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      Geostatistical modelling of malaria indicator survey data to assess the effects of interventions on the geographical distribution of malaria prevalence in children less than 5 years in Uganda

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          Abstract

          Background

          Malaria burden in Uganda has declined disproportionately among regions despite overall high intervention coverage across all regions . The Uganda Malaria Indicator Survey (MIS) 2014–15 was the second nationally representative survey conducted to provide estimates of malaria prevalence among children less than 5 years, and to track the progress of control interventions in the country. In this present study, 2014–15 MIS data were analysed to assess intervention effects on malaria prevalence in Uganda among children less than 5 years, assess intervention effects at regional level, and estimate geographical distribution of malaria prevalence in the country.

          Methods

          Bayesian geostatistical models with spatially varying coefficients were used to determine the effect of interventions on malaria prevalence at national and regional levels. Spike-and-slab variable selection was used to identify the most important predictors and forms. Bayesian kriging was used to predict malaria prevalence at unsampled locations.

          Results

          Indoor Residual Spraying (IRS) and Insecticide Treated Nets (ITN) ownership had a significant but varying protective effect on malaria prevalence. However, no effect was observed for Artemisinin Combination-based Therapies (ACTs). Environmental factors, namely, land cover, rainfall, day and night land surface temperature, and area type were significantly associated with malaria prevalence. Malaria prevalence was higher in rural areas, increased with the child’s age, and decreased with higher household socioeconomic status and higher level of mother’s education. The highest prevalence of malaria in children less than 5 years was predicted for regions of East Central, North East and West Nile, whereas the lowest was predicted in Kampala and South Western regions, and in the mountainous areas in Mid-Western and Mid-Eastern regions.

          Conclusions

          IRS and ITN ownership are important interventions against malaria prevalence in children less than 5 years in Uganda. The varying effects of the interventions calls for selective implementation of control tools suitable to regional ecological settings. To further reduce malaria burden and sustain malaria control in Uganda, current tools should be supplemented by health system strengthening, and socio-economic development.

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          Most cited references41

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          A new world malaria map: Plasmodium falciparum endemicity in 2010

          Background Transmission intensity affects almost all aspects of malaria epidemiology and the impact of malaria on human populations. Maps of transmission intensity are necessary to identify populations at different levels of risk and to evaluate objectively options for disease control. To remain relevant operationally, such maps must be updated frequently. Following the first global effort to map Plasmodium falciparum malaria endemicity in 2007, this paper describes the generation of a new world map for the year 2010. This analysis is extended to provide the first global estimates of two other metrics of transmission intensity for P. falciparum that underpin contemporary questions in malaria control: the entomological inoculation rate (PfEIR) and the basic reproductive number (PfR). Methods Annual parasite incidence data for 13,449 administrative units in 43 endemic countries were sourced to define the spatial limits of P. falciparum transmission in 2010 and 22,212 P. falciparum parasite rate (PfPR) surveys were used in a model-based geostatistical (MBG) prediction to create a continuous contemporary surface of malaria endemicity within these limits. A suite of transmission models were developed that link PfPR to PfEIR and PfR and these were fitted to field data. These models were combined with the PfPR map to create new global predictions of PfEIR and PfR. All output maps included measured uncertainty. Results An estimated 1.13 and 1.44 billion people worldwide were at risk of unstable and stable P. falciparum malaria, respectively. The majority of the endemic world was predicted with a median PfEIR of less than one and a median PfR c of less than two. Values of either metric exceeding 10 were almost exclusive to Africa. The uncertainty described in both PfEIR and PfR was substantial in regions of intense transmission. Conclusions The year 2010 has a particular significance as an evaluation milestone for malaria global health policy. The maps presented here contribute to a rational basis for control and elimination decisions and can serve as a baseline assessment as the global health community looks ahead to the next series of milestones targeted at 2015.
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            Insecticide-treated bed nets and curtains for preventing malaria.

            C Lengeler (2004)
            Malaria is an important cause of illness and death in many parts of the world, especially in sub-Saharan Africa. There has been a renewed emphasis on preventive measures at community and individual levels. Insecticide-treated nets (ITNs) are the most prominent malaria preventive measure for large-scale deployment in highly endemic areas. To assess the impact of insecticide-treated bed nets or curtains on mortality, malarial illness (life-threatening and mild), malaria parasitaemia, anaemia, and spleen rates. I searched the Cochrane Infectious Diseases Group trials register (January 2003), CENTRAL (The Cochrane Library, Issue 1, 2003), MEDLINE (1966 to October 2003), EMBASE (1974 to November 2002), LILACS (1982 to January 2003), and reference lists of reviews, books, and trials. I handsearched journals, contacted researchers, funding agencies, and net and insecticide manufacturers. Individual and cluster randomized controlled trials of insecticide-treated bed nets or curtains compared to nets without insecticide or no nets. Trials including only pregnant women were excluded. The reviewer and two independent assessors reviewed trials for inclusion. The reviewer assessed trial methodological quality and extracted and analysed data. Fourteen cluster randomized and eight individually randomized controlled trials met the inclusion criteria. Five trials measured child mortality: ITNs provided 17% protective efficacy (PE) compared to no nets (relative rate 0.83, 95% confidence interval (CI) 0.76 to 0.90), and 23% PE compared to untreated nets (relative rate 0.77, 95% CI 0.63 to 0.95). About 5.5 lives (95% CI 3.39 to 7.67) can be saved each year for every 1000 children protected with ITNs. In areas with stable malaria, ITNs reduced the incidence of uncomplicated malarial episodes in areas of stable malaria by 50% compared to no nets, and 39% compared to untreated nets; and in areas of unstable malaria: by 62% for compared to no nets and 43% compared to untreated nets for Plasmodium falciparum episodes, and by 52% compared to no nets and 11% compared to untreated nets for P. vivax episodes. When compared to no nets and in areas of stable malaria, ITNs also had an impact on severe malaria (45% PE, 95% CI 20 to 63), parasite prevalence (13% PE), high parasitaemia (29% PE), splenomegaly (30% PE), and their use improved the average haemoglobin level in children by 1.7% packed cell volume. ITNs are highly effective in reducing childhood mortality and morbidity from malaria. Widespread access to ITNs is currently being advocated by Roll Back Malaria, but universal deployment will require major financial, technical, and operational inputs.
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              Changes in the burden of malaria in sub-Saharan Africa.

