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Can you get long Covid if you're vaccinated?

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Can you get long Covid if you're vaccinated?

Posted | Updated by Insights team:

Publication | Update:

May 2022
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The Covid vaccines, while holding up strong against hospitalization and death, offer little protection against long Covid, according to research published Wednesday in the journal Nature Medicine

The findings are disappointing, if not surprising, to researchers who were once hopeful that vaccination could significantly reduce the risk of long Covid

Full coverage of the Covid-19 pandemic

Compared to an unvaccinated individual, the risk of long Covid in a fully vaccinated individual was cut by only about 15 percent, the study found.

“The vaccines are miraculous at doing what they were designed to do” — that is, prevent hospitalization and death, said Dr. Ziyad Al-Aly, a clinical epidemiologist at Washington University in St. Louis and the lead author of the study. But they “offer very modest protection against long Covid,” he said.   

The Covid vaccines were developed early on in the pandemic, long before doctors, scientists and patients knew of the existence of long Covid. They were never designed to protect against it, said Al-Aly, who is also chief of research at the V.A. St. Louis Health Care System. “We need to revisit them now that we know that the virus can also produce long-term consequences.”

Dr. Greg Vanichkachorn, director of the Mayo Clinic’s Covid Activity Rehabilitation Program in Rochester, Minnesota, who was not involved with the new study, said the results were not “too surprising.”

“We know that the majority of folks with long Covid have not had severe infections,” he said.

The study looked at national health care data from the U.S. Department of Veterans Affairs and included medical records of nearly 34,000 vaccinated people who had breakthrough Covid infections and more than 113,000 who were unvaccinated when infected with Covid from January 2021 through October 2021. People were considered fully vaccinated if they had received two doses of either the Pfizer-BioNTech or Moderna vaccine or a single dose of the Johnson & Johnson vaccine.

The researchers followed up six months post-infection to see whether patients had lingering symptoms. While the protection against long Covid in general was relatively small, vaccines were more effective at preventing some of the most life-threatening long Covid symptoms: Vaccination reduced the risk of lung disorders by nearly 50 percent and blood-clotting disorders by 56 percent, compared with those who were not vaccinated. 

Al-Aly noted that a breakthrough case does not mean a person will develop long Covid — only about 10 percent of breakthrough cases will result in the condition — but with so many people infected, this still translates to a large number of people. 

The data did not show whether a person was boosted, but Al-Aly said he doesn’t expect boosting to make a big difference in terms of vaccines protecting against long Covid, nor variants like omicron.

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Vanichkachorn agreed. “Unfortunately, I do not think boosting will do much to prevent long Covid with the vaccine,” he said. “We have many patients with breakthrough infections who are as vaccinated as possible. We also have not seen much of a difference between variants with long Covid symptoms.” 

This is not to say that vaccines are not an important tool in the fight against the pandemic, experts say.

Boosters, in particular, offer the most protection against severe acute Covid and reduce the risk of complications, said Dr. Jason Maley, director of the Critical Illness and COVID-19 Survivorship Program at Beth Israel Deaconess Medical Center in Boston.

But for long Covid, they’re not necessarily the solution. “I don’t believe vaccination is the key to eliminating long Covid,” Al-Aly said. “We really need to think about additional layers to protect us from the long-term consequences of this virus.”

New approaches to preventing long Covid

Covid cases are once again rising again in the U.S., driven now by an omicron subvariant called BA.2.12.1, according to the Centers for Disease Control and Prevention. Even so, public health measures such as masking and social distancing have largely fallen away.

Al-Aly said he doesn’t fault people for that. 

“It isn’t pragmatic to tell people to mask for the next 10 years,” he said. But it does underscore the need to improve vaccines and treatments in a way that could offer protection against long Covid.   

