论文标题
通过新的人口生态增长模型来分析Covid-19的大流行
Analyzing COVID-19 pandemic with a new growth model for population ecology
论文作者
论文摘要
我们提出了一种新形式的人口生态增长率。通常，增长率取决于该特定时期的人口规模。我们引入了一种替代时间依赖的增长率。该形式满足代表人口增长的基本条件，并且可以成为分析人口动态的增长模型的另一种形式。我们已经采用了广义理查德模型来比较我们的结果。此外，在流行病的情况下，我们已经应用了模型。为了检查模型的功效，我们已经验证了2003 SARS数据。该模型以良好的精度估算了最终流行病的规模。此后，我们打算描述当前的2019年大流行。我们已经对意大利，西班牙和德国的数据进行了分析。随后，我们试图预测美国，英国和印度的Covid-19案件的数量以及转折点。
We have proposed a new form of growth rate for population ecology. Generally, the growth rate is dependent on the size of the population at that particular epoch. We have introduced an alternative time-dependent form of growth rate. This form satisfies essential conditions to represent population growth and can be an alternative form for growth models to analyze population dynamics. We have employed the generalized Richards model as a guideline to compare our results. Further, we have applied our model in the case of epidemics. To check the efficacy of our model, we have verified the 2003 SARS data. This model has estimated the final epidemic size with good accuracy. Thereafter, we intend to describe the present COVID-2019 pandemic. We have performed our analysis with data for Italy, Spain, and Germany. Following, we have tried to predict the number of COVID-19 cases and the turning point for the USA, UK, and India.
