Surveillance

Livestock owners normally pay the full cost of disease testing. As a result the number of laboratory submissions is dependent on the owner's perception that testing is beneficial. This decreases the likelihood of an accurate diagnosis and biases the number and type of samples received by a laboratory. Despite these limitations, laboratory data are commonly used for passive disease surveillance. The Ontario Farm-call Surveillance Project (OFSP) analyzed disease-related farm call data supplied by livestock veterinarians. Project goals were to provide a new data source for livestock disease monitoring and to improve the quality of laboratory data. As an incentive for participation, veterinarians were not charged when diagnostic samples were sent to the Animal Health Laboratory (AHL), University of Guelph.

Objective

To evaluate free diagnostic testing as an incentive for compliance with a livestock disease surveillance program.

Public health surveillance (also called field epidemiology) as defined by Centres for Disease Control and Prevention (CDC) is the ongoing systematic, collection, analysis, and interpretation of outcome specific data essential to the planning , implementation and evaluation of public health practises closely integrated with the timely dissemination of this data to those who need to know(1). This modern concept of surveillance includes 3 main features; the systematic collection of all relevant data, orderly consolidation and evaluation of this data and the prompt dissemination of the results to those who need to know (2). The IDSR is a strategy of the WHO Afro region adopted by the member states in 1998 as a regional strategy for strengthening weak national surveillance systems in the African region (3, 4). The DSNOs under the supervision of the Medical Officers of Health (MOHs) are responsible for surveillance activities within their Local Government catchment area. Therefore their role is very crucial to the success of the IDSR strategy. 

Objective

To evaluate the immediate impact of training on Integrated Disease Surveillance and Response (IDSR) on the knowledge of Disease Surveillance and Notification Officers (DSNOs) and the demographic characteristics associated with the change in knowledge.

The spread of infectious diseases is facilitated by human travel. Infectious diseases are often introduced into a population by travelers and then spread among susceptible individuals. Likewise uninfected susceptible travelers can move into populations sustaining the spread of an infectious disease.

Several disease-modeling efforts have incorporated travel data (e.g., air, train, or subway traffic) as well as census data, all in an effort to better understand the spread of infectious diseases. Unfortunately, most travel data is not fine grained enough to capture individual movements over long periods and large spaces. It does not, for example, document what happens when people get off a train or airplane. Thus, other methods have been suggested to measure how people move, including both the tracking of currency and movement of individuals using cell phone data. Although these data are finer grained, they have their own limitations (e.g., sparseness) and are not generally available for research purposes.

FourSquare is a social media application that permits users to "check-in" (i.e., record their current location at stores, restaurants, etc.) via their mobile telephones in exchange for incentives (e.g., location-specific coupons). FourSquare and similar applications (Gowalla, Yelp, etc.) generally broadcast each check-in via Twitter or Facebook; in addition, some GPS-enabled mobile Twitter clients add explicit geocodes to individual tweets.

Here, we propose the use of geocoded social media data as a real-time fine-grained proxy for human travel.

Objective

To use sequential, geocoded social media data as a proxy for human movement to support both disease surveillance and disease modeling efforts.

Noroviruses are the single most common cause of epidemic, non-bacterial gastroenteritis worldwide. NoVs cause an estimated 68-80% of gastroenteritis outbreaks in industrialized countries and possibly more in developing countries.

Objective

The purpose of this study was to identify global epidemiologic trends in human norovirus (NoV) outbreaks by transmission route and setting, and describe relationships between these characteristics, attack rates and the occurrence of genogroup I (GI) or genogroup II (GII) strains in outbreaks.

In Reunion Island, the non-specific surveillance was mainly developed during A(H1N1) influenza pandemic in 2009. In March 2010, a new surveillance system was implemented from National Health Insurance data. This monitoring was based on the weekly consultation number and home visits by general practitioners.

Objective

To assess the ability to detect an unusual health event from National Health Insurance data.

NPDS is a national database of detailed information collected from each call, uploaded in near real-time, from the 57 participating regional poison centers (PCs) located across the US. NPDS is owned and operated by the American Association of Poison Control Centers (AAPCC). Since 2001, scientists from the Centers for Disease Control and Prevention collaborated with AAPCC to use NPDS for surveillance of chemical, poison and radiological exposures. In March of 2011, a 9.0 magnitude earthquake and tsunami damaged the reactors at the Fukushima Daiichi nuclear power plant in Japan, causing a radiological incident classified as a "major accident" according to the International Nuclear Event Scale. The incident resulted in the release of radioactive iodine (I-131) into the global environment, which was detected in precipitation in parts of the United States. While no adverse health effects were expected, concerned citizens contacted public health officials at the local, state and federal levels. Many started to acquire and use potassium iodide (KI) and other iodide-containing products intended for thyroid protection from I-131, even though this was not a public health recommendation by state and federal public health agencies. Shortly after international media coverage began, regional PCs began receiving calls regarding the Japan radiological incident. State and federal health officials were interested in identifying health communication needs and targeting risk communication messages to address radiation concerns and KI usage recommendations as part of the public health response. This was done in part through NPDS-based surveillance.

Objective

To describe how the National Poison Data System (NPDS) was used for surveillance of individuals with potential incident-related exposures in the United States resulting from the Japan earthquake radiological incident of 2011. Our secondary objective is to briefly describe the process used to confirm exposures identified through NPDS-based surveillance.

Although heat illness is preventable, it is a leading cause of death among U.S. high school and college athletes (1). Despite this, the total burden of heat illness during sports and recreation is unknown. With over 250 million U.S. residents reporting occasional participation in sports or recreational activities (2), there is a large population at risk.

Objective

To examine the incidence and characteristics of heat illness during sports and recreation.

After the 2009 H1N1 influenza pandemic, CDC initiated community-based surveillance of self-reported influenza-like illness (ILI)[1], defined as the presence of fever with cough or sore throat. Although ILI is frequently attributed to other pathogens, including rhinovirus, routine surveillance of ILI at the population level does aid in the detection of nascent influenza outbreaks. In the United States, approximately 90% of influenza-related deaths occur among adults aged 65 years and older[2]. We explored the association of influenza vaccination with ILI, among this vulnerable age group.

Objective

To explore the association of influenza vaccination with Influenza-like illness ( ILI) among adults aged 65 years and older

Syndromic surveillance systems use electronic health-related data to support near-real time disease surveillance. Over the last 10 years, the use of ILI syndromes defined from emergency department (ED) data has become an increasingly accepted strategy for public health influenza surveillance at the local and national levels. However, various ILI definitions exist and few studies have used patient-level data to describe validity for influenza specifically.

Objective

Estimate and compare the accuracy of various ILI syndromes for detecting lab-confirmed influenza in children.

Historically, it has been the role of local health departments to administer, monitor, and report flu vaccinations of its residents to the state health department. In 2009, the looming threat of an influenza outbreak (H1N1) led to the extension of the Public Readiness and Emergency Preparedness Act (PREP) (1). On June 15, 2009, Kathleen Sebelius, Secretary of Health and Human Services, assigned all entities, including organizational and individual, tort liability immunity in the distribution and administration of H1N1 vaccines (1). This extension subsequently impaired local health departments ability to capture accurate estimates of flu immunizations being administered to their respective populations. Stark County Health Department, located in Ohio, in collaboration with Kent State University's College of Public Health, designed, developed, and deployed FITS based on the urgent need of accurate population data regarding influenza immunization at the county level.

Objective

To develop and implement a web-based, county-level flu immunization record keeping system that accurately tracks non-identifiable vaccine recipients and seamlessly uploads to the state record keeping system.