<?xml version="1.0" encoding="utf-8"?>
<journal>
<title>Health Science Monitor</title>
<title_fa>Health Science Monitor</title_fa>
<short_title>Health Science Monitor</short_title>
<subject>Basic Sciences</subject>
<web_url>http://hsm.umsu.ac.ir</web_url>
<journal_hbi_system_id>1</journal_hbi_system_id>
<journal_hbi_system_user>admin</journal_hbi_system_user>
<journal_id_issn></journal_id_issn>
<journal_id_issn_online>2980-8723</journal_id_issn_online>
<journal_id_pii>8</journal_id_pii>
<journal_id_doi>10.61882/hsm</journal_id_doi>
<journal_id_iranmedex></journal_id_iranmedex>
<journal_id_magiran></journal_id_magiran>
<journal_id_sid>14</journal_id_sid>
<journal_id_nlai>9104634</journal_id_nlai>
<journal_id_science>13</journal_id_science>
<language>en</language>
<pubdate>
	<type>jalali</type>
	<year>1401</year>
	<month>11</month>
	<day>1</day>
</pubdate>
<pubdate>
	<type>gregorian</type>
	<year>2023</year>
	<month>2</month>
	<day>1</day>
</pubdate>
<volume>2</volume>
<number>1</number>
<publish_type>online</publish_type>
<publish_edition>1</publish_edition>
<article_type>fulltext</article_type>
<articleset>
	<article>


	<language>en</language>
	<article_id_doi></article_id_doi>
	<title_fa></title_fa>
	<title>Estimation and prediction of the prevalence rate of COVID-19 disease based on multilayer perceptron artificial neural networks model</title>
	<subject_fa>عمومى</subject_fa>
	<subject>General</subject>
	<content_type_fa>پژوهشي</content_type_fa>
	<content_type>Research Article</content_type>
	<abstract_fa></abstract_fa>
	<abstract>&lt;span style=&quot;font-size:12pt&quot;&gt;&lt;span style=&quot;line-height:16.0pt&quot;&gt;&lt;span new=&quot;&quot; roman=&quot;&quot; style=&quot;font-family:&quot; times=&quot;&quot;&gt;&lt;b&gt;&lt;i&gt;&lt;span style=&quot;font-size:9.0pt&quot;&gt;Background &amp; Aims&lt;/span&gt;&lt;/i&gt;&lt;/b&gt;&lt;b&gt;&lt;span style=&quot;font-size:9.0pt&quot;&gt;: &lt;/span&gt;&lt;/b&gt;&lt;span style=&quot;font-size:9.0pt&quot;&gt;Nowadays, with the coronavirus disease-2019 (COVID-19) pandemic, millions of people have been infected with the coronavirus, and most countries in the world have been unable to treat and control this condition. The aim of this study was to estimate and predict the COVID-19 prevalence rate based on multilayer perceptron artificial neural network (MLP-ANN) model.&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;br&gt;
&lt;span style=&quot;font-size:12pt&quot;&gt;&lt;span style=&quot;line-height:16.0pt&quot;&gt;&lt;span new=&quot;&quot; roman=&quot;&quot; style=&quot;font-family:&quot; times=&quot;&quot;&gt;&lt;b&gt;&lt;i&gt;&lt;span style=&quot;font-size:9.0pt&quot;&gt;Materials &amp; Methods&lt;/span&gt;&lt;/i&gt;&lt;/b&gt;&lt;b&gt;&lt;span style=&quot;font-size:9.0pt&quot;&gt;:&lt;/span&gt;&lt;/b&gt;&lt;span style=&quot;font-size:9.0pt&quot;&gt; In this cross-sectional study, based on the information of 4,372 patients with COVID-19 referred to Dr. Masih Daneshvari Hospital in Tehran, the prevalence rate of this disease was estimated. In addition, considering the role of the health measures and social restrictions, the trend of this index based on the MLP-ANN model was predicted. &lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;br&gt;
&lt;span style=&quot;font-size:12pt&quot;&gt;&lt;span style=&quot;line-height:16.0pt&quot;&gt;&lt;span new=&quot;&quot; roman=&quot;&quot; style=&quot;font-family:&quot; times=&quot;&quot;&gt;&lt;b&gt;&lt;i&gt;&lt;span style=&quot;font-size:9.0pt&quot;&gt;Results&lt;/span&gt;&lt;/i&gt;&lt;/b&gt;&lt;b&gt;&lt;span style=&quot;font-size:9.0pt&quot;&gt;:&lt;/span&gt;&lt;/b&gt;&lt;span style=&quot;font-size:9.0pt&quot;&gt; According to the results of this study, the prevalence of COVID-19 increased by an average of 7.05 per thousand people daily during the 48 days from the onset of the epidemic, and it reached about 341.96 per thousand people. Based on the MLP-ANN model with a lack of attention to the health measures by individuals in the community and failure to reduce social restrictions by the government, the COVID-19 prevalence increased by an average of 1.03 per thousand people per day. While in the case of attention to the health measures by the people and continued social restrictions by the state, the prevalence of this disease decreased by an average of 2.13 per thousand people, daily. &lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;br&gt;
&lt;b&gt;&lt;i&gt;&lt;span style=&quot;font-size:9.0pt&quot;&gt;&lt;span style=&quot;line-height:200%&quot;&gt;&lt;span new=&quot;&quot; roman=&quot;&quot; style=&quot;font-family:&quot; times=&quot;&quot;&gt;Conclusion&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/i&gt;&lt;span style=&quot;font-size:9.0pt&quot;&gt;&lt;span style=&quot;line-height:200%&quot;&gt;&lt;span new=&quot;&quot; roman=&quot;&quot; style=&quot;font-family:&quot; times=&quot;&quot;&gt;: &lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/b&gt;&lt;span style=&quot;font-size:9.0pt&quot;&gt;&lt;span style=&quot;line-height:200%&quot;&gt;&lt;span new=&quot;&quot; roman=&quot;&quot; style=&quot;font-family:&quot; times=&quot;&quot;&gt;The study on the prevalence of COVID-19 disease and prediction of the trend of this index provides researchers with useful information about the role of the health measures and social restrictions in controlling this disease.&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;</abstract>
	<keyword_fa></keyword_fa>
	<keyword>COVID-19, Prevalence index, Perceptron artificial neural network, Prediction</keyword>
	<start_page>13</start_page>
	<end_page>20</end_page>
	<web_url>http://hsm.umsu.ac.ir/browse.php?a_code=A-10-76-5&amp;slc_lang=en&amp;sid=1</web_url>


