Center for Pandemic Decision Science

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Austin COVID-19 transmission estimates and healthcare projections
(2020-07) Tec, Mauricio; Lachmann, Michael; Fox, Spencer J.; Pasco, Remy; Woody, Spencer; Starling, Jennifer; Dahan, Maytal; Gaither, Kelly; Scott, James; Meyers, Lauren Ancel
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.
COVID-19 alert stages, healthcare projections and mortality patterns in Austin, Texas, May 2021
(2021-05) Arslan, Nazlican; Sürer, Özge; Morton, David P.; Yang, Haoxiang; Lachmann, Michael; Woody, Spencer; Fox, Spencer J.; Meyers, Lauren Ancel
To support public health decision-making in Austin, Texas, we project COVID-19 healthcare demand as vaccines continue to roll out, and we provide retrospective estimates for in-hospital COVID-19 mortality during surge and non-surge periods of the pandemic. The projections indicate that a return to COVID-19 Alert Stage 2 in May 2021 would be unlikely to cause a healthcare surge that exceeds local ICU capacity. However, our retrospective estimates of in-hospital COVID-19 mortality suggest that even modest surges may increase the COVID-19 fatality rate and that, throughout the pandemic, in-hospital mortality has disproportionately occurred in communities with overlapping socioeconomic, occupational, and health risks. The analyses are based on multiple assumptions about the transmission rate, age-specific severity of COVID-19, and efficacy of vaccines, and thus do not represent the full range of uncertainty that the city of Austin may encounter. We are posting these results prior to peer review to provide insights regarding changing COVID-19 risks as vaccination coverage continues to increase and to guide the relaxation of COVID-19 mitigation measures in the spring and summer of 2021.
COVID-19 Healthcare Demand Projections: Austin, Texas
(2020-04) Wang, Xutong; Pasco, Remy; Pierce, Kelly; Du, Zhanwei; Fox, Spencer J.; Meyers, Lauren Ancel
To support planning by the city of Austin and Travis County, we analyzed the Austin-Round Rock module of our US COVID-19 Pandemic Model to project the number of hospitalizations under different social distancing scenarios. Note that the results presented herein are based on multiple assumptions about the transmission rate and age-specific severity of COVID-19. There is still much we do not understand about the transmission dynamics of this virus, including the extent of asymptomatic infection and transmission. These results do not represent the full range of uncertainty. Rather, they are meant to serve as plausible scenarios for gauging the likely impacts of social distancing measures in the Austin-Round Rock Metropolitan Area. We have updated our model inputs based on the daily number of COVID-19 hospitalizations in the Austin-Round Rock MSA between March 13 and April 19, 2020. The data suggest that social distancing following the March 24th Stay Home-Work Safe order has resulted in a 94% reduction in COVID-19 transmission, with our uncertainty in this estimate ranging from 55% and 100%. The data also suggest that approximately 13.6% of symptomatic cases are detected (i.e., reported as confirmed cases). 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 early social distancing measures are mitigating that threat. Our projections indicate that the Stay Home-Work Safe has delayed and possibly even prevented a COVID-19 healthcare crisis in the region.
COVID-19 Healthcare Demand Projections: Austin, Texas
(2020-03) Pasco, Remy; Wang, Xutong; Petty, Michaela; Du, Zhanwei; Fox, Spencer J.; Pignone, Michael; Johnston, Clay; Meyers, Lauren Ancel
COVID-19 in Austin, Texas: Epidemiological Assessment of Grocery Shopping
(2020-04) Pasco, Remy; Wang, Xutong; Du, Zhanwei; Fox, Spencer J.; Meyers, Lauren Ancel
There are an estimated 24,000 grocery store workers in the Austin-Round Rock metropolitan area (MSA) representing 2% of the labor force [1]. The Austin Stay Home - Work Safe order that was issued on March 24, 2020 and extended on April 13, 2020 restricts non-essential work, but permits work in grocery stores and public grocery shopping [2,3]. Daily interactions between grocery workers and the general population may undermine efforts to reduce person-to-person contact, and exacerbate the individual and city-wide risks associated with COVID-19 transmission. In response to a request from the city of Austin, we projected the epidemiological impacts of grocery work under different assumptions regarding the effectiveness of precautionary measures taken by workers and shoppers in grocery stores. To do so, we modified the Austin-Round Rock module of our US COVID-19 Pandemic Model to explicitly include a population subgroup representing grocery workers and contacts that occur between members of the general public and grocery workers in stores. As a base case scenario, we assumed that grocery workers would maintain typical workforce contact rates, estimated as twice the average workplace contacts for 18-49 year olds in the general population. Our analysis suggests that grocery shopping can considerably increase the community-wide risk of COVID-19 and that both shoppers and workers can and should do their part to protect themselves and others from transmission in stores. Furthermore, the risk of COVID-19 hospitalizations within the population of grocery workers is expected to be much higher than that in the non-working 18-49 year old population.
