How can fictional worlds become laboratories for real scientific discovery?
Scientific research often reaches the public through journal articles, conference presentations, and technical reports. These publications communicate discoveries with precision and rigor, yet they rarely capture another equally important part of science—the journey of ideas.
This website is a Narrative Scholarly Archive of the research project "Mathematical Modeling and Computer Simulation of Fictional Epidemiological Events." It preserves not only the project's mathematical models and research outputs, but also the scientific questions, computational thinking, and evolving ideas that shaped the work from its conception to its continuing reinterpretation.
Rather than presenting the research solely as a collection of completed results, this archive invites readers to explore how scientific understanding develops—from curiosity, to abstraction, to mathematical formulation, to computer simulation, and ultimately to new questions that extend beyond the original project.
At first glance, fictional epidemiological events may appear far removed from real scientific inquiry.
Yet fictional worlds offer something remarkably valuable to computational scientists: controlled environments in which complex ideas can be explored without the practical, ethical, or logistical constraints often encountered in real-world systems.
In this project, fictional narratives involving vampires, zombies, cybernetic aliens, and Philippine folklore served as computational laboratories. These imaginative settings made it possible to investigate general principles of contagion, intervention, recovery, and resilience—principles that later proved applicable to public health, computational social science, organizational systems, and other recoverable human systems.
Fiction, in this context, was never the destination.
It was the laboratory.
This archive presents the research through several complementary perspectives.
The motivation behind studying fictional epidemiological events.
The scientific questions that guided the investigation.
The conceptual framework used to organize the research.
The progressive development of mathematical models.
The computational thinking that transformed ideas into simulations.
The historical research outputs produced during the funded project.
The emerging interpretations that became visible only through later reflection.
Together, these perspectives document not only what the project accomplished, but also how its ideas continue to evolve.
Unlike a conventional research website, this archive is organized as a journey through the life cycle of a scientific idea.
Rather than presenting only the final outcomes of research, each section reveals a different stage in the development of scientific knowledge—from the first spark of curiosity to the community of researchers and institutions that made the work possible.
Readers may begin anywhere, but those who follow the sequence will experience the gradual evolution of the research itself.
Overview - Why does this research matter?
Rationale - Why was this question worth asking?
Background - What ideas came before it?
Objectives - What scientific questions guided the investigation?
Modeling Framework - How were those questions organized into a coherent research strategy?
Mathematical Models - How did scientific ideas become mathematics and computation?
Outputs - What knowledge emerged from the research?
Research Team - Who carried the ideas forward through collaboration and mentorship?
Research Support - What institutional support enabled the research?
References - Whose ideas helped make this research possible?
Although each page can be read independently, together they form a continuous narrative that illustrates how scientific ideas are conceived, developed, communicated, supported, and ultimately passed on to future generations.
Although this project formally concluded with the completion of its funded activities, scientific ideas rarely end when projects do.
Preparing this archive revealed conceptual relationships that were not explicitly recognized during the original research, including the progressive abstraction of the mathematical models, their applicability to recoverable human systems, and the computational thinking that connects the entire body of work.
This archive therefore serves two complementary purposes.
It preserves the historical record of a completed research project.
It also invites future students, researchers, educators, and practitioners to reinterpret, extend, and apply its ideas in new domains.
In this sense, every page is both a record of past work and an invitation to future discovery.
Science is often remembered for its answers.
In reality, it advances because people learn to ask better questions.
Throughout this archive, you will encounter Guide Questions that encourage you to pause, reflect, and explore the ideas behind each section. They are not examinations with predetermined answers. Instead, they are invitations to think as scientists do: by observing patterns, forming abstractions, constructing models, and asking new questions that extend beyond what is already known.
Whether you are a high school student discovering mathematical modeling for the first time, a university student developing computational skills, an educator searching for new ways to communicate science, or a researcher exploring complex systems, this archive invites you to participate in that process of discovery.
The mathematical models presented here were inspired by fictional epidemiological events, but the ideas they embody reach far beyond those original narratives.
They illustrate how computational thinking enables us to understand complex systems, how mathematical abstraction reveals patterns that transcend individual applications, and how scientific knowledge continues to mature through reflection and reinterpretation.
Ultimately, this archive is not about vampires, zombies, aliens, or folklore.
It is about the enduring human pursuit of understanding complex systems through curiosity, imagination, mathematics, and computation.
Scientific discoveries begin with questions. Mathematical models give those questions structure. Computational thinking transforms them into understanding. Narrative preserves them so that future generations can continue the journey.