PLOS Computational Biology

1The timeliness of infectious disease surveillance systems largely determines the speed at which mitigation interventions may be implemented. However, it is unclear how surveillance timeliness evolves during a pandemic with changing government policies, testing tools, and population-level infection and immunity landscapes. Here, we adapt an agent-based model for COVID-19 transmission to explore the timeliness of the surveillance signals obtained from polymerase chain reaction (PCR) and rapid ant...

Wastewater is increasingly being recognized as an important data stream that can contribute to infectious disease surveillance and forecasting. With this recognition, a growing number of statistical inference approaches are being developed to use wastewater data to provide quantitative insights into epidemiological dynamics. However, few existing approaches have allowed for systematic integration of data streams for inference, for example by combining case incidence data and/or serological data ...

The COVID-19 pandemic has presented severe challenges in understanding and predicting the spread of infectious diseases, necessitating innovative approaches beyond traditional epidemiological models. This study introduces an advanced method for automated model discovery using the Sparse Identification of Nonlinear Dynamics (SINDy) algorithm, leveraging a dataset from the COVID-19 outbreak in Thuringia, Germany, encompassing over 400,000 patient records and vaccination data. By analysing this dat...

Biological fitness quantifies the efficiency and selective advantage of pathogens and hosts in their bilateral interaction. Key questions--such as how much more infectious an emerging variant is compared with its predecessor, or how much protection vaccination offers relative to no vaccination--require fitness to be measured systematically, in real time, and ideally beyond controlled laboratory settings. We propose an approach that infers biological fitness from mostly non-biological data on inf...

Wastewater-based epidemiology provides a low-cost, scalable view of community infection dynamics, but converting these signals into actionable epidemiological insights remains difficult. Mechanistic models offer interpretability, yet, assumptions such as a constant transmission rate limit realism over long simulation horizons and heterogeneous settings. We present a susceptible-exposed-infectious-recovered (SEIR) universal differential equation (UDE) that links wastewater viral loads to case cou...

Background: Human-to-human transmission of pathogens fundamentally depends on interactions among infectious and susceptible individuals, yet traditional population-scale models often overlook the stochastic, behaviour-driven, and highly heterogeneous nature of these interactions. Methods: Here, we develop a large-scale actor-based model capturing early epidemic dynamics of a novel respiratory pathogen on dynamic contact networks. We build these networks upon explicitly integrating detailed demog...

We introduce PerTexP (Pertussis Time Exploration), an interactive modelling tool designed to investigate pertussis transmission dynamics and to support the evaluation of vaccination strategies and short-term projections. PerTexP allows users to explore and compare maternal, infant, and non-infant booster vaccination scenarios and to assess their potential impact on disease transmission, with a particular focus on the Italian epidemiological context. The tool is based on a discrete-time, stage-st...

BackgroundEpidemic forecasting research often assesses ensembles and their component models using probabilistic scoring rules. Quantifying how individual models affect ensemble performance is challenging, particularly across multiple targets and spatial scales. MethodsWe present Winter 2024-25 forecasts of Influenza and COVID-19 hospital admissions in England and conduct a retrospective simulation using the operational component models. Forecasts were scored using the per capita weighted interv...

Human contact network structure fundamentally shapes infectious disease transmission and control. Most COVID-19 epidemic models assumed approximately homogeneous contact patterns, yet real-world networks are highly heterogeneous. We analysed 59,585 daily non-household contact reports from Germanys COVIMOD study (2020-2021) using a novel heavy-tail regression framework. Throughout the pandemic, contact distributions remained strongly heavy-tailed despite substantial non-pharmaceutical interventio...

We present results from the second season of Influcast, a multi-model collaborative forecasting hub focused on influenza in Italy. During the 2024/25 winter season, Influcast collected one-to four-week-ahead probabilistic forecasts of influenza-like illness (ILI) incidence alongside influenza A and B ILI+ incidence signals. New ILI+ targets were constructed integrating syndromic surveillance data with virological detections collected weekly by the Italian National Institute of Health. Forecasts ...

