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1. Creating a Discipline-specific Commons for Infectious Disease Epidemiology

Author

Wagner, Michael M., Hogan, William, Levander, John, Darr, Adam, Diller, Matt, Sibilla, Max, Sperringer, Jr., Alexander T. Loiacono. Terence, and Brown, Shawn T.

Subjects
Computer Science - Software Engineering, Computer Science - Artificial Intelligence
Abstract

Objective: To create a commons for infectious disease (ID) epidemiology in which epidemiologists, public health officers, data producers, and software developers can not only share data and software, but receive assistance in improving their interoperability. Materials and Methods: We represented 586 datasets, 54 software, and 24 data formats in OWL 2 and then used logical queries to infer potentially interoperable combinations of software and datasets, as well as statistics about the FAIRness of the collection. We represented the objects in DATS 2.2 and a software metadata schema of our own design. We used these representations as the basis for the Content, Search, FAIR-o-meter, and Workflow pages that constitute the MIDAS Digital Commons. Results: Interoperability was limited by lack of standardization of input and output formats of software. When formats existed, they were human-readable specifications (22/24; 92%); only 3 formats (13%) had machine-readable specifications. Nevertheless, logical search of a triple store based on named data formats was able to identify scores of potentially interoperable combinations of software and datasets. Discussion: We improved the findability and availability of a sample of software and datasets and developed metrics for assessing interoperability. The barriers to interoperability included poor documentation of software input/output formats and little attention to standardization of most types of data in this field. Conclusion: Centralizing and formalizing the representation of digital objects within a commons promotes FAIRness, enables its measurement over time and the identification of potentially interoperable combinations of data and software., Comment: 12 pages, 6 figures

Published
2023

2. Multiple models for outbreak decision support in the face of uncertainty.

Author

Shea, Katriona, Borchering, Rebecca K, Probert, William JM, Howerton, Emily, Bogich, Tiffany L, Li, Shou-Li, van Panhuis, Willem G, Viboud, Cecile, Aguás, Ricardo, Belov, Artur A, Bhargava, Sanjana H, Cavany, Sean M, Chang, Joshua C, Chen, Cynthia, Chen, Jinghui, Chen, Shi, Chen, YangQuan, Childs, Lauren M, Chow, Carson C, Crooker, Isabel, Del Valle, Sara Y, España, Guido, Fairchild, Geoffrey, Gerkin, Richard C, Germann, Timothy C, Gu, Quanquan, Guan, Xiangyang, Guo, Lihong, Hart, Gregory R, Hladish, Thomas J, Hupert, Nathaniel, Janies, Daniel, Kerr, Cliff C, Klein, Daniel J, Klein, Eili Y, Lin, Gary, Manore, Carrie, Meyers, Lauren Ancel, Mittler, John E, Mu, Kunpeng, Núñez, Rafael C, Oidtman, Rachel J, Pasco, Remy, Pastore Y Piontti, Ana, Paul, Rajib, Pearson, Carl AB, Perdomo, Dianela R, Perkins, T Alex, Pierce, Kelly, Pillai, Alexander N, Rael, Rosalyn Cherie, Rosenfeld, Katherine, Ross, Chrysm Watson, Spencer, Julie A, Stoltzfus, Arlin B, Toh, Kok Ben, Vattikuti, Shashaank, Vespignani, Alessandro, Wang, Lingxiao, White, Lisa J, Xu, Pan, Yang, Yupeng, Yogurtcu, Osman N, Zhang, Weitong, Zhao, Yanting, Zou, Difan, Ferrari, Matthew J, Pannell, David, Tildesley, Michael J, Seifarth, Jack, Johnson, Elyse, Biggerstaff, Matthew, Johansson, Michael A, Slayton, Rachel B, Levander, John D, Stazer, Jeff, Kerr, Jessica, and Runge, Michael C

Subjects
Humans, Uncertainty, Public Health, Disease Outbreaks, Pandemics, COVID-19, cognitive biases, decision theory, multi-model aggregation, Prevention, Brain Disorders, Good Health and Well Being
Abstract

