Environmental Research Letters

Introduction Hearing loss (HL) affects over 1{middle dot}5 billion people globally and India shares a disproportionately high burden including Disabling Hearing Loss (DHL). HL affects an Individual socio-economically, but there are limited studies on the broader societal economic consequences of HL in India.Methods Using Cost-of-Illness (COI) approach, we studied the societal economic burden of HL in India. This study uses epidemiological and macroeconomic data and modelling to estimate the loss of Gross National Income (GNI) due to HL and DHL across three economic pathways. Uncertainty is evaluated using deterministic and Probabilistic Sensitivity Analyses (PSA).Results The model estimates that there are in India, 289 million and 85{middle dot}9 million people with HL and DHL respectively. Direct Loss of GNI and Indirect Loss of GNI (Caregiver burden) are estimated as INR 4,648{middle dot}4 billion (USD 55{middle dot}6 billion) and INR 3,268 billion (USD 39 billion) respectively. The Loss of GNI due to Low Education amongst those with HL is estimated as INR 1,041{middle dot}9 billion (USD 12{middle dot}45 billion).Discussion Economic burden of HL is presented across three pathways with Direct Loss of GNI due to DHL being the greatest. It also presents age stratified caregiver economic burden. The findings of the study help in estimating similar cost pathways, advocacy, and policy decisions towards reducing HL prevalence in India and LMICs. This study also highlights the need for India specific estimations related to the HL attributable low education, state-wise disaggregates, and prevalence studies. Funding This study has not received any funding.

Background Childhood respiratory mortality in China has fallen by over 90% in three decades alongside sustained national warming, yet national long-run evidence on temperature and child respiratory mortality is lacking. Methods We linked Global Burden of Disease (GBD) 2021 mortality estimates for China - lower respiratory infections (LRI), ages 0-19, and asthma, ages 0-24, 1990-2021 - with C-LSAT 0.5 deg gridded temperature data (1990-2019), aggregated nationally and to five climate zones. Four annual indicators (mean temperature, diurnal temperature range, seasonal amplitude, interannual variability) entered regressions of log mortality rates with Newey-West standard errors. A bootstrapped (500 resamples) quadratic model probed the minimum mortality temperature (MMT), with PM2.5-adjusted analyses and future-exposure, permutation, and detrended falsification tests. Results LRI deaths fell by 96.3% (330,194 in 1990 to 12,098 in 2021; 95% uncertainty interval 9,669-14,891) and asthma deaths by 94.9% (3,287 to 167), while mean temperature rose 0.364 deg C per decade and diurnal temperature range narrowed 0.092 deg C per decade. Baseline coefficients were large (mean temperature -1.696, SE 0.174; diurnal temperature range +2.408, SE 0.336; seasonal amplitude -0.162, SE 0.082; interannual variability +2.924, SE 1.514, per 1 deg C in log rate), but the future-exposure test failed and detrending nullified every coefficient: the associations are trend-level, and short-cycle causal effects are not identifiable. Nor was the national MMT identifiable - observed temperature support spans only 6.66-8.13 deg C, and the nominal turning point of 35.84 deg C is an extrapolation artifact (quadratic term p = 0.963). Within the observed range, warming and declining mortality moved in the same direction. Conclusions The 96% decline in childhood respiratory mortality cannot be attributed to warming. China sits on the low-temperature side of the optimum, and the marginal direction of future warming requires stronger designs to establish. The falsification framework offers a discipline for climate-health inference in China.

Inappropriate antibiotic use presents a major global health challenge, particularly in low-resource settings where access to quality care is limited but antibiotics remain relatively unrestricted. This study estimates the causal effect of frontline primary care quality on inappropriate community antibiotic use, combining detailed community-based data from approximately 100 rural villages in rural China with an instrumental variable (IV) approach embedded within a double/debiased machine learning (DML) framework. We linked objective measures of village doctor clinical practice quality, measured through unannounced standardized patient visits, to household-level antibiotic use data collected from the same villages. To identify the causal effect, we constructed multiple candidate instruments from extensive provider characteristics and used an ensemble of machine learning algorithms within a flexible DML-IV framework to approximate an optimal instrument, addressing a many-weak-instruments problem. We found that improving village provider clinical practice quality reduced both antibiotic receipt during healthcare encounters for common diseases and household antibiotic storage for future self-medication. Our findings suggest that strengthening frontline primary care quality can meaningfully reduce inappropriate community antibiotic use without restricting access to essential treatment. More broadly, this study illustrates how causal machine learning can strengthen conventional causal estimation in complex observational settings in global health economics research.

