Superspreading potential of infection seeded by the SARS-CoV-2 Omicron BA.1 variant in South Korea

Abstract

As a distinct feature of the COVID-19 transmission, superspreading1Majra D. Benson J. Pitts J. Stebbing J. SARS-CoV-2 (COVID-19) superspreader events.J Infect. 2021; 82: 36-40Abstract Full Text Full Text PDF PubMed Scopus (59) Google Scholar, 2Schepers M. Zanger P. Jahn K. König J. Strauch K. Gianicolo E. Multi-household social gatherings contribute to the second SARS-CoV-2 wave in Rhineland-Palatinate, Germany.J Infect. 2020; 4 (2022): 551-557Google Scholar plays an essential role for fueling the disease transmissions in the outbreaks caused by the recent SARS-CoV-2 (B.1.1.529) Omicron variant. In South Korea, superspreading events (SSEs) frequently occurred and thus posed considerable challenges for controlling COVID-19 outbreak through contact tracing.3Lee H. Han C. Jung J. Lee S. Analysis of superspreading potential from transmission clusters of COVID-19 in South Korea.Int J Environ Res Public Health. 2021; 18: 12893Crossref PubMed Scopus (4) Google Scholar Assessing the potential of superspreading could provide insight into the transmissibility of the emerged variant. Here, we used line-list epidemiological contact tracing data that collected during an Omicron outbreak in South Korea to estimate the superspreading potential of the Omicron BA.1 variant.We obtained data of 427 laboratory-confirmed cases infected by the Omicron BA.1 variant from 25 November to 31 December 2021 in South Korea4Kim D. Ali S.T. Kim S. Jo J. Lim J.-.S. Lee S. et al.Estimation of serial interval and reproduction number to quantify the transmissibility of SARS-CoV-2 omicron variant in South Korea.Viruses. 2022; 14: 533Crossref PubMed Scopus (13) Google Scholar. We extracted the contact tracing information and vaccination history for each case. Their contact settings were classified into household, community (including infectious contactoccurred within churches, restaurants, workplaces, and social contacts), and school. Case clusters infected by the same infector were identified to construct a negative binomial model governed by the reproduction number (R) and dispersion (k)5Lloyd-Smith J.O. Schreiber S.J. Kopp P.E. Getz W.M. Superspreading and the effect of individual variation on disease emergence.Nature. 2005; 438: 355-359Crossref PubMed Scopus (1489) Google Scholar, a parameter to characterize the heterogeneity in individual transmissibility. Technical details of the statistical models and parameter estimations were described in the Supplementary material.Of the 427 cases, 85 (19.9%) cases led to at least one secondary cases (Fig. S1), with one case directly seeded 78 cases in the community setting (Fig. S2). Of the 156 cases with known vaccine status, 84 (53.8%), 2 (1.3%), and 70 (44.9%) of them were unvaccinated, received one dose, and two doses, respectively. The R and k were estimated at 0.78 (95% confidence interval (CI): 0.58–1.08) and 0.10 (95% CI: 0.08–0.13), respectively. We inferred that 80% of all transmissions were generated by 9% of the most infectious cases. Community settings had a higher transmission risk and superspreading potential than household and school (lower k value compared to household and school) (Fig. 1A and Table 1). Furthermore, unvaccinated cases had a higher potential in seeding SSEs. The probability of an unvaccinated case seeding an outbreak with ≥100 cases was 7%, as compared to 0.4% for that of a vaccinated case (Fig. 1B).Table 1Estimated reproduction number (R), dispersion (k), and superspreading potential by contact settings and vaccination status.Reproduction number (95%CI)Dispersion (95%CI)Expected Proportion of seed cases generating 80% of transmission,%Contact SettingsHousehold (n = 427)0.22 (0.17–0.30)0.14 (0.09–0.23)8%Community (n = 427)0.35 (0.19–0.74)0.02 (0.02–0.03)2%School (n = 427)0.21 (0.13–0.36)0.04 (0.03–0.06)4%Vaccination statusVaccinated (n = 72)0.47 (0.24–1.10)0.13 (0.06–0.28)10%Unvaccinated (n = 84)1.26 (0.88–1.87)0.44 (0.26–0.75)22%Total (n = 427)0.78 (0.58–1.08)0.10 (0.08–0.13)9% Open table in a new tab Our findings suggest that the transmission of the BA.1 variant had high potential of superspreading, which is higher than the Delta variants6Ryu S. Kim D. Lim J.-.S. Ali S.T. Cowling B.J Serial interval and transmission dynamics during SARS-CoV-2 Delta variant predominance, South Korea.Emerg Infect Dis. 2022; 28: 407-410Crossref PubMed Scopus (15) Google Scholar, and other historical SARS-CoV-2 strains7Wang J. Chen X. Guo Z. Zhao S. Huang Z. Zhuang Z. et al.Superspreading and heterogeneity in transmission of SARS, MERS, and COVID-19: a systematic review.Comput Struct Biotechnol J. 2021; 19: 5039-5046Abstract Full Text Full Text PDF PubMed Scopus (7) Google Scholar. The BA.1 variant appeared more transmissible with a higher risk of superspreading within community settings than in household and school settings. In addition to contact settings, vaccination status was also a potential risk modifier.Given a generally larger scale favoring the social contacts, the transmissibility and superspreading potential of the BA.1 variant were high in community settings. As shown in Figure S2, large SSEs within the community occurred at the edge of the transmission chain, which offers greater opportunity for continuously spreading. The overdispersion feature of the case-cluster distributions across different contact settings could result in a lower effectiveness of population-wide control measures5Lloyd-Smith J.O. Schreiber S.J. Kopp P.E. Getz W.M. Superspreading and the effect of individual variation on disease emergence.Nature. 