Over 200 papers on COVID-19 are published every day! In this episode we chat with Emily Nelson, PhD, about her work on the COVID-19 Literature Surveillance Team (COVID LST), a group of 50 individuals who are collecting, annotating, and summarizing the daily deluge of papers. Emily’s work with COVID LST uniquely positions her to give us a 20,000-feet view of trends in the literature, including what the science is telling us (and not telling us) about serology test development, whether we can get COVID-19 twice, and potential treatments on the horizon.
Returning champion Xueting Qiu tells us about the newest findings from analyzing 10,000+ SARS-CoV-2 genomes. We discuss what the genomes tell us about the origins and spread of the outbreak across the US, how fast the virus is mutating, whether different ‘strains’ of the virus exist, and – the question on everyone’s mind – how we can reopen the country.
How many viral genomes have been sequenced at this point and what is their geographic distribution?
As of 4/17, we have had more than 10,000 sequences deposited in the GISAID database. By country, so far the US has submitted the most. But generally by region, most of data is from Europe, North America, East Asia and Australia.
It is amazing how fast the data have been generated. Two weeks ago, it was only about 4,500 sequences deposited in the database.
What have the genetics taught us about how the virus got to the United States?
Genomic comparative analysis is a great resource to infer viral sources – it can tell you the viral origins from what hosts or from where. Since the virus spreading is now dominated by human hosts, let’s focus on the geographic spreading here. To answer how the virus got to the US: if you check Nextstrain (https://nextstrain.org/ncov/global) which is a nearly real-time tracking platform, we will see the transmissions are globally connected. When we zoom in to see the introductions into the US, we see that there were multiple introductions driving the US epidemic and the earliest was in January. There were multiple paths the virus took to reach the US. There was a direct introduction from China that occurred in late January and there were multiple introductions from the European epidemic that occurred during the course of February.
What have the genetics taught us about how the virus is spreading within the United States?
Last time, we talked about the story in the Washington state. Even before we started massive testing, based on the first two sequences in Washington, we inferred the viral transmissions have been local community transmission for weeks. With more retrospective epidemiological data from Seattle Flu Study, now the inference is confirmed.
In Washington state, about 5,000 new cases were diagnosed in March, most of them are the descendants of the first Washington case based on the genomic data. We later then have found its descendants in New York, California, Connecticut, Minnesota, and Wisconsin, some of the few states to publish viral genome sequences so far. It also spreads to other global regions. The connection by air flights nowadays makes the viral transmission easily a global problem.
What is the genome size of SARS-CoV-2? How many genes does it have and what are the function of a few of the most important ones?
The full length of the SARS-CoV-2 is about 30,000 nucleotides, one of the largest genome among RNA viruses. It is a non-segmented genome, which encodes at least 12 functional proteins. Among these, the important ones are the surface proteins, for example, the spike glycoprotein. The name describes how it looks – they are the spikes on the surface of the virus. For viral functions, it contains the receptor-binding domain, which helps the virus enters human cell and initiates the infection. For human immune response, it contains important antigens to stimulate the immune system in human body. That is, they are important for vaccine design.
How quickly is the virus mutating? Are these results in keeping with the original estimates?
The substitution rate is 0.75 x 10-3 substitutions per site per year, about 24 substitutions per year or 2 substitutions per month for the whole genome, along a transmission chain. It is slower than the original estimates (0.92 x 10-3 substitutions/site/year). This is normal as more data are available. It doesn’t mean the virus mutates slower – it is just the reduction on the uncertainty with more data and longer time period of the samples.
Where in the genome are the mutations occurring?
Not evenly. There are some hotspots in different genes. It may be related to the functions of the protein and different region of the protein is under different selection pressure.
A lot of attention has been paid to different “strains” of SARS-CoV-2 in the media. What does it mean to be a different “strain”?
A strain is a genetic variant or subtype of a microorganism. “Strain” is unfortunately an overloaded scientific term. Here we have to differentiate the concepts of strain vs genetic variant.
In many circumstances, every unique viral genome will be counted as a separate strain. If we use this criteria then we’ve seen thousands of “strains” out of these available SARS-CoV-2 genomes currently. But almost all of the changes in the genome will do very little to affect viral function. So, I would more prefer to call this situation as genetic variants here.
