Project

Discipline

geostatistics; Demographic Health Surveys; mapping; mortality; Malaria Indicator Surveys; Gaussian process; Bayesian methods; Markov chain Monte Carlo; spatio-temporal process; Africa; Millennium Development Goals; malaria

Lead
C'è un forte impegno da parte dei paesi e dei donatori per raggiungere gli obiettivi di malaria fissati per l'anno 2015 all’interno degli Obiettivi di Sviluppo del Millennio. In molti paesi, sono state condotte delle indagini nazionali volte a monitorare gli indicatori di salute principali, quali i casi malaria, mortalità infantile e materna cosí come gli indicatori degli interventi sanitari corrispondenti. Tuttavia, nonostante questi sforzi e le risorse investite nella raccolta dei dati, l’informazione estratta nella maggior parte dei paesi è scarsa e si è piuttosto limitata al calcolo di medie nazionali, trascurando eterogeneità e differenze su scale inferiori. Inoltre, vi è un uso limitato dei dati nella valutazione degli interventi in corso, perché le analisi esistenti non riguardano indicatori di salute, prestazioni del sistema sanitario, né l'attuazione di interventi a scala locale.
Lay summary
L' obiettivo generale del progetto è quello di ridurre i casi malaria in Africa attraverso lo sviluppo e convalida di strumenti  (metodi , conoscenze, software) per migliorare la sorveglianza della malaria al fine di controllo e successiva eliminazione. Il progetto persegue i seguenti obiettivi specifici: (i) valutare le dinamiche spazio-temporali di rischio di malaria e misurare l'efficacia degli interventi a scala locale in Africa; (ii) stimare la mortalità attibuibile alla malaria in tutte le fasce d’età in Africa; (iii) valutare le dinamiche spazio-temporali e ottenere stime aggiornate ad alta risoluzione di mortalità neonatale e infantile in Africa; (iv) stimare il contributo delle prestazioni e degli interventi nei sistemi sanitari sulle dinamiche spazio-temporali del rischio di malaria e sulla mortalità (infantile e materna) in Uganda (Africa orientale) e Burkina Faso (Africa occidentale); (v) proporre strategie per ottimizzare le prestazioni dei sistemi sanitari ed interventi per ridurre i casi di malaria e il tasso di mortalità; (vi) sviluppare e diffondere il software per la sorveglianza della malaria (i.e. software per la mappatura geostatistica di rischio di malaria e diagnosi precoce dei focolai di malaria).Le stime spazio-temporali valuteranno il progresso verso gli obiettivi di malaria e mortalità che sono parte degli Obiettivi  di Sviluppo del Millennio ed altri obiettivi globali considerando le variazioni regionali piuttosto che le medie nazionali. I risultati del progetto saranno tradotti in strumenti  (mappe di rischio di malaria a varie risoluzioni geografiche, analisi di costo-efficacia di diversi interventi  sanitari, strategie per migliorare le performance del sistema sanitario, software di sorveglianza) per l’ausilio diretto dei programmi di controllo per l’eliminazione della malaria e la riduzione di mortalità infantile e materna.

Direct link to Lay Summary

Last update: 09.04.2014

Lead
There is a strong commitment from most countries and donors to reach malaria targets set for the year 2015 in the Millennium Development Goals. In many countries, national surveys have been repeatedly conducted to monitor key health-related indicators such as malaria, child and maternal mortality and relevant interventions. However, despite these efforts and resources invested in data collection, the information extracted from the data by most countries is poor and it is rather limited to national averages, overlooking regional and smaller scale heterogeneities and disparities. Additionally, there is limited use of the data in evaluating on-going interventions because existing analyses do not relate variations in the health indicators, system performance and implementation of interventions at local scale.
Lay summary
The overarching goal of the project is to reduce malaria burden in Africa by developing and validating tools (methods, knowledge, software) to strengthen malaria surveillance for disease control and elimination. The project will pursue the following interrelated specific objectives: (i) assess spatio-temporal dynamics of malaria risk and measure effectiveness of related interventions at local scale in Africa; (ii)   estimate the malaria-related mortality across all age groups in Africa; (iii) assess spatio-temporal dynamics and obtain up-todate high resolution estimates of infant and child mortality  across Africa; (iv) estimate the contribution of health systems performance and interventions in the spatio-temporal dynamics of malaria and mortality (child and maternal) in Uganda (East Africa) and Burkina Faso (West Africa); (v) propose strategies to optimize health systems performance and interventions to reduce malaria and mortality burden; (vi) develop and disseminate software for malaria surveillance (i.e. Bayesian geostatistical  malaria mapping and  early detection of malaria outbreaks). The spatio-temporal estimates will evaluate success in achieving malaria and mortality related MDGs and other global targets considering regional disparities rather than national averages. The project results will be translated to tools (e.g. maps, burden estimates at different geographical resolution, cost-effectiveness of different interventions, strategies to improve health system performance, surveillance software) that can directly assist efforts of the control programmes towards malaria elimination and reduction of child and maternal mortality. Additionally, these products can be used to influence policy makers to choose spatially targeted, cost-effective interventions and improve local health systems in Uganda and Burkina Faso.  The malaria surveillance software would be easily installed in NMCPs other than Burkina Faso and Uganda. It can be also easily adapted for surveillance of other diseases.

