The Center for Epidemiological Modelling and Analysis (CEMA)
at the University of Nairobi brings together a multidisciplinary consortium of epidemiologists, infectious disease specialists, clinicians, mathematicians, statisticians, computer scientists and data scientists using data-driven approaches to control infectious diseases and improve health in Kenya and the African Continent.
at the University of Nairobi brings together a multidisciplinary consortium of epidemiologists, infectious disease specialists, clinicians, mathematicians, statisticians, computer scientists and data scientists using data-driven approaches to control infectious diseases and improve health in Kenya and the African Continent.
We are involved in a range of clinical research projects, with the aim of generating local data that informs clinical practice and policy. Our clinical research work spans several areas: COVID-19 antimicrobial resistance, antimicrobial stewardship and HIV.
We employ mathematical modelling skills to understand the emergence, transmission, spread and control
of infectious diseases. The goal of our research is to gain insights from data and provide evidence that guides policies on prevention
and control of these infectious diseases to improve public health.
We use ecological niche modeling to predict a species' potential distribution by analyzing environmental conditions and species occurrence data.
This approach is important for mapping disease risk, understanding pathogen spread, and guiding public health interventions.
Leveraging on spatial data and advanced statistical techniques, we use geostatistical models to help identify disease hotspots, assess intervention coverage, and optimize resource allocation. These models integrate diverse data sources, including epidemiological surveys, remote sensing, and routine health system data, to generate high-resolution risk maps that support evidence-based decision-making.
We conduct economic evaluation of different healthcare strategies, and the cost effectiveness of strategies, to provide informed economic decisions. We also conduct health technology assessment of different healthcare benefit packages.
Hosted at CEMA, AM2NTD seeks to optimize and increase uptake of interventions within NTD endemic countries.
The network goal is to enhance the control and elimination of NTDs through use of insights from mathematical modelling to accelerate the achievement of NTD elimination targets in endemic countries.
By integrating expertise from public health, veterinary medicine, environmental science, and other disciplines, One Health aims to prevent and control diseases that spread between animals and humans (zoonoses) and ensure food safety. One Health promotes sustainable health solutions that protect both populations and the planet.
We employ statistical modeling to analyze health data, enabling us to identify patterns and predict outcomes. By leveraging advanced statistical techniques, we develop predictive models that inform health decision-making, optimize resource allocation, and improve patient care.
