COVID-19 crisis: IMF told countries facing critical health worker shortages to cut spending on public sector employment

New analysis by ActionAid and Public Services International (PSI) reveals how International Monetary Fund (IMF) austerity policies restricted critical public employment in the lead up to the COVID-19 crisis.

23.06.20

The analysis (see Annex below), released to mark UN Public Service Day (23 June), shows that every single low income country which received IMF advice to cut or freeze public employment in the past three years had already been identified by the World Health Organisation (WHO) as facing a critical health worker shortage.

Key findings include:

  • Of the 57 countries last identified by the WHO as facing critical health worker shortages, 24 received advice from the IMF to cut or freeze public sector wages.
  • When countries are told to contain wage bills – it means fewer doctors, nurses and frontline workers in countries already desperately short of medics.
  • All but one of the 18 low-income countries advised by the IMF to cut or freeze public sector employment funding, are currently below the WHO’s recommended nurse-to-population threshold of 30 per 10,000
  • The WHO predicts that these countries will experience a collective shortage of at least 695,000 nurses by 2030.

The analysis shows tragic lessons from the Ebola crisis were not learnt. In Liberia, where understaffing and inadequate resourcing contributed to the deaths of over 300 health workers during the Ebola outbreak, the IMF recommended the country cut its public sector employment funding by 17%. This was despite Liberia having a nurse to citizen ratio of less than 6 per 10,000.

In Malawi, one of the low-income countries told to freeze spending on public sector wages, there are just four nurses per 10,000, well below the recommended 30. The WHO predicts that by 2030, Malawi will face nurse shortages of 40,000.

Yandura Chipeta from ActionAid Malawi said: “Nurses in Malawi went on strike in April over poor pay and lack of equipment to protect them from contracting coronavirus. Being offered a ‘risk allowance’ of an extra $1.50 a month felt like a slap in the face for health staff risking their lives in underfunded hospitals. The pandemic is exposing the urgent need for investment in our healthcare system, more nurses and doctors, and an end to harmful IMF austerity policies.”

ActionAid’s 2020 report Who Cares for the Future: Finance Gender-responsive Public Services exposed the detrimental IMF loan conditions and austerity measures which have pushed 78% of low-income countries to plan for zero increase in public sector wages.

The health systems of many developed countries with ratios significantly over the threshold –  such as the UK (77 per 10,000) or Italy (55 per 10,000) – have also struggled to cope with the ongoing COVID-19 outbreak, reinforcing the need for even greater investment.

Yet loan conditionality and austerity programs, which the IMF, World Bank and other institutions continue to peddle, consistently undermine this urgent need for expanded public health employment.

Michelle Higelin, Executive Director of ActionAid Australia, said: “Women are on the frontline of the COVID-19 crisis, as health workers, carers, home schoolers and informal workers. Without decent and adequately resourced public services, women will continue to bear the brunt of this and future crises. We have to start building economies that care for people and the planet, and investment in public services is essential as an important equaliser in addressing inequalities and resourcing women’s work.”

For more information & interviews: Liz Pick, Media Manager on 0422 105 840 or [email protected]

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Annex: The Analysis

The ActionAid/PSI Analysis draws from a range of key sources:

  1. WHO CARES FOR THE FUTURE (Action Aid 2020)
    In this report, released April 2020, ActionAid’s research team created a comparative analysis of countries where the IMF has given advice on public sector employment funding, based on data from the IMF.
  2. WHO List of Countries Facing Critical Health worker Shortages (2006)
    This is the WHO’s latest available country-specific list. It is currently being reviewed and our analysis will be updated when a new version is released, however we expect that the countries listed will not have significantly changed.
  3. WHO Nurse Threshold Figures (2018)
    We use the data contained within National Health Workforce Accounts to provide information on whether individual states are above or below Nurse Thresholds in any given year: all figures used are based on the most recent year available. In addition to these figures, we included the WHO’s projections on how many “missing nurses” (IE amount under the threshold) these countries are expected to have by 2030: in all cases we use the lower end of the projections.
  4. World Bank List of Low Income Countries (2020)
    The latest World Bank list contains 31 Low Income Countries: Afghanistan, Burundi, Benin, Burkina Faso, Central African Republic,  Dem. Rep Congo, Eritrea, Ethiopia, Guinea, Gambia, The Guinea-Bissau, Haiti, Liberia, Madagascar, Mali, Mozambique, Malawi, Niger, Nepal, Dem. People’s Rep Korea, Rwanda, Sierra Leone, Somalia, South Sudan, Syrian Arab Republic, Chad, Togo, Tajikistan, Tanzania, Uganda, Yemen. All of these countries were included in the analysis except for North Korea and Eritrea where insufficient data was available. Of these 31 countries, the IMF produced advice on Public Sector Wage Bill for 23, of which 18 were advised to cut or freeze public sector employment funding.

A comparative analysis of these data sets reveals:

  • Of the 57 countries last identified by the WHO as facing a critical health worker shortage, 24 received advice from the IMF to cut or freeze public sector employment funding, representing over a third of the total countries. (This also includes non-low income countries).
  • In the 3 years leading up to the Covid-19 outbreak, the IMF advised 18 Low Income Countries – 58% of all Low Income Countries or 78% of Low Income Countries where they gave advice -to cut or freeze funding for public sector employment
  • 17 of the 18 Low Income Countries advised by the IMF to cut or freeze public sector employment funding are currently below the WHO’s recommended Nurse-to-Population threshold of 30 per 10,000
  • The WHO predicts that the Low Income Countries where the IMF advised public sector funding cuts or freezes will experience a collective shortage of at least 695,000 nurses by 2030

 

Table: Low Income Countries where IMF advised Public Sector Employment Funding Cuts or Freezes

COUNTRY

Public Sector Wage Bill in 2019 as % of National GDP/ IMF steer (= cut = freeze)/ change forecast (as % of GDP)[1]

Nurses per 10,000 WHO recommended threshold is 30[2]

WHO estimate on nurse shortages by 2030[3]

LICs ADVISED TO CUT WAGE BILLS
Nepal

3.1 ⇩ (-1.0)

31

Above threshold

The Gambia

4.8 ⇩ (-0.3)

11.37

5,000

Sierra Leone

6.2 ⇩ (-0.9)

7.7

10,000

Chad

6.7 ⇩ (-1.3)

2.3

40,000

Burkina Faso

9.9 ⇩ (-1.5)

5.4

30,000

Liberia

10 ⇩ (-1.7)

5.3

10,000

Mozambique

11.6 ⇩ (-1.5)

4.8

90,000

LICS ADVISED TO FREEZE WAGE BILLS
Guinea-Conakry

3.6 ⬄

0.86

30,000

Uganda

3.9 ⬄

12.3

30,000

Centrafrique

4.7 ⬄

0.72

10,000

Tanzania

5.1 ⬄

5.8

100,000

Madagascar

5.7 ⬄

1.4

90,000

Mali

5.8 ⬄

2.7

50,000

Rwanda

5.8 ⬄

10.8

20,000

Benin

6.3 ⬄

2.9

30,000

Togo

6.7 ⬄

2.4

20,000

Malawi

7.4 ⬄

4.3

40,000

Afghanistan

13.1 ⬄

1.7

90,000

 TOTAL NURSES NEEDED BY 2030 IN COUNTRIES ADVISED TO CUT OR FREEZE WAGE BILLS  

695,000

Analysis Notes

We have compiled IMF advice on both cutting and freezing of public sector employment funding freeze across multiple years.  In reality, a freeze in funding amounts to an effective cut due to population expansion, inflation and other external factors.

When recommending cuts in overall public sector wage bills, in some cases the IMF suggests exemptions for health and education workers. However, in practice, as these workers are the largest group on most public sector wage bill, the effect is to block the recruitment of new teachers, nurses and doctors at the scale needed to address shortages. In addition, despite IMF assurances, the enormous pressure which the institution exerts to reduce spending has led governments to reduce the conditions of employment for workers in these sectors. For example, workers in the Liberian Health Sector have faced unexplained salary cuts and lack of payment as well as forced retirement after IMF spending advice to cut the public sector wage bill.

While the IMF claims that their advice on Public Sector employment funding is not a required condition or obligatory, the enormous pressure the institution exerts means governments often feel they have little choice. For example, one Liberian politician, responding to widespread discontent at public sector pay cuts, said the IMF was “telling us to bite the bullet” and feared any reversal of the cuts would jeopardize future loans.

Nepal is the only Low-Income Country which currently reports being above the WHO recommended nursing threshold, with 31,000 nurses per 10,000 reported in 2018. In 2017 Nepal reported just 17,000 nurses per thousand. Year on year data may not be entirely reliable. IMF advice to the Nepalese government to cut the public sector wage bill expanded across multiple years, including years in which the country reported being significantly under the recommended nursing threshold.

 

Footnotes:

[1] Source: Review of IMF country documents as contained within Who Cares Action Aid Report. All wage bill figures in % of GDP; change in percentage point shift anticipated from the 2019 data.

[2] Data from WHO’s National Health Workforce Accounts, 2018 https://apps.who.int/nhwaportal/Home/Index

[3] Data From State of the World’s Nursing 2020  https://apps.who.int/nhwaportal/Home/Index    – based on country pages. Figures always given as a range (e.g 40,000- 50,000 or 200,000 to 300,000). In all cases we have selected the lower figure so in fact the estimate could be about one third higher if we had included the upper range.