Vulnerability to the transmission of human visceral leishmaniasis in a Brazilian urban area

ABSTRACT OBJECTIVE To analyze the determinants for the occurrence of human visceral leishmaniasis linked to the conditions of vulnerability. METHODS This is an ecological study, whose spatial analysis unit was the Territorial Analysis Unit in Araguaína, State of Tocantins, Brazil, from 2007 to 2012. We have carried out an analysis of the sociodemographic and urban infrastructure situation of the municipality. Normalized primary indicators were calculated and used to construct the indicators of vulnerability of the social structure, household structure, and urban infrastructure. From them, we have composed a vulnerability index. Kernel density estimation was used to evaluate the density of cases of human visceral leishmaniasis, based on the coordinates of the cases. Bivariate global Moran’s I was used to verify the existence of spatial autocorrelation between the incidence of human visceral leishmaniasis and the indicators and index of vulnerability. Bivariate local Moran’s I was used to identify spatial clusters. RESULTS We have observed a pattern of centrifugal spread of human visceral leishmaniasis in the municipality, where outbreaks of the disease have progressively reached central and peri-urban areas. There has been no correlation between higher incidences of human visceral leishmaniasis and worse living conditions. Statistically significant clusters have been observed between the incidences of human visceral leishmaniasis in both periods analyzed (2007 to 2009 and 2010 to 2012) and the indicators and index of vulnerability. CONCLUSIONS The environment in circumscribed areas helps as protection factor or increases the local vulnerability to the occurrence of human visceral leishmaniasis. The use of methodology that analyzes the conditions of life of the population and the spatial distribution of human visceral leishmaniasis is essential to identify the most vulnerable areas to the spread/maintenance of the disease.

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Analisis Perubahan Tata Guna Lahan di Kabupaten Bantul Menggunakan Metode Global Moran’s I

Jurnal Buana Informatika ◽

10.24002/jbi.v8i4.1446 ◽

2017 ◽

Vol 8 (4) ◽

Cited By ~ 1

Author(s):

Matheus Supriyanto Rumetna ◽

Eko Sediyono ◽

Kristoko Dwi Hartomo

Keyword(s):

Land Use ◽

Land Use Change ◽

Spatial Autocorrelation ◽

Land Use Changes ◽

Geographical Information ◽

Moran’S I ◽

Complete Spatial Randomness ◽

Moran's I ◽

Global Moran’S I ◽

Spatial Randomness

Abstract. Bantul Regency is a part of Yogyakarta Special Province Province which experienced land use changes. This research aims to assess the changes of shape and level of land use, to analyze the pattern of land use changes, and to find the appropriateness of RTRW land use in Bantul District in 2011-2015. Analytical methods are employed including Geoprocessing techniques and analysis of patterns of distribution of land use changes with Spatial Autocorrelation (Global Moran's I). The results of this study of land use in 2011, there are thirty one classifications, while in 2015 there are thirty four classifications. The pattern of distribution of land use change shows that land use change in 2011-2015 has a Complete Spatial Randomness pattern. Land use suitability with the direction of area function at RTRW is 24030,406 Ha (46,995406%) and incompatibility of 27103,115 Ha or equal to 53,004593% of the total area of Bantul Regency.Keywords: Geographical Information System, Land Use, Geoprocessing, Global Moran's I, Bantul Regency. Abstrak. Analisis Perubahan Tata Guna Lahan di Kabupaten Bantul Menggunakan Metode Global Moran’s I. Kabupaten Bantul merupakan bagian dari Provinsi Daerah Istimewa Yogyakarta yang mengalami perubahan tata guna lahan. Penelitian ini bertujuan untuk mengkaji perubahan bentuk dan luas penggunaan lahan, menganalisis pola sebaran perubahan tata guna lahan, serta kesesuaian tata guna lahan terhadap RTRW yang terjadi di Kabupaten Bantul pada tahun 2011-2015. Metode analisis yang digunakan antara lain teknik Geoprocessing serta analisis pola sebaran perubahan tata guna lahan dengan Spatial Autocorrelation (Global Moran’s I). Hasil dari penelitian ini adalah penggunaan tanah pada tahun 2011, terdapat tiga puluh satu klasifikasi, sedangkan pada tahun 2015 terdapat tiga puluh empat klasifikasi. Pola sebaran perubahan tata guna lahan menunjukkan bahwa perubahan tata guna lahan tahun 2011-2015 memiliki pola Complete Spatial Randomness. Kesesuaian tata guna lahan dengan arahan fungsi kawasan pada RTRW adalah seluas 24030,406 Ha atau mencapai 46,995406 % dan ketidaksesuaian seluas 27103,115 Ha atau sebesar 53,004593 % dari total luas wilayah Kabupaten Bantul. Kata Kunci: Sistem Informasi Georafis, tata guna lahan, Geoprocessing, Global Moran’s I, Kabupaten Bantul.

