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Limitations - Case Study Example

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The Response to Concerned Citizens With a diplomatic tone, one can explain that in science, questions answered just invite further questions. In the determination of disease pathophysiology, as more researchers work on the field, more and more are discovered about the intricacies of mechanism…
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Download file to see previous pages Such will be too long and too extensive to do. As such, mathematical models should be given room for error when it comes to their limitations. Making mathematical models depend on the current findings of the scientific community. For example, if the necessary data is inadequate to produce a numerical estimate of exposure to a certain disease, qualitative assessments are allowed to describe the probability of acquiring disease based on the defined factors. With this in mind, assumptions are allowed, as long as the defining variables of the model is based on parameters whose contribution on the development of the disease has been found by several valid studies. Furthermore, the variability and uncertainty of these models should be described extensively (World Health Organization, 2005). Therefore, as the technology continuously improves, mathematical models similarly change constantly to adapt the new findings discovered. What the State should do is to keep itself updated regarding the newest models that represent risks for certain diseases. Exposure Assessments Of course, despite the recognition that mathematical models may not identify all the interplaying risks involved and put enough weight on them, everyone should be vigilant in meticulously looking at how the mathematical models were obtained to determine whether they put enough weight to all identified risk factors or not. In my opinion, all mathematical models on exposure assessments should be validated by the researchers themselves, especially if they are to be used in passing laws by the state. Laws should not be based on unfound mathematical models because they direct focus of concerned government agencies toward what was identified by the mathematical model as the defining risk factors for the development of the disease. When many studies have proven obesity as one of the more important risk factors in the development of cardiovascular diseases that have caused mortality on a lot of Americans, even the first lady Michelle Obama herself promoted healthy diet and exercise. Thalidomide, a drug widely available for use of women, was banned out of the market as it was found through several studies that it causes physical malformation to these women’s newborn. In addition, lawmakers should also choose the exposure assessment and corresponding mathematical model that cater to their purposes (World Health Organization, 2008). For example, if they are planning to mitigate the spread of an infectious disease, an overestimation of the infective agent’s potential is better than underestimating them. However, a more stringent exposure assessment and mathematical model should be used in allowing drugs in the market, which may either be therapeutic or toxic depending on its concentration. Model Validity As discussed above, the reliability of models in sufficiently representing real life situations is crucial, especially in the government. Model validity must thus be conducted regularly. However, one must note that even if a model is valid for one purpose, it does not mean the same is true for other objectives as well. Remember that models are made based on specific objectives (World Health Organization, 2005). First and foremost, validity largely depends on the state of data and documentation. When data is poorly gathered and/or insufficiently documented, the model is not valid, no matter how logical the model seems to be. Documentation must be clear, honest, fully referenced, provided with ...Download file to see next pages Read More
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