撰文/播音：克里斯托弗·因塔利亚塔(Christopher Intagliata)
翻译：郭鑫鹏
审校：丁可含
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.
每当到了流感季节，就像现在春季，流行病学家在流感侵袭国家的时候监测传播情况。然后他们预测流感所带来的影响，这些会在在国家层面进行，也会在每个州地方的层面上。他们也预测如纽约市和洛杉矶一样的大都市。这听起来似乎分得很细，但是你要知道纽约市由5个行政区组成，而洛杉矶甚至包含80多个城市。
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.
所以，在更小的地域范围进行预测将会很有好处。“小范围内的公共健康决策和干涉，如在市、县层面上。“哥伦比亚大学传染病建模者杰弗里·沙曼说。
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. [Wan Yang, Donald R. Olson, Jeffrey Shaman: Forecasting Influenza Outbreaks in Boroughs and Neighborhoods of New York City]
他和他的团队建立一个模型预测流感在纽约市内的传播，他们使用2008年到2013年的流感事件的数据。并且加入了他们称作“联系网“的通勤数据。通勤数据并没有提升超本地化，社区级别的预测精准度，但是它们相比那些没有加入通勤数据的模型，在镇级的预测上有了提升。结果发表在期刊《公共科学图书馆：计算生物学》上。
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 for 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.
沙曼说，这样预测方面的调整可以在传染病大爆发前对当地医院进行预警。“知道传染病什么时候来可以让人们计划好资源的分配，方便召集工作人员。他们还需要许多基础物品，比如手套、床、通风设备。这一切都需要及时地进行配置，以满足这批病人的需要。”这样他们可以将病毒限制在医院内，防止它向人群密集区蔓延。
-Christopher Intagliata
京公网安备11010502039775号
信息网络传播视听节目许可证0111611号
国家科技基础条件平台