Another definition of strain is defined as a functionally distinct virus genotype. What’s very tricky is that we can’t know without doing experiments if one genetic variant behaves differently than another, especially when there’s only a small handful of genetic changes between them. For example, there have been only 11 mutations to proteins that are widely distributed. These are *potentially* functionally distinct variants that deserve attention and experimental and clinical follow up. This could be studied via cross-neutralization assays to see if sera from recovered individuals respond differently to these two variants.
Use flu as a more mature example: think about H3N2 – each season, we have to change the vaccine strain. It is because the genetic drift is causing substantial antigenic change. (In other words, genetic variation in viruses accumulate in the virus genes that code for virus-surface proteins that host antibodies recognize.) We can define them into different strains based on the genetic distance and antigenic distance with experiments.
If you get infected with one strain, will you have immunity against the others?
It depends on the cross-reactivity between the strains, that is, how close these strains are. Two main factors can impact how quickly the strains are diverging. One is the viral mutation rate, one is the immune selection pressure in human.
The per-base mutation rate of SARS-CoV-2 compared to influenza is about 2-3 fold slower. Here we see that seasonal coronaviruses may behave similarly to seasonal flu in which frequent mutations to the spike protein (the protein targeted by immunity) are observed. Plus there is not much immune pressure in the population to select the strains. So the herd immunity takes time to establish, it will still take years to have the virus escaped from current immunity.
Are certain strains more lethal or weaker?
We don’t know yet. But I have to say the case fatality rate is more related to other factors when the virus is extremely similar. That is, the death is not solely depending on viral variants: age structure, economic status, living conditions, health education, prevention measures, healthcare system etc. all play a role.
What are the implications of the mutation rate/strains for the development of therapeutics and vaccines?
This is a great question. Like I mentioned previously, this virus evolves slower compared to flu, and there is not much immune pressure to select it currently. we should see occasional mutations to the spike protein of SARS-CoV-2 that allow the virus to partially escape from vaccines or existing “herd” immunity, but that this process will most likely take years rather than months. Below is the estimation of infected proportion in some European countries, so far it is only 0.5-3% of infected, far from the 50% of expected infection to mount herd immunity. So it probably will take the virus a few years to mutate enough to significantly hinder a vaccine. Similarly to therapeutics, the resistance to anti-viral medicine won’t be a concern for a few years.
Is social distancing working?
Yes. From previous evidence in China. Some evidence from a few European countries, like in Germany, Italy, etc. And from the current changes in several states in the US. For example, in King County in Washington state, researchers correlated Facebook mobility data with effective reproduction number ( Re). ( Re or Rt is the real time estimation of secondary infections under some control measures.) We saw that along with the reduced mobility, the Re is reducing as well. So reality and data all tell us that social distancing works. Because we did social distance, we controlled it, so we didn’t see an extreme surge in cases – people may think we over-reacted. But we did not, it works and we have prevented the worse situation.
What are the proposed ideas for reopening the country?
I don’t think anyone has found a good answer. The pandemic is far from done. It is still in a very early stage, since most of the population in the country remains susceptible. The goal of the current set of restrictions is not to solve the problem, but rather to solve the acute problem of keeping the numbers of patients from exceeding health care capacity.
We saw now the shutdown works out well, the 30-day lockdown has saved many, many lives. What we should do next? There is a heavy dilemma here: if we relax restrictions, as we saw in the 1918 pandemic, and as we’ve seen probably in China, Hong Kong, and Singapore now, There’s every reason to expect a resurgence of coronavirus and we’re back in the same problem. On the other hand, keeping these restrictions in place is economically disastrous.
We probably have to try different things – one proposed strategy is to have serological testing – if people have been infected, they will have protective antibodies and they can go back to work. But now I think the serological testing is still more in a research perspective before it is widely used, since we still don’t know much about the immunity to this virus.
Another thing we can try is to do what China is doing. Very cautiously to reopen business, require people to take all the preventive measures – hand hygiene, wearing masks, close borders, and testing, tracing, and quarantine.
