Comparing the cost of non-metastatic breast cancer care in a low-income vs a high-income country: A plea for an optimal allocation of health resources in Sub-Saharan Africa.
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ABSTRACT:
SUBMITTER: Brandao M
PROVIDER: S-EPMC7930606 | biostudies-literature | 2021 Feb
REPOSITORIES: biostudies-literature
Publications
Comparing the cost of non-metastatic breast cancer care in a low-income vs a high-income country: A plea for an optimal allocation of health resources in Sub-Saharan Africa.
Brandão Mariana M Morais Samantha S Guisseve Assucena A Bata Genoveva G Borges Marina M Tulsidás Satish S Pereira Susana S Carrilho Carla C Lunet Nuno N
Breast (Edinburgh, Scotland) 20210222
Breast cancer incidence is rising in low-income countries, but there is limited information regarding health resource allocation for its care. We assessed the cost of care during the first three years after diagnosis in a low-income country (Mozambique; n = 162 women) and compared it with a high-income country (Portugal, n = 703 women). Local currency prices were converted to 2019 international dollars (Int$). In Mozambique, the median cost was lower than in Portugal (2888 vs 18,533 Int$, respec ...[more]
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Project description:BACKGROUND:Health resources are limited, which means spending should be focused on the people, places and programs that matter most. Choosing the mix of programs to maximize a health outcome is termed allocative efficiency. Here, we extend the methodology of allocative efficiency to answer the question of how resources should be distributed among different geographic regions. METHODS:We describe a novel geographical optimization algorithm, which has been implemented as an extension to the Optima HIV model. This algorithm identifies an optimal funding of services and programs across regions, such as multiple countries or multiple districts within a country. The algorithm consists of three steps: (1) calibrating the model to each region, (2) determining the optimal allocation for each region across a range of different budget levels, and (3) finding the budget level in each region that minimizes the outcome (such as reducing new HIV infections and/or HIV-related deaths), subject to the constraint of fixed total budget across all regions. As a case study, we applied this method to determine an illustrative allocation of HIV program funding across three representative oblasts (regions) in Ukraine (Mykolayiv, Poltava, and Zhytomyr) to minimize the number of new HIV infections. RESULTS:Geographical optimization was found to identify solutions with better outcomes than would be possible by considering region-specific allocations alone. In the case of Ukraine, prior to optimization (i.e. with status quo spending), a total of 244,000 HIV-related disability-adjusted life years (DALYs) were estimated to occur from 2016 to 2030 across the three oblasts. With optimization within (but not between) oblasts, this was estimated to be reduced to 181,000. With geographical optimization (i.e., allowing reallocation of funds between oblasts), this was estimated to be further reduced to 173,000. CONCLUSIONS:With the increasing availability of region- and even facility-level data, geographical optimization is likely to play an increasingly important role in health economic decision making. Although the largest gains are typically due to reallocating resources to the most effective interventions, especially treatment, further gains can be achieved by optimally reallocating resources between regions. Finally, the methods described here are not restricted to geographical optimization, and can be applied to other problems where competing resources need to be allocated with constraints, such as between diseases.
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Project description:Nutrient intake is often measured with substantial error both in commonly used surrogate instruments such as a food frequency questionnaire (FFQ) and in gold standard-type instruments such as a diet record (DR). If there is a correlated error between the FFQ and DR, then standard measurement error correction methods based on regression calibration can produce biased estimates of the regression coefficient (?) of true intake on surrogate intake. However, if a biomarker exists and the error in the biomarker is independent of the error in the FFQ and DR, then the method of triads can be used to obtain unbiased estimates of ?, provided that there are replicate biomarker data on at least a subsample of validation study subjects. Because biomarker measurements are expensive, for a fixed budget, one can use a either design where a large number of subjects have one biomarker measure and only a small subsample is replicated or a design that has a smaller number of subjects and has most or all subjects validated. The purpose of this paper is to optimize the proportion of subjects with replicated biomarker measures, where optimization is with respect to minimizing the variance of ln(??). The methodology is illustrated using vitamin C intake data from the European Prospective Investigation into Cancer and Nutrition study where plasma vitamin C is the biomarker. In this example, the optimal validation study design is to have 21% of subjects with replicated biomarker measures.
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Project description:Several dengue vaccines are under development, and some are expected to become available imminently. Concomitant with the anticipated release of these vaccines, vaccine allocation strategies for dengue-endemic countries in Southeast Asia and Latin America are currently under development. We developed a model of dengue transmission that incorporates the age-specific distributions of dengue burden corresponding to those in Thailand and Brazil, respectively, to determine vaccine allocations that minimize the incidence of dengue hemorrhagic fever, taking into account limited availability of vaccine doses in the initial phase of production. We showed that optimal vaccine allocation strategies vary significantly with the demographic burden of dengue hemorrhagic fever. Consequently, the strategy that is optimal for one country may be sub-optimal for another country. More specifically, we showed that, during the first years following introduction of a dengue vaccine, it is optimal to target children for dengue mass vaccination in Thailand, whereas young adults should be targeted in Brazil.
