title: IMPACT: A generalisable system for simulating public health interventions.
abstract: Populations are under-served by local health policies and management of resources, partly because of a lack of realistically complex models to enable a wide range of potential options to be appraised. Rising computing power coupled with advances in machine learning and healthcare information now enables such models to be constructed and executed. However, such models are not generally accessible to public health practitioners because they do not have the requisite technical knowledge or skills. This paper presents a system for creating, executing and analyzing the results of simulated public health and healthcare policy interventions, which is more accessible and usable by modellers and policy-makers alike.
authors.affiliation: NW Institute Bio-Health Informatics, School of Community Based Medicine, University of Manchester, UK.
authors.forename: Iain
authors.initials: I
authors.lastname: Buchan
authors.forename: John
authors.initials: J
authors.lastname: Ainsworth
authors.forename: Emma
authors.initials: E
authors.lastname: Carruthers
authors.forename: Philip
authors.initials: P
authors.lastname: Couch
authors.forename: Martin
authors.initials: M
authors.lastname: O'Flaherty
authors.forename: Duncan
authors.initials: D
authors.lastname: Smith
authors.forename: Richard
authors.initials: R
authors.lastname: Williams
authors.forename: Simon
authors.initials: S
authors.lastname: Capewell
mesh_terms: D003198:Computer Simulation; D003324:Coronary Artery Disease / Q000401:mortality* / Q000628:therapy*; D006801:Humans; D008962:Models, Theoretical; D015995:Prevalence; D016016:Proportional Hazards Models; D040442:Public Health Informatics / Q000379:methods*; D016019:Survival Analysis; D015996:Survival Rate; D006113:United Kingdom / Q000453:epidemiology