<?xml version="1.0" encoding="utf-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.0 20120330//EN" "JATS-journalpublishing1.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article">
<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">JDS994B</article-id>
<article-id pub-id-type="doi">10.6339/21-JDS994B</article-id>
<article-categories><subj-group subj-group-type="heading">
<subject>Discussion</subject></subj-group></article-categories>
<title-group>
<article-title>Discussion of “Evaluate the Risk of Resumption of Business for the States of New York, New Jersey and Connecticut via a Pre-Symptomatic and Asymptomatic Transmission Model of COVID-19”</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Quick</surname><given-names>Corbin</given-names></name><xref ref-type="aff" rid="j_jds994b_aff_001">1</xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Lin</surname><given-names>Xihong</given-names></name><xref ref-type="aff" rid="j_jds994b_aff_001">1</xref>
</contrib>
<aff id="j_jds994b_aff_001"><label>1</label>Department of Biostatistics, <institution>Harvard T. H. Chan School of Public Health</institution>, Cambridge, MA, <country>USA</country></aff>
</contrib-group>
<pub-date pub-type="ppub"><year>2021</year></pub-date><pub-date pub-type="epub"><day>7</day><month>5</month><year>2021</year></pub-date><volume>19</volume><issue>2</issue><fpage>201</fpage><lpage>202</lpage>
<permissions><copyright-statement>2021 The Author(s). Published by the School of Statistics and the Center for Applied Statistics, Renmin University of China.</copyright-statement><copyright-year>2021</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>
</article-meta>
</front>
<back>
<ref-list id="j_jds994b_reflist_001">
<title>References</title>
<ref id="j_jds994b_ref_001">
<mixed-citation publication-type="journal"> <collab>CDC COVID-19 Response Team</collab> (<year>2020</year>). <article-title>Characteristics of health care personnel with COVID-19 — United States, February 12–April 9</article-title>. <source>Morbidity and Mortality Weekly Report</source>, <volume>69</volume>(<issue>15</issue>): <fpage>477</fpage>–<lpage>481</lpage>. <comment>2020</comment>.</mixed-citation>
</ref>
<ref id="j_jds994b_ref_002">
<mixed-citation publication-type="journal"> <string-name><surname>Cho</surname> <given-names>SW</given-names></string-name> (<year>2020</year>). <article-title>Quantifying the impact of nonpharmaceutical interventions during the COVID-19 outbreak: The case of Sweden</article-title>. <source>The Econometrics Journal</source>, <volume>23</volume>: <fpage>323</fpage>–<lpage>344</lpage>.</mixed-citation>
</ref>
<ref id="j_jds994b_ref_003">
<mixed-citation publication-type="journal"> <string-name><surname>Davies</surname> <given-names>NG</given-names></string-name>, <string-name><surname>Kucharski</surname> <given-names>AJ</given-names></string-name>, <string-name><surname>Eggo</surname> <given-names>RM</given-names></string-name>, <string-name><surname>Gimma</surname> <given-names>A</given-names></string-name>, <string-name><surname>Edmunds</surname> <given-names>WJ</given-names></string-name> (<year>2020</year>). <article-title>Effects of non-pharmaceutical interventions on COVID-19 cases, deaths, and demand for hospital services in the UK: A modelling study</article-title>. <source>The Lancet Public Health</source>, <volume>5</volume>(<issue>7</issue>): <fpage>E375</fpage>–<lpage>E385</lpage>.</mixed-citation>
</ref>
<ref id="j_jds994b_ref_004">
<mixed-citation publication-type="other"> <string-name><surname>Goodman-Bacon</surname> <given-names>A</given-names></string-name>, <string-name><surname>Marcus</surname> <given-names>J</given-names></string-name> (2020). Using difference-in-differences to identify causal effects of COVID-19 policies. SSRN preprint: <uri>http://dx.doi.org/10.2139/ssrn.3603970</uri>.</mixed-citation>
</ref>
<ref id="j_jds994b_ref_005">
<mixed-citation publication-type="journal"> <string-name><surname>Goolsbee</surname> <given-names>A</given-names></string-name>, <string-name><surname>Syverson</surname> <given-names>C</given-names></string-name> (<year>2020</year>). <article-title>Fear, lockdown, and diversion: Comparing drivers of pandemic economic decline 2020</article-title>. <source>Journal of Public Economics</source>, <volume>193</volume>: <fpage>104311</fpage>.</mixed-citation>
</ref>
<ref id="j_jds994b_ref_006">
