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COVID-19: Original Article
Public holidays increased the transmission of COVID-19 in Japan, 2020-2021: a mathematical modelling study
Jiaying Qiao, Hiroshi Nishiura
Epidemiol Health. 2024;46:e2024025.   Published online January 22, 2024
DOI: https://doi.org/10.4178/epih.e2024025
  • 5,358 View
  • 199 Download
  • 1 Crossref
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
OBJECTIVES
Although the role of specific holidays in modifying transmission dynamics of infectious diseases has received some research attention, the epidemiological impact of public holidays on the transmission of coronavirus disease 2019 (COVID-19) remains unclear.
METHODS
To assess the extent of increased transmission frequency during public holidays, we collected COVID-19 incidence and mobility data in Hokkaido, Tokyo, Aichi, and Osaka from February 15, 2020 to September 30, 2021. Models linking the estimated effective reproduction number (Rt) with raw or adjusted mobility, public holidays, and the state of emergency declaration were developed. The best-fit model included public holidays as an essential input variable, and was used to calculate counterfactuals of Rt in the absence of holidays.
RESULTS
During public holidays, on average, Rt increased by 5.71%, 3.19%, 4.84%, and 24.82% in Hokkaido, Tokyo, Aichi, and Osaka, respectively, resulting in a total increase of 580 (95% confidence interval [CI], 213 to 954), 2,209 (95% CI, 1,230 to 3,201), 1,086 (95% CI, 478 to 1,686), and 5,211 (95% CI, 4,554 to 5,867) cases that were attributable to the impact of public holidays.
CONCLUSIONS
Public holidays intensified the transmission of COVID-19, highlighting the importance of considering public holidays in designing appropriate public health and social measures in the future.
Summary
Key Message
• The number of COVID-19 cases increased during public holidays in Japan.
• The increase may have occurred because of elevated mobility rate and altered contact behaviours.
• The effect of holidays varied by prefecture in Japan.

Citations

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  • Impacto de medidas não farmacológicas contra a COVID-19
    Soraya Abegail de Lima, Eduarda Pereira, Auriane Silva Lima Grígolo, Elis Carolina Pacheco, Camila Marinelli Martins, Erildo Vicente Muller, Eliseu Alves Waldman, Pollyanna Kássia de Oliveira Borges
    Cuadernos de Educación y Desarrollo.2025; 17(1): e7154.     CrossRef
COVID-19: Original Article
Epidemiological characteristics of and containment measures for COVID-19 in Busan, Korea
Hyunjin Son, Hyojung Lee, Miyoung Lee, Youngduck Eun, Kyounghee Park, Seungjin Kim, Wonseo Park, Sora Kwon, Byoungseon Ahn, Dongkeun Kim, Changhoon Kim
Epidemiol Health. 2020;42:e2020035.   Published online June 1, 2020
DOI: https://doi.org/10.4178/epih.e2020035
  • 20,056 View
  • 540 Download
  • 24 Web of Science
  • 14 Crossref
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
Objectives
To describe and evaluate epidemiological investigation results and containment measures implemented in Busan, where 108 cases were confirmed with coronavirus disease 2019 (COVID-19) between February 21, 2020 and March 24, 2020.
Methods
Any individual who tested positive for COVID-19 was classified as a confirmed case. Measures were taken to identify the source of infection and trace and quarantine contacts. Serial intervals were estimated and the effective reproduction number was computed.
Results
Of the total 18,303 COVID-19 tests performed between January 16, 2020 and March 24, 2020 in Busan, 108 yielded positive results (positive test rate, 0.6%). All confirmed cases were placed in isolation at hospitals. Of the 108 confirmed cases, 59 (54.6%) were female. The most common age group was 20-29 years with 37 cases (34.3%). Regarding symptoms at the time of diagnosis, cough (n=38, 35.2%) and fever (n=34, 31.5%) were most common; 12 cases (11.1%) were asymptomatic. The source of infection was identified in 99 cases (91.7%). A total of 3,223 contacts were identified and quarantined. Household contacts accounted for 196, and the household secondary attack rate was 8.2% (95% confidence interval [CI], 4.7 to 12.9). The mean serial interval was estimated to be 5.54 days (95% CI, 4.08 to 7.01). After February 26, (R<sub>t</sub>) remained below 1 in Busan.
Conclusions
The early containment strategy implemented in Busan shows that control is possible if outbreaks are of limited scope. In preparation for future outbreaks, public health and healthcare systems should be re-examined and put in a ready state.
Summary
Korean summary
2월 21일부터 3월 24일까지 부산시에서 보고된 108명의 코로나바이러스감염증-19 (코로나19) 확진 환자의 역학 조사 결과와 관리 조치를 기술하고 평가하였다. 초기에는 A 교회 클러스터와 다른 지역에서 유입된 사례로 인해 급격한 환자 증가가 있었고 이후 접촉자를 중심으로 2차 유행을 보였다. 2월 26일 이후 부산 지역의 Rt가 1보다 낮은 값을 보여 전파가 통제되고 있음을 알 수 있었다. 부산에서 초기 containment 전략을 시행한 결과 제한된 발생 규모인 경우 통제가 가능하다는 점을 확인하였다. 이후 발생할 유행에 대비해 적극적으로 공중보건 및 보건의료 체계를 정비하고 준비해야 할 것으로 생각된다

