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Infectious Diseases

The EPA Water Security initiative contamination warning system detection strategy involves the use of multiple monitoring and surveillance components for timely detection of drinking water contamination in the distribution system. The public health surveillance (PHS) component of the contamination warning system involves the analysis of health-related data to identify disease events that may stem from drinking water contamination. Public health data include hospital admission reports, infectious disease surveillance, emergency medical service reports, 911 calls and poison control center calls. Automated analysis of these data streams results in alerts, which are investigated by health department epidemiologists. A comprehensive operational strategy was developed to describe the processes and procedures involved in the the initial investigation and validation of a PHS alert. The operational strategy established specific roles and responsibilities, and detailed procedural flow descriptions. The procedural flow concluded with the determination of whether or not an alert generated from surveillance of public health data streams is indicative of a possible water contamination incident.

 

Objective

To develop standard operating procedures to identify or rule out possible water contamination as a cause for a syndromic surveillance alarm.

Referenced File
Submitted by hparton on

As part of the United States Department of Defense strategy to counter biological threats, the Defense Threat Reduction Agency’s biological threat reduction program is enhancing the capabilities of countries in the former Soviet Union (FSU) to detect, diagnose, and report endemic and epidemic, manmade or natural cases of especially dangerous pathogens. During these engagements, it is noted that Western-trained and Soviet-trained epidemiologists have difficulty, beyond that of simple translation, in exchanging ideas. 

Before 1991, infectious disease surveillance in the FSU was centrally planned in Moscow. The methodologies of infectious disease surveillance and data analysis have remained almost unaltered since this time in most nations of the FSU. Vlassov describes that FSU physicians and other specialists are not taught epidemiology as it is understood in the West. The Soviet public health system and the scientific discipline of epidemiology developed independently of that of other nations. Consequently, many fundamental Soviet terms and concepts lack simple correlates in English and other languages outside the Soviet sphere; the same is true when attempting to translate from English to Russian and other languages of the FSU. Systematic review of the differences in FSU and Western epidemiologic concepts and terminology is therefore needed for international public health efforts, such as disease surveillance, compliance with International Health Regulations 2005, pandemic preparedness, and response to biological terrorism. A multi-language reference in the form of a dictionary would greatly improve mutual comprehension among epidemiologists in the West and the FSU.

 

Objective

The objective of this study is to describe the development of a multilingual lexicon of epidemiology, which is needed for improved communication in public health surveillance internationally.

Referenced File
Submitted by hparton on

The Centers for Disease Control and Prevention's (CDC) Emerging Infections Program (EIP) monitors and studies many infectious diseases, including influenza. In 10 states in the US, information is collected for hospitalized patients with laboratory-confirmed influenza. Data are extracted manually by EIP personnel at each site, stripped of personal identifiers and sent to the CDC. The anonymized data are received and reviewed for consistency at the CDC before they are incorporated into further analyses. This includes identifying errors, which are used for classification.

 

Objective

Introducing data quality checks can be used to generate feedback that remediates and/or reduces error generation at the source. In this report, we introduce a classification of errors generated as part of the data collection process for the EIP’s Influenza Hospitalization Surveillance Project at the CDC. We also describe a set of mechanisms intended to minimize and correct these errors via feedback, with the collection sites.

Referenced File
Submitted by hparton on

Emerging event detection is the process of automatically identifying novel and emerging ideas from text with minimal human intervention. With the rise of social networks like Twitter, topic detection has begun leveraging measures of user influence to identify emerging events. Twitter's highly skewed follower/followee structure lends itself to an intuitive model of influence, yet in a context like the Emerging Infections Network (EIN), a sentinel surveillance listserv of over 1400 infectious disease experts, developing a useful model of authority becomes less clear. Who should we listen to on the EIN? To explore this, we annotated a body of important EIN discussions and tested how well 3 models of user authority performed in identifying those discussions. In previous work we proposed a process by which only posts that are based on specific "important" topics are read, thus drastically reducing the amount of posts that need to be read. The process works by finding a set of "bellwether" users that act as indicators for "important" topics and only posts relating to these topics are then read. This approach does not consider the text of messages, only the patterns of user participation. Our text analysis approach follows that of Cataldi et al.[1], using the idea of semantic "energy" to identify emerging topics within Twitter posts. Authority is calculated via PageRank and used to weight each author's contribution to the semantic energy of all terms occurring in within some interval ti. A decay parameter d defines the impact of prior time steps on the current interval.

Objective

To explore how different models of user influence or authority perform when detecting emerging events within a small-scale community of infectious disease experts.

