Risk areas for Human Visceral Leishmaniosis 2007–2018: A temporal and spatial analysis in Ceará, Brazil

2021 ◽  
Author(s):  
Kellyn Kessiene de Sousa Cavalcante ◽  
Jarier de Oliveira Moreno ◽  
Reagan Nzundu Boigny ◽  
Francisco Roger Aguiar Cavalcante ◽  
Caroline Mary Gurgel Dias Florêncio ◽  
...  
Keyword(s):  
Spatial Analysis ◽  
Risk Areas ◽  
Temporal And Spatial ◽  
Visceral Leishmaniosis

The open access usage advantage: a temporal and spatial analysis

2021 ◽  
Author(s):  
Guangyao Zhang ◽  
Yuqi Wang ◽  
Weixi Xie ◽  
Han Du ◽  
Chunlin Jiang ◽  
...  
Keyword(s):  
Spatial Analysis ◽  
Open Access ◽  
Temporal And Spatial

scholarly journals Spatial and temporal analysis of myocardial infarction incidence in Zanjan province, Iran

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Mohsen Soleimani ◽  
Nasser Bagheri
Keyword(s):  
Myocardial Infarction ◽  
Spatial Analysis ◽  
High Risk ◽  
Incidence Rate ◽  
Temporal Analysis ◽  
Analysis Methods ◽  
Spatial And Temporal Analysis ◽  
Risk Areas ◽  
Adjusted Incidence Rate ◽  
Adjusted Incidence

Abstract Background Myocardial Infarction (MI) is a major important public health concern and has huge burden on health system across the world. This study aimed to explore the spatial and temporal analysis of the incidence of MI to identify potential clusters of the incidence of MI patterns across rural areas in Zanjan province, Iran. Materials & methods This was a retrospective and geospatial analysis study of the incidence of MI data from nine hospitals during 2014–2018. Three different spatial analysis methods (Spatial autocorrelation, hot spot analysis and cluster and outlier analysis) were used to identify potential clusters and high-risk areas of the incidence of MI at the study area. Results Three thousand eight hundred twenty patients were registered at Zanjan hospitals due to MI during 2014–2018. The overall age-adjusted incidence rate of MI was 343 cases per 100,000 person which was raised from 88 cases in 2014 to 114 cases in 2018 per 100,000 person-year (a 30% increase, P < 0.001). Golabar region had the highest age-adjusted incidence rate of MI (515 cases per 100,000 person). Five hot spots and one high-high cluster were detected using spatial analysis methods. Conclusion This study showed that there is a great deal of spatial variations in the pattern of the incidence of MI in Zanjan province. The high incidence rate of MI in the study area compared to the national average, is a warning to local health authorities to determine the possible causes of disease incidence and potential drivers of high-risk areas. The spatial cluster analysis provides new evidence for policy-makers to design tailored interventions to reduce the incidence of MI and allocate health resource to unmet need areas.

scholarly journals Spatial Distribution of Breast Cancer in Sudan 2010-2016

2019 ◽  
Author(s):  
Marwa Maweya Abdelbagi Elbasheer ◽  
Ayah Galal Abdelrahman Alkhidir ◽  
Siham Mohammed Awad Mohammed ◽  
Areej Abuelgasim Hassan Abbas ◽  
Aisha Osman Mohamed ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Spatial Distribution ◽  
Spatial Analysis ◽  
High Risk ◽  
Geographical Information ◽  
Risk Level ◽  
Histopathological Diagnosis ◽  
Cross Sectional ◽  
Distribution Maps ◽  
Risk Areas

