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Table 4 Studies reporting the economic burden of antimicrobial resistance from a societal perspective, 2012–2016

From: Using the best available data to estimate the cost of antimicrobial resistance: a systematic review

Author (year)

Country

Organism

Comparators

Site of infection

Methodology

Excess LOS (days)

Cost drivers

Type of costs (year of cost data) Currency

Excess cost, significance

Taylor (2010)

Global

2010 [21]

S. aureus, E. coli, K. pneumoniae, HIV, malaria, TB

MRSA

3GC-E.coli

3GC-K. pneumoniae

Resistant HIV

Resistant malaria

MDR-TB

BSI, UTI, Lower RTI, SSTI

Theoretical dynamic general equilibrium was used to predict future scenarios of incidence and resistance (0%, current rates, 5, 40, 100% resistance) starting with the population in 2010 and projecting to 2050.

Costs: (a) increased mortality (b) increased morbidity due to prolonged period of sickness leading to productivity loss

Assumptions: (i) Resistance rates increase in a one-off step, not an S-shaped epidemic pattern (ii) Incidence remains constant until 2050 (except malaria where it was projected) (iii) Extra LOS was assumed to be the same for all countries/regions (iv) Mortality risk per infection remained unchanged

Mean excess LOS from the WHO Observatory (2014)

Loss of productivity

Disruption to the supply of labour by increased mortality and morbidity measured as reduction in GDP (2011) US

Current cost:

US$5.8 trillion

Excess cost (over 40 yrs):

Loss of

US$2.1- $124.5 trillion

KPMG (2014)

156 countries

Data sourced from various publication with the latest from year 2012 [22]

S. aureus, E. coli, K. pneumoniae, HIV, malaria, TB

Susceptible versus

Resistant

BSI

Lower RTI

SSTI

UTI

Total factor productivity model used to compute macroeconomic stability, technology, quality of infrastructure, human capital and strength of public institutions.

Life expectancy used as a proxy to measure the quality of human capital and adjustments to country life expectancy score were made to allow for deterioration of human capital as result of increased AMR incidence.

Labour force was based on working age (15–64) and adjusted to AMR mortality rate

Costs: (a) attributable mortality (b) increased morbidity leading to productivity loss.

Assumptions: (i) Correction coefficient used to estimate resistance rate by site of infection was assumed to be the same for all countries/ regions (ii) Extra LOS analysed for EU, Iceland and Norway only (iii) Mortality risk per infection remained unchanged

Combined

(S. aureus + E. coli + K. pneumonia): 4 mil bed-days in 2012

Loss of productivity + cost of hospital bed-days

Impact on labour force and human capital measured as reduction in GDP (2012) EURO

Excess cost:

+€1.6 billion

Global GDP loss (2050):

40% resistant: 1.66%

100% resistant: 3.4%

  1. KP K. pneumonia, TB Mycobacterium tuberculosis, 3GC Third-generation cephalosporin resistant, BSI Bloodstream infection, UTI Urinary tract infection, RTI Respiratory tract infection, SSTI Skin and soft tissue infection, LOS Length of stay, GDP Gross domestic product