scholarly journals Geography matters for sanitation! Spatial heterogeneity of the district‐level correlates of open defecation in India

Author(s):  
Saurav Chakraborty ◽  
Josef Novotný ◽  
Jadab Das ◽  
Aditi Bardhan ◽  
Srijanee Roy ◽  
...  
2020 ◽  
Author(s):  
Saurav Chakraborty ◽  
Josef Novotný ◽  
Jadab Das ◽  
Aditi Bardahn ◽  
Srijanee Roy ◽  
...  

Abstract Background: Sanitation interventions often fail in meeting the desired expectations. A prominent reason is the ecological nature of sanitation phenomena that inherently associates with its high dependence on contextual specifics. This also constrains the generalization of research findings in this domain and substantiates the need to supplement most prevalent micro-level evidence with wider population-level (ecological) studies. This paper thus provides the first quantitative analysis of the spatial heterogeneity of the district-level correlates of open defecation in India. It focuses on a contiguous region of 266 districts (their rural parts) comprising of seven northern and eastern Indian states, all of which had comparatively high open defecation rates in 2011.Methods: We employ standard non-spatial regression, spatially explicit regressions and multi-scale geographically weighted regression to compare the stability of the measurable correlates of open defecation across these different methods as well as across the analyzed spatial units. Results: Attributes like the ownership of household assets, drinking water inaccessibility and prevalent literacy rates were identified as the most stable district-level correlates of open defecation in this region. A higher share of Muslims in the population positively correlated with lower open defecation rates, while this relationship was amplified by the population density. This finding support hypotheses about the positive sanitation externalities stemming from the spatial co-concentrations of Muslim and non-Muslim populations. Conclusions: Our analyses demonstrate notable spatial clustering and significant spatial non-stationarity of the examined variables. Therefore, research findings that ignore the spatial heterogeneity of sanitation drivers possibly provide incomplete information for practice.


2020 ◽  
Author(s):  
Saurav Chakraborty ◽  
Josef Novotný ◽  
Jadab Das ◽  
Aditi Bardahn ◽  
Srijanee Roy ◽  
...  

Abstract The authors have withdrawn this preprint due to author disagreement.


PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249523
Author(s):  
Isaiah Gwitira ◽  
Norbert Karumazondo ◽  
Munyaradzi Davis Shekede ◽  
Charles Sandy ◽  
Nicolas Siziba ◽  
...  

Introduction Accurate mapping of spatial heterogeneity in tuberculosis (TB) cases is critical for achieving high impact control as well as guide resource allocation in most developing countries. The main aim of this study was to explore the spatial patterns of TB occurrence at district level in Zimbabwe from 2015 to 2018 using GIS and spatial statistics as a preamble to identifying areas with elevated risk for prioritisation of control and intervention measures. Methods In this study Getis-Ord Gi* statistics together with SaTscan were used to characterise TB hotspots and clusters in Zimbabwe at district level from 2015 to 2018. GIS software was used to map and visualise the results of cluster analysis. Results Results show that TB occurrence exhibits spatial heterogeneity across the country. The TB hotspots were detected in the central, western and southern part of the country. These areas are characterised by artisanal mining activities as well as high poverty levels. Conclusions and recommendations Results of this study are useful to guide TB control programs and design effective strategies which are important in achieving the United Nations Sustainable Development goals (UNSDGs).


2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Junaid Khan ◽  
Apurba Shil ◽  
Sanjay K. Mohanty

