The lack of capacity in health care today is obvious from the hard time hospitals around the world are having handling large waves of COVID patients requiring medical attention at the same time as providing their regular services to non-COVID patients. Although health systems remain a highly labour-intensive sector, capital has been increasingly important as a factor of production of health services over recent decades, and especially under pandemic situations when a large number of patients require emergency attendance.

On average, health capital expenditure which includes health infrastructure (buildings, machinery, IT) and stocks of vaccines for emergency or outbreaks only accounts for 0.2% of countries national production, equivalent to less than $0.5 trillion globally. Even OECD countries expenditure on health care does not reach 0.5% of their GDP. Investigating these figures further across time, we learn that they have not changed much in the past two decades, especially health capital (see Figure 1). This is alarming given that the total annual expenditure on health infrastructure ($0.5 trillion) is much lower than the loss endured by the public in case of a pandemic. UNCTAD (2020), for example, predicts a $2 trillion loss in global income due to COVID.

Figure 1 Health expenditure over time

Data source: WHO.

The failure to invest in public health and access to health care means much of the world remains ill-equipped to detect viral threats, protect frontline health care workers, and treat those who fall ill. Because of such factors, the kill rate of a virus depends in significant part on the quality of health care in a country, while its contagiousness is enhanced when government response is slow and insufficient. Figure 2 demonstrates the relationship between health expenditure per capita and number of hospital beds with the case fatality rate (CFR) the ratio of fatalities to infections, which appears to be negative for both. This means countries that invest more in their health capital are likely to face a lower CFR, however, the weak relationship is a clear indicator that a strong health system alone cannot be sufficient.

Figure 2 Health capacity and CFRs

Data source: WHO and World Bank.Note: There are two fundamental issues with any COVID-19 data: (i) the figures might be intentionally or unintentionally miss-reported; (ii) the number of cases recorded is in part a function of how much testing is carried out and fatality data might be misattributed. Therefore, using CFR is preferred as it could be more universal.

Outbreaks are inevitable. Whether they become pandemics the uncontrolled spread of contagious diseases across countries and continents depends on our response. To control a disease outbreak, two forces should work simultaneously: (i) controlling the spread of the disease (lowering R_0), and (ii) treating the infected people (lowering the CFR). The former is directly managed by the government through guidance and/or enforcing containment policies and can influence both infection and fatality rates. The latter only influences fatality rates and is dependent on the capacity of the health system, which is proxied by budgets and capital expenditure (for example, the number of hospital beds, especially critical/intensive care beds). It is therefore surprising to learn that number of available beds is falling in many countries. Most EU member states, for example, have reported a decrease in the availability of hospital beds over the past few years (Eurostat 2019).

Scholars at the University of Oxford have recently introduced the Stringency Index, a measure of government responses across the globe constructed using publicly available data on a number of indicators including school closings, travel restrictions, bans on public gatherings, and other interventions to create social distancing or to augment public health provision. Augmenting this measure with rate of COVID infections and fatalities, as well as the number of hospital beds, allows us to compare the current state of affairs in some of the most affected countries.

We already know that rapid and rigorous containment policies are advised to control the spread of an outbreak. However, each country must solve a different optimisation problem given their underlying constraints, namely, their health capacity and the economic cost of enforcing containment measures. In other words, the most cost-effective intervention for two countries with similar infection rates but dissimilar health capacities is different. For example, Figure 3 shows that Germany started responding to the growing rates of the virus much faster than the US. This includes screening/testing and taking social distancing measures. The lack of screening in the US in the first month of the outbreak is clearly seen in the bump in the CFR figure, as this means there were much more infected people as expected at that point. This late response was also amplified by a lower health capacity and resulted in a very sharp growth in both infected and death cases. Comparing the remaining two cases in Figure 3, we can see that not only does South Korea benefit from a significantly greater health capacity, it also started mass testing across the nation relatively early on compared to the UK and the US. A mix of rapid containment policies and high health capacity created a proper head start and made South Koreas intervention exemplary. When comparing Ireland to the UK two comparable nations with similar health capacities yet very different government responses we can see that although the outbreak in Ireland happened some weeks after the UK, it is expected that its rates will stay much lower. Even though Irelands population is lower than that of the UK, its CFR is still substantially lower. This is mainly due to a rapid response by the Irish government (e.g. school and college shutdowns only two weeks in, where this took the UK more than a month).

Figure 3 COVID-19 pandemic case studies

Data source: OECDand Hale et al. (2020)Note: Total hospital beds include acute care beds, rehabilitative care beds, long-term care beds. The number of ICU/CCU beds are much less than what is reported above. However, under shortfall situations a standard bed augmented with a ventilator could be used as an alternative. Overall, the bar above is drawn on the assumption that 10% of total number of hospital beds could be counted as available and adequate.

