Public Health Officials Using Computers to Manage Outbreaks Essay

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Digital Disease Detection, commonly referred to as digital epidemiology provided strategies and methods for allowing digital-technology users to monitor infectious disease and conduct surveillance. These strategies help in the understanding of concerns and attitudes regarding infectious diseases. The process begins with the basics, such as the availability of internet access, online sharing platforms and other digital devices. These sources offer huge amounts of data. It is important to note that while these sources collect data, they do not, do so, with public health objectives in focus (Denecke, 2017).

The past few decades have seen tremendous changes in the world. There have been many and varied threats; from bioterrorism, influenza pandemics and the emergence of infectious diseases. There is also the issue of unforeseen population mobility which is among the reasons that triggered the development of public health surveillance systems. Such systems are invaluable tools in the detection and response to infectious disease outbreaks. However, the systems frequently fail to avail the required lead time promptly to enable response for the best outcome (Signorini, 2014).

It is important to conduct monitoring of emerging infectious disease in order to detect health threats to the public in good time. Emergence of new infections is connected to the upsurge in human population density, trade, travel and ecological issues such as change of climate and agricultural practice. New molecular technologies are now available for identifying pathogens. They also help in accurately monitoring activity of infectious disease. Surveillance tools that are web based along with other epidemic intelligence approaches applied by most big hospitals are meant to provide assessment of risk and detection of outbreak in a timely way (Christaki, 2015).


The rising concerns regarding the spread of influenza of pandemic proportion, bioterrorism and an upsurge of new infectious diseases have triggered efforts to improve surveillance and increase capacity for detecting infections early and controlling them to prevent outbreaks. Significant resources have been directed at developing advanced electronic reporting infrastructure. These are guided by non-specific syndromic symptoms. There is still debate on the effectiveness of these systems. Also, it has been established that informal digital systems have the ability to run several activities and processing information including mining, filtering, categorizing and visualizing information online with regard to epidemics.

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Some common examples of such resources include ProMED-mail, BioCaster and HealthMap (Digital Resources for Disease Detection, 2013).

The use of digital resources has become common. They have been used to monitor infectious diseases using both informal and informal methods. One of the driving forces that informed the evolution of such technologies was the need to reduce the time taken to detect outbreaks of infectious diseases. There is scarce evidence to demonstrate that the resources indeed help in detecting outbreaks faster than traditional methods. Nevertheless, it is evident that the resources help in availing important information for managing these outbreaks through an increased level of situational awareness. The resources help in boosting risk communication information (Digital Resources for Disease Detection, 2013).

Although computer technologies also come with their problems, they have added an important element in the development of public health monitoring. For instance, in the US in 1991, the National Electronics Telecommunications Systems for Surveillance had connected all state health facilities and departments for regular collection, analysis and dissemination of processed data on conditions categorized as notifiable. The country’s CDC started implementing the National Electronic Disease Surveillance Systems in 2001, to manage the huge number of the existing systems for surveillance, and enable the Public Health Services to respond in a faster way to emerging threats. By 2007, 35 states had integrated their public health monitoring systems following the vision by NEDDS. Once NEDDS is implemented fully in the USA, officials from the Public Health section and other professionals in related disciplines will recognize and respond to public health threats faster (Choi, 2012).

France’s Minitel system has sown that office based surveillance is effective in public health matters. Monitoring of public health depends on information systems that include a range of data sources important to influence public health action (Choi, 2012).

According to Chowell et al (2016) news reports from the internet and health bulletins should be used to gather information on cohorts of patients and reconstruct transmission trees and reproduction figures by making use the lessons learnt from Middle East respiratory syndrome as well as the Ebola outbreak......

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Bansal, S., Chowell, G., Simonsen, L., Vespignani, A., & Viboud, C. (2016). Big data for infectious disease surveillance and modeling. The Journal of Infectious Diseases, 214(suppl_4), S375-S379.

Simonsen, L., Gog, J. R., Olson, D., & Viboud, C. (2016). Infectious disease surveillance in the big data era: Towards faster and locally relevant systems. The Journal of Infectious Diseases, 214(suppl_4), S380-S385.

Bourne, P. E. (2015). Confronting the ethical challenges of big data in public health. PLoS computational biology, 11(2), e1004073.

Bond, C. S., Ahmed, O. H., Hind, M., Thomas, B., & Hewitt-Taylor, J. (2013). The conceptual and practical ethical dilemmas of using health discussion board posts as research data. Journal of medical Internet research, 15(6).
Signorini, A. (2014). Use of social media to monitor and predict outbreaks and public opinion on health topics. The University of Iowa.

Chowell, G., Cleaton, J. M., & Viboud, C. (2016). Elucidating transmission patterns from internet reports: Ebola and middle east respiratory syndrome as case studies. The Journal of Infectious Diseases, 214(suppl_4), S421-S426.

Harvard School of Public Health. (2016). HealthMap. Retrieved 23 October 2017 from

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