Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Background: Previous studies have indicated that the risk of infectious disease spread is greatest in locations where a population has massive and convenient access to the epicenter of an outbreak. However, the spatiotemporal variations and risk determinants of COVID-19 in typical labor export regions of China remain unclear. Understanding the geographical distribution of the disease and the socio-economic factors affecting its transmission is critical for disease prevention and control.

Methods: A total of 2152 COVID-19 cases were reported from January 21 to February 24, 2020 across the 34 cities in Henan and Anhui. A Bayesian spatiotemporal hierarchy model was used to detect the spatiotemporal variations of the risk posed by COVID-19, and the GeoDetector q statistic was used to evaluate the determinant power of the potential influence factors.

Results: The risk posed by COVID-19 showed geographical spatiotemporal heterogeneity. Temporally, there was an outbreak period and control period. Spatially, there were high-risk regions and low-risk regions. The high-risk regions were mainly in the southwest areas adjacent to Hubei and cities that served as economic and traffic hubs, while the low-risk regions were mainly in western Henan and eastern Anhui, far away from the epicenter. The accessibility, local economic conditions, and medical infrastructure of Wuhan in Hubei province all played an important role in the spatiotemporal heterogeneity of COVID-19 transmission. The results indicated that the q statistics of the per capita GDP and the proportion of primary industry GDP were 0.47 and 0.47, respectively. The q statistic of the population flow from Wuhan was 0.33. In particular, the results showed that the q statistics for the interaction effects between population density and urbanization, population flow from Wuhan, per capita GDP, and the number of doctors were all greater than 0.8.

Conclusions: COVID-19 showed significant spatiotemporal heterogeneity in the labor export regions of China. The high-risk regions were mainly located in areas adjacent to the epicenter as well as in big cities that served as traffic hubs. Population access to the epicenter, as well as local economic and medical conditions, played an important role in the interactive effects of the disease transmission.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7935008PMC
http://dx.doi.org/10.1186/s12879-021-05926-xDOI Listing

Publication Analysis

Top Keywords

spatiotemporal heterogeneity
16
labor export
12
high-risk regions
12
determinants covid-19
8
covid-19 transmission
8
typical labor
8
access epicenter
8
spatiotemporal variations
8
variations risk
8
export regions
8

Similar Publications

Spatial heterogeneity in the impacts of Ohio's enhanced graduated driver's licensing law on teen motor vehicle crashes.

J Safety Res

September 2025

Center for Injury Research and Policy, Abigail Wexner Research Institute at Nationwide Children's Hospital, Department of Pediatrics, College of Medicine, The Ohio State University, Division of Epidemiology, College of Public Health, USA.

Background: Graduated Driver's Licensing (GDL) policies create an intermediate licensure phase for young novice drivers, and previous studies suggested that they reduce teen motor- vehicle crashes (MVCs). Multiple studies have shown that the effects of GDL laws vary in association with demographic factors and location, motivating estimation of sub-state policy effects. The present study estimates county-level effects of Ohio's 2007 enhanced GDL law on MVCs among 16-17-year-olds.

View Article and Find Full Text PDF

Dynamics of a pine wilt disease control model with nonlocal competition and memory diffusion.

Math Biosci

September 2025

Department of Mathematics, Western University, London, Ontario, N6A 5B7, Canada. Electronic address:

Pine wilt disease (PWD) is mainly spread by Monochamus alternatus (in short, M. alternatus). Woodpecker, as the natural predator of M.

View Article and Find Full Text PDF

Spatiotemporal characteristics, drivers, sources, and health risks of nitrate and sulfate in groundwater on the Chinese Loess Plateau.

Water Res

September 2025

Key Laboratory of Groundwater Remediation of Hebei Province and China Geological Survey, Shijiazhuang, 050061, China; The Institute of Hydrogeology and Environmental Geology, Chinese Academy of Geosciences, Shijiazhuang, 050061, China.

Groundwater nitrate (NO) and sulfate (SO) pollution in semi-arid regions has attracted widespread attention. However, unveiling the dynamics and sources of NO and SO in regional groundwater is challenging because of complex anthropogenic activities and hydrogeological conditions. This study combined physicochemistry and multiple stable isotopes (δH-HO, δO-HO, δN-NO, δO-NO, δS-SO, and δO-SO) to explore the spatiotemporal patterns, driving factors, sources, and potential health hazards of NO and SO in groundwater on the Loess Plateau, China.

View Article and Find Full Text PDF

Self-enriching nanozyme with photothermal-cascade amplification for tumor microenvironment-responsive synergistic therapy and enhanced photoacoustic imaging.

Mater Today Bio

October 2025

Yunnan Key Laboratory of Breast Cancer Precision Medicine, Institute of Biomedical Engineering, Kunming Medical University, Kunming, 650500, Yunnan, China.

Achieving precise intratumoral accumulation and coordinated activation remains a major challenge in nanomedicine. Photothermal therapy (PTT) provides spatiotemporal control, yet its efficacy is hindered by heterogeneous distribution of PTT agents and limited synergy with other modalities. Here, we develop a dual-activation nanoplatform (IrO-P) that integrates exogenous photothermal stimulation with endogenous tumor microenvironment (TME)-responsive catalysis for synergistic chemodynamic therapy (CDT) and ferroptosis induction.

View Article and Find Full Text PDF

Understanding the intricate relationship between land use/land cover (LULC) transformations and land surface temperature (LST) is critical for sustainable urban planning. This study investigates the spatiotemporal dynamics of LULC and LST across Delhi, India, using thermal data from Landsat 7 (2001), Landsat 5 (2011) and Landsat 8 (2021) resampled to 30-m spatial resolution, during the peak summer month of May. The study aims to target three significant aspects: (i) to analyse and present LULC-LST dynamics across Delhi, (ii) to evaluate the implications of LST effects at the district level and (iii) to predict seasonal LST trends in 2041 for North Delhi district using the seasonal auto-regressive integrated moving average (SARIMA) time series model.

View Article and Find Full Text PDF