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Simulating nationwide realistic individual movements with a detailed geographical structure is urgently needed to optimize public health policies. However, existing tools have limited resolution or can only account for a limited number of agents. We introduce Epidemap, a new framework that can capture the daily movement of more than 60 million people in a country at a building-level resolution in a realistic and computational-efficient way. By applying it to the case of an infectious disease spreading in France, we uncover hitherto neglected effects, such as the emergence of two distinct peaks in the daily number of cases or the importance of local density in the timing of arrival of the epidemic. Finally, we show that the importance of super-spreading events strongly varies over time.
", "languages": [ { "id": "eng", "title": { "en": "English" } } ], "publication_date": "2021-04-09", "publisher": "Zenodo", "resource_type": { "id": "publication-article", "title": { "de": "Zeitschriftenartikel", "en": "Journal article" } }, "rights": [ { "description": { "en": "The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited." }, "icon": "cc-by-icon", "id": "cc-by-4.0", "props": { "scheme": "spdx", "url": "https://creativecommons.org/licenses/by/4.0/legalcode" }, "title": { "en": "Creative Commons Attribution 4.0 International" } } ], "subjects": [ { "subject": "multiagent covid-19 epidemics simulation geographic" } ], "title": "Emerging dynamics from high-resolution spatial numerical epidemics" }, "parent": { "access": { "owned_by": { "user": 211533 } }, "communities": { "default": "10f33f78-3f29-41b6-bb10-f757a8f03cb8", "entries": [ { "access": { "member_policy": "open", "members_visibility": "public", "record_policy": "open", "review_policy": "open", "visibility": "public" }, "children": { "allow": false }, "created": "2020-03-16T11:40:44.487619+00:00", "custom_fields": {}, "deletion_status": { "is_deleted": false, "status": "P" }, "id": "10f33f78-3f29-41b6-bb10-f757a8f03cb8", "links": {}, "metadata": { "curation_policy": "The Coronavirus Disease Research Community - COVID-19 is curated by a selected team of experts nominated by OpenAIRE* (see list below). Each time a Zenodo user wants to add a record into the community, an email is sent to the curators that will decide whether to include the record or not.
\r\n\r\nOnly records that may be relevant to the Corona Virus Disease (COVID-19) or the SARS-CoV-2 should be included in this community. The Community curators are not able to edit records, therefore they may ask the corresponding authors to modify the record metadata when necessary, to provide the readers/users with more detailed information according to the FAIR principle of Open Science.
\r\n\r\nIf after its acceptance, a record is subsequently found not to be compliant, we reserve the right to remove it from the community.
\r\n\r\nThe curation team is reachable through the following email address for further clarification or information: covid19@openaire.eu.
\r\n\r\nCurator List:
\r\n\r\n* OpenAIRE: open access and open science training and support since 2009. OpenAIRE is the largest aggregator of European Commission funded research outputs and beyond, also delivering on-demand services for research communities.
\r\n", "page": "This community collects research outputs that may be relevant to the Coronavirus Disease (COVID-19) or the SARS-CoV-2. Scientists are encouraged to upload their outcome in this collection to facilitate sharing and discovery of information. Although Open Access articles and datasets are recommended, also closed and restricted access material are accepted. All types of research outputs can be included in this Community (Publication, Poster, Presentation, Dataset, Image, Video/Audio, Software, Lesson, Other).
\r\n\r\nThe recent Corona Virus Disease (COVID-19) outbreak is requiring unseen efforts of collaboration of the scientific community that need to act fast and to share results in an unpredictable manner. In order to facilitate the Scientist efforts, this community was created to collect all research results that could be relevant for the scientific community working on the Corona Virus Disease (COVID-19) and SARS-CoV-2.
\r\n\r\nAlthough Open Access articles and datasets are recommended, also closed and restricted access material are accepted. All types of research outputs can be included in this Community (Publication, Poster, Presentation, Dataset, Image, Video/Audio, Software, Lesson, Other).
\r\n\r\nWhen depositing a resource that is linked to other resources (not limited to the records deposited in Zenodo but also in other repositories), please make sure that your record is linked to all the other related elements already available, in order to adhere to the FAIR principles of Open Science to maximise the reusability of research results.
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