Dataset Information

Geographically weighted regression of land cover determinants of Plasmodium falciparum transmission in the Ashanti Region of Ghana.

ABSTRACT: Malaria is a mosquito-borne parasitic disease that causes severe mortality and morbidity, particularly in Sub-Saharan Africa. As the vectors predominantly bite between dusk and dawn, risk of infection is determined by the abundance of P. falciparum infected mosquitoes in the surroundings of the households. Remote sensing is commonly employed to detect associations between land use/land cover (LULC) and mosquito-borne diseases. Due to challenges in LULC identification and the fact that LULC merely functions as a proxy for mosquito abundance, assuming spatially homogenous relationships may lead to overgeneralized conclusions.Data on incidence of P. falciparum parasitaemia were recorded by active and passive follow-up over two years. Nine LULC types were identified through remote sensing and ground-truthing. Spatial associations of LULC and P. falciparum parasitaemia rate were described in a semi-parametric geographically weighted Poisson regression model.Complete data were available for 878 individuals, with an annual P. falciparum rate of 3.2 infections per person-year at risk. The influences of built-up areas (median incidence rate ratio (IRR): 0.94, IQR: 0.46), forest (median IRR: 0.9, IQR: 0.51), swampy areas (median IRR: 1.15, IQR: 0.88), as well as banana (median IRR: 1.02, IQR: 0.25), cacao (median IRR: 1.33, IQR: 0.97) and orange plantations (median IRR: 1.11, IQR: 0.68) on P. falciparum rate show strong spatial variations within the study area. Incorporating spatial variability of LULC variables increased model performance compared to the spatially homogenous model.The observed spatial variability of LULC influence in parasitaemia would have been masked by traditional Poisson regression analysis assuming a spatially constant influence of all variables. We conclude that the spatially varying effects of LULC on P. falciparum parasitaemia may in fact be associated with co-factors not captured by remote sensing, and suggest that future studies assess small-scale spatial variation of vegetation to circumvent generalised assumptions on ecological associations that may in fact be artificial.

SUBMITTER: Ehlkes L

PROVIDER: S-EPMC4192530 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Geographically weighted regression of land cover determinants of Plasmodium falciparum transmission in the Ashanti Region of Ghana.

Ehlkes Lutz L Krefis Anne Caroline AC Kreuels Benno B Krumkamp Ralf R Adjei Ohene O Ayim-Akonor Matilda M Kobbe Robin R Hahn Andreas A Vinnemeier Christof C Loag Wibke W Schickhoff Udo U May Jürgen J

International journal of health geographics 20140930

<h4>Background</h4>Malaria is a mosquito-borne parasitic disease that causes severe mortality and morbidity, particularly in Sub-Saharan Africa. As the vectors predominantly bite between dusk and dawn, risk of infection is determined by the abundance of P. falciparum infected mosquitoes in the surroundings of the households. Remote sensing is commonly employed to detect associations between land use/land cover (LULC) and mosquito-borne diseases. Due to challenges in LULC identification and the f ...[more]

PMID: 25270342

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Project description:Background The World Health Organization (WHO) encourages breastfeeding to begin within the first hour after birth in order to save children’s lives. In Ethiopia, different studies are done on the prevalence and determinants of breastfeeding initiation, up to our knowledge, the spatial distribution and the spatial determinants of breast feeding initiation over time are not investigated. Therefore, the objectives of this study were to assess spatial variation and its spatial determinant of delayed initiation of breastfeeding in Ethiopia using Geographically Weighted Regression (GWR). Methods A cross-sectional study was undertaken using the nationally representative 2016 Ethiopian Demographic and Health Survey (EDHS) dataset. Global Moran’s I statistic was used to measure whether delayed breastfeeding initiation was dispersed, clustered, or randomly distributed in study area. Ordinary Least Squares (OLS) regression was used to identify factors explaining the geographic variation in delayed breastfeeding initiation. Besides, spatial variability of relationships between dependent and selected predictors was investigated using geographically weighted regression. Result A total weighted sample of 4169 children of aged 0 to 23 months was included in this study. Delayed initiation of breastfeeding was spatially varies across the country with a global Moran’s I value of 0.158 at (p-value<0.01). The hotspot (high risk) areas were identified in the Amhara, Afar, and Tigray regions. Orthodox religion, poor wealth index, caesarian section, baby postnatal checkup, and small size of a child at birth were spatially significant factors for delayed breastfeeding initiation in Ethiopia. Conclusion In Ethiopia initiation of breastfeeding varies geographically across region. A significant hotspot was identified in the Amhara, Afar, and Tigray regions. The GWR analysis revealed that orthodox religion, poor wealth index, caesarian section, baby postnatal checkup, and small birth weight were spatially significant factors.

Project description:BackgroundUnderstanding why some infants tolerate infections, remaining asymptomatic while others succumb to repeated symptomatic malaria is beneficial for studies of naturally acquired immunity and can guide control interventions. This study compared demographic, host and maternal factors associated with being either parasite negative or having asymptomatic infections versus developing symptomatic malaria in the first year of life.MethodsA birth cohort (n = 1264) was monitored longitudinally over two years for malaria infections in Kintampo, Ghana. Symptomatic and asymptomatic infections were detected actively through monthly home visits, complemented by passive case detection. Light microscopy was used to detect parasitaemia. Based on data from a minimum of eight monthly visits within the first year of life, infants were classified into one of four groups: "parasite negative", "only-asymptomatic", "only-symptomatic" or "alternating" i.e., sometimes symptomatic and other times asymptomatic. The host and maternal characteristics and demographic factors in relation to these four groups were compared.ResultsThe parasite negative group formed 36% of the cohort, whilst the only-symptomatic were 35%. The alternating group were 22% and the only-asymptomatic were 7% of the cohort. There were significant associations between residence, socio-economic status (SES), parity, IPTp doses, delivery place of infant and having or not having malaria parasites. Maternal factors such as early commencement and frequency of ante-natal care (ANC) were significantly higher in the parasite negative group compared to all others. ITN use in pregnancy increased the odds of infant having only asymptomatic infections ("protected against disease"). Placental malaria was more common in the groups of infants with symptomatic malaria. Urban residence was significantly higher in the parasite negative group, while birth in the malaria transmission season were significantly more common in the alternating and parasite negative groups. Risk factors for infants with symptomatic malaria included low SES, birth in private maternity homes, sickle cell normal variant, lower MUAC, reported intake of anti-malarials and increased morbidity before the first microscopic infection was detected.ConclusionStrengthening ANC by encouraging early and regular attendance, the use of IPTp, maternal bed nets and improving the nourishment of infants help reduce the frequency of symptomatic malaria over the first year of life.

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Geographically weighted regression of land cover determinants of Plasmodium falciparum transmission in the Ashanti Region of Ghana.

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Geographically weighted regression of land cover determinants of Plasmodium falciparum transmission in the Ashanti Region of Ghana.

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