Nigerian researcher develops groundbreaking epidemic model for vaccination strategies

A Nigerian public health researcher and mathematician, Omotomilola Jegede, has developed an advanced epidemic modelling tool that promises to revolutionize vaccination strategies in public health.

Her study, titled “On a Novel SVEIRS Markov Chain Epidemic Model with Multiple Discrete Delays and Infection Rates: Modeling and Sensitivity Analysis to Determine Vaccination Effects,” presents a sophisticated approach to managing infectious diseases through predictive modelling.

Published in Advances in Epidemiological Modeling and Control of Viruses, the research builds on the Susceptible-Vaccinated-Exposed-Infected-Recovered-Susceptible (SVEIRS) framework, enhancing it with a Markov chain model that incorporates multiple discrete delays and variable infection rates.

This innovative methodology accounts for critical factors such as immunity waning and infection latency, offering policymakers precise tools to design vaccination strategies tailored to specific population dynamics.

Jegede emphasised the relevance of her work for resource-constrained settings like Nigeria, where vaccination programs often encounter logistical and infrastructural hurdles.

“This model provides actionable data to optimize vaccination campaigns and effectively reduce the spread of infectious diseases,” she noted, highlighting its potential to transform health interventions in Sub-Saharan Africa and beyond.

“By integrating local factors such as climatic patterns, population mobility, and healthcare access, this model enhances our ability to identify disease hotspots, predict the impact of interventions like vaccination or sanitation improvements, and optimize resource allocation. It provides policymakers with actionable data to simulate disease dynamics, assess intervention effectiveness, and forecast resource needs with greater precision.”

She continued, “By increasing the accuracy of predictions, accounting for uncertainty, and deepening our understanding of disease transmission dynamics, this model empowers public health systems to implement evidence-based strategies tailored to local epidemiological and socio-environmental conditions. Whether addressing diseases like typhoid, measles, or influenza, this approach offers an invaluable tool for both research capacity building and policy support to mitigate the infectious disease burden in resource-constrained settings.”

“My overarching goal is to strengthen public health systems in Nigeria and across Africa by equipping them with innovative tools for managing infectious diseases,” Jegede added.

“This includes developing robust statistical frameworks to forecast resource needs, evaluate the cost-effectiveness of interventions, and improve health outcomes through data-driven strategies. By leveraging statistical methods to analyze complex disease patterns and incorporate population variability, my work aims to support policy development and ensure that vulnerable populations—particularly those in densely populated urban areas and underserved rural communities—are better protected against the impacts of infectious diseases. Ultimately, this research seeks to bridge critical gaps in epidemic preparedness and build resilient healthcare systems equipped to respond effectively to emerging health challenges.”

Dr. Emmanuel Dansu, Assistant Professor of Epidemiology at Tohoku University and a renowned expert in mathematical biology, described Jegede’s study as a “game-changer in epidemic modeling and public health strategy.”

He noted, “Omotomilola Jegede’s work bridges theoretical sophistication and practical application, offering an invaluable tool for real-world public health challenges. Her contributions are not only advancing the scientific community’s understanding but are also directly impacting vulnerable populations by providing innovative solutions to manage disease outbreaks.”

“Jegede’s work provides a groundbreaking solution for real-world public health challenges,” he remarked.

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