BackgroundVaccines can prevent severe disease by preventing infection or by reducing progression among those who become infected. Vaccine effectiveness against progression given infection is often used to quantify this second mechanism, but it conditions on infection, which is itself affected by vaccination. As a result, this estimand lacks a clear causal interpretation and may behave non-intuitively over time. MethodsWe introduce a conceptual framework that models protection against infection ...

A concern in infectious disease modelling is how accurately population mixing is incorporated, as it shapes the type and frequency of contacts through which infection spreads, and consequently, estimated intervention effectiveness. Although synthesizing mixing patterns from diary-based surveys is an established framework, geographical information is poorly or sparsely captured. Here we propose a generalizable workflow to quantify geographical connectivity from job registry data covering over 8 m...

Pathogenic organisms are typically thought to be constrained by a tradeoff between the rate and duration of transmission, an assumption that underpins a considerable body of evolutionary theory. Here we test for a transmission-duration tradeoff using detailed historical malaria infection data from an era prior to widespread use of antibiotics when humans were deliberately infected with malaria parasites as treatment for neurosyphilis (malariatherapy). These time series follow individual human in...

Visceral leishmaniasis (VL) is considerably more severe among individuals infected with human immunodeficiency virus (HIV), leading to higher parasite loads, frequent relapse, and increased mortality. To examine the epidemiological interaction between the two diseases, we develop a comprehensive VL-HIV co-infection model that incorporates transmission pathways, treatment effects, and relapse dynamics. The model is parameterized using real-time data from Bihar, India, including monthly VL-only an...

Nipah virus (NiV) is a sporadic yet extremely deadly zoonotic pathogen, with reported case fatality rates of 40%-75% in impacted areas. Prolonged incubation, documented relapse, and delayed-onset encephalitis following apparent recovery indicate that NiV dynamics are influenced by intricate temporal processes. However, mechanistic contributions of these processes to epidemic persistence remain poorly understood. In this study, we develop and analyze a delay differential equation model for NiV tr...

The prospective design of vaccine efficacy trials for deployment in outbreaks requires advance consideration of plausible outbreak scenarios, anticipated vaccine characteristics, and logistical and ethical constraints. As part of CEPIs 100 Days Mission to accelerate vaccine development against a novel Disease X, we evaluated trial designs for a hypothetical Nipah-X outbreak. We assumed Nipah-X would share key features with Nipah, including high case fatality rates and substantial super-spreading...

BackgroundRoutine immunization (RI) is widely used to increase population immunity against measles. In low-resource settings, achieving immunity goals using RI alone has proved challenging and supplemental immunization activities (SIAs), large community-based vaccination campaigns conducted every few years, have been used to close immunity gaps. Although effective at covering the population unreached by RI and boosting the population immunity, SIAs are labor-intensive and expensive, allowing for...

With significant population fractions in many societies who refuse vaccines, it is important to reconsider how vaccination is incorporated into compartmental epidemiology models. It is still most common to apply the vaccination rate to the entire class of susceptibles, rather than to use the more realistic assumption that the vaccination rate function should depend only on the population of susceptibles who are willing and able to receive a vaccination. This study uses a simple generic disease m...

Epigenetic clocks estimate biological age from DNA methylation patterns at CpG sites, providing robust predictions of mortality and morbidity risk. "Blue zones"--regions of exceptional longevity--offer a unique opportunity to investigate how biological aging diverges from chronological age. However, standard clocks are typically trained on large, heterogeneous datasets, reflecting average population trends rather than region-specific dynamics. Using data from the Costa Rican Longevity and Health...

Infection with pnuemococcus bacteria is generally mild but can be more severe in the young and elderly, causing invasive pneumococcal disease (IPD) and community-acquired pneumonia (CAP). Although paediatric pneumococcal conjugate vaccine (PCV) programmes and elderly pneumococcal polysaccharide vaccine (PPV) programmes have reduced cases, we estimate that pneumococcal infection still leads to direct health care costs of around {pound}68M and approximately 16 thousand QALY losses in England per y...