High-resolution epidemic simulation using within-host infection and contact data
- Background: Recent epidemics have entailed global discussions on revamping epidemic control and prevention approaches. A general consensus is that all sources of data should be embraced to improve epidemic preparedness. As a disease transmission is inherently governed by individual-level responses, pathogen dynamics within infected hosts posit high potentials to inform population-level phenomena. We propose a multiscale approach showing that individual dynamics were able to reproduce population-level observations. Methods: Using experimental data, we formulated mathematical models of pathogen infection dynamics from which we simulated mechanistically its transmission parameters. The models were then embedded in our implementation of an age-specific contact network that allows to express individual differences relevant to the transmission processes. This approach is illustrated with an example of Ebola virus (EBOV). Results: The results showed that a within-host infection model can reproduce EBOV’s transmission parameters obtained from population data. At the same time, population age-structure, contact distribution and patterns can be expressed using network generating algorithm. This framework opens a vast opportunity to investigate individual roles of factors involved in the epidemic processes. Estimating EBOV’s reproduction number revealed a heterogeneous pattern among age-groups, prompting cautions on estimates unadjusted for contact pattern. Assessments of mass vaccination strategies showed that vaccination conducted in a time window from five months before to one week after the start of an epidemic appeared to strongly reduce epidemic size. Noticeably, compared to a non-intervention scenario, a low critical vaccination coverage of 33% cannot ensure epidemic extinction but could reduce the number of cases by ten to hundred times as well as lessen the case-fatality rate. Conclusions: Experimental data on the within-host infection have been able to capture upfront key transmission parameters of a pathogen; the applications of this approach will give us more time to prepare for potential epidemics. The population of interest in epidemic assessments could be modelled with an age-specific contact network without exhaustive amount of data. Further assessments and adaptations for different pathogens and scenarios to explore multilevel aspects in infectious diseases epidemics are underway.
Author: | Van Kinh NguyenORCiDGND, Rafael Mikolajczyk, Esteban Abelardo Hernandez-VargasORCiDGND |
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URN: | urn:nbn:de:hebis:30:3-468950 |
DOI: | https://doi.org/10.1186/s12889-018-5709-x |
ISSN: | 1471-2458 |
Pubmed Id: | https://pubmed.ncbi.nlm.nih.gov/30016958 |
Parent Title (English): | BMC public health |
Publisher: | BioMed Central |
Place of publication: | London |
Document Type: | Article |
Language: | English |
Year of Completion: | 2018 |
Date of first Publication: | 2018/07/17 |
Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
Release Date: | 2018/08/02 |
Tag: | Age-structure; Contact network; Ebola virus; Epidemic; High-resolution; Simulation; Within-host infection |
Volume: | 18 |
Issue: | 1, Art. 886 |
Page Number: | 11 |
First Page: | 1 |
Last Page: | 11 |
Note: | Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
HeBIS-PPN: | 435647857 |
Institutes: | Wissenschaftliche Zentren und koordinierte Programme / Frankfurt Institute for Advanced Studies (FIAS) |
Dewey Decimal Classification: | 6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit |
Sammlungen: | Universitätspublikationen |
Licence (German): | Creative Commons - Namensnennung 4.0 |