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Accepted for/Published in: JMIRx Med

Date Submitted: Jul 19, 2020
Open Peer Review Period: Jul 19, 2020 - Nov 4, 2020
Date Accepted: Dec 26, 2020
Date Submitted to PubMed: Aug 4, 2023
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

A Framework for a Statistical Characterization of Epidemic Cycles: COVID-19 Case Study

De Carvalho EA, De Carvalho RA

A Framework for a Statistical Characterization of Epidemic Cycles: COVID-19 Case Study

JMIRx Med 2021;2(1):e22617

DOI: 10.2196/22617

PMID: 34077489

PMCID: 8078446

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Identification of Patterns in Epidemic Cycles and Methods for Estimating Their Duration: COVID-19 Case Study

  • Eduardo Atem De Carvalho; 
  • Rogerio Atem De Carvalho

ABSTRACT

This paper presents several epidemic cycles of COVID-19 that have practically ended in countries, states and cities and normalize them through simple and well-known numerical methods. It is evident that there is a practically universal pattern between them, in a triangular shape. It is also possible to find similar cycles with very close scales and thus use cases with cycles already closed to predict the end of the cycles still in progress. Three methods are presented and discussed and the case of the city of Rio de Janeiro, Brazil, is presented in more detail.


 Citation

Please cite as:

De Carvalho EA, De Carvalho RA

A Framework for a Statistical Characterization of Epidemic Cycles: COVID-19 Case Study

JMIRx Med 2021;2(1):e22617

DOI: 10.2196/22617

PMID: 34077489

PMCID: 8078446

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