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RAPID: DETER: Developing Epidemiology mechanisms in Three-dimensions to Enhance Response

RAPID: DETER: Developing Epidemiology mechanisms in Three-dimensions to Enhance Response
快速:阻止:建立三维流行病学机制以加强应对
批准号:
2027293
负责人:
Debra Laefer
金额:
$9.89万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-05-01 至 2021-04-30

项目摘要

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中文摘要
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英文摘要
The DETER project will collect data sets that can transform the study of virus transmission from two-dimensional mapping exercises into highly detailed, three-dimensional propagation models to better equip communities with the information they need for improved disease tracking, community-transmission prediction, and preventative disinfection strategies. The project will provide new types of data related to human behavior when leaving healthcare facilities that will allow more localized disease transmission models to be created. The project will track human behavior in terms of where people go (e.g. bus, coffee shop) and how they physically interact with the environment (i.e. what they touch and for how long). The project will immediately make publicly available data that could be critical for modeling virus-based outbreaks including predicting further community transmission during the current COVID-19 pandemic.Community-transmission is responsible for over three-quarters of the COVID-19 cases in the US. Yet, current models do not consider localized behavior to predict virus transmission or the extent of propagation within individualized settings and their surrounding communities. The DETER project will provide such data and demonstrate new three-dimensional means to understand community-level risk. The DETER project investigates how generalizable human behavior is in terms of destination selection after visiting a healthcare facility and the extent and types of hand-based interaction with the built environment. These questions will be answered through tracking individuals when leaving healthcare facilities and recording touch-based behaviors on public transportation and public accommodations. The project will provide a transferable framework and a data integration strategy that can be adopted into a wide variety of three-dimensional models and schema that will help equip researchers and local communities with better methods for predicting community-based transmission.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.
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