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The state-level and nationwide analysis of measures such as vaccination drives, testing facilities, and hospital resources has been presented in a concise manner. Mathematical modelling of the epidemic with predictions on fatality rate and under-reporting statistics has been proposed.

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covid-data-analysis

With the onset of the first wave of COVID-19 in India, there have been various precautionary measures taken by the government of India. As the data is made available to the public through news channels and online platforms, the stirred chaos is higher, but now to make informed decisions. The devastating effects of COVID-19 can not be mapped by a plot as they are subjective and have a very high dimensionality in terms of features. However, with the data collected across different states in India and with the help of modern-day computational power, we can understand the feedback of citizens of the country and the response of the government across the pandemic using different measures and inferences from the given data.

From March 2020 to April 2022, India witnessed the fatal effects of three long COVID-19 waves, one of them being the most fatal. As the number of cases rose and reached an alarming number, the government was forced to take preventive measures like practising lockdown, declaration of containment zones, funding COVID-19 vaccine research and at the same time trying to maintain the falling GDP of the country. Subsequently, the responsibility of keeping each other safe fell on the shoulders of the Indian citizens as they spread awareness, comply with the rules and vaccinate themselves and their known ones.

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The state-level and nationwide analysis of measures such as vaccination drives, testing facilities, and hospital resources has been presented in a concise manner. Mathematical modelling of the epidemic with predictions on fatality rate and under-reporting statistics has been proposed.

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