2023 Volume 6 Issue 4 Pages 397-403
Introduction: As the characteristics of coronavirus disease 2019 (COVID-19) vary across regions and countries, the relationship between regional characteristics, such as the distribution of physicians and hospital beds, and COVID-19 mortality was assessed in the 47 prefectures of Japan.
Methods: This ecological study was based on the number of patients with COVID-19 by prefecture during the seventh wave of COVID-19 in Japan (June-October 2022). COVID-19 mortality was indexed as the number of COVID-19 deaths divided by the number of new COVID-19 cases. Data on regional factors, such as population size, number of physicians, and hospital beds by prefecture, were obtained from government statistics. Correlations between regional characteristics and COVID-19 mortality index were analyzed by dividing the 47 prefectures into two groups at the median level of population size (more populated group [MPG] ≥ 1.6 million and less populated group [LPG] < 1.6 million).
Results: The COVID-19 mortality index (mean 12.7, minimum-maximum: 4.7-25.7) was correlated negatively with the number of physicians per hospital bed (r = −0.386, p = 0.007) and positively with the number of long-term care facilities per 10,000 population (r = 0.397, p = 0.006) and aging rate (the proportion of population aged ≥ 65 years) (r = 0.471, p = 0.001). The two groups varied with respect to the number of physicians (28.7 physicians in the LPG vs. 26.1 physicians in the MPG, p = 0.038) and hospital beds (156 beds in the LPG vs. 119 beds in the MPG, p < 0.001) per 10,000 population. In the multiple regression analysis, the COVID-19 mortality index was correlated negatively with the number of physicians per hospital bed (β = −0.543, p = 0.024) and positively with the aging rate (β = 0.434, p = 0.032) in the LPG, with nonsignificant correlations in the MPG.
Conclusions: The data may suggest a need of improvement in the distribution of physicians and hospital beds in the healthcare system in regions with smaller and older populations to reduce the rate of COVID-19.
