scholarly journals 1442. Spatiotemporal Clusters of Varicella and the Regional Risks through Bayesian Approach: A National Five-year Cohort Analysis

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S802-S802
Author(s):  
Kwan Hong ◽  
Jeehyun Kim ◽  
Sujin Yum ◽  
Raquel Elizabeth Gómez Gómez ◽  
Byung Chul Chun
Keyword(s):  
Risk Factors ◽  
Cigarette Smoking ◽  
Hand Hygiene ◽  
Spatial Autocorrelation ◽  
Alcohol Drinking ◽  
Household Income ◽  
Space Time ◽  
Moran's I ◽  
Regional Factors ◽  
Global Moran’S I

Abstract Background Since varicella epidemics repeatedly occurred in Korea, it is essential to control varicella outbreaks preemptively in the targeted region. Therefore, we aimed to reveal spatiotemporal clusters of varicella and the regional risk factor of varicella incidence at the national level. Methods All varicella cases (defined as ICD-10 codes, B01-B09) from 2013 to 2017 in Korea were extracted from National Health Insurance Service. Of the total, 566,978 cases were realigned spatially by 250 administrative districts of Korea and temporally by a week. Spatial autocorrelation was tested using the global Moran’s I statistics using Monte Carlo simulation. Kulldorff’s prospective space-time scan statistics were used to reveal space-time clusters of varicella. Possible risk factors were extracted from the Korean Statistical Information Service and Community Health Survey of Korea, including hand hygiene perceptions, alcohol and smoking status, the proportion of children under 15 years old, the number of households, and household income by regions. After selecting significant risk factors through non-spatial generalized linear models, a conditional autoregressive spatiotempoal model with Bayesian extension was applied to estimate the regional factors affecting varicella incidence. Results There was spatial autocorrelation using Global Moran’s I statistics (P< 0.01). When the maximum cluster size was limited to 10% of the population, 17 spatiotemporal clusters were detected in specific regions in Korea (figure 1). Low perception of hand hygiene, the high proportion of alcohol drinking and cigarette smoking, high children proportion, low number of familial member, and low household income were associated with varicella spatiotemporal incidence (odds ratio: 0.97, 1.01, 2.31, 1.10, 0.99, 0.99, respectively; 95% credible intervals of all risk factors did not include 1). Figure 1. Space-time prospective clusters of varicella in Korea using varicella incidence from 2013 to 2017. Relative risks ratio of each cluster is described at the point. Conclusion Varicella incidence shows spatiotemporal clustering patterns in specific regions. Since regional factors such as the perception rate of hand hygiene, child proportion, alcohol drinking, cigarette smoking, and low household income affect varicella’s spatiotemporal incidence, strategies for targeted control of high-risk regions are strongly recommended. Disclosures All Authors: No reported disclosures

scholarly journals Spatial Analysis of COVID-19 and Exploration of Its Environmental and Socio-Demographic Risk Factors Using Spatial Statistical Methods: A Case Study of Iran

2020 ◽  
Vol 5 (3) ◽  
pp. 145-154
Author(s):  
Mohsen Shariati ◽  
◽  
Mahsa Jahangiri-rad ◽  
Fatima Mahmud Muhammad ◽  
Jafar Shariati ◽  
...  
Keyword(s):  
Risk Factors ◽  
Spatial Autocorrelation ◽  
Confidence Level ◽  
Hot Spot ◽  
Moran’S I ◽  
Moran's I ◽  
Hot Spot Analysis ◽  
The Relationship ◽  
Global Moran’S I ◽  
Spot Analysis