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Spatial Autocorrelation in the Study of Neighbourhoods towards Smart Cities: Empirical Evidence from Kerman, Iran

Scientific Research Journal ◽

10.24191/srj.v9i2.9405 ◽

2012 ◽

Vol 9 (2) ◽

pp. 1

Author(s):

Asra Hosseini

Keyword(s):

Spatial Autocorrelation ◽

Urban Areas ◽

Smart Cities ◽

Moran’S I ◽

Moran's I ◽

Urban Planner ◽

Universal Feature ◽

Autocorrelation Method ◽

Selection Of

From earliest cities to the present, spatial division into residential zones and neighbourhoods is the universal feature of urban areas. This study explored issue of measuring neighbourhoods through spatial autocorrelation method based on Moran's I index in respect of achieving to best neighbourhoods' model for forming cities smarter. The research carried out by selection of 35 neighbourhoods only within central part of traditional city of Kerman in Iran. The results illustrate, 75% of neighbourhoods' area in the inner city of Kerman had clustered pattern, and it shows reduction in Moran's index is associated with disproportional distribution of density and increasing in Moran's I and Z-score have monotonic relation with more dense areas and clustered pattern. It may be more efficient for urban planner to focus on spatial autocorrelation to foster neighbourhood cohesion rather than emphasis on suburban area. It is recommended characteristics of historic neighbourhoods can be successfully linked to redevelopment plans toward making city smarter, and also people's quality of life can be related to the way that neighbourhoods' patterns are defined.

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Geographical variations and associated factors of defaulting from immunization among children aged 12 to 23 months in Ethiopia: using spatial and multilevel analysis of 2016 Ethiopian Demographic and Health Survey

Environmental Health and Preventive Medicine ◽

10.1186/s12199-021-00984-8 ◽

2021 ◽

Vol 26 (1) ◽

Author(s):

Mukemil Awol ◽

Zewdie Aderaw Alemu ◽

Nurilign Abebe Moges ◽

Kemal Jemal

Keyword(s):

Multilevel Analysis ◽

Health Survey ◽

Associated Factors ◽

Demographic And Health Survey ◽

Community Level ◽

Scan Statistics ◽

Moran’S I ◽

Moran's I ◽

Depth Analysis ◽

Global Moran’S I

Abstract Background In Ethiopia, despite the considerable improvement in immunization coverage, the burden of defaulting from immunization among children is still high with marked variation among regions. However, the geographical variation and contextual factors of defaulting from immunization were poorly understood. Hence, this study aimed to identify the spatial pattern and associated factors of defaulting from immunization. Methods An in-depth analysis of the 2016 Ethiopian Demographic and Health Survey (EDHS 2016) data was used. A total of 1638 children nested in 552 enumeration areas (EAs) were included in the analysis. Global Moran’s I statistic and Bernoulli purely spatial scan statistics were employed to identify geographical patterns and detect spatial clusters of defaulting immunization, respectively. Multilevel logistic regression models were fitted to identify factors associated with defaulting immunization. A p value < 0.05 was used to identify significantly associated factors with defaulting of child immunization. Results A spatial heterogeneity of defaulting from immunization was observed (Global Moran’s I = 0.386379, p value < 0.001), and four significant SaTScan clusters of areas with high defaulting from immunization were detected. The most likely primary SaTScan cluster was seen in the Somali region, and secondary clusters were detected in (Afar, South Nation Nationality of people (SNNP), Oromiya, Amhara, and Gambella) regions. In the final model of the multilevel analysis, individual and community level factors accounted for 56.4% of the variance in the odds of defaulting immunization. Children from mothers who had no formal education (AOR = 4.23; 95% CI: 117, 15.78), and children living in Afar, Oromiya, Somali, SNNP, Gambella, and Harari regions had higher odds of having defaulted immunization from community level. Conclusions A clustered pattern of areas with high default of immunization was observed in Ethiopia. Both the individual and community-level characteristics were statistically significant factors of defaulting immunization. Therefore, the Federal Ethiopian Ministry of Health should prioritize the areas with defaulting of immunization and consider the identified factors for immunization interventions.

