Journal article Open Access

Impact of COVID-19 outbreaks and interventions on influenza in China and the United States

Luzhao Feng


DataCite XML Export

<?xml version='1.0' encoding='utf-8'?>
<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd">
  <identifier identifierType="DOI">10.5281/zenodo.4573183</identifier>
  <creators>
    <creator>
      <creatorName>Luzhao Feng</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-5206-5995</nameIdentifier>
      <affiliation>School of Population Medicine &amp; Public Health, Chinese Academy of Medical Sciences/Peking Union Medical College, Beijing, China.</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Impact of COVID-19 outbreaks and interventions on influenza in China and the United States</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2021</publicationYear>
  <dates>
    <date dateType="Issued">2021-03-02</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="JournalArticle"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/4573183</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.4568653</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;In order to predict the influenza positive rate of China and the US&amp;nbsp;in 2018-2019 and 2019-2020 without COVID-19, 2011-2019 influenza positive rate of China and the US&amp;nbsp;were used to establish a prediction model. Through the model evaluation under different parameter combinations, the optimal model can be obtained. The file contains the model evaluation results under all parameter combinations, which is divided into eight&amp;nbsp;parts: 2018-2019 positive rate in southern China, 2018-2019 positive rate in northern China, 2018-2019 positive rate in the US, 2019-2020 positive rate in southern China, 2019-2020 positive rate in northern China, 2019-2020 positive rate in the US, 2019-2020 number of ILI in southern China, 2019-2020 number of ILI in northern China.&lt;/p&gt;</description>
  </descriptions>
</resource>
185
249
views
downloads
All versions This version
Views 185155
Downloads 249243
Data volume 8.8 MB8.6 MB
Unique views 142130
Unique downloads 8682

Share

Cite as