Inferring R0 in emerging epidemics: the effect of common population structure is small
When controlling an emerging outbreak of an infectious disease, it is essential to know the key epidemiological parameters, such as the basic reproduction number R0 and the control effort required to prevent a large outbreak. These parameters are estimated from the observed incidence of new cases an...
| Main Authors: | , , , , , |
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| Format: | Article |
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Royal Society, The
2016
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| Online Access: | https://eprints.nottingham.ac.uk/40526/ |
| _version_ | 1848796078646755328 |
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| author | Trapman, Pieter Ball, Frank Dhersin, Jean-Stéphane Tran, Viet Chi Wallinga, Jacco Britton, Tom |
| author_facet | Trapman, Pieter Ball, Frank Dhersin, Jean-Stéphane Tran, Viet Chi Wallinga, Jacco Britton, Tom |
| author_sort | Trapman, Pieter |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | When controlling an emerging outbreak of an infectious disease, it is essential to know the key epidemiological parameters, such as the basic reproduction number R0 and the control effort required to prevent a large outbreak. These parameters are estimated from the observed incidence of new cases and information about the infectious contact structures of the population in which the disease spreads. However, the relevant infectious contact structures for new, emerging infections are often unknown or hard to obtain. Here, we show that, for many common true underlying heterogeneous contact structures, the simplification to neglect such structures and instead assume that all contacts are made homogeneously in the whole population results in conservative estimates for R0 and the required control effort. This means that robust control policies can be planned during the early stages of an outbreak, using such conservative estimates of the required control effort. |
| first_indexed | 2025-11-14T19:42:16Z |
| format | Article |
| id | nottingham-40526 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:42:16Z |
| publishDate | 2016 |
| publisher | Royal Society, The |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-405262020-05-04T18:05:13Z https://eprints.nottingham.ac.uk/40526/ Inferring R0 in emerging epidemics: the effect of common population structure is small Trapman, Pieter Ball, Frank Dhersin, Jean-Stéphane Tran, Viet Chi Wallinga, Jacco Britton, Tom When controlling an emerging outbreak of an infectious disease, it is essential to know the key epidemiological parameters, such as the basic reproduction number R0 and the control effort required to prevent a large outbreak. These parameters are estimated from the observed incidence of new cases and information about the infectious contact structures of the population in which the disease spreads. However, the relevant infectious contact structures for new, emerging infections are often unknown or hard to obtain. Here, we show that, for many common true underlying heterogeneous contact structures, the simplification to neglect such structures and instead assume that all contacts are made homogeneously in the whole population results in conservative estimates for R0 and the required control effort. This means that robust control policies can be planned during the early stages of an outbreak, using such conservative estimates of the required control effort. Royal Society, The 2016-08-31 Article PeerReviewed Trapman, Pieter, Ball, Frank, Dhersin, Jean-Stéphane, Tran, Viet Chi, Wallinga, Jacco and Britton, Tom (2016) Inferring R0 in emerging epidemics: the effect of common population structure is small. Journal of the Royal Society Interface, 13 (121). 20160288/1-20160288/9. ISSN 1742-5689 Infectious disease modelling Emerging epidemics Population Structure Real-time spread R0 http://dx.doi.org/10.1098/rsif.2016.0288 doi:10.1098/rsif.2016.0288 doi:10.1098/rsif.2016.0288 |
| spellingShingle | Infectious disease modelling Emerging epidemics Population Structure Real-time spread R0 Trapman, Pieter Ball, Frank Dhersin, Jean-Stéphane Tran, Viet Chi Wallinga, Jacco Britton, Tom Inferring R0 in emerging epidemics: the effect of common population structure is small |
| title | Inferring R0 in emerging epidemics: the effect of common population structure is small |
| title_full | Inferring R0 in emerging epidemics: the effect of common population structure is small |
| title_fullStr | Inferring R0 in emerging epidemics: the effect of common population structure is small |
| title_full_unstemmed | Inferring R0 in emerging epidemics: the effect of common population structure is small |
| title_short | Inferring R0 in emerging epidemics: the effect of common population structure is small |
| title_sort | inferring r0 in emerging epidemics: the effect of common population structure is small |
| topic | Infectious disease modelling Emerging epidemics Population Structure Real-time spread R0 |
| url | https://eprints.nottingham.ac.uk/40526/ https://eprints.nottingham.ac.uk/40526/ https://eprints.nottingham.ac.uk/40526/ |