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      Projected health impact of post-discharge malaria chemoprevention among children with severe malarial anaemia in Africa

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          Abstract

          Children recovering from severe malarial anaemia (SMA) remain at high risk of readmission and death after discharge from hospital. However, a recent trial found that post-discharge malaria chemoprevention (PDMC) with dihydroartemisinin-piperaquine reduces this risk. We developed a mathematical model describing the daily incidence of uncomplicated and severe malaria requiring readmission among 0–5-year old children after hospitalised SMA. We fitted the model to a multicentre clinical PDMC trial using Bayesian methods and modelled the potential impact of PDMC across malaria-endemic African countries. In the 20 highest-burden countries, we estimate that only 2–5 children need to be given PDMC to prevent one hospitalised malaria episode, and less than 100 to prevent one death. If all hospitalised SMA cases access PDMC in moderate-to-high transmission areas, 38,600 (range 16,900–88,400) malaria-associated readmissions could be prevented annually, depending on access to hospital care. We estimate that recurrent SMA post-discharge constitutes 19% of all SMA episodes in moderate-to-high transmission settings.

          Abstract

          Trial data have shown that post-discharge malaria chemoprevention (PDMC) reduces the risk of readmission and death in children previously hospitalised with severe malarial anaemia. Here, the authors use mathematical modelling to estimate the potential epidemiological impacts of PDMC in malaria-endemic countries in Africa.

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          Most cited references37

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          Inference from Iterative Simulation Using Multiple Sequences

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            Mapping the global prevalence, incidence, and mortality of Plasmodium falciparum , 2000–17: a spatial and temporal modelling study

            Summary Background Since 2000, the scale-up of malaria control interventions has substantially reduced morbidity and mortality caused by the disease globally, fuelling bold aims for disease elimination. In tandem with increased availability of geospatially resolved data, malaria control programmes increasingly use high-resolution maps to characterise spatially heterogeneous patterns of disease risk and thus efficiently target areas of high burden. Methods We updated and refined the Plasmodium falciparum parasite rate and clinical incidence models for sub-Saharan Africa, which rely on cross-sectional survey data for parasite rate and intervention coverage. For malaria endemic countries outside of sub-Saharan Africa, we produced estimates of parasite rate and incidence by applying an ecological downscaling approach to malaria incidence data acquired via routine surveillance. Mortality estimates were derived by linking incidence to systematically derived vital registration and verbal autopsy data. Informed by high-resolution covariate surfaces, we estimated P falciparum parasite rate, clinical incidence, and mortality at national, subnational, and 5 × 5 km pixel scales with corresponding uncertainty metrics. Findings We present the first global, high-resolution map of P falciparum malaria mortality and the first global prevalence and incidence maps since 2010. These results are combined with those for Plasmodium vivax (published separately) to form the malaria estimates for the Global Burden of Disease 2017 study. The P falciparum estimates span the period 2000–17, and illustrate the rapid decline in burden between 2005 and 2017, with incidence declining by 27·9% and mortality declining by 42·5%. Despite a growing population in endemic regions, P falciparum cases declined between 2005 and 2017, from 232·3 million (95% uncertainty interval 198·8–277·7) to 193·9 million (156·6–240·2) and deaths declined from 925 800 (596 900–1 341 100) to 618 700 (368 600–952 200). Despite the declines in burden, 90·1% of people within sub-Saharan Africa continue to reside in endemic areas, and this region accounted for 79·4% of cases and 87·6% of deaths in 2017. Interpretation High-resolution maps of P falciparum provide a contemporary resource for informing global policy and malaria control planning, programme implementation, and monitoring initiatives. Amid progress in reducing global malaria burden, areas where incidence trends have plateaued or increased in the past 5 years underscore the fragility of hard-won gains against malaria. Efforts towards elimination should be strengthened in such areas, and those where burden remained high throughout the study period. Funding Bill & Melinda Gates Foundation.
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              Modelling the impact of vector control interventions on Anopheles gambiae population dynamics

