key: cord-1028374-pam3etq4 authors: Tobias, A.; satorra, p.; Valls, J.; Tebe, C. title: COVID19-Global: A shiny application to perform a global comparative data visualization for the SARS-CoV-2 epidemic date: 2020-05-22 journal: nan DOI: 10.1101/2020.05.18.20105684 sha: 0dd2cec3a8f953d62bd2b36d9f3b22c29dc757a3 doc_id: 1028374 cord_uid: pam3etq4 Data visualization is an essential tool for exploring and communicating findings in medical research, especially in epidemiological surveillance. The COVID19-Global online web application systematically produces daily updated data visualization and analysis of the SARS-CoV-2 epidemic on a global scale. It collects automatically daily data on COVID-19 diagnosed cases and mortality worldwide from January 1st, 2020 onwards. We have implemented comparative data visualization between countries for the most common indicators in epidemiological surveillance to follow an epidemic: attack rate, population fatality rate, case fatality rate, and basic reproduction number. The application may help for a better understanding of the SARS-CoV-2 epidemic worldwide. The first confirmed case of SARS-CoV-2 in China was reported to the WHO country office in China on December 31 st , 2019 (1) . The outbreak was declared a public health emergency of international concern on January 30 th , 2020 (1) . Since then, 215 countries have been affected worldwide, 4,722,233 people have been diagnosed cases, and 313,266 have died due to the SARS-CoV-2 pandemic (2) . Data visualization and analysis is an essential tool for exploring and communicating findings in medical research, and especially in epidemiological surveillance (3) . It can help researchers and policymakers identify trends that could be overlooked if the data were reviewed in tabular form. We have developed a Shiny application to compare epidemiological indicators on the SARS-CoV-2 epidemic. The COVID19-Tracker app has been developed in RStudio (4), version 1.2.5033, using the Shiny package, version 1.4.0. Shiny offers the ability to develop a graphical user interface (GUI) that can be run locally or deployed online. Last is particularly beneficial to show and communicate updated findings to a broad audience. All the analyses have been carried out using R (5), version 3.6.3. The application has a friendly structure based on menus to shown data visualization for the most common indicators in epidemiological surveillance to follow an epidemic: attack rate, population fatality rate, case fatality rate, and basic reproduction number ( Figure 1 ). All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. We collected daily data on COVID-19 diagnosed cases and mortality, from January 1 s , 2020, onwards. Data is collected automatically from the ECDC's (European Centre for Disease Prevention and Control) the geographical distribution of COVID-19 cases worldwide (6) . The downloadable dataset is updated daily and contains the latest available public data on COVID-19 worldwide. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The attack rate is the ratio between the positively diagnosed cases (T+) and the total population (P) in a given country (AR = C+/P). The population fatality rate is the ratio between the positively diagnosed deaths (D+) and the population (P) in a given country (PFR = D+/P). The case fatality rate is the ratio between the positively diagnosed deaths (D+) and the positively tested cases (C+) in a given country (CFR = D+/C+). The basic reproduction number (R0) is the average number of secondary cases of disease caused by a single infected individual over his or her infectious period (7). Here, we used the R package EpiEstim to estimate the R0 (7). (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (8) . However, we should acknowledge that it is not possible to make an accurate estimate of the rates due to the underreporting of diagnosed cases and mortality in official statistics (9) . Moreover, the application does not take into account the changes in the definition of diagnosed cases, nor the lockdown measures are undertaken in each country, aiming to flatten the curve. Moreover, the selection of the number of people who have been tested is critical for an accurate estimation (8) . Accurate estimation of the rates depends on the testing strategy, the prevalence of infection, and the test accuracy. Differences between countries or overtime may merely reflect differences in selection for testing and test performance (8) . In any case, a routine health system data of basic epidemiological indicators for the SARS-CoV-2 pandemic allowing for the comparison between countries, is essential for surveillance epidemiology and health policy. We continue to plan improvements to the application to include specific data visualizations by country and aggregated by geographical regions. In summary, this application, easy to use, comes to fill a gap in this particular scenario for the visualization of epidemiological data for the COVID-19 at a global scale. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 22, 2020. . https://doi.org/10.1101/2020.05.18.20105684 doi: medRxiv preprint None. World Health Oorganization Ourworld in Data. Coronavirus Disease (COVID-19) Statistics and Research Global Change Data Lab Visualization and analytics tools for infectious disease epidemiology: a systematic review Integrated Development for R. RStudio, Inc R: A language and environment for statistical computing. R Foundation for Statistical Computing European Centre for Disease Prevention and Control. Download today's data on the geographic distribution of COVID-19 cases worldwide Stockholm A new framework and software to estimate time-varying reproduction numbers during epidemics Accurate Statistics on COVID-19 Are Essential for Policy Guidance and Decisions 2019-novel Coronavirus (2019-nCoV): estimating the case fatality rate -a word of caution None. None.All rights reserved. No reuse allowed without permission.(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint this version posted May 22, 2020. . https://doi.org/10.1101/2020.05.18.20105684 doi: medRxiv preprint All rights reserved. No reuse allowed without permission.(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint this version posted May 22, 2020. . https://doi.org/10.1101/2020.05.18.20105684 doi: medRxiv preprint