1. Forest canopies harbour strong microclimatic gradients that shape plant performance, species interactions and ecosystem processes. Yet, despite renewed interest sparked by global change, forest canopies remain difficult-to-access experimental spaces. 2. With the goal to expand access to tree canopies as experimental arenas, we designed, built, and tested TreeTOP, a standardized experimental platform that opens canopy space for manipulative ecological experiments, specifically with potted plants. TreeTOP features lightweight aluminum frames placed in mature tree canopies non-invasively, allowing potted plants to be placed in three different heights, ground level, shade canopy, and sun canopy. 3. We implemented TreeTOP using two contrasting infrastructure concepts to demonstrate its applicability in both highly equipped canopy research facilities and forests without permanent canopy infrastructure. One installation relied on a canopy crane, grid power and fully automated irrigation, whereas the second was built by certified tree climbers and was equipped with an autonomous solar-powered, battery-operated irrigation system. At both sites, environmental sensor networks monitor the experiment. 4. TreeTOP successfully reproduced characteristic canopy microclimatic gradients, including increasing light availability, daytime air temperatures and thermal extremes with canopy height. Despite differing infrastructures, both implementations generated comparable microclimatic patterns, demonstrating that standardized canopy experiments are feasible in forests with or without permanent canopy access. By opening canopy space for manipulative experiments, TreeTOP provides a transferable framework for investigating plant performance, phenology, species interactions and microbiome assembly under realistic forest conditions.

Background In adults, cold-attributable mortality exceeds heat-attributable mortality roughly 17-fold. Child-specific evidence has begun to emerge only recently - a nationwide Brazilian case-crossover study located the minimum mortality temperature (MMT) for under-five deaths, and a 56-country survey-based analysis linked monthly temperature anomalies to under-five mortality - but no multi-country, climate-zone-resolved estimate of the childhood respiratory-infection MMT exists, and whether temperature variability is independently associated with childhood respiratory mortality at the global scale is unknown. We quantified both. Methods We combined Global Burden of Disease 2023 mortality estimates, lower respiratory infection (LRI) deaths at ages 0-19 years and asthma deaths at ages 0-24 years, 171 countries, 1990-2023 - with 0.5 deg monthly land temperature and diurnal temperature range (DTR) fields from C-LSAT/C-LDTR (1901-2023). Four exposure dimensions (annual mean, DTR, seasonal amplitude, interannual variability) entered two-way fixed-effects models with Driscoll-Kraay standard errors. A quadratic term in mean temperature located the MMT, with percentile confidence intervals from a 300-replication country-cluster bootstrap. Future-exposure leads, country-level detrending, and permutation tests assessed contemporaneous causality, applied to both the linear coefficients and the quadratic term generating the MMT; national pneumococcal conjugate vaccine (PCV3) coverage and ambient PM2.5 exposure series were added as time-varying mechanistic covariates. Results The childhood LRI MMT was 17.1 C (95% CI 14.7-19.8), the 36th percentile of the annual-temperature distribution; zone estimates were 24.7 C in tropical and 15.8 C in subtropical countries, with weak temperate and no subarctic identification. The quadratic term underpinning the MMT, however, failed both falsification checks - future temperatures reproduced the U-shape and country-level detrending erased it - so these MMT values describe a trend-level geographic pattern of the annual construct rather than a contemporaneous dose-response. Interannual temperature variability was positively associated with LRI (+0.278, 95% CI 0.102-0.454; p = 0.002) and asthma mortality (+0.836, 95% CI 0.447-1.226; p = 2.6 x 10^-5) per 1 C, but future-exposure models returned nearly identical significant coefficients and detrending erased significance, supporting only a trend-level association; adjustment for national PCV3 coverage and PM2.5 exposure left these estimates essentially unchanged. Annual mean temperature was likewise inversely associated with both outcomes at the trend level; DTR and seasonal amplitude showed no independent within-country effects. Conclusions This study provides the first multi-country, climate-zone-resolved geography of the optimal temperature for childhood respiratory survival, spanning 171 countries; because the underlying quadratic association is trend-level, the estimates are directional. The observed variability-mortality associations are trend-level signals rather than contemporaneous causal evidence; daily-scale, child-specific designs are required to determine whether short-term thermal variability affects paediatric respiratory mortality.

