Statistics, data & modelling
MORU uses mathematical, epidemiological, economics and statistical models to support investigations into the transmission, control and elimination of tropical diseases in the Greater Mekong Sub-Region (GMS). MORU's active policy engagement with governments, stakeholders and communities helps us identify the right research questions, implement pragmatic, data driven solutions and evaluate them in the field for impact and effectiveness.
We work to build capacity in SE Asia and in the institutions/programmes of regional collaborators by training new modellers and data analysts. Working with other disciplines and using data from national control programmes, MORU MAEMOD researchers use statistics, data and modelling to provide pragmatic high tech solutions to regional health problems, including neglected tropical diseases, drug resistant bacterial infections and malaria elimination. We explore the cost effectiveness of new interventions and their clinical, social and ethical implications, and encourage the development of health innovations by finding ways to reduce the lead-in time between scientific results and implementation.
Based in the Clinical Trials Support Group (CTSG), our Statistics Team leads in advising researchers on the design aspects of the different types of studies. This includes determining the appropriate sample sizes needed to answer research hypotheses; writing statistical sections of the study protocols and Statistical analysis Plans (SAPs); reviewing methodological aspects of study protocols; merging complex datasets from several sources, performing data analysis and interpretation of the results; providing statistical clinics and detailed statistical consultations to MORU researchers; provision of both basic and advanced statistical training to researchers in MORU and its satellite Units.
Members of the team sit on Data and Safety Monitoring Boards (DSMBs) both as a study statistician for MORU studies as well as a DSMB Statistician for studies from the other institutions. In addition, we perform research in statistical methodology relevant to medical research studies.