key: cord-0938330-3uuulkla
authors: Newall, A. T.; Leong, R.N.F.; Nazareno, A.; Muscatello, D. J.; Wood, J. G.; Kim, W. J.
title: Delay-adjusted age- and sex-specific case fatality rates for COVID-19 in South Korea: evolution in the estimated risk of mortality throughout the epidemic
date: 2020-10-02
journal: Int J Infect Dis
DOI: 10.1016/j.ijid.2020.09.1478
sha: c7f3bc674a81561f2a04602c016a2ab51a4ba266
doc_id: 938330
cord_uid: 3uuulkla

Objectives The aim of this study was to estimate delay-adjusted case fatality rates (CFRs) for COVID-19 in South Korea and evaluate how these estimates have evolved over time throughout the epidemic. Methods Data from the Korea Centers for Disease Control and Prevention (KCDC) were used to estimate age- and sex-specific CFRs for COVID-19 in South Korea up until the 12th June 2020. We applied statistical methods previously developed to adjust for the delay between diagnosis and death and presented both delay-adjusted and crude (unadjusted) CFRs throughout the epidemic. Results The overall estimated delay-adjusted CFR was 2.39% (3.05% for males and 1.92% for females). Within each age strata where deaths were reported, we found males had significantly higher CFRs than females. The estimated CFRs increased substantially from age 60 years in males and from 70 years in females. We found that both the delay-adjusted CFRs and crude CFRs evolved substantially, particularly early in the epidemic, converging only from mid-April 2020. Conclusions The CFRs for South Korea provide an estimate of mortality risk in a setting where case ascertainment is likely to be more complete. The evolution in CFRs throughout the epidemic highlights the need for caution when interpreting CFRs calculated at a given time point.

Estimation of case fatality rates (CFRs) is an important element of infectious disease risk assessment. As the SARS-CoV-2 (COVID- 19) pandemic has evolved, a number of studies have estimated CFRs from COVID-19 (Li et al., 2020) . However, the lack of availability of widespread testing in many settings has meant that estimates are likely to have been affected by substantial ascertainment bias toward severe cases. Some studies have developed and applied approaches to adjust for underreporting of less severe cases (Verity et al., 2020) , but an alternative approach is to estimate CFRs in settings where case ascertainment is more complete.

After the first case of COVID-19 in South Korea (Republic of Korea) was identified on the 20 th January 2020 (Korea Centers for Disease Control and Prevention, 2020c), a reverse transcription-polymerase chain reaction (RT-PCR) test kit for COVID-19 was rapidly developed and approved on the 4 th February 2020 . Testing capacity then rapidly increased and by the 31 st March 2020 South Korea was able to conduct 20,000 COVID-19 tests per day . Due to this rapid deployment of high levels of J o u r n a l P r e -p r o o f testing and intensive contract tracing (Korea Centers for Disease Control and Prevention, 2020a) South Korea is likely to have captured a high proportion of symptomatic COVID-19 cases. In addition, a substantial proportion of asymptomatic cases may have been detected as part of clinical clusters and/or as close contacts of cases (approximately 20% of all confirmed cases asymptomatic at discharge reported on the 16 th March 2020 (Chang-won, 2020) ).

Another important factor to consider when estimating CFRs for COVID-19 is the substantial delay between the diagnosis (reporting) of a case and death from the disease (Lipsitch et al., 2015) . While crude CFRs based on current reported cases and deaths are readily available, This study aims to estimate delay-adjusted age-and sex-specific case fatality rates for COVID-19 in South Korea and evaluate how these estimates evolved over time throughout the J o u r n a l P r e -p r o o f epidemic. Estimation of age-and sex-specific CFRs from COVID-19 is critical to better understand mortality risk within the population and to help inform planning for prevention and care of severe cases.

J o u r n a l P r e -p r o o f

The public data provided by the Korea Centers for Disease Control and Prevention (KCDC) (Korea Centers for Disease Control and Prevention, 2020d) were used to analyse ageand sex-specific delay-adjusted CFRs. The first case of COVID-19 in South Korea was identified on the 20 th January 2020 and the first death on the 19 th February 2020, however the age-and sexspecific data we used did not begin to be reported publicly until the 10 th March 2020. To allow detailed analysis by age and sex we used the 10 th March 2020 as our index date for the study, however when estimating the overall (all ages) CFR we used the index date of 29 th January 2020.