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Formation of the organizational-managerial model of renovation of urban territories

MATEC Web of Conferences ◽

10.1051/matecconf/201819604029 ◽

2018 ◽

Vol 196 ◽

pp. 04029 ◽

Cited By ~ 21

Author(s):

Dmitriy Topchiy ◽

Andrey Tokarskiy

Keyword(s):

Urban Areas ◽

Urban Infrastructure ◽

Comprehensive Analysis ◽

Social Needs ◽

Added Value ◽

Special Role ◽

The Social ◽

Urban Territories ◽

Production Areas ◽

The City

The pace of modern urban development dictates special requirements for the structure of zoning and the designation of the territories of megacities. Formed requirements for the objects of residential and recreational areas, urban infrastructure and communications facilities. A special role in the issue of improving the comfort of the urban environment, is the process of renovation of production areas. One of the main principles of urban planning is the location of production in the outskirts of cities and settlements. However, with the development of urban areas, once located at the disposal of production, are surrounded by residential and administrative-office blocks. This “neighborhood” not only causes discomfort to residents, but also creates an excessive environmental burden on the environment. In addition, the territory of the city, and especially large megacities, have a much higher cadastral value of land, and, therefore, create an additional tax burden on production, as added value to the output. All these elements make the products uncompetitive, especially in comparison with similar products produced outside the metropolitan area. Thus, the process of output of production beyond the city limits is actually cyclical and uninterrupted. Territories that remain after the withdrawal of production facilities are subject to comprehensive analysis, taking into account the social needs of the city, and further renovation.

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Analysis on Spatial Difference of the Rural Resident’s per Capita Net Income in Qinhuangdao City Based on ESDA

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.955-959.3893 ◽

2014 ◽

Vol 955-959 ◽

pp. 3893-3898

Author(s):

Yu Hong Wu

Keyword(s):

Spatial Data ◽

Rural Economy ◽

Spatial Association ◽

Spatial Data Analysis ◽

Moran’S I ◽

Net Income ◽

Gis Technology ◽

Moran's I ◽

Per Capita ◽

Global Moran’S I

Based on the exploratory spatial data analysis (ESDA) and GIS technology, the spatial differences of the rural economic development level of Qinhuangdao city was investigated by adopting the rural resident’s per capita net income data at town level in Qinhuangdao city from 2007 to 2011. The results of global Moran’s I value for rural resident’s per capita net income at town level showed that there existed significant positive spatial autocorrelation and significant spatial aggregation in the spatial distribution of rural resident’s per capita net income. However, the global Moran’s I value showed a decreasing trend during 2007 to 2011, indicating an enlarged spatial disparity of rural economy at the town level. The results of the Moran scatter plots and LISA cluster maps of 2007 and 2011 showed that most of towns were characterized by positive local spatial association , ie. They were located in the HH or the LL quadrant. The significant HH towns were mostly to be found in the south of Qinhuangdao city, Haigang district, Changli county, Lulong county. The significant LL towns were mostly to be found in the Qinglong county, north of Qinhuangdao city.

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Spatial-temporal Patterns and Risk Factors for Human Leptospirosis in Thailand, 2012-2018

10.21203/rs.3.rs-842308/v1 ◽

2021 ◽

Author(s):

Sudarat Chadsuthi ◽

Karine Chalvet-Monfray ◽

Suchada Geawduanglek ◽

Phrutsamon Wongnak ◽

Julien Cappelle

Keyword(s):

Risk Factors ◽

High Risk ◽

Significant Risk ◽

Temporal Correlation ◽

Moran’S I ◽

Moran's I ◽

Temperature Range ◽

Flood Exposure ◽

Flooded Area ◽

Global Moran’S I

Abstract Leptospirosis is a globally important zoonotic disease. The disease is particularly important in tropical and subtropical countries. Infections in humans can be caused by exposure to infected animals or contaminated soil or water, which are suitable for Leptospira. To explore the cluster area, the Global Moran’s I index was calculated for incidences per 100,000 population at the province level during 2012–2018, using the monthly and annual data. The high-risk and low-risk provinces were identified using the local indicators of spatial association (LISA). The risk factors for leptospirosis were evaluated using a generalized linear mixed model (GLMM) with zero-inflation. We also added spatial and temporal correlation terms to take into account the spatial and temporal structures. The Global Moran’s I index showed significant positive values. It did not demonstrate a random distribution throughout the period of study. The high-risk provinces were almost all in the lower north-east and south parts of Thailand. For yearly reported cases, the significant risk factors from the final best-fitted model were population density, elevation, and primary rice arable areas. Interestingly, our study showed that leptospirosis cases were associated with large areas of rice production but were less prevalent in areas of high rice productivity. For monthly reported cases, the model using temperature range was found to be a better fit than using percentage of flooded area. The significant risk factors from the model using temperature range were temporal correlation, average soil moisture, normalized difference vegetation index, and temperature range. Temperature range, which has strongly negative correlation to percentage of flooded area was a significant risk factor for monthly data. Flood exposure controls should be used to reduce the risk of leptospirosis infection. These results could be used to develop a leptospirosis warning system to support public health organizations in Thailand.

