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Brownstein John

Description

HealthMap is a real-time disease epidemic intelligence tracking and visualization system that collects information from general news media, individual first-hand reports and public health sources around the world. Gaps in this effort clearly occur during times of crisis where traditional mechanisms may be dismantled. Clinical information gathered by deployed physicians can play a key role in providing early insight on emerging public health threats. We developed OutbreakMD to gather such information in real-time and combine with existing HealthMap informal and formal surveillance techniques. 

Objective

OutbreakMD is a mobile Web application that was piloted in post-earthquake Port-au-Prince, Haiti. The application is designed for collecting, organizing and visualizing clinical information from individual patients to better monitor emerging infectious disease in disaster situations, in situations with limited public health infrastructure and unreliable Internet connectivity

Submitted by uysz on
Description

Antibiotic resistance is a mounting public health threat calling for action on global, national and local levels. Antibiotic use has been a major driver of increasing rates of antibiotic resistance. This has given rise to the practice of antibiotic stewardship, which seeks to reduce unnecessary antibiotic use across different care settings. Antibiotic stewardship has been increasingly applied in hospital settings, but adoption has been slow in many ambulatory care settings including primary care of humans. Uptake of antibiotic stewardship in veterinary care has been similarly limited. Audit and feedback systems of antibiotic use coupled with patterns of antibiotic use and best practice guidelines have proven useful in outpatient settings, but scale-up is limited by heterogeneous systems of care and limited resources.

Objective: To develop, evaluate, and implement a universal online platform - termed OPEN Stewardship - to promote responsible antimicrobial prescribing (antimicrobial stewardship).

Submitted by elamb on
Description

School closure has long been proposed as a non-pharmaceutical intervention in reducing the transmission of pandemic influenza. Children are thought to have high transmission potential because of their low immunity to circulating influenza viruses and high contact rates. In the wake of pandemic (H1N1) 2009, simulation studies suggest that early and sustained school closure might be effective at reducing community-wide transmission of influenza. Determining when to close schools once an outbreak occurs has been difficult. Influenza-related absentee data from Japan were previously used to develop an algorithm to predict an outbreak of influenza-related absenteeism. However, the cause of absenteeism is frequently unavailable, making application of this model difficult in certain settings. For this study, we aimed to evaluate the potential for adapting the Japanese algorithm for use with all-cause absenteeism, using data on the rate of influenza-related nurse visits in

corresponding schools to validate our findings.

 

Objective

To determine the optimal pattern in school-specific all-cause absenteeism for use in informing school closure related to pandemic influenza.

Submitted by hparton on
Description

The BioSense program’s mission is to support and improve public health surveillance infrastructure and human capacity required to monitor (with minimal lag) critical population health indicators of the scope and severity of acute health threats to the public health; and support national, state, and local responses to those threats. This mission is consistent with the 2006 Pandemic All Hazards Preparedness Act, and 2007 Homeland Security Presidential Directive (HSPD-21), both of which call for regional and nationwide public health situational awareness, through an interoperable network of systems, built on existing state and local situational awareness capability.

 

Objective

The objective of this study is that the Centers for Disease Control and Prevention will update the International Society for Disease Surveillance community on the latest activities for the BioSense program redesign (Centers for Disease Control and Prevention, USA).

Referenced File
Submitted by hparton on
Description

The Distribute project began in 2006 as a distributed, syndromic surveillance demonstration project that networked state and local health departments to share aggregate emergency department-based influenza-like illness (ILI) syndrome data. Preliminary work found that local systems often applied syndrome definitions specific to their regions; these definitions were sometimes trusted and understood better than standardized ones because they allowed for regional variations in idiom and coding and were tailored by departments for their own surveillance needs. Originally, sites were asked to send whatever syndrome definition they had found most useful for monitoring ILI. Places using multiple definitions were asked to send their broader, higher count syndrome. In 2008, sites were asked to send both a broad syndrome, and a narrow syndrome specific to ILI.

 

Objective

To describe the initial phase of the ISDS Distribute project ILI syndrome standardization pilot.

Submitted by hparton on
Description

Seasonal influenza epidemics are responsible for over 200,000 hospitalizations in the United States per year, and 39,000 of them are in children. In the United States, the Advisory Committee on Immunization Practices guides immunization practices, including influenza vaccination, with recommendations revised on an annual basis. For the 2006–2007 flu season, the Advisory Committee on Immunization Practices recommendations for influenza vaccination began including healthy children aged 24–59 months (two to four years), a shift that added 10.6 million children to the target group.

Canada has a parallel federal organization, the National Advisory Committee on Immunization, which is responsible for guiding the use of vaccines. Recommendations made by the National Advisory Committee on Immunization and the Advisory Committee on Immunization Practices around seasonal influenza vaccination was concordant until the 2006–2007 season. Starting in the 2010–2011 season, the National Advisory Committee on Immunization has further expanded its recommendations to additional pediatric age groups by including two- to four-year-olds for targeted seasonal influenza vaccination.

