Forecasting COVID-19 epidemic in India and high incidence states using SIR and logistic growth models.
Identifieur interne : 000005 ( Main/Exploration ); précédent : 000004; suivant : 000006Forecasting COVID-19 epidemic in India and high incidence states using SIR and logistic growth models.
Auteurs : B. Malavika [Inde] ; S. Marimuthu [Inde] ; Melvin Joy [Inde] ; Ambily Nadaraj [Inde] ; Edwin Sam Asirvatham [Inde] ; L. Jeyaseelan [Inde]Source :
- Clinical epidemiology and global health [ 2452-0918 ]
Abstract
Background
Ever since the Coronavirus disease (COVID-19) outbreak emerged in China, there has been several attempts to predict the epidemic across the world with varying degrees of accuracy and reliability. This paper aims to carry out a short-term projection of new cases; forecast the maximum number of active cases for India and selected high-incidence states; and evaluate the impact of three weeks lock down period using different models.
Methods
We used Logistic growth curve model for short term prediction; SIR models to forecast the maximum number of active cases and peak time; and Time Interrupted Regression model to evaluate the impact of lockdown and other interventions.
Results
The predicted cumulative number of cases for India was 58,912 (95% CI: 57,960, 59,853) by May 08, 2020 and the observed number of cases was 59,695. The model predicts a cumulative number of 1,02,974 (95% CI: 1,01,987, 1,03,904) cases by May 22, 2020. As per SIR model, the maximum number of active cases is projected to be 57,449 on May 18, 2020. The time interrupted regression model indicates a decrease of about 149 daily new cases after the lock down period, which is statistically not significant.
Conclusion
The Logistic growth curve model predicts accurately the short-term scenario for India and high incidence states. The prediction through SIR model may be used for planning and prepare the health systems. The study also suggests that there is no evidence to conclude that there is a positive impact of lockdown in terms of reduction in new cases.
DOI: 10.1016/j.cegh.2020.06.006
PubMed: 32838058
PubMed Central: PMC7319934
Affiliations:
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Marimuthu</name><affiliation wicri:level="1"><nlm:affiliation>Associate Research Officer, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, 632 002, India.</nlm:affiliation><country xml:lang="fr">Inde</country><wicri:regionArea>Associate Research Officer, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, 632 002</wicri:regionArea><wicri:noRegion>632 002</wicri:noRegion></affiliation></author><author><name sortKey="Joy, Melvin" sort="Joy, Melvin" uniqKey="Joy M" first="Melvin" last="Joy">Melvin Joy</name><affiliation wicri:level="1"><nlm:affiliation>Associate Research Officer, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, 632 002, India.</nlm:affiliation><country xml:lang="fr">Inde</country><wicri:regionArea>Associate Research Officer, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, 632 002</wicri:regionArea><wicri:noRegion>632 002</wicri:noRegion></affiliation></author><author><name sortKey="Nadaraj, Ambily" sort="Nadaraj, Ambily" uniqKey="Nadaraj A" first="Ambily" last="Nadaraj">Ambily Nadaraj</name><affiliation wicri:level="1"><nlm:affiliation>Associate Research Officer, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, 632 002, India.</nlm:affiliation><country xml:lang="fr">Inde</country><wicri:regionArea>Associate Research Officer, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, 632 002</wicri:regionArea><wicri:noRegion>632 002</wicri:noRegion></affiliation></author><author><name sortKey="Asirvatham, Edwin Sam" sort="Asirvatham, Edwin Sam" uniqKey="Asirvatham E" first="Edwin Sam" last="Asirvatham">Edwin Sam Asirvatham</name><affiliation wicri:level="1"><nlm:affiliation>Technical Adviser (Health Systems and Policy), Health Systems Research India Initiative (HSRII), Trivandrum, India.</nlm:affiliation><country xml:lang="fr">Inde</country><wicri:regionArea>Technical Adviser (Health Systems and Policy), Health Systems Research India Initiative (HSRII), Trivandrum</wicri:regionArea><wicri:noRegion>Trivandrum</wicri:noRegion></affiliation></author><author><name sortKey="Jeyaseelan, L" sort="Jeyaseelan, L" uniqKey="Jeyaseelan L" first="L" last="Jeyaseelan">L. 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Malavika</name><affiliation wicri:level="1"><nlm:affiliation>Associate Research Officer, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, 632 002, India.</nlm:affiliation><country xml:lang="fr">Inde</country><wicri:regionArea>Associate Research Officer, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, 632 002</wicri:regionArea><wicri:noRegion>632 002</wicri:noRegion></affiliation></author><author><name sortKey="Marimuthu, S" sort="Marimuthu, S" uniqKey="Marimuthu S" first="S" last="Marimuthu">S. Marimuthu</name><affiliation wicri:level="1"><nlm:affiliation>Associate Research Officer, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, 632 002, India.