Real world evidence of trade, test, isolated and quanrantine impact on covid 19 pademic response performance

iew ed Real world evidence of trace, test, isolation, and quarantine impact on the COVID-19 pandemic response performance ev Juhwan Oh1, Seung-sik Hwang2*, Khuong Quynh Long3, Minkyung Kim4, Kunhee Park5, Seunghyun Kwon6, Osvaldo Enrique Artaza Barrios7, Irene Torres8, Matthew M Kavanagh9, Naoki Kondo10, S Patrick Kaucher11, Hoang Van Minh12, Dong Roman Xu13, Mikael Rostila14, Caroline Benski15, Mellissa Withers16, Borwornsom Leerapan17, Myoungsoon You2, Cristiani Vieira Machado18, Chang-Chuan Chan19, Hwa-Young Lee20, Jeonghyun Shin1, Hyejin Jeong21, Sung-In Kim22, Soon Ae Kim4, Soo Kyung Park23, Judith McCool24, Lawrence O Gostin9, S.V Subramanian20, Jeffrey F Markuns25 27, Yun-Chul Hong1 27, Chris Bullen24 27, Jong-Koo Lee 27, Martin McKee26 27 National University College of Medicine, Seoul, Republic of Korea 2Seoul National University Graduate School of Public Health, Seoul, Republic of Korea 3Hasselt Foundation for International Healthcare, Seoul, Republic of Korea 5Gyunggi 6Korea Disease Control and Prevention in Osong, Republic of Korea University of the Americas in Santiago, Chile 8Fundacion Octaedro in Quito, Ecuador, 9Georgetown University School of Public Health in Kyoto, Japan 11Mailman 12Hanoi ot 10Kyoto University in Washington, D.C USA School of Public Health, Columbia University in New York, USA University of Public Health, Hanoi, Vietnam 13Southern Medical University in Guangzhou, Guangdong, China tn 7The Province in Suwon, Republic of Korea pe 4Korea University, Hasselt, Belgium er r 1Seoul University in Stockholm, Sweden 15University Hospital of Geneva, Geneva, Switzerland 16University of Southern California in Los Angeles, CA, USA rin 14Stockholm University Faculty of Medicine Ramathibodi Hospital in Bangkok, Thailand 18Oswaldo Cruz Foundation in Rio de Janeiro, Brazil 19National Taiwan University School of Public Health, Taipei, Taiwan 20Harvard T H Chan School of Public Health, Boston, MA, USA ep 17Mahidol 21Seoul National University Hospital, Seoul, Republic of Korea Correctional Institution in Dagegu, Republic of Korea Pr 22Daegu 23National Health Insurance Research Institute in Wonju, Republic of Korea This preprint research paper has not been peer reviewed Electronic copy available at: https://ssrn.com/abstract=3954082 University of Auckland School of Population Health, Auckland, New Zealand 25Boston University School of Medicine, Boston, MA, USA 26London 27These School of Hygiene and Tropical Medicine, London, UK authors contributed equally as co-senior authors *Corresponding author: Dr Seung-sik Hwang ev cyberdoc@snu.ac.kr iew ed 24The Pr ep rin tn ot pe er r Seoul National University Graduate School of Public Health, Seoul, Republic of Korea This preprint research paper has not been peer reviewed Electronic copy available at: https://ssrn.com/abstract=3954082 iew ed Background There is continuing uncertainty about the effectiveness of testing, tracing, isolation, and quarantine (TTIQ) policies during the pandemic Methods We developed proxy indicators of the implementation of TTIQ policies at subnational and national (Republic of Korea), and international level (111 countries) from the beginning of 2020 to September 2021 These were: proportion of quarantined population (“Q-proportion”) among newly diagnosed COVID-19 cases/week, ratio of quarantined people to cases, and ratio of negative tests to new cases, with higher values suggesting more complete TTIQ We used linear regression to analyze the association between TTIQ indicators and 1-week lagged cases and cumulative deaths, separating periods before and after vaccines becoming available ev Findings er r We found consistently inverse associations between TTIQ indicators and COVID-19 outcomes, with gradual attenuation as vaccination coverage rose Q-proportion overall (β= -0·091; p-value < 0·001) and log-transformed quarantined population per case (β ranges from -0·626; p < 0.001 to -0·288; p= 0·023) in each of provinces were negatively associated with log-transformed 1-week lagged incidence in Korea overall The strength of association decreased with greater vaccination coverage The ratio of negative test results/new case was also inversely associated with incidence (β= -1·19; p-value < 0·001) in Korea Globally, increasing negative test ratio was significantly associated with lower cumulative cases and deaths per capita, more so earlier in the pandemic Jurisdictions with lower vaccination coverage showed the strongest association Interpretation pe A real-world evaluation demonstrates an association between performance of testing, contact tracing, isolation, and quarantine and better disease outcomes Funding Pr ep rin tn ot Ministry of Foreign Affairs, Republic of Korea This preprint research paper has not been peer reviewed Electronic copy available at: https://ssrn.com/abstract=3954082 iew ed Introduction ev In many countries the focus of responses to COVID-19 changed in 2021 as vaccination and, to a lesser extent, advances in therapeutics taking center stage.