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Surveilling Malaria through machine learning and clustering tools in pregnancy

Project description

Malaria surveillance in pregnant women

Malaria remains a significant health threat in certain parts of the world, necessitating effective surveillance systems. The EU-funded PregMal project aims to eliminate malaria transmission by combining molecular, serological and genomic data from pregnant women collected at antenatal care (ANC) clinics. Pregnant women are emerging as a promising, easily accessible group for malaria surveillance given their frequent visits to ANC clinics. Scientists will perform statistical analysis to determine whether data from pregnant women reflect the temporal and spatial malaria trends in the general population. Genetic analysis of the malaria parasites will provide insight into changes of parasite transmission or the introduction of new parasites into the community.

Objective

The vision of the World Health Organisation (WHO) for 2030 is a world free of malaria. For this, agile and robust malaria surveillance systems are required to efficiently guide actions towards interruption of transmission. Estimating malaria trends from passive detection of clinical malaria cases at health facilities or from cross-sectional surveys remains difficult and expensive.

Pregnant women represent a promising convenience group for malaria surveillance, providing a representative section of the overall population in a cost-efficient and sustainable manner. Serological and molecular surveillance has also become a potential key approach to guide elimination efforts, providing information about the history of exposure, the geographic origin (malaria importation) and the intensity of malaria transmission. Here we propose to develop and apply novel statistical tools (adapted from the field of cosmology) to test an innovative and cost-efficient surveillance approach based on the strategic use of parasitological, serological and genomic data from easy-access pregnant women at antenatal care (ANC) clinics. The application of these new tools on data obtained from pregnant women can suppose an enormous breakthrough for sustainable and actionable surveillance systems that can accelerate efforts towards malaria elimination. With these new developed tools I will a) assess the potential of parasitological and serological data from pregnant women at first ANC visit as a source of reliable data to reflect temporal and spatial malaria trends in the community and b) compare genetic metrics in the parasite population of pregnant women and the overall community that can inform about changes of malaria transmission, clustering of infections and parasite importation.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) H2020-MSCA-IF-2019

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Coordinator

FUNDACION PRIVADA INSTITUTO DE SALUD GLOBAL BARCELONA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 172 932,48
Address
C ROSSELLO 132 PLANTA 05
08036 Barcelona
Spain

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Region
Este Cataluña Barcelona
Activity type
Research Organisations
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 172 932,48
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