Predicting mobility using limited data during early stages of a pandemic.

The COVID-19 pandemic has changed consumer behavior substantially. In this study, we explore the drivers of consumer mobility in several metropolitan areas in the United States under the perceived risks of COVID-19. We capture multiple dimensions of perceived risk using local and national cases and death counts of COVID-19, along with real-time Google Trends data for personal protective equipment (PPE). While Google Trends data are popular inputs in many studies, the risk of multicollinearity escalates with the addition of more relevant terms. Therefore, multicollinearity-alleviating methods are needed to appropriately leverage information provided by Google Trends data. We develop and utilize a novel optimization scheme to induce linear models containing strictly significant covariates and minimal multicollinearity. We find that there are a variety of unique factors that drive mobility in different geographic locations, as well as several factors that are common to all locations.

21 Million Opportunities: a 19 Facility Investigation of Factors Affecting Hand-Hygiene Compliance via Linear Predictive Models.

This large-scale study, consisting of 21.3 million hand-hygiene opportunities from 19 distinct facilities in 10 different states, uses linear predictive models to expose factors that may affect hand-hygiene compliance. We examine the use of features such as temperature, relative humidity, influenza severity, day/night shift, federal holidays, and the presence of new medical residents in predicting daily hand-hygiene compliance; the investigation is undertaken using both a "global" model to glean general trends and facility-specific models to elicit facility-specific insights. The results suggest that colder temperatures and federal holidays have an adverse effect on hand-hygiene compliance rates, and that individual cultures and attitudes regarding hand hygiene exist among facilities.

A web-based registry for patients with sarcoidosis.

BACKGROUND/OBJECTIVE: The objective is to present the development of a novel web-based patient registry for sarcoidosis. We describe recruitment efforts and assess efficacy of internet-based advertising on recruitment. METHODS: "Worldwide Sarcoidosis Research Study (WISE)" started in 2011 under the domain www.sarcoidstudy.org. The registry includes thirteen patient-reported surveys about patient characteristics, diagnosis, and treatment. Effects of two internet-based advertising methods (geographically-broad versus geographically-targeted to high sarcoidosis search areas) on recruitment were analyzed with time series regression. RESULTS: Since 2011, over 1500 participants have registered (82% whites, 9% African Americans, 5% mixed, 4% other), with 23% of participants providing saliva samples for DNA. Median age is 43 years (range 21-80). African Americans were more frequently recruited via support groups, while whites had a higher frequency of finding the registry via internet. Generalized internet-based advertising significantly improved recruitment in all demographic groups (p<0.001). However, a higher response rate to internet-based advertising was seen in whites compared to African Americans(p<0.001), females versus males(p=0.043), higher income categories(p=0.048), and increased education level(p<0.001). Targeting advertising campaigns to geographical areas with high internet-search patterns for sarcoidosis, with different demographics, was not effective in raising registry recruitment above baseline or increasing diversity. CONCLUSIONS: A web-based registry is an effective method for establishing a cohort of patients with sarcoidosis invested in clinical research with DNA specimens. Despite limitations, opportunities for research in patient-oriented outcomes and broad internet-based research methodology are possible. Our results demonstrate that web-based approaches to recruit study subjects need to be focused to match different target populations.