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arXiv · 2110.02311

COVID-19 India Dataset: Parsing COVID-19 Data in Daily Health Bulletins from States in India

Mayank Agarwal·Tathagata Chakraborti·Sachin Grover·Arunima Chaudhary
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Abstract

While India has been one of the hotspots of COVID-19, data about the pandemic from the country has proved to be largely inaccessible at scale. Much of the data exists in unstructured form on the web, and limited aspects of such data are available through public APIs maintained manually through volunteer effort. This has proved to be difficult both in terms of ease of access to detailed data and with regards to the maintenance of manual data-keeping over time. This paper reports on our effort at automating the extraction of such data from public health bulletins with the help of a combination of classical PDF parsers and state-of-the-art machine learning techniques. In this paper, we will describe the automated data-extraction technique, the nature of the generated data, and exciting avenues of ongoing work.

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Mayank Agarwal, Tathagata Chakraborti, Sachin Grover, Arunima Chaudhary. 2021-09-27. COVID-19 India Dataset: Parsing COVID-19 Data in Daily Health Bulletins from States in India. https://arxiv.org/abs/2110.02311

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