Background. Nigeria carries one of the world's largest burdens of neonatal death and remains far from the Sustainable Development Goal target. Whether health financing and macroeconomic instability are associated with newborn survival has rarely been examined for neonatal mortality specifically. Methods. We conducted an ecological time-series analysis of national annual data, covering 1990-2024 for macroeconomic models (n = 35) and 2000-2023 for health-financing models (n = 24), the periods for which published data exist; no values were imputed. Neonatal mortality came from the UN Inter-agency Group for Child Mortality Estimation 2025 round with 90% uncertainty intervals, and other series from the World Development Indicators. The primary model regressed log neonatal mortality on government health expenditure per capita (purchasing power parity), out-of-pocket share and currency instability, with a linear trend, a post-break trend spline and Newey-West standard errors; first differences without trend terms were the main sensitivity analysis. The break was located by segmented regression; currency instability was tested under four constructions. Results. The decline broke around 2010, the trend moving from -0.74 to +0.14 deaths per 1,000 annually (F = 145.4, p < 0.001). The subsequent rise fell within estimation uncertainty (2012: 37.6, 90% interval 33.9-41.5; 2022: 39.3, 33.4-46.4), supporting stagnation rather than reversal; Demographic and Health Surveys concur, reporting 42 per 1,000 for the five years preceding the 1990 survey and 41 preceding the 2024 survey. Government health expenditure per capita was inversely associated with neonatal mortality (-0.040, 95% CI -0.051 to -0.029, p < 0.001; first differences -0.016, p = 0.033) and was the only expenditure measure surviving both specifications; share-of-GDP measures did not (p = 0.196 and 0.889) and correlated positively in raw terms. Currency instability showed no association under any construction (p = 0.65-0.83). Public expenditure per capita moved non-monotonically, peaking in 2005, falling by 2010 and recovering by 2023 to a level still below the 2005 peak. Conclusions. Neonatal mortality in Nigeria is ecologically associated with public health expenditure per capita, but not with commonly used share-based measures, nor with currency instability. Rising public spending accompanied stalled progress, directing attention toward how health resources are converted into services. Annual modelled mortality estimates could not support year-to-year inference, a limitation relevant to comparable studies

Most evidence of the consequences of climate change in natural systems has focussed on shifts in mean temperature (1,2), but the effects of extreme climatic events (ECEs) remain far less understood. This is particularly true for very severe ECEs that may occur only once every few decades. Understanding the consequences of these severe events for natural populations is nonetheless critical, since their frequency is predicted to rise under current climate change (3). Here we combine a unique long-term dataset spanning almost five decades of breeding (>20,000 events) and morphological data (>120,000 observations) in adult and nestling great tits (Parus major) and blue tits (Cyanistes caeruleus) with fine-scale temperature records to examine the effects of an unprecedented heatwave in May 2026 on breeding success and morphology. Average temperature during the heatwave (22-29 May 2026) was 7.85 C above the historical record, reaching +10.5 C (+4.32 SD) at its peak (25-26 May). These record-breaking temperatures significantly reduced adult breeding success and nestling bmass relative to expectation in the absence of a heat-wave. Given the heatwave was widespread (Fig. 1A), our findings from a single, exceptionally well-studied population are likely to generalise to other species exposed to the same event, providing key evidence that severe ECEs can substantially harm wild populations.

