scholarly journals The characteristics of spatial-temporal distribution and cluster of tuberculosis in Yunnan Province, China, 2005-2018.

2019 ◽  
Author(s):  
Jinou Chen ◽  
Yubing Qiu ◽  
Rui Yang ◽  
Ling Li ◽  
Jinglong Hou ◽  
...  
Keyword(s):  
Yunnan Province ◽  
Pearson Correlation ◽  
Temporal Distribution ◽  
Scan Statistics ◽  
Sputum Smear ◽  
Time Interval ◽  
County Level ◽  
Control And Prevention ◽  
Greater Mekong Subregion

Abstract Background Tuberculosis (TB) makes a big challenge to public health, especially in high TB burden counties of China and Greater Mekong Subregion (GMS). The aim of this study was to identify the spatial-temporal dynamic process and high-risk region of notified pulmonary tuberculosis (PTB), sputum smear-positive tuberculosis (SSP-TB) and sputum smear-negative tuberculosis (SSN-TB) cases in Yunnan, the south-western of China between years of 2005 to 2018. meanwhile, to evaluate the similarity of prevalence pattern for TB among GMS.Methods Data for notified PTB were extracted from the China Information System for Disease Control and Prevention (CISDCP) correspond to population information in 129 counties of Yunnan between 2005 to 2018. Seasonally adjusted time series defined the trend cycle and seasonality of PTB prevalence. Kulldorff’s space-time scan statistics was applied to identify temporal, spatial and spatial-temporal PTB prevalence clusters at county-level of Yunnan. Pearson correlation coefficient and hierarchical clustering were applied to define the similarity of TB prevalence among borders with GMS.Result There were a total of 381 855 notified PTB cases in Yunnan, and the average prevalence was 59.1 per 100 000 population between 2005 to 2018. A declined long-term trend with seasonality of a peak in spring and a trough in winter for PTB was observed. Spatial-temporal scan statistics detected the significant clusters of PTB prevalence, the most likely cluster concentrated in the northeastern angle of Yunnan between 2011 to 2015 (RR=2.6, P<0.01), though the most recent cluster for PTB and spatial cluster for SSP-TB was in borders with GMS. There were six potential TB prevalence patterns among GMS.Conclusion This study detected aggregated time interval and regions for PTB, SSP-TB, and SSN-TB at county-level of Yunnan province. Similarity prevalence pattern was found in borders and GMS. The localized prevention strategy should focus on cross-boundary transmission and SSN-TB control.

scholarly journals The characteristics of spatial-temporal distribution and cluster of tuberculosis in Yunnan Province, China, 2005–2018

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Jinou Chen ◽  
Yubing Qiu ◽  
Rui Yang ◽  
Ling Li ◽  
Jinglong Hou ◽  
...  
Keyword(s):  
Yunnan Province ◽  
Pearson Correlation ◽  
Temporal Distribution ◽  
Scan Statistics ◽  
Sputum Smear ◽  
Time Interval ◽  
County Level ◽  
Control And Prevention ◽  
Greater Mekong Subregion

