Margarita Pons-Salort

Enterovirus D68 (EV-D68) is a common cause of mild respiratory illness in children but is also linked to acute flaccid myelitis (AFM), a rare and severe neurological condition which can result in permanent paralysis. Tracking EV-D68 transmission is difficult because symptoms overlap with other common childhood illnesses, making case reporting unreliable. As a result, the burden of EV-D68 transmission remains poorly understood, particularly prior to the first widely recognised outbreak in 2014. Phylodynamic approaches offer a powerful alternative to case-based surveillance, inferring epidemiological parameters directly from pathogen genetic sequences. Here we show, using a birth-death-sampling phylodynamic model applied to publicly available EV-D68 sequences from the 1990s to 2023 collected in Europe and North America, that seasonal EV-D68 transmission was well established long before the 2014 outbreak brought the virus to widespread attention. Furthermore, we show that AFM case burden is strongly associated with the transmission dynamics of a specific EV-D68 clade, clade B, an association not seen for clades A and D. These findings suggest that clade-specific biological differences drive AFM risk, with important implications for surveillance prioritisation and the timing of future burden of neurological disease.

Serological assays remain the standard experimental approach for estimating the cumulative incidence of a pathogen and monitoring population immunity. The predominant approach for analysing serum titration data from virus neutralisation assays uses a nearly century-old interpolation-based method which neglects inherent imperfections in the assay and produces estimates with no measure of uncertainty. We introduce a two-part Bayesian modelling framework to estimate the underlying antibody concentrations in the raw serum samples taken from serosurveyed individuals, to improve the interpretation of serological data over age. First, we develop a mechanistic Bayesian model for serum antibody titration data that estimates latent antibody concentrations while accounting for assay variability and quantifying uncertainty. Second, we propagate this uncertainty into an age-structured serocatalytic model by integrating over posterior draws of individual antibody concentrations, allowing joint inference on latent serostate membership, force of infection, and serological waning rate. We use this framework to explore the dynamics of infection and immunity for three enterovirus serotypes: enteroviruses A71 (EV-A71) and D68 (EV-D68) and coxsackievirus A6 (CVA6). These serotypes are leading causes of outbreaks of severe respiratory illness and hand, foot, and mouth disease. Applying these approaches to three cross-sectional serosurveys, we estimated consistently higher and more persistent antibody concentrations throughout life for EV-D68 compared to EV-A71 and CVA6. Our analysis suggests that the proportion of recently infected individuals (i.e. individuals with high estimated antibody concentration levels given their age) peaks around 25% by age 7 years for both EV-A71 and CVA6 before gradually declining with age. In contrast, for EV-D68 the inferred proportion of the population in the infected state exceeds 50% by age 9 years and continues to grow with age. We also estimate that EV-D68 antibody concentration levels are higher than those of the other two serotypes, with the force of infection estimated to be highest in early childhood and declining more gradually with age than for EV-A71 and CVA6. These estimates are different to previous estimates found in the literature. Our inferential framework uncovers the wide-ranging variation in antibody levels that are often obscured by conventional endpoint titre estimation methods. We demonstrate that our framework can infer infection rates without relying on predetermined seropositivity cut-offs and without making explicit assumptions of virus-specific infection mechanisms.

Hand, foot and mouth disease (HFMD) is endemic in Asia-Pacific. There is geographic variability in the timing of HFMD outbreaks throughout the year across the region, and seasonality becomes less clear towards tropical regions. We used syndromic HFMD case surveillance data from 2009 to 2019 (N = 354,769 cases) to characterise the spatio-temporal dynamics of HFMD in Malaysia, which has a tropical climate, and identify factors associated with transmission. Despite the absence of regular annual seasonal patterns of incidence, HFMD epidemics were highly synchronised across districts within Peninsular and East Malaysia, but less so between the two regions. Median estimates of the state-level daily effective reproduction number (Rt) ranged from 0.47 to 1.54. Meteorological factors were found to have a small effect on HFMD transmission compared to the depletion of susceptibles (as a proxy for population immunity) and school closures, likely due to the low seasonal weather variability across the year. Studies using wider spatial scales covering a diversity of climate regions are needed to identify meteorological factors determining the timing of HFMD epidemics across Asia-Pacific countries.

Despite concerted global vaccination efforts, wild poliovirus remains endemic in two countries in 2024, Pakistan and Afghanistan. This study uses phylogeographic analysis of poliovirus genetic and epidemiological data from clinical and wastewater surveillance to identify the causes of poliovirus persistence and routes of spread over the last decade (2012 to 2023). Poliovirus genetic diversity declined after 2020, with one of two major genetic clusters dying out, and recent detections are now closely related genetically. High-risk and hard-to-access regions have sustained polio transmission over the past decade, even when interrupted elsewhere. Karachi, one of the most densely populated cities globally, has acted as a hub for the amplification and spread of poliovirus to other regions, many of which we show to be dead-end for onwards transmission despite frequent virus detection. Phylogenetic analysis has long been central to the polio surveillance network, and advancing the approaches used can provide critical epidemiological insights to accelerate eradication efforts.

