Taking on COVID-19 with math and stats

Professor of Mathematics and Statistics Paul Hurtado and Nevada State Biostatistician and College of Science alumna Kyra Morgan talk COVID-19 and how they’re using numbers to make sense of it all.

Kyra Morgan and Paul Hurtado stand on the quad wearing masks.

Morgan and Hurtado stand socially distanced and masked on the University quad.

Taking on COVID-19 with math and stats

Professor of Mathematics and Statistics Paul Hurtado and Nevada State Biostatistician and College of Science alumna Kyra Morgan talk COVID-19 and how they’re using numbers to make sense of it all.

Morgan and Hurtado stand socially distanced and masked on the University quad.

Kyra Morgan and Paul Hurtado stand on the quad wearing masks.

Morgan and Hurtado stand socially distanced and masked on the University quad.

凯拉·摩根是内华达州的生物统计学家和统计硕士课程的数学和六个部门校友统计,一出来她的七个团队谁正在积极工作的SARS-COV-2 / covid-19响应的部门研究生。她负责集中分析了内华达州,负责该州的反应,因为它涉及到公共健康数据和分析,帮助告知双方政府的领导和内华达州的公民对相关数据和公共卫生信息。她还负责监督,如补充营养援助计划(SNAP)国家计划工作量预测,医疗补助和贫困家庭(TANF),帮助推动国家的年度预算临时援助。这是一项艰巨的任务,并在2020年的春天,她的工作得到更大。作为covid大流行开始在内华达州蔓延,摩根的工作量成倍增加,在时间响应三倍。她立即​​与管理公共仪表板与有关该病毒的传播状态基本数据负责。她的团队创造了一个“PPE计算器”,以帮助个人防护装备(PPE)到内华达州的医院和医疗专业人员的分配。她会见了当地卫生部门,参加了在农村地区积极covid调查,并与州长的医疗顾问团队协作做出了州长办公室的建议。所有的同时,公众健康仍然存在covid之外,摩根的许多其他责任仍然存在为好。事情并没有放缓,摩根继续响应与数学和科学这瞬息万变的健康危机。

Paul Hurtado is a professor of Mathematics and Statistics and a mathematical modeler of biological systems. Hurtado is also part of the Evolution, Ecology, and Conservation Biology (EECB) graduate program faculty. He usually focuses on studying the ecology and evolution of infectious diseases affecting non-human hosts, but in early 2020 he turned his attention to the emerging pandemic. Since then, Hurtado has been working with Morgan and her team to develop COVID models for Nevada and help interpret the output of other publicly available models. In early July, Morgan and Hurtado (virtually) sat down together to discuss the pandemic response from their data-driven perspective.

Morgan: My job is exclusively COVID at this point, except that it’s not. We’re really, as a whole, getting hit from every direction.

Hurtado: I had a much easier transition at the start of all of this. The majority of my time was spent teaching and transitioning my classes to online learning. But COVID did throw a big twist into how I was thinking about research, and in both of my classes, we would spend at least the first 10 minutes talking about Coronavirus and data and models. Students could see some of the things we were talking about happening in real-time. Every week things were shifting.

Morgan:Are, I would say are shifting!

Hurtado: Very true! In terms of the early on March/April time period, how clearly did you have a sense of what data you needed and from whom?

Morgan: Early on, I was approached by my director and asked to get a dashboard up that same day and I had to think about what data we were currently collecting. All of the core data such as how many cases we had or how many people were getting tested came from mechanisms that have been in place for a long time. Mortality data we’ve already had access to, but we initially had a little bit of trouble getting in real-time. We have changed our process so that deaths from COVID are reported simultaneously to a local health authority and the State so we have as much real-time data as possible. 

"We’re back to seeing days where 15% of people tested are coming back positive. In the current atmosphere where testing isn’t limited, that’s a really high number. We know that our population is more saturated with the disease because of that percent positivity rate."

