case-patients (N≈1,100 annually) are attempted to support outbreak investigation and control. Salmonella clusters in NYC are typically identified either by notification from PulseNet, CDC, or other health departments or by a weekly analysis using the historical limits method. More systematic and timely cluster detection could inform resource prioritization and improve the effectiveness of public health interventions. We initiated daily analyses in May 2015 to detect spatio-temporal clusters by serotype among cases since February 23. In July 2015, an analysis was added to detect purely temporal clusters among cases since May 1.

Objective

To prospectively identify serotype-specific clusters of salmonellosis in New York City (NYC).

Anthrax is an acute especially dangerous infectious disease of animals and humans. Bacillus anthracis is a potential bioterrorism tool. In Ukraine, there are favorable natural conditions for the spread of anthrax. There are 13.5 thousand of constantly anthrax-troubled points. Anthrax epidemic situation in Ukraine could be characterized as unstable. Because of the continuing reform of Ukrainian human health entities, the State Sanitary Epidemiological Service (SSES) has lost its control functions and is remaining in an uncertain state, which increases possible risks.

Early detection of outbreaks is crucial in public health surveillance in order to enable rapid control measures. Statistical methods are widely used for outbreak detection but no study has proposed to evaluate and compare thoroughly the performance of these methods.

Objective

Evaluate the performance of 8 statistical methods for outbreak detection in health surveillance with historical data.

In human and animal health, conventional approaches to preventing and controlling GI have not reduced the overall disease burden. In order to understand and mitigate shared GI aetiologies between humans and animals it is necessary to develop One Health Surveillance approaches that integrate data-sources contributed to by human and veterinary healthcare. Such approach is described here.

Objective

To describe how a real-time surveillance system for early detection of gastrointestinal disease (GI) outbreaks in small animal and human health is being developed by collecting electronic health records (EHRs) from veterinary practitioners and a telephone-based 24-hour medical triage service in the UK.

Each year several thousands contract the seasonal flu, and it is estimated that these viruses are responsible for the deaths of over six thousand individuals [1]. Further, when a new strain is detected (e.g. 2009), the result can be substantially more dramatic [2]. Because of the potential threats flu viruses pose, the United States, like many developed countries, has a very well established flu surveillance system consisting of 10 components collecting laboratory data, mortality data, hospitalization data and sentinel outpatient care data [3]. Currently, this surveillance system is estimated to lag behind the actual seasonal outbreak by one to two weeks. As new data streams come online, it is important to understand what added benefit they bring to the flu surveillance system complex. For data streams to be effective, they should provide data in a more timely fashion or provide additional data that current surveillance systems cannot provide. Two types of multiplexed diagnostic tools designed to test syndromically relevant pathogens and wirelessly upload data for rapid integration and interpretation were evaluated to see how they fit into the influenza surveillance scheme in California.

Objective

Evaluate utility of point of need diagnostic tests in relationship to current standard influenza detection methods.

National Influenza Sentinel Surveillance (NISS) was established in Nigeria in 2006 to monitor influenza occurrence in humans in Nigeria and provide a foundation for detecting outbreaks of novel strains of influenza. Surveillance for influenza-like illness (ILI) and severe acute respiratory infection (SARI) is carried out in 4 sentinel sites. Specimens and epidemiological data are collected and transported 4 days a week from the sentinel sites to the National Influenza Reference Laboratory. At the laboratory, they are tested for influenza A and B viruses and further subtyped if positive for influenza A virus.

Objective

To assess the performance of the surveillance system and identify factors affecting the performance.

The World Health Organization (WHO) puts a great emphasis on the study of diseases related to using or consuming poor-quality water and the absence of proper hygiene. Unfortunately, consumption of poor-quality water causes certain diseases in Ukraine.

The World Health Organization (WHO) puts a great emphasis on the study of diseases related to using or consuming poor-quality water and the absence of proper hygiene. Unfortunately, consumption of poor-quality water causes certain diseases in Ukraine.