Statistical Modelling
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.
Data-Driven Insights
From statistical analysis to actionable recommendations
Current Projects
Our statistical modeling projects employ advanced analytical techniques to identify patterns, predict outcomes, and generate evidence for health decision-making and policy development.
Relationship Between Primary Healthcare Outcomes (Maternal Mortality, Neonatal Mortality) and Structural Readiness of Healthcare Services
Statistical analysis examining the correlation between structural readiness indicators of healthcare facilities and primary healthcare outcomes, focusing on maternal and neonatal mortality rates to inform healthcare infrastructure investments.
Excess Mortality During a Pandemic: A Time Series Analysis
Comprehensive time series statistical modeling to quantify excess mortality patterns during pandemic periods, analyzing temporal trends and identifying factors contributing to increased mortality beyond expected baseline levels.
Impact of Disruptions on Systematic Treatment Programs for Neglected Tropical Diseases: A Systematic Review
Systematic review and meta-analysis employing statistical methods to evaluate the impact of service disruptions on neglected tropical disease treatment programs, quantifying intervention effectiveness and identifying resilience factors.
Assessing Factors Associated with Child Mortality
Multivariable statistical modeling to identify and quantify risk factors associated with child mortality, utilizing advanced regression techniques to understand determinants and inform targeted intervention strategies.
Validation of the Diagnostic Potential of Using Rabies Rapid Diagnostic Test Kits as Part of Routine Animal Surveillance to Support Rabies Elimination: A Systematic Review and Meta-Analysis
Statistical meta-analysis evaluating the diagnostic accuracy and validation of rabies rapid diagnostic test kits in animal surveillance programs, providing evidence for their integration into rabies elimination strategies.
Comparison of Health Indicator Reporting from Routine Surveillance and Demographic Health Survey in Kenya
Statistical comparison and validation analysis of health indicators reported through routine surveillance systems versus demographic health surveys, assessing data quality, consistency, and reporting accuracy in Kenya.
Modelling Approaches to Inform Disease Burden and Control Strategies for Visceral Leishmaniasis: A Systematic Review
Systematic review and statistical synthesis of modeling approaches used to estimate visceral leishmaniasis disease burden and evaluate control strategies, providing methodological insights for disease control planning.
Mortality and Predictors of Mortality Among Covid-19 Patients in Kiambu County, Kenya
Statistical analysis of COVID-19 patient outcomes in Kiambu County, employing survival analysis and predictive modeling to identify mortality risk factors and develop clinical decision-support tools.
Time Series Analysis on the Impact of Seasonal Malaria Chemotherapy
Advanced time series statistical modeling to evaluate the impact of seasonal malaria chemotherapy interventions, analyzing temporal patterns and quantifying intervention effectiveness on malaria incidence reduction.