The Biodiversity and Climate Change Virtual Laboratory: Where ecology meets big data

Advances in computing power and infrastructure, increases in the number and size of ecological and environmental datasets, and the number and type of data collection methods, are revolutionizing the field of Ecology. To integrate these advances, virtual laboratories offer a unique tool to facilitate, expedite, and accelerate research into the impacts of climate change on biodiversity. We introduce the uniquely cloud-based Biodiversity and Climate Change Virtual Laboratory (BCCVL), which provides access to numerous species distribution modelling tools; a large and growing collection of biological, climate, and other environmental datasets; and a variety of experiment types to conduct research into the impact of climate change on biodiversity. Users can upload and share datasets, potentially increasing collaboration, cross-fertilisation of ideas, and innovation among the user community. Feedback confirms that the BCCVL's goals of lowering the technical requirements for species distribution modelling, and reducing time spent on such research, are being met

A vertical profile of PM10 dust concentrations measured during a regional dust event identified by MODIS Terra, western Queensland, Australia

Accurate determination of the spatiotemporal properties of dust plumes and their dust concentrations is essential for calibration of satellite products and the initialization and validation of numerical models that simulate the physical properties and affects of dust events. In this paper, we present a 500 m vertical profile of PM10 dust concentrations measured during a regional dust event in western Queensland, Australia. PM10 dust concentrations within the haze were found to be >20 times background ambient values and decreased with height following an exponential function. We apply an over-land algorithm to MODIS Terra satellite images of the dust haze to enhance its visual appearance against the bright land surface and define its size. In conjunction with the measured attenuation of dust concentrations with height we calculate the PM10 dust load of the plume to be ∼60% of that which would have been calculated assuming a constant dust concentration up to the dust ceiling height. Results extend previous findings from tower-based studies made close to the surface and confirm that atmospheric dust concentrations decrease rapidly with increasing height, thereby enabling more accurate calculation of atmospheric dust loads during synoptic-scale dust outbreaks

Effects of acute tryptophan depletion on executive function in healthy male volunteers

BACKGROUND: Neurocognitive impairment is frequently described in a number of psychiatric disorders and may be a direct consequence of serotonergic dysfunction. As impairments in executive functions are some of the most frequently described, the purpose of this study was to examine the performance of normal volunteers on a range of executive tasks following a transient reduction of central serotonin (5-HT) levels using the method of acute tryptophan depletion (ATD). METHODS: Fifteen healthy male subjects participated in a within-subject, double-blind, counterbalanced crossover study. ATD was induced by ingestion of a 100 g amino-acid drink. Executive function was evaluated using the Wisconsin Card Sorting Test, Stroop, Verbal Fluency and Trail Making. Visual analogue scales were administered to assess mood. RESULTS: Plasma free and total tryptophan concentrations were significantly reduced by the depleting drink (P < 0.001). ATD selectively improved motor speed/ attention on the Trails A test (P = 0.027), with no effect on subjective ratings of mood. Interaction effects between drink and the order of drink administration were observed on most neurocognitive tests. CONCLUSIONS: The improvement in simple motor speed/ attention following ATD is in keeping with the ascribed role of 5-HT in the cortex, however performance on tests of executive function is not robustly altered. The presence of interaction effects on most tasks suggests that subtle changes may occur but are masked, possibly by simple learning effects, in the context of a crossover design. This has implications for the design of future studies, particularly those examining executive functions

Global warming and recurrent mass bleaching of corals

During 2015–2016, record temperatures triggered a pan-tropical episode of coral bleaching, the third global-scale event since mass bleaching was first documented in the 1980s. Here we examine how and why the severity of recurrent major bleaching events has varied at multiple scales, using aerial and underwater surveys of Australian reefs combined with satellite-derived sea surface temperatures. The distinctive geographic footprints of recurrent bleaching on the Great Barrier Reef in 1998, 2002 and 2016 were determined by the spatial pattern of sea temperatures in each year. Water quality and fishing pressure had minimal effect on the unprecedented bleaching in 2016, suggesting that local protection of reefs affords little or no resistance to extreme heat. Similarly, past exposure to bleaching in 1998 and 2002 did not lessen the severity of bleaching in 2016. Consequently, immediate global action to curb future warming is essential to secure a future for coral reefs