COVID-19 in Austin, Texas: Relaxing Social Distancing Measures
(2020-04) Wang, Xutong; Du, Zhanwei; Huang, George; Fox, Spencer J.; Meyers, Lauren Ancel
To support planning by the city of Austin and Travis County, we analyzed the Austin-Round Rock module of our US COVID-19 Pandemic Model to project the number of hospitalizations under different scenarios for relaxing social distancing measures following the March 24th Stay Home-Work Safe order. Note that the results presented herein are based on multiple assumptions about the transmission rate and age-specific severity of COVID-19. There is still much we do not understand about the transmission dynamics of this virus, including the extent of asymptomatic infection and transmission. These results do not represent the full range of uncertainty. Rather, they are meant to serve as plausible scenarios for gauging the likely impacts of social distancing measures in the Austin-Round Rock Metropolitan Area. We have updated our model inputs based on the daily number of COVID-19 hospitalizations in the Austin-Round Rock MSA between March 13 and April 19, 2020. The data suggest that social distancing following the March 24th Stay Home-Work Safe order has resulted in a 94% reduction in COVID-19 transmission, with our uncertainty in this estimate ranging from 70% and 100%. The data also suggest that approximately 13.6% of symptomatic cases are detected (i.e., reported as confirmed cases). We are posting these results prior to peer review to provide intuition for both policy makers and the public regarding both the threat of COVID-19 and the extent to which social distancing measures can mitigate that threat. Our projections indicate that the Stay Home-Work Safe has likely prevented a COVID-19 healthcare crisis in the region during the first wave of the pandemic. When current measures are relaxed, we may see more COVID-19 transmission in the area leading to a second pandemic wave. Whether or not and how quickly COVID-19 cases and hospitalizations rise in the second wave will critically depend on the extent to which individuals and communities continue to take steps to reduce the risks of transmission.
COVID-19 scenario projections for Austin, Texas - August 2021
(2021-08) Fox, Spencer J.; Lachmann, Michael; Bouchnita, Anass; Woody, Spencer; Pasco, Remy; Johnson-León, Maureen; Ingle, Tanvi; Johnson, Kaitlyn; Meyers, Lauren Ancel
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, local vaccination estimates, 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 the disease. In this report, we use COVID-19 hospitalization data for Austin from March 13, 2020 to July 28, 2021 to estimate the state of the pandemic in the summer of 2021 and project hospitalizations through November of 2021.
COVID-19 scenario projections for Austin, Texas - July 19, 2021
(2021-07) Lachmann, Michael; Bouchnita, Anass; Woody, Spencer; Pasco, Remy; Johnson-León, Maureen; Johnson, Kaitlyn; Fox, Spencer J.; Meyers, Lauren Ancel
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, local vaccination estimates, 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, 2020 to July 13, 2021 to estimate the state of the pandemic in mid-summer of 2021 and project hospitalizations up to October, 2021.
Potential Impact of Holiday Gatherings on COVID-19 Hospitalizations in Austin
(2020-12) Lachmann, Michael; Fox, Spencer J.; Meyers, Lauren Ancel
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 December 19, 2020 to estimate the state of the pandemic in late December and project hospitalizations through mid January of 2021, under three hypothetical scenarios for the impact of winter holiday gatherings on the transmission of COVID-19 in Austin. 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 potential healthcare surges in Austin. Our estimates suggest that if transmission is elevated to levels measured just after the Thanksgiving holiday for one week starting on December 24, 2020, then there is a 36% chance that the COVID-19 ICU census will reach the estimated capacity of 200 by January 7, with a median date of hitting 200 of January 14 (95% prediction interval: December 30-undetermined ). If the higher levels of transmission are sustained for two weeks, then there is a 39% chance that the COVID-19 ICU census will reach the estimated capacity of 200 by January 7, with a median date of hitting 200 of January 11 (95% prediction interval: December 30-undetermined). 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 importance of heightened social distancing and transmission reducing-precautions as we enter the holiday period, including abstaining from indoor social gatherings, keeping physical distance, wearing cloth face coverings and staying isolated when symptomatic. 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.
Potential impacts of statewide relaxation of COVID-19 policies, the B.1.1.7 variant, and vaccination in Austin - March 2021
(2021-03) Lachmann, Michael; Fox, Spencer J.; Woody, Spencer; Johnson, Kaitlyn; Meyers, Lauren Ancel
To support public health decision-making and healthcare planning, we developed a model for the five-county Austin-Round Rock Metropolitan Statistical Area (henceforth Austinâ€‹) 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, 2020 to March 5, 2021 to estimate the state of the pandemic in early March and project hospitalizations up to June of 2021.
Projecting Need for a COVID-19 Alternative Care Site (ACS) Austin, TX
(2021-01) Yang, Haoxiang; Lachmann, Michael; Sürer, Özge; Fox, Spencer J.; Morton, David P.; Meyers, Lauren Ancel
To support the city of Austin and Travis County in responding to the threatening rise in COVID-19 hospitalizations, we used a data-driven model of COVID-19 transmission in the Austin-Round Rock MSA to project hospitalizations until February 4th, estimate the risk that cases will exceeding local capacity, and determine effective triggers for opening an alternative care site (ACS) to expand capacity. Note that the results presented herein are based on multiple assumptions about the transmission rate and age-specific severity of COVID-19 and do not represent the full range of uncertainty. Rather, they are meant to provide plausible scenarios for COVID-19 healthcare demand and inform decisions that balance the high costs of establishing an ACS with the risks of outstripping local healthcare capacity.
