Every shot counts: Development of a novel predictive model and toolkit to predict and decrease vaccine-preventable rural COVID-19 deaths
Investigators: Jimeng Sun, PhD, University of Illinois at Urbana-Champaign (U of I); Scott Barrows, MA, FAMI, University of Illinois at Chicago (UIC), University of Illinois College of Medicine Peoria (UICOMP), OSF HealthCare; Adam Cross, MD, FAAP, OSF HealthCare, UICOMP; Ann Willemsen-Dunlap, CRNA, PhD, OSF HealthCare, UICOMP; and Mary Stapel, MD, OSF HealthCare
Currently, 12% of the U.S. population has received at least one COVID-19 vaccine which is below the projected 70-90% required to achieve herd immunity to the virus. This project aims to develop a predictive model to predict vaccine-preventable deaths in each county in the U.S. and the most likely reasons for vaccine hesitancy among populations. A toolkit will help guide rural populations in their decision-making about accepting the COVID-19 vaccine.
Human factors in the use of telepresence robots after the COVID-19 pandemic
Investigators: Inki Kim, PhD, U of I; Thenkurussi (Kesh) Kesavadas, PhD, U of I; Jon Michel, MD, OSF HealthCare; and Shandra Jamison, MA, RRT, U of I
The COVID-19 pandemic outbreak resulted in an increase in telemedicine visits to prevent the spread of the virus. The goal of this concept is to establish, justify and optimize a set of existing or new use cases for telepresence robot use in telemedicine to reduce the risk of in-hospital transmission of COVID-19 as well as for continued quality of care delivery in the post-COVID-19 era.
Early insights and recommendation for implementing a COVID-19 saliva-based testing program in K-12 schools: Lessons learned from four under-resourced schools
Investigators; Rebecca Lee Smith, DVM, MS, PhD, U of I; Thanh (Helen) Nguyen, PhD, U of I; Nicole Delinski, DNP, MSN, RN, OSF HealthCare; Michaelene Ostrosky, PhD, U of I; and W. Catherine Cheung, PT, PhD, U of I
With the goal of successfully reopening K-12 schools and keeping them open, this proposed plan will work to gain a better understanding of the acceptability, feasibility and effectiveness of implementing saliva-based testing in under-resourced schools as well as parental behavior of deciding to allow their children to return to in-person learning.
Voice vitals: A new approach for anxiety and depression screening in the era of COVID-19
Investigators: Mary Pietrowicz, PhD, U of I; Ryan Finkenbine, MD, UICOMP, OSF HealthCare; and Sarah Donohue, PhD, UICOMP
Existing systems fall short in identifying and treating individuals with anxiety disorders and major depressive disorders due to a variety of issues including people not seeking medical attention, attitudinal barriers like stigma and structural barriers such as a lack of providers. This proposal aims to develop a prototype of machine models that can listen to speech and language and automatically screen for anxiety and depression disorders.
COVID-19 infection levels in Central Illinois communities without access to frequent testing: A sewage monitoring and epidemiological modeling study
Investigators: Thanh Helen Nguyen PhD, U of I; Ahmed Elbana, U of I; Art Schmidt, U of I; Joanna Shisler, U of I; and John Farrell, OSF HealthCare
New COVID-19 variants spread faster and have evaded some the vaccine-induced protective immune response in the UK and other countries. To determine whether these factors will influence the level of infection and diversity of variants in areas that lack frequent testing, this project will collect and monitor the levels and genotypes of the virus in sewage collected at selected neighborhoods. The goal is to help public health officials prepare for increased burdens on health care facilities and workers.
How to design and operate end-to-end vaccine deployment using social media, addressing supply chain allocations constraints and utilizing telemedicine
Investigators: Anton Ivanov, PhD, U of I; Subhonmesh Bose, PhD, U of I; Albert England III, MD, FIDSA, U of I, UICOMP, OSF HealthCare; Ashen Eren Mehmet, PhD, U of I; Ujjal Mukherjee, PhD, U of I; Sridhar Seshadri, U of I; Sebastian Souyris, Postdoctoral Fellow, U of I; and Yuqian Xu, PhD, U of I
This idea aims to provide a comprehensive vaccine deployment strategy using data analytic frameworks. These frameworks will (1) shape population attitudes towards vaccination by reducing their uncertainty via social media channels, (2) provide a dynamic inventory management tool for perishable or sensitive goods, and (3) develop telemedicine-based solutions for convenient and sufficient post-vaccination patient support.
Building a motivational, interviewing conversational agent (MintBot) for promoting COVID-19 vaccination among people with multiple sclerosis
Investigators: Jessie Chin, PhD, U of I; Suma Bhat, PhD, U of I; Chung-Yi Chiu, PhD, U of I; Jared Rogers, MD, OSF HealthCare; and Brian Laird, PharmD, OSF HealthCare
Individuals with multiple sclerosis are likely to be hesitant to getting the COVID-19 vaccine due to their compromised health condition. This concept aims to develop an accessible, generalizable and efficient digital health solution for promoting COVID-19 vaccination among vulnerable populations, such as people with disabilities.