Background: Iran detected its first COVID-19 case in February 2020 in Qom province, which rapidly spread to other cities in the country. Iran, as one of those countries with the highest number of infected people, has officially reported 1812 deaths from a total number of 23049 confirmed infected cases that we used in the analysis. Materials and Methods: Geographic distribution by the map of calculated incidence rates for COVID -19 in Iran within the period was prepared by GIS 10.6 Spatial autocorrelation (Global Moran’s I) and hot spot analysis were used to assess COVID -19 spatial patterns. The ordinary least square method was used to estimate the relationship between COVID -19 and the risk factors. The next step was to explore Geographically Weighted Regression (GWR) models that might better explain the variation in COVID -19 cases based on the environmental and socio-demographic factors. Results: The spatial autocorrelation (Global Moran’s I) result showed that COVID-19 cases in the studied area were in clustered patterns. For statistically significant positive z-scores, the larger the z-score is, the more intense the clustering of high values (hot spot), such as Semnan, Qom, Isfahan, Mazandaran, Alborz, and Tehran. Hot spot analysis detected clustering of a hot spot with confidence level 99% for Semnan, Qom, Isfahan, Mazandaran, Alborz, and Tehran, as well. The risk factors were removed from the model step by step. Finally, just the distance from the epicenter was adopted in the model. GWR efforts increased the explanatory value of risk factor with better special precision (adjusted R-squared=0.44) Conclusion: The highest CIR was concentrated around Qom. Also, the greater the distance from the center of prevalence (Qom), the fewer the patients. Hot spot analysis also implies that the neighboring provinces of prevalence centers exhibited hot spots with a 99% confidence level. Furthermore, the results of OLS analysis showed the significant correlation of CIR is with the distance from epicenter (Qom). The GWR can result in the spatial granularity providing an opportunity to well understand the relationship between environmental spatial heterogeneity and COVID-19 risk as entailed by the infection of CIR with COVID-19, which would make it possible to better plan managerial policies for public health.

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

2017 ◽  
Vol 8 (4) ◽  
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.

scholarly journals Examining the spread of Aquatic Invasive Species, Bythothephes longimanus, In Inland Lakes Across Ontario

2021 ◽  
Author(s):  
Joseph Arambulo
Keyword(s):  
Invasive Species ◽  
Spatial Autocorrelation ◽  
Aquatic Invasive Species ◽  
Water Flea ◽  
Moran's I ◽  
Secondary Spread ◽  
Independent Variables ◽  
Inland Lakes ◽  
Mean Temperature ◽  
Global Moran’S I

The purpose of this study is to is to examine the secondary spread of Bythothephes longimanus, commonly known as spiny water flea, across inland lakes in Ontario, and potentially determine predictors for the its invasion. Data for 190 inland lakes across 84 quaternary watersheds in Ontario were included in the database. Global Moran's I was used to analyze the spatial autocorrelation of the variables, and McFadden's Rho-Squared was used to determine if a variable was a predictor of invasion. Three independent variables, out of 28, were found to be good predictors of invasion: (1) mean temperature of watersheds during summer (MNTMPWSSU), (2) mean precipitation for watersheds during spring (MNPCPWSSP), and (3) mean precipitation for watersheds during summer (MNPCPWSSU). Of the three, mean precipitation for watersheds during summer was determined to be the best predictor.

scholarly journals Spatiotemporal Characteristics and Risk Factors of the COVID-19 Pandemic in New York State: Implication of Future Policies

2021 ◽  
Vol 10 (9) ◽  
pp. 627
Author(s):  
Anran Zheng ◽  
Tao Wang ◽  
Xiaojuan Li
Keyword(s):  
Risk Factors ◽  
New York ◽  
Environmental Factors ◽  
Spatial Autocorrelation ◽  
Disease Transmission ◽  
New York State ◽  
Space Time ◽  
Spatiotemporal Pattern ◽  
York State ◽  
Time Scan

The Coronavirus disease 2019 (COVID-19) has been spreading in New York State since March 2020, posing health and socioeconomic threats to many areas. Statistics of daily confirmed cases and deaths in New York State have been growing and declining amid changing policies and environmental factors. Based on the county-level COVID-19 cases and environmental factors in the state from March to December 2020, this study investigates spatiotemporal clustering patterns using spatial autocorrelation and space-time scan analysis. Environmental factors influencing the COVID-19 spread were analyzed based on the Geodetector model. Infection clusters first appeared in southern New York State and then moved to the central western parts as the epidemic developed. The statistical results of space-time scan analysis are consistent with those of spatial autocorrelation analysis. The analysis results of Geodetector showed that both temperature and population density were strong indications of the monthly incidence of COVID-19, especially in March and April 2020. There is a trend of increasing interactions between various risk factors. This study explores the spatiotemporal pattern of COVID-19 in New York State over ten months and explains the relationship between the disease transmission and influencing factors.

