IMCCA

Innovative Modelling to Optimise Control of Childhood Anaemia across Africa

Coordinatore	SCHWEIZERISCHES TROPEN- UND PUBLIC HEALTH-INSTITUT    more Spiacenti, non ci sono informazioni su questo coordinatore. Contattare Fabio per maggiori infomrazioni, grazie.
Nazionalità Coordinatore	Switzerland [CH]
Totale costo	2˙494˙800 €
EC contributo	2˙494˙800 €
Programma	FP7-IDEAS-ERC Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
Code Call	ERC-2012-ADG_20120314
Funding Scheme	ERC-AG
Anno di inizio	2013
Periodo (anno-mese-giorno)	2013-10-01   -   2018-09-30

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	SCHWEIZERISCHES TROPEN- UND PUBLIC HEALTH-INSTITUT  Organization address address: SOCINSTRASSE 57 city: Basel postcode: CH-4002 contact info Nome: Stefan Cognome: Moergeli Email: send email Telefono: +41 61 2848320	CH (Basel)	hostInstitution	2˙494˙800.00
2	SCHWEIZERISCHES TROPEN- UND PUBLIC HEALTH-INSTITUT  Organization address address: SOCINSTRASSE 57 city: Basel postcode: CH-4002 contact info Titolo: Prof. Nome: Penelope Cognome: Vounatsou Email: send email Telefono: +41 61 2848109 Fax: +41 61 2848105	CH (Basel)	hostInstitution	2˙494˙800.00

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 Obiettivo del progetto (Objective)

'Anaemia affects two-third of all preschool-aged children in Africa. Malnutrition, malaria and helminth infections are among the main factors contributing to anaemia in this age group, however their relative contribution across the continent is not well understood. Spatially explicit estimates of anaemia risk are important measures of child morbidity and mortality. The goal of the project is to develop Bayesian geostatistical methodology for very large, non-stationary data and employ it to (i) determine the relative contribution of malaria, helminth infections and malnutrition on anaemia and severe anaemia burden among pre-school children; (ii) obtain spatially explicit estimates of the risk of anaemia, severe anaemia and number of affected children; (iii) characterize co-endemicity patterns of anaemia, malaria, helminth infection and malnutrition; and (iv) quantify the contribution of severe anaemia to child mortality. This research will contribute novel statistical methodologies in (i) spatial analysis of very large non-stationary geostatistical data, (ii) variable selection within a non-stationary model for very large geostatistical data, (iii) modelling disease co-endemicity from spatially misaligned surveys arising from independent regression models and (iv) meta-analyses of heterogeneous large spatial data by coupling geostatistical with mathematical transmission models. Applications of geostatistical methodology will help optimising interventions to combat anaemia by generating (i) the first anaemia risk map and number of affected preschool children across Africa which will guide efficient allocation of nutrient supplements and fortified foods; (ii) anaemia co-endemicity maps and estimates of the relative contribution of anaemia risk factors to design integrated interventions based on local conditions; and (ii) estimates of the anaemia-related mortality across Africa.'