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      Plasmodium falciparum gametocyte carriage in longitudinally monitored incident infections is associated with duration of infection and human host factors

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          Abstract

          Malaria transmission depends on the presence of Plasmodium gametocytes that are the only parasite life stage that can infect mosquitoes. Gametocyte production varies between infections and over the course of infections. Infection duration is highly important for gametocyte production but poorly quantified. Between 2017 and 2019 an all-age cohort of individuals from Tororo, eastern Uganda was followed by continuous passive and routine assessments. We longitudinally monitored 104 incident infections from 98 individuals who were sampled once every 28 days and on any day of symptoms. Among infections that lasted ≥ 3 months, gametocyte appearance was near-universal with 96% of infections having detectable gametocytes prior to clearance. However, most infections were of much shorter duration; 55.7% of asymptomatic infections were detected only once. When considering all asymptomatic infections, regardless of their duration, only 36.3% had detectable gametocytes on at least one time-point prior to parasite clearance. Infections in individuals with sickle-cell trait (HbAS) were more likely to have gametocytes detected (Hazard Rate (HR) = 2.68, 95% CI 1.12, 6.38; p = 0.0231) and had gametocytes detected at higher densities (Density Ratio (DR) = 9.19, 95% CI 2.79, 30.23; p = 0.0002) compared to infections in wildtype (HbAA) individuals. Our findings suggest that a large proportion of incident infections is too short in duration and of too low density to contribute to onward transmission.

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          Emergence and clonal expansion of in vitro artemisinin-resistant Plasmodium falciparum kelch13 R561H mutant parasites in Rwanda

          Artemisinin resistance (delayed P. falciparum clearance following artemisinin-based combination therapy), is widespread across Southeast Asia but to date has not been reported in Africa 1–4 . Here we genotyped the P. falciparum K13 (Pfkelch13) propeller domain, mutations in which can mediate artemisinin resistance 5,6 , in pretreatment samples collected from recent dihydroarteminisin-piperaquine and artemether-lumefantrine efficacy trials in Rwanda 7 . While cure rates were >95% in both treatment arms, the Pfkelch13 R561H mutation was identified in 19 of 257 (7.4%) patients at Masaka. Phylogenetic analysis revealed the expansion of an indigenous R561H lineage. Gene editing confirmed that this mutation can drive artemisinin resistance in vitro. This study provides evidence for the de novo emergence of Pfkelch13-mediated artemisinin resistance in Rwanda, potentially compromising the continued success of antimalarial chemotherapy in Africa.
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            Smoothing Parameter and Model Selection for General Smooth Models

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              Competing risks in epidemiology: possibilities and pitfalls.

              In studies of all-cause mortality, the fundamental epidemiological concepts of rate and risk are connected through a well-defined one-to-one relation. An important consequence of this relation is that regression models such as the proportional hazards model that are defined through the hazard (the rate) immediately dictate how the covariates relate to the survival function (the risk). This introductory paper reviews the concepts of rate and risk and their one-to-one relation in all-cause mortality studies and introduces the analogous concepts of rate and risk in the context of competing risks, the cause-specific hazard and the cause-specific cumulative incidence function. The key feature of competing risks is that the one-to-one correspondence between cause-specific hazard and cumulative incidence, between rate and risk, is lost. This fact has two important implications. First, the naïve Kaplan-Meier that takes the competing events as censored observations, is biased. Secondly, the way in which covariates are associated with the cause-specific hazards may not coincide with the way these covariates are associated with the cumulative incidence. An example with relapse and non-relapse mortality as competing risks in a stem cell transplantation study is used for illustration. The two implications of the loss of one-to-one correspondence between cause-specific hazard and cumulative incidence should be kept in mind when deciding on how to make inference in a competing risks situation.
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                Author and article information

                Contributors
                Teun.Bousema@radboudumc.nl
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                1 May 2023
                1 May 2023
                2023
                : 13
                : 7072
                Affiliations
                [1 ]GRID grid.10417.33, ISNI 0000 0004 0444 9382, Department of Medical Microbiology, , Radboud University Nijmegen Medical Centre, ; Nijmegen, The Netherlands
                [2 ]GRID grid.10417.33, ISNI 0000 0004 0444 9382, Department for Health Evidence, , Radboud University Medical Centre, ; Nijmegen, The Netherlands
                [3 ]GRID grid.463352.5, ISNI 0000 0004 8340 3103, Infectious Diseases Research Collaboration, ; Kampala, Uganda
                [4 ]GRID grid.8991.9, ISNI 0000 0004 0425 469X, Department of Infection Biology, , London School of Hygiene and Tropical Medicine, ; London, UK
                [5 ]GRID grid.266102.1, ISNI 0000 0001 2297 6811, Department of Medicine, San Francisco General Hospital, , University of California, ; San Francisco, USA
                [6 ]GRID grid.40263.33, ISNI 0000 0004 1936 9094, Department of Pathology and Laboratory Medicine, , Brown University, ; Providence, RI USA
                [7 ]GRID grid.168645.8, ISNI 0000 0001 0742 0364, Program in Molecular Medicine, , University of Massachusetts Medical School, ; Worcester, MA USA
                [8 ]GRID grid.11194.3c, ISNI 0000 0004 0620 0548, Department of Medicine, , Makerere University College of Health Sciences, ; Kampala, Uganda
                [9 ]GRID grid.8991.9, ISNI 0000 0004 0425 469X, Department of Clinical Research, , London School of Hygiene and Tropical Medicine, ; London, UK
                Article
                33657
                10.1038/s41598-023-33657-3
                10150352
                37127688
                e6f8bd5a-b4a9-4be2-bd78-8e3bea6cf2a1
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 12 October 2022
                : 17 April 2023
                Funding
                Funded by: European Research Council
                Award ID: ERC-CoG 864180
                Funded by: International Centers of Excellence in Malaria Research (ICEMR)
                Award ID: AI089674
                Funded by: Bill & Melinda Gates Foundation
                Award ID: INDIE OPP1173572
                Award ID: OPP1169785
                Award Recipient :
                Funded by: International Centers of Excellence in Malaria Research (ICEMR) program
                Award ID: AI075045
                Categories
                Article
                Custom metadata
                © The Author(s) 2023

                Uncategorized
                computational biology and bioinformatics,microbiology
                Uncategorized
                computational biology and bioinformatics, microbiology

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