Small Area Estimation for Disease Prevalence Mapping.
Int Stat Rev
; 88(2): 398-418, 2020 Aug.
Article
em En
| MEDLINE
| ID: mdl-36081593
ABSTRACT
Small area estimation (SAE) entails estimating characteristics of interest for domains, often geographical areas, in which there may be few or no samples available. SAE has a long history and a wide variety of methods have been suggested, from a bewildering range of philosophical standpoints. We describe design-based and model-based approaches and models that are specified at the area-level and at the unit-level, focusing on health applications and fully Bayesian spatial models. The use of auxiliary information is a key ingredient for successful inference when response data are sparse and we discuss a number of approaches that allow the inclusion of covariate data. SAE for HIV prevalence, using data collected from a Demographic Health Survey in Malawi in 2015-2016, is used to illustrate a number of techniques. The potential use of SAE techniques for outcomes related to COVID-19 is discussed.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prevalence_studies
/
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Int Stat Rev
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Estados Unidos