Abstract Background Tuberculosis (TB) makes a big challenge to public health, especially in high TB burden counties of China and Greater Mekong Subregion (GMS). The aim of this study was to identify the spatial-temporal dynamic process and high-risk region of notified pulmonary tuberculosis (PTB), sputum smear-positive tuberculosis (SSP-TB) and sputum smear-negative tuberculosis (SSN-TB) cases in Yunnan, the south-western of China between years of 2005 to 2018. Meanwhile, to evaluate the similarity of prevalence pattern for TB among GMS. Methods Data for notified PTB were extracted from the China Information System for Disease Control and Prevention (CISDCP) correspond to population information in 129 counties of Yunnan between 2005 to 2018. Seasonally adjusted time series defined the trend cycle and seasonality of PTB prevalence. Kulldorff’s space-time scan statistics was applied to identify temporal, spatial and spatial-temporal PTB prevalence clusters at county-level of Yunnan. Pearson correlation coefficient and hierarchical clustering were applied to define the similarity of TB prevalence among borders with GMS. Result There were a total of 381,855 notified PTB cases in Yunnan, and the average prevalence was 59.1 per 100,000 population between 2005 to 2018. A declined long-term trend with seasonality of a peak in spring and a trough in winter for PTB was observed. Spatial-temporal scan statistics detected the significant clusters of PTB prevalence, the most likely cluster concentrated in the northeastern angle of Yunnan between 2011 to 2015 (RR = 2.6, P < 0.01), though the most recent cluster for PTB and spatial cluster for SSP-TB was in borders with GMS. There were six potential TB prevalence patterns among GMS. Conclusion This study detected aggregated time interval and regions for PTB, SSP-TB, and SSN-TB at county-level of Yunnan province. Similarity prevalence pattern was found in borders and GMS. The localized prevention strategy should focus on cross-boundary transmission and SSN-TB control.

scholarly journals The characteristics of spatial-temporal distribution and cluster of tuberculosis in Yunnan Province, China, 2005-2018.

2019 ◽  
Author(s):  
Jinou Chen ◽  
Yubing Qiu ◽  
Rui Yang ◽  
Ling Li ◽  
Jinglong Hou ◽  
...  
Keyword(s):  
Yunnan Province ◽  
Pearson Correlation ◽  
Temporal Distribution ◽  
Scan Statistics ◽  
Sputum Smear ◽  
Time Interval ◽  
County Level ◽  
Control And Prevention ◽  
Greater Mekong Subregion

Abstract Background Tuberculosis (TB) makes a big challenge to public health, especially in high TB burden counties of China and Greater Mekong Subregion (GMS). The aim of this study was to identify the spatial-temporal dynamic process and high-risk region of notified pulmonary tuberculosis (PTB), sputum smear-positive tuberculosis (SSP-TB) and sputum smear-negative tuberculosis (SSN-TB) cases in Yunnan, the south-western of China between years of 2005 to 2018. meanwhile, to evaluate the similarity of prevalence pattern for TB among GMS. Methods Data for notified PTB were extracted from the China Information System for Disease Control and Prevention (CISDCP) correspond to population information in 129 counties of Yunnan between 2005 to 2018. Seasonally adjusted time series defined the trend cycle and seasonality of PTB prevalence. Kulldorff’s space-time scan statistics was applied to identify temporal, spatial and spatial-temporal PTB prevalence clusters at county-level of Yunnan. Pearson correlation coefficient and hierarchical clustering were applied to define the similarity of TB prevalence among borders with GMS. Result There were a total of 381 855 notified PTB cases in Yunnan, and the average prevalence was 59.1 per 100 000 population between 2005 to 2018. A declined long-term trend with seasonality of a peak in spring and a trough in winter for PTB was observed. Spatial-temporal scan statistics detected the significant clusters of PTB prevalence, the most likely cluster concentrated in the northeastern angle of Yunnan between 2011 to 2015 ( RR =2.6, P <0.01), though the most recent cluster for PTB and spatial cluster for SSP-TB was in borders with GMS. There were six potential TB prevalence patterns among GMS. Conclusion This study detected aggregated time interval and regions for PTB, SSP-TB, and SSN-TB at county-level of Yunnan province. Similarity prevalence pattern was found in borders and GMS. The localized prevention strategy should focus on cross-boundary transmission and SSN-TB control.

scholarly journals The characteristics of spatial-temporal distribution and cluster of tuberculosis in Yunnan Province, China, 2005-2018.

