1 00:00:03,830 --> 00:00:02,149 decades of research and technology have 2 00:00:06,070 --> 00:00:03,840 allowed for better forecasting of the 3 00:00:08,470 --> 00:00:06,080 when where and how intense a hurricane 4 00:00:10,950 --> 00:00:08,480 will be but what if we could predict a 5 00:00:12,789 --> 00:00:10,960 disease outbreak in the wake of a storm 6 00:00:14,789 --> 00:00:12,799 that's the question some researchers 7 00:00:17,510 --> 00:00:14,799 asked about cholera in haiti in the 8 00:00:19,429 --> 00:00:17,520 aftermath of hurricane matthew 9 00:00:21,029 --> 00:00:19,439 cholera is a waterborne infectious 10 00:00:23,189 --> 00:00:21,039 disease that occurs when a person 11 00:00:25,269 --> 00:00:23,199 ingests food or water contaminated with 12 00:00:27,830 --> 00:00:25,279 the vibrio bacterium 13 00:00:30,310 --> 00:00:27,840 cholera causes severe diarrhea nausea 14 00:00:31,990 --> 00:00:30,320 vomiting and dehydration and can lead to 15 00:00:33,910 --> 00:00:32,000 death if untreated 16 00:00:35,750 --> 00:00:33,920 researchers estimate that hundreds of 17 00:00:37,830 --> 00:00:35,760 thousands of cases are reported each 18 00:00:39,430 --> 00:00:37,840 year worldwide 19 00:00:41,830 --> 00:00:39,440 the bacterium is 20 00:00:43,590 --> 00:00:41,840 found in world oceans 21 00:00:45,590 --> 00:00:43,600 globally 22 00:00:47,190 --> 00:00:45,600 especially in the temperate regions and 23 00:00:49,190 --> 00:00:47,200 in the tropics 24 00:00:50,950 --> 00:00:49,200 so in the countries 25 00:00:53,830 --> 00:00:50,960 less developed 26 00:00:55,510 --> 00:00:53,840 with infrastructure that is not the 27 00:00:58,470 --> 00:00:55,520 equivalent let's say 28 00:00:59,430 --> 00:00:58,480 europe or the united states or canada 29 00:01:02,630 --> 00:00:59,440 then 30 00:01:05,030 --> 00:01:02,640 the population that has to rely on 31 00:01:07,350 --> 00:01:05,040 river water pond water 32 00:01:09,830 --> 00:01:07,360 is at risk for cholera 33 00:01:11,590 --> 00:01:09,840 in addition to water insecurity high 34 00:01:13,350 --> 00:01:11,600 seasonal temperatures followed by 35 00:01:15,350 --> 00:01:13,360 extreme rainfall 36 00:01:17,190 --> 00:01:15,360 concentrated populations 37 00:01:19,109 --> 00:01:17,200 and a natural disaster are all 38 00:01:20,469 --> 00:01:19,119 conditions conducive to a cholera 39 00:01:23,670 --> 00:01:20,479 epidemic 40 00:01:25,590 --> 00:01:23,680 this was the case for haiti in 2010 the 41 00:01:27,429 --> 00:01:25,600 data that we were able to to pull 42 00:01:30,550 --> 00:01:27,439 together showed that 43 00:01:33,429 --> 00:01:30,560 in 2010 it was the hottest 44 00:01:34,789 --> 00:01:33,439 summer in 50 years and then as if that 45 00:01:37,350 --> 00:01:34,799 weren't enough 46 00:01:40,310 --> 00:01:37,360 there was a hurricane that skirted the 47 00:01:41,590 --> 00:01:40,320 island but it dumped the heaviest 48 00:01:44,149 --> 00:01:41,600 rainfall 49 00:01:46,389 --> 00:01:44,159 in 50 years we tried to make an 50 00:01:48,630 --> 00:01:46,399 algorithm in a cohesive form to 51 00:01:50,630 --> 00:01:48,640 determine the risk and and that 52 00:01:53,590 --> 00:01:50,640 basically provided us with the first 53 00:01:58,310 --> 00:01:53,600 clues on the risk of outbreak of cholera 54 00:02:04,550 --> 00:02:01,670 then we use the same algorithm 55 00:02:06,789 --> 00:02:04,560 with improved satellite data sets from 56 00:02:09,430 --> 00:02:06,799 global precipitation measurement mission 57 00:02:10,070 --> 00:02:09,440 after hurricane matthew struck that 58 00:02:12,470 --> 00:02:10,080 region again 59 00:02:15,030 --> 00:02:12,480 [Music] 60 00:02:17,350 --> 00:02:15,040 and we were able to in real time predict 61 00:02:19,270 --> 00:02:17,360 the risk of cholera infection in human 62 00:02:21,190 --> 00:02:19,280 population at least four weeks in 63 00:02:23,990 --> 00:02:21,200 advance 64 00:02:25,510 --> 00:02:24,000 we did the same thing for yemen we knew 65 00:02:27,190 --> 00:02:25,520 that there is a mass movement of human 66 00:02:30,150 --> 00:02:27,200 population due to civil unrest in that 67 00:02:32,150 --> 00:02:30,160 part of the world and then we had very 68 00:02:33,990 --> 00:02:32,160 heavy precipitation and then we 69 00:02:36,550 --> 00:02:34,000 immediately started monitoring 70 00:02:40,070 --> 00:02:36,560 conditions and that basically converged 71 00:02:41,830 --> 00:02:40,080 to give us a risk on where and when this 72 00:02:43,110 --> 00:02:41,840 this disease will occur in human 73 00:02:46,229 --> 00:02:43,120 population 74 00:02:48,390 --> 00:02:46,239 i think we can predict and prevent 75 00:02:50,869 --> 00:02:48,400 and i'd like to see that happen very 76 00:02:53,750 --> 00:02:50,879 quickly in the next three to five years 77 00:02:56,869 --> 00:02:53,760 and i'd like to see the satellite system 78 00:02:59,110 --> 00:02:56,879 to be part of the regular public health 79 00:03:00,470 --> 00:02:59,120 tools so that we can do 80 00:03:03,430 --> 00:03:00,480 prediction