住院数据是最大的孔。在过去,这些数据是基于医院账单,所以你可以想像这是相当滞后。但是,在那个时候,有我们需要它迟早没有真正的理由。同时,我们对疾病调查小组通常必须呼吁住院地位阳性病例,并要求实时更新,除其他事物的能力。与covid,这一直没有停止缺口我们,因为我们根本不具备人力和资源做足够的这些电话的。我们试图填补这一空白的方法是使用来自内华达州医院协会的数据。一项调查显示,每天被放出来给我们所有的医院得到一些高层次的信息。扩展上提供的数据是我们的领导有优先选择权,现在,所以我们正在积极努力获得更多的信息。 

Hurtado: On the modeling end, things were similar. Early on, we thought, great, respiratory disease. We know how to model this. We have oodles of models and experience fitting them to data. It wasn’t like we were starting from scratch. What a lot of modelers did was start with flu models and go from there to see what needed to change. However, the pace of changing those models to keep up in real-time was difficult. There were a lot of unknowns early on.            

Morgan: We’re in a bit of a limbo where we’re seeing differences in the trend of the disease, but I’m not seeing that precipitate into different model outputs. For example, when I see every day we have a record high of new cases, and I go to these State-wide models that say we have a 99% chance of having reached the “peak”, obviously I know there is a disconnect between those two things. I’ve actually digressed from reporting models as much as monitoring and reporting on key trends in observed data.

Hurtado: When I started out modeling COVID, I collaborated with a friend of mine who does this stuff for a living and has an army of graduates and postdocs to help her play with different model assumptions. Early on, when looking at age-based models with less complexity built into them, they were all working pretty much the same in terms of forecasts. But as things started to progress and we had changes in who was getting testing and the age group demographics began to act very differently, all of those things started to break the models. As each of those things bent the rules of the models, we had to continually adapt.

Kyra Morgan speaking at a press conference.
Kyra Morgan speaks at an April 12th press conference to announce the phased reopening criteria in the State of Nevada. Photo by Shannon Litz.

Morgan: 这是伟大的,有一个模型,预测和一条优美的曲线。这是真正有价值的,但在实践中,你并不总是需要一个花哨的预测,看看发生了什么事或发生了什么。一些我们在内部监控的事情都没有预期,但我们可以看到的措施有一定的趋势。我们早早就作为一个国家,我们不能只看阳性的数量,因为我们知道测试即将爬升说。但是,另外,我们知道一些的斜坡向上测试不一定是可持续的。当我们第一次看到的个案有增加,同时我们增加测试,这使得有很大的意义。但现在,测试实际上已经变平了。我们已经达到了检测能力,我们看到的仍然是在案件的增加。正因为如此,我们来看看一些超越案件只是数量的东西,因为这显然是严重受到测试。我们看东西就像%的积极性,有多少人我们正在测试回来阳性。早在大流行时,我们大多测试有严重症状的人,测试人员的21%的高带回来一个积极的结果。当我们有一个非常高的测试活动,这个数字蘸下来真的很低。我们看到天凡低于2%回来了正面。现在,我们又回到了看天凡的测试人15%都回来了正面。在目前的氛围,测试没有限制,这是一个非常高的数字。我们知道,我们的人口是更饱和的疾病,因为%的阳性率的。

这也是非常重要的看住院的数据。从理论上说,不应该有很多人住院covid数量偏见,我们必须在这个时候的人住院确诊covid每天都在破纪录的数字。我们又回到峰值比我们的第一个高峰更糟的是,不只是来自新发病例的看法,因为我们明白可能是主观的。我们的百分比阳性见顶,继续往上走,并已住院住院超过之前的峰值。我们已经能够告诉我们在这个上升的轨迹大约一个月了。我不觉得绑需要一个花哨的统计模型,我早早就因为我们有足够的数据来查看发生了什么一样。

