When COVID-19 will decline in India? Prediction by combination of recovery and case load rate.
Identifieur interne : 001A19 ( Main/Corpus ); précédent : 001A18; suivant : 001A20When COVID-19 will decline in India? Prediction by combination of recovery and case load rate.
Auteurs : Atanu Bhattacharjee ; Mukesh Kumar ; Kamalesh Kumar PatelSource :
- Clinical epidemiology and global health [ 2452-0918 ]
Abstract
Background
The World Health Organization (WHO) declared COVID-19 as a pandemic on March 11, 2020. There is sudden need of statistical modeling due to onset of COVID-19 pandemic across the world. But health planning and policy requirements need the estimates of disease problem from clinical data.
Objective
The present study aimed to predict the declination of COVID-19 using recovery rate and case load rate on basis of available data from India.
Methods
The reported COVID-19 cases in the country were obtained from website (https://datahub.io/core/covid-19#resource-covid-19_zip/). The confirmed cases, recovered cases and deaths were used for estimating recovery rate, case load rate and death rate till June 04, 2020.
Results
A total of 216919 confirmed cases were reported nationwide in India on June 04, 2020. It is found that the recovery rate increased to 47.99% and case load rate decreased to 49.21%. Death rate is found to be very low 2.80%. Accordingly, coincidence of the difference of case load rate and recovery rate (delta) will reveal a declination in expected COVID-19 cases.
Conclusion
The epidemic in the country was mainly caused by the movement of people from various foreign countries to India. Lockdown as restricting the migration of population and decision taken by the government to quarantine the population may greatly reduce the risk of continued spread of the epidemic in India. This study predicts that when the case load rate gets lesser than recovery rate, there after COVID-19 patients would be started to decline.
DOI: 10.1016/j.cegh.2020.06.004
PubMed: 32838057
PubMed Central: PMC7308770
Links to Exploration step
pubmed:32838057Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">When COVID-19 will decline in India? Prediction by combination of recovery and case load rate.</title><author><name sortKey="Bhattacharjee, Atanu" sort="Bhattacharjee, Atanu" uniqKey="Bhattacharjee A" first="Atanu" last="Bhattacharjee">Atanu Bhattacharjee</name><affiliation><nlm:affiliation>Section of Biostatistics, Centre for Cancer Epidemiology, TMC, Mumbai, India.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Homi Bhaba National Institute, Mumbai, India.</nlm:affiliation></affiliation></author><author><name sortKey="Kumar, Mukesh" sort="Kumar, Mukesh" uniqKey="Kumar M" first="Mukesh" last="Kumar">Mukesh Kumar</name><affiliation><nlm:affiliation>Department of Statistics, MMV, Banaras Hindu University, Varanasi, India.</nlm:affiliation></affiliation></author><author><name sortKey="Patel, Kamalesh Kumar" sort="Patel, Kamalesh Kumar" uniqKey="Patel K" first="Kamalesh Kumar" last="Patel">Kamalesh Kumar Patel</name><affiliation><nlm:affiliation>Department of Public Health, Indian Institute of Health Management Research, Jaipur, India.</nlm:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2021">2021 Jan-Mar</date><idno type="RBID">pubmed:32838057</idno><idno type="pmid">32838057</idno><idno type="doi">10.1016/j.cegh.2020.06.004</idno><idno type="pmc">PMC7308770</idno><idno type="wicri:Area/Main/Corpus">001A19</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">001A19</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">When COVID-19 will decline in India? Prediction by combination of recovery and case load rate.</title><author><name sortKey="Bhattacharjee, Atanu" sort="Bhattacharjee, Atanu" uniqKey="Bhattacharjee A" first="Atanu" last="Bhattacharjee">Atanu Bhattacharjee</name><affiliation><nlm:affiliation>Section of Biostatistics, Centre for Cancer Epidemiology, TMC, Mumbai, India.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Homi Bhaba National Institute, Mumbai, India.</nlm:affiliation></affiliation></author><author><name sortKey="Kumar, Mukesh" sort="Kumar, Mukesh" uniqKey="Kumar M" first="Mukesh" last="Kumar">Mukesh Kumar</name><affiliation><nlm:affiliation>Department of Statistics, MMV, Banaras Hindu University, Varanasi, India.</nlm:affiliation></affiliation></author><author><name sortKey="Patel, Kamalesh Kumar" sort="Patel, Kamalesh Kumar" uniqKey="Patel K" first="Kamalesh Kumar" last="Patel">Kamalesh Kumar Patel</name><affiliation><nlm:affiliation>Department of Public Health, Indian Institute of Health Management Research, Jaipur, India.</nlm:affiliation></affiliation></author></analytic><series><title level="j">Clinical epidemiology and global health</title><idno type="ISSN">2452-0918</idno></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>Background</b></p><p>The World Health Organization (WHO) declared COVID-19 as a pandemic on March 11, 2020. There is sudden need of statistical modeling due to onset of COVID-19 pandemic across the world. But health planning and policy requirements need the estimates of disease problem from clinical data.</p></div><div type="abstract" xml:lang="en"><p><b>Objective</b></p><p>The present study aimed to predict the declination of COVID-19 using recovery rate and case load rate on basis of available data from India.</p></div><div type="abstract" xml:lang="en"><p><b>Methods</b></p><p>The reported COVID-19 cases in the country were obtained from website (https://datahub.io/core/covid-19#resource-covid-19_zip/). The confirmed cases, recovered cases and deaths were used for estimating recovery rate, case load rate and death rate till June 04, 2020.