Futian District Research Articles

Analysis of genotype and age distribution of cervical human papillomavirus infection in Futian District, Shenzhen, China

Our study aims to understand the prevalence of cervical HPV (Human papilloma virus) infection, different subtypes causing infection and age distribution characteristics of women in Futian District, Shenzhen, China, to provide a reference for effective local prevention and treatment of HPV and targeted development and application of the HPV vaccine. Information on HPV results, age and HPV genotypes infected were collected and retrospectively analysed among women who attended the free cervical cancer screening programme conducted by the Shenzhen Futian District Government between 01 January 2016 and 31 December 2022 at our gynaecology outpatient clinics and medical check-up centres. There were 2792 positive cases among 27,738 females in Futian District, Shenzhen, with a positivity rate of 10.07%. Types 52, 58, 16, 68, 51, 39, 18, 31 and 33 were the top 9 infected genotypes in Futian District, Shenzhen, China. The high prevalence of these three genotypes, HR-HPV (High-risk human papilloma virus) types 68, 51 and 39, in the region is an important finding. Age-related differences in HPV infection rates were considerable, with the bimodal peak of the infection rate curve occurring in the age ranges of 30–34 and 60–65. The distribution of cervical HPV infection types in each region is unique, and different age groups have their susceptibility to different HPV genotypes. Geographical and age specificity should be considered in the therapeutic usage of vaccinations.

Clinical features and transmission risk analysis of dengue virus infections in Shenzhen, During 2014–2019

Dengue fever (DF) and dengue hemorrhagic fever (DHF) are among the most common tropical diseases affecting humans. To analyze the risk of clinical and transmission of DF/DHF in Shenzhen, the surveillance on patients of all-age patients with dengue virus (DENV) infections was conducted. Our findings revealed that the majority of DENV-infected patients are young to middle-aged males, and the development of the disease is accompanied by abnormal changes in the percentages of neutrophils, lymphocytes, and basophils. Demographic analysis revealed that these patients is concentrated in areas such as Futian District, which may be due to the higher mosquito density and temperature than that in other area. Subsequent, mosquito infection experiments confirmed that the effect of temperature shift on DENV proliferation and transmission. Not only that, constant temperatures can enhance the spread of DENV, even increase the risk of epidemic. Thus, the role of innate immune response should be highlighted in the prediction of severe severity of DENV-infected patients, and temperature should be taken into account in the prevention and control of DENV. IntroductionDengue fever (DF) and dengue hemorrhagic fever (DHF) are among the most common tropical diseases affecting humans, and which caused by the four dengue virus serotypes (DENV 1–4). ObjectivesTo analyze the risk of clinical and transmission of DF/DHF in Shenzhen. MethodsThe surveillance on patients of all-age patients with dengue virus (DENV) infections was conducted. ResultsOur findings revealed that the majority of DENV-infected patients are young to middle-aged males, and the development of the disease is accompanied by abnormal changes in the percentages of neutrophils, lymphocytes, and basophils. Demographic analysis revealed that these patients is concentrated in areas such as Futian District, which may be due to the higher mosquito density and temperature than that in other area. Subsequent, mosquito infection experiments confirmed that the effect of temperature shift on DENV proliferation and transmission. Not only that, constant temperatures can enhance the spread of DENV, even increase the risk of epidemic. Conclusion1. Elevated levels of neutrophils, lymphocytes, basophils, and temperature are all significant risk factors for dengue transmission and pathogenesis; 2. Temperature increasing is associated with a higher risk of dengue transmission; 3. Fluctuations in temperature around 28 °C (28 ± 5 °C) would increase dengue transmission.

Mangrovimonas futianensis sp. nov., a novel species isolated from mangrove sediment.

