ArticleJournal of preventive medicine and public health = Yebang Uihakhoe chi2026
Missing Occupation, Missing Risk: Insights From COVID-19 Case Investigation Data in Busan, South Korea.
Article in Journal of preventive medicine and public health = Yebang Uihakhoe chi, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivesThis study evaluated the quality and analytic utility of occupational data in coronavirus disease 2019 (COVID-19) case investigation records from Busan, South Korea, during the period of comprehensive surveillance in 2020-2021, when occupation was inconsistently integrated into routine case reporting despite its importance for infection-risk assessment.
methodsWe analyzed 25 283 confirmed COVID-19 cases reported between February 21, 2020, and December 31, 2021. Occupational information was extracted from investigation forms, epidemiological reports, and electronic medical records. We assessed completeness, internal inconsistencies, and codability to the Korean Standard Classification of Occupations (KSCO), and examined temporal trends across pandemic phases. Descriptive statistics and manual reviews of free-text entries were conducted.
resultsOccupational information was recorded for nearly all investigated cases in 2020-2021 (>99%), but entries were often vague ("unemployed," "other") or institutional ("school," "hospital"), which limited their utility. A minority of entries could be standardized to KSCO 1-3-digit categories because of ambiguous wording or contradictions between occupation and workplace. Although data collection virtually ceased in 2022 and 2023 after individual-level investigations were discontinued, patterns in the 2020-2021 dataset already showed that design flaws in the occupation field reduced analytic value.
conclusionsBusan's early COVID-19 surveillance system recorded occupation for nearly all cases but produced limited analyzable information. The disconnect between data entry and analytic usefulness highlights the need for structured, dual occupation-industry coding, searchable picklists, and real-time quality checks so that occupational risk can be systematically identified and incorporated into future pandemic preparedness and response.
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