Abstract. Large tropical trees store significant amounts of carbon in woody components and their distribution plays an important role in forest carbon stocks and dynamics. Here, we explore the properties of a new lidar-derived index, the large tree canopy area (LCA) defined as the area occupied by canopy above a reference height. We hypothesize that this simple measure of forest structure representing the crown area of large canopy trees could consistently explain the landscape variations in forest volume and aboveground biomass (AGB) across a range of climate and edaphic conditions. To test this hypothesis, we assembled a unique dataset of high-resolution airborne light detection and ranging (lidar) and ground inventory data in nine undisturbed old-growth Neotropical forests, of which four had plots large enough (1 ha) to calibrate our model. We found that the LCA for trees greater than 27 m (∼ 25–30 m) in height and at least 100 m2 crown size in a unit area (1 ha), explains more than 75 % of total forest volume variations, irrespective of the forest biogeographic conditions. When weighted by average wood density of the stand, LCA can be used as an unbiased estimator of AGB across sites (R2 = 0.78, RMSE = 46.02 Mg ha−1, bias = −0.63 Mg ha−1). Unlike other lidar-derived metrics with complex nonlinear relations to biomass, the relationship between LCA and AGB is linear and remains unique across forest types. A comparison with tree inventories across the study sites indicates that LCA correlates best with the crown area (or basal area) of trees with diameter greater than 50 cm. The spatial invariance of the LCA–AGB relationship across the Neotropics suggests a remarkable regularity of forest structure across the landscape and a new technique for systematic monitoring of large trees for their contribution to AGB and changes associated with selective logging, tree mortality and other types of tropical forest disturbance and dynamics.

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Purpose: This qualitative study explores the barriers and facilitators to health care from the perspective of providers who care for patients without documentation status in the San Francisco Bay Area. Methods: Twenty-four direct providers were interviewed using semi-structured in-depth interviews. Participants included health care providers and community-based organization leaders. Interviews were independently coded using grounded theory analysis. The socioecological framework was used to develop the interview guide, analyze findings, and guide the discussion. Results: Participants identified fear as a barrier that transcended multiple levels of influence. At the public policy level, national policies, such as public charge and anti-immigration rhetoric, limited access to services. Local expansion of health care coverage, such as Healthy San Francisco, facilitated access to care. At the organizational level, law enforcement presence generated fear. This was countered by a welcoming environment, described as culturally concordant clinical sites, representation of the community in the provider pool, and resources to address social needs. Individual-level fear, rooted in trauma and economic insecurity, was eased by trauma-informed care and health navigators. Community engagement and sustained partnerships built trust and credibility to transcend the fear that hindered access to care. Conclusion: In a region with expansive policies for improved health care access, barriers are rooted in fear and span individual, organizational, and public policy levels of access to care. Richer community engagement may lessen the national and systemic barriers that this vulnerable population continues to face. Developing an understanding of this topic improves health care providers' ability to meet the needs of this growing and vulnerable population.

Central nervous system infections (CNSI) are a leading cause of death and long-term disability in children. Using ICD-10 data from 2005 to 2015 from three central hospitals in Ho Chi Minh City (HCMC), Vietnam, we exploited generalized additive mixed models (GAMM) to examine the spatial-temporal distribution and spatial and climatic risk factors of paediatric CNSI, excluding tuberculous meningitis, in this setting. From 2005 to 2015, there were 9469 cases of paediatric CNSI; 33% were ⩽1 year old at admission and were mainly diagnosed with presumed bacterial CNSI (BI) (79%), the remainder were >1 year old and mainly diagnosed with presumed non-bacterial CNSI (non-BI) (59%). The urban districts of HCMC in proximity to the hospitals as well as some outer districts had the highest incidences of BI and non-BI; BI incidence was higher in the dry season. Monthly BI incidence exhibited a significant decreasing trend over the study. Both BI and non-BI were significantly associated with lags in monthly average temperature, rainfall, and river water level. Our findings add new insights into this important group of infections in Vietnam, and highlight where resources for the prevention and control of paediatric CNSI should be allocated.

Aim: Survival in patients with hepatocellular carcinoma (HCC) is impacted by stage of liver disease, tumor characteristics, and HCC surveillance in high-risk individuals. Factors associated with HCC tumor growth rate (TGR) and its influence on recurrence-free survival after treatment was investigated. Methods: TGR was calculated in 164 HCC patients with chronic viral hepatitis who had two consecutive magnetic resonance imaging or computed tomography scans ≥ 30 days apart prior to treatment and who were followed prospectively to determine the rates of recurrence-free survival. Results: The median TGR in 164 patients was 17.8% per month (mean 33.3% per month). Regression tree analysis indicated that the top three predictors of TGR were alpha-fetoprotein (AFP) levels (≥ 16.7 ng/mL), platelet counts (≥ 140,000 mm 3), and serum albumin level (< 3.55 g/dL). The regression tree identified patient groups with TGRs ranging from 0.65% to 39.4% per month. At a median follow-up of 22 months, the overall recurrence-free survival was 53.8%.