scholarly journals Spatio-temporal epidemiology of the tuberculosis incidence rate in Iran 2008 to 2018

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Behzad Kiani ◽  
Amene Raouf Rahmati ◽  
Robert Bergquist ◽  
Soheil Hashtarkhani ◽  
Neda Firouraghi ◽  
...  
Keyword(s):  
High Risk ◽  
Incidence Rate ◽  
Policy Development ◽  
Temporal Pattern ◽  
Temporal Analysis ◽  
High Rate ◽  
Spatial Scan Statistic ◽  
Cross Sectional ◽  
Risk Areas ◽  
Spatio Temporal

Abstract Background Effective reduction of tuberculosis (TB) requires information on the distribution of TB incidence rate across time and location. This study aims to identify the spatio-temporal pattern of TB incidence rate in Iran between 2008 and 2018. Methods This cross-sectional study was conducted on aggregated TB data (50,500 patients) at the provincial level provided by the Ministry of Health in Iran between 2008 and 2018. The Anselin Local Moran’s I and Getis-Ord Gi* were performed to identify the spatial variations of the disease. Furthermore, spatial scan statistic was employed for purely temporal and spatio-temporal analyses. In all instances, the null hypothesis of no clusters was rejected at p ≤ 0.05. Results The overall incidence rate of TB decreased from 13.46 per 100,000 (95% CI: 13.19–13.73) in 2008 to 10.88 per 100,000 (95% CI: 10.65–11.11) in 2018. The highest incidence rate of TB was observed in southeast and northeast of Iran for the whole study period. Additionally, spatial cluster analysis discovered Khuzestan Province, in the West of the country, having significantly higher rates than neighbouring provinces in terms of both total TB and smear-positive pulmonary TB (SPPTB). Purely temporal analysis showed that high-rate and low-rate clusters were predominantly distributed in the time periods 2010–2014 and 2017–2018. Spatio-temporal results showed that the statistically significant clusters were mainly distributed from centre to the east during the study period. Some high-trend TB and SPPTB statistically significant clusters were found. Conclusion The results provided an overview of the latest TB spatio-temporal status In Iran and identified decreasing trends of TB in the 2008–2018 period. Despite the decreasing incidence rate, there is still need for screening, and targeting of preventive interventions, especially in high-risk areas. Knowledge of the spatio-temporal pattern of TB can be useful for policy development as the information regarding the high-risk areas would contribute to the selection of areas needed to be targeted for the expansion of health facilities.

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-time Visualization of Cutaneous Leishmaniasis in an Urban Area: Informing Health Policy and Practice

2020 ◽  
Author(s):  
Neda Firouraghi ◽  
Sayyed Mostafa Mostafavi ◽  
Amene Raouf-Rahmati ◽  
Alireza Mohammadi ◽  
Reza Saemi ◽  
...  
Keyword(s):  
High Risk ◽  
Incidence Rate ◽  
Urban Area ◽  
Incidence Rates ◽  
Low Risk ◽  
Health Concern ◽  
Surveillance Systems ◽  
Cross Sectional ◽  
Targeted Interventions ◽  
Risk Areas

Abstract Background:Cutaneous leishmaniasis (CL) is an important public health concern worldwide. Iran is among the most CL-affected countries, being listed as one of the first six endemic countries in the world. In order to develop targeted interventions, we performed a spatial-time visualization of CL cases in an urban area to identify high-risk and low-risk areas during 2016-2019.Methods:This cross-sectional study was conducted in the city of Mashhad. Patient data were gathered from Mashhad health centers. All cases (n=2425) were diagnosed in two stages; the initial diagnosis was based on clinical findings. Subsequently, clinical manifestation was confirmed by parasitological tests. The data were aggregated at the neighborhood and district levels and smoothed CL incidence rates per 100,000 individuals were calculated using the spatial empirical Bayesian approach. Furthermore, we used the Anselin Local Moran’s I statistic to identify clusters and outliers of CL distribution during 2016-2019 in Mashhad. Results:The overall incidence rates decreased from 34.6 per 100,000 in 2016 to 19.9 per 100,000 individuals in 2019. Both cluster analyses by crude incidence rate and smoothed incidence rate identified high-risk areas in southwestern Mashhad over the study period. Furthermore, the analyses revealed low-risk areas in northeastern Mashhad over the same 3-year period.Conclusions:The southwestern area of Mashhad had the highest CL incidence rates. This piece of information might be of value to design tailored interventions such as running effective resource allocation models, informed control plans and implementation of efficient surveillance systems. Furthermore, this study generates new hypotheses to test potential relationships between socio-economic and environmental risk factors and incidence of CL in areas with higher associated risks.