Three bacterial strains, designated as AS18T, AS27 and AS39, were obtained from mangrove sediment sampled in Futian district, Shenzhen, PR China. Cells of these strains were Gram-negative rods with no flagella. They were able to grow at 10-42 °C (optimum, 37 °C), at pH 5-9 (optimum, pH 6) and in 1-11 % (w/v) NaCl (optimum, 2 %). Phylogenetic analysis based on 16S rRNA gene sequences indicated that the new isolates were clustered within the genus Mangrovimonas, closely related to Mangrovimonas yunxiaonensis (95.1 % similarity) and Mangrovimonas spongiae (94.7 % similarity). Phylogenomic analysis based on multiple core genes revealed that the three strains were located in a different cluster from other closely related strains of the genus Mangrovimonas. Digital DNA-DNA hybridization, average nucleotide identity and average amino acid identity values calculated from genome sequences between isolates and type strains were lower than 25, 75 and 72 %, respectively. The dominant fatty acids were iso-C15 : 0 and iso-C15 : 1 G. The main respiratory quinone was identified as MK-6. The major polar lipids contained phosphatidylethanolamine, two unidentified aminolipids and five unidentified lipids. The results of multiphase taxonomy suggested that the three strains should be assigned to a novel species of the genus Mangrovimonas, for which the name Mangrovimonas futianensis sp. nov. is proposed, with the type strain AS18T (=GDMCC 1.2739T=JCM 34871T).

Urban road waterlogging risk assessment based on the source–pathway–receptor concept in Shenzhen, China

AbstractUrban roads are especially vulnerable to waterlogging during rainfall events. Assessments of urban road waterlogging risk are critical for disaster prevention and mitigation. This paper presents a rapid and practical approach for assessing the risk of urban road waterlogging based on a source–pathway–receptor concept and a digital elevation model (DEM). Waterlogging sources are identified by neighborhood analysis, overland flow pathways are extracted using a DEM, and the properties of cross‐nodes between pathways and roads are used to assess the waterlogging risk of roads. Futian District in Shenzhen, China, is selected as the study area. The risk results show that the waterlogging risk sources are clustered in residential land parcels and low‐lying road sections, while most road intersections and overpasses in the central area are at higher risks. The results also found that the waterlogging risk decreases as the road grade increases. Actual telephonic flooding records and reported waterlogging areas were used to validate the method, with the risk results displaying good agreement with the actual conditions. The prospects for generalizing this framework and its usage are discussed. The proposed approach provides support for pluvial flooding risk assessment and urban road waterlogging prevention.

Integrating Point-of-Interest Density and Spatial Heterogeneity to Identify Urban Functional Areas

Accurately identifying and delineating urban functional areas has seen increasing demand in smart urban planning, landscape design, and resource allocation. Recently, POI (point of interest) data have been increasingly applied to identify urban functional areas. However, heterogeneity in urban spaces or the corresponding POI data has not been fully considered in previous studies. In this study, we proposed a new scheme for urban-functional-area identification by combining POI data, OpenStreetMap (OSM) datasets, and high-resolution remote-sensing imagery. A function-intensity index that integrates the quantitative-density index and average-nearest-neighbor index (ANNI) of POIs was built for representing the urban function. The results show that the proposed function-intensity index can balance the impact of the spatial heterogeneity of each type of POI on determining the functional characteristics of the urban units. In Futian District, Shenzhen, China, the method was effective in distinguishing functional areas with fewer POI amounts but high ANNIs from those functional areas with dense POIs. The overall accuracy of the proposed method is about 11% higher than that of the method using the POI density only. This paper argues for considering both the quantitative density and spatial heterogeneity of POIs to improve urban-functional-area identification.

