The human health effects of Florida Red Tide (FRT) blooms : an expanded analysis

Author Posting. © The Author(s), 2014. This is the author's version of the work. It is posted here by permission of Elsevier for personal use, not for redistribution. The definitive version was published in Environment International 68 (2014): 144-153, doi:10.1016/j.envint.2014.03.016.Human respiratory and digestive illnesses can be caused by exposures to brevetoxins from blooms of the marine alga Karenia brevis, also known as Florida red tide (FRT). K. brevis requires macro-nutrients to grow; although the sources of these nutrients have not been resolved completely, they are thought to originate both naturally and anthropogenically. The latter sources comprise atmospheric depositions, industrial effluents, land runoffs, or submerged groundwater discharges. To date, there has been only limited research on the extent of human health risks and economic impacts due to FRT. We hypothesized that FRT blooms were associated with increases in the numbers of emergency room visits and hospital inpatient admissions for both respiratory and digestive illnesses. We sought to estimate these relationships and to calculate the costs of associated adverse health impacts. We developed environmental exposure-response models to test the effects of FRT blooms on human health, using data from diverse sources. We estimated the FRT bloom-associated illness costs, using extant data and parameters from the literature. When controlling for resident population, a proxy for tourism, and seasonal and annual effects, we found that increases in respiratory and digestive illnesses can be explained by FRT blooms. Specifically, FRT blooms were associated with human health and economic effects in older cohorts (≥ 55 years of age) in six southwest Florida counties. Annual costs of illness ranged from $60,000 to$700,000 annually, but these costs could exceed $1.0 million per year for severe, long-lasting FRT blooms, such as the one that occurred during 2005. Assuming that the average annual illness costs of FRT blooms persist into the future, using a discount rate of 3$2-24 million.This research was sponsored by the National Science Foundation under NSF/CNH Grant No. 1009106.L.E. Fleming acknowledges support from the European Regional Development Fund and the European Social Fund Convergence Programme for Cornwall and the Isles of Scilly

Regional extent of an ecosystem engineer: earthworm invasion in northern hardwood forests

Abstract. The invasion of exotic earthworms into northern temperate and boreal forests previously devoid of earthworms is an important driver of ecosystem change. Earthworm invasion can cause significant changes in soil structure and communities, nutrient cycles, and the diversity and abundance of herbaceous plants. However, the regional extent and patterns of this invasion are poorly known. We conducted a regional survey in the Chippewa and Chequamegon National Forests, in Minnesota and Wisconsin, USA, respectively, to measure the extent and patterns of earthworm invasion and their relationship to potential earthworm introduction sites. We sampled earthworms, soils, and vegetation in 20 mature, sugar mapledominated forest stands in each national forest and analyzed the relationship between the presence of five earthworm taxonomic groups, habitat variables, and distance to the nearest potential introduction site. Earthworm invasion was extensive but incomplete in the two national forests. Four of the six earthworm taxonomic groups occurred in 55-95% of transects; however 20% of all transects were invaded by only one taxonomic group that has relatively minor ecological effects. Earthworm taxonomic groups exhibited a similar sequence of invasion found in other studies: Dendrobaena . Aporrectodea ¼ Lumbricus juveniles . L. rubellus . L. terrestris. Distance to the nearest road was the best predictor of earthworm invasion in Wisconsin while distance to the nearest cabin was the best predictor in Minnesota. These data allow us to make preliminary assessments of landscape patterns of earthworm invasion. As an example, we estimate that 82% of upland mesic hardwood stands in the Wisconsin region are likely invaded by most taxonomic groups while only 3% are unlikely to be invaded at present. Distance to roads and cabins provides a coarse-scale predictor of earthworm invasion to focus stand-level assessments that will help forest managers better understand current and potential forest conditions and identify uninvaded areas that could serve as important refugia for plant species threatened by earthworm invasion

The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application

Background: A novel human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified in China in December 2019. There is limited support for many of its key epidemiologic features, including the incubation period for clinical disease (coronavirus disease 2019 [COVID-19]), which has important implications for surveillance and control activities. Objective: To estimate the length of the incubation period of COVID-19 and describe its public health implications. Design: Pooled analysis of confirmed COVID-19 cases reported between 4 January 2020 and 24 February 2020. Setting: News reports and press releases from 50 provinces, regions, and countries outside Wuhan, Hubei province, China. Participants: Persons with confirmed SARS-CoV-2 infection outside Hubei province, China. Measurements: Patient demographic characteristics and dates and times of possible exposure, symptom onset, fever onset, and hospitalization. Results: There were 181 confirmed cases with identifiable exposure and symptom onset windows to estimate the incubation period of COVID-19. The median incubation period was estimated to be 5.1 days (95% CI, 4.5 to 5.8 days), and 97.5% of those who develop symptoms will do so within 11.5 days (CI, 8.2 to 15.6 days) of infection. These estimates imply that, under conservative assumptions, 101 out of every 10 000 cases (99th percentile, 482) will develop symptoms after 14 days of active monitoring or quarantine. Limitation: Publicly reported cases may overrepresent severe cases, the incubation period for which may differ from that of mild cases. Conclusion: This work provides additional evidence for a median incubation period for COVID-19 of approximately 5 days, similar to SARS. Our results support current proposals for the length of quarantine or active monitoring of persons potentially exposed to SARS-CoV-2, although longer monitoring periods might be justified in extreme cases