Abstract Background Although hepatitis B vaccinations have been integrated in the Universal Immunization Program (UIP) in India over a decade, only half of the children are immunized against hepatitis B. The national average in hepatitis B vaccination conceals large variations across states, districts and socio-economic groups. In this context, the aim of this paper is to examine the spatial heterogeneity and contextual determinants of hepatitis B vaccination across the districts of India. Methods Using data of 199,899 children aged 12–59 months from the National Family Health Survey-4 (NFHS-4), 2015–16 we have examined the district level spatial distribution and clustering of hepatitis B vaccination with the help of Moran’s I and Local Indicator of Spatial Autocorrelation (LISA) measures. We investigated the low coverage of HBV vaccination using spatial autoregressive models (SAR) at the meso scale. And we applied multivariate binary logistic regression analysis to understand the micro-level predictors of hepatitis B vaccination. Results In 2015–16, 45% of the children aged 12–59 months were not vaccinated against hepatitis B in India. The coverage of hepatitis B vaccine across the districts of India showed a highly significant spatial dependence (Moran’s I = 0.580). Bivariate Moran’s I confirmed the spatial clustering of hepatitis B vaccination with mother’s education, full antenatal care (ANC) utilization, post natal care (PNC) utilization, institutional births and registration of births at the district level. Districts with a very low coverage of HBV vaccine are clustered in the western, north-eastern regions and in some parts of central India. At the unit (child) level, children’s hepatitis B immunization status is mostly determined by the socio-economic and demographic characteristics like their mother’s educational status, caste, religion, household’s wealth condition, birth order, year of birth and the region they belong to. Conclusions District level variation in hepatitis B vaccination is spatially heterogeneous and clustered in India with a strong neighbourhood effect. Uptake of hepatitis B vaccine among Indian children is predominantly dependent upon their socio-economic and demographic characteristics.


2021 ◽  
Vol 4 (3) ◽  
Author(s):  
Tawanda Manyangadze ◽  
Moses J Chimbari ◽  
Emmanuel Mavhura

This study examined the spatial heterogeneity association of HIV incidence and socio-economic factors including poverty severity index,permanently employed females and males, unemployed females, percentage of poor households i.e., poverty prevalence, night lights index, literacy rate,household food security, and Gini index at district level in Zimbabwe.A mix of spatial analysis methods including Poisson model based on original log likelihood ratios (LLR), global Moran’s I, local indicator of spatial association - LISA were employed to determine the HIV hotspots.Geographically Weighted Poisson Regression (GWPR) and semi-parametric GWPR (s-GWPR) were used to determine the spatial association between HIV incidence and socio-economic factors. HIV incidence (number of cases per 1000) ranged from 0.6 (Buhera district) to 13.30 (Mangwe district). Spatial clustering of HIV incidence was observed (Global Moran’s I = - 0.150; Z score 3.038; p-value 0.002). Significant clusters of HIV were observed at district level. HIV incidence and its association with socioeconomic factors varied across the districts except percentage of females unemployed. Intervention programmes to reduce HIV incidence should address the identified socio-economic factors at district level.


Anemia ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Danielle J. Roberts ◽  
Temesgen Zewotir

Background. Anaemia in children is a significant health problem that receives little attention. This study aimed at determining the factors significantly associated with anaemia in children aged 6 to 59 months in Kenya, Malawi, Tanzania, and Uganda while accounting for the spatial heterogeneity within and between the districts of the four countries. In addition, the performance of the districts with regard to their impact on anaemia was assessed and ranked. Methods. A generalised additive mixed model with a spatial effect based on the geographical coordinates of the clusters was used. A district-level random effect was included to further account for the heterogeneity as well as to rank the performance of the districts based on the best linear unbiased prediction (BLUP). Results. The results depicted significant spatial heterogeneity between and within the districts of the countries. After accounting for such spatial heterogeneity, child-level characteristics (gender, malaria test result, and mother’s highest education level), household-level characteristics (household size, household’s wealth index Z-score, the type of toilet facility available, and the type of place of residence), and the country of residence were found to be significantly associated with the child’s anaemia status. There was a significant interaction between the type of place of residence and the country of residence. Based on the BLUP for the district-level random effect, the top 3 best- and worst-performing districts within each country were identified. Conclusion. The ranking of the performance of the districts allows for the worst-performing districts to be targeted for further research in order to improve their anaemia control strategies, as well as for the best-performing districts to be identified to further determine why they are performing better and then to use these districts as role models in efforts to overcome childhood anaemia.


2020 ◽  
Vol 81 (3) ◽  
pp. 339
Author(s):  
Bhagyashree S. Vadageri ◽  
Lakshmana G. ◽  
Channaveer R.M.
Keyword(s):  

Waterlines ◽  
2015 ◽  
Vol 34 (3) ◽  
pp. 206-209 ◽  
Author(s):  
Sanjay Wijesekera ◽  
Ann Thomas
Keyword(s):  

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