The Original Boatload of Knowledge Down the Ohio River: William Maclure's and Robert Owen's Transfer of Science and Education to the Midwest, 1825-1826

Author Institution: Department of History, University of Southern Indiana... more learning than ever was before contained in a boat was Robert Owen's description of the Boatload of Knowledge that descended the Ohio River from Pittsburgh to his projected Utopia at New Harmony, Indiana, in the winter of 1825-26. Among the scientists and Pestalozzian educators aboard the keelboat christened Philanthropist were key figures from the Academy of Natural Sciences of Philadelphia. William Maclure was its president and the father of American geology. Thomas Say was the Academy's librarian, a conchologist later called the father of American descriptive entomology. Charles Alexandre Lesueur was the Academy's curator known as a naturalist, zoologist, ichthyologist, artist and teacher who made 127 sketches during the voyage. The research, publications, schools, libraries and reforms of those on the Boatload of Knowledge impacted scientifically, culturally, socially and economically to benefit the Midwest and the nation

How the Harmonists Suffered Disharmony: Schism in Communal Utopias

On this descendant reunion occasion, I will try to explain why the Harmony Society suffered disharmony, secessions, and schisms and to compare its experience with other well-known movements that attempted communal utopias

Evaluating epidemic forecasts in an interval format

For practical reasons, many forecasts of case, hospitalization and death counts in the context of the current COVID-19 pandemic are issued in the form of central predictive intervals at various levels. This is also the case for the forecasts collected in the COVID-19 Forecast Hub (https://covid19forecasthub.org/). Forecast evaluation metrics like the logarithmic score, which has been applied in several infectious disease forecasting challenges, are then not available as they require full predictive distributions. This article provides an overview of how established methods for the evaluation of quantile and interval forecasts can be applied to epidemic forecasts in this format. Specifically, we discuss the computation and interpretation of the weighted interval score, which is a proper score that approximates the continuous ranked probability score. It can be interpreted as a generalization of the absolute error to probabilistic forecasts and allows for a decomposition into a measure of sharpness and penalties for over- and underprediction

Epidemic dynamics of respiratory syncytial virus in current and future climates.

A key question for infectious disease dynamics is the impact of the climate on future burden. Here, we evaluate the climate drivers of respiratory syncytial virus (RSV), an important determinant of disease in young children. We combine a dataset of county-level observations from the US with state-level observations from Mexico, spanning much of the global range of climatological conditions. Using a combination of nonlinear epidemic models with statistical techniques, we find consistent patterns of climate drivers at a continental scale explaining latitudinal differences in the dynamics and timing of local epidemics. Strikingly, estimated effects of precipitation and humidity on transmission mirror prior results for influenza. We couple our model with projections for future climate, to show that temperature-driven increases to humidity may lead to a northward shift in the dynamic patterns observed and that the likelihood of severe outbreaks of RSV hinges on projections for extreme rainfall

Time series analysis of malaria in Afghanistan: using ARIMA models to predict future trends in incidence

Additional file 6: Annex 1. Right side: Autocorrelation (ACF) and partial autocorrelation (PACF) functions of the residuals from ARIMA model (1, 0, 1) × (1, 0, 1)12 on log-transformed, differenced data. Left side: ACF and PACF of the residuals from ARIMA model (4, 0, 1) × (1, 0, 1)12 on log-transformed, differenced data

MORPHOLOGICAL AND PHYSIOLOGICAL RESPONSES TO IRRADIANCE IN THE CAM EPIPHYTE TILLANDSIA USNEOIDES L. (BROMELIACEAE)

This is the publisher's version, also available electronically from: http://www.jstor.org/stable/10.2307/2474626Spanish moss (Tillandsia usneoides L.) was collected in situ in South Carolina from sunny and shady locations and grown in a greenhouse under high and low irradiance. Morphological characteristics, including leaf size, internode length, trichome size and density, and stomatal size and density, were similar among plants at the different irradiance levels. Chlorophyll (Chi) a/b ratios did not change with irradiance, but total Chi concentrations were higher in plants exposed to lower irradiances. In spite of these changes in pigment composition, similar levels of nocturnal acidification were found in field, but not greenhouse, plants at all irradiance levels. Thus, Spanish moss can respond physiologically, but not morphologically, to changes in environmental irradiance levels. This ability should prove beneficial to an epiphyte growing in microsites of widely varying irradiance

Direct and indirect effects of rotavirus vaccination: Comparing predictions from transmission dynamic models

