Mathematical Biosciences

This paper looked at the exploration of Lassa fever transmission dynamics through stochastic models which yielded valuable insights into the interplay of factors influencing the probability of extinction and persistence of the virus within a population. By embracing the inherent randomness and variability in the system, the model provided a more realistic representation of the complex ecological and epidemiological dynamics of Lassa fever. We developed the deterministic model using a system of o...

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...

In this research, we create a new fractional-order SEIHRD framework to examine how the Nipah virus moves from one species to another (zoonotic spillover) and how it later spreads throughout a community (via contact with one another) or in a hospital or isolation situation (via entering into a hospital or being placed under quarantine). We used the fractional-derivative formulation of the SEIHRD model to demonstrate memory-based effects related to the progression of an infection and also reflect ...

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...

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...

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...

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 ...

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...

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...

To characterize tuberculosis transmission and assess the impact of important interventions, a data-driven SEITR TB model is created. The potential for disease persistence has been calculated using the basic reproduction number. To determine the factors most significantly affecting the spread of tuberculosis, stability and sensitivity analyses are conducted. Strengthened treatment measures and optimized distancing significantly lower infection levels, according to numerical simulations. The Least...

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...

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...

Infectious diseases and chronic diseases are two major fields in epidemiology that have traditionally been studied separately because of their distinct etiologies and modeling methods. Infectious disease data are typically collected at an aggregated level and analyzed using compartmental models, most commonly the susceptible (S), infectious (I), and recovered (R) (SIR) model, whereas chronic disease data are usually collected at the individual level and analyzed using multi-state survival models...

BackgroundMillions of people worldwide suffer from thyroid dysfunction, and especially hypothyroidism, which is a prevalent endocrine disorder contributing extensively to systemic and metabolic illness. In hypothyroidism, triiodothyronine (T3) and thyroxine (T4), thyroid hormones that control metabolism in several organ systems, are insufficiently secreted. ObjectivesThe objective of this study was to determine the effect of anti-thyroid antibodies on thyroid function in Bangladeshi newly diagn...

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...

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...

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...

BackgroundGait adaptability, defined as the ability to adjust walking performance to environmental challenges, likely reflects complex interactions among the central nervous system (CNS) and other physiological systems, however, the drivers of lower gait adaptability in older adults are poorly understood. MethodsWe applied a Bayesian network framework to quantify multisystem interactions contributing to percent change in gait speed (%GSC) on transition from even to uneven surface in 159 older a...