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Geospatial patterns of comorbidity prevalence among people with osteoarthritis in Alberta Canada

BMC Public Health ◽

10.1186/s12889-020-09599-0 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Xiaoxiao Liu ◽

Rizwan Shahid ◽

Alka B. Patel ◽

Terrence McDonald ◽

Stefania Bertazzon ◽

...

Keyword(s):

First Nations ◽

Rural Areas ◽

Urban Areas ◽

Hot Spot ◽

Local Level ◽

Moran’S I ◽

Local Health ◽

Case Definitions ◽

Moran's I ◽

Remote Areas

Abstract Background Knowledge of geospatial pattern in comorbidities prevalence is critical to an understanding of the local health needs among people with osteoarthritis (OA). It provides valuable information for targeting optimal OA treatment and management at the local level. However, there is, at present, limited evidence about the geospatial pattern of comorbidity prevalence in Alberta, Canada. Methods Five administrative health datasets were linked to identify OA cases and comorbidities using validated case definitions. We explored the geospatial pattern in comorbidity prevalence at two standard geographic areas levels defined by the Alberta Health Services: descriptive analysis at rural-urban continuum level; spatial analysis (global Moran’s I, hot spot analysis, cluster and outlier analysis) at the local geographic area (LGA) level. We compared area-level indicators in comorbidities hotspots to those in the rest of Alberta (non-hotspots). Results Among 359,638 OA cases in 2013, approximately 60% of people resided in Metro and Urban areas, compared to 2% in Rural Remote areas. All comorbidity groups exhibited statistically significant spatial autocorrelation (hypertension: Moran’s I index 0.24, z score 4.61). Comorbidity hotspots, except depression, were located primarily in Rural and Rural Remote areas. Depression was more prevalent in Metro (Edmonton-Abbottsfield: 194 cases per 1000 population, 95%CI 192–195) and Urban LGAs (Lethbridge-North: 169, 95%CI 168–171) compared to Rural areas (Fox Creek: 65, 95%CI 63–68). Comorbidities hotspots included a higher percentage of First Nations or Inuit people. People with OA living in hotspots had lower socioeconomic status and less access to care compared to non-hotspots. Conclusions The findings highlight notable rural-urban disparities in comorbidities prevalence among people with OA in Alberta, Canada. Our study provides valuable evidence for policy and decision makers to design programs that ensure patients with OA receive optimal health management tailored to their local needs and a reduction in current OA health disparities.

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Spatial statistical analysis of Coronavirus Disease 2019 (Covid-19) in China

Geospatial health ◽

10.4081/gh.2020.867 ◽

2020 ◽

Vol 15 (1) ◽

Cited By ~ 1

Author(s):

Huling Li ◽

Hui Li ◽

Zhongxing Ding ◽

Zhibin Hu ◽

Feng Chen ◽

...

Keyword(s):

Cluster Analysis ◽

Statistical Analysis ◽

Spatial Patterns ◽

Moran’S I ◽

Cumulative Number ◽

Moran's I ◽

Spatial Statistical Analysis ◽

Global Concern ◽

And Cluster Analysis ◽

Global Moran’S I

The cluster of pneumonia cases linked to coronavirus disease 2019 (Covid-19), first reported in China in late December 2019 raised global concern, particularly as the cumulative number of cases reported between 10 January and 5 March 2020 reached 80,711. In order to better understand the spread of this new virus, we characterized the spatial patterns of Covid-19 cumulative cases using ArcGIS v.10.4.1 based on spatial autocorrelation and cluster analysis using Global Moran’s I (Moran, 1950), Local Moran’s I and Getis-Ord General G (Ord and Getis, 2001). Up to 5 March 2020, Hubei Province, the origin of the Covid-19 epidemic, had reported 67,592 Covid-19 cases, while the confirmed cases in the surrounding provinces Guangdong, Henan, Zhejiang and Hunan were 1351, 1272, 1215 and 1018, respectively. The top five regions with respect to incidence were the following provinces: Hubei (11.423/10,000), Zhejiang (0.212/10,000), Jiangxi (0.201/10,000), Beijing (0.196/10,000) and Chongqing (0.186/10,000). Global Moran’s I analysis results showed that the incidence of Covid-19 is not negatively correlated in space (p=0.407413>0.05) and the High-Low cluster analysis demonstrated that there were no high-value incidence clusters (p=0.076098>0.05), while Local Moran’s I analysis indicated that Hubei is the only province with High-Low aggregation (p<0.0001).