I think we should learn about all the successful experiences from different countries and trim it to the proper prevention measures for use locally. We cannot 100% copy one set of measures, but we are learning to use the best to save lives, like social distancing, wearing masks, etc.
At this moment, serological testing is promising, but we don’t know yet. People usually hesitate to admit that they don’t know. But admitting what we don’t know first is thriving ourselves to find the answers.
Xueting Qiu, a molecular epidemiologist at the Harvard T.H. Chan School of Public Health, revisits AATB to talk about the current state of the COVID-19 coronavirus pandemic and why we needed to start social distancing yesterday.
What is the current global state of COVID-19 pandemic?
We are in the middle of viral spreading. It will be continuously spreading for a while. By March 12th, globally we have 125,048 confirmed and 4,613 deaths. Outside of China there are 44,067 confirmed and 1,440 deaths from 117 countries/territories/ areas.
In the middle of February, that is, one month ago, our center director Dr. Marc Lipsitch has said it is very likely that we will see a global pandemic. He also said, if pandemic happens and we don’t take effective controls, considering the R0 is 2, 20%-60% of adults world-wide are likely to be infected in the coming year. The unclear part would be what proportion of those will show symptoms.
Have any countries successfully contained the virus? If so, what were their strategies?
Yes. The effective strategies are: early testing on large scale of the population + case monitoring + social distancing.
We would cautiously say China has controlled it well at this point, but at a painful cost with lockdown of Wuhan and nearby cities, and also performing extremely strong social distancing. This experience may not be flexible for other countries to learn. But we know under the outbreak, it may happen for other countries, like Italy has also locked-down the whole country at this point.
Here, I will give the example of the most successful country – Singapore. What have they been doing? Singapore enjoys an exceptional capacity for high-quality outbreak investigation. It was among the first international locations to report cases of COVID-19 exported from the epicenter of the outbreak in Wuhan, but investigators went further. If you only test people who are connected to known cases, you are just one missed infection from completely losing track of the transmission chain. Understanding this, the Singapore authorities tested cases of respiratory disease that were negative for other viral pathogens, and so potentially the result of COVID-19 transmission chains that had escaped detection. They immediately found 4 cases in early February without known contacts with other cases. Diligent contact tracing has managed to keep a lid on the outbreak and, despite reporting their first case on January 23, to date, the total case number for Singapore is only 110 with no deaths (although seven are in serious condition). This is an exceptional achievement.
What is the current state of the COVID-19 pandemic in the US?
There has been local transmission for a while, though many people still doubt it. Based on the data we saw, the US is on the same trajectory with other countries like South Korea, Italy, and Iran.
We believe local transmissions have been established in many communities in the US. Trevor Bedford [Professor of Genome Sciences and Epidemiology at University of Washington] has conducted genomic analysis which has shown that there has been cryptic transmission in Washington state for the past 6 weeks. This analysis is based on two isolates of COVID-19 from Washington state. The first one (WA1) was an imported case from Wuhan China, from Jan 21st. Then, at the end of February, a second patient from Washington state was sequenced, and this sequence clustered with the first sequence. The first and second sequence share a rare variant (a mutation on site 18060 from the viral genome, which is not present in the majority of viruses in China So you know this is most likely from local transmission in Washington. That is, the first WA1 virus has been spreading in the community for 6 weeks with the same rare variant. And from epidemiological perspective, the rapidly increasing tested case numbers in Washington also tells the same information.
There have been many reports about the CDC bungling the tests for COVID-19. Do you know why there were such difficulties creating the test?
So I can list a few things here to say why it’s been so difficult creating massive testing for this virus:
- The criteria on the eligibility of who can get tested. At the beginning, it was limited to people who have direct travel history to Wuhan, China and have showed symptoms, then later to all regions of China. Only until late of last week, the CDC now allows to test people without travel history or contact tracing. With this, we have been missing all the local transmission and the imported cases from other countries that are under outbreak.
- The flaws on the PCR testing kits. The redesign on the PCR testing kits has flaws. The negative control in the kit doesn’t work, resulting in many false negatives. [Editor’s note: By “false negatives”, Xueting is referring to tests that were unclear and thus no results were reported.] This caused a waste of at least a couple of weeks.
