Traditional and Syndromic Surveillance
Order Instructions:
Traditional and Syndromic Surveillance
“While traditional disease surveillance often relies on time-consuming laboratory diagnosis and the reporting of notifiable diseases is often slow and incomplete, a new breed of public health surveillance systems has the potential to significantly speed up detection of disease outbreaks. These new, computer-based surveillance systems offer valuable and timely information to hospitals as well as to state, local, and federal health officials. These systems are capable of real-time or near real-time detection of serious illnesses and potential bioterrorism agent exposures, allowing for a rapid public health response. This public health surveillance approach is generally called syndromic surveillance, which is defined as an ongoing, systematic collection, analysis, and interpretation of ‘syndrome’-specific data for early detection of public health aberrations.”
—Yan, Chen, and Zeng (2008)
Information drives a public health official’s ability to predict disease outbreaks and trends. Increasingly, emerging natural and man-made threats are making the need for timely, accurate, and reliable information more urgent. As discussed previously, valuable information comes from a variety of data sources. A critical task for public health professionals is determining what might be considered “actionable intelligence”—how to gather it, how to validate it, and how to make sense of it.
To complete this Application Assignment, write a 2-page paper analyzing the practical ramifications of identifying, collecting, validating, and analyzing data for syndromic surveillance. Compare your analysis to traditional disease surveillance.
Your written assignments must follow APA guidelines. Be sure to support your work with specific citations from this week’s Learning Resources and additional scholarly sources as appropriate. Refer to the Publication Manual of the American Psychological Association to ensure your in-text citations and reference list are correct.
SAMPLE ANSWER
All countries require sensitive disease surveillance systems capable of detecting diseases early and monitor outbreaks. One such system is syndromic surveillance that has been developed recently. It is a complex technology tool developed for recording data from several sources with an aim of identifying the probability of a disease outbreak. It goes ahead to focus on non clinical information that indicates an outbreak. The information from various relevant sources is collected and analyzed to detect bioterrorism and alert the public on the same. Syndromic surveillance is influenced by the emerging threats of bioterrorism and the advancements in technology that allows the public health officials to analyze data from various sources for detecting cases of disease outbreak on time (Chen, Zeng & Yan, 2010).
Syndromic surveillance includes collection of information from various sources for analysis. One of these sources is monitoring of employees reporting absence from their work. Employee absence from their work is a useful tool of early outbreak identification or disease clusters such as influenza. The main advantage of this source of data for syndromic surveillance is its timeliness. For instance, in Netherlands, the start of influenza and respiratory syncytial virus was detected much earlier than laboratory confirmation. However, this method may capture seasonal aspects of employees’ absence that are not related to any infectious disease. This means that it may have low specificity (National Academy of Sciences (U.S.) et al, 2011).
School absenteeism is another source of syndromic surveillance data. It requires use of school records in order to identify absence of students. This method of data collection has been reported to help in early outbreak identification. It helps in understanding epidemiology of influenza in various communities by monitoring trends of school absenteeism. It has shown to be an effective method of timely detection of influenza prior one week to other systems. It has also shown a correlation between other traditional methods of surveillance such as validity of respiratory pathogens. This method has the ability to combine clinical data on students’ illnesses to make informed decisions on disease control measures, school closures, suspension of classes, and communication with parents. When this method is automated, collection of data on absenteeism requires minimal surveillance and allows public health officials to make use of limited resources effectively. Automated self reporting of diseases in university students provides an opportunity to avail information on self care and timing for return to schools. Although this method of data collection may be effective in some cases, it may be inconsistent in some schools and participation may vary from time to time. Likewise, the criteria for determining the absence of school absenteeism may greatly vary. This method may prove to be ineffective in schools that do not present the reasons for students’ absence. Therefore, reacting to every indication based on students’ absence would cause unacceptable cases of false alarms and hence inefficient use of public health resources (M’ikanatha, 2007).
The other source of information for syndromic surveillance is emergency department chief complaints. ED chief complaints refer to the records of patients’ reported symptoms and signs of disease at presentation. It typically consists of a brief statement entered into the electronic system in short phrases. It has been used in early identification of outbreaks of diseases at the start and the end of seasons of pathogens like influenza. This method is also used in mass gatherings and in monitoring and identification of novel threats. In some cases it is used to supplement data from other sources such as laboratory testing and sentinel physician consults. It has shown to be better than most methods of surveillances as it gives the real picture of the situation, and it detects clusters of diseases much earlier. For instance, in the case of H1N1 pandemic, alerts from ED data was detected about 7 days prior laboratory confirmation. However, this method may not be effective since not all patients use ED when receiving treatment. Additionally, data entry for ED chief is unformatted thereby reducing opportunities of automation for efficiency and effectiveness. This method relies on the specificity and sensitivity of the system and a variety of cases involved. Emergency and non emergence health records, pharmacy sales, and online resources are other source of data for syndromic surveillance that help in early detection of cluster of diseases or outbreaks (Zeng, 2011).
M’ikanatha (2007) confirms that syndromic surveillance is an overhaul of traditional surveillance system, which entails compulsory reporting of certain diseases to central health authority. This shows that traditional surveillance system relies solely on laboratory results to ascertain the probability of a disease outbreak. In case of a communicable disease such as influenza, the public health officials monitor the disease to detect any case of an outbreak. The traditional method is simple, but very slow. Although it can help in detecting a disease outbreak, it is not as effective as syndromic surveillance that detects outbreaks much earlier. Therefore, despite that syndromic disease surveillance is quite expensive and uses a complex of technology, it has proved to be more effectual than the traditional method. It can be used to detect outbreaks of certain infectious diseases on time and allow public health care to react. Early detection of outbreaks helps in saving many lives and managing outbreaks of communicable diseases.
References
Chen, H., Zeng, D., & Yan, P. (2010). Infectious disease informatics: Syndromic surveillance for public health and biodefense. New York: Springer..
M’ikanatha, N. M. (2007). Infectious disease surveillance. Malden, MA: Blackwell Pub.
National Academy of Sciences (U.S.)., Institute of Medicine (U.S.)., National Research Council (U.S.)., National Research Council (U.S.)., & National Academies Press (U.S.). (2011). BioWatch and public health surveillance: Evaluating systems for the early detection of biological threats. Washington, D.C: National Academies Press.
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