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Plenary Session | Speakers
Dr. Fajar Adi Kusumo, M.Si.
Professor of Mathematics
Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada
Title of Talk: Mathematical Modeling of a Diffuse Large B-Cell Lymphoma
We consider a mathematical model of diffuse large B-cell lymphoma (DLBCL) in the germinal center and its microenvironment has been considered. The model is a five-dimensional system of first-order nonlinear ordinary differential equations that consists of interactions between centroblasts, centrocyts, plasmablasts, DLBCL cells, and effector cells. Our analysis focuses on understanding the long-term behavior of the DLBCL from a mathematical perspective. The cycle characteristics of DLBCL growth that can be used to detect the duration of the dormant states of the cancer cells and to choose the treatment methods are important to study. By using codimension-one and codimension-two bifurcations, we found Hopf bifurcations that show the appearance of the cycle and some bifurcations of the periodic solutions that are able to be used to characterize the cycle of the disease. In our case, by varying the carrying capacity parameter and the decay rate of effector cells due to the competition with DLBCL, the system undergoes a Hopf bifurcation and then is followed by a generalized Hopf bifurcation, a limit point bifurcation, and a branch point bifurcation. The occurrence of these bifurcations is crucial for understanding the role of effector cells in the regulation of the DLBCL cycle. Furthermore, the appearance of chaotic solutions reflects the irregularity of the system due to changes in initial conditions, highlighting potential uncertainty in the progression of DLBCL metastasis.
Dr. Stacey Smith?
Full Professor
Department of Mathematics, University of Ottawa
https://www.uottawa.ca/faculty-science/professors/stacey-smith
Title of Talk: A prevalence-based transmission model for the study of the epidemiology and control of soil-transmitted helminthiasis
Much effort has been devoted by the World Health Organization (WHO) to eliminate soil-transmitted helminth (STH) infections by 2030 using mass drug administration targeted at particular risk groups alongside the availability to access water, sanitation and hygiene services. The targets set by the WHO for the control of helminth infections are typically defined in terms of the prevalence of infection, whereas the standard formulation of STH transmission models typically describe dynamic changes in the mean-worm burden. We develop a prevalence-based deterministic model to investigate the transmission dynamics of soil- transmitted helminthiasis in humans, subject to continuous exposure to infection over time. We analytically determine local stability criteria for all equilibria and find bifurcation points. Our model predicts that STH infection will either be eliminated (if the initial prevalence value, y(0), is sufficiently small) or remain endemic (if y(0) is sufficiently large), with the two stable points of endemic infection and parasite eradication separated by a transmission break- point. Two special cases of the model are analysed: (1) the distribution of the STH parasites in the host population is highly aggregated following a negative binomial distribution, and (2) no density-dependent effects act on the parasite population. We find that disease extinction is always possible for Case (1), but it is not so for Case (2) if y(0) is sufficiently large. However, by introducing stochastic perturbation into the deterministic model, we discover that chance effects can lead to outcomes not predicted by the deterministic model alone, with outcomes highly dependent on the degree of worm clumping, k. Specifically, we show that if the reproduction number and clumping are sufficiently bounded, then stochasticity will cause the parasite to die out. It follows that control of soil-transmitted helminths will be more difficult if the worm distribution tends towards clumping.
Dr. Mark Jayson V. Cortez
Associate Professor
Institute of Mathematical Sciences, University of the Philippines Los Baños
Title of Talk: Simplifying Complex Reaction Networks through Delayed Dynamics
Reaction networks often involve components or intermediate steps that are difficult or impossible to observe directly, leading to models with latent dynamics. In this talk, I discuss how certain reaction networks with incomplete or unobserved components can be represented by stochastic models with explicit delays, while preserving the observable system dynamics. This delay-based representation provides a principled way to abridge complex networks while preserving their essential behavior.
I will first talk about the structural conditions under which latent dynamics can be faithfully captured by delays. I will then turn to the inverse problem, presenting methods for inferring the delay distribution directly from data using the reduced model. Finally, I will illustrate the practical utility of this framework through two applications: (i) quantifying cell-to-cell variability in a population from partial observations, and (ii) parameter inference in multi-step reaction models. Together, these examples demonstrate how delayed stochastic processes offer a powerful and interpretable approach for modeling and inference in complex biochemical systems with hidden structure.
Dr. Jacopo Grilli
Research Scientist
The Abdus Salam International Centre for Theoretical Physics
Title of Talk: The evolution of anticipation in microbial populations
Populations evolving in fluctuating environments face the fundamental challenge of balancing adaptation to current conditions against preparation for uncertain futures. Here, we study microbial evolution in partially predictable environments using proteome allocation models that capture the trade-off between growth rate and lag time during environmental transitions. We demonstrate that evolution drives populations toward an evolutionary stable allocation strategy that minimizes resource depletion time, thereby balancing faster growth with shorter adaptation delays. In environments with temporal structure, populations evolve to learn the statistical patterns of environmental transitions through proteome pre-allocation, with the evolved allocations reflecting the transition probabilities between conditions. Our framework reveals how microbial populations can extract and exploit environmental predictability without explicit neural computation, using the proteome as a distributed memory system that encodes environmental patterns. This work demonstrates how information-theoretic principles govern cellular resource allocation and provides a mechanistic foundation for understanding learning-like behavior in evolving biological systems.
