Dataset Information

Exploring Determinants of Spatial Variations in the Dengue Fever Epidemic Using Geographically Weighted Regression Model: A Case Study in the Joint Guangzhou-Foshan Area, China, 2014.

ABSTRACT: Dengue fever (DF) is a common and rapidly spreading vector-borne viral disease in tropical and subtropical regions. In recent years, this imported disease has posed an increasing threat to public health in China, especially in many southern cities. Although the severity of DF outbreaks in these cities is generally associated with known risk factors at various administrative levels, spatial heterogeneities of these associations remain little understood on a finer scale. In this study, the neighboring Guangzhou and Foshan (GF) cities were considered as a joint area for characterizing the spatial variations in the 2014 DF epidemic at various grid levels from 1 × 1 km² to 6 × 6 km². On an appropriate scale, geographically weighted regression (GWR) models were employed to interpret the influences of socioeconomic and environmental factors on this epidemic across the GF area. DF transmissions in Guangzhou and Foshan cities presented synchronous temporal changes and spatial expansions during the main epidemic months. Across the GF area, this epidemic was obviously spatially featured at various grid levels, especially on the 2 × 2 km² scale. Its spatial variations were relatively sufficiently explained by population size, road density, and economic status integrated in the GWR model with the lowest Akaike Information Criterion (AICc = 5227.97) and highest adjusted R square (0.732) values. These results indicated that these three socioeconomic factors acted as geographical determinants of spatial variability of the 2014 DF epidemic across the joint GF area, although some other potential factors should be added to improve the explaining the spatial variations in the central zones. This work improves our understanding of the effects of socioeconomic conditions on the spatial variations in this epidemic and helps local hygienic authorities to make targeted joint interventions for preventing and controlling this epidemic across the GF area.

SUBMITTER: Ren H

PROVIDER: S-EPMC5750936 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundSkilled birth attendant (SBA) delivery is vital for the health of mothers and newborns, as most maternal and newborn deaths occur at the time of childbirth or immediately after birth. This problem becomes worsen in Ethiopia in which only 28% of women give birth with the help of SBA. Therefore, this study aimed to explore the spatial variations of SBA delivery and its associated factors in Ethiopia.MethodsA secondary analysis was carried out using the 2016 Ethiopian Demographic and Health Survey. A total weighted sample of 11,023 women who had a live birth in the 5 years preceding the survey was included in the analysis. Arc-GIS software was used to explore the spatial distribution of SBA and a Bernoulli model was fitted using SaTScan software to identify significant clusters of non-SBA delivery. The Geographic Weighted Regression (GWR) was employed in modeling spatial relationships. Moreover, a multilevel binary logistic regression model was fitted to identify factors associated with SBA delivery.ResultsIn this study, SBA delivery had spatial variations across the country. The SaTScan spatial analysis identified the primary clusters' spatial window in southeastern Oromia and almost the entire Somalia. The GWR analysis identified different predictors of non- SBA delivery across regions of Ethiopia. In the multilevel analysis, mothers having primary and above educational status, health insurance coverage, and mothers from households with higher wealth status had higher odds of SBA delivery. Being multi and grand multiparous, perception of distance from the health facility as big problem, rural residence, women residing in communities with medium and higher poverty level, and women residing in communities with higher childcare burden had lower odds of SBA delivery.ConclusionSkilled birth attendant delivery had spatial variations across the country. Areas with non-skilled birth attendant delivery and mothers who had no formal education, not health insured, mothers from poor households and communities, Primiparous women, mothers from remote areas, and mothers from communities with higher childcare burden could get special attention in terms of allocation of resources including skilled human power, and improved access to health facilities.

Dataset Information

Exploring Determinants of Spatial Variations in the Dengue Fever Epidemic Using Geographically Weighted Regression Model: A Case Study in the Joint Guangzhou-Foshan Area, China, 2014.

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