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Article: Early insights from statistical and mathematical modeling of key epidemiologic parameters of COVID-19

TitleEarly insights from statistical and mathematical modeling of key epidemiologic parameters of COVID-19
Authors
Biggerstaff, MCowling, BJCucunubá, ZMDinh, LFerguson, NMGao, HHill, VImai, NJohansson, MAKada, SMorgan, OPastore y Piontti, APolonsky, JAPrasad, PVQuandelacy, TMRambaut, ATappero, JWVandemaele, KAVespignani, AWarmbrod, KLWong, JY
Keywords2019 novel coronavirus disease
coronavirus
COVID-19
epidemiological parameters
mathematical modeling
Issue Date2020
PublisherUS Department of Health and Human Services, Centers for Disease Control and Prevention. The Journal's web site is located at http://www.cdc.gov/ncidod/EID/index.htm
Citation
Emerging Infectious Diseases, 2020, v. 26 n. 11, p. e1-e14 How to Cite?
DOI: http://dx.doi.org/10.3201/eid2611.201074
AbstractWe report key epidemiologic parameter estimates for coronavirus disease identified in peer-reviewed publications, preprint articles, and online reports. Range estimates for incubation period were 1.8–6.9 days, serial interval 4.0–7.5 days, and doubling time 2.3–7.4 days. The effective reproductive number varied widely, with reductions attributable to interventions. Case burden and infection fatality ratios increased with patient age. Implementation of combined interventions could reduce cases and delay epidemic peak up to 1 month. These parameters for transmission, disease severity, and intervention effectiveness are critical for guiding policy decisions. Estimates will likely change as new information becomes available.
DescriptionFor the WHO COVID-19 Modelling Parameters Group
Persistent Identifierhttp://hdl.handle.net/10722/290485
ISSN
1080-6040
2021 Impact Factor: 16.126
2020 SCImago Journal Rankings: 2.540
PubMed Central ID
PMC7588530
ISI Accession Number ID
WOS:000746993900001

 

DC FieldValueLanguage
dc.contributor.authorBiggerstaff, M-
dc.contributor.authorCowling, BJ-
dc.contributor.authorCucunubá, ZM-
dc.contributor.authorDinh, L-
dc.contributor.authorFerguson, NM-
dc.contributor.authorGao, H-
dc.contributor.authorHill, V-
dc.contributor.authorImai, N-
dc.contributor.authorJohansson, MA-
dc.contributor.authorKada, S-
dc.contributor.authorMorgan, O-
dc.contributor.authorPastore y Piontti, A-
dc.contributor.authorPolonsky, JA-
dc.contributor.authorPrasad, PV-
dc.contributor.authorQuandelacy, TM-
dc.contributor.authorRambaut, A-
dc.contributor.authorTappero, JW-
dc.contributor.authorVandemaele, KA-
dc.contributor.authorVespignani, A-
dc.contributor.authorWarmbrod, KL-
dc.contributor.authorWong, JY-
dc.date.accessioned2020-11-02T05:42:54Z-
dc.date.available2020-11-02T05:42:54Z-
dc.date.issued2020-
dc.identifier.citationEmerging Infectious Diseases, 2020, v. 26 n. 11, p. e1-e14-
dc.identifier.issn1080-6040-
dc.identifier.urihttp://hdl.handle.net/10722/290485-
dc.descriptionFor the WHO COVID-19 Modelling Parameters Group-
dc.description.abstractWe report key epidemiologic parameter estimates for coronavirus disease identified in peer-reviewed publications, preprint articles, and online reports. Range estimates for incubation period were 1.8–6.9 days, serial interval 4.0–7.5 days, and doubling time 2.3–7.4 days. The effective reproductive number varied widely, with reductions attributable to interventions. Case burden and infection fatality ratios increased with patient age. Implementation of combined interventions could reduce cases and delay epidemic peak up to 1 month. These parameters for transmission, disease severity, and intervention effectiveness are critical for guiding policy decisions. Estimates will likely change as new information becomes available.-
dc.languageeng-
dc.publisherUS Department of Health and Human Services, Centers for Disease Control and Prevention. The Journal's web site is located at http://www.cdc.gov/ncidod/EID/index.htm-
dc.relation.ispartofEmerging Infectious Diseases-
dc.subject2019 novel coronavirus disease-
dc.subjectcoronavirus-
dc.subjectCOVID-19-
dc.subjectepidemiological parameters-
dc.subjectmathematical modeling-
dc.titleEarly insights from statistical and mathematical modeling of key epidemiologic parameters of COVID-19-
dc.typeArticle-
dc.identifier.emailCowling, BJ: bcowling@hku.hk-
dc.identifier.emailWong, JY: wongytj@hku.hk-
dc.identifier.authorityCowling, BJ=rp01326-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.3201/eid2611.201074-
dc.identifier.pmid32917290-
dc.identifier.pmcidPMC7588530-
dc.identifier.scopuseid_2-s2.0-85093900447-
dc.identifier.hkuros318579-
dc.identifier.volume26-
dc.identifier.issue11-
dc.identifier.spagee1-
dc.identifier.epagee14-
dc.identifier.isiWOS:000746993900001-
dc.publisher.placeUnited States-
dc.identifier.issnl1080-6040-

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