</nlm:affiliation><country xml:lang="fr">Inde</country><wicri:regionArea>Associate Research Officer, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, 632 002</wicri:regionArea><wicri:noRegion>632 002</wicri:noRegion></affiliation></author><author><name sortKey="Joy, Melvin" sort="Joy, Melvin" uniqKey="Joy M" first="Melvin" last="Joy">Melvin Joy</name><affiliation wicri:level="1"><nlm:affiliation>Associate Research Officer, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, 632 002, India.</nlm:affiliation><country xml:lang="fr">Inde</country><wicri:regionArea>Associate Research Officer, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, 632 002</wicri:regionArea><wicri:noRegion>632 002</wicri:noRegion></affiliation></author><author><name sortKey="Nadaraj, Ambily" sort="Nadaraj, Ambily" uniqKey="Nadaraj A" first="Ambily" last="Nadaraj">Ambily Nadaraj</name><affiliation wicri:level="1"><nlm:affiliation>Associate Research Officer, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, 632 002, India.</nlm:affiliation><country xml:lang="fr">Inde</country><wicri:regionArea>Associate Research Officer, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, 632 002</wicri:regionArea><wicri:noRegion>632 002</wicri:noRegion></affiliation></author><author><name sortKey="Asirvatham, Edwin Sam" sort="Asirvatham, Edwin Sam" uniqKey="Asirvatham E" first="Edwin Sam" last="Asirvatham">Edwin Sam Asirvatham</name><affiliation wicri:level="1"><nlm:affiliation>Technical Adviser (Health Systems and Policy), Health Systems Research India Initiative (HSRII), Trivandrum, India.</nlm:affiliation><country xml:lang="fr">Inde</country><wicri:regionArea>Technical Adviser (Health Systems and Policy), Health Systems Research India Initiative (HSRII), Trivandrum</wicri:regionArea><wicri:noRegion>Trivandrum</wicri:noRegion></affiliation></author><author><name sortKey="Jeyaseelan, L" sort="Jeyaseelan, L" uniqKey="Jeyaseelan L" first="L" last="Jeyaseelan">L. Jeyaseelan</name><affiliation wicri:level="1"><nlm:affiliation>Professor, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, 632 002, India.</nlm:affiliation><country xml:lang="fr">Inde</country><wicri:regionArea>Professor, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, 632 002</wicri:regionArea><wicri:noRegion>632 002</wicri:noRegion></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>Ever since the Coronavirus disease (COVID-19) outbreak emerged in China, there has been several attempts to predict the epidemic across the world with varying degrees of accuracy and reliability. This paper aims to carry out a short-term projection of new cases; forecast the maximum number of active cases for India and selected high-incidence states; and evaluate the impact of three weeks lock down period using different models.</p></div><div type="abstract" xml:lang="en"><p><b>Methods</b></p><p>We used Logistic growth curve model for short term prediction; SIR models to forecast the maximum number of active cases and peak time; and Time Interrupted Regression model to evaluate the impact of lockdown and other interventions.</p></div><div type="abstract" xml:lang="en"><p><b>Results</b></p><p>The predicted cumulative number of cases for India was 58,912 (95% CI: 57,960, 59,853) by May 08, 2020 and the observed number of cases was 59,695. The model predicts a cumulative number of 1,02,974 (95% CI: 1,01,987, 1,03,904) cases by May 22, 2020. As per SIR model, the maximum number of active cases is projected to be 57,449 on May 18, 2020. The time interrupted regression model indicates a decrease of about 149 daily new cases after the lock down period, which is statistically not significant.</p></div><div type="abstract" xml:lang="en"><p><b>Conclusion</b></p><p>The Logistic growth curve model predicts accurately the short-term scenario for India and high incidence states. The prediction through SIR model may be used for planning and prepare the health systems. The study also suggests that there is no evidence to conclude that there is a positive impact of lockdown in terms of reduction in new cases.</p></div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">32838058</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>Forecasting COVID-19 epidemic in India and high incidence states using SIR and logistic growth models.</ArticleTitle><Pagination><MedlinePgn>26-33</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.cegh.2020.06.006</ELocationID><Abstract><AbstractText Label="Background" NlmCategory="UNASSIGNED">Ever since the Coronavirus disease (COVID-19) outbreak emerged in China, there has been several attempts to predict the epidemic across the world with varying degrees of accuracy and reliability. This paper aims to carry out a short-term projection of new cases; forecast the maximum number of active cases for India and selected high-incidence states; and evaluate the impact of three weeks lock down period using different models.