“Now that we have lifted all these other public health measures, vaccines are really the only layer of protection we have,” Al-Aly said. “That places even more urgency on the question of what other prevention or treatments might be available. Can we tweak those original vaccines to also address long Covid, or do we also need intranasal vaccines or other therapies in addition?” 

Intranasal vaccines, for example, could potentially be better at preventing transmission than current vaccines, but this is an area that needs to be investigated, he said. 

Maley, who was also not involved with the study, said that mounting research suggests one of the main risk factors for long Covid is the level of virus in the body during the acute infection. This suggests early treatment with therapies including antivirals may be able to help prevent long Covid by keeping those virus levels low. 

“Right now, antivirals are approved for emergency use authorization for patients who are at high risk for severe Covid-19, usually older adults or people with compromised immune systems,” Maley said. There is also an interest, he said, in studying whether antiviral treatments could benefit long Covid patients. 

Both Al-Aly and Vanichkachorn agreed that more research is needed on long Covid. “We need continued research specifically on long Covid so specific therapies can be developed,” Vanichkachorn said.

But right now, he said, “the best way to not get long Covid is not to get Covid.”

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Forecast methodology

The future outlook “forecast” is based on a set of statistical methods such as regression analysis, industry specific drivers as well as analyst evaluations, as well as analysis of the trends that influence economic outcomes and business decision making.
The Global Economic Model is covering the political environment, the macroeconomic environment, market opportunities, policy towards free enterprise and competition, policy towards foreign investment, foreign trade and exchange controls, taxes, financing, the labour market and infrastructure. We aim update our market forecast to include the latest market developments and trends.

Forecasts, Data modelling and indicator normalisation

Review of independent forecasts for the main macroeconomic variables by the following organizations provide a holistic overview of the range of alternative opinions:

  • Cambridge Econometrics (CE)

  • The Centre for Economic and Business Research (CEBR)

  • Experian Economics (EE)

  • Oxford Economics (OE)

As a result, the reported forecasts derive from different forecasters and may not represent the view of any one forecaster over the whole of the forecast period. These projections provide an indication of what is, in our view most likely to happen, not what it will definitely happen.

Short- and medium-term forecasts are based on a “demand-side” forecasting framework, under the assumption that supply adjusts to meet demand either directly through changes in output or through the depletion of inventories.
Long-term projections rely on a supply-side framework, in which output is determined by the availability of labour and capital equipment and the growth in productivity.
Long-term growth prospects, are impacted by factors including the workforce capabilities, the openness of the economy to trade, the legal framework, fiscal policy, the degree of government regulation.

Direct contribution to GDP
The method for calculating the direct contribution of an industry to GDP, is to measure its ‘gross value added’ (GVA); that is, to calculate the difference between the industry’s total pre­tax revenue and its total bought­in costs (costs excluding wages and salaries).

Forecasts of GDP growth: GDP = CN+IN+GS+NEX

GDP growth estimates take into account:

  • Consumption, expressed as a function of income, wealth, prices and interest rates;

  • Investment as a function of the return on capital and changes in capacity utilization; Government spending as a function of intervention initiatives and state of the economy;

  • Net exports as a function of global economic conditions.

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Market Quantification
All relevant markets are quantified utilizing revenue figures for the forecast period. The Compound Annual Growth Rate (CAGR) within each segment is used to measure growth and to extrapolate data when figures are not publicly available.

Revenues

Our market segments reflect major categories and subcategories of the global market, followed by an analysis of statistical data covering national spending and international trade relations and patterns. Market values reflect revenues paid by the final customer / end user to vendors and service providers either directly or through distribution channels, excluding VAT. Local currencies are converted to USD using the yearly average exchange rates of local currencies to the USD for the respective year as provided by the IMF World Economic Outlook Database.