Referenced File
Submitted by elamb on

The Biological Threat Reduction Program (BTRP) of the U.S. Defense Threat Reduction Agency (DTRA) delivers interventions to enhance surveillance of especially dangerous pathogens of both humans and animals within countries of the former Soviet Union. The program targets the different stages at which threats or their impact can be reduced, for example via i) the reduction of exposure to threats, or ii) measures for the containment of the threat. The program delivers training on surveillance-related subjects through regular events attended by representatives of the Ministry of Agriculture of Uzbekistan (UZ). This provides an opportunity to capture data and conduct simple interventions on specific subjects amenable to basic evaluation. Given the sensitive nature of pathogen-specific data, we focus on non-disease-specific interventions leading to the reduction of exposure to and release of any given hazard. Here we present an opportunistic approach for capturing data, at no additional cost, to assess i) baseline awareness of on-farm biosecurity measures among UZ veterinary officials and ii) the impact of training on their awareness of biosecurity. We also discuss the conceptual design of a study to assess on-farm biosecurity practices in UZ.

Objective

To describe approaches to the evaluation of surveillance-related efforts in resource-limited countries. Here we present an opportunistic approach to measure the success of efforts to improve on-farm biosecurity in Uzbekistan, leading to a reduction of generic threats to animal disease transmission.

Referenced File
Submitted by elamb on
  • Why the syndrome was created? This syndrome was created to monitor Lyme disease related emergency room visits using regular expressions in R. 
  • Syndromic surveillance system (e.g., ESSENCE, R STUDIO, RODS, etc.) Data collected from Epicenter, but parsed and analysed in R/Rstudio
  • Data sources the syndrome was used on (e.g., Emergency room, EMS, Air Quality, etc.) Emergency room and Urgent Care
Submitted by Anonymous on

Lymphatic filariasis is one of the most prevalent of the tropical diseases, but is also the most neglected.Though significant advances have been made in the understanding both the disease and its control, there is general lack of information about its socioeconomic effects, prevalence and distribution in most endemic societies. Presently, there is global effort towards the elimination of the disease by 2020. The success of this programme depends largely on the use of simple, non-invasive procedures to identify endemic communities. Limb elephantiasis is one of the chronic symptoms of lymphatic filariasis that could be easily diagnosed by persons with minimum training. Therefore, the prevalence of elephantiasis could serve as a useful tool to determine the occurrence and spread of lymphatic filariasis in endemic communities.

 

Objective

This paper describes how limb elephantiasis was used to determine the occurrence and spread of lymphatic filariasis in Kano state, Nigeria as well as the use of the results for further epidemiological studies.

Referenced File
Submitted by elamb on

The first prototype syndromic surveillance in Japan was used during the G8 summit meeting in 2000 with two local prefectures involved. The second trial syndromic surveillance and the first internet-based surveillance used in 2002 for the Japan-Korea 2002 World Cup soccer games. Since 2002, surveillances on over-the-counter medications, ambulance call, and outpatient visits were explored as syndromic approach candidates for early detection. Internet-based events and case reporting frame work has been reviewed for outpatient visits daily reporting concurrently. Limited spread of electrical patient record and vast range of commercialized medical record formats posed obstacles to nationwide syndromic surveillance implementation.

Recent threats from bioterrorism and influenza pandemic empowered Japanese government introducing surveillance of rapid detection mechanism. In line with the revision of the Infection Control Law took place in 2007 April, national syndromic surveillance system was implemented.

 

Objective

This paper describes recent establishment of national surveillance system for early detection of infectious diseases in Japan. With diagnostic data fed from existed routine surveillance, newly introduced system is expected to provide timely information for control response. We aim to facilitate cross-informative regional surveillance by sharing our experience and system frame work.

Referenced File
Submitted by elamb on

Zika virus disease became a significant public health problem in Brazil in 2015 and quickly spread to other South American and Central American countries. While not an overly severe illness for many, Zika virus disease has been shown to increase the probability of severe birth defects in babies when their mothers are infected with the virus during pregnancy. Zika virus disease has also been associated with Guillain-Barré syndrome.

Submitted by elamb on
  • Why the syndrome was created?
    • Track food poisoning and potential disease outbreaks due to infected food 
  • Syndromic surveillance system (e.g., ESSENCE, R STUDIO, RODS, etc.)
    • ESSENCE 
  • Data sources the syndrome was used on (e.g., Emergency room, EMS, Air Quality, etc.)
    • Patient Location Full Details 
  • Fields used to query the data (e.g., Chief Complaint, Discharge Diagnosis, Triage Notes, etc.)
    • CCandDD
Submitted by Anonymous on
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