Citations

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  • Asymptomatic SARS-CoV-2 Infection by Age: A Global Systematic Review and Meta-analysis
    Bing Wang, Prabha Andraweera, Salenna Elliott, Hassen Mohammed, Zohra Lassi, Ashley Twigger, Chloe Borgas, Shehani Gunasekera, Shamez Ladhani, Helen Siobhan Marshall
    Pediatric Infectious Disease Journal.2023; 42(3): 232.     CrossRef
  • Evaluation of the EsteR Toolkit for COVID-19 Decision Support: Sensitivity Analysis and Usability Study
    Rieke Alpers, Lisa Kühne, Hong-Phuc Truong, Hajo Zeeb, Max Westphal, Sonja Jäckle
    JMIR Formative Research.2023; 7: e44549.     CrossRef
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    Tobhin Kim, Hyojung Lee, Sungchan Kim, Changhoon Kim, Hyunjin Son, Sunmi Lee
    Frontiers in Public Health.2023;[Epub]     CrossRef
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    Pratha Sah, Meagan C. Fitzpatrick, Charlotte F. Zimmer, Elaheh Abdollahi, Lyndon Juden-Kelly, Seyed M. Moghadas, Burton H. Singer, Alison P. Galvani
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    Kelly Jean Thomas Craig, Rubina Rizvi, Van C Willis, William J Kassler, Gretchen Purcell Jackson
    JMIR Public Health and Surveillance.2021; 7(10): e32468.     CrossRef
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    Stella Talic, Shivangi Shah, Holly Wild, Danijela Gasevic, Ashika Maharaj, Zanfina Ademi, Xue Li, Wei Xu, Ines Mesa-Eguiagaray, Jasmin Rostron, Evropi Theodoratou, Xiaomeng Zhang, Ashmika Motee, Danny Liew, Dragan Ilic
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COVID-19: Health Statistics
Estimation of the reproduction number and early prediction of the COVID-19 outbreak in India using a statistical computing approach
Karthick Kanagarathinam, Kavaskar Sekar
Epidemiol Health. 2020;42:e2020028.   Published online May 9, 2020
DOI: https://doi.org/10.4178/epih.e2020028
  • 14,793 View
  • 294 Download
  • 12 Web of Science
  • 11 Crossref
AbstractAbstract PDF
Abstract
Coronavirus disease 2019 (COVID-19), which causes severe respiratory illness, has become a pandemic. The World Health Organization has declared it a public health crisis of international concern. We developed a susceptible, exposed, infected, recovered (SEIR) model for COVID-19 to show the importance of estimating the reproduction number (R<sub>0</sub>). This work is focused on predicting the COVID-19 outbreak in its early stage in India based on an estimation of R<sub>0</sub>. The developed model will help policymakers to take active measures prior to the further spread of COVID-19. Data on daily newly infected cases in India from March 2, 2020 to April 2, 2020 were to estimate R<sub>0</sub> using the earlyR package. The maximum-likelihood approach was used to analyze the distribution of R<sub>0</sub> values, and the bootstrap strategy was applied for resampling to identify the most likely R<sub>0</sub> value. We estimated the median value of R<sub>0</sub> to be 1.471 (95% confidence interval [CI], 1.351 to 1.592) and predicted that the new case count may reach 39,382 (95% CI, 34,300 to 47,351) in 30 days.
Summary

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COVID-19: Original Article
Estimating the reproductive number and the outbreak size of COVID-19 in Korea
Sunhwa Choi, Moran Ki
Epidemiol Health. 2020;42:e2020011.   Published online March 12, 2020
DOI: https://doi.org/10.4178/epih.e2020011
  • 45,867 View
  • 3,304 Download
  • 154 Web of Science
  • 140 Crossref
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
OBJECTIVES
Since the first novel coronavirus disease 2019 (COVID-19) patient in Korea was diagnosed on January 20, 2020, 30 patients were diagnosed until February 17, 2020. However, 5,298 additional patients were confirmed until March 4, 2020. Therefore, our objective was to estimate the reproduction number (<i>R</i>) and evaluate the effectiveness of preventive measures.
METHODS
A COVID-19 transmission model (SEIHR) was established to suit the Korean outbreak. The number of daily confirmed cases in Daegu and North Gyeongsang Province (NGP), the main area of outbreak, was used. The first patient’ symptom onset date in the Daegu/NGP outbreak was assumed as January 22, 2020. The <i>R</i> according to the start date of the effect of preventive measures was estimated.
RESULTS
The estimated <i>R</i> in Hubei Province, China, was 4.0281, whereas the estimated initial <i>R</i> in Korea was 0.555, but later in Daegu/NGP, the value was between 3.472 and 3.543. When the transmission period decreases from 4-day to 2-day, the outbreak ends early, but the peak of the epidemic increases, and the total number of patients does not change greatly. It was found that, if transmission rate decreases, the outbreak ends early, and the size of the peak and the total number of patients also decreases.
CONCLUSIONS
To end the COVID-19 epidemic, efforts to reduce the spread of the virus, such as social distancing and wearing masks, are absolutely crucial with the participation of the public, along with the policy of reducing the transmission period by finding and isolating patients as quickly as possible through the efforts of the quarantine authorities.
Summary
Korean summary
수학적 모델링을 통하여 코로나-19 감염재생산수( R )와 대구, 경북의 유행 규모와 유행 종료 시점 등을 예측해보았다. 그 결과 중국 후베이성의 R=4, 한국 초기 30일간의 유행은 R=0.5, 대구/경북의 3월 4일까지의 유행은 R=3.5 수준으로 나타났다. 하지만 방역당국의 적극적인 코로나-19검사로 환자들의 감염전파기간이 짧아지고, 국민들의 마스크 쓰기, 사회적 거리두기 등의 감염 예방조치 적극 참여로 전파율이 낮아져 5월 1일경에 하루 환자 1명 수준으로 예측되었다.

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