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      Micro-spatial distribution of malaria cases and control strategies at ward level in Gwanda district, Matabeleland South, Zimbabwe

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          Abstract

          Background

          Although there has been a decline in the number of malaria cases in Zimbabwe since 2010, the disease remains the biggest public health threat in the country. Gwanda district, located in Matabeleland South Province of Zimbabwe has progressed to the malaria pre-elimination phase. The aim of this study was to determine the spatial distribution of malaria incidence at ward level for improving the planning and implementation of malaria elimination in the district.

          Methods

          The Poisson purely spatial model was used to detect malaria clusters and their properties, including relative risk and significance levels at ward level. The geographically weighted Poisson regression (GWPR) model was used to explore the potential role and significance of environmental variables [rainfall, minimum and maximum temperature, altitude, Enhanced Vegetation Index (EVI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), rural/urban] and malaria control strategies [indoor residual spraying (IRS) and long-lasting insecticide-treated nets (LLINs)] on the spatial patterns of malaria incidence at ward level.

          Results

          Two significant clusters (p < 0.05) of malaria cases were identified: (1) ward 24 south of Gwanda district and (2) ward 9 in the urban municipality, with relative risks of 5.583 and 4.316, respectively. The semiparametric-GWPR model with both local and global variables had higher performance based on AICc (70.882) compared to global regression (74.390) and GWPR which assumed that all variables varied locally (73.364). The semiparametric-GWPR captured the spatially non-stationary relationship between malaria cases and minimum temperature, NDVI, NDWI, and altitude at the ward level. The influence of LLINs, IRS and rural or urban did not vary and remained in the model as global terms. NDWI (positive coefficients) and NDVI (range from negative to positive coefficients) showed significant association with malaria cases in some of the wards. The IRS had a protection effect on malaria incidence as expected.

          Conclusions

          Malaria incidence is heterogeneous even in low-transmission zones including those in pre-elimination phase. The relationship between malaria cases and NDWI, NDVI, altitude, and minimum temperature may vary at local level. The results of this study can be used in planning and implementation of malaria control strategies at district and ward levels.

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          Most cited references50

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          Multicollinearity and correlation among local regression coefficients in geographically weighted regression

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            The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives

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              The consequences of reducing transmission of Plasmodium falciparum in Africa.

              Malaria transmission intensity in Africa varies over several log orders, from less than one infected bite per year to more than one thousand. In this review we examine the consequences in terms of age pattern, clinical spectrum and overall burden of disease and discuss the possible implications for interventions that reduce exposure to infected bites. With very low transmission intensity, all age groups are susceptible to severe malaria. With increasing transmission intensities, older children and adults suffer less severe disease and with high transmission rates the majority of severe cases occur in infants under one year of age. This pattern reflects the increasingly rapid acquisition of immune responses that limit the life-threatening effects of malaria with increasing exposure to the parasite. The clinical spectrum of severe malaria varies with transmission: with high transmission, severe malarial anaemia dominates and cerebral malaria is rare. As one moves towards lower transmission rates, cerebral malaria accounts for an increasingly large proportion of cases. Although the population risk of severe disease falls with age, the risk of death at an individual level may rise with age after an initial fall from very high case fatality rates in children aged under 6 months. Of central interest to malaria control is how the overall amount of disease in childhood varies with transmission. Data from a number of sources suggest that, with low transmission, the amount of malarial disease rises with increasing exposure but that this saturates relatively early. A key issue is whether the same pattern obtains for deaths, both those directly due to malaria and those from all causes. The methodological limitations of ecological comparisons between different areas are discussed before presenting a review of attempts to use this approach in Africa. This suggests that children living in areas of low malarial endemicity have all-cause mortality rates about half of those of children living in areas of moderate to high transmission. Deaths in the first year of life rise linearly with increasing exposure to malaria over a wide range of transmission intensities; by contrast all-cause mortality in children aged 0-4 years appears to saturate at relatively low transmission intensities. These data suggest that interventions that reduce exposure to malaria parasites, such as insecticide-treated bed nets (ITNs), will have the greatest chance of a sustained effect when used in areas where disease burdens are high but the frequency of parasite exposure is low-to-moderate. In conditions of high transmission, initial reductions in mortality may prove difficult to sustain as the reduced level of transmission may still lie on the part of the curve where mortality has saturated. However, at all levels of transmission the overall balance of benefits, including reduced load on families and health services from non-life-threatening malaria, favours the widespread introduction of ITNs in endemic areas of Africa.
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                Author and article information

                Contributors
                manyangadze.tawanda@gmail.com
                chimbari@ukzn.ac.za
                mmacherera@gmail.com
                mukaratirwa@ukzn.ac.za
                Journal
                Malar J
                Malar. J
                Malaria Journal
                BioMed Central (London )
                1475-2875
                21 November 2017
                21 November 2017
                2017
                : 16
                : 476
                Affiliations
                [1 ]ISNI 0000 0001 0723 4123, GRID grid.16463.36, Department of Public Health Medicine, School of Nursing and Public Health, , University of KwaZulu-Natal, ; Durban, South Africa
                [2 ]ISNI 0000 0004 0648 4659, GRID grid.469393.2, Geography Department, Faculty of Science, , Bindura University of Science Education, ; Bag 1020, Bindura, Zimbabwe
                [3 ]GRID grid.440812.b, Department of Environmental Science and Health, Faculty of Applied Sciences, , National University of Science and Technology, ; Ascot, P O Box AC 939, Bulawayo, Zimbabwe
                [4 ]ISNI 0000 0001 0723 4123, GRID grid.16463.36, School of Life Sciences, , University of KwaZulu-Natal, ; Durban, South Africa
                Article
                2116
                10.1186/s12936-017-2116-1
                5697109
                29162102
                d45aaa94-eb2a-48e5-8881-80eab32c560f
                © The Author(s) 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 6 May 2017
                : 11 November 2017
                Funding
                Funded by: WHO/TDR
                Award ID: B20273
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2017

                Infectious disease & Microbiology
                cluster detection,malaria hotspots,geographically weighted poisson regression (gwpr) model,malaria pre-elimination phase

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