Akshar Saxena

BackgroundUniversal genetic testing (GT) has been proposed as a public health strategy to reduce Lynch syndrome (LS)-related cancer burden, but lacks economic validation in Singapore. We aimed to identify the most cost-effective LS diagnostic strategy and assess its budget impact.Methods We conducted cost-utility analyses from Singapore's healthcare system perspective with a lifetime horizon, targeting three populations and their first-degree relatives (FDRs): newly diagnosed colorectal (CRC), endometrial cancer (EC) patients, and cancer-unaffected individuals aged 30 years. Strategies included reflex testing, upfront GT, family history (FH)-guided testing, and no testing. Willingness-to-pay (WTP) threshold was $75,000/quality-adjusted life-year (QALY). Uncertainty was assessed deterministically and probabilistically.FindingsFor CRC patients, immunohistochemistry (IHC)-guided GT was the most cost-effective strategy (ICER: $45,959/QALY versus no testing). Upfront GT exceeded the WTP threshold (ICER: $129,808/QALY versus IHC-guided GT) unless LS prevalence is ≥4.10%. For EC patients, Upfront GT was the optimal strategy (ICER: $19,131/QALY versus the next best strategy), demonstrating 66.68% probability of cost-effectiveness. In the cancer-unaffected population, FH-guided testing exhibited decision uncertainty, compared to no testing (45.44% versus. 54.50% probability), but achieved cost-effectiveness by extending cascade testing to second-degree relatives. Cost-effectiveness was highly sensitive to surveillance adherence, cascade testing uptake, and LS prevalence. Implementing optimal strategies for CRC and EC patients, including their FDRs requires $0.50 million annually.InterpretationIHC-guided triage is cost-effective in CRC patients, whereas upfront GT is preferred for EC patients. Implementation efforts should prioritise improving cascade testing uptake, a critical driver of program value.Funding National Research Foundation, Singapore.

Background: Upfront germline genetic testing (GT) has been shown to be cost-effective for diagnosing hereditary breast and ovarian cancer (HBOC) and reducing the hereditary cancer burden in many high-income countries, but lacks economic validation in Singapore. We aimed to evaluate the cost-effectiveness of GT for BRCA1 and BRCA2 compared to age-and/or family history (FH)-guided GT and no testing to diagnose HBOC in women in Singapore.Methods: We conducted cost-utility analyses from Singapore's healthcare system perspective with a lifetime horizon, targeting three populations and their first-degree relatives (FDRs) through cascade testing: newly diagnosed breast cancer (BC) patients, ovarian cancer (OC) patients, and cancer-unaffected women aged 30 years. The cost-effectiveness threshold was SGD$75,000 per quality-adjusted life-year (QALY). Uncertainty was assessed deterministically and probabilistically.Findings: Upfront GT had an incremental cost-effectiveness ratio of $14,775 /QALY in BC patients, $23,173 /QALY in OC patients, and $50,541/QALY for population screening compared with age and/or FH-guided GT and averted 4, 5, and 1 additional cancer cases per 1,000 women, respectively. Upfront GT was the optimal strategy, demonstrating nearly 100% cost-effectiveness in all three target populations. The results were most sensitive to prophylactic surgery costs and uptake, surveillance adherence, number of FDRs and cascade testing participation rate.Interpretation: Upfront BRCA1/2 GT is cost-effective to diagnose HBOC in Singapore. Given the significant influence of prophylactic intervention costs on the model outcomes, subsidies for GT, breast MRI, and prophylactic surgeries should be considered to improve uptake and optimise program effectiveness.

This study quantifies the hidden health burden of air pollution arising from systematic underdiagnosis. Using longitudinal data from the China Health and Retirement Longitudinal Study (CHARLS) linked to high-resolution satellite measures of PM 2.5 and a wind-based instrumental variables strategy, we compare pollution effects measured using self-reported physician diagnoses and biomarker-identified health conditions. A 1% increase in long-term PM 2.5 exposure raises biomarker-identified respiratory disease prevalence by 0.33 percentage points, while self-reported diagnoses exhibit no corresponding response, leaving approximately 73% of the pollution-related disease burden clinically undetected. Similar underdiagnosis patterns arise for dyslipidemia, chronic kidney disease, and cardiovascular disease. The hidden burden is systematically larger among populations with lower diagnostic salience or access, including individuals exposed to household secondhand smoke, residents of cities with limited healthcare resources, those reporting better childhood health, and those living in relatively low-PM 2.5 environments. These findings imply that benefit-cost analyses relying on diagnosed outcomes substantially understate the health and economic costs of air pollution.

