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<bibitem type="J">   <ARLID>0578058</ARLID> <utime>20260108152432.7</utime><mtime>20231114235959.9</mtime>   <SCOPUS>85175848114</SCOPUS>  <WOS>001108929300050</WOS>  <DOI>10.1038/s41598-023-45788-8</DOI>           <title language="eng" primary="1">Rotation-based schedules in elementary schools to prevent COVID-19 spread: a simulation study</title>  <specification> <page_count>9 s.</page_count> <media_type>E</media_type> </specification>   <serial><ARLID>cav_un_epca*0386594</ARLID><ISSN>2045-2322</ISSN><title>Scientific Reports</title><part_num/><part_title/><volume_id>13</volume_id><volume/><publisher><place/><name>Nature Publishing Group</name><year/></publisher></serial>    <keyword>agent-based model</keyword>   <keyword>covid-19</keyword>   <keyword>epidemiological modelling</keyword>   <keyword>SEIR</keyword>    <author primary="1"> <ARLID>cav_un_auth*0222657</ARLID> <name1>Brom</name1> <name2>C.</name2> <country>CZ</country> </author> <author primary="0"> <ARLID>cav_un_auth*0449183</ARLID> <name1>Diviák</name1> <name2>T.</name2> <country>CZ</country> </author> <author primary="0"> <ARLID>cav_un_auth*0051505</ARLID> <name1>Drbohlav</name1> <name2>J.</name2> <country>CZ</country> </author> <author primary="0"> <ARLID>cav_un_auth*0363657</ARLID> <name1>Korbel</name1> <name2>Václav</name2> <institution>NHU-N</institution> <full_dept>Economics Institute</full_dept> <fullinstit>Ekonomický ústav AV ČR, v. v. i.</fullinstit> </author> <author primary="0"> <ARLID>cav_un_auth*0106308</ARLID> <name1>Levínský</name1> <name2>René</name2> <institution>NHU-N</institution> <fullinstit>Ekonomický ústav AV ČR, v. v. i.</fullinstit> </author> <author primary="0"> <ARLID>cav_un_auth*0100794</ARLID> <name1>Neruda</name1> <name2>Roman</name2> <institution>UIVT-O</institution> <full_dept language="cz">Oddělení umělé inteligence</full_dept> <full_dept>Department of Artificial Intelligence</full_dept> <full_dept>Department of Machine Learning</full_dept> <fullinstit>Ústav informatiky AV ČR, v. v. i.</fullinstit> </author> <author primary="0"> <ARLID>cav_un_auth*0434902</ARLID> <name1>Kadlecová</name1> <name2>Gabriela</name2> <institution>UIVT-O</institution> <full_dept language="cz">Oddělení umělé inteligence</full_dept> <full_dept>Department of Artificial Intelligence</full_dept> <country>CZ</country> <fullinstit>Ústav informatiky AV ČR, v. v. i.</fullinstit> </author> <author primary="0"> <ARLID>cav_un_auth*0259020</ARLID> <name1>Šlerka</name1> <name2>J.</name2> <country>CZ</country> </author> <author primary="0"> <ARLID>cav_un_auth*0101206</ARLID> <name1>Šmíd</name1> <name2>Martin</name2> <institution>UTIA-B</institution> <full_dept language="cz">Ekonometrie</full_dept> <full_dept>Department of Econometrics</full_dept> <department language="cz">E</department> <department>E</department> <full_dept>Department of Econometrics</full_dept> <fullinstit>Ústav teorie informace a automatizace AV ČR, v. v. i.</fullinstit> </author> <author primary="0"> <ARLID>cav_un_auth*0091778</ARLID> <name1>Trnka</name1> <name2>J.</name2> <country>CZ</country> <garant>K</garant> </author> <author primary="0"> <ARLID>cav_un_auth*0231277</ARLID> <name1>Vidnerová</name1> <name2>Petra</name2> <institution>UIVT-O</institution> <full_dept language="cz">Oddělení umělé inteligence</full_dept> <full_dept>Department of Artificial Intelligence</full_dept> <full_dept>Department of Machine Learning</full_dept> <fullinstit>Ústav informatiky AV ČR, v. v. i.