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

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.

scholarly journals Examining the spread of Aquatic Invasive Species, Bythothephes longimanus, In Inland Lakes Across Ontario

2021 ◽  
Author(s):  
Joseph Arambulo
Keyword(s):  
Invasive Species ◽  
Spatial Autocorrelation ◽  
Aquatic Invasive Species ◽  
Water Flea ◽  
Moran's I ◽  
Secondary Spread ◽  
Independent Variables ◽  
Inland Lakes ◽  
Mean Temperature ◽  
Global Moran’S I

The purpose of this study is to is to examine the secondary spread of Bythothephes longimanus, commonly known as spiny water flea, across inland lakes in Ontario, and potentially determine predictors for the its invasion. Data for 190 inland lakes across 84 quaternary watersheds in Ontario were included in the database. Global Moran's I was used to analyze the spatial autocorrelation of the variables, and McFadden's Rho-Squared was used to determine if a variable was a predictor of invasion. Three independent variables, out of 28, were found to be good predictors of invasion: (1) mean temperature of watersheds during summer (MNTMPWSSU), (2) mean precipitation for watersheds during spring (MNPCPWSSP), and (3) mean precipitation for watersheds during summer (MNPCPWSSU). Of the three, mean precipitation for watersheds during summer was determined to be the best predictor.

scholarly journals The Prevalence and Severity of Depression, Anxiety and Stress Among Medical Undergraduate Students of Arsi University and Their Association With Substance Use, Southeast Ethiopia.

2021 ◽  
Author(s):  
Leta Melaku ◽  
Guta Bulcha ◽  
Deresa Worku
Keyword(s):  
Risk Factors ◽  
Medical Students ◽  
Cigarette Smoking ◽  
Undergraduate Students ◽  
Alcohol Drinking ◽  
Monthly Income ◽  
Khat Chewing ◽  
Medical Undergraduate ◽  
Severity Of Depression ◽  
Medical Undergraduate Students

Abstract Background: Mental health problems can negatively impact physical and psychological well-being of junior medical students and predisposes them to many unhealthy behaviors.Objective: We aimed to determine the prevalence and severity of depression, anxiety and stress among medical undergraduate students of Arsi University and their association with substance use. Materials and Methods: Institutional based cross-sectional study was conducted on 265 medical students that were selected by systematic random sampling. Data were collected by pre-tested self-administrative questionnaire and analyzed by SPSS-21 software. Logistic regression analysis were employed and statistical significance was accepted at p<0.05.Result: In the present study, 5 questionnaires were rejected for incompleteness giving response rate of 98.1%. The current prevalence rate of depression, anxiety, stress, khat chewing, cigarette smoking and alcohol drinking was found to be 52.3%, 60.8%, 40.4%, 21.5%, 15.4% and 33.8% respectively. Depression was significantly associated with monthly income, residency and alcohol drinking. Anxiety was associated with gender, marital status, educational year, residency and cigarette smoking. Stress was significantly associated with monthly income, educational year, residency, khat chewing, and drinking alcohol. Conclusion: To sum up, depression, anxiety and stress are common problems among medical students of Arsi University. Monthly income, residency and alcohol drinking were identified as risk factors of both depression and stress. Furthermore, educational year and khat chewing were also risk factors for stress. Finally, identified risk factors of anxiety were gender, marital status, educational year, residency and cigarette smoking. Therefore, counseling and awareness creation are recommended.

scholarly journals Space-time description of dengue outbreaks in Cruzeiro, São Paulo, in 2006 and 2011

2014 ◽  
Vol 60 (6) ◽  
pp. 565-570 ◽  
Author(s):  
Renata Marzzano de Carvalho ◽  
Luiz Fernando Costa Nascimento
Keyword(s):  
Spatial Autocorrelation ◽  
Dengue Fever ◽  
Temporal Distribution ◽  
Sao Paulo ◽  
Moran’S I ◽  
Spatial And Temporal Distribution ◽  
Moran's I ◽  
P Values ◽  
The City ◽  
Global Moran’S I