</p></div><div type="abstract" xml:lang="en"><p><b>Results</b></p><p>A total of 216919 confirmed cases were reported nationwide in India on June 04, 2020. It is found that the recovery rate increased to 47.99% and case load rate decreased to 49.21%. Death rate is found to be very low 2.80%. Accordingly, coincidence of the difference of case load rate and recovery rate (delta) will reveal a declination in expected COVID-19 cases.</p></div><div type="abstract" xml:lang="en"><p><b>Conclusion</b></p><p>The epidemic in the country was mainly caused by the movement of people from various foreign countries to India. Lockdown as restricting the migration of population and decision taken by the government to quarantine the population may greatly reduce the risk of continued spread of the epidemic in India. This study predicts that when the case load rate gets lesser than recovery rate, there after COVID-19 patients would be started to decline.</p></div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">32838057</PMID><DateRevised><Year>2020</Year><Month>12</Month><Day>17</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Print">2452-0918</ISSN><JournalIssue CitedMedium="Print"><Volume>9</Volume><PubDate><MedlineDate>2021 Jan-Mar</MedlineDate></PubDate></JournalIssue><Title>Clinical epidemiology and global health</Title><ISOAbbreviation>Clin Epidemiol Glob Health</ISOAbbreviation></Journal><ArticleTitle>When COVID-19 will decline in India? Prediction by combination of recovery and case load rate.</ArticleTitle><Pagination><MedlinePgn>17-20</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.cegh.2020.06.004</ELocationID><Abstract><AbstractText Label="Background" NlmCategory="UNASSIGNED">The World Health Organization (WHO) declared COVID-19 as a pandemic on March 11, 2020. There is sudden need of statistical modeling due to onset of COVID-19 pandemic across the world. But health planning and policy requirements need the estimates of disease problem from clinical data.</AbstractText><AbstractText Label="Objective" NlmCategory="UNASSIGNED">The present study aimed to predict the declination of COVID-19 using recovery rate and case load rate on basis of available data from India.</AbstractText><AbstractText Label="Methods" NlmCategory="UNASSIGNED">The reported COVID-19 cases in the country were obtained from website (https://datahub.io/core/covid-19#resource-covid-19_zip/). The confirmed cases, recovered cases and deaths were used for estimating recovery rate, case load rate and death rate till June 04, 2020.</AbstractText><AbstractText Label="Results" NlmCategory="UNASSIGNED">A total of 216919 confirmed cases were reported nationwide in India on June 04, 2020. It is found that the recovery rate increased to 47.99% and case load rate decreased to 49.21%. Death rate is found to be very low 2.80%. Accordingly, coincidence of the difference of case load rate and recovery rate (delta) will reveal a declination in expected COVID-19 cases.</AbstractText><AbstractText Label="Conclusion" NlmCategory="UNASSIGNED">The epidemic in the country was mainly caused by the movement of people from various foreign countries to India. Lockdown as restricting the migration of population and decision taken by the government to quarantine the population may greatly reduce the risk of continued spread of the epidemic in India. This study predicts that when the case load rate gets lesser than recovery rate, there after COVID-19 patients would be started to decline.</AbstractText><CopyrightInformation>© 2020 Published by Elsevier, a division of RELX India, Pvt. Ltd on behalf of INDIACLEN.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Bhattacharjee</LastName><ForeName>Atanu</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Section of Biostatistics, Centre for Cancer Epidemiology, TMC, Mumbai, India.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Homi Bhaba National Institute, Mumbai, India.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Kumar</LastName><ForeName>Mukesh</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Department of Statistics, MMV, Banaras Hindu University, Varanasi, India.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Patel</LastName><ForeName>Kamalesh Kumar</ForeName><Initials>KK</Initials><AffiliationInfo><Affiliation>Department of Public Health, Indian Institute of Health Management Research, Jaipur, India.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>06</Month><Day>23</Day></ArticleDate></Article><MedlineJournalInfo><Country>India</Country><MedlineTA>Clin Epidemiol Glob Health</MedlineTA><NlmUniqueID>101608821</NlmUniqueID><ISSNLinking>2213-3984</ISSNLinking></MedlineJournalInfo><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">COVID-19</Keyword><Keyword MajorTopicYN="N">Case load rate</Keyword><Keyword MajorTopicYN="N">Death rate</Keyword><Keyword MajorTopicYN="N">India</Keyword><Keyword MajorTopicYN="N">Recovery rate</Keyword></KeywordList><CoiStatement>The authors declare no conflict of interest.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>05</Month><Day>12</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2020</Year><Month>06</Month><Day>08</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>06</Month><Day>19</Day></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>8</Month><Day>25</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>8</Month><Day>25</Day><Hour>6</Hour><Minute>1</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>8</Month><Day>25</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32838057</ArticleId><ArticleId IdType="doi">10.1016/j.cegh.2020.06.004</ArticleId><ArticleId IdType="pii">S2213-3984(20)30161-5</ArticleId><ArticleId IdType="pmc">PMC7308770</ArticleId></ArticleIdList><pmc-dir>pmcsd</pmc-dir>
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