Updates on COVID-19

Scientists are working harder than ever to gather information on COVID-19, or SARS-CoV-2, as fast as possible, and information on their progress is being thrown at us from every direction. This page is a resource where you can receive the newest scientific updates regarding COVID-19. We will try to keep this page up to date on all of the current information. If you haven’t already, read our original post on COVID-19, linked below!

Before we get started with the updates, we want to give a brief overview of the process of publishing a scientific paper and a disclaimer. Usually after a scientific journal has accepted a paper, they will send it to a number of peer reviewers, or other scientists, for revisions. This step is for more than just grammar corrections, it is for ensuring that all of the science is accurate and that all of the necessary experiments were completed. Due to the urgency of gathering and sharing information on SARS-CoV-2, many journals have chosen to publish papers prior to the peer-review process as “pre-prints.” While this helps scientists communicate with each other quickly, it increases the chances for mistakes to be published and accepted. If any of the information that we discuss is later retracted, we will update you as soon as possible and correct all respective posts.

May 14

Falling in line with our last post and the relaxation of stay-at-home mandates, today’s COVID-19 update will discuss the newest guidelines for contact tracing and how this could play a huge role in containment strategies and transmission rates, allowing for more relaxed social-distancing guidelines.

Contact tracing involves finding all of the individuals an affected (infected) person has come into contact with recently, testing those who show symptoms, and guiding others on quarantine practices and self isolation periods. Due to the prevalence of presymptomatic and asymptomatic cases, the efficacy of contact tracing for COVID-19 has been called into question; however, this method will become more important than ever with stay-at-home orders ending and the relaxation of social distancing. This paper specifically looked at the potential benefits of broadening contact tracing guidelines to include mandatory testing of all individuals who have come into contact with an affected person. They found that the testing of asymptomatic individuals has the potential to make a striking difference in the spread of the virus. Further, those that test negative will be saved from unnecessary quarantine time and can continue to work, contributing to the regrowth of the economy. Whether the CDC plans to expand their contact tracing procedures is to be determined, but something everyone can do is strictly abide by self isolation measures if having previous contact with someone who has tested positive for COVID-19.     

This will be our last weekly COVID-19 update. New updates will come with vaccine breakthroughs or if we see a significant peak in new cases/ deaths with the relaxation of social distancing. As always, if you have questions, comments or feedback on COVID-19, please reach out and THANK YOU to everyone who has read our posts. We really appreciate our readers and we hope that our posts helped you feel more knowledgeable on the science behind our current pandemic!

Bilinski, A. (2020). Contact tracing strategies for COVID-19 containment with attenuated physical distancing.

May 8

“Reopening America!” This headline is beginning to appear everywhere as states are slowly lifting their stay-at-home orders and while some people are excited to get back to “normal” there are mixed emotions about how these changes will affect the current virus trend. In today’s COVID-19 update, we are going to take a look at how quarantine affected the spread of the virus and the projected outcomes of the orders being lifted.

The first states began reopening on May 1 and prior to any reopenings, as of April 30, there were more than 1 million confirmed cases of SARS-CoV-2 and over 62,000 deaths in the United States. While the stay-at-home orders have definitely put a damper on everyone’s spring plans (and CINCO DE MAYO! Because drinking margs at home just isn’t the same!!!) a recent statistical analysis has shown just how much these orders have decreased both infection and death. 

In order to accurately analyze infection and death due to COVID-19 on a statewide basis, this study used a standard epidemiology approach. According to dictionary.com, epidemiology can be defined as “the study, assessment, and analysis of public health concerns in a given population; the tracking of patterns and effects of diseases…1” As you can imagine, people who study epidemiology (epidemiologists) have been hard at work studying, assessing and analyzing the effects of COVID-19 in terms of the health of the people. In epidemiology, a standard analysis used to “rate” infectious disease is R0 or RT, a value indicative of the virus’ reproduction number. Typically, the closer this value is to “1”, the harder it is to contain. Another epidemiology analysis involves calculating the cumulative incidence (CI) or the estimated risk that an individual will develop a disease (COVID-19). We will be referring to these values throughout the post in order to describe how different state’s mandates have influenced the spread of COVID-19.