(1,2) The attractions are obvious The non-pharmaceutical interventions (NPI) that proved so effective early in the pandemic(3,4) involved widespread social disruption, economic hardship, and collateral damage to health services.(5,6) Yet this new approach has struggled to cope with the Delta variant, even in those few countries that have achieved high rates of vaccine roll out.(7) Meanwhile, in large parts of the world the prospect of achieving high vaccination rates remains a distant hope, for many reasons, reflecting problems of both supply,(8) with inadequate production, a consequence in part of policies on intellectual property,(9) and inequitable distribution,(10) and of demand, including weak health system infrastructure, vaccine hesitancy,(11) and concerted campaigns of disinformation.(12) Even if high levels of global coverage could be achieved rapidly, waning vaccine effectiveness and the emergence of new variants of concern capable of evading immunity induced by current vaccines or past infection have challenged the hope that the first generation of vaccines would be the ‘magic bullet’.(13,14) Further outbreaks are inevitable(15) and NPIs will remain an essential part of the armamentarium of policy responses.(16–19) er r NPIs can be divided into general and targeted The former, affecting everyone living in a particular area, include stay-at-home orders and school closures The latter apply to individuals and their contacts, based on testing, contact tracing, and isolation and quarantine (TTIQ) The latter approach can be effective in certain circumstances without the need for generalized restrictions, as seen in the 1918 influenza pandemic.(20) Yet, while previously unimaginable advances in surveillance and testing should have made targeted approaches easier than in the past, many countries have opted for generalized restrictions when cases rose.(21) ot pe There are many reasons why this happened but, most often, it was because the capacity to implement TTIQ was inadequate or overwhelmed This is apparent in countries where it worked, at least initially, as in New Zealand, Vietnam, Taiwan, and Singapore).(22–25) They “bought time” by imposing generalized restrictions early, in some cases helped by having invested substantially in preparedness following their experience with SARS in 2003 In other countries, such as the United States, United Kingdom, and some countries in Western Europe, the initial restrictions were delayed, with even a few days having major consequences, exacerbated by underinvestment in preparedness and, in some, specific policy failures.(26,27) In others, particularly middle- and low-income countries facing resource constraints, weak public health capacity, and in particular ability to undertake mass testing,(28) limited what was possible rin Method tn It is, however, only fair to recognize that policymakers faced with the threat of a pandemic were in a difficult position It was not obvious how effective TTIQ would be and, even now, evaluations are limited, often based on experience in particular settings, such as the U.S state of Oregon or Guangzhou in China.(4) There is thus an urgent need to assess the effectiveness of TTIQ in limiting pandemic spread To this end, we have examined the association between cumulative COVID-19 cases and deaths and the implementation of TTIQ interventions, taking account of vaccination coverage, beginning with the experience of one country, the Republic of Korea, and extending our analysis, to the extent possible given data availability, in 111 jurisdictions worldwide Pr ep Study population and data The first analysis, of Korea, used three different data sources, the publicly available national dataset from by Seoul National University Asia Research Center sourced from the Korean Disease Control Agency: 1) cumulative COVID-19 cases, 2) deaths, 3) vaccinated people, and 4) number of negative test