Population-based serological surveys are a key tool in epidemiology to characterize the level of population immunity and reconstruct the past circulation of pathogens. A variety of serocatalytic models have been developed to estimate the force of infection (FOI) (i.e., the rate at which susceptible individuals become infected) from age-stratified seroprevalence data. However, few tool currently exists to easily implement, combine, and compare these models. Here, we introduce an R package, Rsero, that implements a series of serocatalytic models and estimates the FOI from age-stratified seroprevalence data using Bayesian methods. The package also contains a series of features to perform model comparison and visualise model fit. We introduce new serocatalytic models of successive outbreaks and extend existing models of seroreversion to any transmission model. The different features of the package are illustrated with simulated and real-life data. We show we can identify the correct epidemiological scenario and recover model parameters in different epidemiological settings. We also show how the package can support serosurvey study design in a variety of epidemic situations. This package provides a standard framework to epidemiologists and modellers to study the dynamics of past pathogen circulation from cross-sectional serological survey data.

Vaccination timeliness is often not considered among standard performance indicators of routine vaccination programmes, such as vaccination coverage, yet quantifying vaccination delay could inform policies to promote in-time vaccination and help design vaccination schedules. Here, we analysed vaccination timeliness for 24 routine childhood immunisations for 54 countries. We extracted individual vaccination status and timing from Demographic and Health Surveys data from 54 countries with surveys from 2010 onwards. Individual data was used to estimate age at vaccination for <5 year-old children. Recommended age of vaccination for each country and vaccine was compared to the age at vaccination to determine vaccination delay. The evolution of vaccination delay over time was described using estimates from different birth cohorts. To identify socio-demographic indicators associated with delayed vaccination, we used multivariable Cox regression models with country as random effect and estimated the Hazard Ratio for vaccination with each vaccine-dose for each week post recommended vaccination age. Vaccine coverage at the recommended age was highest for birth and first doses (e.g. 50.5% BCG, 18.5% DTP-D1) and lowest for later doses (e.g. 5.5% DTP-D3, 16.3% MCV-D1, 8.2% MCV-D2). Median delay was lowest for birth doses, e.g. BCG (1 week (IQR: 0 to 4)), and it increased with later doses in vaccination courses: 1 (0, 4) week for DTP-D1 versus 4 (2, 9) weeks for DTP-D3. Although the median delay for each vaccine-dose remained largely constant over time, the range of delay estimates moderately decreased. Children living in rural areas, their countries’ poorer wealth quintiles and whose mothers had no formal education were more likely to received delayed vaccinations. Although we report most children are vaccinated within the recommended age window, we found little reduction on routine immunisation delays over the last decade and that children from deprived socioeconomic backgrounds are more likely to receive delayed vaccinations.

Enterovirus A71 (EV-A71) and coxsackievirus A6 (CVA6) primarily cause hand, foot and mouth disease and have emerged to cause potential fatal neurological and systemic manifestations. However, limited surveillance data collected through passive surveillance systems hampers characterization of their epidemiological dynamics. We fit a series of catalytic models to age-stratified seroprevalence data for EV-A71 and CVA6 collected in England at three time points (2006, 2011 and 2017) to estimate the force of infection (FOI) over time and assess possible changes in transmission. For both serotypes, model comparison does not support the occurrence of important changes in transmission over the study period, and we find that a declining risk of infection with age and / or seroreversion are needed to explain the seroprevalence data. Furthermore, we provide evidence that the increased number of reports of CVA6 during 2006–2017 is unlikely to be explained by changes in surveillance. Therefore, we hypothesize that the increased number of CVA6 cases observed since 2011 must be explained by increased virus pathogenicity. Further studies of seroprevalence data from other countries would allow to confirm this. Our results underscore the value of seroprevalence data to unravel changes in the circulation dynamics of pathogens with weak surveillance systems and large number of asymptomatic infections.

Despite concerted global vaccination efforts, wild poliovirus remains endemic in two countries in 2024, Pakistan and Afghanistan. This study uses phylogeographic analysis of poliovirus genetic and epidemiological data from clinical and wastewater surveillance to identify the causes of poliovirus persistence and routes of spread over the last decade (2012 to 2023). Poliovirus genetic diversity declined post-2020, with the die-out of one of two major genetic clusters and recent detections are now close genetic relatives. We find that high-risk and hard-to-access regions have been key to persistent polio transmission over the past decade, supporting transmission when it had stopped elsewhere. Karachi, one of the most densely populated cities globally, has acted as a major hub for the amplification and spread of poliovirus to other regions, many of which we show to be dead-end for onwards transmission despite frequent virus detection. This information has been used to guide polio vaccination and surveillance.