The EU Commission has asked the H2020 MOOD Project coordination to provide all possible assistance to surveillance efforts of the ongoing Coronavirus outbreaks its potential risk to Europe. Project partners have made the following datasets, documents and links to further information available to all.
Documents and publications
| Maps of human mobility change during the COVID-19 outbreak derived from Google reports processed by ERGO |
| Visualizing COVID-19 mortality in Europe and its neighborhood – Renaud Lancelot, CIRAD, France |
| MOOD Spatial Data COVID-19 Covariate Archive – Covariate data collated by ERGO at request of the MOOD partners |
| Kraemer M.U.G, Sadilek A., Zhang Q., Marchal N.A., Tuli G., Cohn E.L., Hswen Y, Perkins T.A., Smith D.L., Reiner Jr R.C., Brownstein J.S. Mapping global variation in human mobility. Nat Hum Behav (2020). DOI: https://doi.org/10.1038/s41562-020-0875-0 |
| Rader B., Astley c.M., Sy K.T.L., Sewalk K., Hswen Y., Brownstein J.S., Kraemer M.U.G. Geographic access to United States SARS-CoV-2 testing sites highlights healthcare disparities and may bias transmission estimates. Journal of Travel Medicine, Published: 15 May 2020 DOI: https://doi.org/10.1093/jtm/taaa076 |
| Pullano G., Valdano E., Scarpa N., Rubrichi S., Colizza V. Population mobility reductions during COVID-19 epidemic in France under lockdown |
| Kraemer M.U.G, Yang C.H., Gutierrez B., Wu C-H., Klein, Pigott D.M., Open COVID-19 Data Working Group, du Plessis L., Faria1 N.R., Li R., Hanage W.P., Brownstein J.S., Layan M., Vespignani A., Tian H., Dye1 C., Pybus O.G., Scarpino S.V. The effect of human mobility and control measures on the COVID-19 epidemic in China. Science 01 May 2020:Vol. 368, Issue 6490, pp. 493-497 DOI: https://doi.org/10.1126/science.abb4218 |
| Oliver N., Lepri b,. Sterly H., Lambiotte R., Delataille S., De Nadai D., Letouzé E., Salah A.A., Benjamins R., Cattuto C., Colizza V., de Cordes N., Fraiberger S.P., Koebe T., Lehmann S., Murillo J., Pentland A., Pham P.N., Pivetta F., Saramäki J., Scarpino S.V., Tizzoni M., Verhulst S. and Vinck P. Mobile phone data for informing public health actions across the COVID-19 pandemic life cycle. Science Advances 27 Apr 2020:eabc0764 DOI: https://doi.org/10.1126/sciadv.abc0764 |
| Guzzetta G., Riccardo F., Marziano V., Poletti P., Trentini F., Bella A., Andrianou X., Del Manso M., Fabiani M., Bellino S., Boros S., Urdiales A.M., Vescio M.F., Piccioli A., COVID-19 working group, Brusaferro S., Rezza G., Pezzotti P., Ajelli M., Merler S. The impact of a nation-wide lockdown on COVID-19 transmissibility in Italy. Pre-print: arXiv:2004.12338 [q-bio.PE] |
| Zhang J., Litvinova M., Liang Y., Wang Y., Wang W., Zhao S., Wu Q., Merler S., Viboud C., Vespignani A., Ajelli M.,, Yu H. Changes in contact patterns shape the dynamics of the COVID-19 outbreak in China. Science 29 Apr 2020:eabb8001 DOI: https://doi.org/10.1126/science.abb8001 |
| Zhang J., Litvinova M., Wang W., Wang Y., Deng X., Chen X., Li M., Zheng W., Yi L., Chen X, Wu Q., Liang Y., Wang X., Yang J., Sun K., Longini Jr I.M., Halloran ME., Wu P., Cowling B.J., Merler S., Viboud C., Vespignani A., Ajelli M., Yu H. Evolving epidemiology and transmission dynamics of coronavirus disease 2019 outside Hubei province, China: a descriptive and modelling study. Lancet Infect Dis 2020 Published Online April 2, 2020 DOI: https://doi.org/10.1016/S1473-3099(20)30264-4 |
| Guzzetta G., Poletti P., Ajelli A., Trentini F., Marziano V., Cereda D., Tirani M., Diurno G, Bodina A., Barone A., Crottogini L, Gramegna M, Melegaro A., Merler1 S., Potential short-term outcome of an uncontrolled COVID-19 epidemic in Lombardy, Italy, February to March 2020. Euro Surveill. 2020;25(12):pii=2000293. https://doi.org/10.2807/1560-7917.ES.2020.25.12.2000293 |