Canopy nitrogen, carbon assimilation, and albedo in temperate and boreal forests: Functional relations and potential climate feedbacks

The availability of nitrogen represents a key constraint on carbon cycling in terrestrial ecosystems, and it is largely in this capacity that the role of N in the Earth\u27s climate system has been considered. Despite this, few studies have included continuous variation in plant N status as a driver of broad-scale carbon cycle analyses. This is partly because of uncertainties in how leaf-level physiological relationships scale to whole ecosystems and because methods for regional to continental detection of plant N concentrations have yet to be developed. Here, we show that ecosystem CO2 uptake capacity in temperate and boreal forests scales directly with whole-canopy N concentrations, mirroring a leaf-level trend that has been observed for woody plants worldwide. We further show that both CO2 uptake capacity and canopy N concentration are strongly and positively correlated with shortwave surface albedo. These results suggest that N plays an additional, and overlooked, role in the climate system via its influence on vegetation reflectivity and shortwave surface energy exchange. We also demonstrate that much of the spatial variation in canopy N can be detected by using broad-band satellite sensors, offering a means through which these findings can be applied toward improved application of coupled carbon cycle–climate models

Political Leadership and Global Governance: Structural Power Versus Custodial Stewardship

This article examines the role of political leadership within the realm of global governance. Drawing upon relevant theories of political agency, particular attention is given to addressing the relationship between leadership and collective action. A two-level analysis of institution building in relation to maritime security and economic trade and investment reveals both strengths and weaknesses in practice. A review of the Law of the Sea Convention and the Multilateral Investment Agreement provides a salutary reminder that material power does not translate easily into dominating the rules of international conduct. The cases of the Asia Pacific Economic Cooperation Forum and the Trans-Pacific Partnership further highlight the importance of mixed sources of political leadership in responding to economic challenges at the regional level. The policy implication for both the United States and China is that taking the lead in Global Governance, either jointly or multilaterally, will require a renewed focus upon custodial stewardship that aims to realign interests with long-term goals

Diffuse continuum gamma rays from the Galaxy

A new study of the diffuse Galactic gamma-ray continuum radiation is presented, using a cosmic-ray propagation model which includes nucleons, antiprotons, electrons, positrons, and synchrotron radiation. Our treatment of the inverse Compton (IC) scattering includes the effect of anisotropic scattering in the Galactic interstellar radiation field (ISRF) and a new evaluation of the ISRF itself. Models based on locally measured electron and nucleon spectra and synchrotron constraints are consistent with gamma-ray measurements in the 30-500 MeV range, but outside this range excesses are apparent. A harder nucleon spectrum is considered but fitting to gamma rays causes it to violate limits from positrons and antiprotons. A harder interstellar electron spectrum allows the gamma-ray spectrum to be fitted above 1 GeV as well, and this can be further improved when combined with a modified nucleon spectrum which still respects the limits imposed by antiprotons and positrons. A large electron/IC halo is proposed which reproduces well the high-latitude variation of gamma-ray emission. The halo contribution of Galactic emission to the high-latitude gamma-ray intensity is large, with implications for the study of the diffuse extragalactic component and signatures of dark matter. The constraints provided by the radio synchrotron spectral index do not allow all of the <30 MeV gamma-ray emission to be explained in terms of a steep electron spectrum unless this takes the form of a sharp upturn below 200 MeV. This leads us to prefer a source population as the origin of the excess low-energy gamma rays.Comment: Final version accepted for publication in The Astrophysical Journal (vol. 537, July 10, 2000 issue); Many Updates; 20 pages including 49 ps-figures, uses emulateapj.sty. More details can be found at http://www.gamma.mpe-garching.mpg.de/~aws/aws.htm

Biotic and abiotic drivers of soil microbial functions across tree diversity experiments

Aim Soil microorganisms are essential for the functioning of terrestrial ecosystems. Although soil microbial communities and functions may be linked to the tree species composition and diversity of forests, there has been no comprehensive study of how general potential relationships are and if these are context-dependent. A global network of tree diversity experiments (TreeDivNet) allows for a first examination of tree diversity-soil microbial function relationships across environmental gradients. Location Global Major Taxa Studied Soil microorganisms Methods Soil samples collected from eleven tree diversity experiments in four biomes across four continents were used to measure soil basal respiration, microbial biomass, and carbon use efficiency using the substrate-induced respiration method. All samples were measured using the same analytical device in the same laboratory to prevent measurement bias. We used linear mixed-effects models to examine the effects of tree species diversity, environmental conditions, and their interactions on soil microbial functions. Results Across biodiversity experiments, abiotic drivers, mainly soil water content, significantly increased soil microbial functions. Potential evapotranspiration (PET) increased, whereas soil C-to-N ratio (CN) decreased soil microbial functions under dry soil conditions, but high soil water content reduced the importance of other abiotic drivers. Tree species richness and phylogenetic diversity had overall similar, but weak and context-dependent (climate, soil abiotic variables) effects on soil microbial respiration. Positive tree diversity effects on soil microbial respiration were most pronounced at low PET, low soil CN, and high tree density. Soil microbial functions increased with the age of the experiment. Main conclusions Our results point at the importance of soil water content for maintaining high levels of soil microbial functions and modulating effects of other environmental drivers. Moreover, overall tree diversity effects on soil microbial functions seem to be negligible in the short term (experiments were 1-18 years old). However, context-dependent tree diversity effects (climate, soil abiotic variables) have greater importance at high tree density, and significant effects of experimental age call for longer-term studies. Such systematic insights are key to better integrate soil carbon dynamics into the management of afforestation projects across environmental contexts, as today’s reforestation efforts remain focused largely on aboveground carbon storage and are still dominated by less diverse forests stands of commercial species

