Evidence map›Paper›PMID 28584172›Full record

ReviewPhilosophical transactions of the Royal Society of London. Series B, Biological sciences2017

Integrative modelling for One Health: pattern, process and participation.

I Scoones, K Jones, G Lo Iacono, D W Redding, A Wilkinson, J L N Wood

Abstract readReview
In one paragraph

Review in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

33 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  7. Towards a 'people and nature' paradigm for biodiversity and infectious disease.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025
    Review
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  12. Observational
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

I ScoonesSTEPS Centre, Institute of Development Studies, University of Sussex, Brighton BN1 9RE, UK i.scoones@ids.ac.uk.ORCID http://orcid.org/0000-0001-8547-4464
K JonesCentre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, Gower Street, London WC1E 6BT, UK.ORCID http://orcid.org/0000-0001-5231-3293
G Lo IaconoDepartment of Veterinary Medicine, Disease Dynamics Unit, University of Cambridge, Madingley Road, Cambridge CB3 0ES, UK.ORCID http://orcid.org/0000-0002-6150-2843
D W ReddingCentre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, Gower Street, London WC1E 6BT, UK.
A WilkinsonSTEPS Centre, Institute of Development Studies, University of Sussex, Brighton BN1 9RE, UK.ORCID http://orcid.org/0000-0002-2114-7023
J L N WoodDepartment of Veterinary Medicine, Disease Dynamics Unit, University of Cambridge, Madingley Road, Cambridge CB3 0ES, UK.

Funding

Medical Research Council MR/R02491X/1
6 · The paper itself

Abstract

This paper argues for an integrative modelling approach for understanding zoonoses disease dynamics, combining process, pattern and participatory models. Each type of modelling provides important insights, but all are limited. Combining these in a '3P' approach offers the opportunity for a productive conversation between modelling efforts, contributing to a 'One Health' agenda. The aim is not to come up with a composite model, but seek synergies between perspectives, encouraging cross-disciplinary interactions. We illustrate our argument with cases from Africa, and in particular from our work on Ebola virus and Lassa fever virus. Combining process-based compartmental models with macroecological data offers a spatial perspective on potential disease impacts. However, without insights from the ground, the 'black box' of transmission dynamics, so crucial to model assumptions, may not be fully understood. We show how participatory modelling and ethnographic research of Ebola and Lassa fever can reveal social roles, unsafe practices, mobility and movement and temporal changes in livelihoods. Together with longer-term dynamics of change in societies and ecologies, all can be important in explaining disease transmission, and provide important complementary insights to other modelling efforts. An integrative modelling approach therefore can offer help to improve disease control efforts and public health responses.This article is part of the themed issue 'One Health for a changing world: zoonoses, ecosystems and human well-being'.

Indexed as

Models, TheoreticalOne HealthAfricaAnimalsHemorrhagic Fever, EbolaHumansLassa FeverZoonosesAfricaEbolaLassa fevermodellingOne Healthzoonoses

Identifiers

PMID28584172
PMCPMC5468689

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.