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Azad, Sarita
- The Spatio-Temporal Trajectory of Covid-19 in India: Insight into Past Pandemics and Future Recommendations
Abstract Views :189 |
PDF Views:82
Authors
Neeraj Poonia
1,
Sarita Azad
1
Affiliations
1 School of Basic Sciences, Indian Institute of Technology, Mandi 175 075, IN
1 School of Basic Sciences, Indian Institute of Technology, Mandi 175 075, IN
Source
Current Science, Vol 121, No 11 (2021), Pagination: 1425-1432Abstract
Pandemics have a high socio-economic impact on countries. Singapore and Taiwan, which had pandemic strategies in place, fared much better than almost all other countries in the world during the recent COVID-19 pandemic. In a massive country like India, the coronavirus (COVID-19) has infected millions of people. While studies have estimated the rate of transmission and vulnerability zones, there is still a pressing need to understand the spatio-temporal progression of various pandemics across the population. Here, we review the spread of pandemics in India and identify states with a high probability of being initial hotspots. It was found that pandemics tend to follow a similar transmission route in India. For the COVID-19 pandemic, a spatial link has been established between seasons and disease progression. For instance, districts are marked where a sudden increase in cases (as high as 800%) was observed during monsoon (i.e. rainy season). Following the spatio-temporal trajectory of COVID-19 in India, we found that in post-monsoon, northern regions with hilly terrain witnessed the highest increase in the number of cases. Identifying areas on the trajectory of pandemics will help us better prepare for an outbreak more effectively in the future.Keywords
Hotspots, Pandemics, Transmission Route, Seasons, Spatio-Temporal Trajectory.Full Text
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- An Optimal Vaccination Strategy for Pandemic Management and its Impact on Economic Recovery
Abstract Views :100 |
PDF Views:63
Authors
Affiliations
1 School of Computing and Electrical Engineering, Indian Institute of Technology, Mandi 175 005, IN
2 School of Engineering and Technology, University of Washington, Tacoma 98402, US
3 School of Mathematical and Statistical Sciences, Indian Institute of Technology, Mandi 175 005, IN
1 School of Computing and Electrical Engineering, Indian Institute of Technology, Mandi 175 005, IN
2 School of Engineering and Technology, University of Washington, Tacoma 98402, US
3 School of Mathematical and Statistical Sciences, Indian Institute of Technology, Mandi 175 005, IN
Source
Current Science, Vol 124, No 3 (2023), Pagination: 319-326Abstract
The economic impact of the COVID-19 pandemic has been devastating for countries across the world. We propose a novel method for estimating reproduction number (R0) using community mobility to obtain optimal vaccination coverage (OVC). Different scenarios for achieving the desired immunization rates are evaluated using nonlinear regression models. The impact of recovery rates on mobility is also assessed to determine how the economy would have fared in various scenarios. Lockdowns due to COVID-19, which restricted mobility, were the main cause of the decline in GDP. For the city of Mumbai in India, with an increase in recovery rate from 1% to 5%, it was observed that mobility and thus economic activity might have been restored to some extent. The findings presented here may aid the governing bodies in developing more effective emergency response plans.Keywords
Economic Recovery, Mobility, Nonlinear Regression, Pandemic Management, Reproduction Number, Vaccination Strategy.Full Text
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