Infectious Disease

Drug sales data as an early indicator in syndromic surveillance has attracted particular interest in recent years, however previous studies were mostly conducted in developed countries or areas. In China, many people (around 60%) choose self-medication as their first option when they encounter a health problem, and electronic sales information system is gradually used by retail pharmacies, which makes drug sales data become a promising data source for syndromic surveillance in China.

Objective

To use an unconventional data - pharmaceutical sales surveillance for the early detection of respiratory and gastrointestinal epidemics in rural China.

Norovirus infection results in considerable morbidity in the United States where an estimated 21 million illnesses, 70,000 hospitalizations, and 800 deaths are caused by NV annually. Additionally, NV is responsible for approximately 50% of foodborne outbreaks. Between January 2008 and June 2012, 875 NV outbreaks were reported to the Virginia Department of Health (VDH). To assist in detecting possible disease outbreaks such as NV, VDH utilizes the web-based Electronic Surveillance System for Early Notification of Community-based Epidemics (ESSENCE) to monitor and detect public health events across Virginia. ESSENCE performs automated parsing of chief complaint text into 10 syndrome categories, including a non-specific GI syndrome that serves as a proxy for GI illnesses like NV.

Objective

To assess the relationship between emergency department and urgent care center chief complaint data for gastrointestinal illness and reported norovirus (NV) outbreaks to develop an early warning tool for NV outbreak activity. The tool will provide an indicator of increasing NV outbreak activity in the community allowing for earlier public health action to mitigate NV outbreaks.

The nation’s first operational infectious disease forecast station, modeled after warning protocols developed in the meteorology community, was activated in 2011. The approach was originally pioneered in Haiti following the 2010 earthquake.

Objective:

To evaluate the sociological effect on indigenous biological event signature recognition and community resilience due to the operational activities of an infectious disease forecast station.

 

Local, national, and global infectious disease surveillance systems have been implemented to meet the demands of monitoring, detecting, and reporting disease outbreaks and prevalence. Varying surveillance goals and geographic reach have led to multiple and disparate systems, each using unique combinations of data streams to meet surveillance criteria. In order to assess the utility and effectiveness of different data streams for global disease surveillance, a comprehensive survey of current human, animal, plant, and marine surveillance systems and data streams was undertaken. Information regarding surveillance systems and data streams has been (and continues to be) systematically culled from websites, peer-reviewed literature, government documents, and subject-matter expert consultations.

Objective:

The goal of this project is to identify systems and data streams relevant for infectious disease biosurveillance. This effort is part of a larger project evaluating existing and potential data streams for use in local, national, and international infectious disease surveillance systems with the intent of developing tools to provide decision-makers with timely information to predict, prepare for, and mitigate the spread of disease.

 

To develop and implement an effective program of rabies eradication in Ukraine in 2008 was founded the unique collection of samples of pathological materials confirmed as positive in rabies at the regional veterinary laboratories of Ukraine. The collection is constantly updated and to present moment it includes 1389 samples from all regions of Ukraine, selected from 17 animal species and humans.

Objective:

To identify the presence of genetic clusters of rabies virus at the territory of Ukraine and to determine the degree of activity of rabies vaccines against these genetic clusters.

 

The livestock sector is vital to the socio-economic development of Nigeria; it contributes about 9-10% of agricultural GDP. Livestock represents an important source of high quality animal protein pro- viding about 36.5 % of total protein intake of Nigerians (1). Lagos State, located in the south-western part of Nigeria, has the smallest landmass (3577 sq. km) and the highest human population density (2519.75 per sq. km) in the Country (2). The State has a poultry pop- ulation of 2.5 million birds and the largest outlet for poultry products with 207 Live bird markets, 375 poultry farms and a large number of poultry products consumers (3). Avian influenza (“bird flu”) is an in- fectious disease of birds caused by type A strains of the influenza virus. The infection is known to cross species barrier to infect hu- mans (4). Between March 2006 and September 2007 Avian influenza (AI) outbreaks occurred in 99 poultry farms in Lagos State (3). The only human case of AI in Nigeria was detected at a health facility in Lagos in January 2007.

Objective

To assess the collaborative efforts in Avian Influenza control that could be harnessed for the control of other Zoonotic diseases.

Mayotte Island, a French overseas department of around 374 km2 and 200 000 inhabitants is located in the North of Mozambique Channel in the Indian Ocean (Figure1). In response to the threat of the pandemic influenza A(H1N1)2009 virus emergence, a syndromic surveillance system has been implemented in order to monitor its spread and its impact on public health (1). This surveillance system which proved to be useful during the influenza pandemic, has been maintained in order to detect infection diseases outbreaks.

Objective

To present the usefulness of syndromic surveillance for the detection of infectious diseases outbreak in small islands, based on the experience of Mayotte.

Screening for Influenza Like Illness (ILI) is an important infection control activity within emergency departments (ED). When ILI screening is routinely completed in the ED it becomes clinically useful in isolating potentially infectious persons and protecting others from exposure to disease. When routinely collected, ILI screening in an electronic clinical application, with real time reporting, can be useful in Public Health surveillance activities and can support resource allocation decisions e.g. increasing decontamination cleaning. However, the reliability of documentation is unproven. Efforts to support the adoption of ILI screening documentation in a computer application, without mandatory field support, can lead to long term success and increased adherence.

The Biological Threat Reduction Program (BTRP) has been being implemented in the Republic of Uzbekistan since 2004 within the framework of the Agreement between the Government of the Republic of Uzbekistan and the Government of the United States of America Concerning Cooperation in the Area of the Promotion of Defense Relations and the Prevention of Proliferation of Weapons of Mass Destruction of 06.05.2001. Threat agent detection and response activities that target a list of especially dangerous pathogens are being carried out under the BTRP within the health care system of Uzbekistan. This presentation reviews some of the achievements of the program to date.

Objective:

To review the implementation of the Biological Threat Reduction Program (BTRP) of the U.S. Defense Threat Reduction Agency in the Republic of Uzbekistan since 2004.

 

The standard approaches to simulation include solving of differential equation systems. Such approach is good for obtaining general picture of epidemics (1, 2). When the detailed analysis of epidemics reasons is needed such model becomes insufficient. To overcome the limitations of standard approaches a new one has been offered. The multiagent approach has been offered to be used for representation of the society. Methods of event-driven programming give essential benefits of the processing time of the events (3).

Objective:

To develop multiagent model of hepatitis B (HBV) infection spreading.