Flood Risk Assessment Using TELEMAC-2D Models Integrated with Multi-Index Analysis in Shenzhen River Basin, China

An urban flood simulation model based on TELEMAC-2D was constructed, and the inundation data of two measured rainstorms (7 June 2018 and 16 September 2018) were selected to validate the model. Flooding processes were simulated under 12 designed rainfall scenarios with rainfall return periods of 20, 50 and 100 years and rainfall peak coefficients of 0.2, 0.4, 0.6 and 0.8, respectively. The hazard-vulnerability (H-V) method was used for urban flood risk assessment. The selected hazard factors included inundation depth, flood velocity, elevation and slope. The vulnerability factors included land use type, population density and property distribution. The analytic hierarchy process (AHP) method was used to calculate the weight values of each indicator factor, and ArcGIS software was used for overlay calculation. The results of the analysis show that as the rainfall peak coefficient factor increases, the area of each risk zone increases to varying degrees. The larger the rainfall peak coefficient factor, the more serious the flooding. As the rainfall return period increases, the effect of the rainfall peak coefficient factor of the change in the area of the highest risk zone diminishes. The highest risk zone is the largest within Luohu District (LHD), accounting for 46.38%, 60.92% and 45.54% of the total highest risk area, respectively. As the return period increases, the area of the highest risk zone within Futian District (FTD) increases, but its proportion has a decreasing trend, and the proportion of the highest risk area within Longgang District (LGD) has an increasing trend. The risk zoning map can better reflect the risk distribution of the basin and provide a scientific basis for early warning of flood prevention and drainage in the Shenzhen River basin.

Revealing Taxi Interaction Network of Urban Functional Area Units in Shenzhen, China

Characterizing the taxi travel network is of fundamental importance to our understanding of urban mobility, and could provide intellectual support for urban planning, traffic congestion, and even the spread of diseases. However, the research on the interaction network between urban functional area (UFA) units are limited and worthy of notice. Therefore, this study has applied the taxi big data to construct a travel flow network for the exploration of spatial interaction relationships between different UFA units in Shenzhen, China. Our results suggested that taxi travel behavior was more active in UFA units dominated by functions, including residential, commercial, scenic, and greenspace during weekends, while more active in UFA units dominated by industrial function during weekdays. In terms of daily average volume, the characteristics of spatial interaction between the various UFA types during weekdays and weekends were similar. During the morning peak period, the sink areas were mainly distributed in Futian District and Nanshan District, while during the evening peak period, the sink areas were mainly distributed in the southern part of Yantian District, the southwestern part of Longgang District, and the eastern part of Luohu District. The average daily taxi mobility network during weekdays showed a spatial pattern of “dense in the west and north, sparse in the south and east”, exhibiting significant spatial unevenness. Compared with weekdays, the daily taxi mobility network during weekends was more dispersed and the differences in node sizes decreased, indicating that taxi travel destinations were more diverse. The pattern of communities was more consistent with the administrative division during weekdays, indicating that taxi trips are predominantly within the districts. Compared with weekdays, the community pattern of network during weekends was clearly different and more in line with the characteristics of a small world network. The findings can provide a better understanding of urban mobility characteristics in Shenzhen, and provide a reference for urban transportation planning and management.

Epidemiological Characteristics of COVID-19 and Effective Public Health Interventions in Shenzhen, China.