Direct link to Lay Summary

Last update: 09.04.2014

Active participation

Self-organised

Number	Title	Start	Funding scheme

Background: There is a strong commitment from most countries and donors to reach malaria targets set for the year 2015 in the Millennium Development Goals (MDG), the World Health Assembly (WHA), the Roll Back Malaria (RBM) Partnership and Global Malaria Action Plan (GMAP). In many countries, national surveys have been repeatedly conducted to monitor key health-related indicators such as malaria, child and maternal mortality and relevant interventions. However, despite these efforts and resources invested in data collection, the information extracted from the data by most countries is poor and it is rather limited to national averages, overlooking regional and smaller scale heterogeneities and disparities. Additionally, there is limited use of the data in evaluating on-going interventions because existing analyses do not relate variations in the health indicators, system performance and implementation of interventions at local scale. Bayesian geostatistical modelling is the state-of-the-art approach for estimating the disease burden or child mortality at local scales and for measuring the effects of interventions from national survey data. However, most analyses focus on the spatial distribution of the health outcomes without linking health intervention and system performance data. In addition, lack of advance statistical expertise in the control programmes and readily available software to perform routinely geostatistical analyses for surveillance limits the use of the methods to statisticians or specialised epidemiologists. Goal and specific objectives: The overarching goal of the project is to reduce malaria burden in Africa by developing and validating tools (methods, knowledge, software) to strengthen malaria surveillance for disease control and elimination. The project will pursue the following interrelated specific objectives: (i) assess spatio-temporal dynamics of malaria risk and measure effectiveness of related interventions at local scale in Africa; (ii) estimate the malaria-related mortality across all age groups in Africa; (iii) assess spatio-temporal dynamics and obtain up-todate high resolution estimates of infant and child mortality across Africa; (iv) estimate the contribution of health systems performance and interventions in the spatio-temporal dynamics of malaria and mortality (child and maternal) in Uganda (East Africa) and Burkina Faso (West Africa); (v) propose strategies to optimize health systems performance and interventions to reduce malaria and mortality burden and (vi) develop and disseminate software for malaria surveillance.Methods of investigation: We propose to accomplish these objectives by (a) employing and further developing Bayesian spatio-temporal methodology for mortality and malaria surveillance; (ii) analysing well known spatially structured databases from Africa (i.e. demographic health surveys (DHS), malaria indicator surveys (MIS), Malaria Indicator Cluster Surveys (MICS), malaria transmission intensity and mortality burden across Africa (MTIMBA)); and © compiling geo-referenced databases on interventions, health systems performance indicators and relevant epidemiological outcomes in Uganda and Burkina Faso. Additional data in the two study countries will be obtained from Health Demographic Surveillance Systems (HDSS), Health Information Systems (HIS), National Malaria Control Programmes (NMCP), health facilities and community surveys.Proposed time frame: January 2013 to December 2016.Significance: The spatio-temporal estimates will evaluate success in achieving malaria and mortality related MDGs and other global targets considering regional disparities rather than national averages. The project results will be translated to tools (e.g. maps, burden estimates at different geographical resolution, cost-effectiveness of different interventions, strategies to improve health system performance, surveillance software) that can directly assist efforts of the control programmes towards malaria elimination and reduction of child and maternal mortality. Additionally, these products can be used to influence policy makers to choose spatially targeted, cost-effective interventions and improve local health systems in Uganda and Burkina Faso. The up-to-date, geo-referenced estimates of infant and under five mortality can be considered as socio-economic proxies at high spatial resolution across Africa. They can be used to improve spatially explicit burden estimates of poverty-related neglected diseases in Africa. The malaria surveillance software would be easily installed in NMCPs other than Burkina Faso and Uganda. It can be also easily adapted for surveillance of other diseases.