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RAISE: IHBEM: Inclusion of Challenges from Social Isolation Governed by Human Behavior through Transformative Research in Epidemiological Modeling

RAISE: IHBEM: Inclusion of Challenges from Social Isolation Governed by Human Behavior through Transformative Research in Epidemiological Modeling
RAISE:IHBEM:通过流行病学模型的变革性研究纳入人类行为所带来的社会孤立的挑战
批准号:
2230117
负责人:
Folashade Agusto
金额:
$100.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-01-01 至 2025-12-31

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中文摘要
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英文摘要
Project INSIGHT is a collaborative effort to develop novel and transformative research aimed at incorporating human social, behavioral, and economic interactions in mathematical epidemiological models. Project INSIGHT addresses two sets of questions about behavioral responses to social isolation during the COVID-19 pandemic: (1) How does compliance with isolation policies drive disease mitigation outcomes? and (2) Does social isolation lead to unanticipated negative social outcomes, and if so, how? Social isolation and individual distancing are key tools in mitigating large-scale infectious disease outbreaks. Yet, social interactions are crucial for the health and prosperity of individuals and their communities. Social isolation is associated with negative outcomes such as substance use and abuse, domestic violence, and reduced mental and physical health. These negative effects are often pronounced in rural, low-income, and older communities. The primary goal of INSIGHT is to model both positive and negative effects and thereby improve our understanding of the course of the COVID-19 pandemic and its long-term effect on society. This project is funded jointly by the Division of Mathematical Sciences (DMS) in the Directorate of Mathematical and Physical Sciences (MPS) and the Division of Social and Economic Sciences (SES) and the Division of Behavioral and Cognitive Sciences (BCS) in the Directorate of Social, Behavioral, and Economic Sciences (SBE).Project INSIGHT develops realistic epidemic models incorporating behavioral responses of compliance and adherence as follows: (1) Isolation compliance. Using a classical segmentation of populations into compliant and non-compliant groups, a switching function is defined to account for changes in behavior. Games with appropriate payoff functions that inform individuals’ behavioral choices are used. (2) Opioid misuse treatment adherence. A model according to severity of substance use disorder is created, implementing treatment adherence with game-derived utility functions and incorporating drug-seeking behavior of affected individuals, Model parameters like recovery and deaths are accounted for via well-defined behavioral functions. (3) Domestic violence. Focusing on intimate partners, economic-dependent functions are used to capture partners’ choices such as abuse, forgiveness, seeking help, or leaving the domestic violence cycle. The modeling efforts use data from several national and local sources. The outcome of Project INSIGHT modeling efforts is a synthetic, in-depth view of the balance of positive (reduction of disease transmission) and negative (substance abuse, domestic violence) implications of social isolation as a response to pandemic situations.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.
期刊论文(3)
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会议论文
DOI: 10.1615/jmachlearnmodelcomput.2023047213
发表时间: 2023
期刊: Journal of Machine Learning for Modeling and Computing
影响因子: --
作者: [Ogueda-Oliva, Alonso G., Martínez-Salinas, Erika Johanna, Arunachalam, Viswanathan, Seshaiyer, Padmanabhan]
通讯作者: Seshaiyer, Padmanabhan
Literate programming for motivating and teaching neural network-based approaches to solve differential equations
用于激励和教授基于神经网络的方法来求解微分方程的文字编程
DOI: 10.1080/0020739x.2023.2249901
发表时间: 2023
期刊: International Journal of Mathematical Education in Science and Technology
影响因子: 0.9
作者: [Ogueda-Oliva, Alonso, Seshaiyer, Padmanabhan]
通讯作者: Seshaiyer, Padmanabhan
RAPID: COVID-19 Behavior, Perception, and Control Across Geographic and Economic Gradients
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