scholarly journals Arabian Sea Tropical Cyclones: A Spatio-Temporal Analysis in Support of Natural Hazard Risk Appraisal in Oman

2021 ◽  
Author(s):  
Suad Al-Manji ◽  
Gordon Mitchell ◽  
Amna Al Ruheili
Keyword(s):  
High Risk ◽  
Tropical Cyclones ◽  
Natural Hazard ◽  
Temporal Distribution ◽  
Storm Surges ◽  
Temporal Analysis ◽  
The North ◽  
Risk Areas ◽  
Spatio Temporal ◽  
Extreme Winds

Tropical cyclones [TCs] are a common natural hazard that have significantly impacted Oman. Over the period 1881–2019, 41 TC systems made landfall in Oman, each associated with extreme winds, storm surges and significant flash floods, often resulting in loss of life and substantial damage to infrastructure. TCs affect Omani coastal areas from Muscat in the north to Salalah in the south. However, developing a better understanding of the high-risk regions is needed, and is of particular interest in disaster risk reduction institutions in Oman. This study aims to find and map TC tracks and their spatio-temporal distribution to landfall in Oman to identify the high-risk areas. The analysis uses Kernel Density Estimation [KDE] and Linear Direction Mean [LDM] methods to better identify the spatio-temporal distribution of TC tracks and their landfall in Oman. The study reveals clear seasonal and monthly patterns. This knowledge will help to improve disaster planning for the high-risk areas.

scholarly journals Identification of Ecological Risk Zoning on Qinghai-Tibet Plateau from the Perspective of Ecosystem Service Supply and Demand

2021 ◽  
Vol 13 (10) ◽  
pp. 5366
Author(s):  
Wei Shi ◽  
Fuwei Qiao ◽  
Liang Zhou
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
High Risk ◽  
Ecological Risk ◽  
Temporal Pattern ◽  
Supply And Demand ◽  
Tibet Plateau ◽  
Risk Areas ◽  
Spatio Temporal ◽  
Qinghai Tibet Plateau

With the interaction of global change and human activities, the contradistinction between supply and demand of ecosystem services in the Qinghai-Tibet Plateau is becoming increasingly tense, which will have a profound impact on the ecological security of China and even Asia. Based on land cover data on the Qinghai-Tibet Plateau in 1990, 2005, and 2015, this paper estimated the supply capacity of ecosystem services using the value equivalent method, calculated the demand for ecosystem services using population density and economic density, established an ecosystem risk index based on the idea of an ecosystem service matrix to reveal the spatio-temporal pattern of the supply and demand of ecosystem services in the Qinghai-Tibet Plateau, and identified the potential ecological risk areas arising from the imbalance between supply and demand. The results showed that: (1) In terms of the spatio-temporal pattern of land use change, the desert area of the Qinghai-Tibet Plateau decreased the most with 26,238.9 km2, and other types of land use increased, of which construction land increased by 131.7%; (2) In terms of the supply and demand of ecosystem services, the Qinghai-Tibet Plateau was mainly dominated by low-level surplus areas, accounting for 64.0%, and the deficit in some areas has worsened significantly; and (3) In terms of division pattern of ecological risk areas, the Qinghai-Tibet Plateau presented characteristics of high risk in the east and low risk in the west. The high-risk area accounted for 1.1%, mainly distributed in the Huangshui Valley and the “One River and Two Tributaries” (Yarlung Zangbo River, Lhasa River, Nianchu River). The research results can provide reference for ecosystem management and policy formulation of the Qinghai-Tibet Plateau and have important significance for realizing the coupling and coordinated development of human–land relationship in Qinghai-Tibet Plateau.