Going through other most affected cases, it appears most governments were somewhat slow in responding given their health capacity constraints, even though they were aware of the outbreak and there was no doubt the virus was highly contagious based on Chinas experience. This is partly justified on the grounds that such measures do not come cheap, but the true explanation is that politicians tended to wilfully ignore the deteriorating situation and to wait until the last critical moment to break the bad news. Also, unpreparedness and a lack of established evidence-based interventions which assure cost-effectiveness are noticeable.

In terms of the economic cost, the IMF predicts a 3% drop in affected countries annual GDP for every month that nonessential services stay closed, as they account for about one-third of output (IMF 2020). And thats before other disruptions and spillovers to the rest of the economy are taken into account. A recent study predicts a 11% year-on-year contraction in the US economy in the fourth quarter of 2020, more than half of which is due to COVID-induced uncertainty (Baker et al. 2020). Therefore, containment measures should be put in place rapidly and must be accompanied by market-stimulating policies, so that they can be at least partially lifted as soon as the situation has stabilised. This would help get the labour force back to work as quickly as possible (Baldwin 2020a).

In the immediate term, increasing government expenditure is a strategy that is endorsed by most financial authorities and economists (IMF 2020, UNCTAD 2020, Baldwin, 2020b). While this prevents the economy from a total meltdown, mass supplies of masks and testing would allow the labour force to gradually return to work while keeping the risk of another spread low (Greenhalgh 2020, Baldwin 2020c).

Given the substantial costs that pandemics impose on the global economy, it is essential to explore further mitigation strategies to minimise their likelihood and consequence, otherwise we will keep moving from one epidemic to another still unprepared. Evidence suggests that the likelihood and frequency of pandemics have increased over the past century because of increased global travel and integration, urbanisation, increased interactions between animals and humans, weak health systems and greater exploitation of the natural environment. Malaria, for instance, took millennia to jump from primates to humans. Yet in the last 50 years, more than 300 pathogens have appeared or reappeared across the globe (Jones 2008). Therefore, we should start planning to prepare for the next pandemic from this very moment, as even if containment limits the spread of disease, other outbreaks will keep happening as long as diseases keep jumping from animals to humans. Public health experts say that it is not a matter of if another pandemic will happen, but when.

It is also quite clear that flattening the curve becomes much easier the higher the health capacity bar is set. Unlike the government response, which can be put into practice almost immediately, increasing health capacity in incremental and time-taking, arithmetic in opposed to the exponential growth of the disease, and it takes much more time in advance. Further capital investment is therefore advised to give health systems a head-start to reduce the response shortfall a standard phase in pandemics where there is not enough capacity to admit everyone in need.

Lastly, there is a dire need for evidence-based approaches to what can and will work in different settings with different types of constraints and challenges. Without understanding the impact and cost of mitigation strategies, it is difficult to find the most cost-effective and sustainable response tailored to each countrys context and available resources. There are, however, not many economic studies on health interventions that target epidemics and disease outbreaks. For example, Chalkidou et al. (2020) finds only one study about COVID mentioning the term cost-effectiveness.

Baldwin, R (2020a), Remobilising the workforce for World War COVID: A two-imperatives approach, VoxEU.org, 13 April 2020.

Baldwin, R (2020b), Keeping the lights on: Economic medicine for a medical shock, VoxEU.org, 13 March 2020.

Baldwin, R (2020c), COVID-19 testing for testing times: Fostering economic recovery and preparing for the second wave, VoxEU.org, 26 March 2020.

Baker, S, N Bloom, S Davis and S and Terry (2020), COVID-induced economic uncertainty and its consequences, VoxEU.org, 13 April 2020.

Chalkidou, K, A Gheorghe and C Krubiner (2020), Strategic Investments for COVID-19 and Future Epidemic Threats, Centre for Global Development, 20 March.

Eurostat (2019), Healthcare resource statistics beds.

Greenhalgh, T, M B Schmid, T Czypionka, D Bassler and L Gruer (2020), Face masks for the public during the covid-19 crisis, British Medical Journal 369.

Hale, T, A Petherick, T Phillips and S Webster (2020), Variation in government responses to Covid-19, Blavatnik School Working Paper, BSG-WP-2020/031.

Jones, K E, N G Patel, M A Levy, A Storeygard, D Balk, J L Gittleman and P Daszak (2008), Global trends in emerging infectious diseases, Nature 451(7181): 990-993.

IMF (2020), Europes COVID-19 Crisis and the Funds Response, The IMF and Covid-19 blogs, 30 March 2020.

UNCTAD (2020), The coronavirus shock: a story of another global crisis untold and what policymakers should be doing about it, United Nations Conference on Trade and Development.

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