results of Korea; the authors’ curation of 5) daily numbers of quarantined population per case from the daily reports of the nine provincial governments, that report numbers quarantined; and the authors’ curation of 6) the proportion of the quarantined population among newly diagnosed COVID-19 cases per week (“Q-proportion”) reporting from the Korean Disease Control and Prevention Agency(29) which is publicly available every Monday The international data covered 111 jurisdictions using three sets of publicly available data: cumulative COVID-19 cases, 2) deaths and 3) vaccinated people per million in each jurisdiction population retrieved from the dataset curated by Our World in Data,(30) which is sourced from multiple national databases by the Center for Systems Science and Engineering at Johns Hopkins University This preprint research paper has not been peer reviewed Electronic copy available at: https://ssrn.com/abstract=3954082 ev iew ed Variables Independent variables We used three proxy or latent variables to estimate the implementation of TTIQ If the system is working well, the number of people tested and quarantined per case will be high as will the proportion of negative tests (as a very high positivity rate suggests that true cases are being missed) In the national analysis, where we had the most granular data, we first used the proportion of the quarantined population among newly diagnosed COVID-19 cases per week This was based on the hypothesis that the greater the completeness of tracing, the greater the proportion of newly confirmed cases that will be found among traced-quarantined population Conversely, when tracing is incomplete most newly confirmed cases will not occur among the quarantined population Second, based on our hypothesis that more effective tracing would generate a greater number of quarantined people for each newly confirmed case, we used the daily log-transformed number of quarantined people per newly confirmed case at provincial level In both the national and global analysis, we used the log-transformed country-specific ratio of cumulative negative tests per case as a proxy for effective TTIQ implementation on the assumption that a more proactive tracing policy generates more negative test results per newly confirmed case Outcome variables We used as our outcome measure the 1-week lagged newly confirmed cases per million for national level and per thousand people for provincial level analysis of Korea For the global analysis we used the cumulative number of new cases per million population, and the cumulative number of deaths per million population in each country All outcome variables were log-transformed er r Analyses In the national analysis, we examined associations between the 1-week lagged number of confirmed cases per unit population (outcome variable) and each of the three proxy latent variables of TTIQ as independent variables In the global analysis, we examined associations between the cumulative number of deaths per million population (log) and number of negative tests per case (log) and the number of negative tests per case (negative test results ratio); and associations between the cumulative number of deaths per million population (log) and number of negative tests per case (log) We performed a subgroup analysis by designating an early phase (2020) and a late phase (2021), based on when vaccines became available tn ot pe For the Korean data analysis, reflecting data availability, we conducted three analyses First, we analyzed data from the week of October 3rd-9th, 2020 through the week of September 12th-18th, 2021 for the Q-proportion As the independent variable, we regressed the publicly available weekly Q-proportion with the outcome variable, which was expressed as 7-day averaged daily COVID-19 cases by million, lagged by week, and log transformed (Figure 1) Second, we analyzed the data from July 1, 2021 through September 14, 2021 for the quarantine analysis (the nine provinces) For the independent variable, we divided the daily numbers of quarantine population by the newly confirmed COVID-19 cases (“Quarantined population per case ratio”), then we divided the ratio by 14 to account for the mandatory week quarantine period enforced by the Korean government, and finally log transformed the ratio For the outcome variable, we divided daily COVID-19 cases by one thousand, lagged the values by week, and finally log transformed the values We divided nine provinces into two categories: (A) higher and (B) lower