Policymakers must make management decisions despite incomplete knowledge and conflicting model projections. Little guidance exists for the rapid, representative, and unbiased collection of policy-relevant scientific input from independent modeling teams. Integrating approaches from decision analysis, expert judgment, and model aggregation, we convened multiple modeling teams to evaluate COVID-19 reopening strategies for a mid-sized United States county early in the pandemic. Projections from seventeen distinct models were inconsistent in magnitude but highly consistent in ranking interventions. The 6-mo-ahead aggregate projections were well in line with observed outbreaks in mid-sized US counties. The aggregate results showed that up to half the population could be infected with full workplace reopening, while workplace restrictions reduced median cumulative infections by 82%. Rankings of interventions were consistent across public health objectives, but there was a strong trade-off between public health outcomes and duration of workplace closures, and no win-win intermediate reopening strategies were identified. Between-model variation was high; the aggregate results thus provide valuable risk quantification for decision making. This approach can be applied to the evaluation of management interventions in any setting where models are used to inform decision making. This case study demonstrated the utility of our approach and was one of several multimodel efforts that laid the groundwork for the COVID-19 Scenario Modeling Hub, which has provided multiple rounds of real-time scenario projections for situational awareness and decision making to the Centers for Disease Control and Prevention since December 2020.

Published
2023

4. Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty

Author

Howerton, Emily, Contamin, Lucie, Mullany, Luke C., Qin, Michelle, Reich, Nicholas G., Bents, Samantha, Borchering, Rebecca K., Jung, Sung-mok, Loo, Sara L., Smith, Claire P., Levander, John, Kerr, Jessica, Espino, J., van Panhuis, Willem G., Hochheiser, Harry, Galanti, Marta, Yamana, Teresa, Pei, Sen, Shaman, Jeffrey, Rainwater-Lovett, Kaitlin, Kinsey, Matt, Tallaksen, Kate, Wilson, Shelby, Shin, Lauren, Lemaitre, Joseph C., Kaminsky, Joshua, Hulse, Juan Dent, Lee, Elizabeth C., McKee, Clifton D., Hill, Alison, Karlen, Dean, Chinazzi, Matteo, Davis, Jessica T., Mu, Kunpeng, Xiong, Xinyue, Pastore y Piontti, Ana, Vespignani, Alessandro, Rosenstrom, Erik T., Ivy, Julie S., Mayorga, Maria E., Swann, Julie L., España, Guido, Cavany, Sean, Moore, Sean, Perkins, Alex, Hladish, Thomas, Pillai, Alexander, Ben Toh, Kok, Longini, Jr., Ira, Chen, Shi, Paul, Rajib, Janies, Daniel, Thill, Jean-Claude, Bouchnita, Anass, Bi, Kaiming, Lachmann, Michael, Fox, Spencer J., Meyers, Lauren Ancel, Srivastava, Ajitesh, Porebski, Przemyslaw, Venkatramanan, Srini, Adiga, Aniruddha, Lewis, Bryan, Klahn, Brian, Outten, Joseph, Hurt, Benjamin, Chen, Jiangzhuo, Mortveit, Henning, Wilson, Amanda, Marathe, Madhav, Hoops, Stefan, Bhattacharya, Parantapa, Machi, Dustin, Cadwell, Betsy L., Healy, Jessica M., Slayton, Rachel B., Johansson, Michael A., Biggerstaff, Matthew, Truelove, Shaun, Runge, Michael C., Shea, Katriona, Viboud, Cécile, and Lessler, Justin

Published
2023
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5. Potential impact of annual vaccination with reformulated COVID-19 vaccines: Lessons from the US COVID-19 scenario modeling hub

