Science Gateways: The Long Road to the Birth of an Institute

Nowadays, research in various disciplines is enhanced via computational methods, cutting-edge technologies and diverse resources including computational infrastructures and instruments. Such infrastructures are often complex and researchers need means to conduct their research in an efficient way without getting distracted with information technology nuances. Science gateways address such demands and offer user interfaces tailored to a specific community. Creators of science gateways face a breadth of topics and manifold challenges, which necessitate close collaboration with the domain specialists but also calling in experts for diverse aspects of a science gateway such as project management, licensing, team composition, sustainability, HPC, visualization, and usability specialists. The Science Gateway Community Institute tackles the challenges around science gateways to support domain specialists and developers via connecting them to diverse experts, offering consultancy as well as providing a software collaborative, which contains ready-to-use science gateway frameworks and science gateway components

Projections for first-wave COVID-19 deaths across the US using social-distancing measures derived from mobile phones

We propose a Bayesian model for projecting first-wave COVID-19 deaths in all 50 U.S. states. Our model's 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 model's 95% credible intervals. Our model's projections are updated daily at https://covid-19.tacc.utexas.edu/projections/.Integrative Biolog

Austin COVID-19 transmission estimates and healthcare projections

To support public health decision-making and healthcare planning, we developed a model for the five-county Austin-Round Rock Metropolitan Statistical Area (henceforth Austin) that can provide real-time estimates of the prevalence and transmission rate of COVID-19 and project healthcare needs into the future. The model incorporates key epidemiological characteristics of the disease, demographic information for Austin, and local mobility data from anonymized cell phone traces. It uses daily COVID-19 hospitalization data to estimate the changing transmission rate and prevalence of disease. The framework can be readily applied to provide pandemic situational awareness and short-term healthcare projections in other cities around the US. In this report, we use COVID-19 hospitalization data for Austin from March 13 to July 14, 2020 to estimate the state of the pandemic in early July and project hospitalizations through early August of 2020. The projections are based on multiple assumptions about the age-specific severity of COVID-19 and the role of asymptomatic infections in the transmission of the virus. These graphs below do not present the full range of uncertainty for the city of Austin, but are intended to provide basic insight into the changing risks of COVID-19 transmission and healthcare surges in Austin. Our estimates suggest that the pandemic slowed considerably during the March 24-May 1, 2020 stay-home order and reached its lowest transmission rate in mid April. As Texas began relaxing social distancing measures in early May, transmission picked up and continued to increase through mid June. The recent decrease in transmission may have stemmed from mid-June tightening of restrictions and an increase in cautionary messaging. Our projections suggest that, if the pandemic continues to spread at the rate estimated from the second week of July, COVID-19 hospitalizations and/or ICU demands could exceed local capacity in early August. We are posting these results prior to peer review to provide intuition for both policy makers and the public regarding both the immediate threat of COVID-19 and the extent to which continued social distancing, transmission-reducing precautions such as keeping physical distance, wearing cloth face coverings and staying isolated when symptomatic, can mitigate that threat. As new hospitalization data become available, we will provide updated estimates and projections on the UT COVID-19 Modeling Consortium's Austin COVID-19 Dashboard.Integrative Biolog

Sustainability in the Tapis Framework

As more research depends fundamentally on software, sustainability becomes increasingly critical. Nevertheless, despite valiant efforts from a growing number of researchers and practitioners, a basic understanding of best-practices for sustainable software remains elusive. In this paper, we review the specific practices and strategies that have helped to sustain Tapis, a cyberinfastructure project that has been in use for over a decade. The Tapis framework is an open-source, software-as-a-service Application Programming Interface (API) for collaborative, automated, reproducible computational research which began as the Foundation API for the iPlant Collaborative Project in 2008, and today is used by tens of thousands of individuals across more than a dozen active projects. This paper describes our multi-faceted approach to sustaining an increasingly complex ecosystem of software, documentation and other digital assets, including both technical and organizational strategies for minimizing the cost of sustainment while maximizing available resources for sustainment activities

Texas Trauma Service Area (TSA) COVID-19 transmission estimates and healthcare projections: Oct. 20 Update

To support public health decision-making and healthcare planning, we developed a model that can provide real-time estimates of the prevalence and transmission rate of COVID-19 and project healthcare needs into the future for each of the 22 Trauma Service Areas (TSA) in Texas. These estimates are updated daily on our Texas COVID-19 Healthcare Projections Dashboard. The model incorporates key epidemiological characteristics of the disease, demographic information for each TSA, and local mobility data from anonymized cell phone traces. It uses daily COVID-19 hospitalization data to estimate the changing transmission rate and prevalence of disease. The framework can be readily applied to provide pandemic situational awareness and short-term healthcare projections in other cities around the US. In this report, we use COVID-19 hospitalization data for each TSA from April 11 to October 18, 2020 to estimate the state of the pandemic in mid October and project hospitalizations through mid November of 2020. The data were provided by Texas DSHS through daily and weekly reports as summarized in the Texas COVID-19 Data Resource by Texas 2036[1]. We note that the data are not available before April 11th and that the projections are based on multiple assumptions about the age-specific severity of COVID-19 and the role of asymptomatic infections in the transmission of the virus. These graphs below do not present the full range of uncertainty, but are intended to provide basic insight into the changing risks of COVID-19 transmission and healthcare surges in each TSA. Texas experienced a large summer pandemic wave that subsided in most regions by August. In mid-September, transmission and healthcare needs began rising in several parts of the state. Our estimates suggest that 15 out of the 22 regions have at least a 50% chance of increasing spread (Re> 1). Only Lufkin, Victoria, Laredo, Corpus Christi, and the Lower Rio Grande Valley have less than a 40% that the pandemic is in a growth phase. El Paso has the highest estimated risk of exceeding its healthcare capacity over the next three weeks, with an 85% probability of exceeding the estimated COVID-19 hospital capacity and 95% probability of exceeding the estimated COVID-19 ICU capacity. Six regions have at least a 25% chance of exceeding hospital capacity in the next three weeks and thirteen regions at least a 25% chance of exceeding ICU capacity, unless policies, behaviors, or healthcare capacities change. We are posting these results prior to peer review to provide intuition for both policy makers and the public regarding both the immediate threat of COVID-19 and the extent to which continued social distancing, transmission-reducing precautions such as keeping physical distance, wearing cloth face coverings and staying isolated when symptomatic, can mitigate that threat.Integrative Biolog