States were examined once they reached 500 confirmed cases of COVID-19. All states, including the District of Columbia were examined, except for Alaska and Montana, the only two states which had not reached 500 cases at the time of analysis. The average R0 for states prior to implementing a stay-at-home order was 1.256. One week after implementing the order, the average was 1.088, meaning that there was a -13.3% change in reproduction number upon implementing stay-at-home orders. When taking into account the cumulative incidence of states with mandated stay-at-home orders, the CI is -0.15 compared to states without state-at-home orders, where the CI is 0.07. Put simply, these values mean that states with stay-at-home orders are protecting their residents and this has been demonstrated by the differences in CI values, indicating that stay-at-home orders are decreasing the risk of individuals developing the disease. Further, other mandates, such as non-essential business closures have generated an average CI of -0.13 while states without non-essential business closures have an average CI of 0.09.  We see a similar trend in states where mass gatherings have been limited, with an average CI of -0.05 whereas states without these mandates have an average CI of 0.18. It is important to note that these values are statistically significant, meaning that there is enough difference between states with and without stay-at-home orders to determine that the outcomes are not due to random chance and are indeed due to the state mandated orders.

In other analyses, hazard curves were generated after each state had 500 confirmed cases to predict the amount of time to reach 1000 confirmed cases (time to double the number of confirmed cases). In states with stay-at-home orders, the amount of time to double the number of confirmed cases was nearly 3x longer than states with stay-at-home mandates in place. Deaths were also calculated using a hazard curve and on average, in states with stay-at-home orders, the time to reach 100 deaths was 16 days where states without stay-at-home orders only took 8 days to reach 100 deaths (2x faster without stay-at-home mandates).

In conclusion, no matter how disruptive stay-at-home orders have been, they have saved lives! The states with the most strict policies (stay-at-home orders), saw the most significant effect in decreasing the spread of COVID-19 and decreasing deaths caused by COVID-19. However, states with poor adherence to their state mandated orders were found to have similar outcomes (infection rates/ death) to states without safety policies in place. As limitations on mass gatherings slowly decline and as businesses, restaurants and gyms reopen, there are still great risks in spreading COVID-19 and potentially seeing another significant spike in cases this summer/ fall. While we are all ready to get back to our normal schedule, please adhere to any guidelines implemented by your city and/ or state. Be smart, practice good hygiene, wear masks when required or when you feel unsafe and let’s continue to flatten the curve.     

1. https://www.dictionary.com/browse/epidemiology?s=t
2. Dreher, N., et al., Impact of policy interventions and social distancing on SARS-CoV-2 transmission in the United States. medRxiv, 2020: p. 2020.05.01.20088179.

May 1

In the most recent post of our introductory series, we talked all about immunology. We mentioned how the immune system acts as the body’s police, protecting us from rule breakers, fugitives and invaders. Invaders can be thought of as pathogens that attack and use our body for their own good. Viruses, including the infamous coronavirus, or SARS-CoV-2, is an example of one of these invasive pathogens. Cases of SARS-CoV-2 range from asymptomatic, mild and even acute respiratory failure and death; however, the underlying mechanisms for this wide variability are still unknown. Previous studies on the original SARS-CoV showed a relationship between CD4 T cells, or “helper” T cells, and a positive outcome, or immune clearance of the virus. In today’s COVID-19 update, we are going to look more closely at one of the first studies to correlate immune subpopulations with SARS-CoV-2 outcomes.

In a study published last week, scientists surveyed the blood of COVID-19 patients and healthy individuals to detect CD4 T cells that directly react to the SARS-CoV-2 spike protein. The spike protein is how the virus enters into the human host cells, ultimately causing illness. These specific T cells, called S-reactive T cells, were identified in 83% of patients that have been diagnosed with COVID-19. Further, 34% of healthy patients showed the presence of these T cells. This is a striking discovery, because if you remember from the immunology intro post, T cells are reactive to pathogens only after they encounter the pathogen. So how do healthy donors have a population of T cells that are reactive against SARS-CoV-2?  When viruses have similarities, T cells may remember proteins or antigens from one virus and be able to react to a similar protein on a completely different virus. Scientists believe that the 34% of healthy donors with S-reactive T cells are due to “cross-reactive clones” or T cells that have been raised against S-proteins and have the ability to recognize multiple S-proteins, like the one on SARS-CoV-2.