              The burden of malaria in countries in sub-Saharan Africa has declined with scaling up of prevention, diagnosis, and treatment. To assess the contribution of specific malaria interventions and other general factors in bringing about these changes, we reviewed studies that have reported recent changes in the incidence or prevalence of malaria in sub-Saharan Africa. Malaria control in southern Africa (South Africa, Mozambique, and Swaziland) began in the 1980s and has shown substantial, lasting declines linked to scale-up of specific interventions. In The Horn of Africa, Ethiopia and Eritrea have also experienced substantial decreases in the burden of malaria linked to the introduction of malaria control measures. Substantial increases in funding for malaria control and the procurement and distribution of effective means for prevention and treatment are associated with falls in malaria burden. In central Africa, little progress has been documented, possibly because of publication bias. In some countries a decline in malaria incidence began several years before scale-up of malaria control. In other countries, the change from a failing drug (chloroquine) to a more effective drug (sulphadoxine plus pyrimethamine or an artemisinin combination) led to immediate improvements; in others malaria reduction seemed to be associated with the scale-up of insecticide-treated bednets and indoor residual spraying. 2010 Elsevier Ltd. All rights reserved.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                4 April 2017
                2017
                : 12
                : 4
                : e0174948
                Affiliations
                [1 ]Swiss Tropical and Public Health Institute, Basel, Switzerland
                [2 ]University of Basel, Basel, Switzerland
                [3 ]School of Public Health, Makerere University, Kampala, Uganda
                [4 ]Ministry of Health, Kampala, Uganda
                Universidade Federal de Minas Gerais, BRAZIL
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: PV SK FM.

                • Data curation: JS JK.

                • Formal analysis: JS.

                • Funding acquisition: PV SK FM.

                • Investigation: JS BN JK BA SK FM PV.

                • Methodology: JS PV.

                • Project administration: PV SK FM.

                • Resources: PV SK FM.

                • Software: JS.

                • Supervision: PV SK FM.

                • Validation: JS.

                • Visualization: JS PV SK FM.

                • Writing – original draft: JS BN JK BA SK FM PV.

                • Writing – review & editing: JS BN JK BA SK FM PV.

                Author information
                http://orcid.org/0000-0002-4904-5352
                Article
                PONE-D-17-03343
                10.1371/journal.pone.0174948
                5380319
                28376112
                227ad3b2-cb61-42e5-ab0d-b3d3cfb8c5e4
                © 2017 Ssempiira et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 25 January 2017
                : 19 March 2017
                Page count
                Figures: 3, Tables: 6, Pages: 20
                Funding
                This research work was supported and funded by the Swiss Programme for Research on Global Issues for Development (r4d) project no. IZ01Z0-147286 and the European Research Council (ERC) advanced grant project no. 323180.
                Categories
                Research Article
                Medicine and Health Sciences
                Parasitic Diseases
                Malaria
                Medicine and Health Sciences
                Tropical Diseases
                Malaria
                People and Places
                Geographical Locations
                Africa
                Uganda
                Biology and Life Sciences
                Agriculture
                Agrochemicals
                Insecticides
                People and Places
                Demography
                People and Places
                Population Groupings
                Age Groups
                Children
                People and Places
                Population Groupings
                Families
                Children
                Medicine and Health Sciences
                Diagnostic Medicine
                Signs and Symptoms
                Fevers
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Signs and Symptoms
                Fevers
                Biology and Life Sciences
                Population Biology
                Population Dynamics
                Geographic Distribution
                Physical Sciences
                Materials Science
                Material Properties
                Surface Properties
                Surface Temperature
                Custom metadata
                The data we used was requested from the DHS program ( www.dhsprogram.com), but the "Dataset Terms of Use" do not permit us to distribute this data as per data access instructions ( http://dhsprogram.com/data/Access-Instructions.cfm). However, data are available from the DHS MEASURE program website ( www.dhsprogram.com) and can be accessed upon request using this contact; Tel: (301) 572-0851, E-mail: archive@ 123456dhsprogram.com .

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                Uncategorized

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