Tests for the Detection of Clustering, Including Scan Statistics

2008 ◽  
pp. 131-158
Keyword(s):  
Scan Statistics

Spatiotemporal clustering, social inequities and the risk of leptospirosis in an endemic area of Brazil: a retrospective spatial modelling

2020 ◽  
Author(s):  
Katyucia O C de Souza ◽  
José Augusto P Góes ◽  
Matheus S Melo ◽  
Paula M G Leite ◽  
Lucas A Andrade ◽  
...  
Keyword(s):  
Urban Areas ◽  
Spatial Regression ◽  
Temporal Trends ◽  
Spatial Dynamics ◽  
Secondary Data ◽  
The State ◽  
Scan Statistics ◽  
Northeastern Brazil ◽  
Metropolitan Region ◽  
Social Inequities

Abstract Background Leptospirosis is an endemic disease in Brazil of social and economic relevance related to behavioural and socioenvironmental factors. This study aimed to analyse the spatiotemporal distribution of the incidence of leptospirosis and its association with social determinants in health in a state of northeastern Brazil. Methods An ecological study of temporal series with techniques of spatial analysis using secondary data of the cases of leptospirosis notified in the Information System of Notifiable Diseases of the state of Sergipe (2008–2017) was conducted. The analysis of temporal trends was performed using Poisson regression. Spatial analyses were performed using the Moran index, the local empirical Bayesian model, scan statistics and spatial regression. Results The incidence rate decreased from 3.66 to 1.44 cases per 100 000 inhabitants in 2008 and 2017, respectively. Leptospirosis was associated with social inequities, mostly affecting males aged 20–49 y living in urban areas. The space-time scan indicated the formation of a risk cluster in municipalities in the metropolitan region of the state. Conclusions The data indicated the persistence of leptospirosis transmission, maintaining a pattern of high endemicity in some municipalities associated with social inequities. The study showed the temporal and spatial dynamics of the disease to better target specific actions for prevention and control.

scholarly journals 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

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.

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

BMC Nutrition ◽  
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.

scholarly journals Exploring spatial variation in BCG vaccination among children 0–35 months in Ethiopia: spatial analysis of Ethiopian Demographic and Health Survey 2016

BMJ Open ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. e043565
Author(s):  
Chilot Desta Agegnehu ◽  
Adugnaw Zeleke Alem
Keyword(s):  
Spatial Variation ◽  
Health Survey ◽  
Addis Ababa ◽  
Public Health Problem ◽  
Demographic And Health Survey ◽  
Scan Statistics ◽  
Major Public Health Problem ◽  
Hotspot Analysis ◽  
Bcg Vaccination ◽  
South West

ObjectiveTuberculosis is a major public health problem and is the second leading cause of death worldwide. BCG vaccination is a life-saving and important part of standard tuberculosis control measures, particularly in Ethiopia where tuberculosis is endemic. The End Tuberculosis Strategy targets of 2020 have not been achieved. Exploring spatial variations in BCG vaccination among children is vital to designing and monitoring effective intervention programmes. Therefore, this study aimed to explore the spatial variation in BCG vaccination among children in Ethiopia.DesignCross-sectional study design.SettingEthiopia.ParticipantsChildren aged 0–35 months.Primary outcomeBCG vaccination coverage.MethodsData from the 2016 Ethiopian Demographic and Health Survey were used and a total of 4453 children aged 0–35 months were included. Spatial autocorrelation analysis, cluster and outlier analysis, hotspot analysis, spatial interpolation, and spatial scan statistics were carried out to identify geographical risk areas for BCG vaccine utilisation. ArcGIS V.10.6 and SaTScan V.9.6 statistical software were employed to explore spatial pattern and significant hotspot areas for BCG vaccination among children.ResultsBCG vaccination was spatially clustered in Ethiopia at the regional level (Global Moran’s I=0.516, p<0.001). A total of 51 most likely clusters of low BCG vaccination were identified in the Somali and Afar regions (log-likelihood ratio=136.58, p<0.001). Significant secondary clusters were also identified in North West Gambela, South Amhara, South West Addis Ababa, North East Southern Nations, Nationalities, and People’s Region, and South West Oromia.ConclusionA low probability of receiving BCG vaccination was found among children in the Somali and Afar regions. Therefore, these areas should be given attention when designing effective immunisation strategies to improve BCG vaccination among children in order to reduce the burden of tuberculosis in Ethiopia.

scholarly journals Spatio-temporal dynamics of schistosomiasis in Rwanda between 2001 and 2012: impact of the national Neglected Tropical Disease control programme

2017 ◽  
Vol 12 (1) ◽  
Author(s):  
Elias Nyandwi ◽  
Tom Veldkamp ◽  
Frank Badu Osei ◽  
Sherif Amer
Keyword(s):  
Temporal Dynamics ◽  
Public Health Problem ◽  
Incidence Rates ◽  
Control Programme ◽  
Scan Statistics ◽  
Major Public Health Problem ◽  
Implementation Phase ◽  
Incidence Data ◽  
Spatio Temporal ◽  
The Impact

Schistosomiasis is recognised as a major public health problem in Rwanda. We aimed to identify the spatio-temporal dynamics of its distribution at a fine-scale spatial resolution and to explore the impact of control programme interventions. Incidence data of Schistosoma mansoni infection at 367 health facilities were obtained for the period 2001-2012. Disease cluster analyses were conducted using spatial scan statistics and geographic information systems. The impact of control interventions was assessed for three distinct sub-periods. Findings demonstrated persisting, emerging and re-emerging clusters of schistosomiasis infection across space and time. The control programme initially caused an abrupt increase in incidence rates during its implementation phase. However, this was followed by declining and disappearing clusters when the programme was fully in place. The findings presented should contribute to a better understanding of the dynamics of schistosomiasis distribution to be used when implementing future control activities, including prevention and elimination efforts.

Multiple Window Discrete Scan Statistics

2004 ◽  
Vol 31 (8) ◽  
pp. 967-980 ◽  
Author(s):  
Joseph Glaz ◽  
Zhenkui Zhang
Keyword(s):  
Scan Statistics ◽  
Multiple Window

Spatial Scan Statistics to Assess Sampling Strategy of Antimicrobial Resistance Monitoring Program

2009 ◽  
Vol 6 (1) ◽  
pp. 15-21 ◽  
Author(s):  
A.R. Vieira ◽  
H. Houe ◽  
H.C. Wegener ◽  
D.M.A. Lo Fo Wong ◽  
R. Bødker ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Monitoring Program ◽  
Sampling Strategy ◽  
Scan Statistics ◽  
Spatial Scan Statistics ◽  
Resistance Monitoring ◽  
Spatial Scan

Two-Dimensional Scan Statistics

2001 ◽  
pp. 273-300
Author(s):  
Joseph Glaz ◽  
Joseph Naus ◽  
Sylvan Wallenstein
Keyword(s):  
Scan Statistics ◽  
Two Dimensional
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