Objectives:This study aims to analyze and summarize the epidemic characteristics of coronavirus disease 2019 (COVID-19), and the public heath interventions in Shenzhen from 1 January 2022 to 4 April 2022, hoping to provide useful reference for resurgence.MethodsData were extracted from the website of Shenzhen Municipal Health Commission from 1 January 2022 to 4 April 2022. The number of new indigenous patients, imported patients, symptomatic and asymptomatic patients, age, gender, regional distribution, screening routes, and clinical subtype were analyzed. The public health interventions were summarized and described.ResultsThere have been 1,215 new indigenous cases and 1,447 imported cases in Shenzhen from 1 January 2022 to 4 April 2022. The age group of the indigenous cases range from 2 months to 92 years. The median age was 35.0. The male-to-female ratio was 1.13 (623:551). The number of symptomatic and asymptomatic patients were 930 (76.5%) and 285 (23.5%), respectively, without death. Shenzhen has experienced three outbreaks. Futian District has the large proportion of confirmed cases (55.8%), followed by Nanshan (13.5%), and Baoan District (13.5%). The indigenous confirmed cases were mainly screened from close contacts under quarantine observation (632 cases, 53.8%), key areas (304 cases, 25.9%), key crowds (93 cases, 7.9%), and communities (145, 12.4%). Among the imported cases outside the Chinses Mainland, China's Hong Kong had the largest number of confirmed cases (n = 1,368), followed by Singapore (n = 18), South Korea (n = 18), and Japan (n = 14). The Shenzhen government quickly implemented effective measures, including citywide screening, quarantine, tracking, classified management for different groups and the dividing epidemic-hit communities, villages into three regions (sealed area, controlled area, and prevention area), and expand the capacity of designated hospitals, etc., which effectively controlled the outbreaks. By 4 April 2022, no new local cases had been reported.ConclusionsThree novel COVID-19 outbreaks occurred in Shenzhen between 1 January to 4 April 2022, linked to importation from outside the Chinese Mainland and subsequently caused the local transmission. The measures of citywide testing–tracking–classified management by risk level have effectively controlled the epidemic and should be continued to prevent resurgence.

Evaluation of Medical Carrying Capacity for Megacities from a Traffic Analysis Zone View: A Case Study in Shenzhen, China

Sustainable Development Goals propose to build inclusive, safe, resilient, and sustainable cities and human settlements, which requires us to scientifically evaluate the carrying capacity of current urban public service facilities, but there is still a lack of in-depth exploration of urban public medical service facilities. Therefore, this paper, within the mobile phone signaling data, improved the potential model and carrying capacity evaluation model of public medical facilities, explored the spatial pattern distribution of public medical resources in Shenzhen, and analyzed the current situation of carrying capacity of public medical resources. The study showed that: (1) the overall spatial distribution of public medical resources in Shenzhen is uneven, showing a pattern of multicenter aggregation and multilevel development; (2) the service potential of public medical facilities has obvious spatial variations, with Futian District, Dapeng New District, and Nanshan District showing more obvious high-gravitational-value aggregation centers; (3) medical facilities in Shenzhen are never empty, but the problems of medical underloading and overloading are severe, and spatial allocation and utilization efficiency need to be further optimized. The research results can provide a scientific basis for the research on the allocation and sustainable construction of medical resources in megacities.

"Chinese style" becomes popular in accordion music, creating brilliance by works at home and abroad -- a review of the second "Chinese style" International Accordion composition competition

On October 1, 2021, the second "Chinese style" International Accordion composition competition hosted by the Publicity Department of Futian District Party committee of Shenzhen and Futian District Public Culture and sports development center of Shenzhen was held in Shenzhen Youth Activity Center, becoming another cultural activity that helps inherit Chinese national style music creation, enrich accordion works and promote the high-quality development of domestic accordion music after the "First Futian Cup International Accordion composition competition (the second competition has been renamed)".
 In addition, the competition gained the strong support from well-known art colleges at home and abroad, including the Central Conservatory of music, Tianjin Conservatory of music, Shanghai Conservatory of music and so on. The chairman of the jury of this competition is Mr. Cao Xiaoqing, and members of the jury consisted of world-famous composers, accordion players and professors, therefore, this competition is one of few professional accordion composing events in the world.

Exploring the Effects of Roadside Vegetation on the Urban Thermal Environment Using Street View Images.

