Submesoscale dispersion in the vicinity of the Deepwater Horizon spill

Reliable forecasts for the dispersion of oceanic contamination are important for coastal ecosystems, society and the economy as evidenced by the Deepwater Horizon oil spill in the Gulf of Mexico in 2010 and the Fukushima nuclear plant incident in the Pacific Ocean in 2011. Accurate prediction of pollutant pathways and concentrations at the ocean surface requires understanding ocean dynamics over a broad range of spatial scales. Fundamental questions concerning the structure of the velocity field at the submesoscales (100 meters to tens of kilometers, hours to days) remain unresolved due to a lack of synoptic measurements at these scales. \textcolor{black} {Using high-frequency position data provided by the near-simultaneous release of hundreds of accurately tracked surface drifters, we study the structure of submesoscale surface velocity fluctuations in the Northern Gulf Mexico. Observed two-point statistics confirm the accuracy of classic turbulence scaling laws at 200m$-$50km scales and clearly indicate that dispersion at the submesoscales is \textit{local}, driven predominantly by energetic submesoscale fluctuations.} The results demonstrate the feasibility and utility of deploying large clusters of drifting instruments to provide synoptic observations of spatial variability of the ocean surface velocity field. Our findings allow quantification of the submesoscale-driven dispersion missing in current operational circulation models and satellite altimeter-derived velocity fields.Comment: 9 pages, 6 figure

On the Nature of the Frontal Zone of the Choctawhatchee Bay Plume in the Gulf of Mexico

River plumes often feature turbulent processes in the frontal zone and interfacial region at base of the plume, which ultimately impact spreading and mixing rates with the ambient coastal ocean. The degree to which these processes govern overall plume mixing is yet to be quantified with microstructure observations. A field campaign was conducted in a river plume in the northeast Gulf of Mexico in December 2013, in order to assess mixing processes that could potentially impact transport and dispersion of surface material near coastal regions. Current velocity, density, and Turbulent Kinetic Energy Values, ε, were obtained using an Acoustic Doppler Current Profiler (ADCP), a Conductivity Temperature Depth (CTD) profiler, a Vertical Microstructure Profiler (VMP), and two Acoustic Doppler Velocimeters (ADVs). The frontal region contained ε values on the order of 10−5 m2 s−3, which were markedly larger than in the ambient water beneath (O 10−9 m2s−3). An energetic wake of moderate ε values (O 10−6 m2 s−3) was observed trailing the frontal edge. The interfacial region of an interior section of the plume featured opposing horizontal velocities and a ε value on the order of 10−6 m2 s−3. A simplified mixing budget was used under significant assumptions to compare contributions from wind, tides, and frontal regions of the plume. The results from this order of magnitude analysis indicated that frontal processes (59%) dominated in overall mixing. This emphasizes the importance of adequate parameterization of river plume frontal processes in coastal predictive models

Measurements of morphodynamics of a sheltered beach along the Dutch Wadden Sea

A field campaign was carried out at a sheltered sandy beach with the aim of gaining new insights into the driving processes behind sheltered beach morphodynamics. Detailed measurements of the local hydrodynamics, bed-level changes and sediment composition were collected at a man-made beach on the leeside of the barrier island Texel, bordering the Marsdiep basin that is part of the Dutch Wadden Sea. The dataset consists of (1) current, wave and turbidity measurements from a dense cross-shore array and a 3 km alongshore array; (2) sediment composition data from beach surface samples; (3) high-temporal-resolution RTK-GNSS beach profile measurements; (4) a pre-campaign spatially covering topobathy map; and (5) meteorological data. This paper outlines how these measurements were set up and how the data have been processed, stored and can be accessed. The novelty of this dataset lies in the detailed approach to resolve forcing conditions on a sheltered beach, where morphological evolution is governed by a subtle interplay between tidal and wind-driven currents, waves and bed composition, primarily due to the low-energy (near-threshold) forcing. The data are publicly available at 4TU Centre for Research Data at: https://doi.org/10.4121/19c5676c-9cea-49d0-b7a3-7c627e436541 (Van der Lugt et al., 2023).</p

Implications of the HIV testing protocol for refusal bias in seroprevalence surveys

