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.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117 Harv+Data+Sci+Rev
2020 ; 2020
(Suppl 1
): ä Nephropedia Template TP
gab.com Text
Twit Text FOAVip
Twit Text #
English Wikipedia
Predictions, role of interventions and effects of a historic national lockdown in
India s response to the COVID-19 pandemic: data science call to arms
#MMPMID32607504
Ray D
; Salvatore M
; Bhattacharyya R
; Wang L
; Du J
; Mohammed S
; Purkayastha S
; Halder A
; Rix A
; Barker D
; Kleinsasser M
; Zhou Y
; Bose D
; Song P
; Banerjee M
; Baladandayuthapani V
; Ghosh P
; Mukherjee B
Harv Data Sci Rev
2020[]; 2020
(Suppl 1
): ä PMID32607504
show ga
With only 536 cases and 11 fatalities, India took the historic decision of a
21-day national lockdown on March 25. The lockdown was first extended to May 3
soon after the analysis of this paper was completed, and then to May 18 while
this paper was being revised. In this paper, we use a Bayesian extension of the
Susceptible-Infected-Removed (eSIR) model designed for intervention forecasting
to study the short- and long-term impact of an initial 21-day lockdown on the
total number of COVID-19 infections in India compared to other less severe
non-pharmaceutical interventions. We compare effects of hypothetical durations of
lockdown on reducing the number of active and new infections. We find that the
lockdown, if implemented correctly, can reduce the total number of cases in the
short term, and buy India invaluable time to prepare its healthcare and
disease-monitoring system. Our analysis shows we need to have some measures of
suppression in place after the lockdown for increased benefit (as measured by
reduction in the number of cases). A longer lockdown between 42-56 days is
preferable to substantially "flatten the curve" when compared to 21-28 days of
lockdown. Our models focus solely on projecting the number of COVID-19 infections
and, thus, inform policymakers about one aspect of this multi-faceted
decision-making problem. We conclude with a discussion on the pivotal role of
increased testing, reliable and transparent data, proper uncertainty
quantification, accurate interpretation of forecasting models, reproducible data
science methods and tools that can enable data-driven policymaking during a
pandemic. Our software products are available at covind19.org.