- The regulations on which lab can conduct the tests. This part I think is the main limitation on the testing capacity. So far, only very limited labs and staffs can do the testing run. We totally understand the underlying rationale for federal regulations of diagnostic assays, but it really creates barriers for the possibility of finding new solutions, like using high-throughput research assays for the viral testing.
But now I think the regulation has been lifted and permissions have been given to many other labs. So we may expect a higher testing capacity soon. But it will still take some time. So the limited testing capacity cannot tell the real situation of the outbreak, but we know it is severe.
At this point, is the virus containable in the US? If not, what measures will have to be implemented in order to contain it?
No, we cannot stop it anymore. We have missed the chance for weeks. Like I mentioned previously, we believe local transmissions have been established in many communities in the US. We missed the containment period, but we have to mitigate it.
Now the most important thing for now is to slow down the outbreak. Massive testing is needed. And start social distancing now. The sooner the better. You have heard of “flattening the curve” a lot recently. Why we have to slow down the outbreak? Because of the limited healthcare system capacity.
A crucial thing to understand about the coronavirus threat — and it’s playing out grimly in Italy — is the difference between the total number of people who might get sick and the number who might get sick at the same time. The US has only 2.8 hospital beds per 1,000 people. That’s fewer than in Italy (3.2), China (4.3) and South Korea (12.3), all of which have had struggles. More important, there are only so many intensive care beds and ventilators. The healthcare capacity is directly related to the case fatality in each country. Because overburdening the healthcare capacity has happened in Wuhan China, and is happening now in Italy and Iran. These locations have case fatality rates as 3~5%. But in South Korea, the case fatality is 0.9%, which can be 10 times of difference.
But we can make a difference if we act in a timely manner. Other places that hesitated when action was needed are paying a heavy price. So we have to ACT QUICKLY, and the actions are to PRACTICE BASIC HAND HYGIENE, SOCIAL DISTANCING and REDUCE GATHERING, where efforts can be made by everyone – if you can work from home, do it; if you have upcoming conferences/meetings/parades/social gathering, try to cancel/postpone them; if possible, change church gathering to remote meetings online for the critical time period, etc.
The earlier, the better. Since the outbreak is counted by day, we can change the situation by taking action even one day earlier.
What does the near and far future hold for us? How long will it take to contain this virus and return to business as usual?
It really depends on how fast we act at this critical time. It is very hard to predict when the epidemic will peak and will end. Different places may be at different stages of the outbreak at this point.
But the most important thing is that we have to take action now. Perform good hand hygiene, avoid gathering, and keep social distancing.
We hope this can be ended soon, but it is a pandemic, it will be going for a while. Let’s do what we can do. And let’s hope for the best and prepare for the worst.
Coronavirus, coming to a neighborhood near you! In this episode we interview Xueting Qiu, a molecular epidemiologist at the Harvard T.H. Chan School of Public Health. After a brief recap of your fave viruses, including MERS (camels!), bird flu (poultry!) and COVID19 (bats? pangolins?), we chat about how next-generation sequencing and viral genetics are rapidly shaping our understanding of how COVID19 entered into humans, how it is spreading, and how its genome could affect therapeutics and vaccines.
What is a coronavirus?
Coronaviruses (CoV) are members of a diverse species. It’s single-stranded positive-sense RNA viruses. They can cause respiratory and intestinal infections in humans and also many other animal species. The genome size of coronaviruses ranges from about 26 to 32 kilobases. It’s the largest among known RNA viruses. The name corona is from Latin, meaning “crown” or “halo”. It describes the characteristic appearance of the virus particles under an electron microscope. Coronaviruses have been classified into 4 types – alpha, beta, gamma, delta.
When and where did the nCOV19 outbreak start?
So for this recent novel coronavirus (SARS-CoV-2), it was first detected in Wuhan, China, and has spread rapidly since December 2019. The first cluster of cases were reported at a seafood market in Wuhan. Imported cases and small transmission clusters have been reported globally now. It has reached Europe, North America, Australia and Africa. As of Feb 18, 2020, globally it has caused over 73,000 confirmed infections and about 1,900 deaths.