| Kraemer M.U.G., Yang C-H., Gutierrez B., Wu C-H., Klein B., Pigott D.M., Open COVID-19 Data Working Group, du Plessis L., Faria1 N.R., Li R., Hanage W.P., Brownstein J.S., Layan M., Vespignani A., Tian H., Dye C., Pybus O.G., S.V. The effect of human mobility and control measures on the COVID-19 epidemic in China. DOI: https://dx.doi.org/10.1126/science.abb4218 |
| Tian H., Liu Y., Li Y., Wu C-H., Chen B., Kraemer M.U.G., Li B.,Cai J., Xu B., Yang Q., Wang B., Yang P., Cui Y., Song Y., Zheng1 P., Wang Q, V Bjornstad O.N., Yang R., GrenfellB.T., Pybus O.G., Dye C. An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China. Science 08 May 2020: Vol. 368, Issue 6491, pp. 638-642 DOI: 10.1126/science.abb6105 |
| Chinazzi M., Davis J.T, Ajelli M., Gioannini C., Litvinova M., Merler S., Pastore y Piontti A., Mu K, Rossi L., Sun K, Viboud C., Xiong X, Yu H., Halloran M.E., Longini Jr I.M., Vespignani A. (2020). The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak. Science. https://dx.doi.org/10.1126/science.aba9757 |
| Gilbert M., Pullano G., Pinotti F., Valdano E, Poletto C, Boelle P-Y., D’Ortenzio E., Yazdanpanah Y., Eholie S.P., Altmann M., Gutierrez B., Kraemer M.U.G., Colizza V. Preparedness and vulnerability of African countries against introductions of 2019-nCoV; doi: https://doi.org/10.1101/2020.02.05.20020792 |
| Xu B., Gutierrez B., Mekaru S., Sewalk K., Goodwin L., Loskill A., Cohn E.L., Hswen T., Hill S.C., Cobo M.M., Zarebski A.E., Li S., Wu C-H., Hulland E., Morgan J.D., Wang L., O’BrienK., Scarpino S.V., Brownstein J.S., Pybus O.G., Pigott D.M., Kraemer M.U.G. Epidemiological data from the COVID-19 outbreak, real-time case information. Sci Data 7, 106 (2020). DOI: https://doi.org/10.1038/s41597-020-0448-0 |
| Di Domenico L., Pullano G., Sabbatini C.E., Boëlle P-Y., Colizza V. Expected impact of school closure and telework to mitigate COVID-19 epidemic in France |
| Pullano G., Pinotti F., Valdano E., Boëlle P-Y., Poletto C., Colizza V.. Novel coronavirus (2019-nCoV) early-stage importation risk to Europe, January 2020. Euro Surveill. 2020;25(4):pii=2000057. https://doi.org/10.2807/1560-7917.ES.2020.25.4.2000057 |
| Di Domenico L., Pullano G., Sabbatini C.E., Boëlle P-Y., Colizza V. Expected impact of lockdown in Île-de-France and possible exit strategies doi: https://doi.org/10.1101/2020.04.13.20063933 |
| Boëlle P-Y., Souty C., Launay T, Guerrisi C, Turbelin C., Behillil S., Enouf V., Poletto C., Lina B., van der Werf S., Lévy-Bruhl D., Colizza V., Hanslik T., Blanchon T. Excess cases of influenza-like illnesses synchronous with coronavirus disease (COVID-19) epidemic, France, March 2020. Euro Surveill. 2020;25(14):pii=2000326. https://doi.org/10.2807/1560-7917.ES.2020.25.14.2000326 |
| Xu B., Kraemer M.U.G. on behalf of theOpen COVID-19 Data Curation Group. Open access epidemiological data from the COVID-19 outbreak. Published:February 19, 2020. DOI:https://doi.org/10.1016/S1473-3099(20)30119-5 |
| Report 8: Expected impact of school closure and telework to mitigate COVID-19 epidemic in France |
| Report 6: Are people excessively pessimistic about the risk of coronavirus infection? |
| Report 5: Lessons learnt from 288 COVID-19 international cases: importations over time, effect of interventions, underdetection of imported cases |
| Report 4: Preparedness and vulnerability of African countries against introductions of 2019-nCoV |
| Report 3: 2019-nCoV importation risk to Europe — 28/01/2020 (Data up to 27/01/2020), after the updates on the German case |