Dialectics and difference: against Harvey's dialectical post-Marxism

David Harvey`s recent book, Justice, nature and the geography of difference (JNGD), engages with a central philosophical debate that continues to dominate human geography: the tension between the radical Marxist project of recent decades and the apparently disempowering relativism and `play of difference' of postmodern thought. In this book, Harvey continues to argue for a revised `post-Marxist' approach in human geography which remains based on Hegelian-Marxian principles of dialectical thought. This article develops a critique of that stance, drawing on the work of Jacques Derrida, Gilles Deleuze and Felix Guattari. I argue that dialectical thinking, as well as Harvey's version of `post-Marxism', has been undermined by the wide-ranging `post-' critique. I suggest that Harvey has failed to appreciate the full force of this critique and the implications it has for `post-Marxist' ontology and epistemology. I argue that `post-Marxism', along with much contemporary human geography, is constrained by an inflexible ontology which excessively prioritizes space in the theory produced, and which implements inflexible concepts. Instead, using the insights of several `post-' writers, I contend there is a need to develop an ontology of `context' leading to the production of `contextual theories'. Such theories utilize flexible concepts in a multilayered understanding of ontology and epistemology. I compare how an approach which produces a `contextual theory' might lead to more politically empowering theory than `post-Marxism' with reference to one of Harvey's case studies in JNGD

Pharmacological risk factors associated with hospital readmission rates in a psychiatric cohort identified using prescriptome data mining

Background Worldwide, over 14% of individuals hospitalized for psychiatric reasons have readmissions to hospitals within 30 days after discharge. Predicting patients at risk and leveraging accelerated interventions can reduce the rates of early readmission, a negative clinical outcome (i.e., a treatment failure) that affects the quality of life of patient. To implement individualized interventions, it is necessary to predict those individuals at highest risk for 30-day readmission. In this study, our aim was to conduct a data-driven investigation to find the pharmacological factors influencing 30-day all-cause, intra- and interdepartmental readmissions after an index psychiatric admission, using the compendium of prescription data (prescriptome) from electronic medical records (EMR). Methods The data scientists in the project received a deidentified database from the Mount Sinai Data Warehouse, which was used to perform all analyses. Data was stored in a secured MySQL database, normalized and indexed using a unique hexadecimal identifier associated with the data for psychiatric illness visits. We used Bayesian logistic regression models to evaluate the association of prescription data with 30-day readmission risk. We constructed individual models and compiled results after adjusting for covariates, including drug exposure, age, and gender. We also performed digital comorbidity survey using EMR data combined with the estimation of shared genetic architecture using genomic annotations to disease phenotypes. Results Using an automated, data-driven approach, we identified prescription medications, side effects (primary side effects), and drug-drug interaction-induced side effects (secondary side effects) associated with readmission risk in a cohort of 1275 patients using prescriptome analytics. In our study, we identified 28 drugs associated with risk for readmission among psychiatric patients. Based on prescription data, Pravastatin had the highest risk of readmission (OR = 13.10; 95% CI (2.82, 60.8)). We also identified enrichment of primary side effects (n = 4006) and secondary side effects (n = 36) induced by prescription drugs in the subset of readmitted patients (n = 89) compared to the non-readmitted subgroup (n = 1186). Digital comorbidity analyses and shared genetic analyses further reveals that cardiovascular disease and psychiatric conditions are comorbid and share functional gene modules (cardiomyopathy and anxiety disorder: shared genes (n = 37; P = 1.06815E-06)). Conclusions Large scale prescriptome data is now available from EMRs and accessible for analytics that could improve healthcare outcomes. Such analyses could also drive hypothesis and data-driven research. In this study, we explored the utility of prescriptome data to identify factors driving readmission in a psychiatric cohort. Converging digital health data from EMRs and systems biology investigations reveal a subset of patient populations that have significant comorbidities with cardiovascular diseases are more likely to be readmitted. Further, the genetic architecture of psychiatric illness also suggests overlap with cardiovascular diseases. In summary, assessment of medications, side effects, and drug-drug interactions in a clinical setting as well as genomic information using a data mining approach could help to find factors that could help to lower readmission rates in patients with mental illness