Overall, about 14% of the illnesses were severe, which included pneumonia and shortness of breath, and about 5% have critical disease, like by respiratory failure, septic shock, and multiple organ failure. Overall, the case fatality rate was 2.3%, and the majority of death cases were in people age 60 and older or those with underlying medical conditions.
What are the major concerns from medical and public health perspective?
Actually, this new coronavirus is not the first time that we saw a coronavirus. There are four seasonal types are associated with mild respiratory symptoms in humans each year – they just cause the common cold. Another two, SARS detected in 2003 and MERS detected in 2012 can cause severe diseases.
So compared to SARS and MERS, the case fatality rate is not as high, but the outbreak scale is way larger than, for example, SARS, so the situation so far is very severe. These official case numbers are likely an underestimate because of limited reporting of mild and asymptomatic cases, and the virus is clearly capable of efficient human-to-human transmission. Based on the possibility of spread to countries with weaker healthcare systems, the World Health Organization (WHO) has declared the COVID-19 outbreak a Public Health Emergency of International Concern.
From the medical perspective, the challenges are the outbreak is right on top of flu season. It overburdens the healthcare system. Plus, there is no effective medication to treat the infections but mostly symptom-related supportive treatment. Antiviral medicines are under development now but the effects have not been well evaluated.
From public health perspective, we are concerned about how many undetected cases, and what the proportion of pre-symptomatic transmission, which will impact the effectiveness of our current control measures. So why is pre-symptomatic transmission so important here? It’s because if a person is infected but has no symptoms and starts shedding the virus and infecting people, it’s very hard to capture that person and control its spread to other people. So far, we don’t know what the proportion of pre-symptomatic transmission which is a key parameter we try to get from epidemiological data.
Nowadays global travels make the containment of outbreak very hard. Infectious diseases from a local place can easily become a global problem. So other challenges are a potential pandemic with no vaccine available. I think public health authorities in countries need to make resources ready for quarantine, contact tracing and other prevention measures.
How many samples have we sequenced of this novel coronavirus; what have we learned from it?
As of February 18, 2020, 119 full genome sequences have been deposited in GISAID (global initiative on sharing all influenza data). Most of them are human isolates (some from China and from other countries as well), some are from environmental samples from the seafood market in Wuhan, some from pangolin.
First with comparative genetic analysis, it quickly identified that the novel virus is a beta-coronavirus that’s genetically close to some SARS-like virus circulating in bats.
One thing about next generation sequencing that is fascinating is that it can recover samples from environmental samples like from soil, water, or from other surfaces from environmental settings. From the sequences of environmental samples in the seafood market, it confirms the initial of the outbreak started there.
Further genomic analysis has tried to evaluate the key parameters of this virus’ evolution like the evolutionary rate or the ancestral time of this outbreak. In the beginning, sequencing data can be noisy, but generally the phylogenetic reconstruction has provided accurate estimations on the viral ancestral time and mutation rates. I have been following two top groups – Andrew Rambaut posts in virological.org and Trever Bedford and Richard Neher developed an interactive and visualization platform called NextStrain.org. They have been updating the analysis with new sequences added in. And similar results are generated from both groups.
The phylogenetic analysis reported limited genetic variation in the currently sampled viruses but more recent ones are showing more divergence as is expected for fast evolving RNA viruses. But the lack of diversity is indicative of a relatively recent common ancestor for all these viruses.
How has genetics informed our understanding of the animal reservoir and how it got into humans?
This is an important question because different scenarios need different control measures. If the situation is multiple introductions from animal reservoir, controlling the animal viral sources are critical to stop transmission. That’s what happened for the avian influenza H7N9 in 2013 in Shanghai, China. That was due to multiple introductions from poultry population to humans. So you have to stop the close contact between poultry and humans. So that time, people closed all the live poultry markets in Shanghai and surrounding areas. People stopped the contact at the interface with the host and the outbreak was rapidly controlled at that time. But, if it is single introduction from animal reservoir, then the animal viral source won’t be a big concern at this point and we can focus on the human transmission control.
