Flu and Measles Vaccines Could Also Help Flatten the Covid-19 Curve

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Have the up-to-date vaccination record as one more weapon once morest Covid-19. And not only with the specific vaccine. New work from researchers at Weill Cornell Medicine and the University of Oxford shows that even unrelated vaccines might help reduce the burden of the pandemic. The study, published Monday in “Proceedings of the National Academy of Sciences,” adds to evidence suggesting that the widespread immune-boosting properties of many vaccines may cross-protect patients once morest multiple pathogens.

Before specific Covid-19 vaccines were available, many public health experts and immunologists suggested immunizing vulnerable populations with other vaccines to provide some degree of protection.

“We know that unrelated vaccines have these heterologous effects, and a reasonable person might tell you that if you used them during a pandemic, you would benefit,” says Dr. Nathaniel Hupert, associate professor of Health Sciences at Weill Cornell Medicine and lead author. of the new article. However, it was unclear how much such an intervention would help, which populations it would best target, or which part of the population would have to receive the unrelated vaccines to have a significant effect.

To answer these questions, Dr. Hupert and Dr. Douglas Nixon, Professor of Immunology in Medicine in the Division of Infectious Diseases at Weill Cornell Medicine, and their colleagues at Weill Cornell Medicine and the University of Oxford used the system. COVID-19 International Modeling Consortium (CoMo), a sophisticated computational modeling platform they had built in response to the pandemic. “If you have a model that can be customized for a particular time and place in the context of an outbreak, you can start to experiment with different immunity conditions in the population and see how things might have developed,” says Dr. Hupert.

Building on the 2020-21 winter Covid-19 wave that hit the United States following the Christmas season reopened, the researchers modeled the likely effects of a targeted, non-Covid-19 vaccine intervention at different times. to different populations. While they did not specify particular vaccines, the researchers chose consistent values ​​for the cross protection with data from previous studies on measles, flu, tuberculosis, and other immunizations. They found that an unrelated vaccine that provided only 5 percent protection once morest severe Covid-19 and was administered to only a small portion of the population would have caused a substantial reduction in the number of cases and hospital use.

“Surprisingly, we found a couple of really interesting emerging results from what we put into the mix,” explains Dr. Hupert. While the severity of Covid-19 is closely correlated with age, an experimental scenario that modeled vaccinating everyone over the age of 20 was more effective than strategies targeting only the elderly. That might be because younger people tend to have more social contacts across all age groups, making them more likely to spread the virus to more vulnerable populations. The timing of vaccinations was also important, as inoculation during the rising phase of the wave of infections had the greatest impact.

«This modeling study shows the Potential power of all vaccines to keep the immune system primed and healthy and reinforces the need for everyone to keep their immunization history up to date, particularly during a pandemic, “says Dr. Nixon.

Dr. Hupert sees the new findings as a “double win,” suggesting that even nations struggling to distribute enough specific Covid-19 vaccines can step in with routine immunizations once morest other pathogens And, in combination with non-pharmaceutical interventions like face masks, it might potentially mitigate the ongoing Covid-19 waves while preventing other diseases.

And as vaccine-escaping variants of the SARS-CoV-2 virus, such as Ómicron, travel the world, he notes that “each and every additional protective measure that we can muster among at-risk populations, including those at risk. small ones like the ones we modeled will lead to fewer infections, which means fewer new variants, which may mean a faster end to the pandemic. ‘

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