COVID-19 growth modeling and forecasting in Pakistan provinces with python

栏目: IT技术 · 发布时间: 6年前

内容简介:Logistic Growth is a mathematical function that can be used in many scenarios, including forecasting growth of COVID-19 cases. Logistic Growth is characterized by increasing Growth in the beginning period, but a decreasing growth at a later stage, as you g

Logistic Growth is a mathematical function that can be used in many scenarios, including forecasting growth of COVID-19 cases. Logistic Growth is characterized by increasing Growth in the beginning period, but a decreasing growth at a later stage, as you get closer to a maximum. For example, in the COVID-19 situation, this maximum limit would be the total number of people in the world or country, because when everybody is sick, Growth will diminish.

COVID-19 growth modeling and forecasting in Pakistan provinces with python

Epidemiolocal studies confirm that in the first period of an epidemic follows Exponential Growth and that the total period can be modeled with a Logistic Growth. In other words, at the begging, we observe a large number of cases and high Growth, but when we look at the number of cases after the Logistic epidemic, growth is more accurate to predict the number of cases over time.

We can also identify if the virus in a particular administrative unit (country, province) is still growing exponentially or Growth starts to follow a flat curve. Virus spread can be modeled by logistic function. If an administrative unit is in the second part of the function, this means Growth is going towards the end, if somewhere in the middle — this means fast Growth is still ahead.

1. When the fastest growth day is still ahead = growth increasing (phase 1).

2. When the fastest growth day is in the past = growth stabilized (phase 2).

In the case of Pakistan, we analyze first the data for the entire country and then for provinces separately, a large number of cases is concentrated in specific parts of the country, and the size of the country, and also restrictions in the movement have an impact on the number of cases.

COVID-19 growth modeling and forecasting in Pakistan provinces with python

For Pakistan number of cases is expected to increase, and the country is currently in the growth increase (1) phase. The total number of cases is expected to reread around 9000, and we can expect a peak around begging of May and stabilization in the second half of May 2020.

Now let’s look at major provinces around Pakistan with a substantial number of cases that will enable us to run the forecast.

Punjab province

COVID-19 growth modeling and forecasting in Pakistan provinces with python

In Punjab province, the Growth based on the number of cases is increasing (phase 1) the number of cases is expected to reach 8500, and we can expect that situation will stabilize in the second half of May 2020.

Sindh province

COVID-19 growth modeling and forecasting in Pakistan provinces with python

The situation in Sindh is different than in Punjab number of cases is stabilizing and should reach around 1100 cases. Also, a number of new cases should stabilize and reach a maximum of around the second half of April.

Important to remember that forecast, it is based on today’s actual numbers, with next day data situation can change.

You can find code and data on my Github page https://github.com/PiotrKrosniak/covid19-growth-modeling

References and inspirations:


以上就是本文的全部内容,希望本文的内容对大家的学习或者工作能带来一定的帮助,也希望大家多多支持 码农网

查看所有标签

本站部分资源来源于网络,本站转载出于传递更多信息之目的,版权归原作者或者来源机构所有,如转载稿涉及版权问题,请联系我们。

引爆社群

引爆社群

唐兴通 / 机械工业出版社华章科技 / 2015-3 / 49

科技延伸媒介,移动互联网技术催生了微信等各种新的媒体;媒介更新人文,新媒介让互联网重回社群时代;人文重塑商业规则,社群时代的商业模式与法则究竟是怎样的?我们应该如何去适应和应对?本书提出的“新4C法则”为此给出了解决方案。关于如何运用这个法则,本书给出了详尽的阐述。但是,要利用好这个法则,需要我们对它有深入的理解。 场景(Context):移动互联网时代场景为王,所有基于移动互联网的产品和服......一起来看看 《引爆社群》 这本书的介绍吧!

XML、JSON 在线转换
XML、JSON 在线转换

在线XML、JSON转换工具

正则表达式在线测试
正则表达式在线测试

正则表达式在线测试

HEX CMYK 转换工具
HEX CMYK 转换工具

HEX CMYK 互转工具