COVID-19 in Okayama Prefecture: Looking back and looking forward

Tsukahara, Hirokazu; Higashionna, Tsukasa; Tsuge, Mitsuru; Miyamura, Junko; Kusano, Nobuchika

doi:10.35772/ghm.2020.01104

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…20 The local government of each prefecture has established policy for the process of admission prioritization as a way of integrating the information from the regional medical situations, including the aforementioned factors, a strategy that may determine the variation in the severity on admission. 21,22 This means that there may be differences in whether a patient can be hospitalized and how long it takes for a patient to be hospitalized, even for clinically similar cases, depending on the prefecture they belong to.…”

Section: Discussionmentioning

confidence: 99%

Impact of regional heterogeneity on the severity of COVID-19

Tsuzuki,

Asai,

Matsunaga

et al. 2024

Preprint

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Background: We aimed to assess the impact of regional heterogeneity on the severity of COVID-19 in Japan. Methods: We included 27,865 cases registered between January 2020 and February 2021 in the COVID-19 Registry of Japan to examine the relationship between the National Early Warning Score (NEWS) of COVID-19 patients on the day of admission and the prefecture where the patients live. A hierarchical Bayesian model was used to examine the random effect of each prefecture in addition to the patients’ backgrounds. In addition, we compared the results of two models; one model included the number of beds secured for COVID-19 patients in each prefecture as one of the fixed effects, and the other model did not. Results: The results indicated that the prefecture had a substantial impact on the severity of COVID-19 on admission. Even when considering the effect of the number of beds separately, the heterogeneity caused by the random effect of each prefecture affected the severity of the case on admission. Conclusions: Our analysis revealed a possible association between regional heterogeneity and increased/decreased risk of severe COVID-19 infection on admission. This heterogeneity was derived not only from the number of beds secured in each prefecture but also from other factors.

show abstract

Section: Discussionmentioning

confidence: 99%

Impact of regional heterogeneity on the severity of COVID-19

Tsuzuki,

Asai,

Matsunaga

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…No epidemic surge in the sentinel surveillance was observed in 2020 owing to the governmental strategy for dealing with the COVID-19 pandemic (declaration of emergency status), including sheltering at home and closing schools. [23][24][25]. Moreover, topics of public interest, such as the announcement of a new drug or vaccine for RSV, will likely affect the search volume on Google Trends, undermining the reliability of the findings.…”

Section: Discussionmentioning

confidence: 99%

Correlation between national surveillance and search engine query data on respiratory syncytial virus infections in Japan

et al. 2022

Self Cite

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Background The respiratory syncytial virus (RSV) disease burden is significant, especially in infants and children with an underlying disease. Prophylaxis with palivizumab is recommended for these high-risk groups. Early recognition of a RSV epidemic is important for timely administration of palivizumab. We herein aimed to assess the correlation between national surveillance and Google Trends data pertaining to RSV infections in Japan. Methods The present, retrospective survey was performed between January 1, 2018 and November 14, 2021 and evaluated the correlation between national surveillance data and Google Trends data. Joinpoint regression was used to identify the points at which changes in trends occurred. Results A strong correlation was observed every study year (2018 [r = 0.87, p < 0.01], 2019 [r = 0.83, p < 0.01], 2020 [r = 0.83, p < 0.01], and 2021 [r = 0.96, p < 0.01]). The change-points in the Google Trends data indicating the start of the RSV epidemic were observed earlier than by sentinel surveillance in 2018 and 2021 and simultaneously with sentinel surveillance in 2019. No epidemic surge was observed in either the Google Trends or the surveillance data from 2020. Conclusions Our data suggested that Google Trends has the potential to enable the early identification of RSV epidemics. In countries without a national surveillance system, Google Trends may serve as an alternative early warning system.

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Impact of regional heterogeneity on the severity of COVID-19

Tsuzuki

Asai

Matsunaga

et al. 2021

Preprint

View full text Add to dashboard Cite

Background: We aimed to assess the impact of regional heterogeneity on the severity of COVID-19 in Japan. Methods: We included 27,865 cases registered between January 2020 and February 2021 in the COVID-19 Registry of Japan to examine the relationship between the National Early Warning Score (NEWS) of COVID-19 patients on the day of admission and the prefecture where the patients live. A hierarchical Bayesian model was used to examine the random effect of each prefecture in addition to the patients' backgrounds. In addition, we compared the results of two models; one model included the number of beds secured for COVID-19 patients in each prefecture as one of the fixed effects, and the other model did not. Results: The results indicated that the prefecture had a substantial impact on the severity of COVID-19 on admission. Even when considering the effect of the number of beds separately, the heterogeneity caused by the random effect of each prefecture affected the severity of the case on admission. Conclusions: Our analysis revealed a possible association between regional heterogeneity and increased/decreased risk of severe COVID-19 infection on admission. This heterogeneity was derived not only from the number of beds secured in each prefecture but also from other factors.

show abstract

COVID-19 in Okayama Prefecture: Looking back and looking forward

Cited by 3 publications

References 6 publications

Impact of regional heterogeneity on the severity of COVID-19

Impact of regional heterogeneity on the severity of COVID-19

Correlation between national surveillance and search engine query data on respiratory syncytial virus infections in Japan

Impact of regional heterogeneity on the severity of COVID-19

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