WEBVTT - What Israel Can Teach Us

0:00:04.280 --> 0:00:08.840
<v Speaker 1>Welcome to Prognosis. I'm Laura Carlson. It's day three hundred

0:00:08.880 --> 0:00:12.840
<v Speaker 1>and sixty two since coronavirus was declared a global pandemic.

0:00:13.720 --> 0:00:17.520
<v Speaker 1>Today's main story Israel has been a model for how

0:00:17.560 --> 0:00:21.800
<v Speaker 1>to quickly vaccinate millions of people. Now the country has

0:00:21.840 --> 0:00:24.360
<v Speaker 1>come out with one of the best studies yet on

0:00:24.440 --> 0:00:29.520
<v Speaker 1>the effectiveness of the vaccine, and the news is very good.

0:00:30.840 --> 0:00:49.159
<v Speaker 1>But first, here's what happened in virus news today. The

0:00:49.280 --> 0:00:52.880
<v Speaker 1>US Centers for Disease Control and Prevention is finally letting

0:00:52.920 --> 0:00:56.040
<v Speaker 1>people know what they can and can't do after they've

0:00:56.080 --> 0:01:01.080
<v Speaker 1>been vaccinated. According to new CDC guidelines, innoculated people can

0:01:01.200 --> 0:01:05.240
<v Speaker 1>visit indoors without masks, but must still wear them in

0:01:05.319 --> 0:01:10.320
<v Speaker 1>public and avoid large gatherings around unvaccinated or vulnerable people.

0:01:12.120 --> 0:01:16.160
<v Speaker 1>Germany will drastically speed up its vaccination campaign to as

0:01:16.160 --> 0:01:20.760
<v Speaker 1>many as ten million weekly inoculations by late March. The

0:01:20.760 --> 0:01:24.560
<v Speaker 1>country's finance ministers set on German television that in April,

0:01:24.800 --> 0:01:28.920
<v Speaker 1>May and June, vaccination centers and doctors will have to

0:01:29.000 --> 0:01:34.200
<v Speaker 1>handle millions of doses every week. Germany has administered a

0:01:34.240 --> 0:01:39.520
<v Speaker 1>total of seven point three three million doses since inoculation

0:01:39.600 --> 0:01:45.759
<v Speaker 1>started ten weeks ago, according to Bloomberg's Vaccine Tracker. Finally,

0:01:46.400 --> 0:01:50.920
<v Speaker 1>India's COVID nineteen vaccination drive has jumped nearly fourfold. After

0:01:50.960 --> 0:01:55.160
<v Speaker 1>a sluggish start, The country's program, one of the world's biggest,

0:01:55.440 --> 0:01:59.200
<v Speaker 1>sped up after it expanded eligibility and got a crucial

0:01:59.240 --> 0:02:03.760
<v Speaker 1>public endorsed it from the inoculation of Prime Minister Norrendra Moody.

0:02:05.280 --> 0:02:08.000
<v Speaker 1>Almost twenty one million shots have been administered in India

0:02:08.080 --> 0:02:11.600
<v Speaker 1>so far, up from five point eight million a month ago,

0:02:11.960 --> 0:02:15.679
<v Speaker 1>according to data compiled as of Monday by Bloomberg and

0:02:15.800 --> 0:02:25.800
<v Speaker 1>Johns Hopkins University and Now for today's main story. Israel

0:02:25.880 --> 0:02:29.359
<v Speaker 1>has had one of the world's most successful vaccination efforts

0:02:29.440 --> 0:02:33.160
<v Speaker 1>yet now a new study from the country shows the

0:02:33.280 --> 0:02:38.880
<v Speaker 1>Fiser vaccine was overwhelmingly effective against the virus. Public health

0:02:38.960 --> 0:02:44.280
<v Speaker 1>experts say the Israeli studies shows that immunizations could end

0:02:44.440 --> 0:02:49.120
<v Speaker 1>the pandemic. Naomi Krasy reports on what makes the Israeli

0:02:49.200 --> 0:02:53.120
<v Speaker 1>study so significant and why at might point to an

