0:00:01.015,0:00:03.777 You may never have heard[br]of Kenema, Sierra Leone 0:00:03.801,0:00:05.333 or Arua, Nigeria. 0:00:05.357,0:00:09.128 But I know them as two of the most[br]extraordinary places on earth. 0:00:09.956,0:00:15.009 In hospitals there, there's a community[br]of nurses, physicians and scientists 0:00:15.033,0:00:16.590 that have been quietly battling 0:00:16.614,0:00:19.314 one of the deadliest threats[br]to humanity for years: 0:00:19.338,0:00:20.512 Lassa virus. 0:00:21.118,0:00:23.256 Lassa virus is a lot like Ebola. 0:00:23.280,0:00:26.513 It can cause a severe fever[br]and can often be fatal. 0:00:27.053,0:00:30.992 But these individuals,[br]they risk their lives every day 0:00:31.016,0:00:33.933 to protect the individuals[br]in their communities, 0:00:33.957,0:00:36.537 and by doing so, protect us all. 0:00:37.093,0:00:40.001 But one of the most extraordinary things[br]I learned about them 0:00:40.025,0:00:42.592 on one of my first visits[br]out there many years ago 0:00:42.616,0:00:44.325 was that they start each morning -- 0:00:44.349,0:00:49.292 these challenging, extraordinary days[br]on the front lines -- by singing. 0:00:49.731,0:00:53.070 They gather together,[br]and they show their joy. 0:00:53.094,0:00:54.616 They show their spirit. 0:00:54.640,0:00:55.799 And over the years, 0:00:55.823,0:00:58.936 from year after year as I've visited them[br]and they've visited me, 0:00:58.960,0:01:00.953 I get to gather with them and I sing 0:01:00.977,0:01:03.151 and we write and we love it, 0:01:03.175,0:01:06.718 because it reminds us that we're not[br]just there to pursue science together; 0:01:06.742,0:01:09.059 we're bonded through a shared humanity. 0:01:09.586,0:01:13.909 And that of course, as you can imagine,[br]becomes extremely important, 0:01:13.933,0:01:16.706 even essential, as things begin to change. 0:01:16.730,0:01:21.519 And that changed a great deal[br]in March of 2014, 0:01:21.543,0:01:23.889 when the Ebola outbreak[br]was declared in Guinea. 0:01:24.426,0:01:26.558 This is the first outbreak in West Africa, 0:01:26.582,0:01:29.024 near the border[br]of Sierra Leone and Liberia. 0:01:30.074,0:01:32.596 And it was frightening,[br]frightening for us all. 0:01:32.620,0:01:34.532 We had actually suspected for some time 0:01:34.556,0:01:37.198 that Lassa and Ebola were more[br]widespread than thought, 0:01:37.222,0:01:39.531 and we thought it could[br]one day come to Kenema. 0:01:39.896,0:01:42.306 And so members of my team[br]immediately went out 0:01:42.330,0:01:44.727 and joined Dr. Humarr Khan[br]and his team there, 0:01:44.751,0:01:48.428 and we set up diagnostics to be able[br]to have sensitive molecular tests 0:01:48.452,0:01:50.605 to pick up Ebola if it came[br]across the border 0:01:50.629,0:01:51.892 and into Sierra Leone. 0:01:51.916,0:01:54.912 We'd already set up this kind[br]of capacity for Lassa virus, 0:01:54.936,0:01:56.093 we knew how to do it, 0:01:56.117,0:01:57.547 the team is outstanding. 0:01:57.571,0:02:00.808 We just had to give them[br]the tools and place to survey for Ebola. 0:02:01.340,0:02:02.968 And unfortunately, that day came. 0:02:02.992,0:02:07.973 On May 23, 2014, a woman checked[br]into the maternity ward at the hospital, 0:02:07.997,0:02:11.723 and the team ran[br]those important molecular tests 0:02:11.747,0:02:15.582 and they identified the first[br]confirmed case of Ebola in Sierra Leone. 0:02:16.107,0:02:18.156 This was an exceptional[br]work that was done. 0:02:18.180,0:02:20.440 They were able to diagnose[br]the case immediately, 0:02:20.464,0:02:22.777 to safely treat the patient 0:02:22.801,0:02:25.819 and to begin to do contact tracing[br]to follow what was going on. 0:02:25.843,0:02:27.815 It could've stopped something. 