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谷歌地球非洲抗疟疾:或拯救无数人生命

Sy Mukherjee 2017年05月02日

谷歌近年来携手慈善机构,积极与其它学术和公共健康组织开展合作,运用谷歌地球引擎的机器学习技术开展疟疾传染源的精确定位工作。

上周二是世界防治疟疾日。近年来,在全球医疗界和许多公办与私营疟疾防治项目的共同努力下,疟疾防治工作取得了显著进步。2010年至2015年,全球疟疾发病率下降了21%,疟疾致死率下降了29%。不过疟疾至今仍是一种十分凶险的传染病,据世界卫生组织近日发布的数据显示,仅在2015年,全球就有2.12亿例疟疾病例,导致了近43万人死亡。

要想有效对抗疟疾等传染性疾病,首先要精确定位这些疾病的传播区域,从而准确切断它们的传播路径。这样一来,一些预防性的措施(如防蚊设施)和相关治疗资源才能得到更精确的部署。着眼于这一目标,谷歌近年来携手比尔和梅琳达盖茨基金会、克林顿健康倡议组织(CHAI)等慈善机构,积极与其它学术和公共健康组织开展合作,运用谷歌地球引擎的机器学习技术开展疟疾传染源的精确定位工作。

以上这些机构都参加了消灭疟疾倡议组织(Malaria Eliminaiton Initiative)发起的DiSARM项目。该项目即将在非洲的斯威士兰和津巴布韦两国试行。它主要通过谷歌地球引擎技术对疟疾传染源进行精确定位。DiSARM项目负责人、加州大学旧金山分校的流行病学和生物统计学教授休•斯特罗克解释了谷歌地球引擎技术何以能够帮助我们对抗这种疾病。

他在一次刊登在谷歌官方博客的采访中表示:“在斯威士兰和津巴布韦,只要有人被确诊得了疟疾,工作人员就会前往感染发生的村子,精确采集感染地点的GPS定位数据。不过只看这些定位点,你还无法准确判定该地区的疟疾风险。你还需要通过卫星图像结合当地的降水、气温、坡度、海拔等环境因素,因为这些因素都会影响到蚊虫的繁殖和寄生虫的发育。”

斯特罗克还指出,除了能够绘制出高清的“疟疾风险地图”,谷歌地球引擎还使这些辅助性(但又十分重要)的数据变得更易于采集。“过去我们必须要通过多个来源才能获得这些数据,比如通过美国宇航局(NASA)、美国地质勘探局(USGS)以及世界各地的多所大学。有了谷歌地球引擎技术,这些数据在同一个地方就能收集到,而且利用谷歌的计算机就能进行处理。我们把谷歌地球引擎的卫星图像数据与该国的国家疟疾控制部门收集到的病例定位信息综合到一起,然而进行建模,就能生成风险地图,判定哪些区域的疟疾爆发风险最高。”

另外,抗虐疾药物的研发过程也能够从这种技术中得到一定助力。本周一,世界卫生组织宣布,一种试验性的疟疾疫苗下一阶段将在非洲进行首次试点应用。(财富中文网)

译者:朴成奎

Tuesday is World Malaria Day. The global health community and a coalition of public-private initiatives has successfully begun taming the scourge, with a 21% decrease in its global incidence and 29% drop in mortality rate between 2010 and 2015; still, there were 212 million malaria cases worldwide and nearly 430,000 deaths from the disease in 2015, according to the latest World Health Organization (WHO) figures.

One key tactic for fighting infectious diseases like malaria is to pinpoint exactly where they're spreading in order to stop them in their tracks. This way, preventive measures like mosquito control and the deployment of treatment resources can be better targeted. Google, the Bill & Melinda Gates Foundation, and the Clinton Health Access Initiative (CHAI) have banded together with academic and public health partners with this very goal in mind—and are harnessing machine learning through the Google Earth Engine to accomplish it.

The organizations are taking part in a Malaria Elimination Initiative effort called project DiSARM which will be piloted in Swaziland and Zimbabwe and uses the Google Earth Engine to map malaria. The University of California, San Francisco's (UCSF) epidemiology and biostatistics professor Hugh Sturrock—who leads DiSARM—explained exactly why Google's tech can help fight the disease.

"Every time someone is diagnosed with malaria in Swaziland and Zimbabwe, a team goes to the village where the infection occurred and collects a GPS point with the precise infection location," he said in an interview posted on Google's blog. "Just looking at these points won’t allow you to accurately determine the risk of malaria, though. You also need satellite imagery of conditions like rainfall, temperature, slope and elevation, which affect mosquito breeding and parasite development."

In addition to producing high-resolution "risk maps," the Google Earth Engine makes this seemingly ancillary (yet critical) data far easier to collect, according to Sturrock. " In the past we had to obtain those images from a range of sources: NASA, USGS and different universities around the world. But with Google Earth Engine, it’s all in one place and can be processed using Google computers. We combine satellite imagery data from Google Earth Engine with the locations of malaria cases collected by a country’s national malaria control program, and create models that let us generate maps identifying areas at greatest risk."

Concurrent advances in malaria drug development could also get a boost from this type of tech; on Monday, the WHO announced the next phase of a real world trial testing an experimental malaria vaccine in Africa.

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