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1.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.12.18.21268024

ABSTRACT

This article aims to study the COVID-19 data for New York City. We use both the daily number of second does vaccination and the daily number of reported cases for New York City. This article provides a method to combine an epidemic model and such data. We explore the influence of vaccine efficacy on our results.


Subject(s)
COVID-19
2.
4.
medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.03.21.20040154

ABSTRACT

We model the COVID-19 coronavirus epidemic in South Korea, Italy, France, and Germany. We use early reported case data to predict the cumulative number of reported cases to a final size. The key features of our model are the timing of implementation of major public policies restricting social movement, the identification and isolation of unreported cases, and the impact of asymptomatic infectious cases.


Subject(s)
COVID-19
5.
medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.03.11.20034314

ABSTRACT

We model the COVID-19 coronavirus epidemic in China. We use early reported case data to predict the cumulative number of reported cases to a final size. The key features of our model are the timing of implementation of major public policies restricting social movement, the identification and isolation of unreported cases, and the impact of asymptomatic infectious cases.


Subject(s)
COVID-19
6.
arxiv; 2020.
Preprint in English | PREPRINT-ARXIV | ID: ppzbmed-2002.12298v1

ABSTRACT

We model the COVID-19 coronavirus epidemic in China. We use early reported case data to predict the cumulative number of reported cases to a final size. The key features of our model are the timing of implementation of major public policies restricting social movement, the identification and isolation of unreported cases, and the impact of asymptomatic infectious cases.


Subject(s)
COVID-19
7.
preprints.org; 2020.
Preprint in English | PREPRINT-PREPRINTS.ORG | ID: ppzbmed-10.20944.preprints202002.0365.v1

ABSTRACT

We model the COVID-19 coronavirus epidemic in China. We use early reported case data to predict the cumulative number of reported cases to a final size. The key features of our model are the timing of implementation of major public policies restricting social movement, the identification and isolation of unreported cases, and the impact of asymptomatic infectious cases.


Subject(s)
COVID-19
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