| Report 2: 2019-nCoV importation risk to Europe — 26/01/2020 (Data up to 25/01/2020) |
| Report 1: 2019-nCoV importation risk to Europe — based on data up to 23/01/2020 at 11am |
| Epidemiological Data from the nCoV-2019 Outbreak: Early Descriptions from Publicly Available Data – Moritz Kramer |
| Preliminary risk analysis of 2019 novel Coronavirus spread within and beyond China — Lai, Bogoch, Watts, Kahn, Li & Tatem. (WorldPop) |
| Assessing spread risk of Wuhan novel coronavirus within and beyond China, January-April 2020: a travel network-based modelling study – WorldPop |
| Effect of non-pharmaceutical interventions for containing the COVID-19 outbreak – WorldPop |
| Effect of non-pharmaceutical interventions for containing the COVID-19 outbreak: an observational and modelling study – WorldPop |
Data & Analysis
Brief description: We have collected publicly available information on cases confirmed during the ongoing COVID-19 outbreak. Data were entered in a spreadsheet with each line representing a unique case, including age, sex, geographic information, history and time of travel where available. Sources were included as a reference for each entry. Data is openly available here: https://tinyurl.com/s6gsq5y and was last updated, January 31, 2020.
This database is being updated regularly and epidemiological information about Wuhan will be included over the coming days. Data are compiled from openly available sources only. We have tried to ensure accuracy of data compilation, but cannot take responsibility for any unintentional errors that may have occurred. Please email us if you have any additional information that would be useful to be include, or any suggested edits. Those information may include updates on recorded cases, especially demographics, clinical outcome, and details on the clusters in Wuhan and Guangdong.
Description of the data and some initial results are posted through Virological.org: http://virological.org/t/epidemiological-data-from-the-ncov-2019-outbreak-early-descriptions-from-publicly-available-data/337.
MOOD Emergency Response Activities
In advance of the project Kick-0ff meeting here is a brief summary of what the MOOD partners are currently doing or propose to implement in collaboration with the Eurpoean Centre for Disease Control (ECDC) in emergency response to the current novel Coronavirus outbreak that originated in Wuhan province in China.
- Chinazzi et al. have published a paper showing how travel restrictions influences the spread of the 2019 novel coronavirus.
- A summary of the current and the planned activities by MOOD partners TETIS on text-mining and EnCov19.
- Inserm has released a report (which is already cited in the medias).
- Moritz Kramer (Oxford University) has released a report on available epi data: Epidemiological Data from the nCoV-2019 Outbreak: Early Descriptions from Publicly Available Data.
- Andrew Tatem (Southampton University) may provide data and models for inner mouvements of Chinese population.
- Luca Busani (ISS Roma) and Annapaola Rizzoli would propose to strengthen / compliment the ECDC rapid risk assessment with a more comprehensive risk analysis, including mobilizing an expert network to define the data needed for this RA, and also contribute.
- Cirad / Inrae (and other WP3 partners) have started adapting the web monitoring platform “Padi-web” to improve event-based surveillance, specifically targeting China. Some adaptations are needed, like changing Google queries to Baidu queries, and defining expressions (group of words) to define relevant information.