How Data is Helping to Fight COVID-19 Pandemic
Early in 2020, the COVID-19 pandemic emerged as a global public health concern requiring urgent attention, concerted efforts and intervention to avoid catastrophe. This necessitated optimal use of fast-emerging data to be analysed to draw out inferences that would shape our response. World Health...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
JCDR Research and Publications Private Limited
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/eb5d1e95fff34cb2ba889ea5f2cbceb0 |
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| Sumario: | Early in 2020, the COVID-19 pandemic emerged as a global public health concern requiring urgent attention, concerted efforts
and intervention to avoid catastrophe. This necessitated optimal use of fast-emerging data to be analysed to draw out inferences
that would shape our response. World Health Organisation (WHO) called this pandemic an infodemic where data played a crucial
role. This paper reviews how data from varied sources and different types helped delay the outbreak, limit the spread, initiate
social and public health measures, decide treatment regimes, optimise healthcare infrastructure and human resources and helped
to initiate a multipronged strategy with emerging evidence for further course correction as the world progressed through the
pandemic. The classical mathematical tools, i.e., Susceptible-Infected-Recovered (SIR) model and its variants, were the primary
analytical techniques utilised to analyse such data. However, newer data analytical techniques utilising artificial intelligence and
machine learning, were also extensively used. These techniques have the capability to handle large quantities of data and develop
prediction models of various emerging situations that offer foreknowledge for policymakers and provide solutions. Data Science
has witnessed a leap in the past few years, and the way it helped shape our response to this pandemic is a testimony to the promise
that it holds for humankind. |
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