Summary
Malaria infects hundreds of millions of people year on year. The WHO is committed to a world ultimately free of malaria. Of the two most important causes of malaria, Plasmodium vivax is the most difficult to eliminate largely because it has the capacity to relapse: causing recurrent malaria via the activation of latent liver-stage parasites. Recurrent malaria can also be caused by the failure to treat a previous blood-stage infection (recrudescence) and, in endemic settings, new infectious mosquito bites (reinfection). Knowing the cause of recurrent malaria is key to understanding malaria epidemiology and to providing efficacious treatment. For example, to evaluate the efficacy of a drug designed to kill P. vivax liver-stage parasites in an endemic setting, reinfections and recrudescence must be separated from relapses. However, there are no direct ways to diagnose the cause of recurrent malaria. To address this problem, I aim to build a tool (Pv3R) that uses Plasmodium vivax genetic data to estimate the probability of Relapse, Recrudescence and Reinfection, and use Pv3R to estimate the burden of relapse and its contribution to transmission, thereby validating Pv3R’s utility. I will achieve my objectives by merging my existing expertise in statistical malaria genetics with the expertise of Dr Michael White and his lab, its ties with field-based P. vivax epidemiology and its capacity to generate P. vivax genetic data. Working with Dr White, I will develop a state-of-the-art statistical inference method to tackle the challenging unsolved problem of differentiating between the causes of recurrent P. vivax. This will generate knowledge that directly improves our understanding of P. vivax epidemiology and, most long-lastingly, a public health resource (Pv3R) that can be used sustainably by the malaria community to generate more epidemiological knowledge and to guide the design of more effective treatment regimens needed for P. vivax control and elimination.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101110393 |
| Start date: | 07-11-2023 |
| End date: | 06-11-2025 |
| Total budget - Public funding: | - 211 754,00 Euro |
Cordis data
Original description
Malaria infects hundreds of millions of people year on year. The WHO is committed to a world ultimately free of malaria. Of the two most important causes of malaria, Plasmodium vivax is the most difficult to eliminate largely because it has the capacity to relapse: causing recurrent malaria via the activation of latent liver-stage parasites. Recurrent malaria can also be caused by the failure to treat a previous blood-stage infection (recrudescence) and, in endemic settings, new infectious mosquito bites (reinfection). Knowing the cause of recurrent malaria is key to understanding malaria epidemiology and to providing efficacious treatment. For example, to evaluate the efficacy of a drug designed to kill P. vivax liver-stage parasites in an endemic setting, reinfections and recrudescence must be separated from relapses. However, there are no direct ways to diagnose the cause of recurrent malaria. To address this problem, I aim to build a tool (Pv3R) that uses Plasmodium vivax genetic data to estimate the probability of Relapse, Recrudescence and Reinfection, and use Pv3R to estimate the burden of relapse and its contribution to transmission, thereby validating Pv3R’s utility. I will achieve my objectives by merging my existing expertise in statistical malaria genetics with the expertise of Dr Michael White and his lab, its ties with field-based P. vivax epidemiology and its capacity to generate P. vivax genetic data. Working with Dr White, I will develop a state-of-the-art statistical inference method to tackle the challenging unsolved problem of differentiating between the causes of recurrent P. vivax. This will generate knowledge that directly improves our understanding of P. vivax epidemiology and, most long-lastingly, a public health resource (Pv3R) that can be used sustainably by the malaria community to generate more epidemiological knowledge and to guide the design of more effective treatment regimens needed for P. vivax control and elimination.Status
SIGNEDCall topic
HORIZON-MSCA-2022-PF-01-01Update Date
31-07-2023
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