MOESM4 of Malaria intervention scale-up in Africa: effectiveness predictions for health programme planning tools, based on dynamic transmission modelling

Additional file 4. Predicted relative burden reductions from alternative statistical models, as part of the sensitivity analysis.

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PID https://www.doi.org/10.6084/m9.figshare.c.3640463_d3
PID https://www.doi.org/10.6084/m9.figshare.c.3640463_d3.v1
URL http://dx.doi.org/10.6084/m9.figshare.c.3640463_d3.v1
URL https://dx.doi.org/10.6084/m9.figshare.c.3640463_d3.v1
URL https://figshare.com/articles/MOESM4_of_Malaria_intervention_scale-up_in_Africa_effectiveness_predictions_for_health_programme_planning_tools_based_on_dynamic_transmission_modelling/4455476
URL http://dx.doi.org/10.6084/m9.figshare.c.3640463_d3
URL https://dx.doi.org/10.6084/M9.FIGSHARE.C.3640463_D3
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Access Right Open Access
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Author Eline Korenromp
Author Guy MahianĂŠ
Author Matthew Hamilton
Author Carel Pretorius
Author Richard Cibulskis
Author Jeremy Lauer
Author Thomas Smith
Author Olivier BriĂŤt
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Collected From Datacite; figshare
Hosted By figshare
Publication Date 2016-12-15
Publisher Figshare
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Language UNKNOWN
Resource Type Dataset
keyword FOS: Biological sciences
keyword FOS: Computer and information sciences
system:type dataset
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Source https://science-innovation-policy.openaire.eu/search/dataset?datasetId=dedup_wf_001::548adce75b303c68d624ce63a2b54c72
Author jsonws_user
Version None
Last Updated 1 January 2021, 22:21 (CET)
Created 1 January 2021, 22:21 (CET)