Water insecurity and gendered risk for depression in rural Uganda: a hotspot analysis

Three very different field sites—First Nations communities in Canada, water charities in the Global South, and the US cities of Flint and Detroit, Michigan—point to the increasing precariousness of water access for historically marginalized groups, including Indigenous peoples, African Americans, and people of color around the globe. This multi-sited ethnography underscores a common theme: power and racism lie deep in the core of today’s global water crisis. These cases reveal the concrete mechanisms, strategies, and interconnections that are galvanized by the economic, political, and racial projects of neoliberalism. In this sense neoliberalism is not only downsizing democracy but also creating both the material and ideological forces for a new form of discrimination in the provision of drinking water around the globe. These cases suggest that contemporary notions of environmental and social justice will largely hinge on how we come to think about water in the twenty-first century.

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Spatial Hotspot Analysis of Bucharest’s Urban Heat Island (UHI) Using Modis Data

Annals of Valahia University of Targoviste Geographical Series ◽

10.2478/avutgs-2018-0002 ◽

2018 ◽

Vol 18 (1) ◽

pp. 14-22 ◽

Cited By ~ 1

Author(s):

Georgiana Grigoraș ◽

Bogdan Urițescu

Keyword(s):

Surface Temperature ◽

Air Temperature ◽

Land Surface Temperature ◽

Hot Spots ◽

Land Surface ◽

Hot Spot ◽

Monitoring Network ◽

Residential Areas ◽

Hotspot Analysis ◽

The City

Abstract The aim of the study is to find the relationship between the land surface temperature and air temperature and to determine the hot spots in the urban area of Bucharest, the capital of Romania. The analysis was based on images from both moderate-resolution imaging spectroradiometer (MODIS), located on both Terra and Aqua platforms, as well as on data recorded by the four automatic weather stations existing in the endowment of The National Air Quality Monitoring Network, from the summer of 2017. Correlation coefficients between land surface temperature and air temperature were higher at night (0.8-0.87) and slightly lower during the day (0.71-0.77). After the validation of satellite data with in-situ temperature measurements, the hot spots in the metropolitan area of Bucharest were identified using Getis-Ord spatial statistics analysis. It has been achieved that the “very hot” areas are grouped in the center of the city and along the main traffic streets and dense residential areas. During the day the "very hot spots” represent 33.2% of the city's surface, and during the night 31.6%. The area where the mentioned spots persist, falls into the "very hot spot" category both day and night, it represents 27.1% of the city’s surface and it is mainly represented by the city center.

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Geospatial Analysis of COVID-19: A Scoping Review

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18052336 ◽

2021 ◽

Vol 18 (5) ◽

pp. 2336

Author(s):

Munazza Fatima ◽

Kara J. O’Keefe ◽

Wenjia Wei ◽

Sana Arshad ◽

Oliver Gruebner

Keyword(s):

Disease Mapping ◽

Geospatial Analysis ◽

Hotspot Analysis ◽

Spatial Studies ◽

Epidemiological Modeling ◽

Wide Range ◽

Scoping Reviews ◽

Disease Pattern ◽

The Usa ◽

Meta Analyses

The outbreak of SARS-CoV-2 in Wuhan, China in late December 2019 became the harbinger of the COVID-19 pandemic. During the pandemic, geospatial techniques, such as modeling and mapping, have helped in disease pattern detection. Here we provide a synthesis of the techniques and associated findings in relation to COVID-19 and its geographic, environmental, and socio-demographic characteristics, following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) methodology for scoping reviews. We searched PubMed for relevant articles and discussed the results separately for three categories: disease mapping, exposure mapping, and spatial epidemiological modeling. The majority of studies were ecological in nature and primarily carried out in China, Brazil, and the USA. The most common spatial methods used were clustering, hotspot analysis, space-time scan statistic, and regression modeling. Researchers used a wide range of spatial and statistical software to apply spatial analysis for the purpose of disease mapping, exposure mapping, and epidemiological modeling. Factors limiting the use of these spatial techniques were the unavailability and bias of COVID-19 data—along with scarcity of fine-scaled demographic, environmental, and socio-economic data—which restrained most of the researchers from exploring causal relationships of potential influencing factors of COVID-19. Our review identified geospatial analysis in COVID-19 research and highlighted current trends and research gaps. Since most of the studies found centered on Asia and the Americas, there is a need for more comparable spatial studies using geographically fine-scaled data in other areas of the world.