<mixed-citation publication-type="journal"> <string-name><surname>Hsiang</surname> <given-names>S</given-names></string-name>, <string-name><surname>Allen</surname> <given-names>D</given-names></string-name>, <string-name><surname>Annan-Phan</surname> <given-names>S</given-names></string-name>, <string-name><surname>Bell</surname> <given-names>K</given-names></string-name>, <string-name><surname>Bolliger</surname> <given-names>I</given-names></string-name>, <string-name><surname>Chong</surname> <given-names>T</given-names></string-name>, <etal>et al.</etal> (<year>2020</year>). <article-title>The effect of large-scale anti-contagion policies on the COVID-19 pandemic</article-title>. <source>Nature</source>, <volume>584</volume>: <fpage>262</fpage>–<lpage>267</lpage>.</mixed-citation>
</ref>
<ref id="j_jds994b_ref_007">
<mixed-citation publication-type="journal"> <string-name><surname>Lauer</surname> <given-names>SA</given-names></string-name>, <string-name><surname>Grantz</surname> <given-names>KH</given-names></string-name>, <string-name><surname>Bi</surname> <given-names>Q</given-names></string-name>, <string-name><surname>Jones</surname> <given-names>FK</given-names></string-name>, <string-name><surname>Zheng</surname> <given-names>Q</given-names></string-name>, <string-name><surname>Meredith</surname> <given-names>HR</given-names></string-name>, <etal>et al.</etal> (<year>2020</year>). <article-title>The incubation period of coronavirus disease 2019 (COVID-19) from publicly reported confirmed cases: estimation and application</article-title>. <source>Annals of Internal Medicine</source>, <volume>172</volume>: <fpage>577</fpage>–<lpage>582</lpage>.</mixed-citation>
</ref>
<ref id="j_jds994b_ref_008">
<mixed-citation publication-type="other"> <string-name><surname>Li</surname> <given-names>Y</given-names></string-name>, <string-name><surname>Undurraga</surname> <given-names>EA</given-names></string-name>, <string-name><surname>Zubizarreta</surname> <given-names>JR</given-names></string-name> (2020). Effectiveness of localized lockdowns in the SARS-CoV-2 pandemic. MedRXiv preprint: <uri>https://doi.org/10.1101/2020.08.25.20182071</uri>.</mixed-citation>
</ref>
<ref id="j_jds994b_ref_009">
<mixed-citation publication-type="journal"> <string-name><surname>Park</surname> <given-names>CL</given-names></string-name>, <string-name><surname>Russell</surname> <given-names>BS</given-names></string-name>, <string-name><surname>Fendrich</surname> <given-names>M</given-names></string-name>, <string-name><surname>Finkelstein-Fox</surname> <given-names>L</given-names></string-name>, <string-name><surname>Hutchison</surname> <given-names>M</given-names></string-name>, <string-name><surname>Becker</surname> <given-names>J</given-names></string-name> (<year>2020</year>). <article-title>Americans’ COVID-19 stress, coping, and adherence to CDC guidelines</article-title>. <source>Journal of General Internal Medicine</source>, <volume>35</volume>(<issue>8</issue>): <fpage>2296</fpage>–<lpage>2303</lpage>.</mixed-citation>
</ref>
<ref id="j_jds994b_ref_010">
<mixed-citation publication-type="journal"> <string-name><surname>Tian</surname> <given-names>T</given-names></string-name>, <string-name><surname>Luo</surname> <given-names>W</given-names></string-name>, <string-name><surname>Tan</surname> <given-names>J</given-names></string-name>, <string-name><surname>Jiang</surname> <given-names>Y</given-names></string-name>, <string-name><surname>Chen</surname> <given-names>M</given-names></string-name>, <string-name><surname>Pan</surname> <given-names>W</given-names></string-name>, <etal>et al.</etal> (<year>2021a</year>). <article-title>The timing and effectiveness of implementing mild interventions of COVID-19 in large industrial regions via a synthetic control method</article-title>. <source>Statistics and Its Interface</source>, <volume>14</volume>(<issue>1</issue>): <fpage>3</fpage>–<lpage>12</lpage>.</mixed-citation>
</ref>
<ref id="j_jds994b_ref_011">
<mixed-citation publication-type="other"> <string-name><surname>Tian</surname> <given-names>T</given-names></string-name>, <string-name><surname>Tan</surname> <given-names>J</given-names></string-name>, <string-name><surname>Jiang</surname> <given-names>Y</given-names></string-name>, <string-name><surname>Wang</surname> <given-names>X</given-names></string-name>, <string-name><surname>Zhang</surname> <given-names>H</given-names></string-name> (2021b). Evaluate the timing of resumption of business for the states of New York, New Jersey, and California via a pre-symptomatic and asymptomatic transmission model of COVID-19. <italic>Journal of Data Science</italic>, 19. In this issue.</mixed-citation>
</ref>
</ref-list>
</back>
</article>
