There is a lot to be optimistic about regarding the new safe and highly effective vaccines, which are moving society closer toward the goal of close human contact once again.
To be clear, these vaccine candidates for COVID-19, both authorized and not yet authorized, are highly effective and safe. In fact, across all trials and sites, all six vaccines were 100% effective in preventing hospitalizations and death from COVID-19.
All Vaccines' Phase 3 Clinical Data
Complete protection against hospitalization and death from COVID-19 exhibited by all vaccines with phase 3 clinical trial data.
This astounding level of protection from SARS-CoV-2 from all vaccine candidates across multiple regions is likely due to robust T cell response from vaccination and will "defang" the virus from the concerns that led to COVID-19 restrictions initially: the ability of the virus to cause severe illness. This is a time of hope and optimism. After the devastating third surge of COVID-19 infections and deaths over the winter, we finally have an opportunity to stem the crisis – if only people readily accept the vaccines.
Amidst these incredible scientific advancements, however, public health officials and politicians have been pushing downright discouraging messaging. The ubiquitous talk of ongoing masks and distancing restrictions without any clear end in sight threatens to dampen uptake of the vaccines. It's imperative that we break down each concern and see if we can revitalize our public health messaging accordingly.
The first concern: we currently do not know if the vaccines block asymptomatic infection as well as symptomatic disease, since none of the phase 3 vaccine trials were set up to answer this question. However, there is biological plausibility that the antibodies and T-cell responses blocking symptomatic disease will also block asymptomatic infection in the nasal passages. IgG immunoglobulins (generated and measured by the vaccine trials) enter the nasal mucosa and systemic vaccinations generate IgA antibodies at mucosal surfaces. Monoclonal antibodies given to outpatients with COVID-19 hasten viral clearance from the airways.
Although it is prudent for those who are vaccinated to wear masks around the unvaccinated in case a slight risk of transmission remains, two fully vaccinated people can comfortably abandon masking around each other.
Moreover, data from the AztraZeneca trial (including in the phase 3 trial final results manuscript), where weekly self-swabbing was done by participants, and data from the Moderna trial, where a nasal swab was performed prior to the second dose, both showed risk reductions in asymptomatic infection with even a single dose. Finally, real-world data from a large Pfizer-based vaccine campaign in Israel shows a 50% reduction in infections (asymptomatic or symptomatic) after just the first dose.
Therefore, the likelihood of these vaccines blocking asymptomatic carriage, as well as symptomatic disease, is high. Although it is prudent for those who are vaccinated to wear masks around the unvaccinated in case a slight risk of transmission remains, two fully vaccinated people can comfortably abandon masking around each other. Moreover, as the percentage of vaccinated people increases, it will be increasingly untenable to impose restrictions on this group. Once herd immunity is reached, these restrictions can and should be abandoned altogether.
The second concern translating to "doom and gloom" messaging lately is around the identification of troubling new variants due to enhanced surveillance via viral sequencing. Four major variants circulating at this point (with others described in the past) are the B.1.1.7 variant ("UK variant"), B.1.351 ("South Africa variant), P.1. ("Brazil variant"), and the L452R variant identified in California. Although the UK variant is likely to be more transmissible, as is the South Africa variant, we have no reason to believe that masks, distancing and ventilation are ineffective against these variants.
Moreover, neutralizing antibody titers with the Pfizer and Moderna vaccines do not seem to be significantly reduced against the variants. Finally, although the Novavax 2-dose and Johnson and Johnson (J&J) 1-dose vaccines had lower rates of efficacy against moderate COVID-19 disease in South Africa, their efficacy against severe disease was impressively high. In fact J&J's vaccine still prevented 100% of hospitalizations and death from COVID-19. When combining both hospitalizations/deaths and severe symptoms managed at home, the J&J 1-dose vaccine was 85% protective across all three sites of the trial: the U.S., Latin America (including Brazil), and South Africa.
In South Africa, nearly all cases of COVID-19 (95%) were due to infection with the B.1.351 SARS-CoV-2 variant. Finally, since herd immunity does not rely on maximal immune responses among all individuals in a society, the Moderna/Pfizer/J&J vaccines are all likely to achieve that goal against variants. And thankfully, all of these vaccines can be easily modified to boost specifically against a new variant if needed (indeed, Moderna and Pfizer are already working on boosters against the prominent variants).
The third concern of some public health officials is that people will abandon all restrictions once vaccinated unless overly cautious messages are drilled into them. Indeed, the false idea that if you "give people an inch, they will take a mile" has been misinforming our messaging about mitigation since the beginning of the pandemic. For example, the very phrase "stay at home" with all of its non-applicability for essential workers and single individuals is stigmatizing and unrealistic for many. Instead, the message should have focused on how people can additively reduce their risks under different circumstances.
The public will be more inclined to trust health officials if those officials communicate with nuanced messages backed up by evidence, rather than with broad brushstrokes that shame. Therefore, we should be saying that "vaccinated people can be together with other vaccinated individuals without restrictions but must protect the unvaccinated with masks and distancing." And we can say "unvaccinated individuals should adhere to all current restrictions until vaccinated" without fear of misunderstandings. Indeed, this kind of layered advice has been communicated to people living with HIV and those without HIV for a long time (if you have HIV but partner does not, take these precautions; if both have HIV, you can do this, etc.).
Our heady progress in vaccine development, along with the incredible efficacy results of all of them, is unprecedented. However, we are at risk of undermining such progress if people balk at the vaccine because they don't believe it will make enough of a difference. One of the most critical messages we can deliver right now is that these vaccines will eventually free us from the restrictions of this pandemic. Let's use tiered messaging and clear communication to boost vaccine optimism and uptake, and get us to the goal of close human contact once again.
A recent study in The Lancet Oncology showed that AI found 20 percent more cancers on mammogram screens than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.