ArticlePLoS computational biology2020
An open source tool to infer epidemiological and immunological dynamics from serological data: serosolver.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 32 citations in OpenAlex.
- SARS-CoV-2 neutralising antibody profiles reveal variant specific antibody dynamics and regional differences in infection histories in Malawi.PLOS global public health · 2026Article
- Multiplex serology reveals age-specific immunodynamics of respiratory pathogens in the wake of the COVID-19 pandemic.Nature communications · 2025Article
- Emergence of SARS-CoV-2 Omicron lineages shifted antibody-mediated protection curves.iScience · 2025Article
- serojump: A Bayesian tool for inferring infection timing and antibody kinetics from longitudinal serological data.PLoS computational biology · 2025Article
- Multiplex serology reveals age-specific immunodynamics of endemic respiratory pathogens in the wake of the COVID-19 pandemic.medRxiv : the preprint server for health sciences · 2025Article
- RSero: A user-friendly R package to reconstruct pathogen circulation history from seroprevalence studies.PLoS computational biology · 2025Article
- Serodynamics: A primer and synthetic review of methods for epidemiological inference using serological data.Epidemics · 2024Review
- Reconstructed influenza A/H3N2 infection histories reveal variation in incidence and antibody dynamics over the life course.PLoS biology · 2024Article
- Navigating cross-reactivity and host species effects in a serological assay: A case study of the microscopic agglutination test for Leptospira serology.PLoS neglected tropical diseases · 2024Article
- Recent approaches in computational modelling for controlling pathogen threats.Life science alliance · 2024Review
- Reconstructed influenza A/H3N2 infection histories reveal variation in incidence and antibody dynamics over the life course.medRxiv : the preprint server for health sciences · 2024Article
- serosim: An R package for simulating serological data arising from vaccination, epidemiological and antibody kinetics processes.PLoS computational biology · 2023Article
- Estimation of Seasonal Influenza Attack Rates and Antibody Dynamics in Children Using Cross-Sectional Serological Data.The Journal of infectious diseases · 2022Article
- Cross-sectional cycle threshold values reflect epidemic dynamics of COVID-19 in Madagascar.Epidemics · 2022Article
- Birth cohort relative to an influenza A virus's antigenic cluster introduction drives patterns of children's antibody titers.PLoS pathogens · 2022Article
- A protocol for a longitudinal, observational cohort study of infection and exposure to zoonotic and vector-borne diseases across a land-use gradient in Sabah, Malaysian Borneo: a socio-ecological systems approach.Wellcome open research · 2022Article
- Model-based assessment of Chikungunya and O'nyong-nyong virus circulation in Mali in a serological cross-reactivity context.Nature communications · 2021Article
- Estimating epidemiologic dynamics from cross-sectional viral load distributions.Science (New York, N.Y.) · 2021Article
- A framework for surveillance of emerging pathogens at the human-animal interface: Pigs and coronaviruses as a case study.Preventive veterinary medicine · 2021Article
- Estimating epidemiologic dynamics from cross-sectional viral load distributions.medRxiv : the preprint server for health sciences · 2021Article
Corrections and comments
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Authors and funding
8 authors at 5 institutions in 2 countries.
Funding
Abstract
We present a flexible, open source R package designed to obtain biological and epidemiological insights from serological datasets. Characterising past exposures for multi-strain pathogens poses a specific statistical challenge: observed antibody responses measured in serological assays depend on multiple unobserved prior infections that produce cross-reactive antibody responses. We provide a general modelling framework to jointly infer infection histories and describe immune responses generated by these infections using antibody titres against current and historical strains. We do this by linking latent infection dynamics with a mechanistic model of antibody kinetics that generates expected antibody titres over time. Our aim is to provide a flexible package to identify infection histories that can be applied to a range of pathogens. We present two case studies to illustrate how our model can infer key immunological parameters, such as antibody titre boosting, waning and cross-reaction, as well as latent epidemiological processes such as attack rates and age-stratified infection risk.
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Registered trials
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.