TY  - JOUR
AU  - Chong, Ka Chun
AU  - Li, Kehang
AU  - Guo, Zihao
AU  - Jia, Katherine Min
AU  - Leung, Eman Yee Man
AU  - Zhao, Shi
AU  - Hung, Chi Tim
AU  - Yam, Carrie Ho Kwan
AU  - Chow, Tsz Yu
AU  - Dong, Dong
AU  - Wang, Huwen
AU  - Wei, Yuchen
AU  - Yeoh, Eng Kiong
PY  - 2023
DA  - 2023/3/7
TI  - Dining-Out Behavior as a Proxy for the Superspreading Potential of SARS-CoV-2 Infections: Modeling Analysis
JO  - JMIR Public Health Surveill
SP  - e44251
VL  - 9
KW  - COVID-19
KW  - contact tracing
KW  - unlinked
KW  - superspreading
KW  - dispersion
KW  - public health
KW  - surveillance
KW  - digital health surveillance
KW  - digital surveillance
KW  - disease spread
AB  - Background: While many studies evaluated the reliability of digital mobility metrics as a proxy of SARS-CoV-2 transmission potential, none examined the relationship between dining-out behavior and the superspreading potential of COVID-19. Objective: We employed the mobility proxy of dining out in eateries to examine this association in Hong Kong with COVID-19 outbreaks highly characterized by superspreading events. Methods: We retrieved the illness onset date and contact-tracing history of all laboratory-confirmed cases of COVID-19 from February 16, 2020, to April 30, 2021. We estimated the time-varying reproduction number (Rt) and dispersion parameter (k), a measure of superspreading potential, and related them to the mobility proxy of dining out in eateries. We compared the relative contribution to the superspreading potential with other common proxies derived by Google LLC and Apple Inc. Results: A total of 6391 clusters involving 8375 cases were used in the estimation. A high correlation between dining-out mobility and superspreading potential was observed. Compared to other mobility proxies derived by Google and Apple, the mobility of dining-out behavior explained the highest variability of k (ΔR-sq=9.7%, 95% credible interval: 5.7% to 13.2%) and Rt (ΔR-sq=15.7%, 95% credible interval: 13.6% to 17.7%). Conclusions: We demonstrated that there was a strong link between dining-out behaviors and the superspreading potential of COVID-19. The methodological innovation suggests a further development using digital mobility proxies of dining-out patterns to generate early warnings of superspreading events. 
SN  - 2369-2960
UR  - https://publichealth.jmir.org/2023/1/e44251
UR  - https://doi.org/10.2196/44251
UR  - http://www.ncbi.nlm.nih.gov/pubmed/36811849
DO  - 10.2196/44251
ID  - info:doi/10.2196/44251
ER  -