Educational and economic returns to cognitive ability in low- and middle-income countries: A systematic review.

There is growing interest to use early cognitive ability to predict schooling and employment outcomes in low- and middle-income countries (LMICs). Rather than using educational attainment and school enrollment as predictors of future economic growth or of improving an individual's earning potential, mounting evidence suggests that cognitive ability may be a better predictor. The relationship between cognitive ability, education, and employment are essential to predict future development in LMICs. We performed a systematic literature review and meta-analysis of the evidence regarding the relationship between cognitive ability and educational outcomes, and between cognitive ability and economic outcomes across LMICs. We searched peer-reviewed studies since 2000 that quantitatively measured these relationships. Based on an initial search of 3,766 records, we identified 14 studies, including 8 studies that examined the cognition-education link and 8 studies that assessed cognition-employment returns in LMICs. Identified studies showed that higher cognitive ability increased the probability of school enrollment, academic achievement, and educational attainment across LMICs. A meta-analysis of returns to wages from cognitive ability suggested that a standard deviation increase in cognitive test scores was associated with a 4.5% (95% CI 2.6%-9.6%) increase in wages. Investments into early cognitive development could play a critical role in improving educational and economic outcomes in LMICs. Further research should focus particularly in low-income countries with the least evidence, and examine the impact on education and economic outcomes by cognitive domains to provide more robust evidence for policy makers to take action.

Cost savings of paper analytical devices (PADs) to detect substandard and falsified antibiotics: Kenya case study.

BACKGROUND: Over 10% of antibiotics in low- and middle-income countries (LMICs) are substandard or falsified. Detection of poor-quality antibiotics via the gold standard method, high-performance liquid chromatography (HPLC), is slow and costly. Paper analytical devices (PADs) and antibiotic paper analytical devices (aPADs) have been developed as an inexpensive way to estimate antibiotic quality in LMICs. AIM: To model the impact of using a rapid screening tools, PADs/aPADs, to improve the quality of amoxicillin used for treatment of childhood pneumonia in Kenya. METHODS: We developed an agent-based model, ESTEEM (Examining Screening Technologies with Economic Evaluations for Medicines), to estimate the effectiveness and cost savings of incorporating PADs and aPADs in amoxicillin quality surveillance in Kenya. We compared the current testing scenario (batches of entire samples tested by HPLC) with an expedited HPLC scenario (testing smaller batches at a time), as well as a screening scenario using PADs/aPADs to identify poor-quality amoxicillin followed by confirmatory analysis with HPLC. RESULTS: Scenarios using PADs/aPADs or expedited HPLC yielded greater incremental benefits than the current testing scenario by annually averting 586 (90% uncertainty range (UR) 364-874) and 221 (90% UR 126-332) child pneumonia deaths, respectively. The PADs/aPADs screening scenario identified and removed poor-quality antibiotics faster than the expedited or regular HPLC scenarios, and reduced costs significantly. The PADs/aPADs scenario resulted in an incremental return of $14.9 million annually compared with the reference scenario of only using HPLC. CONCLUSION: This analysis shows the significant value of PADs/aPADs as a medicine quality screening and testing tool in LMICs with limited resources.

Impact of substandard and falsified antimalarials in Zambia: application of the SAFARI model.

BACKGROUND: Many countries are striving to become malaria-free, but global reduction in case estimates has stagnated in recent years. Substandard and falsified medicines may contribute to this lack of progress. Zambia aims to eliminate their annual burden of 1.2 million pediatric malaria cases and 2500 child deaths due to malaria. We examined the health and economic impact of poor-quality antimalarials in Zambia. METHODS: An agent-based model, Substandard and Falsified Antimalarial Research Impact (SAFARI), was modified and applied to Zambia. The model was developed to simulate population characteristics, malaria incidence, patient care-seeking, disease progression, treatment outcomes, and associated costs of malaria for children under age five. Zambia-specific demographic, epidemiological, and cost inputs were extracted from the literature. Simulations were run to estimate the health and economic impact of poor-quality antimalarials, the effect of potential artemisinin resistance, and six additional malaria focused policy interventions. RESULTS: We simulated annual malaria cases among Zambian children under five. At baseline, we found 2610 deaths resulting in $141.5 million in annual economic burden of malaria. We estimated that elimination of substandard and falsified antimalarials would result in an 8.1% (n = 213) reduction in under-five deaths, prevent 937 hospitalizations, and realize $8.5 million in economic savings, annually. Potential artemisinin resistance could further increase deaths by 6.3% (n = 166) and cost an additional $9.7 million every year. CONCLUSIONS: Eliminating substandard and falsified antimalarials is an important step towards a malaria-free Zambia. Beyond the dissemination of insecticide-treated bed nets, indoor residual spraying, and other malaria control measures, attention must also be paid to assure the quality of antimalarial treatments.

An investment case for maternal and neonatal tetanus elimination.

