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A quadratic trend-based time series method to analyze the early incidence pattern of COVID-19

A quadratic trend-based time series method to analyze the early incidence pattern of COVID-19 The ongoing pandemic of Coronavirus disease has already affected more than 300,000 people. In this study, we propose an appropriate auto-regressive integrated moving-average model with time-varying parameters to analyze the trend pattern of the early incidence of COVID-19 outbreak, and subsequently, estimate the basic reproduction number for different countries. We also incorporate information on total or partial lockdown into the model. The model is concise and flexible in structure. For we use the maximum likelihood method and estimate it for different serial interval distributions. Proper diagnostic measures establish that a time-varying quadratic trend successfully captures the incidence pattern of the disease. We find that the number of affected cases starts increasing more rapidly three to four weeks after the first case is identified. Countrywide lockdown has been effective in reducing the growth rate of the disease in Italy. Estimated of the 2019 novel Coronavirus ranges between 1.4 and 3.2 in different countries, except for the United States where it is higher. A much-needed outcome is that the method gives insight into what epidemiological stage a region is in. This has the potential to help in prompting policies to address the COVID-19 pandemic in different countries. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Biostatistics & Epidemiology Taylor & Francis

A quadratic trend-based time series method to analyze the early incidence pattern of COVID-19

Deb, Soudeep; Majumdar, Manidipa
Biostatistics & Epidemiology , Volume OnlineFirst: 13 – Jun 1, 2022
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A quadratic trend-based time series method to analyze the early incidence pattern of COVID-19

Abstract

The ongoing pandemic of Coronavirus disease has already affected more than 300,000 people. In this study, we propose an appropriate auto-regressive integrated moving-average model with time-varying parameters to analyze the trend pattern of the early incidence of COVID-19 outbreak, and subsequently, estimate the basic reproduction number for different countries. We also incorporate information on total or partial lockdown into the model. The model is concise and flexible in structure. For...
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Publisher
Taylor & Francis
Copyright
© 2022 International Biometric Society – Chinese Region
ISSN
2470-9379
eISSN
2470-9360
DOI
10.1080/24709360.2022.2076529
Publisher site
See Article on Publisher Site

Abstract

The ongoing pandemic of Coronavirus disease has already affected more than 300,000 people. In this study, we propose an appropriate auto-regressive integrated moving-average model with time-varying parameters to analyze the trend pattern of the early incidence of COVID-19 outbreak, and subsequently, estimate the basic reproduction number for different countries. We also incorporate information on total or partial lockdown into the model. The model is concise and flexible in structure. For we use the maximum likelihood method and estimate it for different serial interval distributions. Proper diagnostic measures establish that a time-varying quadratic trend successfully captures the incidence pattern of the disease. We find that the number of affected cases starts increasing more rapidly three to four weeks after the first case is identified. Countrywide lockdown has been effective in reducing the growth rate of the disease in Italy. Estimated of the 2019 novel Coronavirus ranges between 1.4 and 3.2 in different countries, except for the United States where it is higher. A much-needed outcome is that the method gives insight into what epidemiological stage a region is in. This has the potential to help in prompting policies to address the COVID-19 pandemic in different countries.

Journal

Biostatistics & Epidemiology – Taylor & Francis

Published: Jun 1, 2022

Keywords: Coronavirus; epidemiology; reproduction number; ARIMA; COVID-19 pandemic

References

  • Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
  • Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China
  • 2019-novel coronavirus severe adult respiratory distress syndrome in two cases in Italy: an uncommon radiological presentation
  • First case of 2019 novel coronavirus in the United States
  • Nowcasting and forecasting the potential domestic and international spread of the 2019-ncov outbreak originating in Wuhan, China: a modelling study
  • A conceptual model for the outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, China with individual reaction and governmental action
  • The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak
  • Preliminary estimation of the basic reproduction number of novel coronavirus (2019-ncov) in Wuhan, China, from 2019 to 2020: a data-driven analysis in the early phase of the outbreak
  • A mathematical model for simulating the phase-based transmissibility of a novel coronavirus
  • Unraveling r 0: considerations for public health applications