AbstractBackgroundBreast cancer is the most prevalent cancer among females worldwide including Sudan. The aim of this study was to determine the spatial distribution of breast cancer in Sudan.Materials and methodsA facility based cross-sectional study was implemented in eighteen histopathology laboratories distributed in the three localities of Khartoum State on a sample of 4630 Breast Cancer cases diagnosed during the period 2010-2016. A master database was developed through Epi Info™ 7.1.5.2 for computerizing the data collected: the facility name, type (public or private), and its geo- location (latitude and longitude). Personal data on patients were extracted from their respective medical records (name, age, marital status, ethnic group, State, locality, administrative unit, permanent address and phone number, histopathology diagnosis). The data was summarized through SPSS to generate frequency tables for estimating prevalence and the geographical information system (ArcGIS 10.3) was used to generate the epidemiological distribution maps. ArcGIS 10.3 spatial analysis features were used to develop risk maps based on the kriging method.ResultsBreast cancer prevalence was 3.9 cases per 100,000 female populations. Of the 4423 cases of breast cancer, invasive breast carcinoma of no special type (NST) was the most frequent (79.5%, 3517/4423) histopathological diagnosis. The spatial analysis indicated as high risk areas for breast cancer in Sudan the States of Nile River, Northern, Red Sea, White Nile, Northern and Southern Kordofan.ConclusionsThe attempt to develop a predictive map of breast cancer in Sudan revealed three levels of risk areas (risk, intermediate and high risk areas); regardless the risk level, appropriate preventive and curative health interventions with full support from decision makers are urgently needed.

scholarly journals Geographic information system based malaria risk analysis and mapping in Erer District eastern Ethiopia

2019 ◽  
Author(s):  
Maereg Teklay A Amare ◽  
Gebrehiwot Gebretsadik kassa ◽  
Esie G/wahid Gebre ◽  
Abadi Abay ◽  
Mekonen yimer ◽  
...  
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Analytic Hierarchy Process ◽  
Geographic Information ◽  
Malaria Risk ◽  
Analytic Hierarchy ◽  
Risk Areas ◽  
Hazard And Risk ◽  
Temporal And Spatial ◽  
Hierarchy Process

Abstract Background: Erer is one of the districts in Ethiopia where the first malaria transmission season occurs. Although the focus on malaria research has increasingly gained ground, little emphasis has been given to develop quantitative methods for assessing malaria hazard and risk in a temporal and spatial perspective. Objective: To characterize and examine the temporal and spatial malaria trend. The research also aims at producing a predictive model of malaria hazard and risk in Erer district. Methods: In this study a cross sectional research design was used. It was carried out through the collection of both quantitative and qualitative data about the nature of malaria and household’s response towards it. A multi-stage sampling method was used and 136 sample size was determined from the sampling frame of 6203 households. Simple descriptive analysis technique was used to determine the malaria trend of the district. Integration of Geographic information system and analytic hierarchy process was used to determine the weight of each factor pair wise comparison and weighted linear combination was used to aggregate and produce the hazard and malaria risk maps. Results: Results have shown that 19.92%, 27.96%, 32.35%, 18.93% and 0.82% of the district was very high, high, moderate, low and very low malaria risk areas respectively. The malaria trend of the area was found to be variable across time with 2014 the peak year while the minimum case observed was in 2016. Conclusion: It is possible to conclude that risk maps are important for estimating the scale of the risk, and enable detection of high risk areas, thus facilitating decision making and policy formulation for enhanced malaria control interventions. Key words: Analytic Hierarchy Process; Malaria risk; Malaria trend; Weighted overlay

scholarly journals Spatial analysis of dengue hemorrhagic fever in Talaud Islands regency

2020 ◽  
Vol 8 (1) ◽  
pp. 104
Author(s):  
Chreisye K. F. Mandagi ◽  
Angela F. C. Kalesaran ◽  
Febi K. Kolibu
Keyword(s):  
Spatial Analysis ◽  
Population Density ◽  
Dengue Hemorrhagic Fever ◽  
Secondary Data ◽  
Hemorrhagic Fever ◽  
Spatial Description ◽  
District Health ◽  
Study Approach ◽  
Spatial Risk ◽  
Risk Areas

