| Titre : | Multilevel modelling and malaria : a new method for an old disease. (2004) |
| Auteurs : | F. MAUNY ; HANDSCHUMACHER (P.) : FRA. Institut de Recherche pour le Développement. Institut de Géographie. Strasbourg. ; B. SELLIN ; J.F. VIEL ; Faculty of Medicine. Department of Public Health. Biostatistics and Epidemiology Unit. Besançon. FRA ; Institut de Recherche pour le Développement. Programme Ramse. Antananarivo. MDG |
| Type de document : | Article |
| Dans : | International journal of epidemiology (vol. 33, n° 6, 2004) |
| Pagination : | 1337-1344 |
| Langues: | Anglais |
| Mots-clés : | Paludisme ; Parasitose ; Infection ; Altitude ; Ecologie ; Madagascar ; Afrique ; Homme |
| Résumé : | [BDSP. Notice produite par INIST-CNRS R0xgG79u. Diffusion soumise à autorisation]. 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. |
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