This study analyzed the morbidity and mortality rates of the coronavirus disease (COVID-19) pandemic in different prefectures of Japan. Under the constraint that daily maximum confirmed deaths and daily maximum cases should exceed 4 and 10, respectively, 14 prefectures were included, and cofactors affecting the morbidity and mortality rates were evaluated. In particular, the number of confirmed deaths was assessed, excluding cases of nosocomial infections and nursing home patients. The correlations between the morbidity and mortality rates and population density were statistically significant (p-value < 0.05). In addition, the percentage of elderly population was also found to be non-negligible. Among weather parameters, the maximum temperature and absolute humidity averaged over the duration were found to be in modest correlation with the morbidity and mortality rates. Lower morbidity and mortality rates were observed for higher temperature and absolute humidity. Multivariate linear regression considering these factors showed that the adjusted determination coefficient for the confirmed cases was 0.693 in terms of population density, elderly percentage, and maximum absolute humidity (p-value <0.01). These findings could be useful for intervention planning during future pandemics, including a potential second COVID-19 outbreak.

中文翻译：

---

日本的COVID-19发病率和死亡率与当地人口密度，温度和绝对湿度之间的相关性。

这项研究分析了日本不同州的冠状病毒病（COVID-19）大流行的发病率和死亡率。在每天最大确诊死亡人数和每天最大病例数分别超过4和10的约束下，包括14个州，并评估了影响发病率和死亡率的辅助因子。特别是，评估了确定的死亡人数，不包括医院感染病例和疗养院患者。发病率和死亡率与人口密度之间的相关性具有统计学意义（p值<0.05）。此外，还发现老年人口百分比不可忽略。在天气参数中，发现持续时间内平均的最高温度和绝对湿度与发病率和死亡率有适度的相关性。在较高温度和绝对湿度下观察到较低的发病率和死亡率。考虑这些因素的多元线性回归表明，就人口密度，老年人口百分比和最大绝对湿度而言，确诊病例的调整后确定系数为0.693（p值<0.01）。这些发现可能对未来大流行中的干预计划很有用，包括可能的第二次COVID-19爆发。