Dr Rebecca Baggaley MA MSc PhD

Assistant Professor of Modelling for Evaluation

Background

I am a Lecturer in Modelling for Evaluation, working in the Maternal and Newborn Health Group of the Department of Infectious Disease Epidemiology. I am an infectious disease epidemiologist and mathematical modeller, and  I employ mathematical models and statistical analyses to study the transmission dynamics of infectious diseases and the impact of maternal and reproductive health interventions.

I gained a BA in Natural Sciences at the University of Cambridge before studying for a MSc in Control of Infectious Diseases here at the London School of Hygiene and Tropical Medicine (LSHTM). I went on to research HIV epidemiology and mathematical modelling during my PhD in the Department of Infectious Disease Epidemiology, Imperial College London. Since then I have worked modelling HIV/STIs during my Sir Henry Wellcome Postdoctoral Research Fellowship held at Imperial College, as well as working as a health economist on a wide range of medical conditions during my time in industry. I returned to LSHTM in 2014 to resume my research in maternal and reproductive health.

Affiliation

Centres

Teaching

I am keen to recruit PhD students to pursue research projects relating to application of mathematical modelling methods in maternal and reproductive health.

Research

I have recently become a Co-Investigator of the Maternal healthcare markets Evaluation Team (MET) as leader of the Harmonised Indicators and Modelling Project. This is one of six MET projects aiming to evaluate the impact of the MSD for Mothers Initiative (MfM, http://merckformothers.com/), which aims to invest $500 million into preventing maternal mortality over the next ten years. I am responsible for liaising between the various MfM projects regarding the collection of appropriate indicator data with which to evaluate their interventions, and where possible, to standardise these indicators across comparable projects. I am evaluating models that predict the health impacts of maternal, reproductive and child health-related interventions in order to design appropriate modelling frameworks. I will assess the feasibility and appropriate methods to predict the health impacts of MfM interventions. 

I am also involved with a second MET project, the evaluation of a new contraceptive supply chain in Senegal, for which I am developing models to estimate the impact of improvements in stock availability, in terms of unintended pregnancies and maternal deaths averted. For this project, I have also constructed an individual based simulation model to evaluate the sustainability of the new supply chain model as it rolls out from urban to rural regions. The model simulates each woman of reproductive age in union in the catchment area of a dispensary point, and her contraceptive-taking behaviour including choice of method, dependent on stock availability at the dispensary. 

I have also constructed an individual based simulation model of women giving birth in health facilities, reflecting a hypothetical district in a low-income country, in order to explore crowding levels in labour and maternity wards in resource-poor settings. The model is parameterised based on assumptions made by the World Health Organisation (World Health Report 2005, available at: www.who.int/whr/2005/en/index.html), to explore what the implications of these assumptions are. I am currently providing context to this analysis by reparameterising the model using health facility census data from Zanzibar, Tanzania.

As well as maternal health, I am retaining my previous research interests in modelling of HIV interventions. I am currently using transmission modelling to perform a cost-effectiveness analysis of a general-practice based rapid HIV screening intervention in the UK, which has involved the construction of a dynamic model simulating secondary HIV transmission events. I am also working on a deterministic, compartment model reflecting incidence of diagnosed Multiple Myeloma in the US and transitions of patients through lines of treatment, used to estimate numbers of patients on each line of therapy in order to assess the number of patients who could benefit from new therapies and their budgetary impact. 

Research areas

  • Disease control
  • Economic evaluation
  • Impact evaluation
  • Maternal health
  • Modelling
  • Public health
  • Reproductive health
  • Sexual health
  • Systematic reviews

Disciplines

  • Epidemiology
  • Mathematical modelling
  • Statistics

Disease and Health Conditions

  • HIV/AIDS
  • Herpesviruses
  • Human papillomavirus (HPV)
  • Infectious disease
  • Lymphatic filariasis
  • Mental health
  • Neglected Tropical Diseases (NTDs)
  • Sexually transmitted infection

Regions

  • European Union
  • North America
  • South Asia
  • Sub-Saharan Africa (developing only)

Countries

  • United Kingdom

Other interests

  • Cost Effectiveness Analysis
  • Family Planning
  • HIV
  • Health Economics
  • Maternal And Child Health
  • Meta-analysis
  • Population modelling
  • Sexual and Reproductive Health
  • Supply Chain
  • Systematic review
  • Transmission
  • Women's health
  • epidemiology
  • mathematical modeling
Back to top