Background: The number of dengue hemorrhagic fever (DHF) cases in Indonesia from January to February 2016 was 8,487 with 108 deaths. DHF is an infectious disease that continues to increase from 2014 until 2016 in Manado city. DHF cases in Talaud Islands Regency from 2014 to 2016 were 143 cases. Regional spatial analysis would simplify the distribution of DHF cases in high-risk areas. To be aware of the DHF outbreak cycle, it is necessary to model spatial risk factors based on geographic information systems (GIS) to tackle and eradicate DHF cases by region.Methods: This study aimed to analyze the spread of DHF in Talaud regency based on age, sex, population density and area height. The design of this research is qualitative analytic by using an ecological study approach. The research scope was 19 districts in Talaud regency. Secondary data are used which consists of case number, age, sex, population density, and area height taken from the Talaud district health office with 66 DHF cases in 2018-2019 and analyzed using the GIS approach through spatial analysis.Results: Based on the number of DHF cases that is most in the age group of 5-11 years. Male gender is more likely to suffer from DHF than female. Spatial description of the condition of the altitude in the Talaud Islands regency at risk of suffering from DHF is>50 meters above sea level. Spatial description of population density with most DHF cases is not densely populated area with less than 1,620 inhabitants per km.Conclusions: The health office of Talaud islands regency needs to actively promote health by providing information about eradicating mosquitoes.

scholarly journals Spatial analysis of hepatobiliary abnormalities in a population at high-risk of cholangiocarcinoma in Thailand

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Kavin Thinkhamrop ◽  
Apiporn T. Suwannatrai ◽  
Nittaya Chamadol ◽  
Narong Khuntikeo ◽  
Bandit Thinkhamrop ◽  
...  
Keyword(s):  
Spatial Analysis ◽  
High Risk ◽  
Screening Program ◽  
Care Program ◽  
Population Based ◽  
Northeast Thailand ◽  
Survival Prognosis ◽  
Healthcare Facilities ◽  
History Of ◽  
Risk Areas

Abstract Cholangiocarcinoma (CCA) is a serious health challenge with low survival prognosis. The liver fluke, Opisthorchis viverrini, plays a role in the aetiology of CCA, through hepatobiliary abnormalities: liver mass (LM), bile duct dilation, and periductal fibrosis (PDF). A population-based CCA screening program, the Cholangiocarcinoma Screening and Care Program, operates in Northeast Thailand. Hepatobiliary abnormalities were identified through ultrasonography. A multivariate zero-inflated, Poisson regression model measured associations between hepatobiliary abnormalities and covariates including age, sex, distance to water resource, and history of O. viverrini infection. Geographic distribution was described using Bayesian spatial analysis methods. Hepatobiliary abnormality prevalence was 38.7%; highest in males aged > 60 years (39.8%). PDF was most prevalent (20.1% of males). The Standardized Morbidity Ratio (SMR) for hepatobiliary abnormalities was highest in the lower and upper parts of the Northeast region. Hepatobiliary abnormalities specifically associated with CCA were also more common in males and those aged over 60 years and distributed along the Chi, Mun, and Songkram Rivers. Our findings demonstrated a high risk of hepatobiliary disorders in Northeast Thailand, likely associated with infection caused by O. viverrini. Screening for CCA and improvement of healthcare facilities to provide better treatment for CCA patients should be prioritized in these high-risk areas.

Analysis of Tugboat Activities using AIS Data for the Tianjin Port

2020 ◽  
Vol 2674 (5) ◽  
pp. 498-509
Author(s):  
Shukai Chen ◽  
Feng Wang ◽  
Xiaoyang Wei ◽  
Zhijia Tan ◽  
Hua Wang
Keyword(s):  
Spatial Distribution ◽  
Spatial Analysis ◽  
Service Time ◽  
Automatic Identification ◽  
Identification System ◽  
Crucial Importance ◽  
Two Stage ◽  
Temporal And Spatial ◽  
Shed Light

The tugboat is the vessel that helps to maneuver large ships for berthing and un-berthing operations. To achieve efficient tugboat operations, investigating the features of tugboat activities is of crucial importance. This study aims to use automatic identification system (AIS) data to identify the maneuver services and analyze the characteristics of tugboat activities. A two-stage algorithm is developed to extract the time, locations, and involved tugboats for berthing and un-berthing operations from AIS data. The AIS data from Tianjin port, China, are used in the case study to demonstrate the effectiveness of the proposed method and analyze the pattern of tugboat activities. First, some important features of tugboat jobs are presented, such as the daily number of jobs and the spatial distribution of jobs. Then, a temporal and spatial analysis is conducted to investigate tugboat assignment, service time, tugboat utilization, and locations of berthing and un-berthing operations. The obtained results and implications could shed light on the deployment of tugboat berths, tugboat scheduling, and evaluation of tugboat fleet operation.

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