scholarly journals Spatial and spatio-temporal analysis of malaria cases in Zimbabwe

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Isaiah Gwitira ◽  
Munashe Mukonoweshuro ◽  
Grace Mapako ◽  
Munyaradzi D. Shekede ◽  
Joconiah Chirenda ◽  
...  
Keyword(s):  
High Risk ◽  
Spatial Autocorrelation ◽  
Malaria Control ◽  
Temporal Pattern ◽  
Poisson Model ◽  
Space Time ◽  
Spatial Clusters ◽  
Risk Areas ◽  
Geographic Regions ◽  
Spatio Temporal

Abstract Background Although effective treatment for malaria is now available, approximately half of the global population remain at risk of the disease particularly in developing countries. To design effective malaria control strategies there is need to understand the pattern of malaria heterogeneity in an area. Therefore, the main objective of this study was to explore the spatial and spatio-temporal pattern of malaria cases in Zimbabwe based on malaria data aggregated at district level from 2011 to 2016. Methods Geographical information system (GIS) and spatial scan statistic were applied on passive malaria data collected from health facilities and aggregated at district level to detect existence of spatial clusters. The global Moran’s I test was used to infer the presence of spatial autocorrelation while the purely spatial retrospective analyses were performed to detect the spatial clusters of malaria cases with high rates based on the discrete Poisson model. Furthermore, space-time clusters with high rates were detected through the retrospective space-time analysis based on the discrete Poisson model. Results Results showed that there is significant positive spatial autocorrelation in malaria cases in the study area. In addition, malaria exhibits spatial heterogeneity as evidenced by the existence of statistically significant (P < 0.05) spatial and space-time clusters of malaria in specific geographic regions. The detected primary clusters persisted in the eastern region of the study area over the six year study period while the temporal pattern of malaria reflected the seasonality of the disease where clusters were detected within particular months of the year. Conclusions Geographic regions characterised by clusters of high rates were identified as malaria high risk areas. The results of this study could be useful in prioritizing resource allocation in high-risk areas for malaria control and elimination particularly in resource limited settings such as Zimbabwe. The results of this study are also useful to guide further investigation into the possible determinants of persistence of high clusters of malaria cases in particular geographic regions which is useful in reducing malaria burden in such areas.

scholarly journals Spatio-temporal analysis of COVID-19 incidence rate using GIS: a case study—Tehran metropolitan, Iran

GeoJournal ◽  
2021 ◽  
Author(s):  
R. Nasiri ◽  
S. Akbarpour ◽  
AR. Zali ◽  
N. Khodakarami ◽  
MH. Boochani ◽  
...  
Keyword(s):  
Incidence Rate ◽  
Temporal Analysis ◽  
Spatio Temporal

scholarly journals Modelling local patterns of child mortality risk: a Bayesian Spatio-temporal analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Alejandro Lome-Hurtado ◽  
Jacques Lartigue-Mendoza ◽  
Juan C. Trujillo
Keyword(s):  
High Risk ◽  
Mexico City ◽  
Child Mortality ◽  
Mortality Risk ◽  
Temporal Analysis ◽  
Health Concern ◽  
The North ◽  
Greater Mexico ◽  
Spatio Temporal ◽  
Child Mortality Rate

Abstract Background Globally, child mortality rate has remained high over the years, but the figure can be reduced through proper implementation of spatially-targeted public health policies. Due to its alarming rate in comparison to North American standards, child mortality is particularly a health concern in Mexico. Despite this fact, there remains a dearth of studies that address its spatio-temporal identification in the country. The aims of this study are i) to model the evolution of child mortality risk at the municipality level in Greater Mexico City, (ii) to identify municipalities with high, medium, and low risk over time, and (iii) using municipality trends, to ascertain potential high-risk municipalities. Methods In order to control for the space-time patterns of data, the study performs a Bayesian spatio-temporal analysis. This methodology permits the modelling of the geographical variation of child mortality risk across municipalities, within the studied time span. Results The analysis shows that most of the high-risk municipalities were in the east, along with a few in the north and west areas of Greater Mexico City. In some of them, it is possible to distinguish an increasing trend in child mortality risk. The outcomes highlight municipalities currently presenting a medium risk but liable to become high risk, given their trend, after the studied period. Finally, the likelihood of child mortality risk illustrates an overall decreasing tendency throughout the 7-year studied period. Conclusions The identification of high-risk municipalities and risk trends may provide a useful input for policymakers seeking to reduce the incidence of child mortality. The results provide evidence that supports the use of geographical targeting in policy interventions.

