This is an outdated version published on 2022-09-02 05:37:22 UTC. Read the most recent version.
Preprint / Version 3

Pathogenicity of the omicron variant strain comparison with delta variant strain and seasonal influenza in Japan: Updated until June 2022.

##article.authors##

  • Junko Kurita Department of Nursing, Faculty of Sport and Health Science, Daito Bunka University
  • Tamie Sugawara Infectious Disease Surveillance Center, National Institute of Infectious Diseases
  • Yasushi Ohkusa Infectious Disease Surveillance Center, National Institute of Infectious Diseases

DOI:

https://doi.org/10.51094/jxiv.59

Keywords:

excess mortality, COVID-19, all cause death, stochastic frontier estimation, NIID model, Tokyo, Japan

Abstract

Background: No remarkable mortality attributable to COVID-19 confirmed by PCR test has been observed in Japan.

Object: We sought to quantify excess mortality using the National Institute of Infectious Diseases (NIID) model.

Method: We applied the NIID model to deaths of all causes from 1987 up through the June2022 for the whole of Japan and up through March, 2022 for Tokyo.

Results: Results in Japan show huge number of excess mortality, up to 10 thousands in the two months, in August and September, 2021, when delta variant strain prevailed. Moreover, we found the largest number of excess mortality in a month since COVID-19 emerging in February and March 2022 in the whole of Japan, when one month later since the number of newly confirmed patients with omicron variant strain reached the peak.

Discussion and Conclusion: The result in February and March 2022 may indicate the pathogenicity of the omicron variant strain was comparable delta variant strain and stronger than seasonal influenza.

Downloads *Displays the aggregated results up to the previous day.

Download data is not yet available.

References

Lin HC, Chiu HF, Ho SC, Yang CY. Association of influenza vaccination and reduced risk of stroke hospitalization among the elderly: a population-based case-control study. Int J Environ Res Public Health 2014; 11: 3639-49.

Asghar Z, Coupland C, Siriwardena N. Influenza vaccination and risk of stroke: Self-controlled case-series study. Vaccine. 2015; 33: 5458-63.

Riedmann EM. Influenza vaccination reduces risk of heart attack and stroke. Hum Vaccin Immunother 2013; 9: 2500.

Kwok CS, Aslam S, Kontopantelis E, Myint PK, Zaman MJ, Buchan I, Loke YK, Mamas MA. Influenza, influenza-like symptoms and their association with cardiovascular risks: a systematic review and meta-analysis of observational studies. Int J Clin Pract. 2015;69:928-37.

Muhammad S, Haasbach E, Kotchourko M, Strigli A, Krenz A, Ridder DA, Vogel AB, Marti HH, Al-Abed Y, Planz O, Schwaninger M. Influenza virus infection aggravates stroke outcome. Stroke. 201142 783-91.

Assad F, Cockburn WC, Sundaresan TK. Use of excess mortality from respiratory diseases in the study of influenza. Bull WHO 1973; 49: 219-33.

US Center for Disease Control and Prevention. Excess Deaths Associated with COVID-19. https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm [accessed on July 15, 2022]

Japan Times. Japan's daily PCR test capacity tops 20,000. https://www.japantimes.co.jp/news/2020/05/16/national/japans-daily-pcr-test-capacity-20000/#.XuAwImeP6AA [accessed on January 15, 2022]

World Health Organization. Coronavirus disease (COVID-2019) situation reports. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports/ [accessed on January 12,2022]

Sugawara T, Ohkusa Y. Comparison of Models for Excess Mortality of Influenza Applied to Japan. Journal of Biosciences and Medicines, 2019, 7, 13-23. doi:10.4236/jbm.2019.76002

Kurita J, Sugawara T, Ohkusa Y. Mobility data can explain the entire COVID-19 outbreak course in Japan. medRxiv 2020.04.26.20081315; doi: https://doi.org/10.1101/2020.04.26.20081315

Ministry of Health, Labour and Welfare. Preliminary statistics on demographicshttps://www.mhlw.go.jp/toukei/list/81-1a.html (in Japanese) [accessed on January 16, 2022]

Aiger AD, Lovell K, Schmitidt P. Formulation and estimation of stochastic frontier production function models. Journal of Econometrics 1977; 21-37.

Jondrow J, Lovell K, Materov S, Schmidt P. On the estimation of technical inefficiency in the stochastic frontier production function model. Journal of Econometrics 1982; 233-9.

Li T, Rosenman R. Cost inefficiency in Washington Hospitals: A stochastic frontier approach using panel data, Health Care Management Science 2001; 4: 73-81.

Newhouse JP. Frontier Estimation: How useful a tool for health economics? Journal of Health Economics 1994; 13: 317-22.

Shelton Brown H. Managed care and technical efficiency. Health Economics. 2003; 12: 149-58.

Jacobs R. Alternative methods to examine hospital efficiency: Data envelopment analysis and stochastic frontier analysis. Health Care Management Science. 2001; 4: 103-15

Rosko MD. Cost efficiency of US hospitals: A stochastic frontier approach. Health Economics. 2001; 539-51.

COVID-19 Excess Mortality Collaborators. Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020-21. Lancet. 2022 ;399:1513-36.

Sugawara T, Ohkusa Y. Comparison of Models for Excess Mortality of Influenza Applied to Japan. Journal of Biosciences and Medicines, 2019, 7, 13-23. doi:10.4236/jbm.2019.76002

Downloads

Posted


Submitted: 2022-04-27 04:32:31 UTC

Published: 2022-05-02 09:17:47 UTC — Updated on 2022-09-02 05:37:22 UTC

Versions

Reason(s) for revision

The study period has been extended.
Section
General Medicine, Social Medicine, & Nursing Sciences

License

Copyright (c) 2022 Junko Kurita
Tamie Sugawara
Yasushi Ohkusa

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.