Repository logo
 

Bayesian multistate modelling of incomplete chronic disease burden data.

Published version
Peer-reviewed

Repository DOI


Loading...
Thumbnail Image

Type

Article

Change log

Authors

Jackson, Christopher  ORCID logo  https://orcid.org/0000-0002-6656-8913
Zapata-Diomedi, Belen 
Woodcock, James 

Abstract

A widely-used model for determining the long-term health impacts of public health interventions, often called a "multistate lifetable", requires estimates of incidence, case fatality, and sometimes also remission rates, for multiple diseases by age and gender. Generally, direct data on both incidence and case fatality are not available in every disease and setting. For example, we may know population mortality and prevalence rather than case fatality and incidence. This paper presents Bayesian continuous-time multistate models for estimating transition rates between disease states based on incomplete data. This builds on previous methods by using a formal statistical model with transparent data-generating assumptions, while providing accessible software as an R package. Rates for people of different ages and areas can be related flexibly through splines or hierarchical models. Previous methods are also extended to allow age-specific trends through calendar time. The model is used to estimate case fatality for multiple diseases in the city regions of England, based on incidence, prevalence and mortality data from the Global Burden of Disease study. The estimates can be used to inform health impact models relating to those diseases and areas. Different assumptions about rates are compared, and we check the influence of different data sources.

Description

Keywords

stat.AP, stat.AP

Journal Title

J R Stat Soc Ser A Stat Soc

Conference Name

Journal ISSN

0964-1998
1467-985X

Volume Title

Publisher

Oxford University Press (OUP)
Sponsorship
European Commission Horizon 2020 (H2020) ERC (817754)
Medical Research Council (MR/P02663X/1)

Version History

Now showing 1 - 2 of 2
VersionDateSummary
2*
2023-10-11 14:17:04
Published version added
2022-12-21 00:31:17
* Selected version