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 Epidemiology of Thalassemia in Gulf Cooperation Council Countries: A Systematic Review

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Amani Abu-Shaheen ◽  
Humariya Heena ◽  
Abdullah Nofal ◽  
Doaa A. Abdelmoety ◽  
Abdulrahman Almatary ◽  
...  
Keyword(s):  
Systematic Review ◽  
High Risk ◽  
United Arab Emirates ◽  
Observational Studies ◽  
Gulf Cooperation Council ◽  
Cross Sectional ◽  
Gcc Countries ◽  
Premarital Screening ◽  
Risk Areas ◽  
Epidemiological Profile

Background. Thalassemia has a burden on the healthcare systems of many countries. About 56000 conceptions result in thalassemia, globally. Objective. To assess the epidemiological profile of thalassemia in the Gulf Cooperation Council (GCC) countries. Methods. A systematic search was conducted in MEDLINE/PubMed (National Library of Medicine), CINAHL, and Embase. Relevant observational studies reporting the epidemiology of thalassemia among the GCC population were selected. Data on the prevalence, frequency, and complications of thalassemia were extracted. The quality of the retrieved studies was assessed according to the Newcastle–Ottawa Quality Assessment Scale. Results. Eighteen studies (14 cross-sectional studies, two retrospective observational studies, and two retrospective analysis) with a total of 3343042 participants were included in this systematic review. Of the 18 studies, 11 studies were conducted in Saudi Arabia, two in the Kingdom of Bahrain, one in Kuwait, three in the United Arab Emirates (UAE), and one in Qatar. The prevalence of thalassemia among children below five years of age ranged from 0.25% to 33%, while it was 0.9% in children above five years and from 0.035% to 43.3% among adult thalassemia patients. The most-reported risk factors were consanguineous marriage and high-risk marriage. There was a lack of data regarding mortality rates in thalassemia. Conclusions. Despite the premarital screening and genetic counseling (PMSGC) program for thalassemia, the incidence of high-risk couple marriages in GCC countries cannot be effectively diminished. This study suggested that the PMSGC program should adopt more attention for the high-risk areas, to enhance the level of consciousness about the hemoglobinopathy diseases and the consequences of consanguinity among the at-risk couple.

scholarly journals Modelling Local Patterns of Children Mortality. A Bayesian Spatio-Temporal Analysis.

2019 ◽  
Author(s):  
Alejandro Lome-Hurtado ◽  
Jacques Lartigue Mendoza ◽  
Juan Carlos Trujillo
Keyword(s):  
High Risk ◽  
Mortality Risk ◽  
Temporal Analysis ◽  
Health Concern ◽  
North West ◽  
The North ◽  
Policy Interventions ◽  
Medium Risk ◽  
Spatio Temporal ◽  
Over Time

Abstract Background: The number of death children at the international scale are still high, but with proper spatially-targeted health public policies this number could be reduced. In Mexico, children mortality is a particular health concern due to its alarming rate all throughout North America. The aims of this study are i) to model the change of children mortality risk at the municipality level, (ii) to identify municipalities with high, medium and low risk over time and (iii) to ascertain potential high-risk municipalities across time, using local trends of each municipality in Greater Mexico City. Methods: The study uses Bayesian spatio-temporal analysis to control for space-time patterns of data. This allow to model the geographical variation of the municipalities within the time span studied. Results: The analysis shows that most of the high-risk municipalities are in the north, west, and some in the east; some of such municipalities show an increasing children mortality risk over time. The outcomes highlight some municipalities which show a medium risk currently but are likely to become high risk along the study period. Finally, the odds of children mortality risk illustrate a decreasing tendency over the 7-year framework. Conclusions: Identification of high-risk municipalities may provide a useful input to policy-makers seeking out to reduce the incidence of children mortality, since it would provide evidence to support geographical targeting for policy interventions.

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