0:02:53.120 --> 0:03:19.920
<v Speaker 1>eventual way out of the pandemic. Art These are the

0:03:19.960 --> 0:03:24.200
<v Speaker 1>sounds of a busy vaccination center in Israel. Early this month,

0:03:25.120 --> 0:03:30.880
<v Speaker 1>the country's inoculation campaign started on December. By now more

0:03:30.919 --> 0:03:33.760
<v Speaker 1>than half its nine million residents have had at least

0:03:33.760 --> 0:03:38.160
<v Speaker 1>a first dose, largely of the Messenger RNA vaccine developed

0:03:38.160 --> 0:03:42.080
<v Speaker 1>by Fiser and its German partner by On Tech. That's

0:03:42.120 --> 0:03:45.560
<v Speaker 1>the highest COVID vaccination rate in the world. And as

0:03:45.640 --> 0:03:48.360
<v Speaker 1>part of a deal for quick vaccine shipments that Israeli

0:03:48.480 --> 0:03:52.720
<v Speaker 1>Prime Minister Benjamin Netanyah, who made with Fiser, he agreed

0:03:52.760 --> 0:03:57.480
<v Speaker 1>to share the data on the real world results. Netanyah

0:03:57.520 --> 0:04:00.680
<v Speaker 1>who explained the project at a World Economic Forum meeting

0:04:00.800 --> 0:04:04.040
<v Speaker 1>in January, and we offered to share that with Fiser

0:04:04.400 --> 0:04:08.560
<v Speaker 1>and with all humanity to understand what the effects of

0:04:09.120 --> 0:04:12.680
<v Speaker 1>mass inoculations are. The most important thing, I think the

0:04:12.720 --> 0:04:18.520
<v Speaker 1>most pressing thing is the question of what real degree

0:04:19.520 --> 0:04:24.599
<v Speaker 1>not only of personal protection you get from vaccines, but

0:04:24.800 --> 0:04:29.839
<v Speaker 1>what is the level of preventing infections when you receive

0:04:29.960 --> 0:04:34.640
<v Speaker 1>the inoculation. That's critical question obviously, as you want to

0:04:34.640 --> 0:04:38.080
<v Speaker 1>open the economy and restore life to normal. Netania Who's

0:04:38.160 --> 0:04:43.080
<v Speaker 1>deal vaccines for data, did raise some questions within Israel

0:04:43.200 --> 0:04:48.680
<v Speaker 1>about safeguarding patient information, but the country is uniquely positioned

0:04:48.760 --> 0:04:53.360
<v Speaker 1>for this type of experiment. Four large HMOs manage its

0:04:53.440 --> 0:04:58.240
<v Speaker 1>universal health care system, and about of citizens have digital

0:04:58.279 --> 0:05:01.359
<v Speaker 1>health records that go back as many as twenty years.

0:05:02.560 --> 0:05:05.680
<v Speaker 1>Ben Rice, who directs the Predictive Medicine Group at the

0:05:05.680 --> 0:05:11.120
<v Speaker 1>Boston Children's Hospital Computational Health Informatics Program and Harvard Medical School,

0:05:11.680 --> 0:05:16.120
<v Speaker 1>told me Israel's system enables radical integration of health data

0:05:16.520 --> 0:05:20.159
<v Speaker 1>into one place. Since d H and MOS in Israel

0:05:20.160 --> 0:05:24.720
<v Speaker 1>provide the healthcare, provide the vaccination services, and the coronavirus

0:05:24.760 --> 0:05:28.039
<v Speaker 1>testing services, all this data could be integrated into one

0:05:28.120 --> 0:05:33.200
<v Speaker 1>anonymized record to track the real effects of vaccines. Researchers

0:05:33.279 --> 0:05:37.359
<v Speaker 1>needed to use this extremely detailed data on a massive scale.

