As an applied statistician, Aparna Keshaviah brings advanced analytics and innovative data to clarify urgent questions across multiple public health arenas. Her translational approach to wastewater surveillance uses data integration and dynamic visualization to help officials manage infectious diseases and drug epidemics. She has conducted head-to-head comparisons of the safety and efficacy of breast cancer treatments to help clinicians tailor patient management decisions. And she has analyzed and validated psychiatric symptom profiles to inform the diagnosis and treatment of debilitating mental health conditions. Her work aims to communicate scientific findings to technical audiences, academic research communities, and the general public alike. Keshaviah is a 2006-2007 Fulbright fellow and holds a Master’s degree in biostatistics from the Harvard School of Public Health.
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Aug 16 2023 Blog Post Novel Wastewater Toolkit Flags Covid-19 Surges Using Multiple Data Sources Wastewater monitoring has proven to be an effective tool in tracking Covid-19 trends and anticipating impending outbreaks. However, scientists have grappled with challenges in how to interpret and translate wastewater surveillance data to inform public health responses, restricting policymaker response. To address this need, researchers from Mathematica, funded by The Rockefeller Foundation, developed a promising […]
Dec 21 2021 Blog Post Optimizing Disease Detection and Containment Through a #WasteBeforeCase Approach When a new public health threat emerges – like the highly infectious Omicron variant of the SARS-CoV-2 virus – detecting the first case before there has been widespread community transmission can be like searching for the proverbial needle in a haystack. Yet wastewater testing is a tool optimized to do just that. People infected with […]