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Human visceral leishmaniasis: factors associated with deaths in Belo Horizonte, Minas Gerais state, Brazil from 2006 to 2013

Epidemiology and Infection ◽

10.1017/s0950268818000109 ◽

2018 ◽

Vol 146 (5) ◽

pp. 565-570 ◽

Cited By ~ 4

Author(s):

F. R. P. Bruhn ◽

M. H. F. Morais ◽

N. C. P. Bruhn ◽

D. L. Cardoso ◽

F. Ferreira ◽

...

Keyword(s):

Risk Factors ◽

Visceral Leishmaniasis ◽

Minas Gerais ◽

Skin Colour ◽

Social Risk ◽

Social Risk Factors ◽

Human Visceral Leishmaniasis ◽

The Social ◽

Minas Gerais State ◽

Belo Horizonte

AbstractThe aim of this study was to evaluate the distribution of cases and the social determinants associated with death from human visceral leishmaniasis (HVL) and VL–HIV co-infection in Belo Horizonte, Minas Gerais state, Brazil, between 2006 and 2013. Descriptive statistics and analysis of associations were performed using chi-square of the raised variables, such as sex, age, skin colour and schooling of cases of HVL. During the study period, there were 866 cases of HVL with 111 deaths in Belo Horizonte. Morbidity and lethality rates (LR) of HVL in Belo Horizonte remained high over almost all the years evaluated, with an average incidence rate of 4.18 cases/100 000 inhabitants and a LR of 11.16%. With respect to skin colour, it was found that people characterised as black or mulatto had higher morbidity, followed by white. Regarding schooling, LR was more prevalent among individuals with lower education. One of the social risk factors was co-infection with HIV, which was present in many cases of HVL. Furthermore, it was found that older age and the male sex were also risk factors for death from HVL in Belo Horizonte.

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Spatially Varying Relationships between Land Subsidence and Urbanization: A Case Study in Wuhan, China

Remote Sensing ◽

10.3390/rs14020291 ◽

2022 ◽

Vol 14 (2) ◽

pp. 291

Author(s):

Zhengyu Wang ◽

Yaolin Liu ◽

Yang Zhang ◽

Yanfang Liu ◽

Baoshun Wang ◽

...

Keyword(s):

Spatial Pattern ◽

Land Subsidence ◽

Urban Areas ◽

Spatial Scales ◽

Moran’S I ◽

Anthropogenic Factors ◽

Spatial Correlations ◽

Moran's I ◽

Average Value ◽

Gwr Model

Land subsidence has become an increasing global concern over the past few decades due to natural and anthropogenic factors. However, although several studies have examined factors affecting land subsidence in recent years, few have focused on the spatial heterogeneity of relationships between land subsidence and urbanization. In this paper, we adopted the small baseline subset-synthetic aperture radar interferometry (SBAS-InSAR) method using Sentinel-1 radar satellite images to map land subsidence from 2015 to 2018 and characterized its spatial pattern in Wuhan. The bivariate Moran’s I index was used to test and visualize the spatial correlations between land subsidence and urbanization. A geographically weighted regression (GWR) model was employed to explore the strengths and directions of impacts of urbanization on land subsidence. Our findings showed that land subsidence was obvious and unevenly distributed in the study area, the annual deformation rate varied from −42.85 mm/year to +29.98 mm/year, and its average value was −1.0 mm/year. A clear spatial pattern for land subsidence in Wuhan was mapped, and several apparent subsidence funnels were primarily located in central urban areas. All urbanization indicators were found to be significantly spatially correlated with land subsidence at different scales. In addition, the GWR model results showed that all urbanization indicators were significantly associated with land subsidence across the whole study area in Wuhan. The results of bivariate Moran’s I and GWR results confirmed that the relationships between land subsidence and urbanization spatially varied in Wuhan at multiple spatial scales. Although scale dependence existed in both the bivariate Moran’s I and GWR models for land subsidence and urbanization indicators, a “best” spatial scale could not be confirmed because the disturbance of factors varied over different sampling scales. The results can advance the understanding of the relationships between land subsidence and urbanization, and they will provide guidance for subsidence control and sustainable urban planning.

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