A recurrent germline PAX5 mutation confers susceptibility to pre-B cell acute lymphoblastic leukemia

Somatic alterations of the lymphoid transcription factor gene PAX5 (also known as BSAP) are a hallmark of B cell precursor acute lymphoblastic leukemia (B-ALL)1–3, but inherited mutations of PAX5 have not previously been described. Here we report a new heterozygous germline variant, c.547G>A (p.Gly183Ser), affecting the octapeptide domain of PAX5 that was found to segregate with disease in two unrelated kindreds with autosomal dominant B-ALL. Leukemic cells from all affected individuals in both families exhibited 9p deletion, with loss of heterozygosity and retention of the mutant PAX5 allele at 9p13. Two additional sporadic ALL cases with 9p loss harbored somatic PAX5 substitutions affecting Gly183. Functional and gene expression analysis of the PAX5 mutation demonstrated that it had significantly reduced transcriptional activity. These data extend the role of PAX5 alterations in the pathogenesis of pre-B cell ALL and implicate PAX5 in a new syndrome of susceptibility to pre-B cell neoplasia

Comparative assessment of methods for short-term forecasts of COVID-19 hospital admissions in England at the local level

Background: Forecasting healthcare demand is essential in epidemic settings, both to inform situational awareness and facilitate resource planning. Ideally, forecasts should be robust across time and locations. During the COVID-19 pandemic in England, it is an ongoing concern that demand for hospital care for COVID-19 patients in England will exceed available resources. Methods: We made weekly forecasts of daily COVID-19 hospital admissions for National Health Service (NHS) Trusts in England between August 2020 and April 2021 using three disease-agnostic forecasting models: a mean ensemble of autoregressive time series models, a linear regression model with 7-day-lagged local cases as a predictor, and a scaled convolution of local cases and a delay distribution. We compared their point and probabilistic accuracy to a mean-ensemble of them all and to a simple baseline model of no change from the last day of admissions. We measured predictive performance using the weighted interval score (WIS) and considered how this changed in different scenarios (the length of the predictive horizon, the date on which the forecast was made, and by location), as well as how much admissions forecasts improved when future cases were known. Results: All models outperformed the baseline in the majority of scenarios. Forecasting accuracy varied by forecast date and location, depending on the trajectory of the outbreak, and all individual models had instances where they were the top- or bottom-ranked model. Forecasts produced by the mean-ensemble were both the most accurate and most consistently accurate forecasts amongst all the models considered. Forecasting accuracy was improved when using future observed, rather than forecast, cases, especially at longer forecast horizons. Conclusions: Assuming no change in current admissions is rarely better than including at least a trend. Using confirmed COVID-19 cases as a predictor can improve admissions forecasts in some scenarios, but this is variable and depends on the ability to make consistently good case forecasts. However, ensemble forecasts can make forecasts that make consistently more accurate forecasts across time and locations. Given minimal requirements on data and computation, our admissions forecasting ensemble could be used to anticipate healthcare needs in future epidemic or pandemic settings

Simulating respiratory disease transmission within and between classrooms to assess pandemic management strategies at schools

The global spread of coronavirus disease 2019 (COVID-19) has emphasized the need for evidence-based strategies for the safe operation of schools during pandemics that balance infection risk with the society\u27s responsibility of allowing children to attend school. Due to limited empirical data, existing analyses assessing school-based interventions in pandemic situations often impose strong assumptions, for example, on the relationship between class size and transmission risk, which could bias the estimated effect of interventions, such as split classes and staggered attendance. To fill this gap in school outbreak studies, we parameterized an individual-based model that accounts for heterogeneous contact rates within and between classes and grades to a multischool outbreak data of influenza. We then simulated school outbreaks of respiratory infectious diseases of ongoing threat (i.e., COVID-19) and potential threat (i.e., pandemic influenza) under a variety of interventions (changing class structures, symptom screening, regular testing, cohorting, and responsive class closures). Our results suggest that interventions changing class structures (e.g., reduced class sizes) may not be effective in reducing the risk of major school outbreaks upon introduction of a case and that other precautionary measures (e.g., screening and isolation) need to be employed. Class-level closures in response to detection of a case were also suggested to be effective in reducing the size of an outbreak