2019 ◽  
Author(s):  
Jinou Chen ◽  
Yubing Qiu ◽  
Rui Yang ◽  
Ling Li ◽  
Jinglong Hou ◽  
...  
Keyword(s):  
Yunnan Province ◽  
Pearson Correlation ◽  
Temporal Distribution ◽  
Scan Statistics ◽  
Sputum Smear ◽  
Time Interval ◽  
County Level ◽  
Temporal Cluster ◽  
Keywords Tuberculosis ◽  
Greater Mekong Subregion

Abstract Background: Tuberculosis (TB) makes a big challenge to public health, especially in high TB burden counties of China and Greater Mekong Subregion (GMS). The aim of this study was to identify the spatial-temporal dynamic process and high-risk region of notified pulmonary tuberculosis (PTB), sputum smear-positive tuberculosis (SSP-TB) and sputum smear-negative tuberculosis (SSN-TB) cases in Yunnan, the south-western of China between years of 2005 to 2018. meanwhile, to evaluate the similarity of prevalence pattern for TB among GMS. Methods: Data for notified PTB were extracted from the China Information System for Disease Control and Prevention (CISDCP) correspond to population information in 129 counties of Yunnan between 2005 to 2018. Seasonally adjusted time series defined the trend cycle and seasonality of PTB prevalence. Kulldorff’s space-time scan statistics was applied to identify temporal, spatial and spatial-temporal PTB prevalence clusters at county-level of Yunnan. Pearson correlation coefficient and hierarchical clustering were applied to define the similarity of TB prevalence among borders with GMS. Result: There were a total of 381 855 notified PTB cases in Yunnan, and the average prevalence was 59.1 per 100 000 population between 2005 to 2018. A declined long-term trend with seasonality of a peak in spring and a trough in winter for PTB was observed. Spatial-temporal scan statistics detected the significant clusters of PTB prevalence, the most likely cluster concentrated in the northeastern angle of Yunnan between 2011 to 2015 (RR=2.6, P<0.01), though the most recent cluster for PTB and spatial cluster for SSP-TB was in borders with GMS. There were six potential TB prevalence patterns among GMS. Conclusion: This study detected aggregated time interval and regions for PTB, SSP-TB, and SSN-TB at county-level of Yunnan province. Similarity prevalence pattern was found in borders and GMS. The localized prevention strategy should focus on cross-boundary transmission and SSN-TB control. Keywords: Tuberculosis, Spatial-temporal cluster, Scan statistics, Yunnan, Greater Mekong Subregion

scholarly journals Treating Traumatic Brain Injuries with Electroceuticals: Implications for the Neuroanatomy of Consciousness

NeuroSci ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 254-265
Author(s):  
Jihad Aburas ◽  
Areej Aziz ◽  
Maryam Butt ◽  
Angela Leschinsky ◽  
Marsha L. Pierce
Keyword(s):  
Brain Stimulation ◽  
Brain Injuries ◽  
Vegetative State ◽  
Minimally Conscious State ◽  
Conscious State ◽  
Permanent Disability ◽  
United States Food ◽  
Control And Prevention ◽  
Minimally Conscious

According to the Centers for Disease Control and Prevention (CDC), traumatic brain injury (TBI) is the leading cause of loss of consciousness, long-term disability, and death in children and young adults (age 1 to 44). Currently, there are no United States Food and Drug Administration (FDA) approved pharmacological treatments for post-TBI regeneration and recovery, particularly related to permanent disability and level of consciousness. In some cases, long-term disorders of consciousness (DoC) exist, including the vegetative state/unresponsive wakefulness syndrome (VS/UWS) characterized by the exhibition of reflexive behaviors only or a minimally conscious state (MCS) with few purposeful movements and reflexive behaviors. Electroceuticals, including non-invasive brain stimulation (NIBS), vagus nerve stimulation (VNS), and deep brain stimulation (DBS) have proved efficacious in some patients with TBI and DoC. In this review, we examine how electroceuticals have improved our understanding of the neuroanatomy of consciousness. However, the level of improvements in general arousal or basic bodily and visual pursuit that constitute clinically meaningful recovery on the Coma Recovery Scale-Revised (CRS-R) remain undefined. Nevertheless, these advancements demonstrate the importance of the vagal nerve, thalamus, reticular activating system, and cortico-striatal-thalamic-cortical loop in the process of consciousness recovery.