BACKGROUND: HIV serosurveys have become important sources of HIV prevalence estimates, but these estimates may be biased because of refusals and other forms of non-response. We investigate the effect of the post-test counseling study protocol on bias due to the refusal to be tested. METHODS: Data come from a nine-month prospective study of hospital admissions in Addis Ababa during which patients were approached for an HIV test. Patients had the choice between three consent levels: testing and post-test counseling (including the return of HIV test results), testing without post-test counseling, and total refusal. For all patients, information was collected on basic sociodemographic background characteristics as well as admission diagnosis. The three consent levels are used to mimic refusal bias in serosurveys with different post-test counseling study protocols. We first investigate the covariates of consent for testing. Second, we quantify refusal bias in HIV prevalence estimates using Heckman regression models that account for sample selection. RESULTS: Refusal to be tested positively correlates with admission diagnosis (and thus HIV status), but the magnitude of refusal bias in HIV prevalence surveys depends on the study protocol. Bias is larger when post-test counseling and the return of HIV test results is a prerequisite of study participation (compared to a protocol where test results are not returned to study participants, or, where there is an explicit provision for respondents to forego post-test counseling). We also find that consent for testing increased following the introduction of antiretroviral therapy in Ethiopia. Other covariates of refusal are age (non-linear effect), gender (higher refusal rates in men), marital status (lowest refusal rates in singles), educational status (refusal rate increases with educational attainment), and counselor. CONCLUSION: The protocol for post-test counseling and the return of HIV test results to study participants is an important consideration in HIV prevalence surveys that wish to minimize refusal bias. The availability of ART is likely to reduce refusal rates

Genetics of self-reported risk-taking behaviour, trans-ethnic consistency and relevance to brain gene expression

Risk-taking behaviour is an important component of several psychiatric disorders, including attention-deficit hyperactivity disorder, schizophrenia and bipolar disorder. Previously, two genetic loci have been associated with self-reported risk taking and significant genetic overlap with psychiatric disorders was identified within a subsample of UK Biobank. Using the white British participants of the full UK Biobank cohort (n = 83,677 risk takers versus 244,662 controls) for our primary analysis, we conducted a genome-wide association study of self-reported risk-taking behaviour. In secondary analyses, we assessed sex-specific effects, trans-ethnic heterogeneity and genetic overlap with psychiatric traits. We also investigated the impact of risk-taking-associated SNPs on both gene expression and structural brain imaging. We identified 10 independent loci for risk-taking behaviour, of which eight were novel and two replicated previous findings. In addition, we found two further sex-specific risk-taking loci. There were strong positive genetic correlations between risk-taking and attention-deficit hyperactivity disorder, bipolar disorder and schizophrenia. Index genetic variants demonstrated effects generally consistent with the discovery analysis in individuals of non-British White, South Asian, African-Caribbean or mixed ethnicity. Polygenic risk scores comprising alleles associated with increased risk taking were associated with lower white matter integrity. Genotype-specific expression pattern analyses highlighted DPYSL5, CGREF1 and C15orf59 as plausible candidate genes. Overall, our findings substantially advance our understanding of the biology of risk-taking behaviour, including the possibility of sex-specific contributions, and reveal consistency across ethnicities. We further highlight several putative novel candidate genes, which may mediate these genetic effects

What explains gender inequalities in HIV/AIDS prevalence in sub-Saharan Africa? Evidence from the demographic and health surveys

Abstract Background Women are disproportionally affected by human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) in sub-Saharan Africa (SSA). The determinants of gender inequality in HIV/AIDS may vary across countries and require country-specific interventions to address them. This study aimed to identify the socio-demographic and behavioral characteristics underlying gender inequalities in HIV/AIDS in 21 SSA countries. Methods We applied an extension of the Blinder-Oaxaca decomposition approach to data from Demographic and Health Surveys and AIDS Indicator Surveys to quantify the differences in HIV/AIDS prevalence between women and men attributable to socio-demographic factors, sexual behaviours, and awareness of HIV/AIDS. We decomposed gender inequalities into two components: the percentage attributable to different levels of the risk factors between women and men (the “composition effect”) and the percentage attributable to risk factors having differential effects on HIV/AIDS prevalence in women and men (the “response effect”). Results Descriptive analyses showed that the difference between women and men in HIV/AIDS prevalence varied from a low of 0.68 % (P = 0.008) in Liberia to a high of 11.5 % (P < 0.001) in Swaziland. The decomposition analysis showed that 84 % (P < 0.001) and 92 % (P < 0.001) of the higher prevalence of HIV/AIDS among women in Uganda and Ghana, respectively, was explained by the different distributions of HIV/AIDS risk factors, particularly age at first sex between women and men. In the majority of countries, however, observed gender inequalities in HIV/AIDS were chiefly explained by differences in the responses to risk factors; the differential effects of age, marital status and occupation on prevalence of HIV/AIDS for women and men were among the significant contributors to this component. In Cameroon, Guinea, Malawi and Swaziland, a combination of the composition and response effects explained gender inequalities in HIV/AIDS prevalence. Conclusions The factors that explain gender inequality in HIV/AIDS in SSA vary by country, suggesting that country-specific interventions are needed. Unmeasured factors also contributed substantially to the difference in HIV/AIDS prevalence between women and men, highlighting the need for further study