The analysis showed that the lack of genetic diversity in human viral samples of this novel coronavirus support one single introduction from animal reservoir into the human population. Because after the initial zoonotic event, the genome sequence data shows no evidence that any non-human animal reservoir has been involved in generating new cases since January. If cases in January had been the result of new zoonotic jumps from a reservoir, we would expect more genetic diversity in our data. But so far that’s not the situation so it supports one single introduction from animal reservoir into human population.
We don’t know how exactly it got into humans yet. Some coronaviruses from bats and pangolin have high similarity with the novel coronavirus. But this virus may still have one or more other non-human animal species host. We don’t know at this point because we don’t have samples from other animals yet. With more surveillance and genetic data, we may be able to reconstruct the transmission chains among animal species and from which host it jumps to humans.
But with this discovery at an early stage of the outbreak, to control the outbreak, we wont worry much at this point about the viral sources from animals. But use resources to control transmissions only among humans.
Why is it important to understand the evolutionary rate of a virus?
Generally, people are scared about mutation. Especially with new, emerging viruses, people imagine – oh, it must be evolving so fast, it will cause high case fatality and severe outcomes. So that’s why we need to know exactly how fast a new virus will evolve. We have plenty of data to do this estimation. So far the estimated evolutionary rate for the novel coronavirus is about 0.92 * 10-3 mutation/basepair/year (95% CI 0.33×10-3 – 1.46×10-3 ). So that’s not as fast as people imagine, and it’s actually similar to the mutation rates of other coronaviruses. And it’s at least 3 to 5 times slower than the flu virus.
What are other advantages of genomic data during the early stage of an emerging outbreak?
Genomic data has only been used for infectious disease in the recent decade, because next generation sequencing became commercialized since 2005. It’s been new that we can have such rapid generation of viral sequences. And it does provide a lot of advantages during early stages of an emerging outbreak. It can provide estimation on some critical parameters to estimate the situation of the outbreak. For example, for this coronavirus outbreak, we have been providing an estimation on R0 – the basic reproductive number, which is the average number of secondary cases that get infected from the index case. Another parameter is the doubling time, the time it takes for the population to double in size. So basically the larger the R0 and the smaller the doubling time, the faster the disease will spread and the harder to contain the outbreak.
The traditional way to estimate these parameters uses epidemiological data and tracking information, which takes a lot of effort and it’s slow and we usually cannot get that data until very late in the outbreak. But with genomic data now, we can estimate the viral ancestral time and consider it as the start of the outbreak. So now you have a time point and then you have some of the cases. And even if it’s not perfect – you don’t have all the cases or who infected who – you don’t have to know the exact epidemiological information and you can estimate these parameters based on the ancestral time and exponential growth of the virus. That’s how we get early estimation from genomic data on R0 and also doubling time.
How has the scientific efforts around understanding this virus differed from previous epidemics like SARs, etc.?
Compared to SARS in 2003, this time we have relatively rapid response, and scientific efforts for this outbreak have been in great shape. For this outbreak, the data sharing is rapid and data collection is better – with more information, more epidemiological information, more records, shared online, on twitter; people organizing it, people translating it into English immediately. It’s almost real time sharing of data. The rapid identification of the virus is remarkable. For SARS, it took a few months before the data was shared and the global efforts was made after a few months after the outbreak. Another thing is the reviewing process from journals to make the information available to the public is more rapid because journals are making efforts to process papers faster than before.
Are people using the sequencing data to inform vaccine discovery?
For other pathogen, like influenza, people are using sequence data to design more broadly protective vaccines. But for the novel coronavirus, I am not so sure whether people are using sequencing data or not, but I know there are 4 ongoing projects of vaccine design, but we don’t know when it will come out and whether it’s effective or not.
Where do we go from here? What else should we be monitoring and preparing for?
First, we should continue the current prevention strategies until more findings provide other effective measures. Watch the global spread and be ready for the potential of outbreak, especially in areas with stretched health care systems. Like mentioned before, the proportion of pre-symptomatic transmissions or no-symptomatic infections is critical and they should be estimated as we can. If It is likely to be pandemic, based on R0 and the progress of the epidemic, we think it may infect more than half of the population.