0:02:27.839,0:02:30.686 But by the time that day came, 0:02:30.710,0:02:33.068 the outbreak had already[br]been breeding for months. 0:02:33.092,0:02:36.732 With hundreds of cases, it had already[br]eclipsed all previous outbreaks. 0:02:36.756,0:02:40.400 And it came into Sierra Leone[br]not as that singular case, 0:02:40.424,0:02:41.716 but as a tidal wave. 0:02:42.120,0:02:44.395 We had to work[br]with the international community, 0:02:44.419,0:02:48.125 with the Ministry of Health, with Kenema,[br]to begin to deal with the cases, 0:02:48.149,0:02:50.220 as the next week brought 31, 0:02:50.244,0:02:53.918 then 92, then 147 cases --[br]all coming to Kenema, 0:02:53.942,0:02:57.243 one of the only places in Sierra Leone[br]that could deal with this. 0:02:57.610,0:03:01.009 And we worked around the clock[br]trying to do everything we could, 0:03:01.033,0:03:03.994 trying to help the individuals,[br]trying to get attention, 0:03:04.018,0:03:05.965 but we also did one other simple thing. 0:03:06.544,0:03:10.333 From that specimen that we take[br]from a patient's blood to detect Ebola, 0:03:10.357,0:03:12.412 we can discard it, obviously. 0:03:12.436,0:03:16.052 The other thing we can do is, actually,[br]put in a chemical and deactivate it, 0:03:16.076,0:03:18.806 so just place it into a box[br]and ship it across the ocean, 0:03:18.830,0:03:19.981 and that's what we did. 0:03:20.005,0:03:22.101 We sent it to Boston, where my team works. 0:03:22.724,0:03:26.561 And we also worked around the clock[br]doing shift work, day after day, 0:03:26.585,0:03:30.454 and we quickly generated 99 genomes[br]of the Ebola virus. 0:03:30.478,0:03:33.535 This is the blueprint -- the genome[br]of a virus is the blueprint. 0:03:33.559,0:03:34.718 We all have one. 0:03:34.742,0:03:36.687 It says everything that makes up us, 0:03:36.711,0:03:38.620 and it tells us so much information. 0:03:38.644,0:03:41.821 The results of this kind of work[br]are simple and they're powerful. 0:03:42.396,0:03:44.866 We could actually take[br]these 99 different viruses, 0:03:44.890,0:03:46.337 look at them and compare them, 0:03:46.361,0:03:49.207 and we could see, actually,[br]compared to three genomes 0:03:49.231,0:03:52.067 that had been previously[br]published from Guinea, 0:03:52.091,0:03:55.802 we could show that the outbreak[br]emerged in Guinea months before, 0:03:55.826,0:03:57.668 once into the human population, 0:03:57.692,0:04:00.364 and from there had been transmitting[br]from human to human. 0:04:00.388,0:04:01.932 Now, that's incredibly important 0:04:01.956,0:04:04.324 when you're trying to figure out[br]how to intervene, 0:04:04.348,0:04:06.414 but the important thing[br]is contact tracing. 0:04:06.438,0:04:09.840 We also could see that as the virus[br]was moving between humans, 0:04:09.864,0:04:11.121 it was mutating. 0:04:11.145,0:04:13.296 And each of those mutations[br]are so important, 0:04:13.320,0:04:15.640 because the diagnostics, the vaccines, 0:04:15.664,0:04:17.149 the therapies that we're using, 0:04:17.173,0:04:20.531 are all based on that genome[br]sequence, fundamentally -- 0:04:20.555,0:04:21.776 that's what drives it. 0:04:21.800,0:04:24.682 And so global health experts[br]would need to respond, 0:04:24.706,0:04:25.903 would have to develop, 0:04:25.927,0:04:28.480 to recalibrate everything[br]that they were doing. 0:04:29.079,0:04:32.260 But the way that science works,[br]the position I was in at that point 0:04:32.284,0:04:33.435 is, I had the data, 0:04:33.459,0:04:36.095 and I could have worked[br]in a silo for many, many months, 0:04:36.119,0:04:38.318 analyzed the data carefully, slowly, 0:04:38.342,0:04:41.802 submitted the paper for publication,[br]gone through a few back-and-forths, 0:04:41.826,0:04:44.955 and then finally when the paper came out,[br]might release that data. 0:04:44.979,0:04:47.183 That's the way the status quo works. 