Public Health and Engineering team up on five research projects

Pitt’s School of Public Health, Swanson School of Engineering, and Clinical and Translational Science Institute awarded $450,000 to five transdisciplinary pilot investigations focused on precision public health, a field that uses data science to develop targeted interventions by person, place and time. 

This year’s projects bring together the following principal investigators from public health and engineering:

Praveen Kumar, Department of Health Policy and Management
Bo Zeng, Department of Industrial Engineering 

The administration of blood transfusions by paramedics to patients with life threatening injuries while enroute to the hospital – prehospital transfusion – has been introduced in emergency medical service systems (EMS) in several U.S. cities. Evidence indicates that prehospital transfusion helps to improve survival, especially when transport is delayed by heavy traffic or entrapment after a car accident, for example. Through a multidisciplinary collaboration, Kumar and Zeng will use a large EMS dataset to determine how to expand access to this lifesaving treatment and identify a cost-effective approach that can be sustained to save more lives.

Andrea Rosso, Department of Epidemiology
Mark Redfern, Department of Bioengineering 

Assessing the walking patterns of older adults in their everyday environment has been used increasingly to identify potential fall risks related to dementia or Parkinson's disease. Known as free-living gait evaluation, this approach has been limited by available technology. Rosso and Redfern will develop and test wearable products that will combine mobile technologies and global positioning systems to measure both gait and location simultaneously. Their hope is to improve the ability to predict individuals who could be most at risk for falls.

Lisa Parker, Department of Human Genetics 
Takashi Kozai, Department of Bioengineering 

Research on neural prostheses, devices that can substitute for impaired motor, sensory or cognitive functions, such as Cochlear implants, require participant-provided data, but also present challenges related to privacy and consent. By integrating patient input on data collection with advanced analytic methodologies, Parker and Kozai aim to transform neural prosthetic research. Their approach seeks to empower participants to contribute to data collection design, analytic tools and training resources, ultimately bridging the gap between technical development and participant engagement.

Rebecca Deek, Department of Biostatistics and Health Data Science 
Bistra Iordanova, Department of Bioengineering 

Routine and cost-efficient ways to screen people at high risk of developing neurological diseases, such as dementia, are challenging because much remains unknown about how and when brain changes occur that heighten individual risk. In current clinical studies, the link between specific gene expressions and how brain cells may be affected over time is uncertain. Deek and Lordanova propose to combine brain imaging with omics datasets - a collection of data that describes the molecular makeup of an organism – through techniques that break data down into simpler components. This will help the researchers note highly correlated features across modalities and data, and, in turn, determine the predictive capability of their approach.

Ying Ding, Department of Biostatistics and Health Data Science
Wei Gao, Department of Electrical and Computer Engineering

Respiratory diseases such as asthma and chronic obstructive pulmonary disease are widespread. Despite advancements in medical treatments and interventions, severe outcomes remain frequent, leading to emergency department visits or hospitalizations. Ding and Gao will use a smartphone-based system – Smartphone Ultrasonic Respiratory Evaluation – to measure chest wall mobility, which is strongly correlated with lung function, breathing patterns and the severity of symptoms. This system can potentially improve early diagnosis and provide a cost-effective, portable respiratory evaluation tool for detecting, diagnosing and managing chronic respiratory diseases.