Understanding the Community Risk Perceptions of the COVID-19 Outbreak in South Korea: Infodemiology Study

• DOI: 10.2196/19788
• Publication Date: 2020-09-15T02:10:38Z
• Authors: Atina Husnayain; Eunha Shim; Anis Fuad; Emily Chia-Yu Su
• Keywords: 2019-20 coronavirus outbreak

South Korea is among the best-performing countries in tackling coronavirus pandemic by using mass drive-through testing, face mask use, and extensive social distancing. However, understanding patterns of risk perception could also facilitate effective communication to minimize impacts disease spread during this crisis.We attempt explore community health perceptions COVID-19 internet search data.Google Trends (GT) NAVER relative volumes (RSVs) data were collected COVID-19-related terms Korean language retrieved according time, gender, age groups, types device, location. Online queries compared number daily new cases tests reported Kaggle open-access set for time period December 5, 2019, May 31, 2020. Time-lag correlations calculated Spearman rank correlation coefficients employed assess whether between searches affected time. We constructed a prediction model cases, tests, GT RSVs lag periods (of 1-3 days). Single multiple regressions backward elimination variance inflation factor <5.The numbers increased local events including transmission, approval test kits, implementation shortage, widespread campaign distancing as well international such announcement Public Health Emergency International Concern World Organization. stronger women (r=0.763-0.823; P<.001) groups ≤29 years (r=0.726-0.821; P<.001), 30-44 (r=0.701-0.826; ≥50 (r=0.706-0.725; P<.001). In spatial distribution, higher areas. Moreover, greater found mobile (r=0.704-0.804; those desktop (r=0.705-0.717; indicating changing behaviors searching online information outbreak. These varied related represented perceptions. addition, country with high results showed that adults perceived test-related being more important than disease-related knowledge. Meanwhile, younger, older had different can potentially be used assessments predictions. Adding provided increase performance case-based predict epidemic curves.The use both beneficial targeting from several perspectives, population characteristics,