OBJECTIVES This study aimed to evaluate the agreement of disease status collected through a survey of the Korean Atomic Bomb Survivor Cohort (K-ABC), compared with medical claim records from the Korean National Health Insurance Service (NHIS) database and the Korean Central Cancer Registry (KCCR).
METHODS
Data on the lifetime physician-diagnosed morbidities of 1,215 K-ABC participants were collected through an interviewer-administered questionnaire between 2020 and 2022. Survey data were linked to the NHIS and KCCR databases. Eleven diseases were included for validation. We evaluated the following indicators: sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, the area under the curve (AUC), and the kappa coefficient.
RESULTS
The mean (standard deviation) age was 62.1 (18.7) years, and 42.6% of the participants were aged ≥70 years. Hypertension and cataracts showed the highest prevalence rates (33.8% and 28.8%, respectively). Hypertension, diabetes, and cancer demonstrated high sensitivity (>0.8) and specificity (>0.9), whereas diabetes, cancer, myocardial infarction, angina pectoris, and asthma exhibited high accuracy (>0.9). In contrast, arthritis, allergic rhinitis, and asthma showed low sensitivity (<0.4) and kappa values (<0.3). In the participants aged ≥70 years, the kappa value was ≥0.4 for all diseases except arthritis, allergic rhinitis, and asthma.
CONCLUSIONS
The results from this initial analysis showed relatively high agreement between the survey and NHIS/KCCR databases, especially for hypertension, diabetes, and cancer. Our findings suggest that the information on morbidities collected through the questionnaires in this cohort was valid for both younger and older individuals.
OBJECTIVES To estimate time-variant reproductive number (R<sub>t</sub>) of coronavirus disease 19 based on either number of daily confirmed cases or their onset date to monitor effectiveness of quarantine policies.
METHODS
Using number of daily confirmed cases from January 23, 2020 to March 22, 2020 and their symptom onset date from the official website of the Seoul Metropolitan Government and the district office, we calculated R<sub>t</sub> using program R’s package “EpiEstim”. For asymptomatic cases, their symptom onset date was considered as -2, -1, 0, +1, and +2 days of confirmed date.
RESULTS
Based on the information of 313 confirmed cases, the epidemic curve was shaped like ‘propagated epidemic curve’. The daily R<sub>t</sub> based on R<sub>t_c</sub> peaked to 2.6 on February 20, 2020, then showed decreased trend and became <1.0 from March 3, 2020. Comparing both R<sub>t</sub> from R<sub>t_c</sub> and from the number of daily onset cases, we found that the pattern of changes was similar, although the variation of R<sub>t</sub> was greater when using R<sub>t_c</sub>. When we changed assumed onset date for asymptotic cases (-2 days to +2 days of the confirmed date), the results were comparable.
CONCLUSIONS
R<sub>t</sub> can be estimated based on R<sub>t_c</sub> which is available from daily report of the Korea Centers for Disease Control and Prevention. Estimation of R<sub>t</sub> would be useful to continuously monitor the effectiveness of the quarantine policy at the city and province levels.
Summary
Korean summary
우리나라 전체와 각 시도별 일별 증상 발현자 수 또는 확진자 수를 이용하여 추정한 Rt로 방역정책의 효과를 국가 및 시도 수준에서 지속적으로 모니터링 할 필요가 있다.
Citations
Citations to this article as recorded by
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