<author_list>
	<author>
	<first_name>Mehdi</first_name>
	<middle_name></middle_name>
	<last_name>Kazempour Dizaji</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>mehdikazempourdizaji@gmail.com</email>
	<code>10031947532846001388</code>
	<orcid>10031947532846001388</orcid>
	<coreauthor>Yes
</coreauthor>
	<affiliation>Mycobacteriology Research Center (MRC), National Research Institute of Tuberculosis and Lung Disease (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran</affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


	<author>
	<first_name>Arda</first_name>
	<middle_name></middle_name>
	<last_name>Kiani</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>mehdikazempourdizaji@gmail.com</email>
	<code>10031947532846001389</code>
	<orcid>10031947532846001389</orcid>
	<coreauthor>No</coreauthor>
	<affiliation>Tracheal Diseases Research Center, National Research Institute of Tuberculosis and Lung Disease (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran</affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


	<author>
	<first_name>Mohammad</first_name>
	<middle_name></middle_name>
	<last_name>Varahram</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>mehdikazempourdizaji@gmail.com</email>
	<code>10031947532846001390</code>
	<orcid>10031947532846001390</orcid>
	<coreauthor>No</coreauthor>
	<affiliation>Mycobacteriology Research Center (MRC), National Research Institute of Tuberculosis and Lung Disease (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran</affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


	<author>
	<first_name>Atefe</first_name>
	<middle_name></middle_name>
	<last_name>Abedini</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>mehdikazempourdizaji@gmail.com</email>
	<code>10031947532846001391</code>
	<orcid>1111-1111-1111-1111</orcid>
	<coreauthor>No</coreauthor>
	<affiliation>Chronic Respiratory Diseases Research Center, National Research Institute of Tuberculosis and Lung Disease (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran</affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


	<author>
	<first_name>Ali</first_name>
	<middle_name></middle_name>
	<last_name>Zare</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>mehdikazempourdizaji@gmail.com</email>
	<code>10031947532846001392</code>
	<orcid>1111-1111-1111-1111</orcid>
	<coreauthor>No</coreauthor>
	<affiliation>Department of Biostatistics, National Research Institute of Tuberculosis and Lung Disease (NRITLD) , , Tehran, Iran</affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


	<author>
	<first_name>Rahim</first_name>
	<middle_name></middle_name>
	<last_name>Roozbahani</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>mehdikazempourdizaji@gmail.com</email>
	<code>10031947532846001393</code>
	<orcid>1111-1111-1111-1111</orcid>
	<coreauthor>No</coreauthor>
	<affiliation>Clinical Tuberculosis and Epidemiology Research Center, National Research Institute of Tuberculosis and Lung Disease (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran. </affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


	<author>
	<first_name>Niloufar</first_name>
	<middle_name></middle_name>
	<last_name>Alizedeh Kolahdozi</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>mehdikazempourdizaji@gmail.com</email>
	<code>10031947532846001394</code>
	<orcid>1111-1111-1111-1111</orcid>
	<coreauthor>No</coreauthor>
	<affiliation>Department of Biostatistics, National Research Institute of Tuberculosis and Lung Disease (NRITLD) , Shahid Beheshti University of Medical Sciences, Tehran, Iran</affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


	<author>
	<first_name>Syeyd Alireza</first_name>
	<middle_name></middle_name>
	<last_name> Nadji</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>mehdikazempourdizaji@gmail.com</email>
	<code>10031947532846001395</code>
	<orcid>10031947532846001395</orcid>
	<coreauthor>No</coreauthor>
	<affiliation>Virology Research Center, National Research Institute of Tuberculosis and Lung Disease (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran</affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


	<author>
	<first_name>Mohammad Ali</first_name>
	<middle_name></middle_name>
	<last_name> Emamhadi</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>mehdikazempourdizaji@gmail.com</email>
	<code>10031947532846001396</code>
	<orcid>10031947532846001396</orcid>
	<coreauthor>No</coreauthor>
	<affiliation>Department Forensic Medicine, School of Medicine Shahid Beheshti University of Medical Sciences, Tehran, Iran </affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


	<author>
	<first_name>Majid </first_name>
	<middle_name></middle_name>
	<last_name>Marjani</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>mehdikazempourdizaji@gmail.com</email>
	<code>10031947532846001397</code>
	<orcid>10031947532846001397</orcid>
	<coreauthor>No</coreauthor>
	<affiliation>Clinical Tuberculosis and Epidemiology Research Center, National Research Institute of Tuberculosis and Lung Disease (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran</affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


</author_list>


	</article>
</articleset>
</journal>
