{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:52:50Z","timestamp":1760147570327,"version":"build-2065373602"},"reference-count":51,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,2,14]],"date-time":"2023-02-14T00:00:00Z","timestamp":1676332800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China (NSFC)","doi-asserted-by":"publisher","award":["52208039","2020YFF0304900","KM202210009008","LP190100089"],"award-info":[{"award-number":["52208039","2020YFF0304900","KM202210009008","LP190100089"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National key R&amp;D program \u201cScience and Technology Winter Olympics\u201d key project \u201cEvacuation system and support technology for assisting physically challenged communities\u201d","award":["52208039","2020YFF0304900","KM202210009008","LP190100089"],"award-info":[{"award-number":["52208039","2020YFF0304900","KM202210009008","LP190100089"]}]},{"name":"Beijing High-level Overseas Talents Support Funding","award":["52208039","2020YFF0304900","KM202210009008","LP190100089"],"award-info":[{"award-number":["52208039","2020YFF0304900","KM202210009008","LP190100089"]}]},{"DOI":"10.13039\/501100003213","name":"R&amp;D Program of Beijing Municipal Education Commission","doi-asserted-by":"publisher","award":["52208039","2020YFF0304900","KM202210009008","LP190100089"],"award-info":[{"award-number":["52208039","2020YFF0304900","KM202210009008","LP190100089"]}],"id":[{"id":"10.13039\/501100003213","id-type":"DOI","asserted-by":"publisher"}]},{"name":"NCUT Young Scholar Development Project","award":["52208039","2020YFF0304900","KM202210009008","LP190100089"],"award-info":[{"award-number":["52208039","2020YFF0304900","KM202210009008","LP190100089"]}]},{"DOI":"10.13039\/501100000923","name":"Australian Research Council Linkage Project","doi-asserted-by":"publisher","award":["52208039","2020YFF0304900","KM202210009008","LP190100089"],"award-info":[{"award-number":["52208039","2020YFF0304900","KM202210009008","LP190100089"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>The outbreak of COVID-19 in Beijing has been sporadic since the beginning of 2022 and has become increasingly severe since October. In China\u2019s policy of insisting on dynamic clearance, fine-grained management has become the focus of current epidemic prevention and control. In this paper, we conduct a refined COVID-19 risk prediction and identification of its influencing factors in Beijing based on neighborhood-scale spatial statistical units. We obtained geographic coordinate data of COVID-19 cases in Beijing and quantified them into risk indices of each statistical unit. Additionally, spatial autocorrelation was used to analyze the epidemic risk clustering characteristics. With the multi-source data, 20 influencing elements were constructed, and their spatial heterogeneity was explored by screening 8 for Multiscale Geographically weighted regression (MGWR) model analysis. Finally, a neural network classification model was used to predict the risk of COVID-19 within the sixth ring of Beijing. The MGWR model and the neural network classification model showed good performance: the R2 of the MGWR model was 0.770, and the accuracy of the neural network classification model was 0.852. The results of this study show that: (1) COVID-19 risk is uneven, with the highest clustering within the Fifth Ring Road of Beijing; (2) The results of the MGWR model show that population structure, population density, road density, residential area density, and living service facility density have significant spatial heterogeneity on COVID-19 risk; and (3) The prediction results show a high COVID-19 risk, with the most severe risk being in the eastern, southeastern and southern regions. It should be noted that the prediction results are highly consistent with the current epidemic situation in Shijingshan District, Beijing, and can provide a strong reference for fine-grained epidemic prevention and control in Beijing.<\/jats:p>","DOI":"10.3390\/ijgi12020069","type":"journal-article","created":{"date-parts":[[2023,2,15]],"date-time":"2023-02-15T03:37:24Z","timestamp":1676432244000},"page":"69","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multi-Source Data and Machine Learning-Based Refined Governance for Responding to Public Health Emergencies in Beijing: A Case Study of COVID-19"],"prefix":"10.3390","volume":"12","author":[{"given":"Demiao","family":"Yu","sequence":"first","affiliation":[{"name":"School of Architecture and Art, North China University of Technology, Beijing 100144, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8702-2805","authenticated-orcid":false,"given":"Xiaoran","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Architecture and Art, North China University of Technology, Beijing 100144, China"},{"name":"Centre for Design Innovation, Swinburne University of Technology, Hawthorn, VIC 3122, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7338-2212","authenticated-orcid":false,"given":"Hengyi","family":"Zang","sequence":"additional","affiliation":[{"name":"School of Architecture and Art, North China University of Technology, Beijing 100144, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanwei","family":"Li","sequence":"additional","affiliation":[{"name":"Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization, Henan University, Kaifeng 475001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuchen","family":"Qin","sequence":"additional","affiliation":[{"name":"School of Architecture, Huaqiao University, Xiamen 361021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daoyong","family":"Li","sequence":"additional","affiliation":[{"name":"School of Architecture and Art, North China University of Technology, Beijing 100144, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,14]]},"reference":[{"key":"ref_1","unstructured":"(2022, September 23). 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