A1 Journal article (refereed)
A mechanistic underpinning for sigmoid dose-dependent infection (2017)

Anttila, J., Mikonranta, L., Ketola, T., Kaitala, V., Laakso, J., & Ruokolainen, L. (2017). A mechanistic underpinning for sigmoid dose-dependent infection. Oikos, 126(6), 910-916. https://doi.org/10.1111/oik.03242

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Publication details

All authors or editors: Anttila, Jani; Mikonranta, Lauri; Ketola, Tarmo; Kaitala, Veijo; Laakso, Jouni; Ruokolainen, Lasse

Journal or series: Oikos

ISSN: 0030-1299

eISSN: 1600-0706

Publication year: 2017

Volume: 126

Issue number: 6

Pages range: 910-916

Publisher: Wiley-Blackwell Publishing, Inc.; Nordic Society Oikos

Publication country: United Kingdom

Publication language: English

DOI: https://doi.org/10.1111/oik.03242

Research data link: http://dx.doi.org/10.5061/dryad.8t8dh

Publication open access: Not open

Publication channel open access:


Theoretical models of environmentally transmitted diseases often assume that transmission is a constant process, which scales linearly with pathogen dose. Here we question the applicability of such an assumption and propose a sigmoidal form for the pathogens infectivity response. In our formulation, this response arises under two assumptions: 1) multiple invasion events are required for a successful pathogen infection and 2) the host invasion state is reversible. The first assumption reduces pathogen infection rates at low pathogen doses, while the second assumption, due to host immune function, leads to a saturating infection rate at high doses. The derived pathogen dose:infection rate relationship was tested against an experimental data on host mortality rates across different pathogen doses. Compared to two simpler alternatives, the sigmoidal function gave a better fit to patterns in host mortality rate (process), as well as host mortality (endpoint). Combining these alternative approaches made us more confident to conclude that the proposed model for disease transmission is theoretically sound, provides a good description of the data at hand, and is likely to be useful in developing more reliable models for infectious diseases.

Keywords: infections; communicable diseases

Free keywords: environmentally transmitted diseases

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Ministry reporting: Yes

Reporting Year: 2017

JUFO rating: 2

Last updated on 2021-09-06 at 19:27