Zhou Chuanbo, Fang Jiaohong, Mao Mingzhi
School of Mathematics and Physics, China University of Geosciences, Wuhan 430074, China.
Entropy (Basel). 2023 Jul 6;25(7):1028. doi: 10.3390/e25071028.
Mortality is one of the most important epidemiological measures and a key indicator of the effectiveness of potential treatments or interventions. In this paper, a permutation test method of variance analysis is proposed to test the null hypothesis that the real-time fatality rates of multiple groups were equal during the epidemic period. In light of large-scale simulation studies, the proposed test method can accurately identify the differences between different groups and display satisfactory performance. We apply the proposed method to the real dataset of the COVID-19 epidemic in mainland China (excluding Hubei), Hubei Province (excluding Wuhan), and Wuhan from 31 January 2020 to 30 March 2020. By comparing the differences in the disease severity for differential cities, we show that the severity of the early disease of COVID-19 may be related to the effectiveness of interventions and the improvement in medical resources.
死亡率是最重要的流行病学指标之一,也是衡量潜在治疗方法或干预措施有效性的关键指标。本文提出了一种方差分析的排列检验方法,以检验疫情期间多组实时死亡率相等的原假设。根据大规模模拟研究,所提出的检验方法能够准确识别不同组之间的差异,并表现出令人满意的性能。我们将所提出的方法应用于2020年1月31日至2020年3月30日中国大陆(不包括湖北)、湖北省(不包括武汉)和武汉的新冠肺炎疫情真实数据集。通过比较不同城市疾病严重程度的差异,我们表明新冠肺炎早期疾病的严重程度可能与干预措施的有效性和医疗资源的改善有关。
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