“Modeling the Impact of Antiretroviral use in Resource-Poor Settings” is the first mathematical model that I have read. Using a mathematical model to represent the effect of antiretroviral therapy (ART) on HIV prevalence, the article concludes that ART cannot be used as a measure for decreasing HIV transmission since increasing ART coverage and scaling up treatment do not seem to have an effect on HIV transmission. If true, this would change conventional belief that increasing treatment availability leads to a decrease in HIV transmission rate because viral loads are lower when treatment is provided to patients. Thus, the rate of transmission should be lower.
Instead of increasing treatment availability to decrease HIV transmission rate, we should be providing counseling and other services to attempt to change sexual behavior. However, I doubt the conclusions drawn from this mathematical model because there are always “holes” in a model that may alter the results that the model provides. For instance, the model does not take into cultural details that may vary from country to country, and the conclusion drawn from this model may not reflect what would happen in real life, if ART were to be introduced as a possible solution to lower the rate of transmission. I find that instead of making a mathematical model to draw conclusions from, studies should be done on actual groups of people because then the data is more solid and convincing, since it has been drawn from real life.
Data collected from real people is more convincing because the solutions and conclusions made will be applied to real people. Mathematical models have only the benefit that it can keep all variables constant, such as the development of a country that might influence sexual behavior and decrease HIV prevalence even though and increase in provision of ART may increase HIV prevalence, so that the effect of one single variable, in this case provision of ART, can be measured. Models also require less funding and ethical problems, for example whether testing ART on people is ethical, though they may be less convincing.
Sorry about the multiple postings, but copying and pasting into the blog entry still did not work, and my entry did not fit into a single blog.
“Modeling the Impact of Antiretroviral use in Resource-Poor Settings” is the first mathematical model that I have read. Using a mathematical model to represent the effect of antiretroviral therapy (ART) on HIV prevalence, the article concludes that ART cannot be used as a measure for decreasing HIV transmission since increasing ART coverage and scaling up treatment do not seem to have an effect on HIV transmission. If true, this would change conventional belief that increasing treatment availability leads to a decrease in HIV transmission rate because viral loads are lower when treatment is provided to patients. Thus, the rate of transmission should be lower.
ReplyDeleteInstead of increasing treatment availability to decrease HIV transmission rate, we should be providing counseling and other services to attempt to change sexual behavior. However, I doubt the conclusions drawn from this mathematical model because there are always “holes” in a model that may alter the results that the model provides. For instance, the model does not take into cultural details that may vary from country to country, and the conclusion drawn from this model may not reflect what would happen in real life, if ART were to be introduced as a possible solution to lower the rate of transmission. I find that instead of making a mathematical model to draw conclusions from, studies should be done on actual groups of people because then the data is more solid and convincing, since it has been drawn from real life.
ReplyDeleteData collected from real people is more convincing because the solutions and conclusions made will be applied to real people. Mathematical models have only the benefit that it can keep all variables constant, such as the development of a country that might influence sexual behavior and decrease HIV prevalence even though and increase in provision of ART may increase HIV prevalence, so that the effect of one single variable, in this case provision of ART, can be measured. Models also require less funding and ethical problems, for example whether testing ART on people is ethical, though they may be less convincing.
ReplyDeleteSorry about the multiple postings, but copying and pasting into the blog entry still did not work, and my entry did not fit into a single blog.