</fullinstit> </author>   <source> <url>https://doi.org/10.1038/s41598-023-45788-8</url>  </source>        <cas_special>  <abstract language="eng" primary="1">Rotations of schoolchildren were considered as a non-pharmacological intervention in the COVID-19 pandemic. This study investigates the impact of different rotation and testing schedules. We built an agent-based model of interactions among pupils and teachers based on a survey in an elementary school in Prague, Czechia. This model contains 624 schoolchildren and 55 teachers and about 27 thousands social contacts in 10 layers. The layers reflect different types of contacts (classroom, cafeteria, etc.) in the survey. On this multi-graph structure we run a modified SEIR model of covid-19 infection. The parameters of the model are calibrated on data from the outbreak in the Czech Republic in spring 2020. Weekly rotations of in-class and distance learning are an effective preventative measure in schools reducing the spread of covid-19 by 75–81% . Antigen testing twice a week or PCR once a week significantly reduces infections even when using tests with a lower sensitivity. The structure of social contacts between pupils and teachers strongly influences the transmission. While the density of contact graphs for older pupils is 1.5 times higher than for younger pupils, the teachers’ network is an order of magnitude denser. Teachers moreover act as bridges between groups of children, responsible for 14–18% of infections in the secondary school compared to 8–11% in the primary school. Weekly rotations with regular testing are a highly effective non-pharmacological intervention for the prevention of covid-19 spread in schools and a way to keep schools open during an epidemic.</abstract>     <FORD0>10000</FORD0> <FORD1>10200</FORD1> <FORD2>10201</FORD2>     <reportyear>2024</reportyear>      <num_of_auth>11</num_of_auth>  <unknown tag="mrcbC47"> NHU-N 50000 50200 50202 </unknown> <unknown tag="mrcbC47"> UTIA-B 10000 10100 10103 </unknown> <unknown tag="mrcbC52"> 2 4 O 4o as 20241118143041.8 20250320211905.0 A sml 20260108152432.7 </unknown> <inst_support> RVO:67985807 </inst_support> <inst_support> RVO:67985556 </inst_support> <inst_support> RVO:67985998 </inst_support>  <permalink>https://hdl.handle.net/11104/0347085</permalink>  <cooperation> <ARLID>cav_un_auth*0339298</ARLID> <name>UTIA</name> </cooperation> <cooperation> <ARLID>cav_un_auth*0345048</ARLID> <name>Národohospodářský ústav AV ČR</name> </cooperation>  <confidential>S</confidential>  <article_num> 19156 </article_num> <unknown tag="mrcbC86"> Article Multidisciplinary Sciences </unknown> <unknown tag="mrcbC91"> A </unknown>         <unknown tag="mrcbT16-e">MULTIDISCIPLINARYSCIENCES</unknown> <unknown tag="mrcbT16-f">4.3</unknown> <unknown tag="mrcbT16-g">0.8</unknown> <unknown tag="mrcbT16-h">4.8</unknown> <unknown tag="mrcbT16-i">0.90728</unknown> <unknown tag="mrcbT16-j">1.061</unknown> <unknown tag="mrcbT16-k">734947</unknown> <unknown tag="mrcbT16-q">347</unknown> <unknown tag="mrcbT16-s">0.9</unknown> <unknown tag="mrcbT16-y">48.79</unknown> <unknown tag="mrcbT16-x">3.89</unknown> <unknown tag="mrcbT16-3">283942</unknown> <unknown tag="mrcbT16-4">Q1</unknown> <unknown tag="mrcbT16-5">3.700</unknown> <unknown tag="mrcbT16-6">22037</unknown> <unknown tag="mrcbT16-7">Q1</unknown> <unknown tag="mrcbT16-C">81.7</unknown> <unknown tag="mrcbT16-D">Q2</unknown> <unknown tag="mrcbT16-E">Q2</unknown> <unknown tag="mrcbT16-M">1.05</unknown> <unknown tag="mrcbT16-N">Q1</unknown> <unknown tag="mrcbT16-P">81.7</unknown> <arlyear>2023</arlyear>    <unknown tag="mrcbTft">  Soubory v repozitáři: prohlaseni_levinsky.pdf, 0578058-aoa.pdf </unknown>    <unknown tag="mrcbU14"> 85175848114 SCOPUS </unknown> <unknown tag="mrcbU24"> 37932281 PUBMED </unknown> <unknown tag="mrcbU34"> 001108929300050 WOS </unknown> <unknown tag="mrcbU63"> cav_un_epca*0386594 Scientific Reports 2045-2322 2045-2322 Roč. 13 č. 1 2023 Nature Publishing Group </unknown> </cas_special> </bibitem>