Funding in 2012: "great recession" starts to bite.

Biomedical research budgets are frozen or falling in developed countries. Can expansion in developing nations continue as economic contagion spreads?

Seafloor primary production in a changing Arctic Ocean.

Phytoplankton and sea ice algae are traditionally considered to be the main primary producers in the Arctic Ocean. In this Perspective, we explore the importance of benthic primary producers (BPPs) encompassing microalgae, macroalgae, and seagrasses, which represent a poorly quantified source of Arctic marine primary production. Despite scarce observations, models predict that BPPs are widespread, colonizing ~3 million km2 of the extensive Arctic coastal and shelf seas. Using a synthesis of published data and a novel model, we estimate that BPPs currently contribute ~77 Tg C y-1 of primary production to the Arctic, equivalent to ~20 to 35% of annual phytoplankton production. Macroalgae contribute ~43 Tg C y-1, seagrasses contribute ~23 Tg C y-1, and microalgae-dominated shelf habitats contribute ~11 to 16 Tg C y-1. Since 2003, the Arctic seafloor area exposed to sunlight has increased by ~47,000 km2 y-1, expanding the realm of BPPs in a warming Arctic. Increased macrophyte abundance and productivity is expected along Arctic coastlines with continued ocean warming and sea ice loss. However, microalgal benthic primary production has increased in only a few shelf regions despite substantial sea ice loss over the past 20 y, as higher solar irradiance in the ice-free ocean is counterbalanced by reduced water transparency. This suggests complex impacts of climate change on Arctic light availability and marine primary production. Despite significant knowledge gaps on Arctic BPPs, their widespread presence and obvious contribution to coastal and shelf ecosystem production call for further investigation and for their inclusion in Arctic ecosystem models and carbon budgets.

Large numbers cause magnitude neglect: The case of government expenditures.

Four studies demonstrate that the public's understanding of government budgetary expenditures is hampered by difficulty in representing large numerical magnitudes. Despite orders of magnitude difference between millions and billions, study participants struggle with the budgetary magnitudes of government programs. When numerical values are rescaled as smaller magnitudes (in the thousands or lower), lay understanding improves, as indicated by greater sensitivity to numerical ratios and more accurate rank ordering of expenses. A robust benefit of numerical rescaling is demonstrated across a variety of experimental designs, including policy relevant choices and incentive-compatible accuracy measures. This improved sensitivity ultimately impacts funding choices and public perception of respective budgets, indicating the importance of numerical cognition for good citizenship.

Budget impact analyses for treatment of heart failure. A systematic review.

Heart failure (HF) is increasing globally and turning out to be a serious worldwide public health problem with significant morbidity and mortality. This study aims to systemically review the budget impact analysis of heart failure treatments on health care expenditure worldwide. Scientific databases such as PubMed, Web of Science, Scopus, and Google Scholar were searched for budget impact analysis and heart failure treatments, over January 2001 to August 2023. The quality assessment of the selected studies was evaluated through ISPOR practice guideline. Nineteen studies were included in this systematic review. Based on ISPOR recommendations, most studies were performed on a 1-year time horizon and used a government (public health) or health system perspective. Data for selected studies was mainly collected from randomized clinical trials, published literature, pharmaceutical companies, and registry data. Only direct costs were reported in the studies. Sensitivity analyses were stated in almost all studies. However, studies conducted in high-income countries reported sensitivity analyses more elaborately than those performed in low- and middle-income countries. In many published articles related to the budget impact analyses of heart failure treatment, addition of new treatments to the health system's formularies can lead to a reduction in cardiovascular hospitalization rates, re-hospitalization rates, cardiac-associated mortality rates, and an improvement in heart failure class, which can decrease the costs of hospitalizations, specified care visits, primary care visits, and other related treatments.

A field guide to cultivating computational biology.

Evolving in sync with the computation revolution over the past 30 years, computational biology has emerged as a mature scientific field. While the field has made major contributions toward improving scientific knowledge and human health, individual computational biology practitioners at various institutions often languish in career development. As optimistic biologists passionate about the future of our field, we propose solutions for both eager and reluctant individual scientists, institutions, publishers, funding agencies, and educators to fully embrace computational biology. We believe that in order to pave the way for the next generation of discoveries, we need to improve recognition for computational biologists and better align pathways of career success with pathways of scientific progress. With 10 outlined steps, we call on all adjacent fields to move away from the traditional individual, single-discipline investigator research model and embrace multidisciplinary, data-driven, team science.