Introduction: Monthly oral HIV pre-exposure prophylaxis (PrEP) such as MK-8527 offer promise as low-cost, self-administered options that are easily delivered through community-based platforms. Economic evaluations of MK-8527 either alone or alongside other long-acting (LA) PrEP products like lenacapavir are needed for informing HIV prevention strategies. Methods: We adapted an agent-based network model, EMOD-HIV, to simulate LA-PrEP scale-up in South Africa and western Kenya from 2026-2035; scenarios evaluated MK-8527 alone, lenacapavir alone and combined strategies, with varying uptake among female sex workers, their male clients, and individuals with >1 partner. We assumed 95% effectiveness of MK-8527 for 2 months (assuming individuals took 2 of 3 pills dispensed) and 95% lenacapavir effectiveness for 6 months. Scenarios were compared to a baseline of daily oral PrEP only. Results: Assuming the same uptake rates, MK-8527 alone achieved lower health impacts than lenacapavir alone in both settings (6-14% vs. 11-18% of HIV infections averted) but had substantially lower costs; provision costs of MK-8527 were 58-59% lower than lenacapavir assuming $1.00/pill and 40-43% lower at $2.50/pill. In western Kenya, ICERs for MK-8527 alone were $467/DALY averted and $799/DALY averted assuming pill prices of $1.00 and $2.50 respectively, compared to $1,306/DALY averted for lenacapavir. In South Africa, all LA-PrEP strategies were cost-saving over the 35-year horizon, although near-term budget impacts were substantial ($169-348 million over five years). Service delivery accounted for the majority of MK-8527 costs (73% at $1.00 per pill). Combined strategies of lenacapavir and MK-8527 increased health benefits (13-23% infections averted) but had higher provision costs than either strategy alone. Conclusion: MK-8527 can reduce HIV incidence at lower costs than lenacapavir. However, high service delivery costs limit its cost-effectiveness to scenarios in which pill prices are low (US$1.00 per pill) and provision is targeted to populations at substantial HIV risk.

Introduction. By the end of 2023, many low-income countries had not reached 50% COVID-19 vaccine coverage, while most high-income countries had exceeded 80%. It remains unclear whether receiving vaccine deliveries translated into faster population coverage. We examined cross-national inequalities in the timing of the vaccine rollout and whether deliveries through the COVID-19 Vaccines Global Access (COVAX) facility were associated with subsequent national uptake. Methods. We conducted an observational study of 218 countries and territories using country-level data up to December 2023. We used generalized additive mixed models to identify country-level correlates of coverage at an early and a later stage of the pandemic, survival analysis to compare the time to 50% coverage between COVAX Advance Market Commitment (AMC) and non-AMC countries, and an event study to estimate the association between the timing of the first COVAX delivery and subsequent monthly coverage in AMC countries. Results. AMC-supported countries reached 50% coverage substantially more slowly than non-AMC countries. The hazard of reaching the threshold was 0.17 times that of non-AMC countries at month 1 (95% CI 0.07 to 0.41) and 0.53 times at month 18 (95% CI 0.33 to 0.85). One year after rollout began, 65.9% of AMC countries (95% CI 56.7 to 76.6) had not reached 50% coverage, compared with 21.1% of non-AMC countries (95% CI 15.1 to 29.5). The timing of COVAX deliveries was not significantly associated with subsequent national uptake in any post-delivery month. In the early stage of rollout, higher maternal mortality was associated with lower coverage, while a larger urban population was associated with higher coverage. By the end of the observation period, larger household size was associated with lower coverage, while higher health expenditure and a larger urban population were associated with higher coverage. Conclusion. Receiving COVAX deliveries was not, on its own, associated with faster coverage. Coverage differences were more consistently associated with country-level structural and health-system characteristics, while we found no significant association with the timing of the first COVAX delivery. Achieving vaccine equality likely requires strengthening the capacity of health systems to convert deliveries into administered doses, and preparedness efforts should invest in last-mile delivery capacity ahead of future emergencies.