vaccination coverage (Figure 2A, 2B, and supplementary table) Third, we analyzed the data from Feb 22 (100th case day), 2020 through Sep 16, 2021 for testing For the independent variable, we divided the number of negative tests by the newly confirmed case, and log transformed the values For the outcome variable, we divided daily COVID-19 cases by million, lagged the values by week, and finally log transformed the values (Figure 3) rin The period for global analysis for negative test ratio was Jan 1, 2020 through Sep 16, 2021 For the independent variable, we divided the number of negative tests by the newly confirmed case (“Negative test results ratio”), and log transformed the ratio For the outcome variable, we divided the cumulative number of COVID-19 cases and deaths by million, lagged the values by week, and finally log transformed the values We divided 111 jurisdictions into a tertile based on the vaccine coverage per million population (Figure 5) ep We used linear regression analysis in Stata 17 software (StataCorp 2021 Stata Statistical Software: Release 17 College Station, TX: StataCorp LLC.): Level of significance with P=0.05 Results Pr In the national analysis the Q-proportions ranging between 29·9 and 66·4 %, were negatively associated with the log-transformed 1-week lagged new case incidence per million population (β= -0·091; p-value < 0·001) during the period Oct 3-9, 2020, to Sep 12-18, 2021 (Figure 1) The log transformed quarantined population per newly confirmed case (range to 33 quarantined people per case (mean) in each province) was also negatively associated This preprint research paper has not been peer reviewed Electronic copy available at: https://ssrn.com/abstract=3954082 iew ed with the log transformed 1-week lagged confirmed new daily cases in the Korean provinces, of which Seoul (population vaccination rate rank of provinces with 50% coverage) showed the largest association (β = -0·626; p-value < 0·001), the province with the lowest vaccinated population (47·7%) showed the 2nd largest association (β= -0·603; p-value < 0·001), whereas the province with the most vaccinated population (58.3%) showed the smallest association (β= -0·288; p-value = 0·023 during the period July 1, 2021 to September 14, 2021 (Figure 2; supplementary table) The magnitude of the inverse associations was attenuated when vaccination coverage rates were increased (β = -1·253; p-value < 0·001) The log-transformed ratio of negative test results per daily confirmed new case (ranging from to 2981 negative test results per case) were also inversely associated with the 1-week lagged incidence of cases per million-unit population (β= -1·22 p-value < 0·001) during the period of Feb 22, 2020 to Sep 16, 2021 (Figure 3) pe er r ev Turning to the global analysis, Figure shows the distribution of cumulative cases or deaths per million population for each country against the ratio of cumulative negative tests per case in 2020 and 2021 The highest negative test ratio was in China (1890) at the end of 2020 and in Hong Kong (5573) at the end of 2021, while the lowest was in Brazil in both periods, respectively The association between the negative test ratio (log) and cumulative cases per population (log) in the global analyses were all significantly negative in all periods and both the early and the late period subgroups The association was stronger for cumulative deaths (Figure 5A) than cumulative cases (Figure 5B) With cumulative deaths (Figure 5A), the association in the early phase was stronger (β= -0·95 (95% CI: -1·15 to -0·75); p < 0.001) than in the later phase (β= -0·60 (95% CI: -0·80 to -0·40); p < 0·001) A similar pattern was found with cumulative cases (Figure 5B): the association in the early phase was stronger (β= -0·77 (95% CI: -0·96 to -0·57); p < 0·001) than in the later phase (β= -0·31 (95% CI: -0·50 to -0·12); p < 0·001) Consistently inverse associations with gradual attenuation were found when the analysis was stratified by periods before and after vaccines became available — in 2021, jurisdictions in the lowest tertile of vaccination coverage showed a stronger inverse association (β= -1·51 (95% CI: -2·07 to -0·94); p < 0·001) than the highest tertile (β= -0·81 (95% CI: -1·11 to -0·51); p < 0·001), with a similar pattern in COVID-19 incidence (Figure 5C) Discussion tn ot Our study has some important limitations, most related to the validity of the data Especially in the global analysis, we are dependent on the coverage, quality, and consistency of the data Early in the pandemic, the ability to track incidence was limited by testing capacity everywhere and, even now, this remains the case in many places Notwithstanding guidance from WHO, there are national differences in how deaths are attributed to COVID-19,(31) as well as gaps in surveillance coverage in many parts of the world(29,32) and even, in some countries, possible data falsification.