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Umberto D'Alessandro

Researcher at University of London

Publications -  289
Citations -  13619

Umberto D'Alessandro is an academic researcher from University of London. The author has contributed to research in topics: Malaria & Population. The author has an hindex of 58, co-authored 278 publications receiving 11996 citations. Previous affiliations of Umberto D'Alessandro include Medical Research Council & University of Antwerp.

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A significant increase in kdr in Anopheles gambiae is associated with an intensive vector control intervention in Burundi highlands

TL;DR: In Burundi, the occurrence of the knock down resistance (kdr) mutation in Anopheles gambiae sensu lato (s.l.) was determined for six consecutive years within the framework of a vector control programme and was linked with the insecticide resistance status observed with bioassay.
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Spatial targeted vector control in the highlands of Burundi and its impact on malaria transmission

TL;DR: Spatial targeted vector control effectively reduced Anopheles density and transmission in this highland district and could prevent the emergence and spread of an epidemic from these high risk foci.
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Combining individual patient data and aggregate data in mixed treatment comparison meta-analysis: Individual patient data may be beneficial if only for a subset of trials.

TL;DR: The proposed random-effects MTC models combine IPD and AD for a dichotomous outcome by including treatment-by-covariate interactions in the model and describe three different model specifications that make increasingly stronger assumptions regarding the interactions.
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Adherence to 7-day primaquine treatment for the radical cure of P. vivax in the Peruvian Amazon.

TL;DR: Despite being free of charge, treatment adherence to 7-day primaquine for the radical cure of Plasmodium vivax was estimated at 62.2% among patients along the Iquitos-Nauta road in the Peruvian Amazon.
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Malaria in central Vietnam: analysis of risk factors by multivariate analysis and classification tree models

TL;DR: Results show that the control of forest malaria remains an extremely complex task that has to address poverty-related risk factors such as education, ethnicity and housing conditions, and the combination of CART and multivariate analysis constitute a novel analytical approach.