{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T15:39:13Z","timestamp":1761061153660,"version":"build-2065373602"},"reference-count":43,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2020,10,14]],"date-time":"2020-10-14T00:00:00Z","timestamp":1602633600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>We present a GIS-based crowdsourcing application that was launched soon after the first COVID-19 cases had been recorded in Greece, motivated by the need for fast, location-wise data acquisition regarding COVID-19 disease spread during spring 2020, due to limited testing. A single question was posted through a web App, to which the anonymous participants subjectively answered whether or not they had experienced any COVID-19 disease symptoms. Our main goal was to locate geographical areas with increased number of people feeling the symptoms and to determine any temporal changes in the statistics of the survey entries. It was found that the application was rapidly disseminated to the entire Greek territory via social media, having, thus, a great public reception. The higher percentages of participants experiencing symptoms coincided geographically with the highly populated urban areas, having also increased numbers of confirmed cases, while temporal variations were detected that accorded with the restrictions of activities. This application demonstrates that health systems can use crowdsourcing applications that assure anonymity, as an alternative to tracing apps, to identify possible hot spots and to reach and warn the public within a short time interval, increasing at the same time their situational awareness. However, a continuous reminder for participation should be scheduled.<\/jats:p>","DOI":"10.3390\/ijgi9100605","type":"journal-article","created":{"date-parts":[[2020,10,14]],"date-time":"2020-10-14T08:59:22Z","timestamp":1602665962000},"page":"605","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Is Crowdsourcing a Reliable Method for Mass Data Acquisition? The Case of COVID-19 Spread in Greece During Spring 2020"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5099-0351","authenticated-orcid":false,"given":"Varvara","family":"Antoniou","sequence":"first","affiliation":[{"name":"Laboratory of Natural Hazards\u2019 Management and Prevention, Department of Geology and Geoenvironment, National and Kapodistrian University of Athens, 15784 Athens, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1175-3628","authenticated-orcid":false,"given":"Emmanuel","family":"Vassilakis","sequence":"additional","affiliation":[{"name":"Laboratory of Remote Sensing, Department of Geology and Geoenvironment, National and Kapodistrian University of Athens, 15784 Athens, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5524-0576","authenticated-orcid":false,"given":"Maria","family":"Hatzaki","sequence":"additional","affiliation":[{"name":"Laboratory of Climatology and Atmospheric Environment, Department of Geology and Geoenvironment, National and Kapodistrian University of Athens, 15784 Athens, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,10,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"30026","DOI":"10.2807\/1560-7917.ES.2015.20.39.30026","article-title":"Spatial methods for infectious disease outbreak investigations: Systematic literature review","volume":"20","author":"Smith","year":"2015","journal-title":"Eurosurveillance"},{"doi-asserted-by":"crossref","unstructured":"Thakar, V. (2020). Unfolding events in space and time: Geospatial insights into COVID-19 diffusion in Washington State during the initial stage of the outbreak. ISPRS Int. J. Geo-Inf., 9.","key":"ref_2","DOI":"10.3390\/ijgi9060382"},{"doi-asserted-by":"crossref","unstructured":"Song, Z., Zhang, H., and Dolan, C. (2020). Promoting disaster resilience: Operation mechanisms and self-organizing processes of crowdsourcing. Sustainability, 12.","key":"ref_3","DOI":"10.3390\/su12051862"},{"doi-asserted-by":"crossref","unstructured":"Eide, A.H., Dyrstad, K., Munthali, A., Van Rooy, G., Braathen, S.H., Halvorsen, T., Persendt, F., Mvula, P., and R\u00f8d, J.K. (2018). Combining survey data, GIS and qualitative interviews in the analysis of health service access for persons with disabilities. BMC Int. Health and Hum. Rights, 18.","key":"ref_4","DOI":"10.1186\/s12914-018-0166-2"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1177\/1524839909334624","article-title":"Geographic Information Systems (GIS) for health promotion and public health: A review","volume":"12","author":"Nykiforuk","year":"2009","journal-title":"Health Promot. Pract."