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Fil: Sykes, Abagael. London Centre for Neglected Tropical Disease Research, Londres, Inglaterra Fil: Larrieu, Edmundo. Universidad Nacional de Rio Negro, Escuela de Veterinaria. Rio Negro, Argentina. Fil: Poggio, Veronica. Instituto Cesar Milstein, Buenos Aires Fil: Cespedes, Graciela. Instituto Malbran, Parasitologia, Buenos Aires Fil: Mugica, Guillermo. Ministerio de salud de rio negro, Salud Ambiental, Rio Negro Fil: Basanez, Maria Gloria. London Centre for Neglected Tropical Disease Research, Londres, Inglaterra Fil: Prada, Joaquin. London Centre for Neglected Tropical Disease Research, Londres, Inglaterra Echinococcus granulosus sensu lato is a globally prevalent zoonotic parasitic cestode leading to cystic echinococcosis (CE) in both humans and sheep with both medical and financial impacts, whose reduction requires the application of a One Health approach to its control. Regarding the animal health component of this approach, lack of accurate and practical diagnostics in livestock impedes the assessment of disease burden and the implementation and evaluation of control strategies. We use of a Bayesian Latent Class Analysis (LCA) model to estimate ovine CE prevalence in sheep samples from the Río Negro province of Argentina accounting for uncertainty in the diagnostics. We use model outputs to evaluate the performance of a novel recombinant B8/2 antigen B subunit (rEgAgB8/2) indirect enzyme-linked immunosorbent assay (ELISA) for detecting E. granulosus in sheep. Necropsy (as a partial gold standard), western blot (WB) and ELISA diagnostic data were collected from 79 sheep within two Río Negro slaughterhouses, and used to estimate individual infection status (assigned as a latent variable within the model). Using the model outputs, the performance of the novel ELISA at both individual and flock levels was evaluated, respectively, using a receiver operating characteristic (ROC) curve, and simulating a range of sample sizes and prevalence levels within hypothetical flocks. The estimated (mean) prevalence of ovine CE was 27.5% (95%Bayesian credible interval (95%BCI): 13.8%–58.9%) within the sample population. At the individual level, the ELISA had a mean sensitivity and specificity of 55% (95%BCI: 46%–68%) and 68% (95%BCI: 63%–92%), respectively, at an optimal optical density (OD) threshold of 0.378. At the flock level, the ELISA had an 80% probability of correctly classifying infection at an optimal cut-off threshold of 0.496. These results suggest that the novel ELISA could play a useful role as a flock-level diagnostic for CE surveillance in the region, supplementing surveillance activities in the human population and thus strengthening a One Health approach. Importantly, selection of ELISA cut-off threshold values must be tailored according to the epidemiological situation Echinococcus granulosus sensu lato es un cestodo parasitario zoonótico de prevalencia mundial que causa equinococosis quística (EC) tanto en humanos como en ovejas con impactos médicos y financieros, cuya reducción requiere la aplicación de un enfoque de One Health para su control. Con respecto al componente de salud animal de este enfoque, la falta de diagnósticos precisos y prácticos en el ganado impide la evaluación de la carga de la enfermedad y la implementación y evaluación de estrategias de control. Usamos un modelo Bayesiano de Análisis de Clase Latente (LCA) para estimar la prevalencia de CE ovina en muestras de ovinos de la provincia de Río Negro de Argentina teniendo en cuenta la incertidumbre en el diagnóstico. Utilizamos los resultados del modelo para evaluar el rendimiento de un nuevo B8/2 recombinante subunidad del antígeno B (rEgAgB8/2) ensayo inmunoabsorbente ligado a enzimas indirecto (ELISA) para detectar E. granulosus en ovejas Los datos de diagnóstico de necropsia (como estándar de oro parcial), western blot (WB) y ELISA se recopilaron de 79 ovejas dentro de dos mataderos de Río Negro, y se utilizó para estimar el estado de infección individual (asignado como variable latente dentro del modelo). Utilizando los resultados del modelo, se evaluó el rendimiento del nuevo ELISA a nivel individual y de parvada, respectivamente, utilizando una curva característica operativa del receptor (ROC), y simular un rango de tamaños de muestra y niveles de prevalencia dentro de bandadas hipotéticas. La (media) estimada la prevalencia de EC ovina fue del 27,5 % (95 % intervalo creíble bayesiano (95 % BCI): 13,8 %–58,9 %) dentro de la muestra población. A nivel individual, el ELISA tuvo una sensibilidad y especificidad medias del 55% (95%BCI: 46%–68%) y 68 % (95 % BCI: 63 %–92 %), respectivamente, en un umbral óptimo de densidad óptica (OD) de 0,378. en el rebaño nivel, el ELISA tenía un 80% de probabilidad de clasificar correctamente la infección en un umbral de corte óptimo de 0,496. Estos resultados sugieren que el nuevo ELISA podría desempeñar un papel útil como diagnóstico a nivel de parvada para la vigilancia de CE en la región, complementando las actividades de vigilancia en la población humana y fortaleciendo así una Enfoque de salud. Es importante destacar que la selección de los valores de umbral de corte de ELISA debe adaptarse de acuerdo con la situación epidemiológica

Objective To determine the effects of missing and inconsistent data on a weight management mail survey results. Patients and Methods Weight management surveys were sent to 5000 overweight and obese individuals in the Learning Health System Network. Survey information was collected between October 27, 2017, and March 1, 2018. Some participants reported body mass index (BMI) values inconsistent with the intended overweight and obese sampling cohort. Analyses were performed after excluding these surveys and also performed again after setting these low BMI values to missing. Models were run after imputing missing values using expectation-maximization, Markov chain Monte Carlo, random forest imputation, multivariate imputation by chained equations, and multiple imputation and replacing missing BMI values with the minimum, maximum, mean, or median of the known BMI values. Results Of 2799 surveys, 222 (8%) had missing BMI values and 155 (6%) reported invalid BMI values. Overall, 725 of these 2799 surveys (26%) were missing at least 1 variable that was essential to the main analyses. Different imputation methods consistently found that BMI was related to age, sex, race, marital status, and education. Patients with a BMI of 35.0 kg/m2 or greater were more likely to feel judged because of their weight, and patients with a BMI of 40.0 kg/m2 or greater were more likely to feel they were not always treated with respect and treated as an equal. Conclusion Analyses using different imputation methods were consistent with the original published results. Missing data likely did not affect the study results.

A holistic view of racial and gender disparities that simultaneously compares multiple groups can suggest associated underlying contextual factors. Therefore, to more comprehensively understand temporal changes in combined racial and gender disparities, we examine variations in the orders of county-level race-gender specific heart disease death rates by age group from 1973–2015. We estimated county-level heart disease death rates by race, gender, and age group (35–44, 45–54, 55–64, 65–74, 75–84, ≥ 85, and ≥ 35) from the National Vital Statistics System of the National Center for Health Statistics from 1973–2015. We then ordered these rates from lowest to highest for each county and year. The predominant national rate order (i.e., white women (WW) < black women (BW) < white men (WM) < black men (BM)) was most common in younger age groups. Inverted rates for black women and white men (WW, Highlights • Combined racial and gender disparities can suggest underlying contextual factors. • We examined counties’ rate orders of race-gender specific heart disease mortality. • Many counties experienced rate orders that were not observed nationally. • Many counties had higher rates for black women than white men. • Socioeconomic forces may drive heart disease mortality more than biology.