Bulletin of Mathematical Biology

Virtual clinical trials (VCTs) hold significant promise for improving the drug development process, yet their predictive reliability depends critically on design decisions that remain poorly understood. This study examines how model complexity influences VCT outcomes, as well as how the choice of prior parameter distributions and virtual patient inclusion criteria affects those outcomes. Using oncolytic virotherapy treatment of murine tumors as a case study, we compared three mathematical models...

Assessing epidemic risk following pathogen introduction is crucial in infectious disease epidemiology. Risk is commonly encoded through reproduction ratios, which underpin operational decision-making. In spatially structured populations, both local and cross-community transmission shape epidemic trends, a feature that standard reproduction ratios fail to capture simultaneously. Here, we use multitype branching processes to define the outbreak reproduction ratio Rob, a reformulation applicable ac...

In a recent article in Science, Shenhar et al. report that human life span heritability reaches [~]55% after removing "extrinsic" mortality, roughly seven-fold higher than recent large pedigree estimates. This conclusion rests on classifying deaths from infections and accidents as environmental noise independent of genetics. This premise is biologically untenable: susceptibility to severe infection is substantially heritable, with adoptee studies showing relative risks exceeding 5 for infection ...

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...

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...

Plasmodium vivax malaria control requires addressing unique challenges such as latent hypnozoite reservoirs, relapse-driven persistence, and strong climatic modulation of transmission. This study introduces a novel, integrative modeling-optimization framework that couples a relapse- and climate-aware transmission model with structural identifiablity analysis and metaheuristic optimization to design adaptive intervention strategies. Using surveillance data from Seoul, Korea, we calibrated key par...

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...

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...

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...

This study is based on the design and analysis of a novel age- and dose-structured model for assessing the population-level impact of the recently-approved R21/Matrix-M malaria vaccine (which is administered in three doses followed by a booster dose) on controlling the spread of malaria in children under five in Burkina Faso. While the current malaria vaccination program in Burkina Faso prioritizes children 0-3 years of age (Group 1 in our model), we also assessed a hypothetical scenario where c...

Schistosomiasis is a neglected parasitic disease caused by various trematode species of the genus Schistosoma for which 251 million people needed treatment in 2021. Many mathematical models of Schistosoma mansoni transmission incorporate the effect of chemoprophylaxis on parasite burden within the human host. While praziquantel is the most commonly implemented pharmaceutical used to control schistosomiasis, due to its applicability over several species and its negligible side effects, it is not ...

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...

Using the example of an unknown emerging disease with simple SIR (susceptible-infectious-recovered) dynamics, we show that an efficacy randomized clinical trial (RCT) for a vaccine can be misleading when it comes to the cost-effectiveness of that vaccine. An RCT is more likely to demonstrate efficacy with a high confidence level if it is carried out during the peak of the outbreak. However, in this scenario, the vaccine also has a higher chance of being approved too late to be cost-effective. A ...

Violence against women is sustained not only by individual behavior but also by social norms that legitimize coercion and control. While attitudes justifying intimate-partner violence have been extensively documented in large-scale household surveys, they are rarely analyzed as structured, predictable population-level phenomena. Here, we model the continuous prevalence of violence-justifying attitudes across 70 countries and demographic subgroups using country-resolved supervised machine learnin...

We propose a simulator-driven imitation learning framework for sequential decision making in head and neck cancer (HNC) treatment. Our method, Superhuman Policy Gradient Optimization (SPGO), integrates inverse reinforcement learning principles with policy gradient updates to derive three-stage treatment policies directly from recorded physician decisions. It leverages a pre-trained clinical simulator--combining a variational autoencoder and gradient boosting models--to generate complete, tempora...

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...

BackgroundViral interference, in which infection with one pathogen reduces susceptibility to another, may influence respiratory virus dynamics. Inference from surveillance data is complicated by time-varying testing behavior that can induce correlated detection patterns independent of biological interaction. MethodsWe developed a multi-pathogen renewal model augmented with a ratio penalty that constrains interference estimates to be consistent with observed log-odds ratios of pathogen positivit...

1Parameter estimation is often necessary to inform transmission models of infectious diseases. This estimation requires choosing an observation model that links the model outputs to the observed data. Although potentially consequential, this choice has received little attention in the literature. Here, we aimed to compare eight observation models, including common distributions such as the Poisson, binomial, negative binomial, and normal (equivalent to least-squares estimation). Using Bayesian i...

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...