The ongoing coronavirus disease 2019 (COVID-19) pandemic has claimed more than 6.24 million lives worldwide. It has not only impacted the healthcare system adversely but also affected the global economy. The pandemic has been caused by a novel RNA virus, namely, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which was first reported in Wuhan, China. Scientists and healthcare officials formulated various pharmaceutical and non-pharmaceutical strategies to combat the pandemic.
Merits of shielding strategy during the COVID-19 pandemic
To contain the pandemic, many countries around the world have implemented a range of non-pharmaceutical interventions (NPIs), such as social distancing, travel restrictions, and national lockdowns.
Previous studies have suggested that ‘shielding’ or “focused protection of older people and other high-risk groups” while permitting uncontrolled viral transmission among lower-risk individuals could help minimize various societal costs imposed due to the universal implementation of NPIs. Shielding focuses on leveraging the imbalanced risk profile of COVID-19, i.e., older adults and those with comorbidities are at a higher risk of severe illness. In contrast, younger adults and children are at a lower risk of contracting a severe infection.
Theoretically, allowing COVID-19 infection to spread within the lower-risk population during a temporary shielding phase, the vulnerable group would be protected by herd immunity. Several countries worldwide have followed this strategy during the early phase of the pandemic. For instance, Sweden imposed very limited restrictions on the lower-risk population while restricting visits to long-term care (LTC) facilities.
In the autumn of 2020, many countries experienced increased COVID-19 cases after lifting NPIs. This renewed the debate about the merits of implementing shielding rules driven by the Great Barrington Declaration.
Retrospective assessment of shielding policy
Scientists stated the importance of retrospective assessment of shielding policy, which would not only be useful to evaluate the current COVID-19 pandemic but would help prepare for future pandemics. As the efficacy of the available COVID-19 vaccines is reduced against the newly emerging SARS-CoV-2 variants, it is important to make informed decisions between lockdowns and shielding while vaccines are modified.
There are a few mathematical models that can determine the effectiveness of shielding policy under real conditions. However, the consequence of imperfect shielding, changes in contact behavior among low-risk groups as well as the effect of uneven vaccination have not yet been determined.
Recently, researchers have used a mathematical model to assess if shielding the most vulnerable group while allowing infection to transmit through low-risk groups is an effective policy to combat the COVID-19 pandemic. This study has been published in PLOS Global Public Health.
In this study, researchers used a stochastic SEIR (Susceptible-Exposed-Infected-Recovered) framework, where the population was structured by location, i.e., community or long-term care (LTC) facilities and risk of mortality (higher or lower risk). The authors constructed this model based on a large city in England that comprises over one million people. The population contained 7% of individuals at a high risk of contracting severe COVID-19 infection and 10% of vulnerable people living in LTC facilities.
Scientists compared the outcome of epidemics under various conditions, such as no shielding, imperfect and perfect shielding, and lifting of shielding restrictions when the number of COVID-19 cases fell significantly.
The authors of this study indicated vital epidemiological weaknesses in shielding strategies, which were predominantly aimed at attaining herd immunity by protecting the vulnerable groups while simultaneously allowing transmission of infection within the low-risk population.
Scientists stated that the findings of this study are qualitatively robust to sensitivity analysis. Interestingly, this study revealed that tens of thousands of deaths could have been avoided among the low-risk group even under perfect shielding conditions. An overwhelming demand for healthcare centers has played a vital role in increased death rates.
Imperfect shielding assumed more realistic conditions, and the mathematical model predicted deaths to be around 150% to 300% more compared to perfect shielding conditions. Disproportionately higher death rates were observed among LTC residents than similar individuals in the community. This might be because LTC residents are clustered together within facilities, while other individuals at a higher risk of severe infection mix randomly within the community. This finding implies that the clustered high-risk individuals in LTC facilities are more adversely affected than the unclustered group.
Assumptions and implications
The authors made some conservative assumptions in this study that included no pathogenic evolution, low fatality rates, and fixed immunity. Additionally, the model failed to consider overwhelming healthcare burdens under all shielding conditions.
The current study revealed that although the shielding strategy could have worked well under unrealistic or perfect conditions, it is not so under real conditions. Researchers also stated that the shielding strategy would be difficult to follow in a household containing both high and low-risk individuals.