scholarly journals Spatio-temporal distribution characteristics of COVID-19 in China: a city-level modeling study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Qianqian Ma ◽  
Jinghong Gao ◽  
Wenjie Zhang ◽  
Linlin Wang ◽  
Mingyuan Li ◽  
...  
Keyword(s):  
Spatial Autocorrelation ◽  
Southern China ◽  
Early Stage ◽  
Hot Spot ◽  
Statistical Significance ◽  
Mainland China ◽  
Temporal Distribution ◽  
Distribution Characteristics ◽  
Hotspot Analysis ◽  
Spatio Temporal

Abstract Background The coronavirus disease 2019 (COVID-19) has become a pandemic. Few studies have been conducted to investigate the spatio-temporal distribution of COVID-19 on nationwide city-level in China. Objective To analyze and visualize the spatiotemporal distribution characteristics and clustering pattern of COVID-19 cases from 362 cities of 31 provinces, municipalities and autonomous regions in mainland China. Methods A spatiotemporal statistical analysis of COVID-19 cases was carried out by collecting the confirmed COVID-19 cases in mainland China from January 10, 2020 to October 5, 2020. Methods including statistical charts, hotspot analysis, spatial autocorrelation, and Poisson space–time scan statistic were conducted. Results The high incidence stage of China’s COVID-19 epidemic was from January 17 to February 9, 2020 with daily increase rate greater than 7.5%. The hot spot analysis suggested that the cities including Wuhan, Huangshi, Ezhou, Xiaogan, Jingzhou, Huanggang, Xianning, and Xiantao, were the hot spots with statistical significance. Spatial autocorrelation analysis indicated a moderately correlated pattern of spatial clustering of COVID-19 cases across China in the early phase, with Moran’s I statistic reaching maximum value on January 31, at 0.235 (Z = 12.344, P = 0.001), but the spatial correlation gradually decreased later and showed a discrete trend to a random distribution. Considering both space and time, 19 statistically significant clusters were identified. 63.16% of the clusters occurred from January to February. Larger clusters were located in central and southern China. The most likely cluster (RR = 845.01, P < 0.01) included 6 cities in Hubei province with Wuhan as the centre. Overall, the clusters with larger coverage were in the early stage of the epidemic, while it changed to only gather in a specific city in the later period. The pattern and scope of clusters changed and reduced over time in China. Conclusions Spatio-temporal cluster detection plays a vital role in the exploration of epidemic evolution and early warning of disease outbreaks and recurrences. This study can provide scientific reference for the allocation of medical resources and monitoring potential rebound of the COVID-19 epidemic in China.

scholarly journals Spatio-temporal distribution characteristics of cysticercosis from 2000 to 2014 in Dali, Yunnan province, China.

2020 ◽  
Vol 15 (2) ◽  
Author(s):  
Huanzhang Li ◽  
Xinzhong Zang ◽  
Xiaokang Hu ◽  
Eniola Michael Abe ◽  
Menbao Qian ◽  
...  
Keyword(s):  
Public Health ◽  
Yunnan Province ◽  
Disease Incidence ◽  
Temporal Distribution ◽  
Public Health Problem ◽  
Effective Control ◽  
Distribution Characteristics ◽  
Hotspot Analysis ◽  
Spatio Temporal ◽  
And Control

Cysticercosis remains a public health problem in China, with disease prevalence attributed to poor socio-economic and public health conditions. This parasitic food-borne disease was prioritized for effective control following implementation of the national surveys on parasitic diseases carried out in China. We predicted the cysticercosis distribution in Dali, Yunnan Province by assessing spatio-temporal distribution characteristics between 2000 and 2014 to better understand the trend of the disease incidence. A database of cysticercosis cases was provided by the clinical department at the Dali Prefectural Institute of Research and Control of Schistosomiasis. Describing the epidemiological features of cysticercosis and analyzing its spatiotemporal distribution of cases using mapping, scanning and spatial autocorrelation analysis, our findings found a total of 3,347 patients with cysticercosis infection, neurocysticercosis in particular. Cysticercosis prevalence was the highest among young and middle-aged male farmers, and also predominant among the Bai nationality. Three aggregation areas were identified during the period 2000-2014. Hotspot analysis implicated Dali City, Eryuan County and Yangbi County between 2000 and 2007, with areas gradually shifting towards the western and northern parts of the province. The hotspot map indicated that Eryuan County was a constant problem with respect to cysticercosis. The results indicated three cysticercosis clusters in Dali that could be attributed to environmental factors and unhealthy lifestyles. Multi-sectoral control initiatives are, therefore, recommended in these areas to effectively control and prevent cysticercosis among the population.

