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Abstract
Disease surveillance involves the analysis of data provided by different agencies about a specific medical condition. Many health institutions participate in this process, especially where deadly diseases are concerned. The process helps in controlling a condition or finding a cure for a disease. The current paper provided information on how surveillance and data collection on meningococcal meningitis can be done. The author analyzed the disease and the people likely to be affected by it. In addition, the issues of the data needed for the surveillance of the disease were tackled. The process of collecting the information was clearly explained. The information to be used has to be accurate. The accuracy is determined by the person responsible for handling and giving out the data. The author expounded on the people supposed to handle the data and those supposed to provide it. The parties responsible for the collection of the information were mentioned in the paper. Quality of data is important. If it is tampered with, then the mission of surveillance may fail. As such, surveillance is critical to the management of conditions and has to be done systematically.
Identification of the Disease
Meningococcal meningitis is a bacterial infection. It is a serious condition affecting the thin lining surrounding the brain and the spinal cord. The condition is caused by an infection that leads to the inflammation of the brain and the spinal cord (National Information Center on Health Services Research and Health Care Technology, 2011). The condition is serious but rare in society. The symptoms associated with the disease include pain in the muscles, neck, and back. Red rashes can also be seen on the body (World Health Organization, 2012). The condition can be treated.
The population that is at Risk of Suffering from Meningococcal Meningitis
The people at risk of getting meningococcal meningitis include infants, adolescents, and young adults. The disease is infectious and can spread fast, especially in gatherings of large groups of people (Centers for Disease Control and Prevention [CDC], 2012). Given the fact that the condition is infectious, everyone is at risk. For example, travelers are at high risk of contracting the disease. The reason is that they may move into regions affected by the condition.
Data Needed for the Surveillance of the Disease
To have a better understanding of the disease, a systematic collection, and analysis of data concerning the condition will be carried out. Both primary and secondary sources of data will be used. Primary data will be gathered from local health departments. A one-on-one interview with the people affected by the condition is also one of the ways that information will be collected (Babin, Magruder, Hakre, Coberly & Lombardo, 2007). Experts from different medical fields are making efforts to collect information about the problem. To this end, experts working on various CDC programs will help the author secure secondary information about the condition. The data needed will involve the symptoms of the disease among different patients and other health complications related to it (Doyle, Glynn, & Groseclose, 2002). Medications taken by the people affected by the problem will also be part of the data.
Collection of Information and Data
The collection of information for the surveillance program will take different forms. The first method will involve interviews. Patients suffering from the disease and those who have undergone the experience in the past will be interviewed to get their opinion and other information. Analysis of reports and direct observation will also be used to collect data (Milken Institute, 2007). Reports and records from health centers and other CDC programs manned by experts will be used.
Persons Responsible for the Collection and Provision of Data
The persons responsible for the provision of the data when it comes to secondary sources include doctors or individuals charged with the responsibility of keeping records of patients. Primary data from the interviews will be provided by patients and those who have successfully been treated for the condition (Babin et al., 2007). The persons responsible for the collection of data are those involved in the surveillance. It is advisable to collect first-hand information and avoid delegation of duties to avert instances of biasness (World Health Organization, 2008). Biasness and inaccuracies can jeopardize the whole surveillance process.
Aggregate Records of Data to be Used
To enhance diversity and avoid biasness, the aggregate records of data to be used should contain information collected from not less than 50 respondents. Fifty is an average number. It will be easy to work on it to gather information regarding the condition (Wagner et al., 2004). The respondents are patients suffering from the disease and those who have been treated successfully.
Enhancing the Quality of the Data
The quality of the data collected will be enhanced by gathering information from certified health centers. Respondents will also be screened to ensure that only genuine subjects are allowed to participate (Magruder, 2003). Data from CDC programs will be analyzed to highlight similarities and discrepancies. The move will help the researcher to determine the ‘worthiness’ of the data (Zhang, Fiedler & Popovich, 2004). Such measures will enhance the quality of the data.
Conclusion
Surveillance of meningococcal meningitis should be carried out systematically. To reduce the chances of errors, it is important to collect information from genuine sources. Data should be analyzed carefully to guarantee the success of the surveillance program. Proper surveillance can help stakeholders to come up with effective ways to treat and manage the disease.
References
Babin, S., Magruder, S., Hakre, S., Coberly, J., & Lombardo, J. (2007). Understanding the data: Health indicators in disease surveillance. In J. Lombardo & D. Buckeridge (Eds.), Disease surveillance: A public health informatics approach (pp. 43-90). Hoboken, NJ: Wiley-Interscience
Centers for Disease Control and Prevention. (2012). Chronic disease prevention and health promotion. Web.
Doyle, T., Glynn, M., & Groseclose, S. (2002). Completeness of notifiable infectious disease reporting in the United States: An analytical literature review. American Journal of Epidemiology, 155(9), 866-874.
Magruder, S. (2003). Evaluation of over-the-counter pharmaceutical sales as a possible early warning indicator of human disease. Johns Hopkins University APL Technical Digest, 24, 349-353.
Milken Institute. (2007). An unhealthy America. The economic burden of chronic disease. Web.
National Information Center on Health Services Research and Health Care Technology. (2011). Health informatics. Web.
Wagner, M., Tsui, F., Espino, J., Hogan, W., Hutman, J., Hersh, J.,…& Aller, R. (2004). National retail data monitor for public health surveillance. Morbidity and Mortality Weekly Report, 53(suppl), 40-42.
World Health Organization. (2008). A guide to establishing event-based surveillance. Web.
World Health Organization. (2012). Chronic diseases. Web.
Zhang, X., Fiedler, R., & Popovich, M. (2004). A bio intelligence system for identifying potential disease outbreaks. Engineering in Medicine and Biology Magazine, IEEE, 23(1), 58-64.
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