Evidence map›Paper›PMID 38126066›Full record

ArticleRoyal Society open science2023

A mixed-method approach to determining contact matrices in the Cox's Bazar refugee settlement.

Joseph Walker, Joseph Aylett-Bullock, Difu Shi, Allen Gidraf Kahindo Maina, Egmond Samir Evers, Sandra Harlass, Frank Krauss

Open access · goldAbstract read
In one paragraph

Article in Royal Society open science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 48% of its field
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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Infectious Disease Modelling · 2024
    Review
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

7 authors at 4 institutions in 3 countries.

Joseph WalkerInstitute for Data Science, Durham, UK.ORCID 0000-0001-8734-8293
Joseph Aylett-BullockInstitute for Data Science, Durham, UK.ORCID 0000-0001-7551-3423
Difu ShiInstitute for Data Science, Durham, UK.
Allen Gidraf Kahindo MainaUNHCR Public Health Unit, Cox's Bazar, Bangladesh.
Egmond Samir EversWHO Headquarters, Geneva, Switzerland.
Sandra HarlassUNHCR Public Health Unit, Geneva, Switzerland.
Frank KraussInstitute for Data Science, Durham, UK.ORCID 0000-0001-5043-3099
Durham University · GBOffice of the United Nations High Commissioner for Refugees · CHUnited Nations · USWorld Health Organization · CH

Funding

World Health Organization 001
6 · The paper itself

Abstract

Contact matrices are an important ingredient in age-structured epidemic models to inform the simulated spread of the disease between subgroups of the population. These matrices are generally derived using resource-intensive diary-based surveys and few exist in the Global South or tailored to vulnerable populations. In particular, no contact matrices exist for refugee settlements-locations under-served by epidemic models in general. In this paper, we present a novel, mixed-method approach for deriving contact matrices in populations, which combines a lightweight, rapidly deployable survey with an agent-based model of the population informed by census and behavioural data. We use this method to derive the first set of contact matrices for the Cox's Bazar refugee settlement in Bangladesh. To validate our approach, we apply it to the UK population and compare our derived matrices with well-known contact matrices collected using traditional methods. Our findings demonstrate that our mixed-method approach successfully addresses some of the challenges faced by traditional and agent-based approaches to deriving contact matrices. It also shows potential for implementation in resource-constrained environments. This work therefore contributes to a broader aim of developing new methods and mechanisms of data collection for modelling disease spread in refugee and internally displaced person (IDP) settlements and better serving these vulnerable communities.

Indexed as

contact matricesindividual-based modelsimulation

Identifiers

PMID38126066
PMCPMC10731328
OpenAlexW4390009328

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.