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Project description:Nodding syndrome has affected and led to the deaths of children between the ages of 5 and 15 in Northern Uganda since 2009. There is no reliable explanation of the disease, and currently the only treatment is through a nutritional programme of vitamins, combined with medication to prevent symptoms. In the absence of a proper medical treatment, we develop a dynamic compartmental model to plan the management of the syndrome and to curb its effects. We use incidence data from 2012 and 2013 from Pader, Lamwo and Kitgum regions of Uganda to parameterize the model. The model is then used to look at how to best plan the nutritional programme in terms of first getting children on to the programme through outreach, and then making sure they remain on the programme, through follow-up. For the current outbreak of nodding disease, we estimate that about half of available resources should be put into outreach. We show how to optimize the balance between outreach and follow-up in this particular example, and provide a general methodology for allocating resources in similar situations. Given the uncertainty of parameter estimates in such situations, we perform a robustness analysis to identify the best investment strategy. Our analysis offers a way of using available data to determine the best investment strategy of controlling nodding syndrome.
| S-EPMC5347997 | biostudies-literature
Project description:IntroductionThe Short Form Survey 12-item (SF12) mental and physical health version has been applied in several studies on populations from Sub-Saharan Africa. However, the SF12 has not been computed and validated for these populations. We address in this paper these gaps in the literature and use a health intervention example in Malawi to show the importance of our analysis for health policy.MethodsWe firstly compute the weights of the SF12 physical and mental health measure for the Malawian population using principal component analysis on a sample of 2838 adults from wave four (2006) of Malawian Longitudinal Study of Aging (MLSFH). We secondly test the construct validity of our computed and the US-population weighted SF12 measures using regression analysis and Fixed Effect estimation on waves four, seven (2012) and eight (2013) of the MLSFH. Finally, we use a Malawian cash transfer programme to exemplify the implications of using US- and Malawi-weighted SF12 mental health measures in policy evaluation.ResultsWe find that the Malawian SF12 health measure weighted by our computed Malawian population weights is strongly associated with other mental health measures (Depression:-0.501, p = < 0.001; Anxiety:-1.755; p = < 0.001) and shows better construct validity in comparison to the US-weighted SF12 mental health component (rs = 0.675 versus rs = 0.495). None of the SF12 measures shows strong associations with other measures of physical health. The estimated average effect of the cash transfer is significant when using the Malawi-weighted SF12 mental health measure (treatment effect: 1.124; p = < 0.1), but not when using the US-weighted counterpart (treatment effect: 1.129; p > 0.1). The weightings affect the size of the impacts across mental health quantiles suggesting that the weighting scheme matters for empirical health policy analysis.ConclusionMental health shows more pronounced associations with the physical health dimension in a Low-Income Country like Malawi compared to the US. This is important for the construct validity of the SF12 health measures and has strong implications in health policy analysis. Further analysis is required for the physical health dimension of the SF12.
| S-EPMC7081543 | biostudies-literature
Project description:This paper presents a simple bi-level multi-objective linear program (BLMOLP) with a hierarchical structure consisting of reservoir managers and several water use sectors under a multi-objective framework for the optimal allocation of limited water resources. Being the upper level decision makers (i.e., leader) in the hierarchy, the reservoir managers control the water allocation system and tend to create a balance among the competing water users thereby maximizing the total benefits to the society. On the other hand, the competing water use sectors, being the lower level decision makers (i.e., followers) in the hierarchy, aim only to maximize individual sectoral benefits. This multi-objective bi-level optimization problem can be solved using the simultaneous compromise constraint (SICCON) technique which creates a compromise between upper and lower level decision makers (DMs), and transforms the multi-objective function into a single decision-making problem. The bi-level model developed in this study has been applied to the Swat River basin in Pakistan for the optimal allocation of water resources among competing water demand sectors and different scenarios have been developed. The application of the model in this study shows that the SICCON is a simple, applicable and feasible approach to solve the BLMOLP problem. Finally, the comparisons of the model results show that the optimization model is practical and efficient when it is applied to different conditions with priorities assigned to various water users.