Financial Characteristics of Outcomes-Based Agreements: What Do Canadian Public Payers and Pharmaceutical Manufacturers Prefer?

OBJECTIVES: This study sought to gain insight into the financial characteristics of outcomes-based agreements (OBAs) considered most suitable to Canadian public payers and pharmaceutical manufacturers, and the rationale for their preferences. METHODS: A total of 17 public payers and pharmaceutical manufacturers participated in semistructured qualitative interviews, which assessed their knowledge of OBAs and their preferred financial characteristics. RESULTS: Payers identified 5 OBA financial models that they considered both acceptable and feasible, in no preferential order: (1) discontinuation of therapy, (2) rebates for nonresponders, (3) free trial period, (4) adjustable pricing, and (5) blended rebate. Payers had a clear preference for short-term OBAs (<1 year), whereas both payers and manufacturers agreed OBAs with longer durations (up to 5 years) would be manageable if appropriately designed. Six key success factors to design suitable and acceptable OBA financial models were identified, including the areas of interim reporting, easily measurable health outcomes, trusted data sources, engaging unbiased third-party data experts, harmonizing OBA billing methods, and the inclusion of budget caps. CONCLUSIONS: Manufacturers and payers showed high level of interest in OBAs and a robust understanding of their potential role in supporting timely market access for patients in need, with the caveat that they need to be carefully designed to provide value. Further opportunities for discussion and engagement between public payers and manufacturers are needed to establish how to implement OBAs at a pan-Canadian level and how individual provinces and territories can incorporate them within their existing governance infrastructures.

Values Beyond "Health" in Budget-Constrained Healthcare Systems.

OBJECTIVES: Most current methods to value healthcare treatments only incorporate measures such as quality-adjusted life-years, combining gains in health-related quality of life and life expectancy in specific ways. Failure of these methods to recognize other dimensions of value has led to calls for methods to include additional values that are associated with the healthcare treatments but not captured directly by quality-adjusted life-years. This article seeks to provide methodologically sound ways to incorporate additional health-related outcomes, focusing on budget-constrained healthcare systems, in which using standard welfare economics methods are often eschewed. METHODS: The analysis develops standard extra-welfarist approaches to maximizing aggregate health, subject to fixed-budget constraints, using Lagrange multiplier methods. Then, additional valuable health-related outcomes, eg, reduced caregiver burden, real option value, and market- and non-market productivity are introduced. The article also introduces a social welfare function approach to illuminate how disability, disease severity and other equity-related issues can be incorporated into complete welfare measures. RESULTS: Resulting analysis, fully developed in an Appendix in Supplemental Materials found at https://doi.org/10.1016/j.jval.2024.02.005 and summarized in the main text, show that understanding how average and marginal healthcare costs increase with output and how health augments "additional values" provides ways to assess willingness to pay for them in these fixed-budget situations. CONCLUSIONS: In budget-constrained healthcare systems, only from actual budget allocations can values both of health itself and "additional values" be inferred. These methods, combined with methodologically sound social welfare functions, demonstrate how to move from "health" to "welfare" in measuring the value of increased healthcare use.

Payment Innovation in Emergency Care: A Case for Global Clinician Budgets.

The fee-for-service funding model for US emergency department (ED) clinician groups is increasingly fragile. Traditional fee-for-service payment systems offer no financial incentives to improve quality, address population health, or make value-based clinical decisions. Fee-for-service also does not support maintaining ED capacity to handle peak demand periods. In fee-for-service, clinicians rely heavily on cross-subsidization, where high reimbursement from commercial payors offsets low reimbursement from government payors and the uninsured. Although fee-for-service survived decades of steady cuts in government reimbursement rates, it is increasingly strained because of visit volatility and the effects of the No Surprises Act, which is driving down commercial reimbursement. Financial pressures on ED clinician groups and higher hospital boarding and clinical workloads are increasing workforce attrition. Here, we propose an alternative model to address some of these fundamental issues: an all-payer-funded, voluntary global budget for ED clinician services. If designed and implemented effectively, the model could support robust clinician staffing over the long term, ensure stability in clinical workload, and potentially improve equity in payments. The model could also be combined with population health programs (eg, pre-ED and post-ED telehealth, frequent ED use programs, and other innovations), offering significant payer returns and addressing quality and value. A linked program could also change hospital incentives that contribute to boarding. Strategies exist to test and refine ED clinician global budgets through existing government programs in Maryland and potentially through state-level legislation as a precursor to broader adoption.

