Modeling the Economic Impact of Substandard and Falsified Antimalarials in the Democratic Republic of the Congo

Abstract

Substandard and falsified medicines pose significant risks to global health, including increased deaths, prolonged treatments, and growing drug resistance. Antimalarials are one of the most common medications to be of poor quality in low-and middle-income countries. We assessed the health and economic impact of substandard and falsified antimalarials for children less than 5 years of age in the Democratic Republic of the Congo, which has one of the world's highest malaria mortality rates. We developed an agent-based model to simulate patient care-seeking behavior and medicine supply chain processes to examine the impact of antimalarial quality in Kinshasa province and Katanga region. We simulated the impact of potential interventions to improve medicinal quality, reduce stockouts, or educate caregivers. We estimated that substandard and falsified antimalarials are responsible for $20.

Importance of medicine quality in achieving universal health coverage

“…To illustrate the potential health and economic impact that can result from ensuring the quality of antimalarials, we analyzed the current landscape of the impact of poor-quality antimalarials in a case study. Four countries were included in our analysis: the Democratic Republic of the Congo (DRC), Nigeria, Uganda, and Zambia [26][27][28]. Malaria is associated with high levels of morbidity and mortality in LMICs, and medicines to treat malaria (i.e.…”

“…Estimates of country-specific impact were obtained from the Substandard and Falsified Antimalarial Research Impact (SAFARI) model, an agent-based model we built that simulates malaria disease progression, care seeking, and outcomes for children under age five [26][27][28]. The SAFARI model was adapted and run separately for each country using country-specific demographic and epidemiological inputs.…”

“…The SAFARI model was adapted and run separately for each country using country-specific demographic and epidemiological inputs. Methods for the development of the SAFARI model and individual country data are described in detail in other publications [26][27][28]. We PLOS ONE simulated child agents who sought malaria treatment and received either quality-assured or poor-quality antimalarials.…”

Tackling the blind spot of poor-quality medicines in Universal Health Coverage

“…A review of modelling studies show that poor-quality medicines can result in serious harm and large inefficiencies which can be pitfalls to UHC, as shown in Tables 1 and 3 [15,[17][18][19][20][21][22]. The estimated economic losess from SF anti-malarials alone constitute a significant portion of the national budget for impacted countries (Table 1).…”

“…The estimated economic losess from SF anti-malarials alone constitute a significant portion of the national budget for impacted countries (Table 1). In Congo, for example, the estimated USD 151 million loss equals 2.5% of the USD 5.9 billion 2019 national budget [21,23] . In Uganda, the USD 31 million loss is about 5% of the USD 637 million Health Budget for 2019/2020 [22,30].…”