The project used data available at the World Health Organization and NASA / JAXA / ESA sites, which are freely accessible and some are updated periodically, ensuring real-time information, which are guiding for the timely decision-making of policy makers. The data shown on our platform would be made available in a language that is widely understood (maps, tables and graphs) both by the scientific community and by managers and the population with average education. Scientifically, the platform proposed by us is based on Covid's Natural History and the Social Determination of the disease (model scientifically validated by Solar and Irwin, 2010 - WHO), so that the general map visualized will contain the statistical correlation between those variables recognized associated with illness and death by Covid-19. We create, tables, graphs and maps; we carry out geostatistical analyzes that show the spatial dynamics of the covid19 morbidity and mortality process in the chosen countries. With accessible data, health managers were able to make decisions and measures to control the disease.
We believe that integrated datas are the future! Database is working by itself with daily statistical analysis. We look for socio economics datas in websites available like “WHO”. These datas was used to build geodatabase with the variable case fatality rate. This analyze is shown on thematic maps and graphs.
Our project used R, Python and JavaScript programming languages and the softwares were QGIS, RSTUDIO, Excel.
One of the main problem was in the database collection. The WHO website, for example, isn’t very straightforward in terms of database availability, and it could be simpler, and the database is out of data.
LINK TO VIDEO: https://drive.google.com/file/d/1UCAXOqo_aqew56nZFI4-osTrktqXEPwI/view?usp=sharing
LINK TO REPOSITORY: https://covid-hackaton.herokuapp.com/analitc/dashboard/
DATABASES:
NASA COVID-19 data pathfinders
PUBMED CENTRAL
SCIENTIFIC ARTICLES:
Smith JA, Judd J. COVID-19: Vulnerability and the power of privilege in a pandemic. Health Promot J Austr. 2020;31(2):158‐160. doi:10.1002/hpja.333
Zhou, F. et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet395, 1054–1062 (2020).
WHO . Q & A on Coronaviruses (COVID‐19). Available from:https://www.who.int/news-room/q-a-detail/q-a-coronaviruses [cited 2020 May 12].
Wise, T., Zbozinek, T. D., Michelini, G., Hagan, C. C. & Mobbs, D. Changes in risk perception and protective behavior during the first week of the COVID-19 pandemic in the United States. Preprint at PsyArXivhttps://osf.io/dz428 (2020).
Luzi L, Radaelli MG. Influenza and obesity: its odd relationship and the lessons for COVID-19 pandemic. Acta Diabetol. 2020;57(6):759‐764. doi:10.1007/s00592-020-01522-8
Hamid S, Mir MY, Rohela GK. Novel coronavirus disease (COVID-19): a pandemic (epidemiology, pathogenesis and potential therapeutics). New Microbes New Infect. 2020;35:100679. Published 2020 Apr 14. doi:10.1016/j.nmni.2020.100679
Xiao H, Zhang Y, Kong D, Li S, Yang N. Social Capital and Sleep Quality in Individuals Who Self-Isolated for 14 Days During the Coronavirus Disease 2019 (COVID-19) Outbreak in January 2020 in China. Med Sci Monit. 2020;26:e923921. Published 2020 Mar 20. doi:10.12659/MSM.923921
Ryan BJ, Coppola D, Canyon DV, Brickhouse M, Swienton R. COVID-19 Community Stabilization and Sustainability Framework: An Integration of the Maslow Hierarchy of Needs and Social Determinants of Health [published online ahead of print, 2020 Apr 21]. Disaster Med Public Health Prep. 2020;1‐7. doi:10.1017/dmp.2020.109