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Data Collection

Electronic disease surveillance systems can be extremely valuable tools; however, a critical step in system implementation is collection of data. Without accurate and complete data, statistical anomalies that are detected hold little meaning. Many people who have established successful surveillance systems acknowledge the initial data collection process to be one of the most challenging aspects of system implementation. These challenges manifest from varying degrees of economical, infrastructural, environmental, cultural, and political factors. Although some factors are not controllable, selecting a suitable collection framework can mitigate many of these obstacles. JHU/APL, with support from the Armed Forces Health Surveillance Center, has developed a suite of tools, Suite for Automated Global bioSurveillance (SAGES), that is adaptable for a particular deployment’s environment and takes the above factors into account. These subsystems span communication systems such as telephone lines, mobile devices, internet applications, and desktop solutions--each has compelling advantages and disadvantages depending on the environment in which they are deployed. When these subsystems are appropriately configured and implemented, the data are collected with more accuracy and timeliness.

Objective

This paper describes the common challenges of data collection and presents a variety of adaptable frameworks that succeed in overcoming obstacles in applications of public health and electronic disease surveillance systems and/or processes, particularly in resource-limited settings.

Referenced File
Submitted by teresa.hamby@d… on

Electronic disease surveillance systems can be extremely valuable tools; however, a critical step in system implementation is collection of data. Without accurate and complete data, statistical anomalies that are detected hold little meaning. Many people who have established successful surveillance systems acknowledge the initial data collection process to be one of the most challenging aspects of system implementation. These challenges manifest from varying degrees of economical, infrastructural, environmental, cultural, and political factors. Although some factors are not controllable, selecting a suitable collection framework can mitigate many of these obstacles. JHU/APL, with support from the Armed Forces Health Surveillance Center, has developed a suite of tools, Suite for Automated Global bioSurveillance, that is adaptable for a particular deployment’s environment and takes the above factors into account. These subsystems span communication systems such as telephone lines, mobile devices, internet applications, and desktop solutions - each has compelling advantages and disadvantages depending on the environment in which they are deployed. When these subsystems are appropriately configured and implemented, the data are collected with more accuracy and timeliness.

 

Objective

This paper describes the common challenges of data collection and presents a variety of adaptable frameworks that succeed in overcoming obstacles in applications of public health and electronic disease surveillance systems and/or processes, particularly in resource-limited settings.

Referenced File
Submitted by hparton on

Emerging and re-emerging infectious diseases are a serious threat to global public health. The World Health Organization (WHO) has identified more than 1100 epidemic events worldwide in the last 5 years alone. Recently, the emergence of the novel 2009 influenza A (H1N1) virus and the SARS coronavirus has demonstrated how rapidly pathogens can spread worldwide. This infectious disease threat, combined with a concern over man-made biological or chemical events, spurred WHO to update their International Health Regulations (IHR) in 2005. The new 2005 IHR, a legally binding instrument for all 194 WHO member countries, significantly expanded the scope of reportable conditions, and are intended to help prevent and respond to global public health threats. SAGES aims to improve local public health surveillance and IHR compliance, with particular emphasis on resource-limited settings.

Objective

This paper describes the development of the Suite for Automated Global bioSurveillance (SAGES), a collection of freely available software tools intended to enhance electronic disease surveillance in resource-limited settings around the world.

Referenced File
Submitted by Magou on

Disease surveillance systems are currently used for the early detection of disease outbreak before diagnosis is confirmed in order to mobilize a rapid response . The fear of epidemics or bioterrorism resulted in the development of systems for the general population; however research efforts for sensitive population groups are missing. Sensitive groups could be considered patients suffering from chronic diseases (such as diabetes and renal failure), elderly people and infants. It is well known that these groups are quite susceptible to diseases that can be easily spread under certain circumstances e.g. in a dialysis room where patients with renal failure receive their regular treatment. In addition to that, several diseases seem to affect them more. Therefore, the development of disease surveillance systems for sensitive population groups is an issue that should be addressed.

Objective

The aim of this study is to reveal the need for developing disease surveillance systems for sensitive populations.