INTRODUCTION: Globally, 13 countries have yet to eliminate maternal and neonatal tetanus. While efforts have improved access to tetanus toxoid containing vaccines (TTCVs) and increased clean delivery practices, reaching elimination targets (<1 case of neonatal tetanus per 1000 live births per district per year) may require significant resources to reach the remaining high risk and hard-to-reach districts. METHODS: We estimated the cost to achieve maternal and neonatal tetanus elimination (MNTE) in three years in the remaining 13 countries: Afghanistan, Angola, Central African Republic, Democratic Republic of the Congo, Guinea, Mali, Nigeria, Pakistan, Papua New Guinea, Somalia, South Sudan, Sudan, and Yemen. Costs were estimated for: (1) vaccination campaigns using standard TTCVs and TT-Uniject™ targeting women of reproductive age in high risk areas, (2) additional vaccinations delivered to pregnant women at antenatal care (ANC) clinics, (3) clean delivery and umbilical cord care promotion, (4) neonatal tetanus surveillance strengthening, and (5) validation activities. We forecasted the averted mortality to assess the cost-effectiveness of achieving MNTE. RESULTS: It will cost an estimated US$197.7 million to realize MNTE over three years. These costs include $161.4 million for vaccination campaigns, $6.1 million for routine vaccination during ANC, $23.3 million for promotion of clean delivery practices, $4 million for surveillance, and $3 million for validation of MNTE. Achieving MNTE will avert approximately 70,000 neonatal deaths over ten years of vaccine protection, resulting in approximately 4.4 million life years gained. It will cost $2,900 per death averted and $45 per life year gained. CONCLUSION: Maternal and neonatal tetanus can be eliminated with significant financial investment, high prioritization, and strong political will. While substantial costs must be incurred to reach hard-to-reach populations, MNTE should be accomplished as a matter of health equity, and will significantly contribute to reaching the United Nations' Sustainable Development Goals.

Poor-quality antimalarials further health inequities in Uganda.

Substandard and falsified medications are a major threat to public health, directly increasing the risk of treatment failure, antimicrobial resistance, morbidity, mortality and health expenditures. While antimalarial medicines are one of the most common to be of poor quality in low- and middle-income countries, their distributional impact has not been examined. This study assessed the health equity impact of substandard and falsified antimalarials among children under five in Uganda. Using a probabilistic agent-based model of paediatric malaria infection (Substandard and Falsified Antimalarial Research Impact, SAFARI model), we examine the present day distribution of the burden of poor-quality antimalarials by socio-economic status and urban/rural settings, and simulate supply chain, policy and patient education interventions. Patients incur US$26.1 million (7.8%) of the estimated total annual economic burden of substandard and falsified antimalarials, including $2.3 million (9.1%) in direct costs and $23.8 million (7.7%) in productivity losses due to early death. Poor-quality antimalarials annually cost $2.9 million to the government. The burden of the health and economic impact of malaria and poor-quality antimalarials predominantly rests on the poor (concentration index -0.28) and rural populations (98%). The number of deaths among the poorest wealth quintile due to substandard and falsified antimalarials was 12.7 times that of the wealthiest quintile, and the poor paid 12.1 times as much per person in out-of-pocket payments. Rural populations experienced 97.9% of the deaths due to poor-quality antimalarials, and paid 10.7 times as much annually in out-of-pocket expenses compared with urban populations. Our simulations demonstrated that interventions to improve medicine quality could have the greatest impact at reducing inequities, and improving adherence to antimalarials could have the largest economic impact. Substandard and falsified antimalarials have a significant health and economic impact, with greater burden of deaths, disability and costs on poor and rural populations, contributing to health inequities in Uganda.

The economic impact of substandard and falsified antimalarial medications in Nigeria.

INTRODUCTION: Substandard and falsified medications pose significant risks to global health. Nearly one in five antimalarials circulating in low- and middle-income countries are substandard or falsified. We assessed the health and economic impact of substandard and falsified antimalarials on children under five in Nigeria, where malaria is endemic and poor-quality medications are commonplace. METHODS: We developed a dynamic agent-based SAFARI (Substandard and Falsified Antimalarial Research Impact) model to capture the impact of antimalarial use in Nigeria. The model simulated children with background characteristics, malaria infections, patient care-seeking, disease progression, treatment outcomes, and incurred costs. Using scenario analyses, we simulated the impact of substandard and falsified medicines, antimalarial resistance, as well as possible interventions to improve the quality of treatment, reduce stock-outs, and educate caregivers about antimalarial quality. RESULTS: We estimated that poor quality antimalarials are responsible for 12,300 deaths and $892 million ($890-$893 million) in costs annually in Nigeria. If antimalarial resistance develops, we simulated that current costs of malaria could increase by $839 million (11% increase, $837-$841 million). The northern regions of Nigeria have a greater burden as compared to the southern regions, with 9,700 deaths and $698 million ($697-$700 million) in total economic losses annually due to substandard and falsified antimalarials. Furthermore, our scenario analyses demonstrated that possible interventions-such as removing stock-outs in all facilities ($1.11 billion), having only ACTs available for treatment ($594 million), and 20% more patients seeking care ($469 million)-can save hundreds of millions in costs annually in Nigeria. CONCLUSIONS: The results highlight the significant health and economic burden of poor quality antimalarials in Nigeria, and the impact of potential interventions to counter them. In order to reduce the burden of malaria and prevent antimalarials from developing resistance, policymakers and donors must understand the problem and implement interventions to reduce the impact of ineffective and harmful antimalarials.