(33) This analysis does not allow us to isolate the TTIQ impact from the many other variables that influence COVID-19 responses: i.e behavioral characteristics such as adherence to physical distancing and face covering guidelines as well as indoor ventilation use and performance However, given the complex nature of these relationships the analytic challenges of disentangling these factors would be formidable even if data on the omitted variables were available ep rin These results suggest that proactive implementation of TTIQ is associated with both reduced numbers of COVID-19 cases and deaths across multiple countries The greater Q-proportion (an indicator of effective contact-tracing), the lower the 1-week lagged incidence A higher number of quarantined people per new case and a higher negative test ratio were also associated with fewer cases one week later Globally, a higher negative test results ratio was associated with fewer cumulative deaths and cases, in both 2020 and 2021 In a further analysis limited to the period when vaccines became available, in 2021, it appears that TTIQ was more effective in countries unable to reach high vaccination rates (noting that while these tended to be poorer countries with less testing capacity many also had lower COVID burdens) The value of TTIQ was sustained, even as vaccine roll out has proceeded in both analyses Our results support the value of TTIQ even with increasing vaccination rates, a finding that is likely to assume greater importance should new variants with greater vaccine escape become widespread and because of likely political unwillingness to impose further large-scale lockdowns in many countries, especially given evidence that the latter vary in their effectiveness.(34) Pr Conclusion This preprint research paper has not been peer reviewed Electronic copy available at: https://ssrn.com/abstract=3954082 Pr ep rin tn ot pe er r ev iew ed We provide empirical evidence of the effectiveness of TTIQ in reducing cases and deaths using a real-world evaluation, offering support for continued investment in the capacity to implement these measures However, further studies, such as that using the Korean data above, are needed to corroborate our findings, linked to mixed methods studies to understand how best to implement this approach in different contexts This preprint research paper has not been peer reviewed Electronic copy available at: https://ssrn.com/abstract=3954082 iew ed References Polack FP, Thomas SJ, Kitchin N, Absalon J, Gurtman A, Lockhart S, et al Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine N Engl J Med 2020 Dec 31;383(27):2603–15 Baden LR, El Sahly HM, Essink B, Kotloff K, Frey S, Novak R, et al Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine N Engl J Med 2021 Feb 4;384(5):403–16 Lee J-K, Bullen C, Ben Amor Y, Bush SR, Colombo F, Gaviria A, et al Institutional and behaviour-change interventions to support COVID-19 public health measures: a review by the Lancet Commission Task Force on public health measures to suppress the pandemic Int Health 2021 Sep 3;13(5):399–409 Kucharski AJ, Klepac P, Conlan AJK, Kissler SM, Tang ML, Fry H, et al Effectiveness of isolation, testing, contact tracing, and physical distancing on reducing transmission of SARS-CoV-2 in different settings: a mathematical modelling study Lancet Infect Dis 2020 Oct;20(10):1151–60 Mansfield KE, Mathur R, Tazare J, Henderson AD, Mulick AR, Carreira H, et al Indirect acute effects of the COVID-19 pandemic on physical and mental health in the UK: a population-based study Lancet Digit Health 2021 Apr;3(4):e217–30 Douglas M, Katikireddi SV, Taulbut M, McKee M, McCartney G Mitigating the wider health effects of covid19 pandemic response BMJ 2020 Apr 27;369:m1557 Baraniuk C Covid-19: How effective are vaccines against the delta variant? BMJ 2021 Aug 9;374:n1960 Wouters OJ, Shadlen KC, Salcher-Konrad M, Pollard AJ, Larson HJ, Teerawattananon Y, et al Challenges in ensuring global access to COVID-19 vaccines: production, affordability, allocation, and deployment Lancet Lond Engl 2021 Mar 13;397(10278):1023–34 Jecker NS, Atuire