Attributable societal cost of antimicrobial resistance in Ghana: a microsimulation study focusing on sociodemographic groups

Objective We performed a microsimulation analysis predicting the societal cost of antimicrobial resistance (AMR), which represents the potential cost savings if Ghana eliminates AMR. Design This study combined bacterial resistance epidemiology and cost data from Ghana to perform a microsimulation analysis focusing on sociodemographic groups, predicting the potential societal cost savings should Ghana eliminate AMR. The nationally representative data were collected from 12 reference laboratories across Ghana’s three geographical belts between June 2021 and December 2023. Case definition was enterobacterial third-generation cephalosporin (3GC) resistant infections, methicillin-resistant Staphylococcus aureus (MRSA) and multidrug-resistant Mycobacterium tuberculosis. Using an adapted microsimulation framework, the simulation incorporated four integrated data modules: population demographics, infection epidemiology, healthcare resource use and expenditure and labour market characteristics. This approach allowed for the construction of synthetic individuals from national data sets and the projection of annual outcomes over a 7-year horizon. Costs were calculated from a societal perspective under a status quo scenario, assuming that admission rates, resistant infection probabilities and mortality rates remain the same. This analysis also considers a 2.1% annual population growth rate, a 5% discount rate for future costs and age-specific resistance risk profile. We stratified the outcome of interest by age groups, sex and wealth quintiles to account for distributional effects and reported the costs in purchasing power parity equivalent in international US dollars. Setting Ghana in West Africa. Participants A simulated population of AMR patients of all ages and sex. Main outcome measures Societal cost attributable to AMR in Ghana. Results Assuming probabilities of all-cause hospital admissions of 0.102 for females and 0.093 for males, along with probabilities of AMR infections of 0.239 and 0.193, we predicted nearly 78000 (95% CI 72000 to 83 520) annual AMR infections and approximately 6300 (95% CI 3900 to 8638) attributable deaths. MRSA and 3GC-resistant infections made up 20.2% and 79.2% of the predicted annual infections, corresponding to an estimated mean societal cost of about US$435million. In decreasing order of magnitude, the estimated mean annual cost of productivity loss due to AMR attributable mortality accounted for 40.6% of the mean annual societal cost, followed by the cost to healthcare providers (24.1%), direct medical cost to patients and caregivers (22.4%), productivity loss for surviving patients and caregivers (10.4%) and direct non-medical costs to patients and caregivers (2.6%). Resistant infections in children under 5 and adults over 60 years contributed 48.2% and 26.9% of the estimated annual societal cost, respectively. Except for the number of resistant infections, the estimated mean annual costs between wealth quintile groups were significantly different (p=0.03) due to differences in productivity costs between wealth quintile groups. Conclusion The study shows that the societal cost implications attributable to AMR are enormous, requiring a concerted effort by society to mitigate the development and spread of AMR organisms.