              Background Intensive anti-malaria campaigns targeting the Anopheles population have demonstrated substantial reductions in adult mosquito density. Understanding the population dynamics of Anopheles mosquitoes throughout their whole lifecycle is important to assess the likely impact of vector control interventions alone and in combination as well as to aid the design of novel interventions. Methods An ecological model of Anopheles gambiae sensu lato populations incorporating a rainfall-dependent carrying capacity and density-dependent regulation of mosquito larvae in breeding sites is developed. The model is fitted to adult mosquito catch and rainfall data from 8 villages in the Garki District of Nigeria (the 'Garki Project') using Bayesian Markov Chain Monte Carlo methods and prior estimates of parameters derived from the literature. The model is used to compare the impact of vector control interventions directed against adult mosquito stages - long-lasting insecticide treated nets (LLIN), indoor residual spraying (IRS) - and directed against aquatic mosquito stages, alone and in combination on adult mosquito density. Results A model in which density-dependent regulation occurs in the larval stages via a linear association between larval density and larval death rates provided a good fit to seasonal adult mosquito catches. The effective mosquito reproduction number in the presence of density-dependent regulation is dependent on seasonal rainfall patterns and peaks at the start of the rainy season. In addition to killing adult mosquitoes during the extrinsic incubation period, LLINs and IRS also result in less eggs being oviposited in breeding sites leading to further reductions in adult mosquito density. Combining interventions such as the application of larvicidal or pupacidal agents that target the aquatic stages of the mosquito lifecycle with LLINs or IRS can lead to substantial reductions in adult mosquito density. Conclusions Density-dependent regulation of anopheline larvae in breeding sites ensures robust, stable mosquito populations that can persist in the face of intensive vector control interventions. Selecting combinations of interventions that target different stages in the vector's lifecycle will result in maximum reductions in mosquito density.
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                Author and article information

                Contributors
                l.okell@imperial.ac.uk
                pax_amani@yahoo.com
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                25 January 2023
                25 January 2023
                2023
                : 14
                : 402
                Affiliations
                [1 ]GRID grid.7445.2, ISNI 0000 0001 2113 8111, MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, , Imperial College, ; London, W2 1PG UK
                [2 ]GRID grid.33058.3d, ISNI 0000 0001 0155 5938, Centre for Global Health Research (CGHR), , Kenya Medical Research Institute (KEMRI), ; Kisumu, Kenya
                [3 ]GRID grid.48004.38, ISNI 0000 0004 1936 9764, Department of Clinical Sciences, , Liverpool School of Tropical Medicine (LSTM), ; Liverpool, UK
                [4 ]GRID grid.11194.3c, ISNI 0000 0004 0620 0548, College of Health Sciences, , Makerere University, ; Kampala, Uganda
                [5 ]Kamuzu University of Health Sciences, Blantyre, Malawi
                [6 ]Training and Research Unit of Excellence, Blantyre, Malawi
                [7 ]GRID grid.7914.b, ISNI 0000 0004 1936 7443, Section for Ethics and Health Economics, Department of Global Public Health and Primary Care, , University of Bergen, ; P.O. Box 7804, 5020 Bergen, Norway
                [8 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Big Data Institute, , University of Oxford, ; Oxford, UK
                [9 ]Malaria Atlas Project, Telethon Kids Institute, Perth Children’s Hospital, 15 Hospital Avenue, Nedlands, Australia
                [10 ]GRID grid.1032.0, ISNI 0000 0004 0375 4078, Curtin University, ; Bentley, Australia
                [11 ]GRID grid.8991.9, ISNI 0000 0004 0425 469X, International Statistics and Epidemiology Group, , London School of Hygiene and Tropical Medicine, ; London, UK
                [12 ]GRID grid.424027.7, ISNI 0000 0001 1089 4923, Chr. Michelsen Institute, ; P.O. Box 6033, N-5892 Bergen, Norway
                [13 ]GRID grid.25867.3e, ISNI 0000 0001 1481 7466, Muhimbili University of Health and Allied Sciences, ; P.O.Box 65001, Dar es Salaam, Tanzania
                Author information
                http://orcid.org/0000-0001-7202-6873
                http://orcid.org/0000-0003-3001-4959
                http://orcid.org/0000-0001-9406-7481
                http://orcid.org/0000-0003-4694-8107
                http://orcid.org/0000-0001-6029-1733
                http://orcid.org/0000-0003-1068-9713
                http://orcid.org/0000-0003-3663-5617
                http://orcid.org/0000-0002-9968-3635
                Article
                35939
                10.1038/s41467-023-35939-w
                9876927
                36697413
                0eee6154-cb82-45fd-9937-35b3ce6ca892
                © 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 14 April 2022
                : 9 January 2023
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000288, Royal Society;
                Award ID: Dorothy Hodgkin fellowship
                Award Recipient :
                Categories
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                Custom metadata
                © The Author(s) 2023

                Uncategorized
                malaria,disease prevention,computational models,parasitology,epidemiology
                Uncategorized
                malaria, disease prevention, computational models, parasitology, epidemiology

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