DOI: 10.17603/ds2-vdfr-hg21
title: Relating Egress Observations from Health Care Facilities During the Initial COVID-19 Outbreak to Demographics, Weather, and Census Data
title: in Egress Behavior from Select NYC COVID-19 Exposed Health Facilities March-May 2020

description: Egress behaviors, including PPE usage, route taken, primary and secondary destinations upon leaving the healthcare facility, and qualitative behavioral observations, were recorded at healthcare facilities throughout NYC during the onset of the COVID-19 pandemic. 16 students spent a combined 1,500 hours in the field collecting 5,065 unique records around 19 hospitals in 4 of the 5 NYC boroughs.  These records were georeferenced using Google MyMaps and GIS software (QGIS and ArcGIS) to provide location data corresponding to these recorded observations. By comparing this dataset to communities with similar demographics and census records, predictions can be made on social behaviors around healthcare facilities during other spikes of COVID-19 variants and pandemics of similar transmissibility and severity. By analyzing the most common touch points or vector surfaces (ex. Door handle, cell phone) and initial destinations (subway, nearby food vendors), public health programs can be informed to help mitigate spread.
description: This project describes a unique dataset of 5,065 records documenting the perishable behavior of 6,075 individuals around 19 hospitals and urgent care clinics across 4 of New York’s 5 boroughs at the height of the city’s COVID-19 outbreak in the Spring of 2020 (March 22-May 19). The records were collected opportunistically by 16 student observers over 1,500 hours across all hours of the day and days of the week. The records document the date, time, location, and gender, as well as objects touched, route taken, and destination selected (including various transportation options and specific types of retail establishments). Forty-nine percent of them also noted the usage or absence of personal protective equipment (PPE) usage. Subjects were observed from a distance for periods of up to 20 minutes or for a distance of 1.3 km or until they were no longer visible from a street location. Observations were scraped from kml/kmz records generated in-situ on personal smartphones and assembled in a master csv file. Each record was joined with locational information about the facility, 7 hourly weather attributes obtained from the closest weather station, and 61 attributes related to the demographics of the zip code in which the facility is located. These external data sources were drawn from Center for Disease Control (CDC) Vulnerability Index and the TimeandDate weather API. The cleaned data are available in a single csv file with a codebook and the individual kml/kmz files. Additionally, 20 percent of the spatial records are available in a joined dataset in a GIS system, in which the individual kmz files are joined as a single shapefile to demonstrate the high usability of the data. Initial observations include that 75 percent of individuals touched something, 11 percent touched their phone, 55 percent left the area by a form of mechanized transportation, 13 percent returned to the medical facility, and 81 percent were wearing PPE. This project was funded by a National Science Foundation grant, "RAPID: DETER: Developing Epidemiology mechanisms in Three-dimensions to Enhance Response,” Award 2027293, 05/20-4/21. A February 2022 update of the data files (v2) is a more complete version of all project data including maximum distance data. The project is also funded by the Data Science and Software Services (DS3) program and by the Moore and Sloane foundations through the NYU Moore Sloane Data Science Environment.