We analysed data up until the 12 th June 2020. The age groupings we explored were those aged 0-29, 30-49, 50-59, 60-69, 70-79, and 80+ years and these were further stratified by sex (male and female) to provide age-and sex-specific CFR estimates.

The statistical methods we used to estimate the delay-adjusted age-and sex-specific where , ( ) is the adjustment factor to account for the expected delay until death among diagnosed cases whose outcome is not yet known. This is expressed as where is the number of days since 10 th March 2020, our index date when both age-and sexstratified data were first made available, until day so that − is the delay time since a case was first confirmed. In principle, the CFR denominator by day is the sum of cases with known outcomes (e.g. died, , ( )) and the expected number of other cases predicted to have a known outcome, based on the delay distribution , among those still considered active ( , ( ) × ( , ( ) − , ( ))). For comparison, we also computed the crude daily CFRs given by , ( )/ , ( ).

To generate 95% confidence intervals (CIs), we assumed that Modified Jeffreys CIs were computed as ( ) is very close to 0% ensuring that the lower limit is bounded by 0% and the upper limit is adjusted so that the resulting CI has coverage probability of 95%.

To estimate the delay between diagnosis of a case and reporting of death we used a South

Korean study which reported on the first 66 deaths from COVID-19 (Korea Centers for Disease

Control and Prevention, 2020b). In the primary analysis we used the estimated delay between symptom onset and death (median 10 days; range 1-24) and as a sensitivity analysis we used the estimated delay between hospitalisation and death (median 5 days; range 0-16) (Korea Centers for Disease Control and Prevention, 2020b). We fitted differing lognormal distributions to these J o u r n a l P r e -p r o o f two delay distributions such that the medians of the distributions corresponded to the reported medians and the reported ranges corresponded to the 0 th (minimum) and 95 th percentiles to account for the right-skewness of the lognormal distributions (Appendix 1. Figure A1 ). The choice of a lognormal distribution was based on a previous study that found that this distribution type best fit data for delay until death (Linton et al., 2020) .

In addition to the primary methods used to estimate the delay-adjusted age-and sex- Appendix 2 provides an outline of the R code used to generate the results.

There was a substantially higher proportion of females (57.8%) among cases of COVID-19 during the period of analysis for South Korea. However, male deaths were slightly more frequent at 53.2% of total COVID-19 deaths recorded ( Table 1 ). The age distribution of cases was (approximately) similar to population estimates for South Korea (Figure 1 ), but with some differences, such as a lower proportion of total cases aged 30-49 years (24.4% vs 29.8% of the population). When disaggregated by sex, we also noted an increased proportion of cases in males aged over 80 years (3.3%) compared to the population (2.4%). Deaths recorded for COVID-19 increased substantially with age, with 49.3% of total deaths occurring in those aged over 80 years. The number of deaths increased at an earlier age in males than in females, 88.4%

of deaths in females were in those aged 70 years and above, compared with 70.1% in males ( Figure 1 ). There were no COVID-19 deaths recorded in those aged under 30 years in South

Korea during the period of analysis.

The crude and delay-adjusted CFRs were very similar at the end of the analysis ( Table 2 ). This is because enough time has elapsed from the peak in cases so that most cases resolved by the endpoint of the analysis, either by recovery or death. The estimated CFRs increased substantially from age 60 years in males and from 70 years in females. We found substantial and consistent differences in sex-specific CFRs within age groups, with estimates in younger males several times higher than females but based on small numbers of deaths. 

The delay-adjusted CFR was highly unstable in the initial period (Figure 1 ), increasing to very high levels shortly after the first death was reported on the 19 th February 2020 before declining rapidly. This early and rapid rise occurred because the number of deaths reported in late February increased at approximately the same time as cases started to increase (Appendix 1. Figure A6) and by sex (Appendix 1. Figure A7 ) also started at a very high level and rapidly declined. In these analyses, the CFR adjusted for the delay from symptom onset to death converged earlier on a value closer to the CFR at the end of the period of analysis, than either the CFR adjusted for the delay from hospitalisation to death or the crude CFR.

In scenario analysis, based on the alternative approach to adjust for delay outlined in 

We found that both crude and delay-adjusted CFRs for South Korea increased rapidly in older age, with males at substantially higher risk of death in all age strata where deaths were reported. This highlights the importance of presenting age-and sex-specific CFRs when assessing the risk of mortality from COVID-19, rather than reporting the overall CFR, which if given without appropriate context may result in a misleading assessment of the risk of mortality.

