A new paper describes a strategy that could help decide which workers can safely go back to work once a lockdown is easing off. The study, published on the preprint server medRxiv* in May 2020, could help to apply required measures for serological testing and income replacement among affected workers with accuracy and completeness.
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The Double Impact of the Pandemic and the Lockdown
The first case of COVID-19 was reported on December 31, 2019, by China. Little did the world know that a crisis was about to begin, which would reduce most of the working world to mere bystanders at home, as more and more of the population fell sick, and many died of a mysteriously selective virus.
Many parts of the world, beginning with China, responded with lockdowns. The immediate effect of a lockdown on health is evident and significant. The interruption of multiple routes of viral spread results in a drastic decline in the incidence of severe disease and death rates, which in turn relieves some of the overwhelming strain on healthcare systems that are on the verge of collapse.
Secondly, lockdown reduces the number of cases while a vaccine or therapeutic drug is under development.
However, the full-scale lockdown of a country is a measure which involves significant economic disruption. Lockdowns reduce productivity, and so reduce GDP, sending stock markets tumbling and the unemployment rate soars. Liquidity is affected, reflected in the falling financial performance of financial institutions.
As a result, it is an urgent matter to decide when to relax lockdown measures correctly. If lifted too soon, the lockdown will have caused unnecessary and profound harm, without reducing the number of deaths.
On the other hand, prolonging the lockdown is associated with increasingly tricky financial situations, where recovery may be extended and incomplete at times.
How to Exit the Lockdown
In countries hard-hit by the virus, the impossibility of thoroughly assessing the effectiveness of the interventions aimed at controlling viral spread makes the decision-making process still more complicated. However, with the passing of the peak of the pandemic in some countries, the need now is to develop a safe and feasible lockdown exit strategy.
Geographical strategies are being executed in several countries like the USA and Spain, where regions have marked autonomy. Differences in the incidence, rate of spread, and mortality will contribute to such decisions.
Many and deep changes will be required in business and manufacturing operations. Thus, a simple lifting of the lockdown will not suffice. The main factors to be invoked are the geographical characteristics, the nature of the work sector, and the age-related risk to workers and other high-risk populations.
The final criterion involves immunity passports following serological testing for antibodies to the virus. However, the WHO warns, “There is currently no evidence that people who have recovered from COVID-19 and have antibodies are protected from a second infection.”
A Decision-Making Model
Taking all these dimensions into consideration, the current paper presents a system for determining the number of workers that can go back to work. The strategy is called Sequential Selective Multidimensional Decisioning (SSMD) and incorporates four factors.
The paper describes the possible application of its theory by using Spain as an example.
Decision Level 1: Mortality
This involves considering the location-wise incidence at present, dividing them into high and low cumulative infection rates. The reference group contains the countries where the lockdown exit strategies were below average, as observed from the Google data on mobility variations.
High and low mortality areas are also determined based on the average incidence in Europe as a whole. Low-mortality areas come under full-scale lockdown exit strategies, while high-mortality areas are assigned to phase 2.
The obvious limitation of this strategy is the tight border security and population-level discipline it entails.
Decision Level 2: Infectiousness
Here again, sectors are classified as those with high and low contagion potential. The lack of objective data on what constitutes these sectors makes it necessary to rely on the lockdown criteria already in force and the social contacts involved. That is, low-contagion areas are those not significantly affected by lockdown, while the others constitute those that are usually disrupted by such measures.
Low-contagion areas within this level move into full-scale exit strategies, while the others are reassigned to the next level. Examples of the latter include arts, recreational activity, motor vehicle repair, trade, and bars or restaurants.
The difficulties here involve the requirement for social distancing in the workplace as well as the pressure exerted by non-exiting sectors, depending on their contribution to the GDP. Here again, political will and public health follow-through are crucial to ensure the right conditions in the workplace and restricting the demand for products, so as to limit the risk for the worker and the consumer.
Decision Level 3: Age
Here, the criterion applied is age-based risk. Age-related mortality data within the EU is used to decide the reference, which is the average cumulative mortality rate per 100,000 people for each age group.
Groups which have a lower rate compared to the EU rate are progressed to the exit strategies, while the rest move to the next level. Since this level contains work sectors that were not released to exit from the lockdown so far, this strategy allows a sizable proportion of workers even in this group to return to work, from the working population segment of the age pyramid, because the effect of the virus is different in different age groups. In practice, this would exclude all those above 59 years.
For those exiting at this level, workplace protection and restriction of demand is still more vital to preserve the benefits of the lockdown while exiting.
Decision Level 4: Antibody testing
At this level, only those at the highest risk by age, contagion, and mortality are still in lockdown, and here antibody testing is applied to sort out those who have already recovered. (The assumption is that the antibodies detected are protective.) Since antibody data is required to arrive at a precise incidence, an approximation is taken from the Gangelt study in Germany, which represents a community with high COVID-19 incidence, and had 14% seropositivity.
Economic impact of SSMD
The economic impact of lockdown exit strategies also comes in here, where those that are required to remain in lockdown because of increased susceptibility are to be compensated monetarily. The researchers say, “This compensation is no longer an emergency compensation, and the amount must, therefore, be close to replacing the income lost during lockdown.”
The final step is to calculate the mortality rate for every 100,000 workers, thus released to return to work.
Advantages of the SSMD Approach
The researchers point out that it is futile to apply the same lockdown strategy to achieve the same results in widely differing situations.
To quote, “A country succeeds in reducing daily infections of COVID-19 by lockdown strategies. Yet in areas of the country where no infections have occurred, it has failed to reduce anything. Isolating those infected, social distancing, frequent hand-washing, wearing a face mask, avoiding concentrations of people in confined places, preventing long-distance travel, etc., are measures that have a similar effect in any area, while confining an entire population to their homes can have a negligible effect in a rural area but a very significant one in a large city like Madrid or Barcelona.”
Given this truth, a targeted strategy is always superior to a one-size-fits-all approach.
Another benefit is the potential it offers to release large segments of the population to work and so reduce the number that needs to be subject to emergency public health interventions such as antibody testing. In the given study, the researchers note that less than 2% of workers ultimately need to be tested, which enables the better organization and reduces the number of tests immediately needed.
Avoiding a strictly age-based lockdown also has ethical and moral benefits and the costs to the country of having to sustain a large worker community who are unable to go for work.
Finally, the SSMD strategy is flexible enough to adapt to entirely different and stricter public health policies, to remove or add one or more levels, and thus improve the end result in terms of health protection.
In summary, the benefits of the SSMD strategy are fivefold:
- It allows lockdown exit for over 98% of workers on social security rolls in Spain (the country selected for the study) to return to work without increasing the workplace risk for the high-risk group.
- It avoids increasing the costs of the lockdown in terms of replacing the income lost to workers who are prevented by the lockdown from going for work.
- It reduces the target population for antibody testing.
- It assesses the compensation required for those who are affected.
- It can be altered to fit different situations.
This will, however, be contingent on stringent workplace safety measures in light of the COVID-19 risk, increasing testing for active cases, and properly tracing contacts.
medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.