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/S0065-308X(00)47007-7","article-title":"Spatial statistics and geographical information systems in epidemiology and public health","volume":"Volume 47","author":"Robinson","year":"2000","journal-title":"Advances in Parasitology"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1016\/S0065-308X(00)47013-2","article-title":"Forecasting disease risk for increased epidemic preparedness in public health","volume":"Volume 47","author":"Myers","year":"2000","journal-title":"Advances in Parasitology"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"478","DOI":"10.1186\/s13071-019-3744-9","article-title":"Potential impact of climate change on the geographical distribution of two wild vectors of Chagas disease in Chile: Mepraia spinolai and Mepraia gajardoi","volume":"12","author":"Garrido","year":"2019","journal-title":"Parasites Vectors"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1078\/1438-4639-00145","article-title":"New perspectives on the use of Geographical Information Systems (GIS) in environmental health sciences","volume":"205","author":"Kistemann","year":"2002","journal-title":"Int. J. Hyg. Environ. Health"},{"unstructured":"WHO (2020, October 02). Coronavirus Disease (COVID-19) Dashboard. Available online: https:\/\/covid19.who.int\/.","key":"ref_10"},{"unstructured":"(2020, October 02). COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). Available online: https:\/\/coronavirus.jhu.edu\/map.html.","key":"ref_11"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"546","DOI":"10.1177\/0309132515581094","article-title":"Health geography II: \u2018Dividing\u2019 health geography","volume":"40","author":"Rosenberg","year":"2015","journal-title":"Prog. Hum. Geogr."},{"doi-asserted-by":"crossref","unstructured":"Sifaki-Pistolla, D., Pistolla, G., Chatzea, V.-E., and Tzanakis, N. (2017). Geospatial and spatio-temporal analysis in health research: GIS in health. Handbook of Research on Geographic Information Systems Applications and Advancements, IGI Global.","key":"ref_13","DOI":"10.4018\/978-1-5225-0937-0.ch019"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"102202","DOI":"10.1016\/j.apgeog.2020.102202","article-title":"Rapid surveillance of COVID-19 in the United States using a prospective space-time scan statistic: Detecting and evaluating emerging clusters","volume":"118","author":"Desjardins","year":"2020","journal-title":"Appl. Geogr."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"140033","DOI":"10.1016\/j.scitotenv.2020.140033","article-title":"Spatial analysis and GIS in the study of COVID-19. A review","volume":"739","author":"Napoletano","year":"2020","journal-title":"Sci. Total Environ."},{"unstructured":"Campagna, M. (2020). Geographic information and Covid-19 outbreak does the spatial dimension matter?. TeMA J. Land Use Mobil. Environ., 31\u201344.","key":"ref_16"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1007\/s10900-016-0298-z","article-title":"Using GIS mapping to target public health interventions: Examining birth outcomes across GIS techniques","volume":"42","author":"MacQuillan","year":"2017","journal-title":"J. Community Health"},{"unstructured":"(2020, June 28). iMEdD\u2014COVID-19. Available online: https:\/\/lab.imedd.org\/covid19\/.","key":"ref_18"},{"unstructured":"(2020, June 28). Information for COVID-19. Available online: https:\/\/arcg.is\/1G5Si9.","key":"ref_19"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/19475683.2019.1702099","article-title":"Why public health needs GIS: A methodological overview","volume":"26","author":"Wang","year":"2020","journal-title":"Ann. GIS"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"7987","DOI":"10.1016\/j.eswa.2014.06.044","article-title":"Brief survey of crowdsourcing for data mining","volume":"41","author":"Guo","year":"2014","journal-title":"Expert Syst. Appl."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1007\/s10708-008-9188-y","article-title":"The credibility of volunteered geographic information","volume":"72","author":"Flanagin","year":"2008","journal-title":"GeoJournal"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1016\/j.spasta.2012.03.002","article-title":"Assuring the quality of volunteered geographic information","volume":"1","author":"Goodchild","year":"2012","journal-title":"Spat. Stat."},{"doi-asserted-by":"crossref","unstructured":"Sui, D., Elwood, S., and Goodchild, M. (2012). Crowdsourcing Geographic Knowledge: Volunteered Geographic Information (VGI) in Theory and Practice, Springer.","key":"ref_24","DOI":"10.1007\/978-94-007-4587-2"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1080\/00045608.2011.595657","article-title":"Researching volunteered geographic information: Spatial data, geographic research, and new social practice","volume":"102","author":"Elwood","year":"2012","journal-title":"Ann. Assoc. Am. Geogr."