By Moses Chisunka

The Epidemiology & Biostatistics Club recently engaged with the Center for Epidemiological Modelling and Analysis (CEMA) in an insightful session aimed at exploring the practical applications of epidemiology, biostatistics, and disease modeling. This session provided club members with firsthand exposure to the real-world impact of epidemiological research, highlighting how mathematical models, data analysis, and statistical tools contribute to public health decision-making.

The session also emphasized the growing role of technology in epidemiology, with CEMA experts shedding light on how Python, R, and other statistical software are revolutionizing the way health data is analyzed and interpreted. This engagement was not only a learning experience but also a motivation for the club to integrate more practical, skill-based learning opportunities into future activities.

One of the core discussions focused on how epidemiological models are used to predict and control disease outbreaks. CEMA researchers provided an overview of the different types of epidemiological models (deterministic vs. stochastic models), how these models were applied in COVID-19 response, malaria control, and other disease outbreaks, as well as the importance of data-driven decision-making in public health interventions. The club members were particularly interested in how mathematical models are built, validated, and used by policymakers to guide health interventions.

The discussion then shifted to the technical tools that epidemiologists and biostatisticians use in research. CEMA experts emphasized the importance of learning Python & R for statistical computing, data visualization, and predictive modeling, SPSS & Stata for biostatistical analysis and public health research, and geospatial Mapping Tools used in tracking the spread of diseases and identifying high-risk areas. This part of the session highlighted the need to incorporate more software training sessions in our future club activities.

The CEMA team also provided guidance on career paths in epidemiology and biostatistics,

sharing insights on internships and mentorship programs available for students interested in epidemiology, the skills required for careers in disease modeling, outbreak response, and health research, as well as how students can actively participate in ongoing research projects and collaborate with institutions like CEMA.

The club members had the chance to ask questions about how to gain research experience, publish studies, and apply epidemiology in different fields, including global health, policy,

and clinical research.

At the end of the session, the students understood that practical skills are essential and that it is not enough to learn epidemiology in theory, students must develop hands-on skills in data analysis and disease modeling. They also learnt that technology is transforming epidemiology therefore, modern epidemiologists must be proficient in programming languages like Python and statistical tools like R to remain relevant in the field. Additionally, the club members were informed that collaboration is key and that engaging with research institutions, government agencies, and NGOs is crucial for real-world application of epidemiological research. Lastly students realized that they must take initiative. CEMA experts encouraged us to start small research projects, publish findings, and actively seek mentorship opportunities.

The engagement with CEMA was a transformative experience for the Epidemiology & Biostatistics Club marking the beginning of a new chapter for the club, as it looks forward to implementing these initiatives learnt.