ArticleBMC infectious diseases2021
Spatiotemporal heterogeneity and its determinants of COVID-19 transmission in typical labor export provinces of China.
Article in BMC infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Spatio-Temporal COVID-19 Modeling: A Global Systematic Review of Data Integration, Equity, and Lessons for Pandemic Preparedness.International journal of environmental research and public health · 2026Pooled it
- Methods Used in the Spatial and Spatiotemporal Analysis of COVID-19 Epidemiology: A Systematic Review.International journal of environmental research and public health · 2022Pooled it
- Correlation between notifiable infectious diseases and transportation passenger traffic from 2013 to 2019 in mainland China.BMC public health · 2024Article
- Spatial distribution characteristics and influencing factors of youth soccer specialty schools in China.Scientific reports · 2024Article
- Determinants of health poverty vulnerability in rural areas of Western China in the post-poverty relief era: an analysis based on the Anderson behavioral model.BMC public health · 2024Article
- Using Regional Sero-Epidemiology SARS-CoV-2 Anti-S Antibodies in the Dominican Republic to Inform Targeted Public Health Response.Tropical medicine and infectious disease · 2023Article
- Spatial analysis of overweight prevalence in China: exploring the association with air pollution.BMC public health · 2023Article
- Integrative Effects between a Bubble and Seal Program and Workers' Compliance to Health Advice on Successful COVID-19 Transmission Control in a Factory in Southern Thailand.International journal of environmental research and public health · 2022Article
- A joint Bayesian spatiotemporal risk prediction model of COVID-19 incidence, IC admission, and death with application to Sweden.The Annals of regional science · 2022Article
- Use of Recently Vaccinated Individuals to Detect Bias in Test-Negative Case-Control Studies of COVID-19 Vaccine Effectiveness.Epidemiology (Cambridge, Mass.) · 2022Article
- Identifying spatiotemporal patterns of COVID-19 transmissions and the drivers of the patterns in Toronto: a Bayesian hierarchical spatiotemporal modelling.Scientific reports · 2022Article
- The Geographical Distribution and Influencing Factors of COVID-19 in China.Tropical medicine and infectious disease · 2022Article
- Establishment of hospital resilience framework in urban China: insight from Wuhan City.Computational urban science · 2022Article
- Tracking and Controlling the Spatiotemporal Spread of SARS-CoV-2 Lineage B.1.1.7 in COVID-19 Reopenings.GeoHealth · 2021Article
- Spatial heterogeneity of bacillary dysentery and the impact of temperature in the Beijing-Tianjin-Hebei region of China.International journal of biometeorology · 2021Article
- Study of SARS-CoV-2 transmission in urban environment by questionnaire and modeling for sustainable risk control.Journal of hazardous materials · 2021Article
- Spatio-temporal variation in tuberculosis incidence and risk factors for the disease in a region of unbalanced socio-economic development.BMC public health · 2021Article
- Emergence of universality in the transmission dynamics of COVID-19.Scientific reports · 2021Article
- Spatial pattern of the population casualty rate caused by super typhoon Lekima and quantification of the interactive effects of potential impact factors.BMC public health · 2021Article
- Determinant Powers of Socioeconomic Factors and Their Interactive Impacts on Particulate Matter Pollution in North China.International journal of environmental research and public health · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundPrevious 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.
methodsA 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.
resultsThe 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.
conclusionsCOVID-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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.