Abstract
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.
Keywords: COVID-19; severity; regional heterogeneity; hierarchical
Bayesian model
Introduction
Coronavirus disease 2019 (COVID-19), which is caused by the SARS-CoV-2
virus, has become a global health threat, imposing a substantial disease
burden on our society.1 Although it has fluctuated,
the epidemic has continued.2
COVID-19 is more infectious than other respiratory tract
infections,3 such as influenza, and is sometimes fatal
to the elderly and those with underlying medical conditions. Considering
these characteristics, the capacity of healthcare facilities for
COVID-19 patients is an important factor in the management of newly
infected COVID-19 patients.
When we consider countermeasures against COVID-19, the proportion of
patients with severe disease is extremely
important.4–6 Mild and/or asymptomatic cases can be
easily managed as they need no specific treatment. Conversely, severe
cases often require intensive, multidisciplinary care. Furthermore, the
duration of the disease in severe cases is generally longer than that of
other viral pneumonias7 and therefore places a greater
burden on healthcare capacity. It is important, therefore, to precisely
recognize the factors associated with the severity of COVID-19. For
example, new variants may contribute to the severity of COVID-19
cases.8 However, such variants are not the only
determinants of severity; age, sex, past medical history, and many other
factors have been attributed to the severity of
COVID-19.5,9,10 In addition, it is conceivable that
there are other factors influencing the severity of COVID-19 aside from
such biological aspects.
In Japan, the number and proportion of severe COVID-19 cases vary by
prefecture. This phenomenon seems difficult to explain; nevertheless,
there are differences in the management of COVID-19 cases among
prefectures, and these differences may contribute to the capacity of
healthcare facilities in each prefecture. Understanding the extent of
such regional differences will help us tailor the countermeasures
against COVID-19 more appropriately in each prefecture. The main
objective of our study was to examine this regional heterogeneity
quantitatively.