Analytical performance specifications for combined uncertainty budget in the implementation of metrological traceability.

In addition to the correct implementation of calibration traceability, the definition and fulfillment of maximum allowable measurement uncertainty (MAU) are essential in assuring that laboratory measurements are clinically usable. Across the entire calibration hierarchy, three major contributors to the measurement uncertainty (MU) budget are identified, starting with the higher-order reference providers, extending through the in vitro diagnostic (IVD) manufacturers and their processes for assigning calibrator values, and ending with medical laboratories generating the random variability of results reported to clinicians. To understand if it is possible to achieve MAU and, consequently, to fix the possible drawbacks, the definition of combined MU budget limits across the entire calibration hierarchy has a central role. In particular, quality specifications for MU of reference and commercial calibrator materials should be defined according to the MAU on clinical samples. All involved stakeholders (i.e., higher-order reference providers, IVD manufacturers, medical laboratories) should be prepared to improve their performance whenever the clinical application of the test is made questionable by the failure to achieve MAU.

Allocating aid for COVID-19 support: A constrained optimisation approach.

The objective of this paper is to develop a prescriptive model for the inter-country allocation of aid for COVID-19 support. Aid allocations are increasing functions of three dimensions of need: (i) hazard and exposure to COVID-19; (ii) vulnerability to COVID-19 impacts; and (iii) the capacity to cope, subject to an aid budget constraint. COVID-19 support from official donors to all ODA eligible countries is modeled. Aid allocations for COVID-19 support prescribed by the model are compared to actual allocations in 2020. Findings from the main model suggest that low-income countries are over-represented among the countries that should have received a greater share of the aid for COVID-19 support. Middle-income countries tended to receive more donor support for COVID-19 than amounts suggested by the model. The choice of weights assigned to the dimensions of need is arbitrary but findings are broadly consistent with respect to the use of different weights, alternative measures of support and changes to other parameters of the model. It is recommended that the donor community commit to a transparent needs-based funding formula when addressing a global pandemic.

Crowding-out effect of tobacco consumption in Indonesia.

BACKGROUND: Tobacco consumption is pervasive in Indonesia, with 6 out of 10 households in the country consuming tobacco. Smoking households, on average, divert a significant share (10.7%) of their monthly budget on tobacco products, which is higher than spending on staples, meat or vegetables. Nevertheless, evidence of the causal link between tobacco expenditure and spending on other commodities in Indonesia is limited. OBJECTIVE: This study aims to estimate the crowding-out effects of tobacco spending on the expenditure of other goods and services in Indonesia. METHOD: This research estimates the conditional Engel curve with three-stage least square regression, where the instrumental variable technique is applied to address the simultaneity of tobacco and total non-tobacco spending. The study employs a large-scale household budget survey from the Indonesian socioeconomic survey (Susenas) from 2017 to 2019, comprising over 900 000 households. FINDING: Tobacco spending crowds out the share of a household's budget allocated for food, such as spending on staples, meat, dairy, vegetables and fruits. Moreover, tobacco spending also reduces the share of expenditure spent on non-food commodities, such as clothing, housing, utilities, durable and non-durable goods, education, healthcare and entertainment, although its effect is not as large as the crowding out on food. The analysis shows that the crowding-out effects of tobacco are observed across low-income, middle-income and high-income households. In addition, the simulation suggests that reducing tobacco expenditure will increase household spending on essential needs.

Finding the missing many: improving Tuberculosis care in Kajiado county through active case finding and community approaches.

BACKGROUND: Tuberculosis related deaths remain a priority globally. Despite advancements in TB care, access to quality care remains inequitable to the disadvantage of those in rural and urban informal settlements. The Awareness, Traditions, and Innovation in combating Tuberculosis (ATI TB) project incorporated active case finding (ACF), use of GeneXpert technology and decentralized services to improve TB care in Kajiado County. This study sought to establish the impact of the project as well as implementation lessons learnt during its tenure in Kajiado County, Kenya. METHODS: This evaluation adopted a mixed-methods approach with retrospective cohort analysis for the quantitative data and qualitative data sought through key informant interviews with 28 purposively sampled respondents. The qualitative data was analyzed thematically using Taguette while quantitative data was analyzed using R Software yielding descriptive statistics and measures of association. RESULTS: While the males were a minority among the presumptive cases (623; 46%), they were the majority (59.3%) among the confirmed TB cases. 70% of the confirmed cases were aged between 15 and 44 years; with those aged between 25- and 34-years being majority (30% of the cases). Majority of the confirmed cases within the project were from rural Kajiado West (79; 66.9%). Though 61% of the presumptive cases were through ACF, only 7% of these tested positive. Conversely, 13% of the self-referrals tested positive. 53% (66) of the positive cases with valid data were self-referrals while ACF accounted for 47% (58) of the positives. CONCLUSION: Continued capacity development among health workers, sustained and targeted sensitization and screening among vulnerable groups, strategic collaborations, alongside increased budgetary prioritization of health and TB care by government and partners, and government investments in Social Determinants of Health can ensure gains in TB care are sustained.

