ArticleEnvironmental monitoring and assessment2020
GIS-based spatial analysis: basic sanitation services in Parana State, Southern Brazil.
Article in Environmental monitoring and assessment, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Synthesis of water, sanitation, and hygiene (WaSH) spatial pattern in rural India: an integrated interpretation of WaSH practices.Environmental science and pollution research international · 2022Article
- Analysis of the spatial distribution and influencing factors of China national forest villages.Environmental monitoring and assessment · 2022Article
- Optimal layout of tourist toilets using resilience theory: An empirical study on Dunhua City in ethnic region of China.PloS one · 2021Article
- Coronavirus disease and basic sanitation: too early to be worried?Revista da Sociedade Brasileira de Medicina Tropical · 2020Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The objective of this study is to provide a view of the geographic distribution of basic sanitation services offered in Parana, Brazil. Temporal distributions, spatial patterns, and clusters were determined using 2000, 2010, and 2016 data. Tabular data of the percentages of households receiving water supply, waste collection, and sanitary sewage treatments were used as the basic inputs of the study. Time series maps were created using geographic information systems (GIS) for the visualization of the temporal changes in basic sanitation rates. The spatial variation in sanitation services was measured using Moran's Global Index (Moran's I), while the Local Indicators of Spatial Association (LISA) and Getis-Ord Gi*(d) were used to identify the presence of possible clusters and hot spots in the percentage of households with sanitation services. The study showed strong evidence that the service rates for sanitary sewage were significantly lower than those for water supply and waste collection. Waste collection proved to have the highest service rate in the study area. Waste collection was also the service that increased the most in the study period, followed by the water supply service. Identification of the most vulnerable municipalities was performed using LISA and the local Getis-Ord Gi*(d) statistic. Most of the low value clusters and cold spots were detected in the southern and west-central regions, while the high value hot spots and clusters were detected in the northern and northeastern regions of the state of Parana.
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