},{"doi-asserted-by":"crossref","unstructured":"Quinn, A., and Bederson, B. (2011, January 7\u201312). Human computation: A survey and taxonomy of a growing field. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Vancouver, BC, Canada.","key":"ref_26","DOI":"10.1145\/1978942.1979148"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1007\/s10462-014-9423-5","article-title":"A survey of task-oriented crowdsourcing","volume":"44","author":"Luz","year":"2015","journal-title":"Artif. Intell. Rev."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.cageo.2015.04.001","article-title":"Development of a spatial decision support system for flood risk management in Brazil that combines volunteered geographic information with wireless sensor networks","volume":"80","author":"Horita","year":"2015","journal-title":"Comput. Geosci."},{"doi-asserted-by":"crossref","unstructured":"Lai, T.-P., Yao, S., Siu, W.-L., Cheng, Y.-C., Su, H.-Y., and Chen, Y.-C. (2019). An Interactive, Location-Aware Taiwanese Social Network for Both Everyday Use and Disaster Management. MISNC 2019: Multidisciplinary Social Networks Research, Springer.","key":"ref_29","DOI":"10.1007\/978-981-15-1758-7_13"},{"unstructured":"Schulz, A., Paulheim, H., and Probst, F. (2012, January 22\u201325). Crisis information management in the Web 3.0 age. Proceedings of the 9th International ISCRAM Conference, Vancouver, BC, Canada.","key":"ref_30"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"473","DOI":"10.1038\/s43018-020-0065-z","article-title":"Crowdsourcing a crisis response for COVID-19 in oncology","volume":"1","author":"Desai","year":"2020","journal-title":"Nat. Cancer"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1111\/jrh.12486","article-title":"Progression of COVID-19 from urban to rural areas in the United States: A spatiotemporal analysis of prevalence rates","volume":"36","author":"Rajib","year":"2020","journal-title":"J. Rural Health"},{"doi-asserted-by":"crossref","unstructured":"Rashid, M.T., and Wang, D. (2020). CovidSens: A vision on reliable social sensing for COVID-19. Artif. Intell. Rev.","key":"ref_33","DOI":"10.1007\/s10462-020-09852-3"},{"unstructured":"(2020, October 02). Opendemic\u2014Anonymous COVID19 Proximity Alerts. Available online: https:\/\/www.opendemic.org\/.","key":"ref_34"},{"unstructured":"(2020, October 02). Flusurvey. Available online: https:\/\/flusurvey.net\/.","key":"ref_35"},{"unstructured":"(2020, October 02). COVID Symptom Tracker. Available online: https:\/\/covid.joinzoe.com\/.","key":"ref_36"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1038\/d41586-020-01578-0","article-title":"Ethical guidelines for COVID-19 tracing apps","volume":"582","author":"Morley","year":"2020","journal-title":"Nature"},{"unstructured":"(2020, October 02). COVID-19 Symptom Survey of the University of Maryland. Available online: https:\/\/umdsurvey.umd.edu\/jfe\/form\/SV_7ZN4Qe5wYnfxXVz?token=kF8qRLfPy8Y24cnZRb&Q_CreateFormSession=1&Q_Language=EN=GB.","key":"ref_38"},{"unstructured":"(2020, October 02). COVID-19 Tracker Switzerland. Available online: https:\/\/www.covidtracker.ch\/en\/.","key":"ref_39"},{"unstructured":"(2020, October 02). Folding@home. Available online: https:\/\/foldingathome.org\/.","key":"ref_40"},{"unstructured":"Spiegel, M.R.S., and Larry, J. (2017). Schaum\u2019s Outline of Statistics, McGraw Hill. [6th ed.].","key":"ref_41"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1111\/j.1538-4632.1992.tb00261.x","article-title":"The analysis of spatial association by use of distance statistics","volume":"24","author":"Getis","year":"1992","journal-title":"Geogr. Anal."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1111\/j.1538-4632.1995.tb00912.x","article-title":"Local spatial autocorrelation statistics: Distributional issues and an application","volume":"27","author":"Ord","year":"1995","journal-title":"Geogr. Anal."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/9\/10\/605\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:21:00Z","timestamp":1760178060000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/9\/10\/605"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,14]]},"references-count":43,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2020,10]]}},"alternative-id":["ijgi9100605"],"URL":"https:\/\/doi.org\/10.3390\/ijgi9100605","relation":{},"ISSN":["2220-9964"],"issn-type":[{"type":"electronic","value":"2220-9964"}],"subject":[],"published":{"date-parts":[[2020,10,14]]}}}