scholarly journals Nationwide Temporal and Geographical Distribution of Tick Populations and Phylogenetic Analysis of Severe Fever with Thrombocytopenia Syndrome Virus in Ticks in Korea, 2020

2021 ◽  
Vol 9 (8) ◽  
pp. 1630
Author(s):  
Min-Goo Seo ◽  
Byung-Eon Noh ◽  
Hak Seon Lee ◽  
Tae-Kyu Kim ◽  
Bong-Goo Song ◽  
...  
Keyword(s):  
Tick Species ◽  
Temporal Distribution ◽  
Epidemiological Studies ◽  
Haemaphysalis Longicornis ◽  
Geographical Regions ◽  
Control And Prevention ◽  
Amblyomma Testudinarium ◽  
High Degree ◽  
Severe Fever ◽  
Minimum Infection Rate

Since 2010, the Korea Disease Control and Prevention Agency has established centers at 16 locations to monitor disease vectors and pathogens. Here, we examined tick populations to understand the geographical and temporal distribution of severe fever with thrombocytopenia syndrome virus (SFTSV) vectors in 2020. From April to November, 63,376 ticks were collected from traps to monitor tick populations, with a trap index of 41.3. Tick incidence varied from April to October, with population peaks observed for nymphs in May, adults in July, and larvae in September. The predominant tick species were Haemaphysalis longicornis, Haemaphysalis spp., H. flava, Ixodes spp., Amblyomma testudinarium, and Ixodes nipponensis. Approximately 50% of the collected ticks were pooled into 2973 groups to detect the rate of SFTSV infection in ticks. The minimum infection rate (MIR) of SFTSV was 0.2%, and Andong had the highest MIR for SFTSV (4.0%). The B3 genotype was the most prevalent (52.2%) followed by B2 (28.6%), B5 (15.9%), B4 (1.6%), and B6 (1.6%). We identified widely distributed tick species and a high degree of diversity in SFTSV strains in ticks from different geographical regions. The results may provide a basis for future epidemiological studies and risk assessments for tick-borne diseases.

scholarly journals A Novel Deep Learning Approach for Machinery Prognostics Based on Time Windows

2019 ◽  
Vol 9 (22) ◽  
pp. 4813 ◽  
Author(s):  
Hanbo Yang ◽  
Fei Zhao ◽  
Gedong Jiang ◽  
Zheng Sun ◽  
Xuesong Mei
Keyword(s):  
Time Windows ◽  
Remaining Useful Life ◽  
Sensor Data ◽  
Time Interval ◽  
Kernel Module ◽  
Initial Stage ◽  
Research Task ◽  
Consecutive Time ◽  
Useful Life

Remaining useful life (RUL) prediction is a challenging research task in prognostics and receives extensive attention from academia to industry. This paper proposes a novel deep convolutional neural network (CNN) for RUL prediction. Unlike health indicator-based methods which require the long-term tracking of sensor data from the initial stage, the proposed network aims to utilize data from consecutive time samples at any time interval for RUL prediction. Additionally, a new kernel module for prognostics is designed where the kernels are selected automatically, which can further enhance the feature extraction ability of the network. The effectiveness of the proposed network is validated using the C-MAPSS dataset for aircraft engines provided by NASA. Compared with the state-of-the-art results on the same dataset, the prediction results demonstrate the superiority of the proposed network.

scholarly journals Time Interval to Biochemical Failure as a Surrogate End Point in Locally Advanced Prostate Cancer: Analysis of Randomized Trial NRG/RTOG 9202

2019 ◽  
Vol 37 (3) ◽  
pp. 213-221 ◽  
Author(s):  
James J. Dignam ◽  
Daniel A. Hamstra ◽  
Herbert Lepor ◽  
David Grignon ◽  
Harmar Brereton ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Randomized Trial ◽  
Locally Advanced ◽  
Biochemical Failure ◽  
Mediating Effect ◽  
Time Interval ◽  
Short Term ◽  
End Points ◽  
End Point