Texas Trauma Service Area (TSA) COVID-19 transmission estimates and healthcare projections

To support public health decision-making and healthcare planning, we developed a model that can provide real-time estimates of the prevalence and transmission rate of COVID-19 and project healthcare needs into the future for each of the 22 Trauma Service Areas (TSA) in Texas. The model incorporates key epidemiological characteristics of the disease, demographic information for each TSA, and local mobility data from anonymized cell phone traces. It uses daily COVID-19 hospitalization data to estimate the changing transmission rate and prevalence of disease. The framework can be readily applied to provide pandemic situational awareness and short-term healthcare projections in other cities around the US. In this report, we use COVID-19 hospitalization data for each TSA from April 11 to July 22, 2020 to estimate the state of the pandemic in late July and project hospitalizations through early August of 2020. The data were provided by Texas DSHS through daily and weekly reports as summarized in the Texas 2036 dashboard. We note two limitations with these data that could bias our projections. First, data are not available before April 11th. Second, the ratio between COVID-19 hospital admissions and hospitalizations is variable across TSA regions. Thus, there may be regional differences in reporting confirmed COVID-19 hospital admissions which are not explicitly considered in the projections below. In addition, the projections are based on multiple assumptions about the age-specific severity of COVID-19 and the role of asymptomatic infections in the transmission of the virus. These graphs below do not present the full range of uncertainty, but are intended to provide basic insight into the changing risks of COVID-19 transmission and healthcare surges in each TSA. Our estimates suggest that every TSA has experienced a recent surge in cases, hospitalizations, and mortality, with transmission starting to rise in early May. Many regions are now seeing declining numbers. In four TSAs, covering the largest metropolitan areas, the data indicate over a 90% chance that the current wave is subsiding (TSAs E, I, P, and Q). Our projections suggest that the only region with over a 90% chance that the current pandemic wave is still growing is Waco. In the remaining 17 TSAs, the future is more uncertain. COVID-19 is straining healthcare systems across the state. Although most TSAs are at low risk for reaching total hospital bed capacity, several could exceed ICU capacity. Only the Dallas, Paris, El Paso, Midland/Odessa, Austin, San Antonio, and Houston regions have at least 90% certainty of remaining within their ICU bed capacity over the next 3 weeks. We are posting these results prior to peer review to provide intuition for both policy makers and the public regarding both the immediate threat of COVID-19 and the extent to which continued social distancing, transmission-reducing precautions such as keeping physical distance, wearing cloth face coverings and staying isolated when symptomatic, can mitigate that threat.Integrative Biolog

Texas Trauma Service Area (TSA) COVID-19 transmission estimates and healthcare projections: August 25, 2020

To support public health decision-making and healthcare planning, we developed a model that can provide real-time estimates of the prevalence and transmission rate of COVID-19 and project healthcare needs into the future for each of the 22 Trauma Service Areas (TSA) in Texas. The model incorporates key epidemiological characteristics of the disease, demographic information for each TSA, and local mobility data from anonymized cell phone traces. It uses daily COVID-19 hospitalization data to estimate the changing transmission rate and prevalence of disease. The framework can be readily applied to provide pandemic situational awareness and short-term healthcare projections in other cities around the US. In this report, we use COVID-19 hospitalization data for each TSA from April 11 to August 11, 2020 to estimate the state of the pandemic in late July and project hospitalizations through early September of 2020. The data were provided by Texas DSHS through daily and weekly reports as summarized in the Texas COVID-19 Data Resource by Texas 2036[1]. We note that the data are not available before April 11th and that the projections are based on multiple assumptions about the age-specific severity of COVID-19 and the role of asymptomatic infections in the transmission of the virus. These graphs below do not present the full range of uncertainty, but are intended to provide basic insight into the changing risks of COVID-19 transmission and healthcare surges in each TSA. Our estimates suggest that every TSA has experienced a recent surge in cases, hospitalizations, and mortality, with transmission starting to rise in early May. Transmission rates have declined since our July 22nd report, with no regions having over a 50% chance of a growing epidemic. While COVID-19 is still straining healthcare systems across the state, the risks of overwhelming surges have diminished. In all TSAs, the risk of exceeding general hospital capacity is now below 10%; only four TSAs have over a 10% risk of exceeding baseline (non-surge) ICU bed capacity: Laredo (20.6%), Abilene (19%), Wichita Falls (16.6%), and Amarillo (10.6%). We are posting these results prior to peer review to provide intuition for both policy makers and the public regarding both the immediate threat of COVID-19 and the extent to which continued social distancing, transmission-reducing precautions such as keeping physical distance, wearing cloth face coverings and staying isolated when symptomatic, can mitigate that threat. Note, this report replaces a report posted on August 19th, 2020. We recently identified inconsistencies in the reporting of hospital admissions across TSAs since July 21, 2020. Thus, we revised our estimates using only COVID-19 hospital census rather than both COVID-19 hospital admissions and census data starting on July 22, 2020.Integrative Biolog