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Project description:IntroductionGreat strides in responding to the HIV epidemic have led to improved access to and uptake of HIV services in Guyana, a lower-middle-income country with a generalized HIV epidemic. Despite efforts to scale up HIV treatment and adopt the test and start strategy, little is known about costs of HIV services across the care cascade.MethodsWe collected cost data from the national laboratory and nine selected treatment facilities in five of the country's ten Regions, and estimated the costs associated with HIV testing and services (HTS) and antiretroviral therapy (ART) from a provider perspective from January 1, 2016 to December 31, 2016. We then used the unit costs to construct four resource allocation scenarios. In the first two scenarios, we calculated how close Guyana would currently be to its 2020 targets if the allocation of funding across programs and regions over 2017-2020 had (a) remained unchanged from latest-reported levels, or (b) been optimally distributed to minimize incidence and deaths. In the next two, we estimated the resources that would have been required to meet the 2020 targets if those resources had been distributed (a) according to latest-reported patterns, or (b) optimally to minimize incidence and deaths.ResultsThe mean cost per test was US$15 and the mean cost per person tested positive was US$796. The mean annual cost per of maintaining established adult and pediatric patients on ART were US$428 and US$410, respectively. The mean annual cost of maintaining virally suppressed patients was US$648. Cost variation across sites may suggest opportunities for improvements in efficiency, or may reflect variation in facility type and patient volume. There may also be scope for improvements in allocative efficiency; we estimated a 28% reduction in the total resources required to meet Guyana's 2020 targets if funds had been optimally distributed to minimize infections and deaths.ConclusionsWe provide the first estimates of costs along the HIV cascade in the Caribbean and assessed efficiencies using novel context-specific data on the costs associated with diagnostic, treatment, and viral suppression. The findings call for better targeting of services, and efficient service delivery models and resource allocation, while scaling up HIV services to maximize investment impact.
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Project description:Rabies causes more than 24 000 human deaths annually in Sub-Saharan Africa. The World Health Organization recommends annual canine vaccination campaigns with at least 70% coverage to control the disease. While previous studies have considered optimal coverage of animal rabies vaccination, variation in the frequency of vaccination campaigns has not been explored. To evaluate the cost-effectiveness of rabies canine vaccination campaigns at varying coverage and frequency, we parametrized a rabies virus transmission model to two districts of northwest Tanzania, Ngorongoro (pastoral) and Serengeti (agro-pastoral). We found that optimal vaccination strategies were every 2 years, at 80% coverage in Ngorongoro and annually at 70% coverage in Serengeti. We further found that the optimality of these strategies was sensitive to the rate of rabies reintroduction from outside the district. Specifically, if a geographically coordinated campaign could reduce reintroduction, vaccination campaigns every 2 years could effectively manage rabies in both districts. Thus, coordinated campaigns may provide monetary savings in addition to public health benefits. Our results indicate that frequency and coverage of canine vaccination campaigns should be evaluated simultaneously and tailored to local canine ecology as well as to the risk of disease reintroduction from surrounding regions.
| S-EPMC5124087 | biostudies-literature
Project description:BackgroundSubstantial progress has been achieved in managing childhood cancers in many high-income countries (HICs). In contrast, survival rates in lower-middle-income countries (LMICs) are less favorable. Here, we aimed to compare outcomes and associated factors between two large institutions; Egypt (LMIC) and Germany (HIC).MethodsA retrospective review was conducted on newly diagnosed children with cancer between 2006 and 2010 in the departments of pediatric oncology at the South Egypt Cancer Institute (SECI) (n = 502) and the University Hospital of Cologne-Uniklinik Köln (UKK) (n = 238). Characteristics including age, sex, diagnosis, travel time from home to the cancer center, the time interval from initial symptoms to the start of treatment, treatment-related complications, compliance, and outcome were analyzed. A Cox proportional hazards regression model was applied to investigate the influence of risk factors.ResultsThe most common diagnoses in SECI were leukemia (48.8%), lymphomas (24.1%), brain tumors (1%), and other solid tumors (24.7%), compared to 22.3%, 19.3%, 28.6%, and 26.5% in UKK, respectively. Patients from SECI were younger (5.2 vs. 9.0 years, P < 0.001), needed longer travel time to reach the treatment center (1.44 ± 0.07 vs. 0.53 ± 0.03 h, P < 0.001), received therapy earlier (7.53 ± 0.59 vs. 12.09 ± 1.01 days, P = 0.034), showed less compliance (85.1% vs. 97.1%, P < 0.001), and relapsed earlier (7 vs. 12 months, P = 0.008). Deaths in SECI were more frequent (47.4% vs. 18.1%) and caused mainly by infection (60% in SECI, 7% in UKK), while in UKK, they were primarily disease-related (79% in UKK, 27.7% in SECI). Differences in overall and event-free survival were observed for leukemias but not for non-Hodgkin lymphoma.ConclusionsOutcome differences were associated with different causes of death and other less prominent factors.
| S-EPMC10478379 | biostudies-literature