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Spatial distribution and determinant factors of anemia among adults aged 15–59 in Ethiopia; using mixed-effects ordinal logistic regression model

BMC Nutrition ◽

10.1186/s40795-021-00424-4 ◽

2021 ◽

Vol 7 (1) ◽

Author(s):

Biruk Shalmeno Tusa ◽

Sewnet Adem Kebede ◽

Adisu Birhanu Weldesenbet

Keyword(s):

Public Health ◽

Spatial Distribution ◽

Scan Statistics ◽

Moran’S I ◽

Demographic And Health Surveys ◽

Targeted Prevention ◽

Hotspot Analysis ◽

Mixed Effect ◽

Moran's I ◽

Determinant Factors

Abstract Background Anemia is a global public health problem, particularly in developing countries. Assessing the geographic distributions and determinant factors is a key and crucial step in designing targeted prevention and intervention programmes to address anemia. Thus, the current study is aimed to assess the spatial distribution and determinant factors of anemia in Ethiopia among adults aged 15–59. Methods A secondary data analysis was done based on 2016 Ethiopian Demographic and Health Surveys (EDHS). Total weighted samples of 29,140 adults were included. Data processing and analysis were performed using STATA 14; ArcGIS 10.1 and SaTScan 9.6 software. Spatial autocorrelation was checked using Global Moran’s index (Moran’s I). Hotspot analysis was made using Gettis-OrdGi*statistics. Additionally, spatial scan statistics were applied to identify significant primary and secondary cluster of anemia. Mixed effect ordinal logistics were fitted to determine factors associated with the level of anemia. Result The spatial distribution of anemia in Ethiopia among adults age 15–59 was found to be clustered (Global Moran’s I = 0.81, p value < 0.0001). In the multivariable mixed-effectordinal regression analysis; Females [AOR = 1.53; 95% CI: 1.42, 1.66], Never married [AOR = 0.86; 95% CI: 0.77, 0.96], highly educated [AOR = 0.71; 95% CI: 0.60, 0.84], rural residents [AOR = 1.53; 95% CI: 1.23, 1.81], rich wealth status [AOR = 0.77; 95% CI: 0.69, 0.86] and underweight [AOR = 1.15; 1.06, 1.24] were significant predictors of anemia among adults. Conclusions A significant clustering of anemia among adults aged 15–59 were found in Ethiopia and the significant hotspot areas with high cluster anemia were identified in Somalia, Afar, Gambella, Dire Dewa and Harari regions. Besides, sex, marital status, educational level, place of residence, region, wealth index and BMI were significant predictors of anemia. Therefore, effective public health intervention and nutritional education should be designed for the identified hotspot areas and risk groups in order to decrease the incidence of anemia.

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Addressing Water Insecurity with a Greywater Hydroponics System in South Africa

2020 IEEE Global Humanitarian Technology Conference (GHTC) ◽

10.1109/ghtc46280.2020.9342850 ◽

2020 ◽

Author(s):

Carson Edgerton ◽

Alex Estrada ◽

Katya Fairchok ◽

Michele T. Parker ◽

Andrew Jezak ◽

...

Keyword(s):

South Africa ◽

Water Insecurity

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Modeling spatial determinates of teenage pregnancy in Ethiopia; geographically weighted regression

BMC Women s Health ◽

10.1186/s12905-021-01400-7 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Seblewongel Tigabu ◽

Alemneh Mekuriaw Liyew ◽

Bisrat Misganaw Geremew

Keyword(s):

Spatial Distribution ◽

Geographically Weighted Regression ◽

Teenage Pregnancy ◽

Wealth Quintile ◽

Ordinary Least Squares ◽

Weighted Regression ◽

Contraceptive Methods ◽

Hotspot Analysis ◽

Increased Risk ◽

Risk Areas

Abstract Background In developing countries, 20,000 under 18 children give birth every day. In Ethiopia, teenage pregnancy is high with Afar and Somalia regions having the largest share. Even though teenage pregnancy has bad maternal and child health consequences, to date there is limited evidence on its spatial distribution and driving factors. Therefore, this study is aimed to assess the spatial distribution and spatial determinates of teenage pregnancy in Ethiopia. Methods A secondary data analysis was conducted using 2016 EDHS data. A total weighted sample of 3381 teenagers was included. The spatial clustering of teenage pregnancy was priorly explored by using hotspot analysis and spatial scanning statistics to indicate geographical risk areas of teenage pregnancy. Besides spatial modeling was conducted by applying Ordinary least squares regression and geographically weighted regression to determine factors explaining the geographic variation of teenage pregnancy. Result Based on the findings of exploratory analysis the high-risk areas of teenage pregnancy were observed in the Somali, Afar, Oromia, and Hareri regions. Women with primary education, being in the household with a poorer wealth quintile using none of the contraceptive methods and using traditional contraceptive methods were significant spatial determinates of the spatial variation of teenage pregnancy in Ethiopia. Conclusion geographic areas where a high proportion of women didn’t use any type of contraceptive methods, use traditional contraceptive methods, and from households with poor wealth quintile had increased risk of teenage pregnancy. Whereas, those areas with a higher proportion of women with secondary education had a decreased risk of teenage pregnancy. The detailed maps of hotspots of teenage pregnancy and its predictors had supreme importance to policymakers for the design and implementation of adolescent targeted programs.

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