2005; 438: 355-359Crossref PubMed Scopus (1489) Google Scholar because of the heterogeneity in individual transmissibility, that is, only a few cases generated majority of the infections. As such, public health interventions that are developed to trim the “long-tailed events” (i.e., SSEs) of the case-cluster distributions would disproportionately reduce the virus transmissibility and thereby suppress the outbreak. Given the behavioral and biological factors including social gatherings and high viral load within the host are well-established key drivers of SSEs, enforcement of the monitoring and physical distancing in high-risk settings (e.g., churches, restaurants, and health care facilities)8Wong N.S. Lee S.S. Kwan T.H. Yeoh E.-.K. Settings of virus exposure and their implications in the propagation of transmission networks in a COVID-19 outbreak.Lancet Reg Health West Pac. 2020; 4100052Google Scholar, accompanied by timely identification and isolation of highly infectious cases should be the focal points for controlling the Omicron outbreaks.Additionally, given that vaccinated cases had a diminished transmissibility and a lower superspreading potential than unvaccinated cases, we speculated that T cells induced by the vaccine may lower the infectivity of the Omicron cases. During the study period, three types of COVID-19 vaccine, including mRNA, viral vector, and subunit vaccine were used in South Korea. Despite a relatively low effectiveness of these vaccines against the Omicron infection due to immune escape, immunization should be promoted to lower the transmissibility and mitigate the outbreak size.Because only self-limited case clusters were observed, our findings may only serve as preliminary results for assessing the superspreading potential of the ongoing epidemics in South Korea. Nevertheless, we highlighted the importance of monitoring the superspreading potential under different settings and for other emerging variants. While two doses of vaccination may significantly contribute to reducing the transmissibility of cases infected with the BA.1 variant, administration of the booster dose is warranted given that the protection from vaccination would wane over time.FundingThis research was supported by Health and Medical Research Fund [grant numbers COVID190105, INF-CUHK-1], National Natural Science Foundation of China [71974165], Group Research Scheme from The Chinese University of Hong Kong, Guangdong-Hong Kong-Macau Joint Laboratory of Respiratory Infectious Disease [grant numbers 20191205], and visiting scientist scheme from Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore. As a distinct feature of the COVID-19 transmission, superspreading1Majra D. Benson J. Pitts J. Stebbing J. SARS-CoV-2 (COVID-19) superspreader events.J Infect. 2021; 82: 36-40Abstract Full Text Full Text PDF PubMed Scopus (59) Google Scholar, 2Schepers M. Zanger P. Jahn K. König J. Strauch K. Gianicolo E. Multi-household social gatherings contribute to the second SARS-CoV-2 wave in Rhineland-Palatinate, Germany.J Infect. 2020; 4 (2022): 551-557Google Scholar plays an essential role for fueling the disease transmissions in the outbreaks caused by the recent SARS-CoV-2 (B.1.1.529) Omicron variant. In South Korea, superspreading events (SSEs) frequently occurred and thus posed considerable challenges for controlling COVID-19 outbreak through contact tracing.3Lee H. Han C. Jung J. Lee S. Analysis of superspreading potential from transmission clusters of COVID-19 in South Korea.Int J Environ Res Public Health. 2021; 18: 12893Crossref PubMed Scopus (4) Google Scholar Assessing the potential of superspreading could provide insight into the transmissibility of the emerged variant. Here, we used line-list epidemiological contact tracing data that collected during an Omicron outbreak in South Korea to estimate the superspreading potential of the Omicron BA.1 variant. We obtained data of 427 laboratory-confirmed cases infected by the Omicron BA.1 variant from 25 November to 31 December 2021 in South Korea4Kim D. Ali S.T. Kim S. Jo J. Lim J.-.S. Lee S. et al.Estimation of serial interval and reproduction number to quantify the transmissibility of SARS-CoV-2 omicron variant in South Korea.Viruses. 2022; 14: 533Crossref PubMed Scopus (13) Google Scholar. We extracted the contact tracing information and vaccination history for each case. Their contact settings were classified into household, community (including infectious contact occurred within churches, restaurants, workplaces, and social contacts), and school. Case clusters infected by the same infector were identified to construct a negative binomial model governed by the reproduction number (R) and dispersion (k)5Lloyd-Smith J.O. Schreiber S.J. Kopp P.E. Getz W.M. Superspreading and the effect of individual variation on disease emergence.Nature. 