听力文本

This is Scientific American — 60-Second Science. I'm Christopher Intagliata.
Every flu season—that's now through the spring—epidemiologists track flu infections as they break out across the country. And they forecast how bad it's going to get: at the national level, regionally, state by state. They even forecast for metro areas, like New York City, and L.A. Which sounds pretty fine-grained, until you consider that New York City is made up of five boroughs. And that there are actually more than 80 cities... in L.A. County.
So there might be an advantage to forecasting at even smaller scales. "Public health decision-making and interventions are done at small scales, they're done at the municipal and county scale." Jeffrey Shaman, an infectious disease modeler at Columbia University.

He and his team built a model to forecast flu within New York City neighborhoods and boroughs, using data on flu cases from 2008 through 2013. They added in something they called "network connectivity"—commuter data, basically. The commuter data didn't improve the accuracy of hyper-local, neighborhood-level forecasts. But it did improve predictions at the borough level, compared to models without that sort of commuter flow built in. The results are in the journal PLoS Computational Biology.
Shaman says fine-tuned forecasts could warn local hospitals before a big outbreak. "Knowing when that's going to be will allow them to plan the resources out. Have the staff available. They also need the very basic things, They need gloves, beds, they need ventilators, they need to have those appropriately available in time so they can meet that patient surge." And—so they can stop the virus' spread in that most local of networks: within the hospital itself.
Thanks for listening for Scientific American — 60-Second Science Science. I'm Christopher Intagliata.

参考译文

这里是科学美国人——60秒科学vv9VG-qbKLnZ~Hd3,。我是克里斯托弗·因塔利亚塔t%6mLS#~IsJc~dI。
每次流感季，现在流感季会持续整个春天，在全国爆发流感传染病时，流行病学家对流感进行了追踪调查ltFYTH~#IgPB。另外，流行病学家还从国家层面、区域层面以及州水平对流感疫情的发展程度进行了预测r)~BdBq_69cYR_。他们甚至还对纽约、洛杉矶等大都市的情况进行了预测sbPvK-)0kCVRvI,。听起来划分的非常精细，但是你要考虑一下，纽约是由五个区构成的fV2-+tLC,4hPkl。而且洛杉矶县由80多个城市组成V!Zu%9s24tj#8d-Mq。
所以，在更小的范围内预测可能有好处~#0O3~2d^TZVH=VZ7。“公共卫生决策和干预措施在小范围完成，通常是在市或县的范围内进行~E;fbu.!j~|;|34(N=。”杰弗里·夏曼是哥伦比亚大学的传染病模型专家8+#HsgkjT,49。
他和他的团队建造了一个模型，利用2008年到2013年的流感病例数据来预测纽约市社区和行政区的流感病情L+IrWT*PvON。他们在模型中加入了他们称为“网络连接性”的东西，也就是通勤数据NO,c^&xB^phu^L。这些数据并没有提高超本地和社区性预测的的准确性KTAX0@7ikTU@O=Tj。但是，与没有加入通勤数据的模型相比，这些数据提高了各行政区预测的准确性jW+[uZzE|a。这一研究结果发表在《公共科学图书馆·计算生物学》期刊上dR+c8NZYB6gMDS)UoF。
夏曼表示，精确的预测可以在传染疾病爆发之前警示当地的医院SXGQ9J2UKTmWdw。“知道什么时候爆发疾病，可以让医院提前计划资源分配1-Fj&&rj2Os_TvG&)87。确保有工作人员可用!V|RdFgtK65Vbr*UJ。他们还需要基础设备，他们需要手套、病床、呼吸机，他们要及时准备好这些设备，以应对病患激增等问题gn(S;qQLv%L9J%G!。”另外，这也可以阻止病毒在大部分地方网络的传播，将病毒限制在医院范围内rkp7AhbxYad。
谢谢大家收听科学美国人——60秒科学Z*RWtGIjEp[nDOYuvmnz。我是克里斯托弗·因塔利亚塔GD8zi.,KpQy*P。

译文为可可英语翻译，未经授权请勿转载！

重点讲解

重点讲解：
1. break out （战争、战斗或疾病）爆发；
例句：A cholera epidemic broke out after the flood.
一场流行性霍乱在洪水过后就突发了]~tz^Pj^+8NwH。
2. be made up of 组成；构成；
例句：Life is made up of sobs, sniffles, and smiles, with sniffles predominating.
人生是以哭、泣、笑三者构成的，尤以泣为最G0E=8+%)e7N,KuP7]。
3. add in 加入；
例句：Once the vegetables start to cook add in a couple of tablespoons of water.
开始烹调蔬菜时，加入几调羹水.-l+gO5&k.T_@XY3g~O_。
4. plan out 周密地计划；详尽地安；
例句：I have started planning out what I shall be doing next week.
我已开始详细安排下周要干的事儿了,V!u+pw~fP!JFQ2M。