Author

Jung, Sung-mok, Loo, Sara L., Howerton, Emily, Contamin, Lucie, Smith, Claire P., Carcelén, Erica C., Yan, Katie, Bents, Samantha J., Levander, John, Espino, Jessi, Lemaitre, Joseph C., Sato, Koji, McKee, Clifton D., Hill, Alison L., Chinazzi, Matteo, Davis, Jessica T., Mu, Kunpeng, Vespignani, Alessandro, Rosenstrom, Erik T., Rodriguez-Cartes, Sebastian A., Ivy, Julie S., Mayorga, Maria E., Swann, Julie L., España, Guido, Cavany, Sean, Moore, Sean M., Perkins, T. Alex, Chen, Shi, Paul, Rajib, Janies, Daniel, Thill, Jean-Claude, Srivastava, Ajitesh, Aawar, Majd Al, Bi, Kaiming, Bandekar, Shraddha Ramdas, Bouchnita, Anass, Fox, Spencer J., Meyers, Lauren Ancel, Porebski, Przemyslaw, Venkatramanan, Srini, Adiga, Aniruddha, Hurt, Benjamin, Klahn, Brian, Outten, Joseph, Chen, Jiangzhuo, Mortveit, Henning, Wilson, Amanda, Hoops, Stefan, Bhattacharya, Parantapa, Machi, Dustin, Vullikanti, Anil, Lewis, Bryan, Marathe, Madhav, Hochheiser, Harry, Runge, Michael C., Shea, Katriona, Truelove, Shaun, Viboud, Cécile, and Lessler, Justin

Subjects
United States. National Science Foundation, United States. Food and Drug Administration, United States. Centers for Disease Control and Prevention, Epidemics -- Models -- Usage -- Forecasts and trends, Vaccination -- Usage -- Forecasts and trends -- Models, Medical research -- Models -- Forecasts and trends -- Usage, Medicine, Experimental -- Models -- Forecasts and trends -- Usage, Mortality -- Models -- Usage -- Forecasts and trends, Influenza vaccines -- Usage, Influenza -- Models -- Usage -- Forecasts and trends, Drug approval -- Models -- Usage -- Forecasts and trends, Public health -- Models -- Usage -- Forecasts and trends, Market trend/market analysis, Biological sciences
Abstract

Background Coronavirus Disease 2019 (COVID-19) continues to cause significant hospitalizations and deaths in the United States. Its continued burden and the impact of annually reformulated vaccines remain unclear. Here, we present projections of COVID-19 hospitalizations and deaths in the United States for the next 2 years under 2 plausible assumptions about immune escape (20% per year and 50% per year) and 3 possible CDC recommendations for the use of annually reformulated vaccines (no recommendation, vaccination for those aged 65 years and over, vaccination for all eligible age groups based on FDA approval). Methods and findings The COVID-19 Scenario Modeling Hub solicited projections of COVID-19 hospitalization and deaths between April 15, 2023 and April 15, 2025 under 6 scenarios representing the intersection of considered levels of immune escape and vaccination. Annually reformulated vaccines are assumed to be 65% effective against symptomatic infection with strains circulating on June 15 of each year and to become available on September 1. Age- and state-specific coverage in recommended groups was assumed to match that seen for the first (fall 2021) COVID-19 booster. State and national projections from 8 modeling teams were ensembled to produce projections for each scenario and expected reductions in disease outcomes due to vaccination over the projection period. From April 15, 2023 to April 15, 2025, COVID-19 is projected to cause annual epidemics peaking November to January. In the most pessimistic scenario (high immune escape, no vaccination recommendation), we project 2.1 million (90% projection interval (PI) [1,438,000, 4,270,000]) hospitalizations and 209,000 (90% PI [139,000, 461,000]) deaths, exceeding pre-pandemic mortality of influenza and pneumonia. In high immune escape scenarios, vaccination of those aged 65+ results in 230,000 (95% confidence interval (CI) [104,000, 355,000]) fewer hospitalizations and 33,000 (95% CI [12,000, 54,000]) fewer deaths, while vaccination of all eligible individuals results in 431,000 (95% CI: 264,000-598,000) fewer hospitalizations and 49,000 (95% CI [29,000, 69,000]) fewer deaths. Conclusions COVID-19 is projected to be a significant public health threat over the coming 2 years. Broad vaccination has the potential to substantially reduce the burden of this disease, saving tens of thousands of lives each year., Author(s): Sung-mok Jung 1, Sara L. Loo 2, Emily Howerton 3, Lucie Contamin 4, Claire P. Smith 2, Erica C. Carcelén 2, Katie Yan 3, Samantha J. Bents 5, John [...]

