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Abhishek Pandey

Researcher at Yale University

Publications -  69
Citations -  2919

Abhishek Pandey is an academic researcher from Yale University. The author has contributed to research in topics: Population & Medicine. The author has an hindex of 19, co-authored 47 publications receiving 1946 citations. Previous affiliations of Abhishek Pandey include Clemson University.

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Projecting hospital utilization during the COVID-19 outbreaks in the United States.

TL;DR: It is highlighted that the growing coronavirus disease 2019 (COVID-19) outbreak in the United States could gravely challenge the critical care capacity, thereby exacerbating case fatality rates, and policies that encourage self-isolation may delay the epidemic peak, giving a window of time that could facilitate emergency mobilization to expand hospital capacity.
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Impact of international travel and border control measures on the global spread of the novel 2019 coronavirus outbreak.

TL;DR: The results show that these measures likely slowed the rate of exportation from mainland China to other countries, but are insufficient to contain the global spread of COVID-19, and suggest that rapid contact tracing is essential both within the epicenter and at importation sites to limit human-to-human transmission outside of mainland China.
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The implications of silent transmission for the control of COVID-19 outbreaks.

TL;DR: It is found that over one-third of silent infections must be isolated to suppress a future outbreak below 1% of the population, and that symptom-based isolation must be supplemented by rapid contact tracing and testing that identifies asymptomatic and presymPTomatic cases, in order to safely lift current restrictions and minimize the risk of resurgence.
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Strategies for containing Ebola in West Africa.

TL;DR: It is found that a combined approach of case isolation, contact-tracing with quarantine, and sanitary funeral practices must be implemented with utmost urgency in order to reverse the growth of the outbreak of Ebola.
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Optimal COVID-19 quarantine and testing strategies.

TL;DR: In this article, the authors developed a mathematical model that quantifies the probability of post-quarantine transmission incorporating testing into travel quarantine, quarantine of traced contacts with an unknown time of infection, and quarantine of cases with a known time of exposure.