Dr. Keisuke Ejima
Assistant Professor
Lee Kong Chian School of Medicine, Nanyang Technological University
Title of Talk: Why Antiviral Trials Succeed or Fail?: A Retrospective Power Analysis via Digital Twin Simulation
Clinical trials of antiviral drugs sometimes fail despite genuine efficacy. We developed a digital-twin modeling framework to retrospectively assess design and power in nirmatrelvir/ritonavir (Paxlovid) trials. From five randomized controlled trials identified through a systematic review, we recreated each study’s design—sample size, treatment timing, and participant characteristics—using viral-dynamics models calibrated to Shanghai clinical data. Simulations reproduced observed outcomes: trials reporting significant effects had estimated power >95%, whereas those with null or mixed findings showed power between 2% and 65%. These results highlight how trial design and participant mix critically influence success. Digital twins can guide future antiviral trials by optimizing enrolment timing, endpoints, and statistical power.
Dr. Wilfredo Campos
Professor
Division of Biological Sciences, College of Arts and Sciences, University of the Philippines Visayas
Title of Talk: The need for more mathematical approaches in understanding fisheries productivity
Fisheries provide over 50% of current daily meat requirements in the Philippines and is hence an important field of study. Because most of the stocks in the country’s major fishing grounds are overexploited, the need for quantitative information as well as reliable projections are important. Some of the work at the OceanBio Lab of the CAS at UP Visayas has involved substantial amounts of mathematical applications. The ecosystem trophic model ECOPATH and its expansion applications, for example, is largely biologist-friendly since this was designed for use in different aquatic ecosystems, and its applications have been extensively published. Other studies however, such as fisheries oceanography, need more in-depth understanding of features and processes to be more meaningful to fisheries managment. We have worked with the oceanography working group of the UP Marine Science Institute on several studies in the past but because of the extensive need for the expertise of this relatively small group, there were limited opportunities to further pursue our joint findings to improve our understanding of productivity and fisheries. These included (1) work where general circulation models were applied to simulate fish larval transport in various areas of the country to aid in designing ecologically functional networks of MPAs; (2) the potential role of mesoscale eddies in larval transport and subsequent stock recruitment, and more recently (3) the dynamics of seasonal hydrographic processes and their role in the spawning and dispersal of stocks of small pelagic fish in the area. Future work along these lines will benefit immensely through collaborations with the more mathematically adept, including geodetic engineers and physical oceanographers.
Dr. Farai Nyabadza
Professor
Department of Mathematics and Applied Mathematics, University of Johannesburg
Title of Talk: On the Concept of Digital Pathogens and the Psychosocial Epidemiology of Future Techno-Pandemics
The accelerating evolution of digital technologies has given rise to a new class of cognitive and affective disturbances herein conceptualized as Digital Pathogens (DPs). Unlike biological agents, DPs propagate through algorithmic exposure, neurocognitive entrainment, and behavioural reinforcement within hyperconnected digital ecosystems. This study identifies six high-risk entities Anxietovirus sapiens, Narcissomia proliferata, Echochamberis compulsiva, Contentitis viralis, Statitis contagiosa, and FOMOvirus persistens that are metaphorical constructs modelled after epidemiological and psychological analogues, each representing a distinct psychosocial infection pattern arising in hyper-digitalized societies. We give examples drawn from network models. The results indicate that these psychosocial contagions possess epidemic potential analogous to biological pathogens, with self-sustaining transmission dynamics mediated by digital feedback loops and algorithmic amplification. Without immediate and coordinated interventions in digital public health, humanity risks entering a phase of persistent psychosocial endemicity, characterized by chronic emotional dysregulation and cognitive overload at the population scale.
Dr. Ganna Rozhnova
Associate Professor
University Medical Center Utrecht in the Netherlands and the Faculty of Sciences at the University of Lisbon in Portugal
Title of Talk: Mathematical modelling of infectious diseases for public health
Mathematical modelling has become an essential tool in infectious disease epidemiology and public health. This talk will highlight the dynamic nature of infectious diseases—an aspect that clearly distinguishes them from conditions such as cardiovascular disease and cancer. In addition to examining the dynamics of respiratory infections such as SARS-CoV-2, the presentation will briefly compare them to sexually transmitted infections such as HIV. The talk aims to provide participants with an introduction to infectious disease modelling and data analysis, equipping them with the background needed to engage in modelling studies. Key concepts will include transmission dynamics, basic reproduction number, deterministic and stochastic models, heterogeneity, statistical inference, population dynamics, and vaccination. Illustrative examples will be drawn from recent research that informs public health policy in Europe.
Dr. Pia D. Bagamasbad
Professor & Director
National Institute of Molecular Biology and Biotechnology, University of the Philippines Diliman
Title of Talk: Disrupting the Rhythm: Establishing the Link Between Circadian Dysregulation and Hormone Signaling in Breast Cancer
Epidemiological studies have linked altered circadian rhythms due to irregular shift work, chronic jet lag, and heightened night-time light exposure to increased breast cancer (BCa) pathogenesis. Indeed, several clock genes participate in the gating of mitotic entry, regulation of DNA damage response, and epithelial-to-mesenchymal transition, thus impacting BCa etiology. In addition, maladaptive alterations to hormone signaling that is prevalent in BCa result in dysregulated expression of hormone-regulated clock genes, cascading onto the entire circadian molecular network owing to its interdependent nature. Hormone-dependent disruption of the local mammary clock ultimately results in the aberrant circadian control of proliferation, metabolism, and invasive capacity, further exacerbating BCa progression. In this study, we utilize a combination of in silico analysis of patient-derived tumors, gene expression analysis, and genetic and biochemical assays in breast epithelial models to identify key players at the intersection of hormone and circadian axis and the functional impact of this axis towards BCa progression.
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