In modelling how the Covid-19 crisis will impact the economy, it is absolutely crucial to focus on people, because they are the vulnerable factor in any economy’s productive capacity. Only people, not machines, must stop working when they or members of their households become ill.

In our new work my US colleagues and I have used epidemiological and economic models to examine the effect of Covid-19 on the supply of labour, an essential input into economic production.

We found that too little social distancing, which would have allowed the infection rate to rise too high, may have caused a large upfront contraction in economic activity by knocking out too many workers in sectors of the economy that are critical to production.

With critical or core sectors hit by absences due to sick leave, we show how the supply shock spreads through the economy. We also consider how to rethink social distancing by differentiating by sector and occupational requirements.

Over the last few months, a recurring theme in the political debate has been that social distancing measures save lives, but are also responsible for a deep and damaging fall in economic activity which destroys livelihoods.

However, our latest work questions this view and challenges many existing assumptions. By integrating epidemiological and economic models we have shown that, if only because of the effect of the disease on labour supply, letting the infection rise unmitigated would have also caused a large upfront contraction in economic activity.

A high number of symptomatic infected workers at the peak of the pandemic could have produced a drop in economic activity of up to 30% per month. This would be independent of any additional impact caused by a fall in demand due to loss of income and other financial disruption.

Our results draw attention to the varying consequences of the disease on the core and non-core industries. There are two reasons for this. The first is that, by definition, industries in the core sector produce goods and services that allow other industries to operate. When a larger number of their  workers fall sick this may cause disproportionate repercussions for the rest of the economy, creating widespread disruption.

It may be difficult to know exactly which industries are part of the core, and hence where large disruption may originate. But a reasonable list includes transportation and warehousing, petroleum and coal products, utilities (energy), health care, government services such as police and sanitation services), food, beverages and agriculture. In the United States, these industries account for 28% of GDP, and 37% of employment.

In producing goods and services essential to other industries which cannot easily be replaced in the short run, many core industries rely on specialised labour working in teams.

For example, you need at least a minimum number of train conductors for the subway to function; a minimum number of nurses and doctors to run a ward; a minimum number of truck drivers to have your trash picked up. If workers are sick in large numbers, these industries may be unable to operate.

To the extent that this is a common feature of core industries, the main economic risk of a rapid runup of infection rates stems exactly from this problem. By reducing labour activity sharply down to critical levels, the disease may create severe shortages in essential production and services, and thus create widespread economic damage.

The second reason is that in the core industries, the percentage of workers who can perform their occupational tasks from home is relatively limited. Based on U.S. data, only 15% of workers in the core industries can work from home, as opposed to 40% in the other industries.

To avoid the risk of economic disruption, protecting workers in core industries seems to be a logical way to go. So how can this be facilitated through social distancing?

Measures could be stricter for workers in other sectors, and/or for the old and the young, outside the labour force. Fewer people in public spaces reduces the probability of essential workers being infected when commuting, shopping and working. We use our model framework to have a first-pass quantitative assessment of this strategy.

To be efficient, social distancing should be differentiated by sector and occupation. As a starting point, consider a lockdown extended to all the workers who are able to work from home. This would basically minimise labour supply disruption with no healthy person prevented from working.

Now, here is the catch. If we include an equal proportion, say a third, of the young and the old in a lockdown, these measures should be in place for eight months, to avoid a new outburst of the disease.

With a third of the population in a lockdown for eight months, supply disruptions due to the absence from work of sick and symptomatic workers will become lower and smoother over time.  Still, the outcome is not painless: output would still contract up to 15% at a monthly rate.

Moreover, at the peak of the infection, the number of infected people would be too high for the health care system to cope. This has been estimated at 7% of the population.

Starting with this scenario, we can see the difficult trade-offs ahead: putting more people under the lockdown, say, 50% of the population, would be enough to help the health care system to cope. However (a) the economic costs would be substantially higher and (b) it would take longer to achieve herd immunity; to avoid a resurgence of the infection, the measures would have to last longer than 8 months.

Most of the calculations above rest on the idea that the ultimate goal of health measures is to achieve herd immunity while minimising economic damage. In the scenario we construct, different groups of people achieve it at different times, keeping peak infections low, so that workers who are ill can get proper hospital treatment.

What could make these scenarios less dire? We can hope that the epidemiological assumptions we derived from the literature turn out to be too pessimistic; the uncertainty is quite high, but in both directions.

More positively, the lockdown could be complemented by targeted testing and tracking, once again, in our view, concentrated on the group of essential workers who could also have been given (subsidised) PPE equipment, reducing the need to lockdown large sections of the population.

Yet the latest surveys suggest that only 10 to 20% of the population has been infected already, hence there is a long way to go before reaching herd immunity. Without a medical breakthrough in treatment  of the disease, or without the development of a vaccine, there is no easy way out.

Giancarlo Corsetti is Professor of Macroeconomics at Cambridge University.