key: cord-0868145-nmpppztq authors: Das, A.; Gopalan, S. S. title: Epidemiology of CoVID-19 and predictors of recovery in the Republic of Korea date: 2020-05-11 journal: nan DOI: 10.1101/2020.05.07.20094094 sha: 660f52aed5a6b6fd3dd189b3305253127b443d07 doc_id: 868145 cord_uid: nmpppztq Background: The recent CoVID-19 pandemic has emerged as a threat to global health. Though current evidence on the epidemiology of the disease is emerging, very little is known about the predictors of recovery. We describe the epidemiology of confirmed CoVID-19 patients in Republic of Korea and identify predictors of recovery. Materials and methods: Using publicly available data for confirmed CoVID-19 cases from the Korea Centers for Disease Control and Prevention from January 20, 2020 to April 30, 2020, we undertook descriptive analyses of cases stratified by sex, age group, place of exposure, date of confirmation and province. Correlation was tested among all predictors (sex, age group, place of exposure and province) with the Pearsons correlation coefficient. Associations between recovery from CoVID-19 and predictors were estimated using a multivariable logistic regression model. Results: Majority of the confirmed cases were females (56 percent), from 20-29 age group (24.3 percent), and primarily from three provinces Gyeongsangbuk (36.9 percent), Gyeonggi (20.5 percent) and Seoul (17.1 percent). Case fatality ratio was 2.1 percent and 41.6 percent cases recovered. Older patients, patients from certain provinces such as Daegu, Gyeonggi, Gyeongsangbuk, Jeju, Jeollabuk and Jeollanam, and those contracting the disease from healthcare settings had lower recovery. Conclusions: Our study adds to the very limited evidence base on potential predictors of recovery among confirmed CoVID-19 cases. We call additional research to explore the predictors of recovery and support development of policies to protect the vulnerable patient groups. deaths due to CoVID-19 as of May 5, 2020. 4 We present the epidemiology of CoVID-19 in the Republic of Korea using data from Korea Centers for Disease Control and Prevention and identify the predictors of recovery from the disease. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 11, 2020. . https://doi.org/10.1101/2020.05.07.20094094 doi: medRxiv preprint The data were obtained from the Korea Centers for Disease Control and Prevention's publicly shared sources. The dataset contains information about 3,388 confirmed COVID-19 cases in the Republic of Korea from January 20, 2020 through April 30, 2020. After excluding cases with missing values, 3,299 cases were included in the analysis. A confirmed case was defined as a person with laboratory confirmed positive test. The data contained the following patient detailsage (in groups), sex, province, date of diagnosis, mode of exposure and outcome. There were 11 age groupsbelow 10 years, 10-19 years, 20-29 years, 30-39 years, 40-49 years, 50-59 years, 60-69 years, 70-79 years, 80-89 years, 90-99 years and above 100 years. We combined the last two age groups to create 90 years and above, and thus recategorized age to 10 groups. All seventeen provinces of the Republic of Korea were represented -Busan, Chungcheongbuk-do, Chungcheongnam-do, Daegu, Daejeon, Gangwon-do, Gwangju, Gyeonggi-do, Gyeongsangbuk-do, Gyeongsangnam-do, Incheon, Jeju-do, Jeollabukdo, Jeollanam-do, Sejong, Seoul, and Ulsan. We categorized the dates of diagnosis by weeks, and they were as follows -20-26 Jan 2020, 27 Jan-02 Feb 2020, 03-09 Feb 2020, 10- Apr 2020. Patients were exposed to potential CoVID-19 sources in multiple settings. The settings were nursing home, hospital, religious gathering, call center, community center, shelter and apartment, gym facility, overseas inflow, contact with patients and others. There were three . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 11, 2020. . https://doi.org/10.1101/2020.05.07.20094094 doi: medRxiv preprint outcomesdeath, recovery and isolation. The confirmed patients after spending some days in isolation were retested. They were considered as recovered only after receiving a negative COVID-19 test. We undertook descriptive analyses for the patient characteristics and presented the results stratified by sub-groups for each characteristic. Correlation was tested among all patient characteristics with the Pearson's correlation coefficient. Associations between recovery from CoVID-19 and predictors (age group, sex, province and exposure) were estimated using a multivariable logistic regression model. We considered associations statistically significant if the p-value was below 0.05. The statistical analyses were performed using Python programming . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 11, 2020. . https://doi.org/10.1101/2020.05.07.20094094 doi: medRxiv preprint As shown in figure 1 , the first case of CoVID-19 was confirmed on January 20, 2020. There were a few daily cases of new infections for about a month. After a month, the curve suddenly rose starting February 19, 2020 to reach the peak around end of February and early March. It Table 1 shows the profile of the patients. Out of 3,299 confirmed patients, a slightly more than half were females (56%). While there were cases from all age groups, the maximum patients is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 11, 2020. . https://doi.org/10.1101/2020.05.07.20094094 doi: medRxiv preprint were from 20-29 years (24.3%), followed by 50-59 years (18.1%), 40-49 years (13.8%), 30-39 years (13.3%) and 60-69 years (12.2%). Three provinces -Gyeongsangbuk-do (36.9%), Gyeonggi-do (20.5%) and Seoul (17.1%)together accounted for the maximum patients. With respect to the exposure, it was unknown for the most (44%) followed by direct contact with patients (29%), from overseas (16.8%) and religious gathering (4.9%). According to this available data source, 85% percent of the patients were confirmed of their diagnosis between 24 February and 05 April of 2020. There were 61 deaths accounting for 2.1 percent (case fatality rate) of the patients. More than half were isolated (56.3%) and 41.6% recovered. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 11, 2020. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 11, 2020. . https://doi.org/10.1101/2020.05.07.20094094 doi: medRxiv preprint As shown in figure 2, there were strong no correlations between the predictors. Compared to younger age groups (table 2) When compared with exposure from nursing homes, patients who were exposed to COVID-19 infection from religious gatherings, community dwellings, and others had higher recovery rates. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 11, 2020 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 11, 2020. Our study shows that females constituted the majority of confirmed cases, whereas males accounted for most of the confirmed cases in China and Italy. [6] [7] [8] [9] Around a fourth of the cases were from 20-29 years age group unlike in most other countries where the infected were older. 6, 7 The possible reason for higher representation of younger population in our sample could be specific exposure to cluster of cases through participation in religious activities or workplaces. 5, 10 The case fatality rate was much lower (2.1%) compared to other countries such as Italy (13.3%) and China (4%). Similar to findings from several other countries, we found the elderly to be more vulnerable with lower probabilities of recovery. 6, 8, 11 It is quite possible that presence of pre-existing medical conditions in elderly predispose them to delayed recovery. We also found cases contracting the infection in non-healthcare setting had higher recovery. While there is no such evidence currently, there could be a possibility that the exposure outside non-healthcare setting might have involved relative younger and healthier cases. Considering our study findings, we suggest additional measures to protect the vulnerable cases who are less likely to recover from the infection. Thus, elderly and cases contracting infection from healthcare settings should be given special attention. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 11, 2020. Our study has two potential limitations. First, we used publicly available data of only a third of confirmed cases in the country. Thus, we are unable to ascertain the representativeness of the data for all confirmed cases in South Korea. So, the findings will have to be interpreted with caution. Secondly, the data lacks information of patients' symptoms and clinical features. Inclusion of these potential predictors would have enhanced the relevance of this study further. Despite these limitations, our study adds to the very limited evidence base on potential predictors of recovery among confirmed CoVID-19 cases. 12 However, we believe the evidence base be strengthened with further relevant research as authorities make more data publicly available or through primary hospital based studies. The CoVID-19 pandemic has emerged as a great threat to global health challenging health systems across the world to efficiently deal with this situation. Emerging evidence on vulnerability to COVID-19 and predictors of recovery will inform providers and policy makers to effectively triage and prioritize limited resources. Therefore, we call for additional research to explore the predictors of recovery and support development of policies to protect the vulnerable patient groups. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 11, 2020. . https://doi.org/10.1101/2020.05.07.20094094 doi: medRxiv preprint The data used to support the findings of this study are available publicly through the Korea Centers for Disease Control and Prevention. The authors declare that there is no conflict of interest. The views expressed in the paper are that of the authors and do not reflect that of their affiliations. This particular work was conducted outside of the authors' organizational affiliations. This study did not receive funding from any source. WHO. WHO Coronavirus disease (COVID-2019) situation reports 2020 Epidemiological characteristics of 2019 novel coronavirus: an interim review Coronavirus disease-19: The first 7,755 cases in the Republic of Korea Coronavirus Disease 2019 (COVID-19) in Italy Clinical Characteristics of Coronavirus Disease 2019 in China Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study Coronavirus Disease Outbreak in Call Center Epidemiological characteristics of coronavirus disease 2019 (COVID-19) patients in IRAN: A single center study Data Analysis of Coronavirus CoVID-19 Epidemic in South Korea Based on Recovered and Death Cases We are grateful to Korea Centers for Disease Control and Prevention for making this data publicly available.. CC-BY-NC-ND 4.0 International license It is made available under a