Generalized trapezoidal ogive curves for fatality rate modeling

Johan René van Dorp , Ekundayo Shittu , Thomas A. Mazzuchi
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Abstract

The construction of a continuous family of distributions on a compact set is demonstrated by concatenating, in a continuous manner, three probability density functions with bounded support using a modified mixture technique. The construction technique is similar to that of generalized trapezoidal (GT) distributions, but contrary to GT distributions, the resulting density function is smooth within its bounded domain. The construction of Generalized Trapezoidal Ogive (GTO) distributions was motivated by the COVID-19 epidemic, where smoothness of an infection rate curve may be a desirable property combined with the ability to separately model three stages and their durations as the epidemic progresses, being: (1) an increasing infection rate stage, (2) an infection rate stage of some stability and (3) a decreasing infection rate stage. The resulting model allows for asymmetry of the infection rate curve opposite to, for example, the Gaussian Error Infection (GEI) rate curve utilized early on for COVID-19 epidemic projections by the Institute for Health Metrics and Evaluation (IHME). While other asymmetric distributions too allow for the modeling of asymmetry, the ability to separately model the above three stages of an epidemic’s progression is a distinct feature of the model proposed. The latter avoids unrealistic projections of an epidemic’s right-tail in the absence of right tail data, which is an artifact of any fatality rate model where a left-tail fit determines its right-tail behavior.

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用于死亡率建模的广义梯形ogive曲线
利用改进的混合技术,通过连续连接三个有界支持的概率密度函数,证明了紧集上连续分布族的构造。构造技术类似于广义梯形分布,但与广义梯形分布相反,得到的密度函数在其有界区域内是光滑的。构建广义梯形Ogive (GTO)分布的动机是受COVID-19流行的启发,其中感染率曲线的平滑性可能是理想的特性,并且能够根据流行病的进展分别对三个阶段及其持续时间进行建模,即:(1)感染率上升阶段,(2)感染率有一定稳定性的阶段和(3)感染率下降阶段。由此产生的模型允许感染率曲线的不对称性,例如,与卫生计量与评估研究所(IHME)早期用于COVID-19流行病预测的高斯误差感染(GEI)率曲线相反。虽然其他不对称分布也允许对不对称进行建模,但能够分别对流行病发展的上述三个阶段进行建模是所提出模型的一个显著特征。后者避免了在没有右尾数据的情况下对流行病右尾的不切实际的预测,右尾数据是任何死亡率模型的伪产物,其中左尾拟合决定了其右尾行为。
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来源期刊
Chaos, Solitons and Fractals: X
Chaos, Solitons and Fractals: X Mathematics-Mathematics (all)
CiteScore
5.00
自引率
0.00%
发文量
15
审稿时长
20 weeks
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