This study quantifies the hidden health burden of air pollution arising from systematic underdiagnosis. Using longitudinal data from the China Health and Retirement Longitudinal Study (CHARLS) linked to high-resolution satellite measures of PM2.5 and a wind-based instrumental variables strategy, we compare pollution's effects measured using self-reported physician diagnoses and biomarker-identified health conditions. A 1% increase in long-term PM2.5 exposure raises biomarker-identified respiratory disease prevalence by 0.33 percentage points, while self-reported diagnoses exhibit no corresponding response, leaving approximately 73% of the pollution-related disease burden clinically undetected. Similar underdiagnosis patterns arise for dyslipidemia, chronic kidney disease, and cardiovascular disease. The hidden burden is systematically larger among populations with lower diagnostic salience or access, including individuals exposed to household secondhand smoke, residents of cities with limited healthcare resources, those reporting better childhood health, and those living in relatively low-PM2.5 environments. These findings imply that benefit-cost analyses relying on diagnosed outcomes substantially understate the health and economic costs of air pollution.

Objective: To examine the association between socioeconomic status (SES), financial subsidies and awareness-related factors such as age, cancer stage and family history, and the uptake of cancer genetic testing, with a focus on equitable access to care. Design: Retrospective cohort study. Setting: Tertiary care cancer genetics service in Singapore. Participants: The study population included 2687 individuals of all ages, genders and ethnicities who attended pretest counselling between 2014 and 2020 and were eligible for genetic testing for hereditary cancer syndromes. Primary and secondary outcome measures: The primary outcome was the uptake of genetic testing. The main explanatory variables were SES (proxied by Housing Index), subsidy status, age, cancer stage and family history. Analyses examined whether associations varied across SES and age subgroups. Results: Receipt of financial subsidies was strongly associated with testing uptake (adjusted OR 9.15, 95% CI 2.68 to 31.20). Uptake exceeded 90% among subsidised individuals across all socioeconomic strata, compared with 56–68% among non-subsidised individuals, with the largest gains in the lowest SES group (43 vs 28 percentage points (pp) in the highest). The level of subsidy was not associated with uptake. Younger patients (18–39 years) had higher uptake than those aged 60+ (66% vs 57%); patients with advanced cancer (stage IV) had the highest uptake (82% vs 57–66% in earlier stages); and family history was associated with increased uptake, strongest for having a child with cancer (+28 pp). Interaction analysis suggested that the additive effects of subsidies were greatest in lower SES groups and in older adults. Conclusions: Financial subsidies were strongly associated with higher genetic testing uptake. Awareness indicators like age, cancer stage and family history were associated with higher uptake. The association between subsidies and uptake varied by SES and age, suggesting that subsidies may help reduce disparities and improve equitable access to genetic testing services.

Defensive behavior against disease risk shapes residential energy demand in ways standard health evaluations overlook. We provide causal evidence on this relationship by exploiting the staggered rollout of Singapore's Wolbachia-based dengue control program. Using monthly data from over 5,000 residential buildings, we find that Wolbachia deployment reduces electricity consumption by 4.7%, equivalent to 30 to 45 minutes of air-conditioning per household per day. Households respond to reductions in disease risk by substituting away from defensive air-conditioning toward natural ventilation. Our findings reveal that disease risk creates energy burdens and that public health interventions generate environmental co-benefits.

Fiscal food policies can be used, among others, to minimize the burden of diet-related diseases. To inform the design of such policies in Australia, we used the large grocery-purchasing dataset NielsenIQ Homescan to estimate own-price elasticities and cross-price elasticities for 18 food categories. We found that households were most responsive to changes in price for non-sugar-sweetened beverages and sugar-sweetened beverages: a 10% increase in price was associated with reductions in demand of 15% and 12%, respectively. Additionally, an increase in the price of one category was associated with relatively small changes in the quantity demanded for other categories (that is, 92% of cross-price elasticities had an absolute value <0.2). There were small differences in own-price and cross-price elasticities across socioeconomic quintiles. These price elasticity estimates can be used to model the health and equity impacts of fiscal food policies in Australia.

Fiscal policies to improve diet are a promising strategy to address the increasing burden of non-communicable disease, the leading cause of death globally. Sugar-sweetened beverage taxes are the most implemented type of fiscal policy to improve diet. Yet taxes on food, if appropriately structured and applied across the food supply, may support a larger population-level shift towards a healthier diet. Designing these policies and guiding them through the legislative process requires evidence. Equity-oriented cost-effectiveness analyses that estimate the distribution of potential health and economic gains can provide this critical evidence. Taxes on less healthy foods are rarely modelled in low-income and middle-income countries. We describe considerations for modelling the effect of a food tax, which can provide guidance for food tax policy design. This includes describing issues related to the availability, reliability and level of detail of national data on dietary habits, the nutrient content of foods and food prices; the structure of the nutrient profile model; type of tax; tax rate; pass-through rate and price elasticity. Using the Philippines as an example, we discuss considerations for using existing data to model the potential effect of a tax, while also taking into account the political and food policy context. In this way, we provide a modelling framework that can help guide policy-makers and advocates in designing a food policy to improve the health and well-being of future generations in the Philippines and elsewhere.