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

International Journal of Epidemiology
F MaunyB Sellin

Abstract

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. 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). 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. 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.

Citations

Aug 7, 2013·Malaria Journal·Adugna WoyessaBernt Lindtjørn
May 20, 2014·PloS One·Lauren SaundersUNKNOWN RAISIN group
Sep 18, 2012·Trends in Parasitology·Robert E SindenMichael J Delves
Jul 12, 2011·Acta Tropica·Myriam Arevalo-HerreraSocrates Herrera
Feb 7, 2015·Tropical Medicine & International Health : TM & IH·Jacob MazalaleManuela De Allegri
Sep 9, 2011·Memórias do Instituto Oswaldo Cruz·Julio César Mateus, Gabriel Carrasquilla
Apr 11, 2019·International Journal of Environmental Research and Public Health·Sehyeong Kim, Youngho Kim

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