化学 lab students predict spread of 新型冠状病毒肺炎 with kinetics models

化学家 轨迹陈 looked at the rapid spread of 新型冠状病毒肺炎 early in the pandemic and saw a novel opportunity for his kinetics lab, 研究反应速率的地方.

他第一次管理实验室是在2021年春天, undergraduate students concluded that social regulations such as lockdowns, face masks and 社会距离 were effective ways to slow the speed of the spread of COVID. 但他们也发现了建模的局限性, 注意的是 that a large number of confirmed cases didn't necessarily associate with an increasing rate of spread.

隔壁实验室的学生也写了 一篇关于他们经历的期刊文章 ,研究人员 应该 继续这项工作 当 感染率和接种率显著提高fi斜面.

事情就是这样发生的. The spring 2022 lab students in CHEM 4540 Physical 化学 II extended the mathematical model to make predictions on the rate of spread of 新型冠状病毒肺炎 in the United States 大量的疫苗接种.

They also ran the model for the state of Ohio through fall 2022 — correctly predicting the upsurge in cases the state is experiencing at the end of summer.

The second group of lab students also wrote up their lab experience, this time seeing it 发表在《newbb电子》上. All the students walked away from the lab with the requisites filled. But they also could add several lines to their resumes — for modeling software experience, 数据分析技能, 以及期刊出版物.

"The most surprising and fun thing for me was how research can be accessible. 我们只使用了免费网站上的资源和数据, but from there we were able to push further and dive into something so relevant to today's society,” 艾玛Lintelman, a 不断上升的高级 化学专业 辅修生物科学 在艺术学院 & 科学.

实时化学

2021年春天，世界变得遥远, using the COVID model enabled Chen's students to work on their own computers with publicly accessible data and software.

It worked so well that undergraduate students submitted 一篇关于他们经历的期刊文章, 注意的是, "The viral spreading model is complicated but parameters, such as its reproduction 数, Rt, can be estimated with the susceptible, infectious, or recovered model. 新型冠状病毒肺炎 data for many states and countries are widely available online. 这为……提供了机会 学生可以远程分析其扩散动力学." 

陈，副教授 化学 & 生物化学 in the 文理学院, noted that COVID modeling provided an 优势，当它来解释稳定教科书中一些模型的状态近似. The students noted that they benefited by exploring the simulation function of commonly-used software Excel.

模型的力量

2022年春天，陈和他的学生参加了 动力学数值模拟 还有回归建模.

“我们第一次使用这种方法时， the students were able to apply the kinetic techniques learned in physical chemistry to analyze an ongoing real-world problem through a remote learning environment," Chen said. "今年, another group of undergraduate students led by graduate students Dylan Smith and Tharushi Ambagaspitiya did the same practice and extended the mathematical model to predict 新型冠状病毒肺炎 spread in the U.S. 大量的疫苗接种."

在实验室里, the susceptible-infectious-recovery (SIR) model and the SIR-vaccinated (SIRV) model are explained to the students and are used to analyze the 新型冠状病毒肺炎 spread data from the U.S. 美国疾病控制与预防中心. The basic reproduction number R0 and the real-time reproduction number Rt of 新型冠状病毒肺炎 are extracted by fitting the data with the models, which explains the spreading kinetics and provides a prediction of the spreading trend in a given state.

The students can quickly see the differences between the SIR model and the SIRV model, Chen said. SIRV模型考虑了疫苗接种的影响, 这有助于解释当前大流行的后期阶段.

"A surprising part of the experiment we conducted was how we could really see the impact various changes in our everyday habits had on the virus. This aspect of the experiment helps create a direct link between the study of chemical kinetics to the real physical world for students,迪伦·史密斯说, a chemistry graduate student and a teaching assistant in the lab. "I found the review process to be personally challenging but ultimately a great learning experience in my own education."

The students also learned the predictive power of the models as they made predictions for the following months.

"I think the most surprising part of performing our 新型冠状病毒肺炎 kinetics simulation was seeing the drastic effects of varying the time-dependent reproduction number in our simulation,大卫·麦克尤恩说, 化学专业的大四学生，辅修商科. "This allowed us to directly simulate different levels of regulation of the virus through masking, 社会距离, 等. 通过大量改变数字, we were able to directly see with our data the increased or decreased spread rate of the virus, 这有时是令人震惊的.

"I think the most challenging parts for me were initially setting up our simulation parameters and fitting the simulated data to the collected case data. Fitting the simulated data to the actual case numbers sometimes required precise adjustment and took some time,麦克尤恩说.

Lintelman同意, 添加, "The most challenging part for me was working out the bugs in our formulas. This can be tricky 当 you've been staring at your data for hours. 这一切都开始在脑海中盘旋, but that's just 当 you need to come back to it later 当 you have a clear mind."

陈指出，美国国立卫生研究院(nih)的一项拨款(Super-Resolution Optical Mapping for DNA Analysis Using Triplex-Forming Oligonucleotides as Stochastic Molecular Probes部分资助了教学实验室.