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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">JDS</journal-id>
<journal-title-group><journal-title>Journal of Data Science</journal-title></journal-title-group>
<issn pub-type="epub">1683-8602</issn><issn pub-type="ppub">1680-743X</issn><issn-l>1680-743X</issn-l>
<publisher>
<publisher-name>School of Statistics, Renmin University of China</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">JDS1089</article-id>
<article-id pub-id-type="doi">10.6339/23-JDS1089</article-id>
<article-categories><subj-group subj-group-type="heading">
<subject>Statistical Data Science</subject></subj-group></article-categories>
<title-group>
<article-title>Covid-19 Vaccine Efficacy: Accuracy Assessment, Comparison, and Caveats</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Fu</surname><given-names>Wenjiang</given-names></name><email xlink:href="mailto:fuw@math.uh.edu">fuw@math.uh.edu</email><xref ref-type="aff" rid="j_jds1089_aff_001">1</xref><xref ref-type="aff" rid="j_jds1089_aff_002">2</xref><xref ref-type="corresp" rid="cor1">∗</xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Li</surname><given-names>Jieni</given-names></name><xref ref-type="aff" rid="j_jds1089_aff_003">3</xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Scheet</surname><given-names>Paul A.</given-names></name><xref ref-type="aff" rid="j_jds1089_aff_004">4</xref>
</contrib>
<aff id="j_jds1089_aff_001"><label>1</label>Department of Mathematics, <institution>University of Houston</institution>, Houston, Texas 77204, <country>USA</country></aff>
<aff id="j_jds1089_aff_002"><label>2</label>Department of Biostatistics, <institution>The University of Texas MD Anderson Cancer Center</institution>, Houston, Texas 77230, <country>USA</country></aff>
<aff id="j_jds1089_aff_003"><label>3</label>Department of Pharmaceutical Health Outcomes and Policy, <institution>University of Houston</institution>, Houston, Texas 77204, <country>USA</country></aff>
<aff id="j_jds1089_aff_004"><label>4</label>Department of Epidemiology, <institution>The University of Texas MD Anderson Cancer Center</institution>, Houston, Texas 77230, <country>USA</country></aff>
</contrib-group>
<author-notes>
<corresp id="cor1"><label>∗</label>Corresponding author. Email: <ext-link ext-link-type="uri" xlink:href="mailto:fuw@math.uh.edu">fuw@math.uh.edu</ext-link>.</corresp>
</author-notes>
<pub-date pub-type="ppub"><year>2024</year></pub-date><pub-date pub-type="epub"><day>7</day><month>3</month><year>2023</year></pub-date><volume>22</volume><issue>1</issue><fpage>45</fpage><lpage>55</lpage><history><date date-type="received"><day>5</day><month>11</month><year>2022</year></date><date date-type="accepted"><day>5</day><month>2</month><year>2023</year></date></history>
<permissions><copyright-statement>2024 The Author(s). Published by the School of Statistics and the Center for Applied Statistics, Renmin University of China.</copyright-statement><copyright-year>2024</copyright-year>
<license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/">
<license-p>Open access article under the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">CC BY</ext-link> license.</license-p></license></permissions>
<abstract>
<p>Vaccine efficacy is a key index to evaluate vaccines in initial clinical trials during the development of vaccines. In particular, it plays a crucial role in authorizing Covid-19 vaccines. It has been reported that Covid-19 vaccine efficacy varies with a number of factors, including demographics of population, time after vaccine administration, and virus strains. By examining clinical trial data of three Covid-19 vaccine studies, we find that current approach to evaluating vaccines with an overall efficacy does not provide desired accuracy. It requires no time frame during which a candidate vaccine is evaluated, and is subject to misuse, resulting in potential misleading information and interpretation. In particular, we illustrate with clinical trial data that the variability of vaccine efficacy is underestimated. We demonstrate that a new method may help to address these caveats. It leads to accurate estimation of the variation of efficacy, provides useful information to define a reasonable time frame to evaluate vaccines, and avoids misuse of vaccine efficacy and misleading information.</p>
</abstract>
<kwd-group>
<label>Keywords</label>
<kwd>confidence interval</kwd>
<kwd>efficacy curve</kwd>
<kwd>loess smoothing</kwd>
<kwd>time window</kwd>
<kwd>weekly efficacy</kwd>
</kwd-group>
</article-meta>
</front>
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