11/11: Informatics, Diagnostics, and Implementing ART in Africa

In this article about diagnostic tests and information, the authors illustrate a very intriguing and validated point: that not only do diagnostic tests save lives, they reduce the disease burden as a result of morbitity as opposed to sickness (measured as DALYs) and as a result of prevention and potential decrease of disease prevalence. It is only after reading an article like this that you realize how important effective diagnostic tests are especially in low resource areas where diseases are inevitably prevalent. These tests are also important because unlike most people in the developed world, residents of this low or no infrastructure areas do not have a primary doctor or even a trained clinician available to inform them of their illnesses: most of them learn about their illnesses at the onset of symptoms which for some diseases might be too late for people to be treated. And where there are diagnostic tests, they need to be effective as in highly sensitive and specific because in these areas and with these types of diseases, TB, malaria and others, a misdiagnosis can be the difference between life and death for a patient. But as the authors express, it is difficult to design a diagnostic test that can be this effective and yet so simple that it can be used in a low resource site but research continues and new methods have been found.
I am confused about how the authors came about with their results: they repeatedly say that they used mathematical models but it would be perhaps helpful if they should an example of the model and how or what kind of results it produced although they do have a thorough summary of what needs to be known.