Roadsides are important urban public spaces where residents are in direct contact with the thermal environment. Understanding the effects of different vegetation types on the roadside thermal environment has been an important aspect of recent urban research. Although previous studies have shown that the thermal environment is related to the type and configuration of vegetation, remote sensing-based technology is not applicable for extracting different vegetation types at the roadside scale. The rapid development and usage of street view data provide a way to solve this problem, as street view data have a unique pedestrian perspective. In this study, we explored the effects of different roadside vegetation types on land surface temperatures (LSTs) using street view images. First, the grasses–shrubs–trees (GST) ratios were extracted from 19,596 street view images using semantic segmentation technology, while LST and normalized difference vegetation index (NDVI) values were extracted from Landsat-8 images using the radiation transfer equation algorithm. Second, the effects of different vegetation types on roadside LSTs were explored based on geographically weighted regression (GWR), and the different performances of the analyses using remotely sensed images and street view images were discussed. The results indicate that GST vegetation has different cooling effects in different spaces, with a fitting value of 0.835 determined using GWR. Among these spaces, the areas with a significant cooling effect provided by grass are mainly located in the core commercial area of Futian District, which is densely populated by people and vehicles; the areas with a significant cooling effect provided by shrubs are mainly located in the industrial park in the south, which has the highest industrial heat emissions; the areas with a significant cooling effect provided by trees are mainly located in the core area of Futian, which is densely populated by roads and buildings. These are also the areas with the most severe heat island effect in Futian. This study expands our understanding of the relationship between roadside vegetation and the urban thermal environment, and has scientific significance for the planning and guiding of urban thermal environment regulation.

Improving Urban Land Cover Mapping with the Fusion of Optical and SAR Data Based on Feature Selection Strategy

Taking the Futian District as the research area, this study proposed an effective urban land cover mapping framework fusing optical and SAR data. To simplify the model complexity and improve the mapping results, various feature selection methods were compared and evaluated. The results showed that feature selection can eliminate irrelevant features, increase the mean correlation between features slightly, and improve the classification accuracy and computational efficiency significantly. The recursive feature elimination-support vector machine (RFE-SVM) model obtained the best results, with an overall accuracy of 89.17% and a kappa coefficient of 0.8695, respectively. In addition, this study proved that the fusion of optical and SAR data can effectively improve mapping and reduce the confusion between different land covers. The novelty of this study is with the insight into the merits of multi-source data fusion and feature selection in the land cover mapping process over complex urban environments, and to evaluate the performance differences between different feature selection methods.

Improving Urban Land Cover Mapping with the Fusion of Optical and SAR Data Based on Feature Selection Strategy

Taking the Futian District as the research area, this study proposed an effective urban land cover mapping framework fusing optical and SAR data. To simplify the model complexity and improve the mapping results, various feature selection methods were compared and evaluated. The results showed that feature selection can eliminate irrelevant features, increase the mean correlation between features slightly, and improve the classification accuracy and computational efficiency significantly. The recursive feature elimination-support vector machine (RFE-SVM) model obtained the best results, with an overall accuracy of 89.17% and a kappa coefficient of 0.8695, respectively. In addition, this study proved that the fusion of optical and SAR data can effectively improve mapping and reduce the confusion between different land covers. The novelty of this study is with the insight into the merits of multi-source data fusion and feature selection in the land cover mapping process over complex urban environments, and to evaluate the performance differences between different feature selection methods.

Urban livability: Agent-based simulation, assessment, and interpretation for the case of Futian District, Shenzhen

The livability of a city, which includes social, economic, environmental, and other connotations, assumes a central role in determining the quality of life. Only when the city develops in a coordinated manner in these aspects can it truly build a sustainable urbanism. Current literature on urban livability show gaps in terms of its measurement and assessment, especially from a dynamic point of view. To address these gaps, in this paper we design an indicator system for measuring urban livability which is built upon a comprehensive synthesis of existing literature to our knowledge. Based on the indicator system, we build an agent-based simulation model on the NetLogo platform for urban livability which utilizes multi-source geographical data. In applying the model in our study case, Futian District, Shenzhen, the simulated livability scores are tested valid and robust, thus hinting its potentials for generalization. A further global sensitivity analysis on the simulation results reveals the first- and second-order factors’ contribution structure to the overall livability score, which proves a useful tool in policy analysis. The simulation tools developed in this paper constitute a practical approach for sustainable development of cities in supporting governance policy evaluation and design, and the methodological framework offers a new scope for understanding the mechanisms of the making of urban livability.

