Probability and Public Health

Public health policies and studies are focused on keeping the nation healthy, avoiding possible epidemics and learning more about keeping diseases from spreading rapidly. While it is impossible to avoid or eliminate every disease, although there are many that occur less and less, the probabilities of these diseases are the foundation of many hospitals, learning hospitals, and the Center for Disease Control. It is the job of these facilities to find out the risks and factors that can be attributed to diseases and also how they can be kept in check and not become a full blown epidemic.

The basic statistical method to begin their studies is the use of probabilities. Probability is the assumption that an event will occur in certain circumstances. To public health this equates to the diagnosis of a disease in the general population. Making it simpler it is the chances a person has to at some point in their lives be afflicted with a disease. This is why medical facilities and governmental agencies watch and compare and analyze the medical data that is available. In recent years, this data is available almost instantaneously through electronic means.

It allows for the early detection of possible epidemics and which illness and diseases are on the rise in specific areas (Early Detection, 2005; Levy & Stolte, 2000; Mayo Clinic, 2007). There are two main categories of probability or risk. The first is the absolute risk with is defined as the chance a certain disease will happen in a certain time frame. It is in this absolute risk that the medical researchers find the lifetime risks of disease. For example, there is a 50% chance that a male will develop cancer in his lifetime. This probability is pretty scary, but it needs to be taken in context.

It does not mean that every man will have a 50% chance of being diagnosed with cancer; it just means that in general there is a 50% chance. The individual risk is almost impossible to ascertain due to the variety of factors in an individual’s life. Hence, individual risk is not considered in research, only the generalized assumption can be used (Early Detection, 2005; Levy & Stolte, 2000; Mayo Clinic, 2007). The second type of probability is the relative risk with is a comparison of factors that may or may not cause an event, or disease.

The relative risk takes variables and tests their relational strength in regard to the disease and the variable, such as the correlation between drug use and HIV. Again, individual risk is excluded because of the number of factors that have to be considered. Even when two exact individual with equivalent histories are compared there is no way to give an accurate probability of being diagnosed with a disease. Therefore, the relative risk used with the absolute risk is how the governmental agencies explain the probability of diseases and epidemics (Early Detection, 2005; Levy & Stolte, 2000; Mayo Clinic, 2007).

In November of 2003 a new type of probability model was put to use. It was called the “space-time permutation scan statistic” (Early Detection, 2005, pg 46). This model worked with early detection of diseases in a New York City hospital. The program compensated for missing data and for making assumptions about the data in relation to the chance of full blown occurrence. While it is very helpful in stopping illness and diseases from reaching epidemic levels it is not as accurate if the geographical information is spread out rather than localized.

Even these new ideas need some work (Early Detection, 2005) Another way in which probability is being used in public health is with the threat of bioterrorism. The concept is that bioterrorism detectors be placed in areas where bioterrorism attacks could occur, such as a subway or transit system. The information that would be gathered by the detector would include the type of biological warfare being used and the number of possible people affected. This information would be sent to local hospitals which in turn would be able to treat those who were exposed properly and quickly, saving time and money.

This new system is being created after the 2001 anthrax assault on United States Post Offices. If the detector had been available, fewer people would have been hurt and the postal service would not have shut down. This is still new and still expensive, but proponents believe the cost is justified and worth it in time and lives (Schneider, 2005). Probability is important to public health and public health policy. It is being used to detect biological warfare and in predicting possible epidemics of illnesses or disease. This type of statistical analysis is not an end all nor is it completely accurate.

The fact is that there are many factors and variable such as age, family history, environment, habits, and other individual actions that affect the chances of a person. However, probabilities are the first step in prediction and the first line of defense to try to keep outbreaks to a minimum and the country medical safe. References Early Detection of Disease Outbreaks. (2005, October). Journal of Environmental Health, Retrieved December 18, 2008, from Academic Search Premier database. Levy, P. , & Stolte, K. (2000, February). Statistical methods in public health and epidemiology: a look at the recent past and projections for the next decade.

Statistical Methods in Medical Research, 9(1), 41-55. Retrieved December 18, 2008, from Academic Search Premier database. Mayo Clinic. (2007, April). Cancer risk: What the numbers mean. Arizona: Mayo foundation for Medical Education and Research. Retrieved on December 15, 2008 from http://www. mayoclinic. com/health/cancer/CA00053 Schneider, H. (2005, December). Protecting Public Health in the Age of Bioterrorism Surveillance: Is the Price Right?. Journal of Environmental Health, 68(5), 9-13. Retrieved December 18, 2008, from Academic Search Premier database.

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