Food budget ratio as an equitable metric for food affordability and insecurity: a population-based cohort study of 121 remote Indigenous communities in Canada.

BACKGROUND: Food insecurity is a public health issue for many regions globally, and especially Indigenous communities. We propose food budget ratio (FBR)-the ratio of food spending to after-tax income-as an affordability metric that better aligns with health equity over traditional price-focused metrics. Existing census and inflation monitoring programs render FBR an accessible tool for future affordability research. METHODS: Public census and food pricing datasets from 2011 to 2021 were analyzed to evaluate food affordability for a cohort of 121 remote Indigenous communities in Canada (n = 80,354 persons as of March 2021). Trends in population-weighted versus community-weighted averages, inflation-adjusted mean price of the Revised Northern Food Basket (RNFB), and distributions of FBR, per-capita price of food, and per-capita after-tax income were calculated and compared to Canada at large. RESULTS: Population-weighted versus community-weighted mean price of the RNFB differed by < 5% for most points in time, peaking at 17%. Mean raw price of the RNFB was relatively stable, while mean inflation-adjusted price of the RNFB decreased 19%. Mean and standard deviation in FBR trended downwards from (0.40; 0.21) in 2011 to (0.25; 0.10) in 2021, while the mean for Canada held stable at 0.10 ± 0.01. Mean and standard deviation in inflation-adjusted per-capita price of food fell from ($5,621; $493) to ($4,510; $243), while the Canada-wide mean rose from $2,189 to $2,567; values for per-capita after-tax income increased from ($17,384; $7,816) to ($21,661; $9,707), while the Canada-wide mean remained between $24,443 and $26,006. Current Nutrition North Canada (NNC) subsidy rates correlate closely with distance to nearest transportation hub (σXY = 0.68 to 0.70) whereas food pricing, after-tax income, and FBR correlate poorly with distance (σXY = -0.22 to 0.03). CONCLUSIONS: The FBR approach yields greater insights on food affordability compared to price-based results, while using readily available public datasets. Whereas 19% reductions in RNFB per-capita food price were observed, FBR decreased 63% yet remained 2.5 times the Canada-wide FBR. The reduction in FBR was driven both by the reduced price of food and a 25% increase in after-tax income. It is recommended that NNC consider FBR for performance measurement and setting subsidy rates.

Integrated assessment modeling reveals near-channel management as cost-effective to improve water quality in agricultural watersheds.

Despite decades of policy that strives to reduce nutrient and sediment export from agricultural fields, surface water quality in intensively managed agricultural landscapes remains highly degraded. Recent analyses show that current conservation efforts are not sufficient to reverse widespread water degradation in Midwestern agricultural systems. Intensifying row crop agriculture and increasing climate pressure require a more integrated approach to water quality management that addresses diverse sources of nutrients and sediment and off-field mitigation actions. We used multiobjective optimization analysis and integrated three biophysical models to evaluate the cost-effectiveness of alternative portfolios of watershed management practices at achieving nitrate and suspended sediment reduction goals in an agricultural basin of the Upper Midwestern United States. Integrating watershed-scale models enabled the inclusion of near-channel management alongside more typical field management and thus directly the comparison of cost-effectiveness across portfolios. The optimization analysis revealed that fluvial wetlands (i.e., wide, slow-flowing, vegetated water bodies within the riverine corridor) are the single-most cost-effective management action to reduce both nitrate and sediment loads and will be essential for meeting moderate to aggressive water quality targets. Although highly cost-effective, wetland construction was costly compared to other practices, and it was not selected in portfolios at low investment levels. Wetland performance was sensitive to placement, emphasizing the importance of watershed scale planning to realize potential benefits of wetland restorations. We conclude that extensive interagency cooperation and coordination at a watershed scale is required to achieve substantial, economically viable improvements in water quality under intensive row crop agricultural production.