Cost-effectiveness Of Scenarios Research Articles

Achieving malaria testing and treatment targets for children under five in Mozambique: a cost-effectiveness analysis

BackgroundThe entire population of Mozambique is at risk for malaria, which remains one of the leading causes of death. The 2017–2022 National Malaria Strategic Plan focuses on reducing malaria morbidity and mortality in high- and low-transmission areas. This study aimed to estimate the costs and health benefits of six variations of the World Health Organization’s “test-and-treat” strategy among children under five.MethodsA decision tree model was developed that estimates the costs and health outcomes for children under five. Data on probabilities, costs, weights for disability-adjusted life years (DALYs), and quality-adjusted life years (QALYs) were based on peer-reviewed, grey literature, and primary data analysis of the 2018 Malaria Indicator Survey. Six scenarios were compared to the status quo and calculated the incremental cost-effectiveness ratio (ICER) in terms of cost per QALY gained, DALY averted, and life saved. Deterministic and probabilistic sensitivity analyses were conducted to understand the effect of parameter uncertainty on the findings.ResultsIn the base case, reaching the target of 100% testing with rapid diagnostic tests (RDTs; Scenario 1) is more cost-effective than improving the testing rate alone by 10% (Scenario 2). Achieving a 100% (Scenario 3) or a 10% increase in treatment rate (Scenario 4) have ICERs that are lower than Scenarios 1 and 2. Both Scenarios 5 and 6, which represent combinations of Scenarios 1–4, have lower ICERs than their constituent strategies on their own, which suggests that improvements in treatment are more cost-effective than improvements in testing alone. These results held when DALYs averted or lives saved were used as health outcomes. Deterministic and probabilistic sensitivity analyses revealed that the cost-effectiveness of Scenarios 1–6 are subject sensitive to parameter uncertainty, though Scenarios 4 and 5 are the optimal choice when DALYs averted or QALYs gained were used as the measure of health outcomes across all cost-effectiveness thresholds.ConclusionsImproving testing rates alone among children at risk for malaria has the potential to improve health but may not be the most efficient use of limited resources. Instead, small or large improvements in treatment, whether alone or in conjunction with improvements in testing, are the most cost-effective strategies for children under five in Mozambique.

320Applying novel multi-disciplinary methodologies to accelerate malaria elimination

Abstract Focus and outcomes for participants Presented by researchers from the Australian Centre of Research Excellence in Malaria Elimination (ACREME, www.acreme.org.au), the focus of the symposium will be the application of multi-disciplinary epidemiological and statistical approaches to inform the control and elimination of malaria in the Asia-Pacific region. The epidemiology of malaria is complex as it involves multiple mosquito vectors, different malarial species (that require species-specific treatments) and emerging insecticide and antimalarial drug resistance. The symposium will provide an overview of the significance of the changing epidemiological landscape of malaria globally, and how modern epidemiological methods, such as stepped-wedge designs, multi-state modelling, within-host mechanistic mathematical models, geospatial methods and cost-effectiveness modelling applied to clinical effectiveness trials, prospective cohort studies, volunteer infection studies and national and regional data have contributed to answering the key challenges in malaria research. Specifically we will discuss evidence for effective interventions to reduce the risk of malaria transmission, the effect of recurrent episodes of malaria on risk of hospitalisation and mortality, the selection of antimalarial drug combination therapies to fast track new drugs, understanding geospatial heterogeneity of malaria transmission, and the cost-effectiveness of scenarios using different treatment regimens. Discussion of the importance of these methodologies and their findings will be contextualised in the current global malaria elimination goals. As similar transformations in epidemiological environment have occurred in other disease elimination settings, we believe this symposium will have broad appeal and that the challenges faced and the methodological solutions proposed to accelerate progress in malaria elimination will have a high degree of relevance and be useful to researchers working in global health or infectious diseases. Rationale for the symposium, including for its inclusion in the Congress Following a two-decade period of declining malaria burden due to intensified control efforts, global progress against the disease has stalled, and in some countries, malaria has resurged. Emerging parasite resistance to insecticides and antimalarial drugs has reduced the effectiveness of cornerstone malaria control interventions. Malaria endemic areas of the Greater Mekong Sub region (GMS) have set the target to eliminate malaria by 2030, however, the failure of these established interventions and transition to low-transmission endemic environments has necessitated fundamental re-evaluation of the epidemiological landscape of the disease and emphasised timely development of robust evidence for novel interventions. In order to provide evidence, a wide range of advanced multi-disciplinary methodologies have been developed and applied in many malaria epidemiology areas and we believe discussion of these in the symposium will be highly relevant given the principal theme of the 2020 WCE (Methodological Innovations in Epidemiology). Additionally, the symposium will feature research where findings have been effectively translated to national and regional policy and practice, an important theme of the 2020 WCE. Presentation program Names of presenters

OPTIMIZATION PROCEDURE FOR COST EFFECTIVE BMP PLACEMENT AT A WATERSHED SCALE1

ABSTRACT: A combinatorial optimization procedure for best management practice (BMP) placement at the watershed level facilitates selection of cost effective BMP scenarios to control non point source (NFS) pollution. A genetic algorithm (GA) was selected from among several optimization heuristics. The GA combines an optimization component written in the C++ language with spatially variable NFS pollution prediction and economic analysis components written within the Arc View geographic information system. The procedure is modular in design, allowing for component modifications while maintaining the basic conceptual framework. An objective function was developed to lexicographically optimize pollution reduction followed by cost increase. Scenario cost effectiveness is then calculated for scenario comparisons. The NPS pollutant fitness score allows for evaluation of multiple pollutants, based on prioritization of each pollutant. The economic component considers farm level public and private costs, cost distribution, and land area requirements. Development of a sediment transport function, used with the Universal Soil Loss Equation, allows the optimization procedure to run within a reasonable timeframe. The procedure identifies multiple near optimal solutions, providing an indication of which fields have a more critical impact on overall cost effectiveness and flexibility in the final solution selected for implementation. The procedure was demonstrated for a 1,014‐ha watershed in the Ridge and Valley physiographic region of Virginia.