Objective: to identify patterns in the spatial and temporal distribution of cases of dengue fever occurring in the city of Cruzeiro, state of São Paulo (SP). Methods: an ecological and exploratory study was undertaken using spatial analysis tools and data from dengue cases obtained on the SinanNet. The analysis was carried out by area, using the IBGE census sector as a unit. The months of March to June 2006 and 2011 were assessed, revealing progress of the disease. TerraView 3.3.1 was used to calculate the Global Moran’s I, month to month, and the Kernel estimator. Results: in the year 2006, 691 cases of dengue fever (rate of 864.2 cases/100,000 inhabitants) were georeferenced; and the Moran’s I and p-values were significant in the months of April and May (IM = 0.28; p = 0.01; IM = 0.20; p = 0.01) with higher densities in the central, north, northeast and south regions. In the year 2011, 654 cases of dengue fever (rate of 886.8 cases/100,000 inhabitants) were georeferenced; and the Moran’s I and p-values were significant in the months of April and May (IM = 0.28; p = 0.01; IM = 0.16; p = 0.05) with densities in the same regions as 2006. The Global Moran’s I is a global measure of spatial autocorrelation, which indicates the degree of spatial association in the set of information from the product in relation to the average. The I varies between -1 and +1 and can be attributed to a level of significance (p-value). The positive value points to a positive or direct spatial autocorrelation. Conclusion: we were able to identify patterns in the spatial and temporal distribution of dengue cases occurring in the city of Cruzeiro, SP, and locate the census sectors where the outbreak began and how it evolved.

scholarly journals The Prevalence and Severity of Depression, Anxiety, and Stress among Medical Undergraduate Students of Arsi University and Their Association with Substance Use, Southeast Ethiopia

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Leta Melaku ◽  
Guta Bulcha ◽  
Deresa Worku
Keyword(s):  
Risk Factors ◽  
Medical Students ◽  
Cigarette Smoking ◽  
Undergraduate Students ◽  
Alcohol Drinking ◽  
Monthly Income ◽  
Khat Chewing ◽  
Medical Undergraduate ◽  
Severity Of Depression ◽  
Medical Undergraduate Students

Background. Mental problems can negatively impact physical and psychological well-being of junior medical students and predispose them to many unhealthy behaviors. Objective. We aimed to determine the prevalence and severity of depression, anxiety, and stress among medical undergraduate students of Arsi University and their association with substance use. Methods. Institutional-based cross-sectional study was conducted on 265 sampled medical students. Participants were selected by systematic random sampling. Data were collected by a pretested self-administrative questionnaire and analyzed using SPSS-21 software. Logistic regression analysis was employed, and statistical significance was accepted at p < 0.05 . Result. In the present study, 5 questionnaires were rejected for incompleteness giving response rate of 98.1%. The mean age was 22.03 (SD = 2.074) years. The current prevalence rates of depression, anxiety, and stress were 52.3%, 60.8%, and 40.4%, respectively. The overall prevalence of khat chewing, cigarette smoking, and alcohol drinking was found to be 21.5%, 15.4%, and 33.8%, respectively. Depression was significantly associated with monthly income [AOR = 2.13], residency [AOR = 13.10], and alcohol drinking [AOR = 1.68]. Anxiety was associated with gender [AOR = 0.51], marital status [AOR = 0.46], educational year [AOR = 20.43], residency [AOR = 58.72], and cigarette smoking [AOR = 2.60]. Stress was significantly associated with monthly income [AOR = 2.21], educational year [AOR = 3.05], residency [AOR = 4.82], khat chewing [AOR = 1.90], and drinking alcohol [AOR = 1.84]. Conclusion. To sum up, depression, anxiety, and stress are common problems among medical students of Arsi University. Monthly income, residency, and alcohol drinking were identified as risk factors of both depression and stress. In addition to other mentioned factors, educational year and khat chewing were identified as risk factors of stress. However, gender, marital status, educational year, residency, and cigarette smoking were identified as risk factors of anxiety. Counselling and awareness creation are recommended.

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