For long term prevention of future potential emerging virus, we need to understand the virus origins clearly. So identifying the immediate non-human animal source and obtaining virus sequences from it would be the most definitive way. So the ongoing surveillance of pneumonia in humans and other animals is very important.
Any final takeaways from this outbreak so we can prepare for the future?
The history of human is also a history of fighting infectious diseases. Emerging diseases are unpredictable. We don’t know when it will happen again but we know it will definitely happen again. So we have to learn the most from this one to get ready for future outbreak response. The key point is time – the earlier with professional response, the better containment of the outbreak. We need more investment in resource preparation or training experts. It is necessary to have in place ahead of time sufficient funding and standard protocols for both the collection of samples and the accurate recording and archiving of associated epidemiological data and to ensure patient privacy. To be able to use better tools including real-time sequencing technologies is also critical.
Another thing concerns me a lot is that misinformation regarding the coronavirus outbreak on social media is spreading crazily in the middle of the viral epidemic. It causes panic. But what we need the most is resource and information, not panic. Being scared is useless, being educated and being able to pick reliable information sources to follow are better choices to do. I would recommend to follow people from our center, for example Marc Lipsitch, Coraline Buckee, Bill Hanage and Michael Mina, and also experts like Andrew Rambaut and Trever Bedford, as well as Ben Cowling and Joseph Wu in Hong Kong.
I surely believe we will control the outbreak with great efforts together, but the important things are how we can reduce the harm and protect more people during the outbreak, how we can consider more humanity and safety for those individuals while implementing control measures, and how we can learn more from this experience and do better in the future.
Do we need a Bernie Sanders or AOC for academia? We tackle this question with Yarden Katz, a departmental fellow in Systems Biology at Harvard Medical School, who has written about how the politics and culture of academia influence the scientific questions we pursue. We discuss how intellectual property laws reshaped university and scientific priorities, whether this incentive structure has in fact led to more innovation, and what the barriers are to changing a system that no one is really satisfied with.
Track art by the always talented Caroline Hu.
Genetics field trip! In this episode we hopped in Jenny’s car and headed to Vertex Pharmaceuticals where we spoke with Chief Scientific Officer, David Altschuler. Previously, as a core member of the Broad Institute, David’s academic research focused on using human population genetics to identify therapeutic targets for complex diseases. In our conversation, David tells us about his transition into industry and how his former research strategy now informs his scientific vision at Vertex Pharmaceuticals.
Decisions, decisions, decisions. Clare Malone, a postdoctoral fellow studying the genetics of neuroblastoma, is currently undecided about whether to apply to faculty positions or for jobs in industry. We talk through it all: her thoughts on money, morals, mentors, and the hidden work of being a female PI.
What would happen if everyone got their genome sequenced? This question is no longer the stuff of science fiction. Instead, it is a research question that Senior Genetic Counselor Carrie Blout and her colleagues at the Genomes2People initiative at Brigham and Women’s hospital are trying to answer. We discuss the medical, psychological, and economic impact of whole genome sequencing, the rollout of a new preventative genomics clinic at Brigham and Women’s, and the future of genomic medicine.
“PhDs are hard”. We all heard this when we were deciding to apply to PhD programs, but even after completing one it is difficult to articulate why a PhD is difficult. In this episode we tackle this question with Nyssa Boardman, a clinical psychologist who works with graduate students at Harvard’s Counseling and Mental Health Services. In our interview we discuss the “five-year itch”, becoming your work, how to spot a breakdown, and what Nyssa would say if she had all PhD advisors in a room.
If you have noticed persistent changes in your sleep, eating, mood, or energy level — or even if you are just feeling overwhelmed — make an appointment with your institution’s mental health center. If you or someone you know has had thoughts of harming themselves or suicide, contact a medical professional or crisis hotline such as 1-800-273-8255 (TALK).
Ever since we read Justin Chen’s article in STAT news about his experience as a PhD student at MIT, we knew we needed to interview him. The article, titled “Coming to terms with six years in science: obsession, isolation, and moments of wonder” poignantly describes the burnout and mental health issues which are all too common amongst PhD students. During our interview we learn more of the backstory; what prompted him to write the article, how it was received, and what he is up to now that he’s finished with his PhD.