Health Beliefs, Networks and Inference
Lead Research Organisation:
Imperial College London
Department Name: Mathematics
Abstract
This project explores how we can use partial information about the co-ordinates of individuals in a social space, partial information about which individuals share social connections and partial information about health-related behaviour to select parameters both for health belief-processes on graphs and to establish the form of the graph ensembles themselves. This will then allow us to design optimal interventions to tackle problematic health behaviour.
This research will be linked to the EPSRC Centre for the Mathematics of Precision Healthcare, the London School of Hygiene and Tropical Medicine
The project is linked to strategic themes in mathematical sciences, digital economy and healthcare technologies. Linked research areas are Artificial Intelligence technologies, Mathematical Biology, Operational Research, Statistics and applied probability.
This research will be linked to the EPSRC Centre for the Mathematics of Precision Healthcare, the London School of Hygiene and Tropical Medicine
The project is linked to strategic themes in mathematical sciences, digital economy and healthcare technologies. Linked research areas are Artificial Intelligence technologies, Mathematical Biology, Operational Research, Statistics and applied probability.
Organisations
People |
ORCID iD |
| Nick Jones (Primary Supervisor) | |
| Sahil Loomba (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/R513052/1 | 01/10/2018 | 30/09/2023 | |||
| 2129793 | Studentship | EP/R513052/1 | 01/10/2018 | 31/03/2022 | Sahil Loomba |
| Description | Sunbelt Conference 2020 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | The talk, which featured in the computational social science and social network theory track of the Sunbelt Conference, piqued interest amongst fellow researchers for presenting a novel methodology of learning statistics for social networks of entire societies using partially observed but widely available socio-demographic datasets. Questions posed after the talk indicated significant interest in seeing this methodology being applied to more countries. |
| Year(s) Of Engagement Activity | 2020 |