</AbstractText><AbstractText Label="Methods" NlmCategory="UNASSIGNED">We used Logistic growth curve model for short term prediction; SIR models to forecast the maximum number of active cases and peak time; and Time Interrupted Regression model to evaluate the impact of lockdown and other interventions.</AbstractText><AbstractText Label="Results" NlmCategory="UNASSIGNED">The predicted cumulative number of cases for India was 58,912 (95% CI: 57,960, 59,853) by May 08, 2020 and the observed number of cases was 59,695. The model predicts a cumulative number of 1,02,974 (95% CI: 1,01,987, 1,03,904) cases by May 22, 2020. As per SIR model, the maximum number of active cases is projected to be 57,449 on May 18, 2020. The time interrupted regression model indicates a decrease of about 149 daily new cases after the lock down period, which is statistically not significant.</AbstractText><AbstractText Label="Conclusion" NlmCategory="UNASSIGNED">The Logistic growth curve model predicts accurately the short-term scenario for India and high incidence states. The prediction through SIR model may be used for planning and prepare the health systems. The study also suggests that there is no evidence to conclude that there is a positive impact of lockdown in terms of reduction in new cases.</AbstractText><CopyrightInformation>© 2020 INDIACLEN. Published by Elsevier, a division of RELX India, Pvt. Ltd.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Malavika</LastName><ForeName>B</ForeName><Initials>B</Initials><AffiliationInfo><Affiliation>Associate Research Officer, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, 632 002, India.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Marimuthu</LastName><ForeName>S</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Associate Research Officer, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, 632 002, India.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Joy</LastName><ForeName>Melvin</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Associate Research Officer, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, 632 002, India.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Nadaraj</LastName><ForeName>Ambily</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Associate Research Officer, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, 632 002, India.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Asirvatham</LastName><ForeName>Edwin Sam</ForeName><Initials>ES</Initials><AffiliationInfo><Affiliation>Technical Adviser (Health Systems and Policy), Health Systems Research India Initiative (HSRII), Trivandrum, India.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Jeyaseelan</LastName><ForeName>L</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Professor, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, 632 002, 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>27</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">Logistic growth model</Keyword><Keyword MajorTopicYN="N">Projection</Keyword><Keyword MajorTopicYN="N">SIR model</Keyword><Keyword MajorTopicYN="N">Time interrupted regression model</Keyword></KeywordList><CoiStatement>Prominence, professional advancement or a successful outcome. CEGH Editors strive to ensure that what is published in the Journal is as balanced, objective and evidence-based as possible. Since it can be difficult to distinguish between an actual conflict of interest and a perceived conflict of interest, the Journal requires authors to disclose all and any potential conflicts of interest. Section I. The authors whose names are listed immediately below certify that they have NO affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in Testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript. Section II. The authors whose names are listed immediately below report the following details of affiliation or involvement in an organization or entity with a financial or non-financial interest in the subject matter or materials discussed in this manuscript. Please specify the nature of the conflict on a separate sheet of paper if the space below is inadequate.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>05</Month><Day>13</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2020</Year><Month>06</Month><Day>02</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>06</Month><Day>22</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">32838058</ArticleId><ArticleId IdType="doi">10.1016/j.cegh.2020.06.006</ArticleId><ArticleId IdType="pii">S2213-3984(20)30163-9</ArticleId><ArticleId IdType="pmc">PMC7319934</ArticleId></ArticleIdList><pmc-dir>pmcsd</pmc-dir>
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