To evaluate the cost-utility and 5-year budget impact of first-line olaparib plus abiraterone versus abiraterone alone for metastatic castration-resistant prostate cancer (mCRPC) in China after the eleventh round of volume-based procurement (VBP). The intention-to-treat (ITT) population was assigned primary decision-analytic weight; the prespecified BRCA1/2-mutated (BRCAm) subgroup was a supporting analysis.

Context Pumping stations pose a threat to fish globally through land use change, habitat fragmentation and entrainment risk, with the catadromous and critically endangered European eel particularly impacted. Objectives/methods Establish, model, assess and understand the present-day distribution of European eel and resident fishes in 152 pumping station catchments in a once extensive wetland (The Fens) using eDNA metabarcoding (855 samples over two and half years), with specific focus on anthropogenic influences on hydrological connectivity and habitat quality. A removal survey design maximised confidence in negative results while minimising time and consumable costs. Results Eel occurrence upstream of pumping stations was low (occupancy = 28.3%) and positively associated with catchment area, fish species richness and natural hydrological connectivity (gravity drainage or flooding) and negatively associated with distance from the tidal limit. Fish species richness replaced catchment area and improved model performance, potentially acting as a biotic indicator of habitat quality and connectivity. Pumped catchments with manually operated upstream water transfers had reduced eel presence, potentially linked to the direction of water flow or the timing of operation. By contrast, fish species richness increased in these catchments during summer, suggesting displacement into unsuitable long-term habitats. Physical habitat maintenance had no detectable effect on eel occurrence or fish species richness. Conclusions This study provides the first landscape-scale assessment of European eel distribution and drivers of occurrence in pumped river catchments. The highly novel and comprehensive insights have implications for European eel conservation as well as infrastructure and catchment management, including compliance with legislation (EC Regulation No. 1100/2007).

Background: Pro-inflammatory and high-environmental-impact diets both threaten population and planetary health, but whether the two objectives align or conflict across countries is unresolved. We tested whether a supply-based dietary inflammatory index (sDII) is coupled to greenhouse-gas (GHG), land and freshwater footprints, and whether a nutrition-feasible reallocation can lower both simultaneously. Methods: From FAO Food Balance Sheets we built sDII (12 inflammatory-weighted components; construct validity r=0.9999) and five per-capita footprints using three independent life-cycle inventories for 182 national food-supply series. For each country, constrained optimisation reallocated 13 food-group supplies under isoenergetic, protein-preserving and food-group-bound constraints, minimising sDII and GHG jointly (Pareto frontier). Health burden was estimated via pooled relative-risk meta-analysis and 2023 World Bank population data. Results: sDII was only weakly associated with GHG (Spearman rho=0.14), land (rho=0.13) and freshwater (rho=0.28) in 2023. The balanced-Pareto reallocation lowered both sDII and GHG in 182/182 series (100% synergy): population-weighted delta sDII=-0.235, GHG -37.5%, land -49.3%, water -17.2%, i.e. 4.28 Gt CO2e/yr avoided. The associated reduction in metabolic-syndrome burden was directionally consistent but modest (~1.1% of the prevalent pool, ~2.84 million cases). Results were robust to three life-cycle inventories and three feasibility-bound regimes. Conclusions: Anti-inflammatory and low-carbon goals are decoupled rather than conflicting, and an isoenergetic, protein-preserving reallocation reconciles them in every country. Environmental gains are large and robust; health gains are directionally consistent but modest--triangulation, not a causal claim.