Hurtado: 我会同意这一点。有这么多不同的因素进入发射上升和下降。它是如此复杂,如果你花时间写下来,会做预测你的直觉已经告诉你一个好工作的模式,第一,你不会有需要进到这些模型数据不够,第二,你必须做出关于数学术语一些有趣的假设和扭曲。但是,一旦你得到的是如何仔细考虑数据有很好的了解,专家的意见是真实的东西。我已经看到了很多我的朋友造型让你在谈论这个相同的过渡。他们去了研究生院和研究数学和统计,现在他们正在与有关发廊怎么比吧不同的政策制定者说话。他们能够采取了很多的批判和认真思考定量的东西,能力做的更好即兴比他们自己做的模型做这样的时刻,事情正在迅速发生变化。

"Public perception is driving the response to COVID. Public perception has a lot to do with what policymakers are deciding and the push back they are getting to open or close, wear masks or not."

Morgan: 当你有一个数学学位,你不认为你会是健康和人类服务的公众形象。一个已经在准科学/准领导角色我们很多的艰难转型。统计人员,我们没有学到了很多关于事物的真实世界的一部分。事情我认为是常识都没有常识给其他人。例如,我们知道模型是基于真实的数据。当我看着我的新闻发布会回来,有很多的评论中引用的信念,我们不使用真实的数据来创建我们的模型。我不知道有多少人在总人口中的误解,我们是如何创造这些模型。我可以做解释工作做得更好。公众感知驾驶covid响应。公众的看法有很多事情要做什么决策者在决定和推背他们得到打开或关闭,戴口罩或没有。我可以做解释如何在实际工作模式的一个更好的工作,我如何及早处理公众。

Hurtado: Kyra, that happens to everybody. You always find an audience where you will struggle to figure out where their head is at. That’s a really important lesson to learn and one that’s really hard to teach. Especially for folks that get mathematical and statistical training, there’s not a lot of opportunity to practice. You are not the first person with a nice quantitative background who’s had to get up in front of a bunch of people and explain math to them.

Morgan: 和对话是非常重要的!我们身在何处,因为它涉及到covid社会解释是数字中去的方向很重要,我知道这一点。从我的轶事世界上最少的,我在工作,这显然是由一组的人最多某些人口和社会背景,covid是这个庞大的紧急情况和每个人都开始在做社会疏远了伟大的工作。现在有这种想法我看到反映在新闻媒体和人们的行为,我们正在下坡附近某处,我们是如此的不。要认识到,人们越来越covid疲劳是很重要的。这很容易让人想到“这已经有一段时间了,东西都开放,但必须变得更好,它必须是安全的。”数据不显示,内华达州。该数据不建议这是一个更安全的时间走出去,做的事情。该数据不建议你应该在你的面具,穿着习惯更宽松。数据真的建议我们在一个周期的增长和传输的增加。我们都在紧锣密鼓中兴现在。

Hurtado: 驱动模型的预测,我让我没有良好的数据,我不指望曾经有良好的数据头号最重要的信息是人的行为。跌宕起伏,我们在传输现在看到的不管有没有人纯粹是驱动在做什么,他们可以使用个人防护装备,呆在家里,不出去和交流。在人类行为跌宕起伏的那些五花八门的是不容易预测。我们需要的是能够预测哪些人会在三周内做明白是怎么回事在两个月内发生,而我们只是永远不会知道。人们都在它是否是认真对待或不顺心的事情方面在地图上。甚至那些谁当真谁,这是累人!即使他们最终破裂,需要去拜访他人和社交这是完全可以理解的。希望,我们能够得到一些好的疫苗和更多的治疗选择。但就像你说的,这不是结束或covid甚至中间。 

One thing that’s been great to see is the collaboration within the scientific community. The pace of science has picked up quite a bit. When there are these rapidly evolving situations, it helps that you can just call someone on the phone and have a conversation. Conversations just like this!

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