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评估其他假设以解释新冠疫情死亡率指数的下降趋势。

Evaluating alternative hypotheses to explain the downward trend in the indices of the COVID-19 pandemic death rate.

作者信息

Shinde Sonali, Ranade Pratima, Watve Milind

机构信息

Department of Biodiversity, Abasaheb Garware College, Pune, Pune, Maharashtra, India.

Independent Researcher, Pune, Maharashtra, India.

出版信息

PeerJ. 2021 Apr 20;9:e11150. doi: 10.7717/peerj.11150. eCollection 2021.

Abstract

BACKGROUND

In the ongoing Covid-19 pandemic, in the global data on the case fatality ratio (CFR) and other indices reflecting death rate, there is a consistent downward trend from mid-April to mid-November. The downward trend can be an illusion caused by biases and limitations of data or it could faithfully reflect a declining death rate. A variety of explanations for this trend are possible, but a systematic analysis of the testable predictions of the alternative hypotheses has not yet been attempted.

METHODOLOGY

We state six testable alternative hypotheses, analyze their testable predictions using public domain data and evaluate their relative contributions to the downward trend.

RESULTS

We show that a decline in the death rate is real; changing age structure of the infected population and evolution of the virus towards reduced virulence are the most supported hypotheses and together contribute to major part of the trend. The testable predictions from other explanations including altered testing efficiency, time lag, improved treatment protocols and herd immunity are not consistently supported, or do not appear to make a major contribution to this trend although they may influence some other patterns of the epidemic.

CONCLUSION

The fatality of the infection showed a robust declining time trend between mid April to mid November. Changing age class of the infected and decreasing virulence of the pathogen were found to be the strongest contributors to the trend.

摘要

背景

在持续的新冠疫情中,在全球病死率(CFR)及其他反映死亡率的指标数据中,从4月中旬到11月中旬呈现出持续下降趋势。这种下降趋势可能是由数据偏差和局限性导致的错觉,也可能真实反映了死亡率的下降。对于这一趋势有多种解释,但尚未有人尝试对替代假设的可检验预测进行系统分析。

方法

我们阐述了六个可检验的替代假设,利用公开数据对其可检验预测进行分析,并评估它们对下降趋势的相对贡献。

结果

我们表明死亡率的下降是真实的;感染人群年龄结构的变化以及病毒向毒力降低方向的演变是最受支持的假设,它们共同构成了该趋势的主要部分。包括检测效率改变、时间滞后、治疗方案改进和群体免疫等其他解释的可检验预测未得到一致支持,或者似乎对这一趋势没有重大贡献,尽管它们可能会影响疫情的其他一些模式。

结论

4月中旬至11月中旬期间,感染的致死率呈现出强劲的下降时间趋势。发现感染人群年龄类别变化和病原体毒力降低是导致该趋势的最主要因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a013/8063871/15d0e58ac61c/peerj-09-11150-g001.jpg

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