Citizen science observations are abundant, but conservation requires turning uneven records into reliable predictions and directing new surveys to where information is missing. We developed a biodiversity platform for Japan that is updated monthly and integrates 2.32 million records to predict 8,297 species across seven taxonomic groups. Shared representation models outperformed species-specific models in four groups and extended predictions to species with few records. Five independent datasets, including structured monitoring, environmental DNA and complete forest inventories, confirmed that the models ranked observed species and occupied sites above alternatives, with median AUCs of 0.724 to 0.894 across sites and 0.650 to 0.841 across species. For any user-selected area, the platform returns candidate species, distribution predictions, a biodiversity map corrected for uneven observation effort, a conservation priority map for native species and a map recommending where to survey next. This map highlights places where species with few records are predicted to occur despite limited sampling. Independent observations showed that areas ranked highly by this predicted potential contained many such species, indicating that model predictions can help direct surveys toward knowledge gaps. New observations are incorporated into monthly updates, creating a national feedback system connecting citizen science, local conservation decisions and future surveys.

The 17th Ebola outbreak in the Democratic Republic of the Congo, announced on 15 May 2026, was attributed to Bundibugyo ebolavirus (BDBV). Although case isolation is the main control strategy, its effectiveness is compromised when patients escape isolation facilities before recovery. Between 14 May and 17 June 2026, 175 individuals reportedly left isolation facilities without formal discharge across Ituri Province. We assessed how this "isolation leakage" affects community transmission. We refined the SEIHFR framework to distinguish undetected community infections, detected but not-yet-isolated cases, isolated individuals, leakage, funeral-associated transmission, and removals. Using Bayesian inference, we fitted the model to daily Ituri surveillance data, escapee counts, and isolation census records. We estimated the leakage rate, reporting and detection probabilities, and the transmission rate, while fixing other parameters based on the BDBV literature. The model reproduced confirmed cases, deaths, discharges, and escapees. We estimated R_0=3.67 (95% HDI: 2.0-5.7), a leakage rate of {rho} {approx} 0.034 day^-1 (0.022-0.051), and high contact-tracing-driven detection (p_d {approx} 0.91-0.99). Leakage increased the detection-dependent reproduction number [R](p_d) from approximately 3.2 to above 5. Eliminating leakage reduced cumulative infections by about one-third, from 1,120 to 764, while the minimum detection level required for control increased from p_d [&ge;] 0.73 without leakage to p_d [&ge;] 0.87 at the fitted leakage rate. Shortening time to isolation prevented the most infections (73.4%; 59-84), followed by reducing leakage (29.7%; 14-52) and re-isolating escapees (12.6%; 6-24). Delaying leakage reduction until week 4 reduced its benefit from about 27% to below 2%. Isolation leakage represents a major transmission pathway that has until now gone largely unmeasured. While rapid initiation of isolation is highly beneficial, it cannot compensate for permeable isolation; therefore, early, community-driven efforts to control leakage, embedded within a multilayered response, are critical.

Squid abundance has been reported to increase globally between 1970 and 2010. This increase has been hypothesized to result from two primary factors: the loss of top predators due to overfishing and rising ocean temperatures. The decline in apex predators may lead to the expansion of squid populations either through reduced predation pressure or diminished competition with juvenile predators. Concurrently, increased temperatures could enhance the somatic growth rates of squid, thereby accelerating their population growth. However, empirically disentangling the impacts of predator loss and temperature on squid biomass remains challenging, especially in a food-web context. In this study, we used a size- and trait-based model of upper trophic levels that resolves the ecosystem structure -- biomass and trophic interactions of fish and squid -- for varying depth, temperature, and secondary production, to investigate two hypotheses of the historical expansion of squid, i.e., the effects of predator depletion from fishing and rising temperatures on squid biomass. Our model reveals that intensified fishing of squid predators -- specifically large demersal fish in shelf systems and large pelagic fish in open oceans -- leads to a slight increase in squid biomass. Conversely, elevated temperatures are associated with a decline in squid biomass. This temperature-driven reduction in biomass is attributed to an increased metabolism of squids beyond the available food supply. If historic overfishing on large marine predators continues to be curtailed, we expect a corresponding reduction in global squid biomass and fisheries potential, which could be further exacerbated by rising temperatures.