CA What’s yours is ours: waiving intellectual property protections for COVID-19 vaccines J Med Ethics 2021 Sep;47(9):595–8 ot pe er r ev 10 Hyder AA, Hyder MA, Nasir K, Ndebele P Inequitable COVID-19 vaccine distribution and its effects Bull World Health Organ 2021 Jun 1;99(6):406-406A tn 11 Lazarus JV, Ratzan SC, Palayew A, Gostin LO, Larson HJ, Rabin K, et al A global survey of potential acceptance of a COVID-19 vaccine Nat Med 2021 Feb;27(2):225–8 rin 12 The HART Files: Inside the Group Trying to Smuggle Anti-Vaccine Myths into Westminster [Internet] 2021 [cited 2021 Sep 24] Available from: https://www.logically.ai/articles/hart-files-anti-vaccine-myths-westminster 13 Nanduri S, Pilishvili T, Derado G, Soe MM, Dollard P, Wu H, et al Effectiveness of Pfizer-BioNTech and Moderna Vaccines in Preventing SARS-CoV-2 Infection Among Nursing Home Residents Before and During Widespread Circulation of the SARS-CoV-2 B.1.617.2 (Delta) Variant - National Healthcare Safety Network, March 1-August 1, 2021 MMWR Morb Mortal Wkly Rep 2021 Aug 27;70(34):1163–6 ep 14 Lopez Bernal J, Andrews N, Gower C, Gallagher E, Simmons R, Thelwall S, et al Effectiveness of Covid-19 Vaccines against the B.1.617.2 (Delta) Variant N Engl J Med 2021 Aug 12;385(7):585–94 Pr 15 Iftekhar EN, Priesemann V, Balling R, Bauer S, Beutels P, Calero Valdez A, et al A look into the future of the COVID-19 pandemic in Europe: an expert consultation Lancet Reg Health Eur 2021 Sep;8:100185 16 Moore S, Hill EM, Tildesley MJ, Dyson L, Keeling MJ Vaccination and non-pharmaceutical interventions for COVID-19: a mathematical modelling study Lancet Infect Dis 2021 Jun;21(6):793–802 This preprint research paper has not been peer reviewed Electronic copy available at: https://ssrn.com/abstract=3954082 iew ed 17 Yang J, Marziano V, Deng X, Guzzetta G, Zhang J, Trentini F, et al Despite vaccination, China needs nonpharmaceutical interventions to prevent widespread outbreaks of COVID-19 in 2021 Nat Hum Behav 2021 Aug;5(8):1009–20 18 Gozzi N, Bajardi P, Perra N The importance of non-pharmaceutical interventions during the COVID-19 vaccine rollout PLoS Comput Biol 2021 Sep;17(9):e1009346 19 Contreras S, Dehning J, Mohr SB, Bauer S, Spitzner FP, Priesemann V Low case numbers enable long-term stable pandemic control without lockdowns Sci Adv 7(41):eabg2243 20 Markel H, Lipman HB, Navarro JA, Sloan A, Michalsen JR, Stern AM, et al Nonpharmaceutical interventions implemented by US cities during the 1918-1919 influenza pandemic JAMA 2007 Aug 8;298(6):644–54 ev 21 Perra N Non-pharmaceutical interventions during the COVID-19 pandemic: A review Phys Rep 2021 May 23;913:1–52 er r 22 Baker MG, Wilson N, Anglemyer A Successful Elimination of Covid-19 Transmission in New Zealand N Engl J Med 2020 Aug 20;383(8):e56 23 Nguyen TV, Tran QD, Phan LT, Vu LN, Truong DTT, Truong HC, et al In the interest of public safety: rapid response to the COVID-19 epidemic in Vietnam BMJ Glob Health 2021 Jan;6(1):e004100 pe 24 Summers J, Cheng H-Y, Lin H-H, Barnard LT, Kvalsvig A, Wilson N, et al Potential lessons from the Taiwan and New Zealand health responses to the COVID-19 pandemic Lancet Reg Health West Pac 2020 Nov;4:100044 25 Leung K, Wu JT The gradual release exit strategy after lockdown against COVID-19 Lancet Reg Health West Pac 2020 Aug;1:100008 ot 26 Lewis D Why many countries failed at COVID contact-tracing - but some got it right Nature 2020 Dec;588(7838):384–7 tn 27 Chung S-C, Marlow S, Tobias N, Alogna A, Alogna I, You S-L, et al Lessons from countries implementing find, test, trace, isolation and support policies in the rapid response of the COVID-19 pandemic: a systematic review BMJ Open 2021 Jun 29;11(7):e047832 28 Torres I, Sippy R, Sacoto F Assessing critical gaps in COVID-19 testing capacity: the case of delayed results in Ecuador BMC Public Health 2021 Apr 1;21(1):637 rin 29 The Korean Disease Control and Prevention Agency [Internet] [cited 2021 Oct 1] Available from: http://kdca.go.kr 30 Coronavirus Pandemic (COVID-19) [Internet] Our World in Data 2020 Available from: https://ourworldindata.org/coronavirus ep 31 Karanikolos M, McKee M How comparable is COVID-19 mortality across countries? EuroHealth 2020;6 Pr 32 Sempé L, Lloyd-Sherlock P, Martínez R, Ebrahim S, McKee M, Acosta E Estimation of all-cause excess mortality by age-specific mortality patterns for countries with incomplete vital statistics: a population-based study of the case of Peru during the first wave of the COVID-19 pandemic Lancet Reg Health – Am [Internet] 2021 Aug 20 [cited 2021 Sep 25];0(0) Available from: https://www.thelancet.com/journals/lanam/article/PIIS2667-193X(21)00031-4/fulltext 33 Kilani A An interpretation of reported COVID-19 cases in post-Soviet states J Public Health Oxf Engl 2021 Jun 7;43(2):e409–10 This preprint research paper has not been peer reviewed Electronic copy available at: https://ssrn.com/abstract=3954082 Pr ep rin tn ot pe er r ev iew ed 34 Oh J, Lee H-Y, Khuong QL, Markuns JF, Bullen C, Barrios OEA, et al Mobility restrictions were associated with reductions in COVID-19 incidence early in the pandemic: evidence from a real-time evaluation in 34 countries Sci Rep 2021 Jul 2;11(1):13717 This preprint research paper has not been peer reviewed Electronic copy available at: https://ssrn.com/abstract=3954082 iew ed ev er r pe ot tn rin Pr ep Figure Association between quarantined population proportion among weekly new cases and the 1-week lagged confirmed weekly new cases (log) from the week of Oct 3-9, 2020 to the week of Sep 12-18, 2021 in Republic of Korea This preprint research paper has not been peer reviewed Electronic copy available at: https://ssrn.com/abstract=3954082 Pr ep rin tn ot pe er r ev iew ed A This preprint research paper has not been peer reviewed Electronic copy available at: https://ssrn.com/abstract=3954082 rin tn ot pe er r ev iew ed B Pr ep Figure Association between quarantined population per new daily cases (log) and the 1-week lagged confirmed new daily cases (log) from Jul 1, 2021, to Sep 14, 2021 in most COVID-19 prevalent provinces of Republic of Korea: Higher vaccination coverage provinces (A) vs lower vaccination coverage provinces (B) This preprint research paper has not been peer reviewed Electronic copy available at: https://ssrn.com/abstract=3954082 iew ed ev er r pe ot tn Pr ep rin Figure Association between traced negative tests results ratio per newly confirmed case (log) and the 1-week lagged confirmed new cases (log) from Feb 22, 2020, to Sep 16, 2021 in Republic of Korea This preprint research paper has not been peer reviewed Electronic copy available at: https://ssrn.com/abstract=3954082 iew ed ev er r pe ot tn rin ep Pr Figure Cumulative deaths and cases and negative test result ratio of the 111 jurisdictions in 2020 and 2021 This preprint research paper has not been peer reviewed Electronic copy available at: https://ssrn.com/abstract=3954082 er r ev iew ed A ep rin tn ot pe B Pr C This preprint research paper has not been peer reviewed Electronic copy available at: https://ssrn.com/abstract=3954082 iew ed ev er r pe ot tn rin ep Pr This preprint research paper has not been peer reviewed Electronic copy available at: https://ssrn.com/abstract=3954082 iew ed Figure Association between log-transformed 1-week lagged cumulative deaths (A), cases (B) and negative test result ratio (log) of the 111 jurisdictions in 2020 and 2021, and stratified associations between log-transformed 1week lagged cumulative cases and deaths and negative test result ratio (log) across tertile of vaccination coverage per million population among 111 jurisdictions in 2021 (C) (as of Sep 14) Supplementary table Associations between quarantined population per COVID-19 case in each vaccination coverage rank among provinces from Jul 1, 2021, to Sep 14, 2021 -0.288 -0.213 0.023 0.054 Upper confidence interval -0.536 -0.429 Gyeongbuk 54.5 -0.438 0.029 -0.830 -0.047 Busan Gyeongnam Seoul Daejeon Incheon Gyeonggi 53.0 52.2 50.0 49.5 48.4 47.7 -0.564 -0.436 -0.626 -0.402 -0.530 -0.603 0.000 0.000 0.000 0.001 0.000 0.000 -0.854 -0.653 -0.777 -0.637 -0.694 -0.827 -0.274 -0.219 -0.475 -0.166 -0.367 -0.378 β p-value ev Cheonbuk Chungnam Vaccinated population (%) 58.3 55.0 er r Vaccination rank Lower confidence interval -0.041 0.003 Pr ep rin tn ot pe Province This preprint research paper has not been peer reviewed Electronic copy available at: https://ssrn.com/abstract=3954082 ...University of Auckland School of Population Health, Auckland, New Zealand 25Boston University School of Medicine, Boston, MA, USA 26London 27These School of Hygiene and Tropical Medicine, London, UK... Jurisdictions with lower vaccination coverage showed the strongest association Interpretation pe A real- world evaluation demonstrates an association between performance of testing, contact tracing,... the association between cumulative COVID- 19 cases and deaths and the implementation of TTIQ interventions, taking account of vaccination coverage, beginning with the experience of one country,