0:04:47.207,0:04:49.778 Well, that was not going to work[br]at this point, right? 0:04:49.802,0:04:51.410 We had friends on the front lines 0:04:51.434,0:04:54.688 and to us it was just obvious[br]that what we needed is help, 0:04:54.712,0:04:55.868 lots of help. 0:04:55.892,0:04:57.289 So the first thing we did is, 0:04:57.313,0:04:59.998 as soon as the sequences[br]came off the machines, 0:05:00.022,0:05:01.451 we published it to the web. 0:05:01.475,0:05:04.311 We just released it to the whole world[br]and said, "Help us." 0:05:04.335,0:05:05.670 And help came. 0:05:05.694,0:05:06.856 Before we knew it, 0:05:06.880,0:05:09.216 we were being contacted[br]from people all over, 0:05:09.240,0:05:11.684 surprised to see the data[br]out there and released. 0:05:11.708,0:05:13.960 Some of the greatest[br]viral trackers in the world 0:05:13.984,0:05:16.063 were suddenly part of our community. 0:05:16.087,0:05:18.417 We were working together[br]in this virtual way, 0:05:18.441,0:05:21.422 sharing, regular calls, communications, 0:05:21.446,0:05:24.197 trying to follow the virus[br]minute by minute, 0:05:24.221,0:05:26.442 to see ways that we could stop it. 0:05:27.027,0:05:30.785 And there are so many ways[br]that we can form communities like that. 0:05:31.182,0:05:35.507 Everybody, particularly when the outbreak[br]started to expand globally, 0:05:35.531,0:05:39.121 was reaching out to learn,[br]to participate, to engage. 0:05:39.788,0:05:41.382 Everybody wants to play a part. 0:05:41.406,0:05:44.186 The amount of human capacity[br]out there is just amazing, 0:05:44.210,0:05:45.933 and the Internet connects us all. 0:05:45.957,0:05:49.208 And could you imagine that instead[br]of being frightened of each other, 0:05:49.232,0:05:51.089 that we all just said, "Let's do this. 0:05:51.113,0:05:53.636 Let's work together,[br]and let's make this happen." 0:05:53.660,0:05:56.402 But the problem is that the data[br]that all of us are using, 0:05:56.426,0:06:00.463 Googling on the web, is just too limited[br]to do what we need to do. 0:06:00.487,0:06:03.138 And so many opportunities[br]get missed when that happens. 0:06:03.162,0:06:05.643 So in the early part[br]of the epidemic from Kenema, 0:06:05.667,0:06:08.409 we'd had 106 clinical records[br]from patients, 0:06:08.433,0:06:11.267 and we once again made that[br]publicly available to the world. 0:06:11.291,0:06:14.961 And in our own lab, we could show[br]that you could take those 106 records, 0:06:14.985,0:06:18.603 we could train computers to predict[br]the prognosis for Ebola patients 0:06:18.627,0:06:20.404 to near 100 percent accuracy. 0:06:20.428,0:06:22.525 And we made an app[br]that could release that, 0:06:22.549,0:06:25.319 to make that available[br]to health-care workers in the field. 0:06:25.343,0:06:28.602 But 106 is just not enough[br]to make it powerful, 0:06:28.626,0:06:29.777 to validate it. 0:06:29.801,0:06:32.455 So we were waiting for more data[br]to release that. 0:06:32.479,0:06:34.523 and the data has still not come. 0:06:34.547,0:06:37.079 We are still waiting, tweaking away, 0:06:37.103,0:06:39.941 in silos rather than working together. 0:06:39.965,0:06:42.197 And this just -- we can't accept that. 0:06:42.221,0:06:46.025 Right? You, all of you,[br]cannot accept that. 0:06:46.049,0:06:47.731 It's our lives on the line. 0:06:47.755,0:06:49.466 And in fact, actually, 0:06:49.490,0:06:52.033 many lives were lost,[br]many health-care workers, 0:06:52.057,0:06:53.951 including beloved colleagues of mine, 0:06:53.975,0:06:57.722 five colleagues:[br]Mbalu Fonnie, Alex Moigboi, 0:06:57.746,0:07:01.757 Dr. Humarr Khan, Alice Kovoma[br]and Mohamed Fullah. 