Projections for Austin's COVID-19 Staged Alert System, Incorporating Reported Cases as Additional Indicator
(2021-11) Arslan, Nazlican; Morton, David P.; Pichette, Janet; Walkes, Desmar; Meyers, Lauren Ancel
To support public health decision-making in Austin, Texas, we use a data-driven model of COVID-19 transmission in the five-county Austin-Round Rock Metropolitan Statistical Area (MSA) to project hospitalizations under plausible scenarios for future COVID-19 transmission. This model integrates Austin's COVID-19 staged-alert system, which informs the city's adaptive risk-based guidelines. Given the emergence of SARS-CoV-2 variants and the ongoing roll-out of vaccines, the existing threshold for triggering the return from the second lowest alert stage (Stage 2) to the lowest alert stage (Stage 1) may be insufficient to prevent surges, as described in our recent report [1]. To address this concern, we evaluate the addition of new criteria for reducing the alert stage, based on a CDC framework for estimating levels of community transmission. Specifically, we consider tracking the number of new cases reported over the preceding seven days, and requiring that this value: (i) drops below 10 per 100,000 before relaxing from Stage 3 to Stage 2 and (ii) drops below 5 per 100,000 before relaxing to Stage 1. The projections we present consider several scenarios for the future transmission of the Delta variant and the emergence of other variants of concern. We assume that Delta is 1.65 times more transmissible than previous variants, has a higher hospitalization rate among symptomatic individuals, has a shorter incubation period, and leads to longer ICU stays. The hypothesized variants of concern are identical to Delta, except that they are instead 2.0 and 2.5 times more transmissible than pre-Delta variants. The results presented here are based on multiple assumptions about the transmission rate, age-specific severity of COVID-19, efficacy of vaccines, waning immunity following infection or vaccination, and uptake of an initial two-dose vaccination as well as boosters. They do not represent the full range of uncertainty that the City of Austin may encounter. Our projections suggest that the current hospitalization threshold for transitioning from Stage 2 (blue) to Stage 1 (green) may fail to guard against future variants of concern, and that adding the proposed community transmission criteria for changing stages would substantially reduce the risk of surges that exceed healthcare capacity. We are posting these results prior to peer review to provide intuition for both policy-makers and the public regarding the near-term threat of COVID-19.
Projections for Variants of Concern under Austin's COVID-19 Staged-Alert System
(2021-10) Arslan, Nazlican; Morton, David P.; Walkes, Desmar; Meyers, Lauren Ancel
To support public health decision-making in Austin, Texas, we use a data-driven model of COVID-19 transmission in the five-county Austin-Round Rock Metropolitan Statistical Area to project hospital demand under plausible scenario for future COVID-19 transmission. This model integrates Austin's COVID-19 staged-alert system, which informs the city's adaptive risk-based guidelines. Given the emergence of SARS-CoV-2 variants and the ongoing roll-out of vaccines, we apply the model to evaluate the robustness of the thresholds governing changes between alert stages. The projections consider several scenarios for the future transmission of the Delta variant and the emergence of other variants of concern. We assume that Delta is 1.65 times more transmissible than previous variants, has a higher hospitalization rate among symptomatic individuals, has a shorter incubation period, and leads to longer ICU stays. The hypothesized variants of concern are identical to Delta, except that they are instead 2.0 and 2.5 times more transmissible than pre-Delta variants. The results presented here are based on multiple assumptions about the transmission rate, age-specific severity of COVID-19, efficacy of vaccines, waning immunity following infection or vaccination, and uptake of initial two-dose vaccination as well as boosters. They do not represent the full range of uncertainty that the City of Austin may encounter. The projections suggest that the current threshold for transitioning from Stage 2 (blue) to Stage 1 (green) may fail to guard against future variants of concern. Reducing the threshold from a rolling-average of five new COVID-19 admissions to zero would be expected to reduce risks of rapid resurgences. We are posting these results prior to peer review to provide intuition for both policy makers and the public regarding the near-term threat of COVID-19.
Spatial distribution of COVID-19 infections and vaccinations in Austin, Texas
(2021-04) Woody, Spencer; Javan, Emily; Johnson, Kaitlyn; Pasco, Remy; Johnson-León, Maureen; Lachmann, Michael; Fox, Spencer J.; Meyers, Lauren Ancel
In this report, we estimate the spatial distribution of SARS-CoV-2 infections and vaccine administration across Austin, TX. We find marked geographic differences in these outcomes. In particular, ZIP codes on the western side of the city tend to have higher vaccine coverage and lower estimated cumulative infections than ZIP codes on the eastern side of the city. These differences mirror disparities in social vulnerability, as measured by the CDC's social vulnerability index (SVI), which tends to be higher in eastern ZIP codes than in western ZIP codes.

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