The impact of COVID-19 vaccination in prisons in England and Wales : a metapopulation model

Background: High incidence of cases and deaths due to coronavirus disease 2019 (COVID-19) have been reported in prisons worldwide. This study aimed to evaluate the impact of different COVID-19 vaccination strategies in epidemiologically semi-enclosed settings such as prisons, where staff interact regularly with those incarcerated and the wider community. Methods: We used a metapopulation transmission-dynamic model of a local prison in England and Wales. Two-dose vaccination strategies included no vaccination, vaccination of all individuals who are incarcerated and/or staff, and an age-based approach. Outcomes were quantified in terms of COVID-19-related symptomatic cases, losses in quality-adjusted life-years (QALYs), and deaths. Results: Compared to no vaccination, vaccinating all people living and working in prison reduced cases, QALY loss and deaths over a one-year period by 41%, 32% and 36% respectively. However, if vaccine introduction was delayed until the start of an outbreak, the impact was negligible. Vaccinating individuals who are incarcerated and staff over 50 years old averted one death for every 104 vaccination courses administered. All-staff-only strategies reduced cases by up to 5%. Increasing coverage from 30 to 90% among those who are incarcerated reduced cases by around 30 percentage points. Conclusions: The impact of vaccination in prison settings was highly dependent on early and rapid vaccine delivery. If administered to both those living and working in prison prior to an outbreak occurring, vaccines could substantially reduce COVID-19-related morbidity and mortality in prison settings

Estimating the impact of reopening schools on the reproduction number of SARS-CoV-2 in England, using weekly contact survey data

Background: Schools were closed in England on 4 January 2021 as part of increased national restrictions to curb transmission of SARS-CoV-2. The UK government reopened schools on 8 March. Although there was evidence of lower individual-level transmission risk amongst children compared to adults, the combined effects of this with increased contact rates in school settings and the resulting impact on the overall transmission rate in the population were not clear. Methods: We measured social contacts of > 5000 participants weekly from March 2020, including periods when schools were both open and closed, amongst other restrictions. We combined these data with estimates of the susceptibility and infectiousness of children compared with adults to estimate the impact of reopening schools on the reproduction number. Results: Our analysis indicates that reopening all schools under the same measures as previous periods that combined lockdown with face-to-face schooling would be likely to increase the reproduction number substantially. Assuming a baseline of 0.8, we estimated a likely increase to between 1.0 and 1.5 with the reopening of all schools or to between 0.9 and 1.2 reopening primary or secondary schools alone. Conclusion: Our results suggest that reopening schools would likely halt the fall in cases observed between January and March 2021 and would risk a return to rising infections, but these estimates relied heavily on the latest estimates or reproduction number and the validity of the susceptibility and infectiousness profiles we used at the time of reopening

Modelling the medium-term dynamics of SARS-CoV-2 transmission in England in the Omicron era

England has experienced a heavy burden of COVID-19, with multiple waves of SARS-CoV-2 transmission since early 2020 and high infection levels following the emergence and spread of Omicron variants since late 2021. In response to rising Omicron cases, booster vaccinations were accelerated and offered to all adults in England. Using a model fitted to more than 2 years of epidemiological data, we project potential dynamics of SARS-CoV-2 infections, hospital admissions and deaths in England to December 2022. We consider key uncertainties including future behavioural change and waning immunity and assess the effectiveness of booster vaccinations in mitigating SARS-CoV-2 disease burden between October 2021 and December 2022. If no new variants emerge, SARS-CoV-2 transmission is expected to decline, with low levels remaining in the coming months. The extent to which projected SARS-CoV-2 transmission resurges later in 2022 depends largely on assumptions around waning immunity and to some extent, behaviour, and seasonality