Multilevel modelling and malaria: a new method for an old disease.

Abstract:

BACKGROUND:Malaria is influenced by a web of individual and ecological factors, i.e. factors relating to people and relating to environment. For a long time analysing these factors concurrently has raised statistical problems. Multilevel modelling provides a new attractive solution, which is still uncommon in tropical medicine. METHODS:Using an actual data set of 3864 individuals from 38 villages of the Highland Madagascar, a two-level modelling process is presented. Individual malaria parasitaemia is modelled step by step according to age (individual factor), altitude, and DDT indoor house-spraying status (village factors). RESULTS:The hierarchical organization of a data set in levels, fixed and random effects, and cross-level interactions are considered. Accurate estimations of standard errors, impact of unknown or unmeasured variables quantified and accounted for through random effects, are the highlighted advantages of multilevel modelling. CONCLUSION:While not denying the importance of understanding an aetiological chain, the authors recommend an increased use of multilevel modelling, mainly to identify accurately ecological targets for public health policy.

journal_name

Int J Epidemiol

authors

Mauny F,Viel JF,Handschumacher P,Sellin B

doi

10.1093/ije/dyh274

keywords:

subject

Has Abstract

pub_date

2004-12-01 00:00:00

pages

1337-44

issue

6

eissn

0300-5771

issn

1464-3685

pii

dyh274

journal_volume

33

pub_type

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