Spatio-temporal Distribution Characteristics of Water Quality in Miju River and Erhai Lake

2019 ◽  
Vol 93 (sp1) ◽  
pp. 31
Author(s):  
Junlong Liu ◽  
Jijun Xu ◽  
Jin Chen ◽  
Xiaofeng Hong ◽  
Mingyuan Zhou
Keyword(s):  
Water Quality ◽  
Temporal Distribution ◽  
Erhai Lake ◽  
Distribution Characteristics ◽  
Spatio Temporal

Spatio-temporal distribution characteristics of cropland water use efficiency and its relationship with climate in Anhui Province

2018 ◽  
Vol 38 (17) ◽  
Author(s):  
王芳 WANG Fang ◽  
汪左 WANG Zuo ◽  
黄静 HUANG Jing ◽  
杨淑杰 YANG Shujie ◽  
贺广均 HE Guangjun ◽  
...  
Keyword(s):  
Water Use Efficiency ◽  
Water Use ◽  
Temporal Distribution ◽  
Anhui Province ◽  
Distribution Characteristics ◽  
Use Efficiency ◽  
Spatio Temporal

scholarly journals Spatio-temporal clustering of Mountain-type Zoonotic Visceral Leishmaniasis in China between 2015 and 2019

2021 ◽  
Vol 15 (3) ◽  
pp. e0009152
Author(s):  
Yuwan Hao ◽  
Xiaokang Hu ◽  
Yanfeng Gong ◽  
Jingbo Xue ◽  
Zhengbin Zhou ◽  
...  
Keyword(s):  
Visceral Leishmaniasis ◽  
Spatial Autocorrelation ◽  
Study Time ◽  
Western China ◽  
Shanxi Province ◽  
Hotspot Analysis ◽  
Temporal Clustering ◽  
Time Period ◽  
Spatio Temporal ◽  
Zoonotic Visceral Leishmaniasis

With several decades of concerted control efforts, visceral leishmaniasis(VL) eradication had almost been achieved in China. However, VL cases continue to be detected in parts of western China recent years. Using data of reported cases, this study aimed to investigate the epidemiology and spatio⁃temporal distribution, of mountain-type zoonotic visceral leishmaniasis (MT-ZVL) in China between the years 2015 and 2019. Epidemiological data pertaining to patients with visceral leishmaniasis (VL) were collected in Gansu, Shaanxi, Sichuan, Shanxi, Henan and Hebei provinces between the years 2015 and 2019. Joinpoint regression analysis was performed to determine changes in the epidemic trend of MT-ZVL within the time period during which data was collected. Spatial autocorrelation of infection was examined using the Global Moran’s I statistic wand hotspot analysis was carried out using the Getis-Ord Gi* statistic. Spatio-temporal clustering analysis was conducted using the retrospective space-time permutation flexible spatial scanning statistics. A total of 529 cases of MT-ZVL were detected in the six provinces from which data were collected during the study time period, predominantly in Gansu (55.0%), Shanxi (21.7%), Shaanxi (12.5%) and Sichuan (8.9%) provinces. A decline in VL incidence in China was observed during the study period, whereas an increase in MT-ZVL incidence was observed in the six provinces from which data was obtained (t = 4.87, P < 0.05), with highest incidence in Shanxi province (t = 16.91, P < 0.05). Significant differences in the Moran’s I statistic were observed during study time period (P < 0.05), indicating spatial autocorrelation in the spatial distribution of MT-ZVL. Hotspot and spatial autocorrelation analysis revealed clustering of infection cases in the Shaanxi-Shanxi border areas and in east of Shanxi province, where transmission increased rapidly over the study duration, as well as in well know high transmission areas in the south of Gansu province and the north of the Sichuan province. It indicates resurgence of MT-ZVL transmission over the latter three years of the study. Spatial clustering of infection was observed in localized areas, as well as sporadic outbreaks of infection.

scholarly journals Hot spot detection and spatio-temporal dynamics of dengue in Queensland, Australia