Background In prostate cancer, end points that reliably portend prognosis and treatment benefit (surrogate end points) can accelerate therapy development. Although surrogate end point candidates have been evaluated in the context of radiotherapy and short-term androgen deprivation (AD), potential surrogates under long-term (24 month) AD, a proven therapy in high-risk localized disease, have not been investigated. Materials and Methods In the NRG/RTOG 9202 randomized trial (N = 1,520) of short-term AD (4 months) versus long-term AD (LTAD; 28 months), the time interval free of biochemical failure (IBF) was evaluated in relation to clinical end points of prostate cancer–specific survival (PCSS) and overall survival (OS). Survival modeling and landmark analysis methods were applied to evaluate LTAD benefit on IBF and clinical end points, association between IBF and clinical end points, and the mediating effect of IBF on LTAD clinical end point benefits. Results LTAD was superior to short-term AD for both biochemical failure (BF) and the clinical end points. Men remaining free of BF for 3 years had relative risk reductions of 39% for OS and 73% for PCSS. Accounting for 3-year IBF status reduced the LTAD OS benefit from 12% (hazard ratio [HR], 0.88; 95% CI, 0.79 to 0.98) to 6% (HR, 0.94; 95% CI, 0.83 to 1.07). For PCSS, the LTAD benefit was reduced from 30% (HR, 0.70; 95% CI, 0.52 to 0.82) to 6% (HR, 0.94; 95% CI, 0.72 to 1.22). Among men with BF, by 3 years, 50% of subsequent deaths were attributed to prostate cancer, compared with 19% among men free of BF through 3 years. Conclusion The IBF satisfied surrogacy criteria and identified the benefit of LTAD on disease-specific survival and OS. The IBF may serve as a valid end point in clinical trials and may also aid in risk monitoring after initial treatment.

scholarly journals Long-Term Observations of Beach Variability at Hasaki, Japan

2020 ◽  
Vol 8 (11) ◽  
pp. 871
Author(s):  
Masayuki Banno ◽  
Satoshi Nakamura ◽  
Taichi Kosako ◽  
Yasuyuki Nakagawa ◽  
Shin-ichi Yanagishima ◽  
...  
Keyword(s):  
Morphological Change ◽  
High Frequency ◽  
Climate Changes ◽  
Wave Climate ◽  
Time Interval ◽  
Observation Data ◽  
Beach Profile ◽  
Water Level Variations ◽  
Monthly Variations

Long-term beach observation data for several decades are essential to validate beach morphodynamic models that are used to predict coastal responses to sea-level rise and wave climate changes. At the Hasaki coast, Japan, the beach profile has been measured for 34 years at a daily to weekly time interval. This beach morphological dataset is one of the longest and most high-frequency measurements of the beach morphological change worldwide. The profile data, with more than 6800 records, reflect short- to long-term beach morphological change, showing coastal dune development, foreshore morphological change and longshore bar movement. We investigated the temporal beach variability from the decadal and monthly variations in elevation. Extremely high waves and tidal anomalies from an extratropical cyclone caused a significant change in the long-term bar behavior and foreshore slope. The berm and bar variability were also affected by seasonal wave and water level variations. The variabilities identified here from the long-term observations contribute to our understanding of various coastal phenomena.

scholarly journals Emergence and Spread of kelch13 Mutations Associated with Artemisinin Resistance in Plasmodium falciparum Parasites in 12 Thai Provinces from 2007 to 2016

2018 ◽  
Vol 62 (4) ◽  
Author(s):  
Theerayot Kobasa ◽  
Eldin Talundzic ◽  
Rungniran Sug-aram ◽  
Patcharida Boondat ◽  
Ira F. Goldman ◽  
...  
Keyword(s):  
Plasmodium Falciparum ◽  
Gene Mutations ◽  
Artemisinin Resistance ◽  
Parasite Clearance ◽  
Resistance Mutations ◽  
Content Type ◽  
Artemisinin Derivatives ◽  
Reduced Ring ◽  
Control And Prevention ◽  
Greater Mekong Subregion

