RAPID: Variant Emergence and Scenario Design for the COVID-19 Scenario Modeling Hub

COVID-19情景建模中心收集和汇总了多个建模团队在州和国家层面上对6个月内美国公共卫生结果（病例、住院和死亡）的预测。长期预测的目标是比较不同情景、干预措施或假设下的疫情轨迹，而不是对将要发生的事情提供具体预测。这个项目将通过增加包括潜在的未来病毒变种在内的信息，以及通过建立一个网络来收集、组织和综合有关任何实际的新变种的新特征的信息，来改进这些预测。COVID-19情景建模中心向白宫COVID-19数据团队、疾病控制和预防中心的预测和爆发分析中心、世界卫生组织报告。州和地区流行病学家委员会，以及其他组织。公共网页使公共卫生专家、国家一级的利益攸关方、媒体和公众可以访问这项工作。我们的工作将为未来几个月国家和全球未来变体激增的规划和应对措施提供信息，并可能适用于其他疾病的暴发。它还将培养一名博士后研究员和一名研究生的科学专业知识和沟通技巧。COVID-19情景中心已经完成了对美国的12轮情景预测。影响情景设计和预测的不确定性的一个主要来源是新的遗传变异。首先，该项目将通过与免疫学、流行病学和病毒进化领域的科学家合作，通过专家启发方法，获得有关可能出现时间和潜在新变异可能特征范围的信息，从而提高信息获取和减少不确定性。第二，为了作出反应，该项目将开始建立一个网络，收集、组织和综合有关任何实际的新关切变种的新特征的信息，以改进中心用于Omicron变种的应急程序，简化和加强信息获取。这两种信息流都将用于改进场景开发，并为参与建模的团队提供最好的数据。该项目是与美国疾病控制与预防中心合作资助的，旨在支持快速反应研究项目，进一步提高联邦传染病建模能力。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The COVID-19 Scenario Modeling Hub collects and aggregates projections from multiple modeling teams of US public health outcomes (cases, hospitalizations, and deaths) over 6 months at the state and national level. The goal of long-term projections is to compare outbreak trajectories under different scenarios, interventions, or assumptions, as opposed to offering a specific prediction of what will happen. This project will improve those projections by adding information that includes potential future viral variants and by building a network to gather, organize and synthesize information on the emerging characteristics of any actual new variant of concern. The COVID-19 Scenario Modeling Hub reports to the White House COVID-19 data team, the Center for Forecasting and Outbreak Analytics at the Centers for Disease Control and Prevention, the World Health Organization. the Council of State and Territorial Epidemiologists, and other organizations. A public webpage makes the work accessible to public health experts, state-level stakeholders, the media, and the general public. Our work will inform planning and response measures for future variant surges in the coming months, both nationally and globally, and may be adapted for outbreaks of other diseases. It will also train a postdoctoral researcher and a graduate student in scientific expertise and communications skills.The COVID-19 Scenario Hub has completed 12 rounds of scenario projections for the USA. A major source of uncertainty that affects scenario design and projections is new genetic variants. First, this project will improve information gain and uncertainty reduction pertaining by engaging with scientists working on immunology, epidemiology, and viral evolution to elicit information on plausible emergence timing and the range of possible characteristics of potential new variants, via expert elicitation methods. Second, for response purposes, the project will commence to build a network to gather, organize and synthesize information on the emerging characteristics of any actual new variant of concern that will improve the emergency process the Hub used for the Omicron variant, streamlining and enhancing information gain. Both information streams will be used to improve scenario development and to provide the best possible data to participating modeling teams. This project was funded in collaboration with the CDC to support rapid-response research projects to further advance federal infectious disease modeling capabilities.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.