Digital Commons Network^™

A Strategy To Identify Event Specific Hospitalizations In Large Health Claims Databases, Joshua Lambert, Harpal Sandhu, Emily Kean, Teenu Xavier, Aviv Brokman, Zachary Steckler, Lee Park, Arnold Stromberg

Statistics Faculty Publications

Background: Health insurance claims data offer a unique opportunity to study disease distribution on a large scale. Challenges arise in the process of accurately analyzing these raw data. One important challenge to overcome is the accurate classification of study outcomes. For example, using claims data, there is no clear way of classifying hospitalizations due to a specific event. This is because of the inherent disjointedness and lack of context that typically come with raw claims data.

Methods: In this paper, we propose a framework for classifying hospitalizations due to a specific event. We then tested this framework in …

Characterizing Long Covid: Deep Phenotype Of A Complex Condition, Rachel R. Deer, Madeline A. Rock, Nicole Vasilevsky, Leigh Carmody, Halie Rando, Alfred J. Anzalone, Marc D. Basson, Tellen D. Bennett, Timothy Bergquist, Eilis A. Boudreau, Carolyn T. Bramante, James Brian Byrd, Tiffany J. Callahan, Lauren E. Chan, Haitao Chu, Christopher G. Chute, Ben D. Coleman, Hannah E. Davis, Joel Gagnier, Casey S. Greene, Ramakanth Kavuluru

Institute for Biomedical Informatics Faculty Publications

BACKGROUND: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or "long COVID"), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies.

METHODS: The Human Phenotype Ontology …

Recent Advances In Wearable Sensing Technologies, Alfredo J. Perez, Sherali Zeadally

Information Science Faculty Publications

Wearable sensing technologies are having a worldwide impact on the creation of novel business opportunities and application services that are benefiting the common citizen. By using these technologies, people have transformed the way they live, interact with each other and their surroundings, their daily routines, and how they monitor their health conditions. We review recent advances in the area of wearable sensing technologies, focusing on aspects such as sensor technologies, communication infrastructures, service infrastructures, security, and privacy. We also review the use of consumer wearables during the coronavirus disease 19 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus …

Covid-19 And The Impact On Rural And Black Church Congregants: Results Of The C-M-C Project, Lovoria B. Williams, Anita F. Fernander, Tofial Azam, Maria L. Gomez, Junghee Kang, Cassidy L. Moody, Hannah Bowman, Nancy E. Schoenberg

Nursing Faculty Publications

The COVID-19 pandemic has had devastating effects on Black and rural populations with a mortality rate among Blacks three times that of Whites and both rural and Black populations experiencing limited access to COVID-19 resources. The primary purpose of this study was to explore the health, financial, and psychological impact of COVID-19 among rural White Appalachian and Black nonrural central Kentucky church congregants. Secondarily we sought to examine the association between sociodemographics and behaviors, attitudes, and beliefs regarding COVID-19 and intent to vaccinate. We used a cross sectional survey design developed with the constructs of the Health Belief and Theory …

Modes Of Transmission Of Severe Acute Respiratory Syndrome-Coronavirus-2 (Sars-Cov-2) And Factors Influencing On The Airborne Transmission: A Review, Mahdieh Delikhoon, Marcelo I. Guzman, Ramin Nabizadeh, Abbas Norouzian Baghani

Chemistry Faculty Publications

The multiple modes of SARS-CoV-2 transmission including airborne, droplet, contact, and fecal–oral transmissions that cause coronavirus disease 2019 (COVID-19) contribute to a public threat to the lives of people worldwide. Herein, different databases are reviewed to evaluate modes of transmission of SARS-CoV-2 and study the effects of negative pressure ventilation, air conditioning system, and related protection approaches of this virus. Droplet transmission was commonly reported to occur in particles with diameter >5 µm that can quickly settle gravitationally on surfaces (1–2 m). Instead, fine and ultrafine particles (airborne transmission) can stay suspended for an extended period of time (≥2 h) …

An Overview Of The Effect Of Bioaerosol Size In Coronavirus Disease 2019 Transmission, Marcelo I. Guzman

Chemistry Faculty Publications

The fast spread of coronavirus disease 2019 (COVID-19) constitutes a worldwide challenge to the public health, educational and trade systems, affecting the overall well-being of human societies. The high transmission and mortality rates of this virus, and the unavailability of a vaccine or treatment, resulted in the decision of multiple governments to enact measures of social distancing. Such measures can reduce the exposure to bioaerosols, which can result in pathogen deposition in the respiratory tract of the host causing disease and an immunological response. Thus, it is important to consider the validity of the proposal for keeping a distance of …

Viral Data, Agnieszka Leszczynski, Matthew Zook

Geography Faculty Publications

We are experiencing a historical moment characterized by unprecedented conditions of virality: a viral pandemic, the viral diffusion of misinformation and conspiracy theories, the viral momentum of ongoing Hong Kong protests, and the viral spread of #BlackLivesMatter demonstrations and related efforts to defund policing. These co-articulations of crises, traumas, and virality both implicate and are implicated by big data practices occurring in a present that is pervasively mediated by data materialities, deeply rooted dataist ideologies that entrench processes of datafication as granting objective access to truth and attendant practices of tracking, data analytics, algorithmic prediction, and data-driven targeting of individuals …

Simulating Phase Transitions And Control Measures For Network Epidemics Caused By Infections With Presymptomatic, Asymptomatic, And Symptomatic Stages, Benjamin Braun, Başak Taraktaş, Brian Beckage, Jane Molofsky

Mathematics Faculty Publications

We investigate phase transitions associated with three control methods for epidemics on small world networks. Motivated by the behavior of SARS-CoV-2, we construct a theoretical SIR model of a virus that exhibits presymptomatic, asymptomatic, and symptomatic stages in two possible pathways. Using agent-based simulations on small world networks, we observe phase transitions for epidemic spread related to: 1) Global social distancing with a fixed probability of adherence. 2) Individually initiated social isolation when a threshold number of contacts are infected. 3) Viral shedding rate. The primary driver of total number of infections is the viral shedding rate, with probability of …

Covid-19 Is Spatial: Ensuring That Mobile Big Data Is Used For Social Good, Age Poom, Olle Järv, Matthew Zook, Tuuli Toivonen

Geography Faculty Publications

The mobility restrictions related to COVID-19 pandemic have resulted in the biggest disruption to individual mobilities in modern times. The crisis is clearly spatial in nature, and examining the geographical aspect is important in understanding the broad implications of the pandemic. The avalanche of mobile Big Data makes it possible to study the spatial effects of the crisis with spatiotemporal detail at the national and global scales. However, the current crisis also highlights serious limitations in the readiness to take the advantage of mobile Big Data for social good, both within and beyond the interests of health sector. We propose …