The goal of the study is to use mathematical concepts like Ordinary Differential Equations to model Epidemiology (i.e. disease control).
The project's main goal is to assist the nation's healthcare business in surviving and assisting the citizens of the country in fighting the pandemic
DATASET :
The dataset used are as follows:
COVID-19 Data Hub ,Guidotti, E., Ardia, D., (2020), “COVID-19 Data Hub”, Journal of Open Source Software 5(51):2376, doi: 10.21105/joss.02376.
Our World In Data Hasell, J., Mathieu, E., Beltekian, D. et al. A cross-country database of COVID-19 testing. Sci Data 7, 345 (2020). https://doi.org/10.1038/s41597-020-00688-8
COVID-19 Open Data by Google Cloud Platform O. Wahltinez and others (2020), COVID-19 Open-Data: curating a fine-grained, global-scale data repository for SARS-CoV-2, Work in progress, https://goo.gle/covid-19-open-data
The SIR model is a mathematical model of disease. An outbreak occurs when the number of people infected with a disease grows in a population. Using various parameters such as rate of recovery, time elapsed, total population, effective contact rate, and so on, to conduct a pandemic analysis and provide acceptable results and future projections.
We created a comparison graph for the First Phase of the COVID-19 pandemic, which runs from March 19 to March 30, 2020. The SIRF model was then drawn for the Second Phase of the pandemic, which runs from May 12 to May 24, 2021.
Key factors for analysis :
A. Computing Growth Factor
B. SIR Modelling
C. SIR-F Modelling
D. SR Trend Analysis
Outcome :
We were able to stimulate and predict the end of the second wave approximately, The results are attached in the report and presentation slides
About
The project is based on modelling the second wave of COVID-19 in India