Human deep-space missions face bone-kidney risks that cannot be extrapolated from six-month ISS data. We built a 12-state Ca-bone-urine-stone mechanistic ODE model and jointly calibrated its 11 physiological parameters on eight ISS targets by Bayesian identification (M0 base = 19-D; M1 extension adds a GCR-bone coupling term for parsimony testing only), then propagated the M0 posterior to four environments (ISS, Lunar subsurface, Lunar surface, Mars). Lumbar-lower BMD loss increases with mission duration and partial-gravity unloading (ISS 180 d -4.83% -> Mars 730 d -12.15%; 2^3 factorial: duration 82.9%, gravity 12.5%, GCR main effect ~ 0), whereas stone rate follows the opposite gradient (ISS 16.1 vs Mars 13.1 per 1000 person-years), reflecting weakened partial-gravity bone resorption alongside residual urinary chemistry changes. The dominant pathway thus shifts from bone-centric on the ISS to kidney-centric on Mars, where residual urinary-chemistry changes-not bone resorption-drive stone risk. The direct GCR-bone coupling term is unidentifiable at current ISS doses (DeltaWAIC = +0.0076 +/- 0.126 SE), so M0 is retained as the main inference model. Bisphosphonates provide >=84% BMD protection but leave a urinary-chemistry residual, so bisphosphonate monotherapy would underestimate Mars stone risk; potassium-magnesium-citrate combinations (RRR_RSS 51%) should therefore be added to deep-space countermeasures. A Lunar-surface 365-day mission is the earliest environment on the NASA roadmap to cross a composite RED threshold. That profile differs from the regolith-shielded 180-day case in both cumulative GCR (~69x) and duration (2x), so a shielding-specific effect cannot be isolated here; forcing the GCR coupling terms to zero leaves all four composite tiers unchanged (0/4, Supp S24), and the shielded 180-day profile is YELLOW rather than GREEN. Independent hold-out validation (Culliton 2025 60-day HDT-bedrest RCT, n=8 control arm of n=24 total) supports the M0 posterior predictive distribution on the lumbar-BMD sub-scope.

Background Floods are among the most devastating natural disasters worldwide and are increasingly associated with adverse mental health outcomes, particularly Post-Traumatic Stress Disorder (PTSD). In December 2023, Hanang District in northern Tanzania experienced catastrophic mud floods that resulted in extensive loss of life, destruction of property, displacement of households, and disruption of livelihoods. While emergency humanitarian responses focused primarily on physical needs, limited evidence exists regarding the long-term psychological consequences among survivors. Therefore, this study aimed to determine the patterns of PTSD manifestations and assess cognitive factors associated with PTSD symptoms among flood victims in Hanang District, Tanzania. Methods A community-based cross-sectional study was conducted among 360 flood victims one year after the disaster. PTSD symptoms were assessed using the PTSD Checklist for DSM-5 (PCL-5). Descriptive statistics summarized PTSD severity, while chi-square tests and regression analyses examined associations between socio-demographic characteristics and PTSD manifestations. Cognitive factors were assessed based on participants' exposure to traumatic experiences and perceptions of traumatic events. Results The mean PCL-5 score was 39.2 (SD = 20.6), indicating a high burden of psychological distress. Approximately 45% of respondents had severe PTSD symptoms (PCL-5 [&ge;]45), while another substantial proportion demonstrated moderate symptom severity. PTSD manifestations varied significantly by geographical location (p < 0.001), household income (p = 0.011), and marital status (p = 0.002). Age positively predicted PTSD severity ({beta} = 0.019, p = 0.001), whereas household income negatively predicted symptom severity ({beta} = -0.297, p = 0.001). Exposure to natural disasters constituted the predominant cognitive factor, with 45% directly experiencing the flood and 38.3% witnessing the event. Exposure to secondary traumatic experiences through witnessing or learning about violent events was also common. Cognitive trauma exposure demonstrated a significant association with PTSD symptoms ({chi}2, p < 0.001). Conclusion PTSD remains highly prevalent among flood survivors in Hanang district. Both direct and indirect trauma exposure significantly contributed to PTSD manifestations. Comprehensive disaster recovery programmes should integrate trauma-focused psychological services, cognitive behavioural interventions, routine PTSD screening, and community-based psychosocial support alongside socioeconomic recovery initiatives.

