Focus: Understanding fundamental characteristics of infectious disease transmission and developing accessible software tools for outbreak analysis.
Transmission Dynamics
Disease Investigations
Epidemiology of Scabies
Scabies is a contagious skin disease caused by the Sarcoptes scabiei mite, affecting over 400 million people annually worldwide. Despite its global burden, fundamental epidemiological characteristics had remained poorly described. Using data from Dutch sentinel surveillance (2011–2023), this work produced the first published estimates of the mean serial interval of scabies infection and time-varying reproduction numbers, revealing increasing transmission in recent years.
Related software: mitey Tools page →
Mpox Transmission
Following the 2022 mpox outbreak in non-endemic regions, transmission characteristics were investigated using detailed exposure histories from cases in the Netherlands. The work produced serial interval estimates from identified transmission pairs and found evidence of presymptomatic transmission, informing isolation guidance and contact tracing protocols.
Miura, F., Backer, J. A., van Rijckevorsel, G., et al. Time Scales of Human Mpox Transmission in The Netherlands. J Infect Dis. 2023. Read paper →
COVID-19
Real-time estimation of SARS-CoV-2 transmission dynamics during the pandemic, including methods for appropriately smoothing prevalence data to produce reliable estimates of growth rate and reproduction number.
Eales, O., Ainslie, K. E. C., Walters, C. E., et al. Appropriately smoothing prevalence data to inform estimates of growth rate and reproduction number. Epidemics 2022. Read paper →
Related software: pika Tools page →
Influenza
Serological data provide a powerful lens for reconstructing past infection histories and estimating immunity. serosolver uses a Bayesian framework to infer individual-level infection histories and antibody kinetics from haemagglutination inhibition (HI) titres.
Hay, J. A., Minter, A., Ainslie, K. E. C., et al. An open source tool to infer epidemiological and immunological dynamics from serological data: serosolver. PLOS Computational Biology 2020. Read paper →
Related software: serosolver Tools page →
Delay Distributions & Event-Time Methods
Linking Epidemiological Delays
Epidemiological delays — latent periods, incubation periods, generation intervals, and serial intervals — are typically estimated independently, even though they arise from the same underlying within-host infection process. This work develops a stochastic, within-host-informed event-time framework that treats these delays as coupled outcomes of a shared biological process, yielding internally consistent, mechanistically interpretable estimates. Applied to SARS-CoV-2 and mpox data, the framework outperformed conventional lognormal models in several settings and identified shorter generation intervals for Omicron than Delta.
Jamieson, N., Park, S. W., Ainslie, K. E. C., et al. A within-host-informed event-time framework linking epidemiological delay distributions. medRxiv 2026 (preprint). Read preprint →
Tools
mitey
A lightweight R package with methods to estimate serial intervals and time-varying reproduction numbers from infectious disease outbreak data, developed alongside the scabies epidemiology work below.
Links: GitHub Scabies Vignette Software page → Related research →
serosolver
An open source R package using a Bayesian framework to infer individual-level infection histories and antibody kinetics from serological (HI titre) data.
pika
A lightweight R package for estimating the optimal lag and rolling correlation between two time series, used to compare epidemic signals such as case counts and mobility or policy indicators.
isolatr
An R package for simulating COVID-19 transmission dynamics during quarantine and evaluating the effectiveness of different testing strategies. isolatr models household transmission structures, vaccination status, and realistic test sensitivity curves across Test-Trace-Isolate-Quarantine (TTIQ) scenarios, using an Infection Potential in Quarantine (IPq) metric to compare testing frequencies and quarantine durations.
Links: GitHub Software page →