We found that both the estimated delay-adjusted CFRs and crude CFRs evolved substantially While we used South Korean data for the delay adjustment distributions, these were by necessity based on imperfect data on the delay from symptom onset to death (or hospitalisation to death) rather the data on the specific delay between reporting/diagnosis of a case and reporting of death. The median delay from symptom onset to death in Europe and the UK has been estimated at 11 days (European Centre for Disease Prevention and Control, 2020) which is similar to the 10-day median delay used in our primary analysis (Korea Centers for Disease

Control and Prevention, 2020b). The ECDC weekly surveillance report provides estimates of delays for European countries, however while delay from symptom onset and/or hospitalisation to death is available for many countries, delays from diagnosis to death are rarely reported (European Centre for Disease Prevention and Control, 2020). While these proxies for delay to death have been used in many studies to date (e.g. (Shim et al., 2020) ), caution is needed as these delays may differ to the delay from diagnosis of a case to reporting of death. (KOSIS), 2020), the age group who had the highest CFR, is relatively low compared to other high-income settings. For example, many European countries have substantially higher

proportions of their population aged over 80 years (2015 estimates, Italy = 6.5%, Spain = 5.9%, France = 5.8%) (Eurostat, 2016) . This may partly explain, for example, the higher all-age crude CFR in Italy of 13.9% (16 th June 2020 (Epicentro, 2020)). However, although population age structure is clearly important, even when comparing within the same age groups there were substantial differences in CFRs between countries. For example, in Italy those aged 60-69 years had a crude CFR of 10.6% (Epicentro, 2020), substantially higher than the CFR of 2.73% we estimated in the same age group in South Korea. In Italy, the crude CFR for persons aged over 70 years of approximately 30% (Epicentro, 2020) was more similar to estimates for those aged over 80 in South Korea. These large differences in age-specific CFR results are likely to reflect differences in the comprehensiveness of testing, with many milder cases potentially missed in some settings.

Alongside population demographics, differences in case demographics among settings may also help explain differences in CFRs (Sudharsanan et al., 2020) . For example, a relatively higher proportion of the recorded total cases of COVID-19 in South Korea were in younger adults compared with other countries, such as China and some other high-income countries (Natale et al., 2020) . Although the extent to which this reflects differences in the true number of infections by age or difference in testing practices between settings is difficult to ascertain.

Healthcare system differences and accessibility to these services may also help explain differences between settings. In South Korea, the healthcare system has generally not been The higher CFR estimated for males in South Korea is in line with other countries such as

Italy who found rates approximately 75%-100% higher in males than in females for those aged over 70 years and larger differences in younger age groups (Epicentro, 2020 provided some evidence to support substantial numbers of undiagnosed cases in South Korea (Song et al., 2020) . However, the successful control of the epidemic during our period of the analysis in South Korea suggests a relatively high degree of case capture. One complication with the South Korean data we used is that it includes a proportion of, but not all asymptomatic cases, which means it does not represent purely an estimate of symptomatic CFR but also does not reflect a CFR for all infections. Furthermore, the aggregated public data from the KCDC did not provide daily data by age and sex during the entire period. This limitation does not impact on our J o u r n a l P r e -p r o o f estimates of CFR at the end of the period of analysis as the cumulative number of cases and deaths were still available. However, there appears to have been occasional delays from the reporting of a death to the classification into the age-and sex-specific data used in our study.

Finally, although we found substantial and important differences by age and sex, further investigation is needed to better understand independent predictors of mortality risk for COVID- This study presents crude and delay-adjusted age-and sex-specific CFRs using data from South Korea, one of the most completely ascertained epidemics of COVID-19. The variation in the crude and delay-adjusted CFRs throughout the epidemic highlights the need for caution when interpreting these estimates, particularly earlier in the epidemic.

All authors declare they have no known conflicts of interest.

No funding was received to support this specific study.

Ethics approval was provided by the UNSW Human Research Advisory Panel Executive (HC200222).

J o u r n a l P r e -p r o o f

☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

June 2020). Shaded areas indicate the age groupings used. Population estimates for January 2020 obtained from public data from (Korean Statistical Information Service (KOSIS), 2020).

Shaded areas indicate the 95% confidence intervals for each case-fatality rate estimated. Note that the figure is capped at 15% but that the confidence intervals extend beyond this in the initial period (not shown). The index date for these estimates was the 29 th January 2020. 

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We wish to acknowledge all those involved in providing the public data we used from the Korea Centers for Disease Control and Prevention (KCDC) website.J o u r n a l P r e -p r o o f