Referenced File
Submitted by elamb on

The University of Washington has been working since 2000 with partners in Washington State to advance bioterrorism (BT) detection and preparedness. This project collects data on patients presenting with influenza-like illnesses and other potentially BT-related syndromes at emergency departments and primary care clinics (Kitsap, Clallam, and Jefferson counties) using a secure automated informatics approach. Local health jurisdiction epidemiologists use a web-based interface to view de-identified data and use a version of CDC’s EARS disease detection algorithms to watch for variances in patterns of diagnoses, volume, time and space as part of the public health real-time disease surveillance system. This processed hospital data is also made available back to the officials and administrators at the reporting hospital.

 

Objective

To understand GIS issues in a rural-tourban setting and demonstrate limitations of ZIPcode-only approaches compared to census tract and block approaches.

Referenced File
Submitted by elamb on

The syndromic surveillance system in Scotland was implemented in response to Gleneagles hosting the G8 summit in July 2005. Part of this surveillance system used data from NHS24, a nurse led telephone help line that is the means of access to out of hours general practice services for the Scottish population. This data was processed by the ERS system and reports generated for 10 syndromes considered relevant to possible bio-terrorism or disease outbreaks. These syndromes are; colds and flu, difficulty breathing, fever, diarrhoea, coughs, double vision, eye problems, rash, lumps and vomiting. Following the G8 summit the ERS has been updated weekly using data pre-catagorised into syndromes at NHS24 (known as protocolled data). The proportion of calls processed by the protocol at NHS24 over this time has however fallen to around 40%. This change has given the impetus to create a free text searching algorithm which can classify all calls received by NHS 24 into one of the 10 syndromes or “other”. This therefore allows all calls to be analysed by the ERS.

 

Objective

Public Health consultants at Health Protection Scotland (HPS) monitor routine data from the NHS24 telephone helpline to provide information on possible epidemics of flu or other infectious diseases in Scotland. Within this paper the exception reporting system run at HPS is described and the adaptations made to the classification system as a response to the change of data recording patterns at NHS24 are described.

Referenced File
Submitted by elamb on

The Centre for Health Protection in Hong Kong has operated a sentinel surveillance system for infectious diseases at child care centre (CCC) since March 2004, among its multi-faceted disease surveillance systems. Forty-six CCCs have participated in the system and are contributing data weekly on absenteeism and common infectious disease symptoms such as fever, diarrhea, vomiting, and cough. The system was originally driven by a manual data collection mechanism via fax, followed by secondary data input and subsequent analysis. However, such mechanism might sometimes result in delayed data transmission and data loss. As an alternative to accommodate these limitations, a web-based platform is developed to increase the timeliness of data submission by the sentinel CCCs. The new platform not only speeds up data collection and eliminates the need for human data entry, but at the same time delivers summary statistics directly on the web through computer programmes on a real time basis, as soon as data is entered by the provider.

 

Objective

This paper describes the attempt to develop an internet-based community surveillance network to enhance timeliness and sensitivity in detecting community-wide infectious disease outbreaks among young children at CCCs in Hong Kong.

Referenced File
Submitted by elamb on

Surveillance strategies following major natural disasters have varied widely with respect to methods used to collect and analyze data. Following Hurricane Katrina, public health concerns included infectious disease outbreaks, injuries, mental health and exacerbation of preexisting chronic conditions resulting from unprecedented population displacement and disruption of public health services and health-care infrastructure.

 

Objective

This paper describes the public health surveillance response to hurricane Katrina in New Orleans and surrounding Parishes; particularly illustrating the methods, results, and lessons learned for implementing passive, active and electronic syndromic surveillance systems during a major disaster.

Referenced File
Submitted by elamb on

To compare the completeness of emergency department (ED) visit and hospital admissions data collected electronically for syndromic surveillance and data collected manually for a field surveillance exercise.

Referenced File
Submitted by elamb on

This paper describes the value of a distributed approach to population health efforts that span clinical research, quality measurement and public health. The goal of the paper is to challenge the traditional paradigm which relies on centralized data repositories with more distributed models where data collection and analysis remains as close to local data sources as possible. We will propose that a distributed approach is desirable because it allows for information to reside more closely with those who can act upon it and it can overcome existing barriers by allowing information to be shared more rapidly and effectively while minimizing privacy risks.

Referenced File
Submitted by elamb on
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