How common are high-risk coronavirus contacts? A video-observational analysis of outdoor public place behavior during the COVID-19 pandemic

Epidemiological evidence and recommendations from the World Health Organization suggest that close face-to-face interactions pose a particular coronavirus transmission risk. The real-life prevalence and nature of such high-risk contacts are understudied, however. Here, we video-observed high-risk contacts in outdoor public places in Amsterdam, the Netherlands, during the COVID-19 pandemic. We found that high-risk contacts were relatively uncommon: Of the 7,813 individuals observed, only 20 (0.26%) displayed high-risk contacts. Further, we qualitatively examined the 20 high-risk contacts identified and found that they occurred disproportionally between affiliated persons engaged in affiliative behaviors. We discuss the potential public health implications of the relatively low incident rate of high-risk contacts

Human Observers Are Accurate in Judging Personal Relationships in Real-life Settings:A Methodological Tool for Human Observational Research

One limitation of the naturalistic observation method is that it is understudied how accurately personal relationships may be judged by observers in real-life settings. To assess this judgment accuracy, we observed 285 dyads of individuals in public places and then asked whether they were affiliated or strangers. We found that human observers were very accurate in judging peoples’ actual personal relationships. Moreover, several nonverbal cues, including direct interaction and age similarities, were identified as correlates of affiliation. We conclude that researchers may accurately judge personal relationships from nonverbal observational data and recommend that this should be utilized as a methodological tool in naturalistic observational studies.</p

Face-touching behaviour as a possible correlate of mask-wearing: A video observational study of public place incidents during the COVID-19 pandemic

Most countries in the world have recommended or mandated face masks in some or all public places during the COVID-19 pandemic. However, mask use has been thought to increase people's face-touching frequency and thus risk of self-inoculation. Across two studies, we video-observed the face-touching behaviour of members of the public in Amsterdam and Rotterdam (the Netherlands) during the first wave of the pandemic. Study 1 (n = 383) yielded evidence in favour of the absence of an association between mask-wearing and face-touching (defined as touches of face or mask), and Study 2 (n = 421) replicated this result. Secondary outcome analysis of the two studies-analysed separately and with pooled data sets-evidenced a negative association between mask-wearing and hand contact with the face and its t-zone (i.e. eyes, nose and mouth). In sum, the current findings alleviate the concern that mask-wearing has an adverse face-touching effect

Promise Into Practice:Application of Computer Vision in Empirical Research on Social Distancing

Social scientists increasingly use video data, but large-scale analysis of its content is often constrained by scarce manual coding resources. Upscaling may be possible with the application of automated coding procedures, which are being developed in the field of computer vision. Here, we introduce computer vision to social scientists, review the state-of-the-art in relevant subfields, and provide a working example of how computer vision can be applied in empirical sociological work. Our application involves defining a ground truth by human coders, developing an algorithm for automated coding, testing the performance of the algorithm against the ground truth, and running the algorithm on a large-scale dataset of CCTV images. The working example concerns monitoring social distancing behavior in public space over more than a year of the COVID-19 pandemic. Finally, we discuss prospects for the use of computer vision in empirical social science research and address technical and ethical challenges.</p