Published
2024
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6. Bayesian Biosurveillance of Disease Outbreaks

Author

Cooper, Gregory F., Dash, Denver, Levander, John, Wong, Weng-Keen, Hogan, William, and Wagner, Michael

Subjects
Statistics - Applications, Computer Science - Artificial Intelligence, Computer Science - Computational Engineering, Finance, and Science
Abstract

Early, reliable detection of disease outbreaks is a critical problem today. This paper reports an investigation of the use of causal Bayesian networks to model spatio-temporal patterns of a non-contagious disease (respiratory anthrax infection) in a population of people. The number of parameters in such a network can become enormous, if not carefully managed. Also, inference needs to be performed in real time as population data stream in. We describe techniques we have applied to address both the modeling and inference challenges. A key contribution of this paper is the explication of assumptions and techniques that are sufficient to allow the scaling of Bayesian network modeling and inference to millions of nodes for real-time surveillance applications. The results reported here provide a proof-of-concept that Bayesian networks can serve as the foundation of a system that effectively performs Bayesian biosurveillance of disease outbreaks., Comment: Appears in Proceedings of the Twentieth Conference on Uncertainty in Artificial Intelligence (UAI2004)

Published
2012

7. Potential impact of annual vaccination with reformulated COVID-19 vaccines: lessons from the U.S. COVID-19 Scenario Modeling Hub

Author

Jung, Sung-mok, primary, Loo, Sara L, additional, Howerton, Emily, additional, Contamin, Lucie, additional, Smith, Claire P, additional, Carcelén, Erica C, additional, Yan, Katie, additional, Bents, Samantha J, additional, Espino, Jessi, additional, Levander, John, additional, Reich, Nicholas G, additional, Lemaitre, Joseph C, additional, Sato, Koji, additional, McKee, Clifton D, additional, Hill, Alison L, additional, Chinazzi, Matteo, additional, Davis, Jessica T, additional, Mu, Kunpeng, additional, Vespignani, Alessandro, additional, Rosenstrom, Erik T, additional, Rodriguez-Cartes, Sebastian A, additional, Ivy, Julie S, additional, Mayorga, Maria E, additional, Swann, Julie L, additional, España, Guido, additional, Cavany, Sean, additional, Moore, Sean M, additional, Perkins, Alex, additional, Chen, Shi, additional, Paul, Rajib, additional, Janies, Daniel, additional, Thill, Jean-Claude, additional, Srivastava, Ajitesh, additional, Aawar, Majd Al, additional, Bi, Kaiming, additional, Bandekar, Shraddha Ramdas, additional, Bouchnita, Anass, additional, Fox, Spencer J, additional, Meyers, Lauren Ancel, additional, Porebski, Przemyslaw, additional, Venkatramanan, Srinivasan, additional, Adiga, Aniruddha, additional, Lewis, Bryan, additional, Klahn, Brian, additional, Hurt, Benjamin, additional, Chen, Jiangzhuo, additional, Wilson, Amanda, additional, Hoops, Stefan, additional, Bhattacharya, Parantapa, additional, Machi, Dustin, additional, Outten, Joseph, additional, Mortveit, Henning, additional, Vullikanti, Anil, additional, Marathe, Madhav, additional, Hochheiser, Harry, additional, Runge, Michael C, additional, Shea, Katriona, additional, Truelove, Shaun, additional, Viboud, Cécile, additional, and Lessler, Justin, additional

Published
2023
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8. Impact of SARS-CoV-2 vaccination of children ages 5–11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021–March 2022: a multi-model study

Author

Borchering, