AMHERST, Mass. – Chaitra Gopalappa, an engineer at the University of Massachusetts Amherst, has received a five-year, $1.5-million grant from the National Institutes of Health (NIH) to help refine the national strategy for reducing HIV infection and to develop new analytic models and methods to measure how the plan is working.
Gopalappa, an assistant professor of mechanical and industrial engineering, has expertise in advancing mathematical methodologies to derive information that may help in decision-making for public health strategies. She works closely with the Centers for Disease Control and Prevention and the World Health Organization on non-communicable diseases such as cancers and communicable diseases such as HIV.
At UMass Amherst, Gopalappa is the director of the Disease Prediction and Prevention Lab that works on developing new methods and computational models for simulating the dynamics of disease incidence and spread for purposes of disease prediction, prevention and control.
One of Gopalappa’s goals under the grant will be to help improve the efficiency of the National HIV/AIDS Strategy (NHAS) that was created in 2010 to serve as a roadmap for implementing interventions to reduce the incidence of HIV infections.
As the principal investigator under the grant, Gopalappa is coordinating her own mathematical modeling done at UMass Amherst with a team composed of Paul Farnham, Stephanie Sansom and Yao-Hsuan Chen at the Centers for Disease Control and Prevention in Atlanta, along with Robert McKinnon at Avenir Health in Glastonbury, Conn.
She says, “National and global strategic plans for disease prevention and control are extremely critical as they drive allocation of resources to intervention programs from national to local levels. Decision-makers are often faced with a challenge of developing evidence-based strategies when usually such decision-making precedes evidence availability.”
NHAS drives most HIV-related activities at local and national levels and how resources are allocated, with an annual federal spending budget of about $25 billion including about $8 billion for HIV prevention. Expected outcomes of this research effort include analyses of a new methodology for simulating sexual and needle sharing contact networks; a new model for multi-level integrated analyses of population-specific portfolio interventions for HIV; and an open-access software package for real-time decision analyses.
This research could help guide decisions toward implementing interventions to best reach NHAS goals. In addition, Gopalappa’s mathematical concepts, if successful, will be basic building blocks for developing advanced disease models for real-time decision analyses during outbreaks of emerging infectious diseases.