RAPID: Mathematical models for uncovering neurological disorders among the U.S. population infected with COVID-19

从统计数据来看，COVID-19病毒与大脑和神经系统相关的特定医学疾病有关。尽管过去有一小部分SARS和mers患者被证明患有焦虑和其他神经系统疾病，但2020年和2021年冠状病毒大流行的规模是另一个数量级。在美国和其他国家，COVID-19患者出现神经系统疾病的原因尚不清楚，但数据表明，一些COVID-19患者在意识、意识和认知方面存在问题。对世界各地的患者进行了实验，并记录了COVID-19患者的行为数据。在这个项目中，主要研究人员将开发一个数学模型来理解这些神经机制。待开发的模型将被验证和验证。一旦该模型与美国和其他国家的数据进行校准，研究人员将研究COVID在发展脑部疾病中的作用。他们将根据参数的随机波动结合模型的可预测性。其结果将对人口和整个社会的全面福祉产生重要影响。如果对脑损伤原因的不确定性继续下去，那么美国患神经系统疾病的人数可能会进一步增加。尽管疫苗接种计划产生了积极影响，但COVID-19在现有患者中引起了一些神经系统疾病。除了COVID-19的负担，医院和卫生管理人员还需要了解人群中其他长期的大脑相关疾病。一项良好的定量研究将立即有助于控制美国COVID-19脑相关损伤患者的发病率。研究人员打算在全国范围内为神经内科医生提供免费咨询，如果他们需要任何即时的定量预测帮助（在有限的时间范围内）。研究人员将开发一个数学模型，以了解美国大脑退化与COVID-19之间关联的规模和复杂性。具体而言，他们将预测和评估美国可能患有精神病、出血、谵妄和中风等神经系统疾病的人。临床数据显示了一些关联，但从这些研究中尚不清楚为什么会出现COVID患者的这些疾病原因。几项针对COVID患者的研究发现，精神科诊断的临床病例定义与脑出血之间存在统计学相关性。另一个不确定性仍然是了解COVID对血脑屏障位置的影响；临床研究正在朝这个方向发展。对大量临床人群的统计回归分析可能提供神经系统疾病的各种独立变量之间的关联。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 virus has been statistically linked to specific medical disorders connected to the brain and nervous system. Although in the past a fraction of SARS and MER patients have been shown to have anxiety and other neurological disorders, the scale of the coronavirus pandemic in 2020 and 2021 is another order of magnitude. The reasons for neurological disorders among COVID-19 patients in the U.S. and other countries are not clear, but the data indicate that some of COVID-19 patients have issues with their awareness, consciousness, and cognizance. Experiments have been conducted on patients worldwide and data was recorded on the behavior of COVID-19 patients. In this project, the principal investigators will develop a mathematical model for an understanding of these neurological mechanisms. The model to be developed will be validated and verified. Once the model is calibrated with data from the U.S. and other countries, the investigators will study the role of COVID in developing brain disorders. They will combine the predictability of the model according to the stochastic volatility of the parameters. The results will have an important impact on the overall well-being of the population and society as a whole.If uncertainty concerning the reasons behind brain damage continues then that could further increase the number of people in the U.S. who would have neurological disorders. In spite of the positive influence of vaccination programs, COVID-19 causes some of neurological disorders among the current patients. Along with the COVID-19 burden, hospitals and health administrators need to understand other long-term, brain-related disorders in the population. A good, quantitative study will be of immediate help in controlling the incidence of brain-related damaged individuals who have COVID-19 in the U.S. The investigators intend to provide a free consultation to neuro-physicians across the nation if and when they need any immediate quantitative assistance in predictions (within a limited time frame). The investigators will develop a mathematical model to understand the size and complexity of the association between brain deterioration and COVID-19 in the U.S. Specifically, they will predict and evaluate people in the U.S. who will likely have neurological disorders like psychosis, hemorrhage, delirium, and stroke. Clinical data have shown some association, but why there are such causes of disorders for the COVID patients is not yet clear from these studies. Several studies among COVID patients have found a statistical correlation between clinical case definitions for psychiatric diagnoses and intracerebral hemorrhage. Another uncertainty remains in understanding the impact of COVID in blood-brain barrier locations; clinical studies are in progress in this direction. A statistical regression analysis on a large clinical population might provide an association among various independent variables of neurological disorders.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.