2005; 438: 355-359Crossref PubMed Scopus (1489) Google Scholar, a parameter to characterize the heterogeneity in individual transmissibility. Technical details of the statistical models and parameter estimations were described in the Supplementary material. Of the 427 cases, 85 (19.9%) cases led to at least one secondary cases (Fig. S1), with one case directly seeded 78 cases in the community setting (Fig. S2). Of the 156 cases with known vaccine status, 84 (53.8%), 2 (1.3%), and 70 (44.9%) of them were unvaccinated, received one dose, and two doses, respectively. The R and k were estimated at 0.78 (95% confidence interval (CI): 0.58–1.08) and 0.10 (95% CI: 0.08–0.13), respectively. We inferred that 80% of all transmissions were generated by 9% of the most infectious cases. Community settings had a higher transmission risk and superspreading potential than household and school (lower k value compared to household and school) (Fig. 1A and Table 1). Furthermore, unvaccinated cases had a higher potential in seeding SSEs. The probability of an unvaccinated case seeding an outbreak with ≥100 cases was 7%, as compared to 0.4% for that of a vaccinated case (Fig. 1B). Our findings suggest that the transmission of the BA.1 variant had high potential of superspreading, which is higher than the Delta variants6Ryu S. Kim D. Lim J.-.S. Ali S.T. Cowling B.J Serial interval and transmission dynamics during SARS-CoV-2 Delta variant predominance, South Korea.Emerg Infect Dis. 2022; 28: 407-410Crossref PubMed Scopus (15) Google Scholar, and other historical SARS-CoV-2 strains7Wang J. Chen X. Guo Z. Zhao S. Huang Z. Zhuang Z. et al.Superspreading and heterogeneity in transmission of SARS, MERS, and COVID-19: a systematic review.Comput Struct Biotechnol J. 2021; 19: 5039-5046Abstract Full Text Full Text PDF PubMed Scopus (7) Google Scholar. The BA.1 variant appeared more transmissible with a higher risk of superspreading within community settings than in household and school settings. In addition to contact settings, vaccination status was also a potential risk modifier. Given a generally larger scale favoring the social contacts, the transmissibility and superspreading potential of the BA.1 variant were high in community settings. As shown in Figure S2, large SSEs within the community occurred at the edge of the transmission chain, which offers greater opportunity for continuously spreading. The overdispersion feature of the case-cluster distributions across different contact settings could result in a lower effectiveness of population-wide control measures5Lloyd-Smith J.O. Schreiber S.J. Kopp P.E. Getz W.M. Superspreading and the effect of individual variation on disease emergence.Nature. 2005; 438: 355-359Crossref PubMed Scopus (1489) Google Scholar because of the heterogeneity in individual transmissibility, that is, only a few cases generated majority of the infections. As such, public health interventions that are developed to trim the “long-tailed events” (i.e., SSEs) of the case-cluster distributions would disproportionately reduce the virus transmissibility and thereby suppress the outbreak. Given the behavioral and biological factors including social gatherings and high viral load within the host are well-established key drivers of SSEs, enforcement of the monitoring and physical distancing in high-risk settings (e.g., churches, restaurants, and health care facilities)8Wong N.S. Lee S.S. Kwan T.H. Yeoh E.-.K. Settings of virus exposure and their implications in the propagation of transmission networks in a COVID-19 outbreak.Lancet Reg Health West Pac. 2020; 4100052Google Scholar, accompanied by timely identification and isolation of highly infectious cases should be the focal points for controlling the Omicron outbreaks. Additionally, given that vaccinated cases had a diminished transmissibility and a lower superspreading potential than unvaccinated cases, we speculated that T cells induced by the vaccine may lower the infectivity of the Omicron cases. During the study period, three types of COVID-19 vaccine, including mRNA, viral vector, and subunit vaccine were used in South Korea. Despite a relatively low effectiveness of these vaccines against the Omicron infection due to immune escape, immunization should be promoted to lower the transmissibility and mitigate the outbreak size. Because only self-limited case clusters were observed, our findings may only serve as preliminary results for assessing the superspreading potential of the ongoing epidemics in South Korea. Nevertheless, we highlighted the importance of monitoring the superspreading potential under different settings and for other emerging variants. While two doses of vaccination may significantly contribute to reducing the transmissibility of cases infected with the BA.1 variant, administration of the booster dose is warranted given that the protection from vaccination would wane over time. FundingThis research was supported by Health and Medical Research Fund [grant numbers COVID190105, INF-CUHK-1], National Natural Science Foundation of China [71974165], Group Research Scheme from The Chinese University of Hong Kong, Guangdong-Hong Kong-Macau Joint Laboratory of Respiratory Infectious Disease [grant numbers 20191205], and visiting scientist scheme from Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore.