Cost-effectiveness and return on investment of protecting health workers in low- and middle-income countries during the COVID-19 pandemic

PLoS One. 2020 Oct 9;15(10):e0240503. doi: 10.1371/journal.pone.0240503. eCollection 2020.

Abstract

Background: In this paper, we predict the health and economic consequences of immediate investment in personal protective equipment (PPE) for health care workers (HCWs) in low- and middle-income countries (LMICs).

Methods: To account for health consequences, we estimated mortality for HCWs and present a cost-effectiveness and return on investment (ROI) analysis using a decision-analytic model with Bayesian multivariate sensitivity analysis and Monte Carlo simulation. Data sources included inputs from the World Health Organization Essential Supplies Forecasting Tool and the Imperial College of London epidemiologic model.

Results: An investment of $9.6 billion USD would adequately protect HCWs in all LMICs. This intervention would save 2,299,543 lives across LMICs, costing $59 USD per HCW case averted and $4,309 USD per HCW life saved. The societal ROI would be $755.3 billion USD, the equivalent of a 7,932% return. Regional and national estimates are also presented.

Discussion: In scenarios where PPE remains scarce, 70-100% of HCWs will get infected, irrespective of nationwide social distancing policies. Maintaining HCW infection rates below 10% and mortality below 1% requires inclusion of a PPE scale-up strategy as part of the pandemic response. In conclusion, wide-scale procurement and distribution of PPE for LMICs is an essential strategy to prevent widespread HCW morbidity and mortality. It is cost-effective and yields a large downstream return on investment.

MeSH terms

  • Bayes Theorem
  • Betacoronavirus / isolation & purification
  • COVID-19
  • Coronavirus Infections / economics
  • Coronavirus Infections / epidemiology
  • Coronavirus Infections / pathology*
  • Coronavirus Infections / virology
  • Cost-Benefit Analysis*
  • Developing Countries
  • Health Personnel / statistics & numerical data
  • Health Workforce / economics*
  • Humans
  • Monte Carlo Method
  • Pandemics / economics
  • Personal Protective Equipment / economics*
  • Personal Protective Equipment / supply & distribution
  • Pneumonia, Viral / economics
  • Pneumonia, Viral / epidemiology
  • Pneumonia, Viral / pathology*
  • Pneumonia, Viral / virology
  • SARS-CoV-2

Grants and funding

The authors received no specific funding for this work.