Early observations from countries that have introduced rotavirus vaccination suggest that there may be indirect protection for unvaccinated individuals, but it is unclear whether these benefits will extend to the long term. Transmission dynamic models have attempted to quantify the indirect protection that might be expected from rotavirus vaccination in developed countries, but results have varied. To better understand the magnitude and sources of variability in model projections, we undertook a comparative analysis of transmission dynamic models for rotavirus. We fit five models to reported rotavirus gastroenteritis (RVGE) data from England and Wales, and evaluated outcomes for short- and long-term vaccination effects. All of our models reproduced the important features of rotavirus epidemics in England and Wales. Models predicted that during the initial year after vaccine introduction, incidence of severe RVGE would be reduced 1.8-2.9 times more than expected from the direct effects of the vaccine alone (28-50% at 90% coverage), but over a 5-year period following vaccine introduction severe RVGE would be reduced only by 1.1-1.7 times more than expected from the direct effects (54-90% at 90% coverage). Projections for the long-term reduction of severe RVGE ranged from a 55% reduction at full coverage to elimination with at least 80% coverage. Our models predicted short-term reductions in the incidence of RVGE that exceeded estimates of the direct effects, consistent with observations from the United States and other countries. Some of the models predicted that the short-term indirect benefits may be offset by a partial shifting of the burden of RVGE to older unvaccinated individuals. Nonetheless, even when such a shift occurs, the overall reduction in severe RVGE is considerable. Discrepancies among model predictions reflect uncertainties about age variation in the risk and reporting of RVGE, and the duration of natural and vaccine-induced immunity, highlighting important questions for future research

High turnover drives prolonged persistence of influenza in managed pig herds.

Pigs have long been hypothesized to play a central role in the emergence of novel human influenza A virus (IAV) strains, by serving as mixing vessels for mammalian and avian variants. However, the key issue of viral persistence in swine populations at different scales is ill understood. We address this gap using epidemiological models calibrated against seroprevalence data from Dutch finishing pigs to estimate the 'critical herd size' (CHS) for IAV persistence. We then examine the viral phylogenetic evidence for persistence by comparing human and swine IAV. Models suggest a CHS of approximately 3000 pigs above which influenza was likely to persist, i.e. orders of magnitude lower than persistence thresholds for IAV and other acute viruses in humans. At national and regional scales, we found much stronger empirical signatures of prolonged persistence of IAV in swine compared with human populations. These striking levels of persistence in small populations are driven by the high recruitment rate of susceptible piglets, and have significant implications for management of swine and for overall patterns of genetic diversity of IAV.This work was supported by the RAPIDD program of the Science and Technology Directorate, Department of Homeland Security, and the Fogarty International Center, National Institutes of Health (V.E.P., S.R., J.L.N.W. and B.T.G.) and the Bill & Melinda Gates Foundation (V.E.P. and B.T.G.). J.L.N.W. is also supported by the Alborada Trust, the European Union FP7 project ANTIGONE (contract no. 278976) and by Biotechnology and Biological Sciences Research Council sLOLA BB/L001330/1.This is the final version of the article. It first appeared from Royal Society Publishing via http://dx.doi.org/10.1098/rsif.2016.013

Calibration of individual-based models to epidemiological data : a systematic review

Individual-based models (IBMs) informing public health policy should be calibrated to data and provide estimates of uncertainty. Two main components of model-calibration methods are the parameter-search strategy and the goodness-of-fit (GOF) measure; many options exist for each of these. This review provides an overview of calibration methods used in IBMs modelling infectious disease spread. We identified articles on PubMed employing simulation-based methods to calibrate IBMs informing public health policy in HIV, tuberculosis, and malaria epidemiology published between 1 January 2013 and 31 December 2018. Articles were included if models stored individual-specific information, and calibration involved comparing model output to population-level targets. We extracted information on parameter-search strategies, GOF measures, and model validation. The PubMed search identified 653 candidate articles, of which 84 met the review criteria. Of the included articles, 40 (48%) combined a quantitative GOF measure with an algorithmic parameter-search strategy–either an optimisation algorithm (14/40) or a sampling algorithm (26/40). These 40 articles varied widely in their choices of parameter-search strategies and GOF measures. For the remaining 44 (52%) articles, the parameter-search strategy could either not be identified (32/44) or was described as an informal, non-reproducible method (12/44). Of these 44 articles, the majority (25/44) were unclear about the GOF measure used; of the rest, only five quantitatively evaluated GOF. Only a minority of the included articles, 14 (17%) provided a rationale for their choice of model-calibration method. Model validation was reported in 31 (37%) articles. Reporting on calibration methods is far from optimal in epidemiological modelling studies of HIV, malaria and TB transmission dynamics. The adoption of better documented, algorithmic calibration methods could improve both reproducibility and the quality of inference in model-based epidemiology. There is a need for research comparing the performance of calibration methods to inform decisions about the parameter-search strategies and GOF measures