论文标题
Covid-19疾病流行的常见趋势
Common trends in the epidemic of Covid-19 disease
论文作者
论文摘要
SARS-COV-2的发现是COVID-19的责任病毒，引发了许多受影响国家的全球健康问题。开发可以解释流行病并提供共同趋势参数的模型可用于预测流行病早期阶段的其他国家。它对于未来针对病毒呼吸道疾病的计划也很有用。开发了一种模型来解释流行病的快速增长阶段，另一个模型来解释整个数据集。两种模型都与数据合理地一致。第一个模型表明，在快速阶段，新受感染案例的数量取决于幂律关系总数等于0.82。第二个模型在流行病开始初期的范围1到3天内给出了重复的时间，另一个参数alpha = 0.1-0.5），使流行病的进展偏离了指数式生长。我们的模型可用于数据解释和指导有关该疾病的预测，例如新案例数中最大值的开始。
The discovery of SARS-CoV-2, the responsible virus for the Covid-19 epidemic, has sparked a global health concern with many countries affected. Developing models that can interpret the epidemic and give common trend parameters are useful for prediction purposes by other countries that are at an earlier phase of the epidemic; it is also useful for future planning against viral respiratory diseases. One model is developed to interpret the fast-growth phase of the epidemic and another model for an interpretation of the entire data set. Both models agree reasonably with the data. It is shown by the first model that during the fast phase, the number of new infected cases depends on the total number of cases by a power-law relation with a scaling exponent equal to 0.82. The second model gives a duplication time in the range 1 to 3 days early in the start of the epidemic, and another parameter alpha = 0.1-0.5) that deviates the progress of the epidemic from an exponential growth. Our models may be used for data interpretation and for guiding predictions regarding this disease, e.g. the onset of the maximum in the number of new cases.