Development of an agent-based model to assess the impact of substandard and falsified anti-malarials: Uganda case study.

BACKGROUND: Global efforts to address the burden of malaria have stagnated in recent years with malaria cases beginning to rise. Substandard and falsified anti-malarial treatments contribute to this stagnation. Poor quality anti-malarials directly affect health outcomes by increasing malaria morbidity and mortality, as well as threaten the effectiveness of treatment by contributing to artemisinin resistance. Research to assess the scope and impact of poor quality anti-malarials is essential to raise awareness and allocate resources to improve the quality of treatment. A probabilistic agent-based model was developed to provide country-specific estimates of the health and economic impact of poor quality anti-malarials on paediatric malaria. This paper presents the methodology and case study of the Substandard and Falsified Antimalarial Research Impact (SAFARI) model developed and applied to Uganda. RESULTS: The total annual economic impact of malaria in Ugandan children under age five was estimated at US$614 million. Among children who sought medical care, the total economic impact was estimated at $403 million, including $57.7 million in direct costs. Substandard and falsified anti-malarials were a significant contributor to this annual burden, accounting for $31 million (8% of care-seeking children) in total economic impact involving $5.2 million in direct costs. Further, 9% of malaria deaths relating to cases seeking treatment were attributable to poor quality anti-malarials. In the event of widespread artemisinin resistance in Uganda, we simulated a 12% yearly increase in costs associated with paediatric malaria cases that sought care, inflicting $48.5 million in additional economic impact annually. CONCLUSIONS: Improving the quality of treatment is essential to combat the burden of malaria and prevent the development of drug resistance. The SAFARI model provides country-specific estimates of the health and economic impact of substandard and falsified anti-malarials to inform governments, policy makers, donors and the malaria community about the threat posed by poor quality medicines. The model findings are useful to illustrate the significance of the issue and inform policy and interventions to improve medicinal quality.

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

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 $20.9 million (35% of $59.6 million; 95% CI: $20.7-$21.2 million) in malaria costs in Kinshasa province and $130 million (43% of $301 million; $129-$131 million) in malaria costs in the Katanga region annually. If drug resistance to artemisinin were to develop, total annual costs of malaria could increase by $17.9 million (30%; $17.7-$18.0 million) and $73 million (24%; $72.2-$72.8 million) in Kinshasa and Katanga, respectively. Replacing substandard and falsified antimalarials with good quality medicines had a larger impact than interventions that prevented stockouts or educated caregivers. The results highlight the importance of improving access to good quality antimalarials to reduce the burden of malaria and mitigate the development of antimalarial resistance.

Prevalence and Estimated Economic Burden of Substandard and Falsified Medicines in Low- and Middle-Income Countries: A Systematic Review and Meta-analysis.

Importance: Substandard and falsified medicines burden health systems by diverting resources to ineffective or harmful therapies, causing medical complications and prolonging illnesses. However, the prevalence and economic impact of poor-quality medicines is unclear. Objective: To conduct a systematic review and meta-analysis to assess the prevalence and estimated economic burden of substandard and falsified essential medicines in low- and middle-income countries. Data Sources: Five databases (PubMed, EconLit, Global Health, Embase, and Scopus) were searched from inception until November 3, 2017. Study Selection: Publications were assessed to determine whether they examined medicine quality and the prevalence and/or economic burden of substandard and falsified medicines in low- and middle-income countries. Studies with a sample size of 50 or more were included in the meta-analysis. Data Extraction and Synthesis: The study is registered in PROSPERO and reported via the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines. Study quality was assessed using an adapted Medicine Quality Assessment Reporting Guidelines scoring metric. Multiple reviewers conducted the data extraction and quality assessment independently. Main Outcomes and Measures: Prevalence and/or estimated economic impact of substandard and falsified medicines. Results: Two hundred sixty-five studies that estimated the prevalence of poor-quality essential medicines in low- and middle-income countries were identified. Among 96 studies that tested 50 samples or more (67 839 total drug samples), overall prevalence of poor-quality medicines was 13.6% (95% CI, 11.0%-16.3%), with regional prevalence of 18.7% in Africa (95% CI, 12.9%-24.5%) and 13.7% in Asia (95% CI, 8.2%-19.1%). Of studies included in the meta-analysis, 19.1% (95% CI, 15.0%-23.3%) of antimalarials and 12.4% (95% CI, 7.1%-17.7%) of antibiotics were substandard or falsified. Eight approximations of the economic impact, focused primarily on market size, with poor or undisclosed methods in estimation were identified, ranging from $10 billion to $200 billion. Conclusions and Relevance: Poor-quality essential medicines are a substantial and understudied problem. Methodological standards for prevalence and rigorous economic studies estimating the burden beyond market size are needed to accurately assess the scope of the issue and inform efforts to address it. Global collaborative efforts are needed to improve supply-chain management, surveillance, and regulatory capacity in low- and middle-income countries to reduce the threat of poor-quality medicines. Trial Registration: PROSPERO Identifier: CRD42017080266.