Journal of Theoretical Biology

The risk of highly pathogenic avian influenza infection to humans is challenging to estimate because many human avian influenza virus (AIV) infections are undetected as they may be asymptomatic, symptomatic but not tested, and as contact tracing is difficult because human-to-human spread is rare. We derive equations that consider the evolutionary mechanisms that give rise to pandemics and are parameterized to be consistent with records of past pandemics. We estimate that thousands of human AIV i...

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...

This study presents a theoretical and mathematical framework for understanding the dynamical behavior of infectious disease spread using a compartmental modeling approach. The proposed model incorporates memory effects to capture temporal dependencies that are not adequately represented by classical formulations. Qualitative analysis is employed to investigate the stability properties of the system and the role of key mechanisms in shaping long term dynamics. Publicly available surveillance info...

Cervical cancer remains a significant cause of mortality and economic burden, particularly in developing countries with low rates of human papillomavirus (HPV) vaccination and screening. To address this, we present a mathematical model for controlling cervical cancer by integrating strategic HPV vaccination, screening and treatment. The population is divided into seven compartment: susceptible, vaccinated, infected with HPV, screened, cervical cancer, under treatment, and recovered. The models w...

Biological and behavioral differences between genders influence infectious disease dynamics. Yet, most epidemiological models overlook these aspects in favor of age stratification alone. Here, we systematically evaluate the impact of incorporating gender-specific features into an age-structured epidemic compartmental model, calibrated to COVID-19 mortality data from the second wave in Italy (Autumn 2020-Winter 2021). We develop eight model versions representing different combinations of three da...

BackgroundCOVID-19 epidemic waves display pronounced temporal structure in mortality, with substantial variation in wave shape, duration, and asymmetry across regions. These dynamics are commonly interpreted within transmission-based compartmental models, in which epidemic growth is driven by interactions between infectious and susceptible individuals. However, several empirical features of observed mortality curves, including prolonged declines, asymmetric wave shapes, and coherent temporal pat...

Nosocomial transmission of respiratory infections poses a major threat to patient safety, while also affecting healthcare workers (HCW) health, generating substantial costs for hospitals. These infections spread through both close-proximity interactions at short distances, and via aerosols that remain suspended in the air, enabling long-range transmission. The relative contribution of each transmission route is pathogen-dependent, and evidence to distinguish them remains scarce. Here, we propose...

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...

Human African Trypanosomiasis (HAT) remains a persistent public health threat in sub-Saharan Africa, with transmission dynamics tightly coupled to the ecology and physiology of its tsetse fly vector. Despite growing evidence that temperature strongly modulates vector survival, development, and biting behavior, most existing transmission models assume static environmental conditions. We develop a model for HAT that incorporates temperature-dependent vector recruitment, mortality, and biting rates...

BackgroundThe COVID-19 pandemic was strongly shaped by the interaction between population behaviour and transmission dynamics. Standard mathematical models do not account for this interaction, however. Objectivewe tested whether adding a mechanistic representation of population behavioural dynamics improves the ability of a mathematical model to explain and predict COVID-19 pandemic waves. MethodsWe compared a standard Susceptible-Infected-Recovered (SIR) model to a variant (SIRx) with a mecha...

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 ...

Measles resurgence in high-income countries that previously achieved elimination reveals a critical surveillance failure: current systems rely on county-level aggregates that obscure fine-scale clustering where outbreaks originate. We assembled the nationwide multiscale vaccination database spanning 45 US states (2013-2025), encompassing over 50,000 schools, 13,000 districts, and 3,000 counties. We developed a gravity-based transmission framework and demonstrate that school-level effective repro...

Mathematical models of infectious disease dynamics are routinely fitted to surveillance data to estimate epidemiological parameters and inform public health decisions. Such data are typically discrete and noisy, but before attempting estimation, it is essential to ask whether the model structure itself permits unique parameter identification at least under perfect (continuous, noise-free) observations. This mathematical property of a model with respect to observation(s), known as structural iden...

Most models for infectious disease spread simplify contact heterogeneity by assuming constant rates within a week. However, empirical studies show clear variation, such as reduced workplace contacts on weekends. In this work, we investigate the effects of daily variation in workplace contacts on the spread of respiratory infections using the individual-based framework GEMS (German Epidemic Micro-Simulation System) with a synthetic population of 5 million individuals. We compare a baseline scenar...

Decision-making by governments during disease outbreaks is increasingly reliant on large-scale pathogen genomics and detailed individual-level data. We use 293,841 SARS-CoV-2 genomes collected in Denmark, between September 1st 2020 and December 31st 2021, and combine these with comprehensive individual-level data on settings, including households, schools, workplaces and family relationships, to infer plausible transmission pathways. Next, we use the plausible transmission pathways to assess the...

We describe a fast, noninvasive, low-cost survey method designed to understand the mode of transmission of an emerging pathogen. It is inspired from the standard household prevalence survey consisting in sampling households and counting the total number of people infected in each household, but refines it with the aim of improving diagnosis and estimating more parameters of the model of intra-household transmission. The survey was carried out in May-June 2020, during part of the first national ...

Collective interaction of individuals in various settings is crucial for exposure to infections, encompassing complex viral interplay and amplifying infectious risk through phenomena such as social reinforcement, clustering and superspreading events, during the COVID-19 pandemic. However, standard epidemic models often inadequately capture such heterogeneity, overlooking the higher-order social structural. Spatiotemporal variation in transmission, an essential feature of the pandemic, remains po...

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...

During an outbreak, infectious disease can spread among populations through host movement, potentially fueling local outbreaks with their own epidemiological dynamics. However, it is difficult to know how often infections between populations are transmitted by diseased travelers infecting healthy residents when abroad, rather than by diseased residents infecting healthy travelers, who later return home with the new pathogen. In this paper, we introduce a phylogeographic model where pathogens spr...

BackgroundAccurately capturing social contact data is essential for developing effective mathematical models to forecast disease trends and evaluate interventions. There are limited population-based data of social contacts in the United States (US) which limits our ability to accurately model infectious disease transmission. MethodsTo fill in this gap, we conducted a staggered longitudinal cohort study in metropolitan Atlanta, Georgia, USA. We aimed to characterize contact patterns and examine ...