High-resolution assessment of urban disaster resilience: a case study of Futian District, Shenzhen, China

Quantifying urban disaster resilience is needed to strengthen the capacity of urban disaster prevention and mitigation strategies. In previous studies, the spatial unit used for urban disaster resilience assessment was coarse, which could easily cause local differences to be overlooked. To rectify the problem, this study integrated high spatial-resolution urban grid data and built an index system from economic, social, administrative, and technological dimensions. On this basis, both exponential decay function and spatial analysis techniques were applied to establish a high-precision evaluation method of urban disaster resilience. The results showed that the urban disaster resilience of Futian District (FTUDRI) had a certain spatial aggregation effect, with an average of 0.37 ± 0.08, which was at a middle level. Areas with low and middle-low levels of FTUDRI which accounted for 27.28% were mainly located in the western, northern, and southern edges of Futian District, with undeveloped economy and inadequate emergency infrastructures. We considered the neighborhood impact of point indicators on urban disaster resilience and the results indicated if we neglected this there would be an underestimation of the urban disaster resilience assessment. Hospitals, administrations, and emergency material points were key driving indicators for improving FTUDRI. In conclusion, our results demonstrated the necessity of pursuing high-resolution urban disaster resilience assessments and the effectiveness of the newly proposed method. The results of this study can provide policymakers with a clear location of where a low level of urban disaster resilience occurs, providing a basis for urban disaster prevention and improvement measures.

Study on an Artificial Society of Urban Safety Livability Change

Improving the urban livability status has become the core goal of urban development, and reasonable assessment of the urban livability status and impact is crucial. By combining an objective environment with residents’ subjective cognition, an artificial society (urban livability change artificial society; ULC-AS) is constructed. The ULC-AS includes four types of agents, namely, government, family, resident and safety facility management agency agents, and recognizes dynamic interaction among various agents and between agents and the environment. Taking the Futian District of Shenzhen as an example, this paper examines factors such as migrants, birth policies, and government investment. We simulate the interactions among resident satisfaction changes, relocation decision-making behavior and urban safety livability and analyze the change processes and development trends of urban safety livability under multiple scenarios. Our main result indicates that population change and investment construction are important factors affecting urban safety livability. At present, the population of the Futian District is saturated. Therefore, the government must assess the urban safety livability and increase investment in high-demand areas. Through this method, the goals of urban resource allocation optimization and coordinated urban development can be achieved.

Identification of Urban Rainstorm Waterlogging Based on Multi-source Information Fusion：A Case Study in Futian District, Shenzhen

Flood disasters have become one of the most threatening natural disasters in the world, in which waterlogging is the most common form in the context of highly urbanized megacities. The formation of flood disaster is related to many factors and involves information from multiple sources, making it difficult be predicted. This paper integrates multi-source information data, classifies the study area into different categories according to hydrological analysis results, and combines hydrodynamic theory and ArcGIS to get the quantitative prediction of the range and depth of waterlogging under different rainfall inputs. The evaluation results provide the government with accurate and timely information of waterlogging risks and locations in order to improve promptness of emergency management such as evacuation and managing traffics.

An Adaptive Network-Constrained Clustering (ANCC) Model for Fine- Scale Urban Functional Zones

Urban functional zones are considered significant components for understanding urban landscape patterns in the socioeconomic environment. Although the spatial configuration of road networks contributes to urban function delineation at the block level, the morphological uncertainties caused by the road network structure in fine-scale urban function retrieval are ignored. This paper proposes an adaptive network-constrained clustering (ANCC) model to map urban function distributions at a finer level. By utilizing points of interest (POIs) to indicate independent functional places, the adaptive road configuration with a multilevel bandwidth selection strategy is proposed. On this basis, a term frequency–inverse document frequency-weighted latent Dirichlet allocation (TW-LDA) topic model is designed to delineate urban functions from semantic information. Taking Futian District, Shenzhen, as a case study, the results show an overall accuracy of approximately 77.10% in urban function mapping. A comparison of a block-level mapping model, a non-adaptive network-based model and the ANCC model reveals accuracies of 53.10%, 59.20% and 77.10%, respectively, indicating the advantages of the ANCC model for improving urban function mapping accuracy. The proposed ANCC model shows potential application prospects in monitoring urban land use for sustainable city planning.