0:05:38.279 --> 0:05:41.680
<v Speaker 1>Rice and a team of other researchers from Harvard and Klalite,

0:05:41.880 --> 0:05:45.200
<v Speaker 1>the policy arm of Israel's biggest HMO, set out to

0:05:45.200 --> 0:05:53.440
<v Speaker 1>solve the problem. Fiser wasn't involved with their project. So

0:05:53.520 --> 0:05:56.440
<v Speaker 1>in order to conduct such a study, you need a

0:05:56.520 --> 0:06:01.320
<v Speaker 1>very specific set of circumstances that will happen. It's Noah Taken,

0:06:01.480 --> 0:06:05.039
<v Speaker 1>director of Data and AI driven Medicine at Kluit and

0:06:05.080 --> 0:06:07.800
<v Speaker 1>one of the lead researchers on the study. First, you

0:06:07.880 --> 0:06:11.719
<v Speaker 1>have to have information about a community based cohort of

0:06:11.720 --> 0:06:17.720
<v Speaker 1>individuals for which you know all background medical information, and

0:06:17.760 --> 0:06:19.840
<v Speaker 1>for the same cohort of individuals, you need to know

0:06:19.960 --> 0:06:22.960
<v Speaker 1>several things. You need to know which of these are

0:06:23.040 --> 0:06:27.440
<v Speaker 1>being tested for COVID nineteen, the PCR results. You'll have

0:06:27.520 --> 0:06:30.800
<v Speaker 1>to know the results of those tests. You have to

0:06:30.839 --> 0:06:35.479
<v Speaker 1>know who got vaccinated at at what date, and you

0:06:35.600 --> 0:06:37.720
<v Speaker 1>have to know what happened to them. And that means

0:06:37.760 --> 0:06:40.839
<v Speaker 1>that you have to have an integrated data source that

0:06:40.920 --> 0:06:45.720
<v Speaker 1>takes all of these different resources together, because usually hospital

0:06:45.800 --> 0:06:50.160
<v Speaker 1>data is collected in one electronical medical record, and laboratory

0:06:50.200 --> 0:06:54.120
<v Speaker 1>results are collected in another setting, and the community electronical

0:06:54.360 --> 0:06:57.400
<v Speaker 1>medical record is the third setting, and all these together

0:06:57.560 --> 0:07:00.120
<v Speaker 1>are needed in order to do that. In Israel, the

0:07:00.160 --> 0:07:04.160
<v Speaker 1>Ministry of Health created a reporting system that asks everyone

0:07:04.200 --> 0:07:08.760
<v Speaker 1>to record COVID nineteen test results, hospitalizations, and degrees of

0:07:08.880 --> 0:07:13.360
<v Speaker 1>severity of hospitalization. That gave Noah and the team two

0:07:13.480 --> 0:07:16.720
<v Speaker 1>data sets to work with, the h m MOS decades

0:07:16.760 --> 0:07:21.760
<v Speaker 1>of health data and the government's detailed pandemic data. And

0:07:22.000 --> 0:07:25.120
<v Speaker 1>when we cross these two resources together, we can actually

0:07:25.160 --> 0:07:28.520
<v Speaker 1>know where each patient is and what happened to them

0:07:28.720 --> 0:07:31.600
<v Speaker 1>in order to tell how well the vaccine was working.

0:07:32.000 --> 0:07:35.960
<v Speaker 1>The team needed as unbiased a comparison between the vaccinated

0:07:36.280 --> 0:07:40.679
<v Speaker 1>and unvaccinated as possible. They needed to match up each

0:07:40.720 --> 0:07:45.400
<v Speaker 1>inoculated person with someone as similar as possible who hadn't

0:07:45.480 --> 0:07:49.280
<v Speaker 1>yet gotten a shot. So as an example, for you,

0:07:49.400 --> 0:07:52.320
<v Speaker 1>to be matched in the study, you have to find

0:07:52.320 --> 0:07:55.360
<v Speaker 1>someone was very similar to you. So a seventies six

0:07:55.480 --> 0:08:00.280
<v Speaker 1>year old ultra Orthodox Jewish male from specific neighborhoods from

0:08:00.280 --> 0:08:03.640
<v Speaker 1>Tel Aviv who received four influenza vaccines in the last

