tetano
Editor, Senior Moderator
JMA J
. 2021 Jul 15;4(3):198-206.
doi: 10.31662/jmaj.2021-0043. Epub 2021 Jul 9.
Epidemiology of Coronavirus Disease 2019 in Japan: Descriptive Findings and Lessons Learned through Surveillance during the First Three Waves
Yuzo Arima[SUP] 1 [/SUP], Kazuhiko Kanou[SUP] 1 [/SUP], Takeshi Arashiro[SUP] 1 [/SUP], Yura K Ko[SUP] 1 [/SUP], Kanako Otani[SUP] 1 [/SUP], Yuuki Tsuchihashi[SUP] 1 [/SUP], Takuri Takahashi[SUP] 1 [/SUP], Reiko Miyahara[SUP] 1 [/SUP], Tomimasa Sunagawa[SUP] 1 [/SUP], Motoi Suzuki[SUP] 1 [/SUP]
Affiliations
Abstract
Introduction: Coronavirus disease 2019 (COVID-19) has caused unprecedented global morbidity and mortality. Japan has faced three epidemic "waves" of COVID-19 from early 2020 through early 2021. Here we narratively review the three waves in Japan, describe the key epidemiologic features of COVID-19, and discuss lessons learned.
Methods: We assessed publicly available surveillance data, routine surveillance reports, and other relevant sources-multiple indicators were monitored to improve interpretation of surveillance data. Weekly trends for each wave were described based on the number of case notifications; number of tests performed; proportion of those tests that were positive for the novel coronavirus; the prevalent number of COVID-19 hospitalizations (total hospitalizations and those categorized as severe); and number of COVID-19 deaths. For each indicator and wave, we recorded the first calendar week to show an increase over two consecutive previous weeks, along with the peak week.
Results: The spring wave was characterized by detection of cases imported from China, followed by notifications of sporadic cases without travel history, clusters, and mild/asymptomatic cases. The summer wave saw a large increase in notifications and a younger age distribution, but in the context of increased testing with lower test positivity. The winter wave brought considerable morbidity and mortality, surpassing the cumulative case counts and fatalities from the earlier waves, with high peak values. Overall, relative to the first wave, the burden of severe outcomes was lower in the second and higher in the third wave, but varied by prefecture. In all three waves, severe outcomes peaked after notification counts and test positivity peaked; severe outcomes were also consistently skewed toward the elderly.
Conclusions: Important lessons were learned from each wave and across waves-some aspects remained constant, while others changed over time. In order to rapidly detect an increase in incidence, continuous, timely, and sensitive surveillance-using multiple information sources with careful interpretations-will be key in COVID-19 control.
Keywords: SARS-CoV-2; bias; descriptive epidemiology; surveillance.
. 2021 Jul 15;4(3):198-206.
doi: 10.31662/jmaj.2021-0043. Epub 2021 Jul 9.
Epidemiology of Coronavirus Disease 2019 in Japan: Descriptive Findings and Lessons Learned through Surveillance during the First Three Waves
Yuzo Arima[SUP] 1 [/SUP], Kazuhiko Kanou[SUP] 1 [/SUP], Takeshi Arashiro[SUP] 1 [/SUP], Yura K Ko[SUP] 1 [/SUP], Kanako Otani[SUP] 1 [/SUP], Yuuki Tsuchihashi[SUP] 1 [/SUP], Takuri Takahashi[SUP] 1 [/SUP], Reiko Miyahara[SUP] 1 [/SUP], Tomimasa Sunagawa[SUP] 1 [/SUP], Motoi Suzuki[SUP] 1 [/SUP]
Affiliations
- PMID: 34414313
- PMCID: PMC8355718
- DOI: 10.31662/jmaj.2021-0043
Abstract
Introduction: Coronavirus disease 2019 (COVID-19) has caused unprecedented global morbidity and mortality. Japan has faced three epidemic "waves" of COVID-19 from early 2020 through early 2021. Here we narratively review the three waves in Japan, describe the key epidemiologic features of COVID-19, and discuss lessons learned.
Methods: We assessed publicly available surveillance data, routine surveillance reports, and other relevant sources-multiple indicators were monitored to improve interpretation of surveillance data. Weekly trends for each wave were described based on the number of case notifications; number of tests performed; proportion of those tests that were positive for the novel coronavirus; the prevalent number of COVID-19 hospitalizations (total hospitalizations and those categorized as severe); and number of COVID-19 deaths. For each indicator and wave, we recorded the first calendar week to show an increase over two consecutive previous weeks, along with the peak week.
Results: The spring wave was characterized by detection of cases imported from China, followed by notifications of sporadic cases without travel history, clusters, and mild/asymptomatic cases. The summer wave saw a large increase in notifications and a younger age distribution, but in the context of increased testing with lower test positivity. The winter wave brought considerable morbidity and mortality, surpassing the cumulative case counts and fatalities from the earlier waves, with high peak values. Overall, relative to the first wave, the burden of severe outcomes was lower in the second and higher in the third wave, but varied by prefecture. In all three waves, severe outcomes peaked after notification counts and test positivity peaked; severe outcomes were also consistently skewed toward the elderly.
Conclusions: Important lessons were learned from each wave and across waves-some aspects remained constant, while others changed over time. In order to rapidly detect an increase in incidence, continuous, timely, and sensitive surveillance-using multiple information sources with careful interpretations-will be key in COVID-19 control.
Keywords: SARS-CoV-2; bias; descriptive epidemiology; surveillance.