Remote pharmacy service in primary care: The implementation of a cloud-based pre-prescription review system

BackgroundTo reduce the occurrence of inappropriate prescription in primary care through the introduction of a cloud-based pre-prescription review system. ObjectiveWe aimed to describe the implementation of a cloud-based pre-prescription review system in the pharmacy practice of Chinese community health centers (CHCs), which currently have few qualified pharmacists. Practice descriptionThe cloud-based pre-prescription review system featured reviews by remote clinical pharmacists and targeted the prevention of inappropriate prescription in primary care. Practice innovationThis study describes the implementation of remote pharmacy at 22 CHCs in Futian District, Shenzhen, China. A pre-prescription system was developed and deployed in the cloud, which is linked to CHCs, and a consortium of qualified clinical pharmacists located in tertiary hospital. All prescriptions were mandatorily reviewed before printing and payment. First, prescriptions were reviewed using cloud-based rational drug use software. Then any detected potentially inappropriate prescriptions were reviewed by the remote pharmacist. The pharmacist consortium also modified review rules to improve efficiency and accuracy. Evaluation methodsThe frequency and proportions of potentially inappropriate prescriptions identified by the review software and the remote pharmacist consortium were analyzed descriptively. ResultsDuring the 6-month study period (July 1, 2019-December 31, 2019), 340,117 prescription entries from general practitioners in 22 community health care centers were reviewed. Of these, 6479 (3.0%) unique potential entries were suspended for pharmacist review, of which 3230 (49.9%) needed correction from prescribers in the CHCs. The most common corrections were related to improper administration routes or drug-drug interactions or had no justified indications. ConclusionInappropriate prescription is not uncommon in CHCs. The cloud-based prescription prereview model proposed in this study can serve as an important tool for the prevention of inappropriate prescription in primary care. The pre-prescription review system also provided opportunities for pharmacists to participate in the enhancement of patient care in primary care.

Epidemic-related sites in covid-19 media reports

Background: Since the outbreak of the COVID-19 virus in Wuhan, China, in early 2020, the Chinese government has formed a mode of information disclosure. More than 400 cities have announced specific location information for newly diagnosed cases of novel coronavirus pneumonia, including residential areas or places of stay. We have established a conditional random field model and a rule-dependent model based on Chinese geographical name elements. Taking Guangdong Province as an example, the identification of named entities and the automatic extraction of epidemic-related sites are carried out. This method will help locate the spread of the epidemic, prevent and control the spread of the epidemic, and gain more time for vaccine clinical trials. Methods: Based on the presentation form of the habitual place or place of stay of the diagnosed cases in the text of the web page, a conditional random field model is established, and a rule-dependent model is established according to the combination rule of the elements of the place words and the place name dictionary composed of provinces, cities and administrative regions. Findings: The results of the analysis based on the conditional random field model and the rule-dependent model show that the location of confirmed cases of new coronavirus pneumonia in Guangdong Province in mid-February is mainly concentrated in Guangzhou，Shenzhen，Zhuhai and Shantou Cities. In Guangzhou, Futian District has more epidemicsites and Huangpu and Conghua District have fewer epidemic sites. Government officials in Guangzhou City should pay attention to Futian District. Interpretation: Governments at all levels in Guangzhou Province have intervened to control the epidemic through various means in mid-February. According to the results of the model analysis, we believe that the administrative regions with more diagnosed locations should focus on and take measures such as blockades and control of personnel flow to control the disease in those administrative regions to avoid affecting other adjacent administrative regions.