Evidence map›Paper›PMID 40696544›Full record

ArticleStatistics in medicine2025

The Mathematics of Serocatalytic Models With Applications to Public Health Data.

Everlyn Kamau, Junjie Chen, Sumali Bajaj, Nicolás Torres, Richard Creswell, Jaime A Pavlich-Mariscal, Christl Donnelly, Zulma Cucunubá, Ben Lambert

Abstract read
In one paragraph

Article in Statistics in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Modelling the risk of West Nile virus infection in seven European countries from published serological and case notification data, 2008 to 2022.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2026
    Pooled it
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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

9 authors.

Everlyn KamauFrancis I. Proctor Foundation, University of California San Francisco, San Francisco, California, USA.ORCID https://orcid.org/0000-0003-4285-2255
Junjie ChenDepartment of Statistics & Pandemic Sciences Institute, University of Oxford, Oxford, UK.
Sumali BajajDepartment of Biology & Department of Statistics & Merton College & Pandemic Sciences Institute, University of Oxford, Oxford, UK.
Nicolás TorresInstituto de Salud Pública, Pontificia Universidad Javeriana, Bogota, Colombia.
Richard CreswellMelbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
Jaime A Pavlich-MariscalFacultad de Ingeniería, Pontificia Universidad Javeriana, Bogota, Colombia.ORCID https://orcid.org/0000-0002-3892-6680
Christl DonnellyDepartment of Statistics & Pandemic Sciences Institute, University of Oxford, Oxford, UK.
Zulma CucunubáInstituto de Salud Pública, Pontificia Universidad Javeriana, Bogota, Colombia.
Ben LambertDepartment of Statistics & Pandemic Sciences Institute, University of Oxford, Oxford, UK.

Funding

International Development Research CenterOxford-Moh Family Foundation Global Health ScholarshipTRACE-LAC project 109848-002UKHSA, University of Oxford, University of Liverpool, and Liverpool School of Tropical Medicine NIHR200907University of Oxford NE/S007474/1
6 · The paper itself

Abstract

Serocatalytic models are powerful tools which can be used to infer historical infection patterns from age-structured serological surveys. These surveys are especially useful when disease surveillance is limited and have an important role to play in providing a ground truth gauge of infection burden. In this tutorial, we consider a wide range of serocatalytic models to generate epidemiological insights. With mathematical analysis, we explore the properties and intuition behind these models and include applications to real data for a range of pathogens and epidemiological scenarios. We also include practical steps and code in R and Stan for interested learners to build experience with this modeling framework. Our work highlights the usefulness of serocatalytic models and shows that accounting for the epidemiological context is crucial when using these models to understand infectious disease epidemiology.

Indexed as

Epidemiological ModelsModels, StatisticalPublic HealthCommunicable DiseasesHumans

Identifiers

PMID40696544
PMCPMC12284347

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.