0:08:03.680 --> 0:08:06.680
<v Speaker 1>five years and has two common abilities that are known

0:08:06.760 --> 0:08:09.960
<v Speaker 1>risk factors for severe corby nineteen will only be matched

0:08:09.960 --> 0:08:12.680
<v Speaker 1>in the study if we can find a similar ultra

0:08:12.840 --> 0:08:16.840
<v Speaker 1>Orthodox Jewish mail from the same neighborhood who's aged seventy

0:08:16.920 --> 0:08:19.760
<v Speaker 1>six to seventy seven years and received three to four

0:08:19.800 --> 0:08:25.160
<v Speaker 1>influenza vaccine and has two common abilities. It was a

0:08:25.160 --> 0:08:30.760
<v Speaker 1>computing challenge. Every day from December twentie to February one,

0:08:30.920 --> 0:08:36.240
<v Speaker 1>the team matched each newly vaccinated person with an unvaccinated control.

0:08:36.679 --> 0:08:39.440
<v Speaker 1>So I can tell you that the first iteration of

0:08:39.520 --> 0:08:43.320
<v Speaker 1>code that we've written took four or five days just

0:08:43.400 --> 0:08:46.600
<v Speaker 1>to run to run it, not to write it. And

0:08:46.640 --> 0:08:50.120
<v Speaker 1>we wrote that piece of code in different languages and

0:08:50.160 --> 0:08:54.720
<v Speaker 1>with different algorithms again and again until if we reduced

0:08:54.720 --> 0:08:58.000
<v Speaker 1>the running times from five days to one day, and

0:08:58.040 --> 0:09:00.760
<v Speaker 1>from one day to four or five hours, and in

0:09:00.800 --> 0:09:03.760
<v Speaker 1>the final version to ten or fifteen minutes, and that

0:09:03.760 --> 0:09:06.120
<v Speaker 1>that's the current version that we're using now, and we

0:09:06.160 --> 0:09:09.160
<v Speaker 1>are rerunning every few days to see what what's the

0:09:09.200 --> 0:09:14.280
<v Speaker 1>status with the information that is gradually building. Ultimately, the

0:09:14.320 --> 0:09:18.520
<v Speaker 1>team was able to compare five hundred and ninety six thousand,

0:09:18.600 --> 0:09:24.120
<v Speaker 1>six hundred and eighteen people vaccinated between December and February

0:09:24.280 --> 0:09:29.800
<v Speaker 1>one with their unvaccinated counterparts added together almost one point

0:09:29.840 --> 0:09:34.880
<v Speaker 1>two million people in all. Published on February in the

0:09:34.880 --> 0:09:39.199
<v Speaker 1>New England Journal of Medicine, their results were overwhelmingly positive.

0:09:40.000 --> 0:09:45.720
<v Speaker 1>Two doses of the vaccine prevented of symptomatic COVID nineteen cases.

0:09:46.679 --> 0:09:49.960
<v Speaker 1>Once the team counted people who hadn't had symptoms but

0:09:50.080 --> 0:09:54.120
<v Speaker 1>tested positive for the virus anyway, they found two doses

0:09:54.200 --> 0:10:00.079
<v Speaker 1>prevented of the documented infections, and importantly, it showed the

0:10:00.160 --> 0:10:04.000
<v Speaker 1>vaccine was also extremely effective for people who are older

0:10:04.480 --> 0:10:08.960
<v Speaker 1>or who have other diseases. Here's Ron Ballaser, director of

0:10:09.000 --> 0:10:13.160
<v Speaker 1>health policy planning for Klalite, and we've been able to

0:10:13.200 --> 0:10:16.720
<v Speaker 1>demonstrate that the vaccine is exceedingly effective as it was

0:10:16.760 --> 0:10:20.439
<v Speaker 1>in the clinical trial. This study that was performed in

0:10:20.480 --> 0:10:23.920
<v Speaker 1>Israel at Kalite, would be able to demonstrate for decision

0:10:23.920 --> 0:10:27.960
<v Speaker 1>makers and the public worldwide that mass vaccination campaigns have

0:10:28.080 --> 0:10:32.840
<v Speaker 1>a huge potential in controlling the illness globally, as well

0:10:32.880 --> 0:10:37.839
<v Speaker 1>as curbing the detrimental impact of disease dissemination on human lives.

