{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T06:51:42Z","timestamp":1769842302653,"version":"3.49.0"},"reference-count":23,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2022,8,3]],"date-time":"2022-08-03T00:00:00Z","timestamp":1659484800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"Introduction:<\/jats:title>Coronavirus disease (COVID-19) rapidly spread from Wuhan, China to other parts of China and other regions\/countries around the world, resulting in a pandemic due to large populations moving through the massive transport hubs connecting all regions of China via<\/jats:italic> railways and a major international airport. COVID-19 will remain a threat until safe and effective vaccines and antiviral drugs have been developed, distributed, and administered on a global scale. Thus, there is urgent need to establish effective implementation of preemptive non-pharmaceutical interventions for appropriate prevention and control strategies, and predicting future COVID-19 cases is required to monitor and control the issue.<\/jats:p><\/jats:sec>Methods<\/jats:title>This study attempts to utilize a three-layer graph convolutional network (GCN) model to predict future COVID-19 cases in 190 regions and countries using COVID-19 case data, commercial flight route data, and digital maps of public transportation in terms of transnational human mobility. We compared the performance of the proposed GCN model to a multilayer perceptron (MLP) model on a dataset of COVID-19 cases (excluding the graph representation). The prediction performance of the models was evaluated using the mean squared error.<\/jats:p><\/jats:sec>Results<\/jats:title>Our results demonstrate that the proposed GCN model can achieve better graph utilization and performance compared to the baseline in terms of both prediction accuracy and stability.<\/jats:p><\/jats:sec>Discussion<\/jats:title>The proposed GCN model is a useful means to predict COVID-19 cases at regional and national levels. Such predictions can be used to facilitate public health solutions in public health responses to the COVID-19 pandemic using deep learning and data pooling. In addition, the proposed GCN model may help public health policymakers in decision making in terms of epidemic prevention and control strategies.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fpubh.2022.911336","type":"journal-article","created":{"date-parts":[[2022,8,3]],"date-time":"2022-08-03T04:46:06Z","timestamp":1659501966000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["A graph convolutional network for predicting COVID-19 dynamics in 190 regions\/countries"],"prefix":"10.3389","volume":"10","author":[{"given":"Sumiko","family":"Anno","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tsubasa","family":"Hirakawa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Satoru","family":"Sugita","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shinya","family":"Yasumoto","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2022,8,3]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1007\/s15010-020-01401-y","article-title":"2019 Novel coronavirus: where we are and what we know","volume":"48","author":"Cheng","year":"2020","journal-title":"Infection."},{"key":"B2","doi-asserted-by":"publisher","first-page":"1199","DOI":"10.1056\/NEJMoa2001316","article-title":"Early transmission dynamics in Wuhan, China, of novel coronavirus\u2013infected pneumonia","volume":"382","author":"Li","year":"2020","journal-title":"N Engl J Med."},{"key":"B3","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1016\/j.ijid.2020.01.009","article-title":"The continuing 2019-nCoV epidemic threat of novel coronaviruses to global health-The latest 2019 novel coronavirus outbreak in Wuhan, China","volume":"91","author":"Hui","year":"2020","journal-title":"Int J Infect Dis."},{"key":"B4","doi-asserted-by":"publisher","first-page":"514","DOI":"10.1016\/S0140-6736(20)30154-9","article-title":"A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster","volume":"395","author":"Chan","year":"2020","journal-title":"Lancet."},{"key":"B5","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1186\/s40779-020-00240-0","article-title":"The origin, transmission and clinical therapies on coronavirus disease 2019 (COVID-19) outbreak\u2013an update on the status","volume":"7","author":"Guo","year":"2020","journal-title":"Mil Med Res."},{"key":"B6","doi-asserted-by":"publisher","first-page":"1679","DOI":"10.3390\/ijerph17051679","article-title":"Prediction of epidemic spread of the 2019 novel coronavirus driven by spring festival transportation in China: a population-based study","volume":"17","author":"Fan","year":"2020","journal-title":"Int J Environ Res Public Health."