Rachel Cassidy is an honorary Research Fellow in Health Systems Modelling. She is leading the systems thinking workstream on the COSMIC (Using Computer Modelling to Optimise the Design of Health System Programmes) Project. The work stream focus is on using systems thinking approaches (causal loop diagrams, system dynamics modelling) to further understanding on pathways to impact for results-based financing programmes and design recommendations for future implementation.
Rachel holds a MSc in Epidemiology and a MSc in Bioinformatics and Theoretical Systems Biology from Imperial College, London. Rachel successfully defended her PhD thesis in March 2023 at LSHTM. The thesis describes a body of work where Rachel used causal loop diagrams and system dynamics modelling to investigate health system strengthening in low-income settings, with aim to optimise the effect of interventions that target maternal and child health service delivery.
Rachel holds a MSc in Epidemiology and a MSc in Bioinformatics and Theoretical Systems Biology from Imperial College, London. Rachel successfully defended her PhD thesis in March 2023 at LSHTM. The thesis describes a body of work where Rachel used causal loop diagrams and system dynamics modelling to investigate health system strengthening in low-income settings, with aim to optimise the effect of interventions that target maternal and child health service delivery.
Affiliations
Department of Global Health and Development
Faculty of Public Health and Policy
Centres
Antimicrobial Resistance Centre
Research
Research Area
Maternal health
Child health
Disease and Health Conditions
HIV/AIDS
Non-communicable diseases
Country
Tanzania
Zambia
Ethiopia
Kenya
Italy
United States of America
Selected Publications
How to do (or not to do)…using causal loop diagrams for health system research in low and middle-income settings.
2022
Health policy and planning
Mathematical modelling for health systems research: a systematic review of system dynamics and agent-based models.
2019
BMC Health Services Research
Mapping the Current and Future Noncommunicable Disease Burden in Kenya by Human Immunodeficiency Virus Status: A Modeling Study.
2019
Clinical Infectious Diseases
The potential impact of integrating services for the secondary prevention of cardiovascular outcomes into HIV care in Kenya: A mathematical modelling study
2018
AIDS 2018, 22nd International AIDS conference
Predictive Modelling Strategies to Understand Heterogeneous Manifestations of Asthma in Early Life
2018
2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA)
Epidemiological benefits of integrating services for the secondary prevention of cervical cancer into HIV care in Kenya: A mathematical modelling study
2018
AIDS 2018, 22nd International AIDS Conference
Quantifying the future clinical burden of an ageing HIV-positive population in the USA: a mathematical modelling study.
2016
Journal of the International AIDS Society