Currently, much remains unknown concerning the impacts of these T cells in healthy donors. However, one of the potential benefits of these S-reactive T cells is the ability to initiate quicker immune responses (particularly the adaptive immune response) to COVID-19, which could partially explain why there is wide variability concerning how the virus affects different people. This subset of T cells could also play a role in risk evaluation (who is more likely to be asymptomatic vs develop severe illness). Like all of the other articles that we have posted in our COVID-19 Updates, this study is one of the first of its kind and only offers novel preliminary data. However, it’s exciting to be able to relate our introductory posts back to prevalent information concerning the virus. We hope that you all are understanding more of the science that goes into these studies and feeling more informed.  

Braun, J., et al., Presence of SARS-CoV-2 reactive T cells in COVID-19 patients and healthy donors. medRxiv, 2020: p. 2020.04.17.20061440.

April 24, 2020

The use of hydroxychloroquine as a treatment for COVID-19 has been highly debated. Nevertheless, for only the second time in history the FDA has given emergency approval to use this drug as a last resort (when no clinical trial drugs are available). This has only further increased the need to research hydroxychloroquine’s efficacy as a SARS-CoV-2 antiviral drug. Just yesterday, researchers published the results from a retrospective study looking at mortality rates between male patients over 65 years old who received hydroxychloroquine treatment, hydroxychloroquine in conjunction with azithromycin, and neither drug. A retrospective study means that they looked back at data from these patients and used statistics to compare the groups. These studies have certain limitations including, but not limited to, the lack of treatment randomization. Regardless, researchers found that the group of patients treated with hydroxychloroquine alone had a higher mortality rate than either of the other groups. These results need to be interpreted with caution because lifestyle factors varied between the three groups; however, they do demonstrate the need for more research into the risks associated with hydroxychloroquine use and increased caution when using it in a treatment plan.     

Magagnoli, J., Narendran, S., D, F. P. M., Ph, D., Hardin, J. W., Ph, D., Sutton, S. S., Pharm, D., & Ambati, J. (2020). Outcomes of hydroxychloroquine usage in United States veterans hospitalized with Covid-19.

For more information on potential drugs used to fight COVID-19, check out this Q&A from the chair of MUSC’s Drug Discovery program:
Disclaimer: We did not write the article linked above and are not affiliated with Dr. Wooster, the DD program or the MUSC College of Pharmacy.

April 16, 2020

Current data indicates that SARS-CoV-2 has infected more that 2 million people, resulting in over 130,000 deaths. The factors separating mild and fatal infections are poorly understood. A recent study analyzing previous experimental data suggests one of these contributing factors is cigarette smoke, which has been shown to play a role in developing a more severe infection.

Our previous two updates have mentioned ACE2, the SARS-CoV-2 receptor. As a reminder, the ACE2 receptor is required for SARS-CoV-2 to infect the host. Some cells may contain the ACE2 receptor, while others do not. You can imagine the receptor as a fingerprint scanner that allows entrance into the home. Only some houses have fingerprint scanners, just like only some cells contain the ACE2 receptor. Further, only certain people can gain access through each scanner, just like each receptor is specific for certain molecules. It’s important to identify the different cell types that express ACE2, because these are the only cells the SARS-CoV-2 can enter into.

Scientists can look at an individual cell’s gene expression and using this data, they can conclude which cells express the ACE2 receptor. Single cell analyses have shown that the ACE2 receptor is expressed on certain cells lining the respiratory tract, or airway, that produce mucus. Further, exposure to chronic cigarette smoke can increase the number of these cells, resulting in a higher number of cells that have the possibility to be infected by SARS-CoV-2. This data partially explains why smokers are more likely to develop an infection from SARS-CoV-2 and also gives insight on why smokers are more likely to develop severe, or possibly fatal symptoms upon infection. Data from this research also suggests that quitting smoking can decrease levels of ACE2 over time which could lessen the risk of infection and symptoms. 