All primary healthcare centers owned by the Ugandan government in the Western Region of Uganda were submitted to a questionnaire concerning current availability of POCT from the Essential diagnostic List 2 part 1a and 1b, and the African laboratory inventory done by African Society of Laboratory Medicine and AfricaCDC. The data from the questionnaire was then linked to open source geodata provided by TomTom, and population data to calculate and visualize the accessibility of captured POCT. Findings: Availability of POCT Malaria is almost 100%, HIV 68-90%, and >30% for a majority of the POCT in the EDL-2 panel. 90% of the population in Western Region live within 1 hour by car from most of the essential POCT. Figures in the complementary web-based application visualize the accessibility of POCT for Western Uganda. Diagnostic deserts are visualized. Interpretation: Access to POCT at primary health care facilities in western Uganda has expanded substantially over the past decades. The geo-mapping tool presented here could inform policy decisions on strengthening diagnostic capacity at the national, regional, and provincial level. Funding: Swedish Research Council and Infravis All supplementary materials and a preprint of this submission are available on our OSF repository https://osf.io/j7puk/.

Purpose: This study assesses the association between colorectal cancer (CRC) screening and a validated, housing-based measure of individual-level socioeconomic status (SES, called HOUSES hereafter) within rural communities and determines whether HOUSES-integrated geospatial analysis can be used to tailor interventions. Methods: We used CRC screening data from a subset of Mayo Clinic Midwest patients living in cities without ready access to routine care in the Mayo Clinic Health System in 2019 to represent rural communities. At the individual level, we assessed the association between CRC screening rates and the HOUSES index, adjusting for age, sex, race/ethnicity, comorbidity, distance from home address to clinic, and area deprivation index, using a multilevel mixed-effects logistic regression model. Additionally, we conducted geospatial analysis to examine the correlation between hotspots of 1) lower CRC screening rates and 2) lower SES of the subject population (HOUSES quartile 1). Findings: Among 34,489 individuals (median age 64.0 years, 52.4% female), those with the lowest SES (HOUSES Q1) had 37% lower odds of being CRC screening adherent than those with the highest SES (HOUSES Q4) (adj. OR [95% CI]: 0.63 [0.58-0.69]). In the 14 identified HOUSES Q1 hotspots, there was a significant correlation in counts of HOUSES Q1 and low CRC screening (correlation coefficient=0.81). Conclusion: Lower SES was significantly associated with lower CRC screening among rural populations. HOUSES-enabled geospatial analysis identified geographic hotspots with lower CRC screening rates for targeted interventions to address disparities in CRC screening in rural communities. HOUSES may be a useful digital tool for cancer preventive care and research.

The analysis uses a global 2010-2023 panel comprising 3,038 economy-years across 217 economies. It explicitly separates between-economy and within-economy estimands and tests the longitudinal interpretation using an identical-sample temporal analysis with cluster-aware coefficient contrasts, a formal isometric log-ratio sensitivity analysis, independent fixed-effects replication, and wild-cluster-bootstrap inference. The central finding is deliberately calibrated: cross-economy agreement cannot validate national sugar availability for longitudinal obesity surveillance. The study identifies temporal and construct instability without claiming that sugar is protective or that the mechanisms producing the instability have been identified. The manuscript aligns well with PLOS ONEs emphasis on technically sound, transparent and reproducible research of broad relevance. All data required to reproduce the findings, complete metadata, executable code, full-precision results, diagnostic outputs and a completed STROBE checklist are provided as S1-S5. Figures are provided separately as compliant 350-dpi TIFF files. The study used only publicly available, aggregated economy-year statistics and involved no individual participants, identifiable information or biological specimens; institutional ethics review and consent were therefore not required. This is original work; it is not under consideration elsewhere, and the sole author has approved the submission and accepts responsibility for its content. Funding and competing-interest declarations will be entered accurately in the submission portal. An Academic Editor with expertise in nutritional epidemiology, global health metrics, longitudinal panel methods, or food-system surveillance would be well placed to assess the work.