0:07:01.781,0:07:04.307 These are just five[br]of many health-care workers 0:07:04.331,0:07:06.095 at Kenema and beyond 0:07:06.119,0:07:09.155 that died while the world waited[br]and while we all worked, 0:07:09.179,0:07:11.039 quietly and separately. 0:07:11.063,0:07:13.096 See, Ebola, like all threats to humanity, 0:07:13.120,0:07:17.004 it's fueled by mistrust[br]and distraction and division. 0:07:17.028,0:07:20.801 When we build barriers amongst ourselves[br]and we fight amongst ourselves, 0:07:20.825,0:07:22.645 the virus thrives. 0:07:22.669,0:07:24.461 But unlike all threats to humanity, 0:07:24.485,0:07:27.131 Ebola is one where[br]we're actually all the same. 0:07:27.155,0:07:29.035 We're all in this fight together. 0:07:29.059,0:07:31.693 Ebola on one person's doorstep[br]could soon be on ours. 0:07:32.177,0:07:34.979 And so in this place[br]with the same vulnerabilities, 0:07:35.003,0:07:37.416 the same strengths,[br]the same fears, the same hopes, 0:07:37.440,0:07:40.649 I hope that we work together with joy. 0:07:42.427,0:07:45.497 A graduate student of mine[br]was reading a book about Sierra Leone, 0:07:45.521,0:07:47.855 and she discovered that the word "Kenema," 0:07:47.879,0:07:51.322 the hospital that we work at and the city[br]where we work in Sierra Leone, 0:07:51.346,0:07:55.527 is named after the Mende word[br]for "clear like a river, translucent 0:07:55.551,0:07:57.138 and open to the public gaze." 0:07:57.439,0:07:58.984 That was really profound for us, 0:07:59.008,0:08:01.102 because without knowing it,[br]we'd always felt 0:08:01.126,0:08:04.310 that in order to honor the individuals[br]in Kenema where we worked, 0:08:04.334,0:08:08.621 we had to work openly, we had to share[br]and we had to work together. 0:08:09.074,0:08:10.251 And we have to do that. 0:08:10.275,0:08:14.036 We all have to demand that[br]of ourselves and others -- 0:08:14.060,0:08:16.934 to be open to each other[br]when an outbreak happens, 0:08:16.958,0:08:18.608 to fight in this fight together. 0:08:18.632,0:08:21.541 Because this is not the first[br]outbreak of Ebola, 0:08:21.565,0:08:23.013 it will not be the last, 0:08:23.037,0:08:26.192 and there are many other microbes[br]out there that are lying in wait, 0:08:26.216,0:08:27.641 like Lassa virus and others. 0:08:27.665,0:08:29.174 And the next time this happens, 0:08:29.198,0:08:32.394 it could happen in a city of millions,[br]it could start there. 0:08:32.418,0:08:35.117 It could be something[br]that's transmitted through the air. 0:08:35.141,0:08:37.288 It could even be[br]disseminated intentionally. 0:08:37.312,0:08:40.293 And I know that that is frightening,[br]I understand that, 0:08:40.317,0:08:42.971 but I know also,[br]and this experience shows us, 0:08:42.995,0:08:46.315 that we have the technology[br]and we have the capacity 0:08:46.339,0:08:47.934 to win this thing, 0:08:47.958,0:08:50.804 to win this and have[br]the upper hand over viruses. 0:08:50.828,0:08:53.100 But we can only do it if we do it together 0:08:53.124,0:08:54.321 and we do it with joy. 0:08:54.871,0:08:56.392 So for Dr. Khan 0:08:56.416,0:09:00.582 and for all of those who sacrificed[br]their lives on the front lines 0:09:00.606,0:09:03.006 in this fight with us always, 0:09:03.030,0:09:05.837 let us be in this fight with them always. 0:09:05.861,0:09:07.736 And let us not let the world be defined 0:09:07.760,0:09:09.879 by the destruction wrought by one virus, 0:09:09.903,0:09:12.684 but illuminated by billions[br]of hearts and minds 0:09:12.708,0:09:13.916 working in unity. 0:09:13.940,0:09:15.114 Thank you. 0:09:15.138,0:09:22.007 (Applause)