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Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multi-model ensemble forecast that combined predictions from dozens of different research groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naive baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-week horizon 3-5 times larger than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks. Significance StatementThis paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the US. Results show high variation in accuracy between and within stand-alone models, and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public health action.
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ObjectivesIn most European countries, patients seeking medication abortion during the COVID-19 pandemic are still expected to attend healthcare settings in person despite lockdown measures and infection risk. We assessed whether demand for self-managed medication abortion provided by a fully remote online telemedicine service increased following the emergence of COVID-19. DesignWe used regression discontinuity to compare the number of requests to online telemedicine service Women on Web in eight European countries before and after they implemented lockdown measures to slow COVID-19 transmission. We examined the number deaths due to COVID-19, the degree of government-provided economic support, the severity of lockdown travel restrictions, and the medication abortion service provision model in countries with and without significant changes in requests. SettingEight European countries served by Women on Web. Participants3,915 people who made requests for self-managed abortion to Women on Web between January 1st, 2019 and June 1st, 2020. Main Outcome MeasuresPercent change in requests to Women on Web before and after the emergence of COVID-19 and associated lockdown measures. ResultsFive countries showed significant increases in requests, ranging from 28% in Northern Ireland (p=0.001) to 139% in Portugal (p<0.001). Two countries showed no significant change in requests, and one country, Great Britain, showed an 88% decrease in requests (p<0.001). Countries with significant increases in requests were either countries where abortion services are mainly provided in hospitals or where no abortion services are available and international travel was prohibited during lockdown. By contrast, Great Britain authorized teleconsultation for medication abortion and provision of medications by mail during the pandemic. ConclusionThese marked changes in requests for self-managed medication abortion during COVID-19 demonstrate demand for fully remote models of abortion care and an urgent need for policymakers to expand access to medication abortion by telemedicine. O_TEXTBOXO_TEXTBOXNOWhat this paper addsC_TEXTBOXNO What is already know on this subjectO_LIThe COVID-19 pandemic has presented challenges to patients seeking medication abortion, including lockdown travel restrictions and infection risk during in-person clinic visits. C_LIO_LIYet in most European countries, medication abortion must still be provided through in-person models of care. The sole exception is Great Britain, where a fully remote medication abortion service was introduced in response to the pandemic. C_LIO_LIAnecdotal reports suggest that patients are struggling to access in-person abortion services and may turn to self-managed abortion as a result. However, to date there has been no systematic assessment of this possibility. C_LI What this study addsO_LIOur study provides the best evidence to date that demand for self-managed medication abortion provided using online telemedicine increased following the emergence of the COVID-19 pandemic. C_LIO_LIThe largest increases were observed in countries where medication abortion is provided mainly in hospitals and where travel restrictions were most stringent. By contrast, in the one country that implemented fully remote services, demand for self-managed abortion declined almost to zero. C_LIO_LIOur findings demonstrate the urgent need for policymakers to expand access to telemedicine models of medication abortion within the formal healthcare setting. C_LI C_TEXTBOX
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We propose a Bayesian model for projecting first-wave COVID-19 deaths in all 50 U.S. states. Our models projections are based on data derived from mobile-phone GPS traces, which allows us to estimate how social-distancing behavior is "flattening the curve" in each state. In a two-week look-ahead test of out-of-sample forecasting accuracy, our model significantly outperforms the widely used model from the Institute for Health Metrics and Evaluation (IHME), achieving 42% lower prediction error: 13.2 deaths per day average error across all U.S. states, versus 22.8 deaths per day average error for the IHME model. Our model also provides an accurate, if slightly conservative, assessment of forecasting accuracy: in the same look-ahead test, 98% of data points fell within the models 95% credible intervals. Our models projections are updated daily at https://covid-19.tacc.utexas.edu/projections/.
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OBJECTIVE: Garcinia mangostana Linn., commonly known as mangosteen, is a tropical fruit with a thick pericarp rind containing bioactive compounds that may be beneficial as an adjunctive treatment for schizophrenia. The biological underpinnings of schizophrenia are believed to involve altered neurotransmission, inflammation, redox systems, mitochondrial dysfunction, and neurogenesis. Mangosteen pericarp contains xanthones which may target these biological pathways and improve symptoms; this is supported by preclinical evidence. Here we outline the protocol for a double-blind randomized placebo-controlled trial evaluating the efficacy of adjunctive mangosteen pericarp (1,000 mg/day), compared to placebo, in the treatment of schizophrenia. METHODS: We aim to recruit 150 participants across two sites (Geelong and Brisbane). Participants diagnosed with schizophrenia or schizoaffective disorder will be randomized to receive 24 weeks of either adjunctive 1,000 mg/day of mangosteen pericarp or matched placebo, in addition to their usual treatment. The primary outcome measure is mean change in the Positive and Negative Symptom Scale (total score) over the 24 weeks. Secondary outcomes include positive and negative symptoms, general psychopathology, clinical global severity and improvement, depressive symptoms, life satisfaction, functioning, participants reported overall improvement, substance use, cognition, safety and biological data. A 4-week post treatment interview at week 28 will explore post-discontinuations effects. RESULTS: Ethical and governance approvals were gained and the trial commenced. CONCLUSION: A positive finding in this study has the potential to provide a new adjunctive treatment option for people with schizophrenia and schizoaffective disorder. It may also lead to a greater understanding of the pathophysiology of the disorder.
