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http://hdl.handle.net/1942/34696
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DC Field | Value | Language |
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dc.contributor.author | KREMER, Cécile | - |
dc.contributor.author | TORNERI, Andrea | - |
dc.contributor.author | Boesmans, Sien | - |
dc.contributor.author | MEUWISSEN, Hanne | - |
dc.contributor.author | VERDONSCHOT, Selina | - |
dc.contributor.author | VANDEN DRIESSCHE, Koen | - |
dc.contributor.author | Althaus, Christian L | - |
dc.contributor.author | FAES, Christel | - |
dc.contributor.author | HENS, Niel | - |
dc.date.accessioned | 2021-08-20T13:18:59Z | - |
dc.date.available | 2021-08-20T13:18:59Z | - |
dc.date.issued | 2021 | - |
dc.date.submitted | 2021-08-18T09:59:09Z | - |
dc.identifier.citation | Scientific reports (Nature Publishing Group), 11 (1) (Art N° 14107) | - |
dc.identifier.uri | http://hdl.handle.net/1942/34696 | - |
dc.description.abstract | The number of secondary cases, i.e. the number of new infections generated by an infectious individual, is an important parameter for the control of infectious diseases. When individual variation in disease transmission is present, like for COVID-19, the distribution of the number of secondary cases is skewed and often modeled using a negative binomial distribution. However, this may not always be the best distribution to describe the underlying transmission process. We propose the use of three other offspring distributions to quantify heterogeneity in transmission, and we assess the possible bias in estimates of the mean and variance of this distribution when the data generating distribution is different from the one used for inference. We also analyze COVID-19 data from Hong Kong, India, and Rwanda, and quantify the proportion of cases responsible for 80% of transmission, [Formula: see text], while acknowledging the variation arising from the assumed offspring distribution. In a simulation study, we find that variance estimates may be biased when there is a substantial amount of heterogeneity, and that selection of the most accurate distribution from a set of distributions is important. In addition we find that the number of secondary cases for two of the three COVID-19 datasets is better described by a Poisson-lognormal distribution. | - |
dc.language.iso | en | - |
dc.publisher | NATURE RESEARCH | - |
dc.subject.other | COVID-19 | - |
dc.subject.other | Computer Simulation | - |
dc.subject.other | Hong Kong | - |
dc.subject.other | Humans | - |
dc.subject.other | India | - |
dc.subject.other | Infectious Disease Transmission, Vertical | - |
dc.subject.other | Poisson Distribution | - |
dc.subject.other | Rwanda | - |
dc.subject.other | SARS-CoV-2 | - |
dc.title | Quantifying superspreading for COVID-19 using Poisson mixture distributions | - |
dc.type | Journal Contribution | - |
dc.identifier.issue | 1 | - |
dc.identifier.volume | 11 | - |
local.bibliographicCitation.jcat | A1 | - |
local.publisher.place | HEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
local.bibliographicCitation.artnr | 14107 | - |
local.type.programme | VSC | - |
local.type.programme | H2020 | - |
local.relation.h2020 | 101003688 | - |
dc.identifier.doi | 10.1038/s41598-021-93578-x | - |
dc.identifier.pmid | 34238978 | - |
dc.identifier.isi | WOS:000674513600025 | - |
local.provider.type | PubMed | - |
local.uhasselt.uhpub | yes | - |
local.uhasselt.international | yes | - |
item.fulltext | With Fulltext | - |
item.accessRights | Open Access | - |
item.fullcitation | KREMER, Cécile; TORNERI, Andrea; Boesmans, Sien; MEUWISSEN, Hanne; VERDONSCHOT, Selina; VANDEN DRIESSCHE, Koen; Althaus, Christian L; FAES, Christel & HENS, Niel (2021) Quantifying superspreading for COVID-19 using Poisson mixture distributions. In: Scientific reports (Nature Publishing Group), 11 (1) (Art N° 14107). | - |
item.validation | ecoom 2022 | - |
item.contributor | KREMER, Cécile | - |
item.contributor | TORNERI, Andrea | - |
item.contributor | Boesmans, Sien | - |
item.contributor | MEUWISSEN, Hanne | - |
item.contributor | VERDONSCHOT, Selina | - |
item.contributor | VANDEN DRIESSCHE, Koen | - |
item.contributor | Althaus, Christian L | - |
item.contributor | FAES, Christel | - |
item.contributor | HENS, Niel | - |
crisitem.journal.issn | 2045-2322 | - |
crisitem.journal.eissn | 2045-2322 | - |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
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s41598-021-93578-x.pdf | Published version | 3.49 MB | Adobe PDF | View/Open |
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