Industry Life Cycle Market Phase

Market phase is determined using factors in the Industry Life Cycle model. The adapted market phase definitions are as follows:

  • Nascent: New market need not yet determined; growth begins increasing toward end of cycle

  • Growth: Growth trajectory picks up; high growth rates

  • Mature: Typically fewer firms than growth phase, as dominant solutions continue to capture the majority of market share and market consolidation occurs, displaying lower growth rates that are typically on par with the general economy

  • Decline: Further market consolidation, rapidly declining growth rates

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The Global Economic Model
The Global Economic Model brings together macroeconomic and sectoral forecasts for quantifying the key relationships.

The model is a hybrid statistical model that uses macroeconomic variables and inter-industry linkages to forecast sectoral output. The model is used to forecast not just output, but prices, wages, employment and investment. The principal variables driving the industry model are the components of final demand, which directly or indirectly determine the demand facing each industry. However, other macroeconomic assumptions — in particular exchange rates, as well as world commodity prices — also enter into the equation, as well as other industry specific factors that have been or are expected to impact.

  • Vector Auto Regression (VAR) statistical models capturing the linear interdependencies among multiple time series, are best used for short-term forecasting, whereby shocks to demand will generate economic cycles that can be influenced by fiscal and monetary policy.

  • Dynamic-Stochastic Equilibrium (DSE) models replicate the behaviour of the economy by analyzing the interaction of economic variables, whereby output is determined by supply side factors, such as investment, demographics, labour participation and productivity.

  • Dynamic Econometric Error Correction (DEEC) modelling combines VAR and DSE models by estimating the speed at which a dependent variable returns to its equilibrium after a shock, as well as assessing the impact of a company, industry, new technology, regulation, or market change. DEEC modelling is best suited for forecasting.

Forecasts of GDP growth per capita based on these factors can then be combined with demographic projections to give forecasts for overall GDP growth.
Wherever possible, publicly available data from official sources are used for the latest available year. Qualitative indicators are normalised (on the basis of: Normalised x = (x - Min(x)) / (Max(x) - Min(x)) where Min(x) and Max(x) are, the lowest and highest values for any given indicator respectively) and then aggregated across categories to enable an overall comparison. The normalised value is then transformed into a positive number on a scale of 0 to 100. The weighting assigned to each indicator can be changed to reflect different assumptions about their relative importance.

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The principal explanatory variable in each industry’s output equation is the Total Demand variable, encompassing exogenous macroeconomic assumptions, consumer spending and investment, and intermediate demand for goods and services by sectors of the economy for use as inputs in the production of their own goods and services.

Elasticities
Elasticity measures the response of one economic variable to a change in another economic variable, whether the good or service is demanded as an input into a final product or whether it is the final product, and provides insight into the proportional impact of different economic actions and policy decisions.
Demand elasticities measure the change in the quantity demanded of a particular good or service as a result of changes to other economic variables, such as its own price, the price of competing or complementary goods and services, income levels, taxes.
Demand elasticities can be influenced by several factors. Each of these factors, along with the specific characteristics of the product, will interact to determine its overall responsiveness of demand to changes in prices and incomes.
The individual characteristics of a good or service will have an impact, but there are also a number of general factors that will typically affect the sensitivity of demand, such as the availability of substitutes, whereby the elasticity is typically higher the greater the number of available substitutes, as consumers can easily switch between different products.
The degree of necessity. Luxury products and habit forming ones, typically have a higher elasticity.
Proportion of the budget consumed by the item. Products that consume a large portion of the consumer’s budget tend to have greater elasticity.
Elasticities tend to be greater over the long run because consumers have more time to adjust their behaviour.
Finally, if the product or service is an input into a final product then the price elasticity will depend on the price elasticity of the final product, its cost share in the production costs, and the availability of substitutes for that good or service.

Prices
Prices are also forecast using an input-output framework. Input costs have two components; labour costs are driven by wages, while intermediate costs are computed as an input-output weighted aggregate of input sectors’ prices. Employment is a function of output and real sectoral wages, that are forecast as a function of whole economy growth in wages. Investment is forecast as a function of output and aggregate level business investment.

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