0:10:38.520 --> 0:10:41.280
<v Speaker 1>Ron told me that he hopes at some point the

0:10:41.360 --> 0:10:44.800
<v Speaker 1>study won't be able to continue because they'll run out

0:10:44.840 --> 0:10:49.640
<v Speaker 1>of unvaccinated people to use as control comparisons, But for now,

0:10:50.040 --> 0:10:54.559
<v Speaker 1>the team is continuing as their study population grows. They

0:10:54.600 --> 0:10:57.880
<v Speaker 1>hope to answer questions about how specific groups of people

0:10:58.000 --> 0:11:02.000
<v Speaker 1>respond to the vaccine and help CLAD and other health

0:11:02.040 --> 0:11:06.959
<v Speaker 1>providers know how to handle COVID nineteen immunizations for those groups.

0:11:08.040 --> 0:11:11.319
<v Speaker 1>Here's no one part of clear It's head of epidemiology

0:11:11.320 --> 0:11:16.960
<v Speaker 1>and research, so we constantly gather data so we have

0:11:17.080 --> 0:11:22.280
<v Speaker 1>the biggest possible result pool with which to to inform

0:11:22.360 --> 0:11:26.560
<v Speaker 1>decisions within the organization. Also for subgroups. So for example,

0:11:26.559 --> 0:11:30.959
<v Speaker 1>what we do have a huge sympathize for the overall population,

0:11:31.440 --> 0:11:34.439
<v Speaker 1>maybe we specifically want to know what is happening with

0:11:34.640 --> 0:11:37.880
<v Speaker 1>people who are immuno compromise with people who have certain

0:11:38.160 --> 0:11:42.160
<v Speaker 1>remote with conditions. So we do continue to gather these

0:11:42.280 --> 0:11:47.240
<v Speaker 1>data daily to have better and better hands. But for now,

0:11:47.760 --> 0:11:51.119
<v Speaker 1>at the end of this long dark winter of seemingly

0:11:51.440 --> 0:11:56.520
<v Speaker 1>unending pandemic anxiety, we were finally given something really solid

0:11:56.679 --> 0:12:01.040
<v Speaker 1>to cheer about, real world evidence that the vaccine is

0:12:01.120 --> 0:12:05.600
<v Speaker 1>working and perhaps even better than people thought, because it

0:12:05.640 --> 0:12:09.520
<v Speaker 1>seems to prevent not just infection with COVID, but also

0:12:09.600 --> 0:12:22.920
<v Speaker 1>transmission of the virus. That was Naomi Kraski. And that's

0:12:22.960 --> 0:12:24.959
<v Speaker 1>it for our show. To day for coverage of the

0:12:25.000 --> 0:12:28.360
<v Speaker 1>outbreak from one and twenty bureaus across the world, visit

0:12:28.400 --> 0:12:33.120
<v Speaker 1>Bloomberg dot com slash coronavirus and if you like the show,

0:12:33.360 --> 0:12:35.640
<v Speaker 1>please leave us a review and a rating on Apple

0:12:35.720 --> 0:12:38.839
<v Speaker 1>Podcasts or Spotify. It's the best way to help more

0:12:38.920 --> 0:12:43.400
<v Speaker 1>listeners find our global reporting. The Prognosis Daily edition is

0:12:43.400 --> 0:12:48.000
<v Speaker 1>produced by Tophor foreheads Magnus Henrickson and me Laura Carlson.

0:12:48.600 --> 0:12:53.079
<v Speaker 1>Today's main story was reported by Naomi Kresky. Original music

0:12:53.080 --> 0:12:57.000
<v Speaker 1>by Leo Cedrin. Our editors are Rick Shine and Francesca Levi.

0:12:57.600 --> 0:13:02.080
<v Speaker 1>Francesco Levi is Bloomberg's head of punk casts. Thanks for listening.