Infectious Disease

While norovirus is the leading cause of gastroenteritis in the United States, leading to an estimated 21 million illnesses per year [1], timely surveillance data are limited. Google Insights for Search (GIfS) is a new application that allows users to track specific Google search queries during specified time periods and geographic regions [2].

Objective

We compared norovirus syndromic search query trends with existing surveillance data in the United States in order to assess whether GIfS data can be used to monitor norovirus disease.

In March-April, 2011, Salt Lake Valley Health Department (SLVHD) investigated an outbreak of measles (N=9) resulting from a single imported case from Europe. Syndromic surveillance was used to identify measles-like illness (MLI) and enhance early case detection, which is crucial for proper public health intervention [1].

Objective

To detect measles cases during an outbreak using syndromic surveillance.

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

Influenza is a major cause of mortality. In developed countries, mortality is at its highest during winter months, not only as a result of deaths from influenza and pneumonia but also as a result of deaths attributed to other diseases (e.g. cardiovascular disease). Understandably, much of the surveillance of influenza follows predefined geographic regions (e.g. census regions or state boundaries). However, the spread of influenza and its resulting mortality does not respect such boundaries.

Objective

To cluster cities in the United States based on their levels of mortality from influenza and pneumonia.

The threat of epidemics due to non-human strains of influenza A viruses is ever present1. Surveillance is a critical aspect of pandemic preparedness for early case detection2. Identification of the index cases of a pandemic virus can trigger public health mitigation efforts3. To develop an appropriate surveillance process, it is important to understand the two possibilities of pandemic evolution. A new pandemic may begin with mild cases, during which surveillance should be concentrated on work/school absenteeism and in physician offices. The other possibility begins with severe cases, characterized by sCAP, respiratory failure, and ICU admission. As the syndrome of pneumonia is not reportable to health agencies for public health surveillance, a year-round, hospital-based surveillance mechanism may be an important tool for early case detection in the event of an epidemic of sCAP. To fill these gaps, we developed a statewide, hospital-based surveillance network for sCAP surveillance in Kentucky.

Objective

To present the development and implementation of the SIPS project, a statewide, hospital-based surveillance system for severe community-acquired pneumonia (sCAP) in Kentucky.

Much progress has been made on the development of novel systems for influenza surveillance, or explored the choices of algorithms for detecting the start of a peak season. The use of multiple streams of surveillance data has been shown to improve performance but few studies have explored its use in situational awareness to quantify level or trend of disease activity. In this study we propose a multivariate statistical approach which describes overall influenza activity and handles interrupted or drop-in surveillance systems.

Objective

This paper describes the use of multiple influenza surveillance data for situational awareness of influenza activity.

Detection of the signs of HIV epidemic transition from concentrated to generalized stage is an important issue for many countries including Ukraine. Objective and timely detection of the generalization of HIV epidemic is a significant factor for the development and implementation of appropriate preventive programs. As an additional method for estimating HIV epidemic stage, the spatial analysis of the reported new HIV cases among injection drug use (IDU) and other populations (due to sexual way of transmission) has been recommended. For studying new HIV cases in small societies, Relative Risk (RR) rates are preferred over incidence indicators. Spatial clustering based on the calculation of RR rates allows us to locate the high risk areas of HIV infection with greater accuracy. In our opinion, in the process of epidemic generalization the spatial divergence of epidemic will be observed as well. In particular, clusters with high RR of sexual HIV transmission independent from the clusters with high RR of injection HIV transmission may appear.

Objective

To investigate the utility of spatial analysis in the tracking of the stages of the HIV epidemic at an administrative territory level, using the Odessa region, Ukraine as an example.

Hepatitis A virus (HAV) infection is usually mild in childhood but more severe in adolescents and adults'. An estimated 1.4 million cases of HAV infection occur annually in the world. The case-fatality rate among patients of all ages is approximately 0.3%, but tends to be higher among older persons (approximately 2% over 40 years of age). HAV is a notifiable disease on weekly basis where health centers and hospitals report cases to the health directorates which in turn report electronically to the Communicable Diseases Directorate, with subsequent paper reporting of detailed epidemiological description. The due time is Tuesday next week. Diagnosis is clinically based and depends on case definition..A previous study in Jordan revealed that reporting rate increased from 6.4 in 2004 to 7.9 in 2008/100,000, the highest reporting rate was in the North region mainly Mafraq.

Objective

The study aims to asses' HAV surveillance in Mafraq Health directorate, and to determine whether the increase in reporting is related to a public health issue or is a result of a relatively good surveillance.

In April 2009, a novel strain of influenza A was detected in Mexico, which quickly spread to the United States and the rest of the world. In response to the pandemic, the New Hampshire Department of Health and Human Services (NH DHHS) developed a web-based school absenteeism reporting system to track and record overall absenteeism and influenza-like-illness (ILI) related absenteeism in New Hampshire schools.

Objective

To monitor community illness and detect outbreaks during the 2009 influenza A/H1N1 pandemic using a newly developed surveillance system for monitoring school absenteeism.

With an estimated 500 million people infected each year, dengue ranks as one of the most significant mosquito-borne viral human diseases, and one of the most rapidly emerging vectorborne diseases. A variety of obstacles including bureaucracy and lack of resources have interfered with timely detection and reporting of dengue cases in many endemic countries. Surveillance efforts have turned to modern data sources, such as Internet search queries, which have been shown to be effective for monitoring influenza-like illnesses. However, few have evaluated the utility of web search query data for other diseases, especially those of high morbidity and mortality or where a vaccine may not exist.

Objective

We aimed to assess whether web search queries are a viable data source for the early detection and monitoring of dengue epidemics.