How COVID-19 is tragically exposing systemic vulnerabilities in Peru

Despite early assessments that Peru was faring well in the COVID-19 pandemic and that its preparedness was due to its strict application of austerity and reforms over the last 30 years, these quickly turned out to be tragically premature as the country emerged over the summer as one of the worst impacted globally in terms of confirmed deaths per capita. While much of the blame has been focused on people’s behaviour, the crisis ultimately points to deep overlapping structural inequalities within the social protection, employment, and health systems, which austerity and reform have not resolved and in some cases worsened.

COVID testing in Peru
COVID-19 testing in Peru. Credit: Ministerio de Defensa del Perú on Flickr.

Precocious optimism followed by demise

Peru was one of the first countries to adopt strict measures to cope with COVID-19 in Latin America. A week after the first COVID-19 case was reported on 6 March, the country closed its borders on 13 March and declared a mandatory immobilization, allowing the population to go out only for acquiring essential services. At the same time, it launched an economic plan equivalent to 12% of the GDP, considered by experts as unprecedented – the greatest economic stimulus in Latin America against COVID-19. The plan included cash transfers for the vulnerable population, subsidies for services and salaries, food provisioning, financial aid for companies, and a large budget allocation for the health system, among other measures.

The current Minister of Economy and Finance, Maria Antonieta Alva, argued that the last 30 years of good fiscal behaviour – as a result of the strict application of austerity measures – allowed the country to face this health and economic crisis. These statements and international news coverage created a positive narrative that seemed to vindicate the country’s economic and social policies in recent decades. Even as recently as 21 July, an article in the Financial Times presented Peru as better prepared for the crisis compared to other countries in the region that were in worse fiscal and macroeconomic positions, such as neighbouring Ecuador.

However, this congratulatory assessment was tragically premature, as has now become evident. As of 24 August, Peru has the highest number of confirmed COVID-19 deaths per capita in Latin America and second only to Belgium globally (and soon to overtake), at 842 per million people, versus 542 for Brazil or 468 for Mexico. It also has the sixth largest number of confirmed cases in the world, with 600,438 confirmed cases. Per capita, it has slightly more confirmed cases than Brazil and more than four times than Mexico.

After initially controlling a sharp spike in cases in late May, daily confirmed cases first plateaued at between 3,000 to 4,000 per day, and after removing the nationwide quarantine on 30 June, they again surged since the beginning of August to surpass the peak levels reported in May (see Figure 1). Confirmed deaths have been running at about 200 deaths a day since July after a peak of about 300 a day in June (see Figure 2).1

Confirmed daily new COVID-19 cases, Peru
Figure 1: Confirmed daily new cases, Peru
Confirmed daily COVID-19 deaths, Peru
Figure 2: Confirmed daily deaths, Peru

Source of both figures: https://www.worldometers.info/coronavirus/country/peru/ (last accessed 24 August 2020).

The dire comparison with its neighbours is partly due to a much higher level of testing (besides Chile), which is also reflective of at least one aspect of greater capacity in the health system (and it also underscores the certain underestimation of the severity of the crisis in Mexico and Ecuador). However, this statistic is also problematic because the Peruvian numbers include both PCR as well as serology tests, with the large majority being serological, whereas other countries only include PCR tests. As a result, the numbers are not comparable, although this being said, Peru’s positivity rate is also one of the highest in the world, meaning that far more testing is needed relative to the current prevalence of infection.2

Proximate explanations of failure: mobility and behaviour

The lack of success in controlling the pandemic was partially due to an inability to restrict peoples’ mobility despite the lockdown, which has been widely reported in media and noted by commentators. This became more evident following the initial 15-day quarantine period, even despite the extension of this initial period. As in many parts of the world, migrant workers in places such as the capital city of Lima began returning to their places of origin by foot. Specialists also noted that the lack of refrigerators in households and the habit of buying fresh products caused people to go out to markets frequently. Social protection measures to help vulnerable people ironically made this situation worse. For instance, a monetary grant of 760 soles (about 214 USD) was one of the measures intended to help people without a formal income and who lost their job because of COVID-19. However, the payment of the grant caused people to crowd in the banks. Indeed, markets and banks became the main hot spots of infection.

As a result, many experts claimed that people’s behaviour was the main factor that undermined the COVID-19 response, that lack of education about health care and respect for rules was aggravating the spread of the virus, especially among poor people. However, the discussion generally revolves around proximate reasons rather than highlighting fundamental structural inequalities that in fact point back to the legacy of social and economic policies over the last 30 years.

More fundamental structural reasons

Although the COVID-19 response at first seemed to be strong and promising, it actually quickly exposed the deep and overlapping structural problems within the social protection system, the employment structure, and the health system, which 30 years of reform did not resolve and in some cases worsened.

One crucial problem, as noted above, is the high degree of informality, which is estimated at 72.5% of the economically active population (16.511 million people), with no access to any formal social security. Poverty was estimated at about one-fifth of the national population in 2018, based on a money-metric poverty line of 344 soles (roughly 98 USD) per person per month (the extreme poverty line was 183 soles). This means that about half of employed people were informal but not considered poor by this metric, even though they might have been just above the poverty line.

Moreover, only a fraction of those deemed poor receive assistance. For instance, before the lockdown, only about 725,000 households were affiliated with the main cash transfer programme (Juntos), or less than 9% of households in the general household register that is used for poverty targeting. Those uncovered and working informally become part of the ‘missing middle’ given that they are also not covered by any social protection.

As noted above, the government has created different monetary subsidies and adapted the existing cash transfer programmes to address the vulnerability of these uncovered populations. As of 21 August, these have been extended in principle to more than 8.5 million households, with transfer values from 160 soles to 760 soles (it is unclear whether these are monthly or one-off payments). However, the government has not yet completed paying many of these households and for many it would amount to only one transfer within the six-month period from March to August. Beyond such limited support and facing unemployment with little or no savings, adhering to mobility restrictions were quite simply unrealistic or impossible for a large majority of the population.

In addition, although Peru is in a better fiscal or financial position compared to other Latin American countries, this position was achieved by austerity and reforms that have undermined the public health system. Health specialists have noted the lack of historical investment in this system, as well as fragmentation and inequality, all of which have hampered the COVID-19 response effectiveness.3

Austerity clearly contributed to critical deficiencies in terms of infrastructure, human resources and medical supplies, and also constrained the composition of health spending, producing inefficient combinations of spending and thus impacting negatively on the implementation of services. For instance, Peru has a higher number of beds per capita compared with Ecuador and Mexico, but a lower number of doctors (see here). The distribution has also been historically uneven among the regions.4

Acknowledging this situation, the lockdown helped the government to gain time to increase the supply of beds, intensive care units, personal protective equipment, health staff, and to improve the infrastructure and also allocate financial resources to the sector. It has also generated alliances between the different health subsystems (public and private) to improve the availability of beds and intensive care units.

Despite the efforts, the number of cases exceeds the capacity of hospitals, the number of health personnel is insufficient, and there is a scarcity of essential supplies. Health professionals and local authorities have recently reported the collapse of the health system in different regions including Loreto, Piura, Lambayeque, Ucayali, Ica, Lima, Huánuco and Arequipa due to lack of human resources and key medical supplies, including scarcity of medicinal oxygen.5

Realities exposed

In sum, COVID-19 has exposed a reality that is distant from what the government and the international news media celebrated at the beginning of the pandemic. In a short period of time, Peru went from being heralded as better prepared to having the world’s worst performance in coping with the crisis. This has been in large part because of deep structural inequalities in Peruvian society, exacerbated by the high cost of austere policy choices that, despite producing strong economic performance according to conventional measures, did not solve the most pressing social problems of the last decades and exacerbated the crisis.

COVID-19 exposed an illusion. A political commitment to redefine the last 30 years of policies is required, alongside an allocation and distribution of resources to make it happen.

About the authors:

Kattia Talla CornejoKattia Liz Talla Cornejo lives in Lima, Peru. She has been working as a consultant monitoring a health project aimed at strengthening the COVID-19 response in Ancash, one of the Peruvian regions most impacted by the pandemic. This allows her to observe the critical situation of the health system and the COVID-19 response from the inside. She holds an MA in Development Studies from ISS with a major in Social Policy, and degree in Economics and International Business. She has experience in public finance, policy advocacy and monitoring within the fields of social policy, health and childhood, and has worked in governmental and non-governmental organizations in Peru.

Andrew FischerAndrew M. Fischer is Associate Professor of Social Policy and Development Studies at the ISS and the Scientific Director of CERES, The Dutch Research School for International Development. His latest book, Poverty as Ideology (Zed, 2018), was awarded the International Studies in Poverty Prize by the Comparative Research Programme on Poverty (CROP) and Zed Books and, as part of the award, is now fully open access (http://bora.uib.no/handle/1956/20614). Since 2015, he has been leading a European Research Council Starting Grant on the political economy of externally financing social policy in developing countries. He has been known to tweet @AndrewM_Fischer

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  1. All data from https://www.worldometers.info/coronavirus/ (last accessed 24 August 2020).
  2. The Peruvian numbers include both PCR as well as serology tests, with the large majority being serological. For instance, about three quarters of the total confirmed cases were detected through serology as of 16 August. In contrast, other countries in the region only count PCR tests, as recommended by the WHO. As a result, the numbers are not comparable.

    This also results in some confusion. Our World in Data (OWID) does not even report testing numbers for Peru given the lack of up-to-date data on how much of the current testing involves PCR tests, whereas the positivity rate reported in the John Hopkins University site, at over 50%, is linked to the OWID data and appears outdated. The government itself reports a positivity rate of 19%, although given that this includes serology tests, the rate that is comparable to other countries would be much higher, giving Peru one of the highest positivity rates in the world. (Note that the WHO recommends a positivity rate of 5-12%).

    The problem with serology tests is also that they have a high rate of false negatives and antibody responses typically only develop one or more weeks after the onset of symptoms. Hence, while they are more effective than PCR tests for studying population prevalence, they are of relatively little use for diagnostic purposes of detecting cases with sufficient time to stop contagion, or what is known as epidemiological vigilance. The political decision of using predominantly serology tests is considered as one of the biggest mistakes of the COVID-19 response of the government and the new Minister of Health changed the strategy by gradually replacing serology with PCR tests in the second week of August.

  3. In effect, Peru has had one of the lowest levels of investment in health as percentage of GDP in Latin America (5% versus 6.6% on average) and this level increased only 0.27 percentage points between 2010 and 2016 despite rapid economic growth. It also has lower per capita spending on health ($679 USD), but with higher capital investment in health as percentage of GDP (0.32%), above the Latin American average (0.19%) – see pages 121, 127 and 139 here.
  4. For instance, in terms of the number of health professionals per 10,000 people, Lima (41.4), Callao (50.1), Arequipa (41.5), Tacna (44.3), Apurimac (48.9) have more than double to number of Piura (21.4), San Martin (21.8), Loreto (22.3), which have the lowest rates (see p.22 here).
  5. For some insights on this situation, see here, here, here, here, here, here and here.

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2 Comments
  • Gabriela Izurieta
    September 2, 2020

    Great analysis! We have a similar situation in Ecuador: the covid-crisis has exposed many vulnerabilities in our system. We were already facing austerity (for instance, last year government diminished health budget). And now that crisis is even worse: public sector workers are not receiving salaries (including teachers and doctors), unemployment is increasing and a great number of people are now on poverty. Yes, this crisis has exposed those vulnerabilities in our systems, and what’s even worse, it has deepened them.

  • Raquel H
    August 26, 2020

    Very interesting to understand and see reflected the peruvian reality! Hopefully the situation changes for the better