We took advantage of this divergence in policy between two neighboring countries with similar annual seasonal influenza epidemics to try to understand the effects of the

policy change in the United States to expand influenza vaccination coverage to other pediatric populations.

 

Objective

The objective of this study is to estimate the effect of expanding recommendations for routine seasonal influenza vaccination to include 24–59-month-old children.

Submitted by hparton on
Description

During the spring of 2009, a public health emergency was declared in response to the emergence of the 2009 Influenza A (H1N1) virus. Owing to the response, timely data were needed to improve situational awareness and to inform public health officials. Traditional influenza surveillance is time-consuming and resource intensive, and electronic data sources are often more timely and resource saving. Collaboration began between the Centers for Disease Control and Prevention (CDC), the International Society for Disease Surveillance, and the Public Health Informatics Institute to expand syndromic Emergency Department (ED) surveillance through the Distribute project.

Distribute collects aggregate, daily or weekly reports of influenza-like illness (ILI) and total patient visits to EDs from participating health jurisdictions, stratified by age group and other variables. Additional variables included the three digit zip code of the patient’s residence as well as the disposition and temperature, however not all jurisdictions collect these variables. Distribute data are typically extracted from ED-based electronic health data systems. The ILI definition is determined by the participating jurisdiction that can be a city, county, or state. At the time of analysis, the network consisted of 33 jurisdictions.

Because ILI data reported to Distribute had not been systematically compared with data reported through other surveillance systems, CDC planned an evaluation of the Distribute data, which included a comparison to the Influenza-like Illness Network (ILINet). 

ILINet is a collaborative effort between the CDC, local and state health departments and primary health care providers. The network currently consists of approximately 3000 healthcare providers in all 50 states, Chicago, the District of Columbia, New York City, and the US Virgin Islands. Enrolled providers send CDC weekly reports via internet or fax that consist of the total number of patients seen for any reason and the number of those patients with ILI by age group. ILI is defined as fever (temperature of X1001F (37.8 1C)) and a cough and/or sore throat in the absence of a known cause other than influenza.

 

Objective

To compare ILI data reported to the Distribute surveillance project to data from an existing influenza surveillance system, the US Outpatient ILINet.

Submitted by hparton on
Description

Public health and medical research on mass gatherings (MGs) are emerging disciplines. MGs present surveillance challenges quite different from routine outbreak monitoring, including prompt detection of outbreaks of an unusual disease. Lack of familiarity with a disease can result in a diagnostic delay; that delay can be reduced or eliminated if potential threats are identified in advance and staff is then trained in those areas. Anticipatory surveillance focuses on disease threats in the countries of origin of MG participants. Surveillance of infectious disease (ID) reports in mass media for those locations allows for adequate preparation of local staff in advance of the MG. In this study, we present a novel approach to ID surveillance for MGs: anticipatory surveillance of mass media to provide early reconnaissance information.

 

Objective

To present the value of early media-based surveillance for infectious disease outbreaks during mass gatherings, and enable participants and organizers to anticipate public health threats.

Submitted by hparton on
Description

The illegal wildlife trade is a multi-faceted, clandestine industry that has led to the disruption of fragile ecosystems, facilitated the spread of pathogens, and has led to the emergence of novel infectious diseases in humans, domestic animals, and native wildlife(1, 2). The trade is as diverse as it is large, with live and dead wildlife representing multiple species sold to satisfy human demands for food, medicine, pets and trophies. Wildlife are harvested at astonishing numbers and used for such things as exotic pets, ornamental jewelry and clothing, and traditional Chinese medicine(3). An estimated 75% of recently emerging infectious diseases originated from animals(4), which can include both live animals and animal products.

Objective

We aim to develop an automated, real-time, comprehensive, global system for monitoring official and unofficial reports of illegal wildlife trade activity, and to determine potential hot-spot regions for emerging zoonotic pathogens along commonly utilized illegal wildlife trade routes.

Submitted by elamb on
Description

A devastating cholera outbreak began in Haiti in 2010. Sequencing of Vibrio cholerae isolates showed that the epidemic was likely the result of the introduction of cholera from a distant geographic source. The same strain of cholera was detected in other countries within 100 days. The unique instigation and geographic spread of this epidemic highlight the need for improvements in timely global outbreak surveillance. Novel information sources have been shown to provide early information about public health events and disease epidemiology. Particularly, volume of Internet metrics such as web searches or micro-blogs have been shown to be a good corollary for public health events. In this study, we evaluate geographic trends in online social media following an infectious disease outbreak to determine whether this may enable prediction of secondary outbreak locations.

 

Objective

To evaluate the association between and develop a risk model relating geographic trends of social media and spread of an infectious disease outbreak.

Submitted by elamb on