<html><head><meta http-equiv="Content-Type" content="text/html; charset=utf-8"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class="">This sounds interesting, if any of you have lots of spare cycles. —Pete<br class=""><div><br class=""><blockquote type="cite" class=""><div class="">Begin forwarded message:</div><br class="Apple-interchange-newline"><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px;" class=""><span style="font-family: -webkit-system-font, Helvetica Neue, Helvetica, sans-serif; color:rgba(0, 0, 0, 1.0);" class=""><b class="">From: </b></span><span style="font-family: -webkit-system-font, Helvetica Neue, Helvetica, sans-serif;" class="">AAAI Community Announcement <<a href="mailto:aaai@memberclicks-mail.net" class="">aaai@memberclicks-mail.net</a>><br class=""></span></div><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px;" class=""><span style="font-family: -webkit-system-font, Helvetica Neue, Helvetica, sans-serif; color:rgba(0, 0, 0, 1.0);" class=""><b class="">Subject: </b></span><span style="font-family: -webkit-system-font, Helvetica Neue, Helvetica, sans-serif;" class=""><b class="">Invitation: XPRIZE on COVID-19 predictive and prescriptive modeling</b><br class=""></span></div><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px;" class=""><span style="font-family: -webkit-system-font, Helvetica Neue, Helvetica, sans-serif; color:rgba(0, 0, 0, 1.0);" class=""><b class="">Date: </b></span><span style="font-family: -webkit-system-font, Helvetica Neue, Helvetica, sans-serif;" class="">November 2, 2020 at 2:25:14 PM EST<br class=""></span></div><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px;" class=""><span style="font-family: -webkit-system-font, Helvetica Neue, Helvetica, sans-serif; color:rgba(0, 0, 0, 1.0);" class=""><b class="">To: </b></span><span style="font-family: -webkit-system-font, Helvetica Neue, Helvetica, sans-serif;" class=""><a href="mailto:PSZ@MIT.EDU" class="">PSZ@MIT.EDU</a><br class=""></span></div><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px;" class=""><span style="font-family: -webkit-system-font, Helvetica Neue, Helvetica, sans-serif; color:rgba(0, 0, 0, 1.0);" class=""><b class="">Reply-To: </b></span><span style="font-family: -webkit-system-font, Helvetica Neue, Helvetica, sans-serif;" class=""><a href="mailto:covidinterventions@xprize.org" class="">covidinterventions@xprize.org</a><br class=""></span></div><br class=""><div class="">
<div class=""><p class="">Dear AAAI Members and Affiliates,</p><p class="">We are thrilled to share that XPRIZE, in partnership with Cognizant, is launching the Pandemic Response Challenge on November 17. Because of the urgency of the topic, we are reaching out to potential participants now.</p><p class="">The Pandemic Response Challenge will focus on the development of data-driven models to predict COVID-19 infection rates and prescribe Intervention Plans that regional governments, communities, and organizations can implement to contain the pandemic and reopen safely. We encourage teams to get started on their prediction and prescription models as soon as possible. Please share this information with others who may be interested in competing, but kindly refrain from sharing publicly until the official launch on November 17, 2020. For more information (i.e. competition guidelines, access to the GitHub repository and slack channel), visit</p><p class=""><a href="https://xprize.org/pandemicresponse" class="">https://xprize.org/pandemicresponse</a></p><p class="">Additional Information:<br class="">- Goal: Over a four month period, teams will develop predictive models that deliver localized predictions of COVID-19 transmission, and will create prescriptor models that represent a tradeoff between minimizing the number of COVID-19 cases while lessening stringency (economic and social impact) of the intervention plans.<br class="">- Technical Skills Needed: This is a data-driven challenge. Teams need at least one member who is competent in Python, knows how to run a model, and can install a library in a Jupyter sandbox environment. Teams can use any methods, including machine learning, statistical, and epidemiological approaches.<br class="">- Prize and Registration Details: $500,000 total, distributed to two winning teams ($250K each). You need to sign up at Xprize pandemic response site to access competition information, and fully register your team before December 8, 2020; registration is limited to the first 200 teams.</p>
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