2014 ◽  
Vol XL-8 ◽  
pp. 197-204 ◽  
Author(s):  
S. Naish ◽  
S. Tong
Keyword(s):  
Temporal Variation ◽  
Temporal Dynamics ◽  
Hot Spot ◽  
Seasonal Pattern ◽  
Temporal Distribution ◽  
Health Concern ◽  
Spatial And Temporal Variation ◽  
Dengue Case ◽  
Spatio Temporal ◽  
Over Time

Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992&ndash;1993. This study explored spatio-temporal distribution and clustering of locally-acquired dengue cases in Queensland State, Australia and identified target areas for effective interventions. A computerised locally-acquired dengue case dataset was collected from Queensland Health for Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. Dengue hot spots were detected using SatScan method. Descriptive spatial analysis showed that a total of 2,398 locally-acquired dengue cases were recorded in central and northern regions of tropical Queensland. A seasonal pattern was observed with most of the cases occurring in autumn. Spatial and temporal variation of dengue cases was observed in the geographic areas affected by dengue over time. Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in tropical Queensland, Australia. There is a clear evidence for the existence of statistically significant clusters of dengue and these clusters varied over time. These findings enabled us to detect and target dengue clusters suggesting that the use of geospatial information can assist the health authority in planning dengue control activities and it would allow for better design and implementation of dengue management programs.

scholarly journals Spatial-temporal analysis and visualization of scarlet fever in mainland China from 2004 to 2017

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Wei-tong Li ◽  
Rui-hua Feng ◽  
Tong Li ◽  
Yan-bing Du ◽  
Nan Zhou ◽  
...  
Keyword(s):  
Surface Analysis ◽  
Scarlet Fever ◽  
Spatial Clustering ◽  
National Level ◽  
Mainland China ◽  
Temporal Distribution ◽  
Temporal Analysis ◽  
Trend Surface Analysis ◽  
Trend Surface ◽  
Spatio Temporal

This study retrospectively analyzed the spatio-temporal distribution and spatial clustering of scarlet fever in mainland China from 2004 to 2017. In recent years, the incidence of scarlet fever is increasing. Previous studies on the spatial distribution of scarlet fever in China are mainly focused at the provincial and municipal levels, and there is few systematic report on the spatial and temporal distribution characteristics of scarlet fever on the national level. Based on the incidence information of scarlet fever in mainland China between 2004 and 2017 collected from the China Center for Disease Control, this paper systematically explored the Spatio-temporal distribution of scarlet fever by three methods, contains spatial autocorrelation analysis, Spatio-temporal scanning analysis, and trend surface analysis. The results demonstrate that the incidence of scarlet fever varies by seasons, which is in line with double-peak distribution.The first peak generally occurs from May to June and the second one from November to December, while February and August is the lowest period of incidence. Trend surface analysis indicates that the incidence of scarlet fever in northern China is higher than the south, slightly higher in western compared to the east, and lower in the central part. Additionally, the results show that the clustering regions of scarlet fever centrally distributed in the northeast, northwest, north china and some provinces in the east, such as Zhejiang, Shanghai, Shandong, and Jiangsu.       

scholarly journals Spatio-temporal distribution and classification of utilization of urban bare lots in low-slope hilly regions

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0246746
Author(s):  
Qi Cao ◽  
Manjiang Shi
Keyword(s):  
Remote Sensing ◽  
Temporal Distribution ◽  
Urban Landscapes ◽  
Distribution Characteristics ◽  
Remote Sensing Images ◽  
Landscape Index ◽  
Activity Intensity ◽  
Transportation Service ◽  
Spatio Temporal

Urban bare lots are persistent phenomena in urban landscapes in the course of urbanization. In the present study, we examined the spatio-temporal distribution of urban bare lots in low-slope hilly areas, and to assess the major pathways by which they are generated and later re-transformed for exploitation. We extracted land use and land cover (LULC) change information and analyzed spatio-temporal distribution characteristics of urban bare lots using Landsat TM/OLI series remote sensing images. Subsequently, we proposed an index system for their evaluation and classification, and identified five types of urban bare lots. Urban bare lot quantity and distribution are closely correlated with human activity intensity. Stakeholders should consider the multiple effects of location, topography, landscape index, transportation, service facilities, and urban planning in urban bare lot classification activities for renovation and re-transformation.

Sign in / Sign up

Export Citation Format

Share Document