A probabilistic analysis with random walks of the number of people living with HIV worldwide
Revista Facultad Nacional de Salud Publica, ISSN: 2256-3334, Vol: 36, Issue: 1, Page: 27-33
2018
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Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Article Description
Introduction: This is a study of the yearly dynamic of the HIV epidemic based on random walks has proven to be useful to take this highly variable phenomenon to a predictable behavior. Objective: Predict the behavior of the dynamic of the number of people living with HIV via a probabilistic random walk. Methodology: The yearly value of people living with HIV worldwide was analyzed from 1990 to 2009, based on probability spaces produced with a probabilistic random walk, and then, developed the prediction of the yearly value of people living with HIV for 2010, 2011 and 2012. Results: The yearly volume of people living with HIV was predicted with a 98.95% success rate in 2010, 98.82% in 2011 and 98.99% for the 2012 prediction. Conclusions: Mathematical orders were established based on the probabilistic random walk, establishing practically deterministic predictions of the number of people living with HIV which could be useful for public health decisions and to evaluate interventions.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85168287367&origin=inward; http://dx.doi.org/10.17533/udea.rfnsp.v36n1a04; https://revistas.udea.edu.co/index.php/fnsp/article/view/328339; http://aprendeenlinea.udea.edu.co/revistas/index.php/fnsp/article/download/328339/20787614; http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0120-386X2018000100027&lng=en&tlng=en; http://www.scielo.org.co/scielo.php?script=sci_abstract&pid=S0120-386X2018000100027&lng=en&tlng=en; http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0120-386X2018000100027; http://www.scielo.org.co/scielo.php?script=sci_abstract&pid=S0120-386X2018000100027; https://dx.doi.org/10.17533/udea.rfnsp.v36n1a04
Universidad de Antioquia
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