ABSTRACT Artemisinin-based combination therapy (ACT) is the most effective and widely used treatment for uncomplicated Plasmodium falciparum malaria and is a cornerstone for malaria control and prevention globally. Resistance to artemisinin derivatives has been confirmed in the Greater Mekong Subregion (GMS) and manifests as slow parasite clearance in patients and reduced ring stage susceptibility to artemisinins in survival assays. The P. falciparum kelch13 gene mutations associated with artemisinin-resistant parasites are now widespread in the GMS. We genotyped 277 samples collected during an observational study from 2012 to 2016 from eight provinces in Thailand to identify P. falciparum kelch13 mutations. The results were combined with previously reported genotyping results from Thailand to construct a map illustrating the evolution of P. falciparum kelch13 mutations from 2007 to 2016 in that country. Different mutant alleles were found in strains with different geographical origins. The artemisinin resistance-conferring Y493H and R539T mutations were detected mainly in eastern Thailand (bordering Cambodia), while P574L was found only in western Thailand and R561H only in northwestern Thailand. The C580Y mutation was found across the entire country and was nearing fixation along the Thai-Cambodia border. Overall, the prevalence of artemisinin resistance mutations increased over the last 10 years across Thailand, especially along the Thai-Cambodia border. Molecular surveillance and therapeutic efficacy monitoring should be intensified in the region to further assess the extent and spread of artemisinin resistance.

Abstract P636: Social Determinants of Stroke Hospitalization and Mortality in the United States

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Randhir Sagar Yadav ◽  
Durgesh Chaudhary ◽  
Shima Shahjouei ◽  
Jiang Li ◽  
Vida Abedi ◽  
...  
Keyword(s):  
United States ◽  
Income Inequality ◽  
Social Determinants ◽  
Hemorrhagic Stroke ◽  
The United States ◽  
Care Physician ◽  
County Level ◽  
Medicare Beneficiaries ◽  
Level Data ◽  
Control And Prevention

Introduction: Stroke hospitalization and mortality are influenced by various social determinants. This ecological study aimed to determine the associations between social determinants and stroke hospitalization and outcome at county-level in the United States. Methods: County-level data were recorded from the Centers for Disease Control and Prevention as of January 7, 2020. We considered four outcomes: all-age (1) Ischemic and (2) Hemorrhagic stroke Death rates per 100,000 individuals (ID and HD respectively), and (3) Ischemic and (4) Hemorrhagic stroke Hospitalization rate per 1,000 Medicare beneficiaries (IH and HH respectively). Results: Data of 3,225 counties showed IH (12.5 ± 3.4) and ID (22.2 ± 5.1) were more frequent than HH (2.0 ± 0.4) and HD (9.8 ± 2.1). Income inequality as expressed by Gini Index was found to be 44.6% ± 3.6% and unemployment rate was 4.3% ± 1.5%. Only 29.8% of the counties had at least one hospital with neurological services. The uninsured rate was 11.0% ± 4.7% and people living within half a mile of a park was only 18.7% ± 17.6%. Age-adjusted obesity rate was 32.0% ± 4.5%. In regression models, age-adjusted obesity (OR for IH: 1.11; HH: 1.04) and number of hospitals with neurological services (IH: 1.40; HH: 1.50) showed an association with IH and HH. Age-adjusted obesity (ID: 1.16; HD: 1.11), unemployment (ID: 1.21; HD: 1.18) and income inequality (ID: 1.09; HD: 1.11) showed an association with ID and HD. Park access showed inverse associations with all four outcomes. Additionally, population per primary-care physician was associated with HH while number of pharmacy and uninsured rate were associated with ID. All associations and OR had p ≤0.04. Conclusion: Unemployment and income inequality are significantly associated with increased stroke mortality rates.

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