},{"key":"B7","doi-asserted-by":"publisher","first-page":"717","DOI":"10.1093\/ije\/dyaa033","article-title":"The SARS, MERS and novel coronavirus (COVID-19) epidemics, the newest and biggest global health threats: what lessons have we learned?","volume":"49","author":"Peeri","year":"2020","journal-title":"Int J Epidemiol."},{"key":"B8","doi-asserted-by":"publisher","first-page":"taaa008","DOI":"10.1093\/jtm\/taaa008","article-title":"Pneumonia of unknown etiology in Wuhan, China: potential for international spread via commercial air travel","volume":"27","author":"Bogoch","year":"2020","journal-title":"J Travel Med."},{"key":"B9","doi-asserted-by":"publisher","first-page":"601","DOI":"10.3390\/jcm9020601","article-title":"Assessing the impact of reduced travel on exportation dynamics of novel coronavirus infection (COVID-19)","volume":"9","author":"Anzai","year":"2020","journal-title":"J Clin Med."},{"key":"B10","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1186\/s12942-020-00202-8","article-title":"Geographical tracking and mapping of coronavirus disease COVID-19\/severe acute respiratory syndrome coronavirus 2 (SARS-CoV 2) epidemic and associated events around the world: how 21st century GIS technologies are supporting the global fight against outbreaks and epidemics","volume":"19","author":"Boulos","year":"2020","journal-title":"Int J Health Geogr."},{"key":"B11","doi-asserted-by":"publisher","first-page":"667","DOI":"10.1016\/j.jiph.2020.03.019","article-title":"Coronavirus disease 2019 (COVID-19): a literature review","volume":"13","author":"Harapan","year":"2020","journal-title":"J Infect Public Health."},{"key":"B12","doi-asserted-by":"publisher","first-page":"495","DOI":"10.1038\/s41586-021-03792-w","article-title":"After the pandemic: perspectives on the future trajectory of COVID-19","volume":"596","author":"Telenti","year":"2021","journal-title":"Nature."},{"key":"B13","doi-asserted-by":"publisher","first-page":"4725","DOI":"10.1038\/s41598-021-84055-6","article-title":"Inefficiency of SIR models in forecasting COVID-19 epidemic: a case study of Isfahan","volume":"11","author":"Moein","year":"2021","journal-title":"Sci Rep."},{"key":"B14","doi-asserted-by":"publisher","first-page":"1467","DOI":"10.1016\/j.dsx.2020.07.045","article-title":"Prediction of new active cases of coronavirus disease (COVID-19) pandemic using multiple linear regression model","volume":"14","author":"Rath","year":"2020","journal-title":"Diabetes Metab Syndr."},{"key":"B15","doi-asserted-by":"publisher","first-page":"105342","DOI":"10.1016\/j.compbiomed.2022.105342","article-title":"Forecasting COVID-19 new cases using deep learning methods","volume":"144","author":"Xu","year":"2022","journal-title":"Comput Biol Med."},{"key":"B16","doi-asserted-by":"publisher","first-page":"4720","DOI":"10.1038\/s41467-021-24732-2","article-title":"Deep learning of contagion dynamics on complex networks","volume":"12","author":"Murphy","year":"2021","journal-title":"Nat Commun."},{"key":"B17","unstructured":"Our World in Data"},{"key":"B18","unstructured":"OAG Flight Data"},{"key":"B19","unstructured":"The Natural Earth"},{"key":"B20","article-title":"Semi-supervised classification with graph convolutional networks","author":"Kipf","year":"2016","journal-title":"arXiv preprint"},{"key":"B21","doi-asserted-by":"publisher","first-page":"11941","DOI":"10.1038\/s41598-019-48391-y","article-title":"Toward perturbation prediction of biological networks using deep learning","volume":"9","author":"Li","year":"2019","journal-title":"Sci Rep."},{"key":"B22","doi-asserted-by":"publisher","first-page":"772","DOI":"10.1016\/j.pt.2018.07.004","article-title":"Human mobility and the global spread of infectious diseases: a focus on air travel","volume":"34","author":"Findlater","year":"2018","journal-title":"Trends Parasitol."},{"key":"B23","doi-asserted-by":"publisher","first-page":"1624","DOI":"10.1108\/JES-07-2020-0326","article-title":"A panel path analysis approach to the determinants of coronavirus disease 2019 transmission: does testing matter for confirmed cases?","volume":"48","author":"Goswami","year":"2020","journal-title":"J Econ Stud."}],"container-title":["Frontiers in Public Health"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fpubh.2022.911336\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,3]],"date-time":"2022-08-03T04:46:08Z","timestamp":1659501968000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fpubh.2022.911336\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,3]]},"references-count":23,"alternative-id":["10.3389\/fpubh.2022.911336"],"URL":"https:\/\/doi.org\/10.3389\/fpubh.2022.911336","relation":{},"ISSN":["2296-2565"],"issn-type":[{"value":"2296-2565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,8,3]]},"article-number":"911336"}}