ABSTRACT
Data analysis and visualization are essential for exploring and communicating findings in medical research, especially in epidemiological surveillance. Data on COVID-19 diagnosed cases and mortality from crowdsourced website COVID-19 India Tracker, Census 2011, and Google Mobility reports has been used to develop a real-time analytics and monitoring system for the COVID-19 outbreak in India. We have developed a dashboard application for data visualization and analysis of several indicators to follow the SARS-CoV-2 epidemic using data science techniques. A district-level tool for basic epidemiological surveillance, in an interactive and user-friendly manner, which includes time trends, epidemic curves, and key epidemiological parameters such as growth rate, doubling time, and effective reproduction number, has been estimated. This demonstrates the application of data science methods and epidemiological techniques in public health decision-making while addressing the gap of timely and reliable decision-aiding tools. © Authors retain all copyrights.
ABSTRACT
This chapter documents how internal migrants, largely poor urban informal workers, were not only disproportionately affected by the COVID-19 pandemic but also by the containment measures put in place by the governments. We have tried to highlight the adverse effects of control strategies on this group by collating available evidence, predominantly from civil society organizations (CSOs) involved in the relief work. We argue that need for involvement of CSOs on a large scale reflects the gaps in systems meant to protect migrant workers. We argue that CSOs cannot be the replacement of the state and, hence, this experience should be used to design a systematic and comprehensive approach towards ensuring health as a human right for these vulnerable population. © 2022 selection and editorial matter, S. Irudaya Rajan;individual chapters, the contributors.