1. A Direct Observation Video Method for Describing COVID-19 Transmission Factors on a Micro-Geographical Scale: Viral Transmission (VT)-Scan
- Author
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Gregory M. Dominick, Richard R. Suminski, and Norman J. Wagner
- Subjects
Male ,medicine.medical_specialty ,Coronavirus disease 2019 (COVID-19) ,Computer science ,Distancing ,Health, Toxicology and Mutagenesis ,infectious disease ,Viral transmission ,Audiology ,Article ,law.invention ,Correlation ,observation method ,health behavior ,law ,medicine ,Humans ,Pandemics ,Environmental Setting ,SARS-CoV-2 ,pandemic ,public health ,Public Health, Environmental and Occupational Health ,Direct observation ,Masks ,COVID-19 ,Reproducibility of Results ,Transmission (mechanics) ,Scale (social sciences) ,Medicine ,Female ,measurement - Abstract
The COVID-19 pandemic severely affected many aspects of human life. While most health agencies agree mask wearing and physical distancing reduce viral transmission, efforts to improve the assessment of these behaviors are lacking. This study aimed to develop a direct observation video method [Viral Transmission (VT)-Scan] for assessing COVID-19 transmission behaviors and related factors (e.g., environmental setting). A wearable video device (WVD) was used to obtain videos of outdoor, public areas. The videos were examined to extract relevant information. All outcomes displayed good to excellent intra- and inter-reliability with intra-class correlation coefficients ranging from 0.836 to 0.997. The majority of people had a mask (60.8%) but 22.1% of them wore it improperly, 45.4% were not physical distancing, and 27.6% were simultaneously mask and physical distancing non-compliant. Transmission behaviors varied by demographics with white, obese males least likely to be mask-compliant and white, obese females least likely to physical distance. Certain environments (e.g., crosswalks) were identified as “hot spots” where higher rates of adverse transmission behaviors occurred. This study introduces a reliable method for obtaining objective data on COVID-19 transmission behaviors and related factors which may be useful for agent-based modeling and policy formation.
- Published
- 2021