Smith, J. C., & Sheltzer, J. M. (2020). Cigarette smoke triggers the expansion of a subpopulation of respiratory epithelial cells that express the SARS-CoV-2 receptor ACE2. BioRxiv, 2020.03.28.013672. https://doi.org/10.1101/2020.03.28.013672

April 9, 2020

Last week, our update focused on potential therapeutic effects of targeting the spike glycoprotein that is found on SARS-CoV-2, and the receptor that binds SARS-CoV-2, ACE2. On March 27, a paper published in Science further decoded this interaction. Scientists in China used a high-resolution microscopic technique called cryo-electron microscopy (cryo-EM) to take an atomic-scale picture of ACE2 binding to the virus. While this may not seem like a big deal, this image allows scientists to map the way SARS-CoV-2 infects human cells. This information can be used as a basis for designing clinical therapeutics that block this critical interaction.

Since the outbreak of COVID-19 and the identification of the SARS-CoV-2 – ACE2 interaction, there has been speculation regarding whether or not ACE inhibitors can offer therapeutic effects in preventing COVID-19. If you remember from last week, a receptor can be thought of as a cell’s hand that has a very specific shape so that it can only hold onto, or bind, very specific items. An inhibitor works by mimicking the shape that would normally sit in the receptor. This way, the receptor is holding onto the inhibitor and can not bind to its normal partner. So, in the case of COVID-19, an effective inhibitor would block the ability of the virus and the human cell to interact, ultimately leading to the inability of SARS-CoV-2 to infect humans. In a report last week from New England Journal of Medicine, a team of UK and US scientists began testing different ACE inhibitors to determine their effects on COVID-19. While there is currently insufficient data in determining whether ACE inhibitors could be used to treat and/or prevent COVID-19, these fundamental steps in better understanding the interaction between SARS-CoV-2 and ACE2 is vital for designing effective drugs to help treat this global health crisis.

Yan, R., Zhang, Y., Li, Y., Xia, L., Guo, Y., and Zhou, Q. (2020). Structural basis for the recognition of SARS-CoV-2 by full-length human ACE2. Science 367, 1444-1448. https://10.1126/science.abb2762
Vaduganathan, M., Vardeny, O., Michel, T., McMurray, J., Pfeffer, M. A., & Solomon, S. D. (2020). Renin-Angiotensin-Aldosterone System Inhibitors in Patients with Covid-19. The New England journal of medicine, NEJMsr2005760. https://doi.org/10.1056/NEJMsr2005760

April 3, 2020

For a virus to enter and infect a host cell, it has to first bind to that cell through a specific receptor on the cell’s surface. Think of a receptor like a cell’s hand, except this hand has a very specific shape so that it can only hold onto, or bind, with other receptors that fit into that shape. On March 19th, a paper published in the journal Cells described the human receptor, ACE2, that SARS-CoV-2 binds with to gain entry into host cells, and characterized the specific part of the SARS-CoV-2 viral structure, the spike glycoprotein, that binds to ACE2. They found that this spike glycoprotein was very similar to the one used by SARS-CoV, the coronavirus from 2002-2003, and that antibodies targeting the SARS-CoV spike glycoprotein were capable of preventing SARS-CoV-2 from entering into host cells. While this does not necessarily mean that people previously infected with SARS-CoV will be immune to SARS-CoV-2, it provides information that scientists can use to develop a vaccine. Vaccines help us develop antibodies against viruses before we get infected, almost like giving our immune system a cheat code, but the trouble comes from deciding which part of the virus the antibodies should target. From this paper, it seems that if scientists develop a SARS-CoV-2 vaccine that helps our bodies develop antibodies against this spike glycoprotein, the vaccine may be effective at preventing infection.  

A paper published on April 1st in EBioMedicine has shown that may just be true. Researchers at the University of Pittsburgh have developed a vaccine against SARS-CoV-2 that has shown promising results in mice. This vaccine is given as a micro-needle array – a small patch that has 400 needles containing specific parts of the spike glycoprotein and sugar. This is a new method utilizing the high number of immune cells within the skin. These needles dissolve into the skin, and the patch can then be removed. This study is still in the early stages, but the researchers hope to start a human clinical trial soon. 

Walls, A. C., Park, Y.-J., Tortorici, M. A., Wall, A., McGuire, A. T., & Veesler, D. (2020). Structure, Function, and Antigenicity of the SARS-CoV-2 Spike Glycoprotein. Cell, 1–12. https://doi.org/10.1016/j.cell.2020.02.058

E. Kim et al. (2020). Microneedle array delivered recombinant coronavirus vaccines: Immunogenicity and rapid translational development. EBioMedicinehttps://doi.org/10.1016/j.ebiom.2020.102743