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Questions for Brandon Marshall: Predicting outcomes of HIV efforts in NYC

By Guest PostMarch 22, 2014Healthaffordable care act, brandon marshall, brown university, columbia university, david orenstein, drug user, high impact, hiv care, hiv efforts, hiv epidemic, hiv incidence, hiv treatment, hiv-positive, new york city, nyc, outcome, predictive computer model

New York City continues to battle an HIV epidemic, including among drug users. There are many possible interventions. Researchers have developed a sophisticated predictive computer model to help policymakers figure out which interventions, or combinations of interventions, would have the most meaningful impact.

Brandon Marshall, assistant professor of epidemiology at Brown University, has led the simulation effort ever since he was a postdoctoral scholar at Columbia University. In a new paper in the March edition of the journal Health Affairs a team from Brown and Columbia published the results of the simulation, which projects that New York can significantly reduce new infections among drug users by 2040 by implementing certain combinations of interventions. Marshall spoke with David Orenstein about what the predictive computer model shows. (more…)

For College Students, Job Market a Mixed Bag

EAST LANSING, Mich. — As Michigan State University’s Recruiting Trends report shows, college students are experiencing a mixed bag of outcomes when it comes to finding a job.

For some MSU students, like MBA candidate Megan Brody, the job search was short and rewarding. For others, like journalism senior Alex Mitchell, the hunt hasn’t led to any full-time positions.

Mitchell, who graduates in December with a degree in journalism, has sent out about 15 resumes to communications employers in Michigan and Ohio hoping to stay close to his hometown of Blissfield in southeastern Michigan. He said he will continue the process until he gets a job he sees fit. (more…)

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Questions for Brandon Marshall: Predicting outcomes of HIV efforts in NYC

For College Students, Job Market a Mixed Bag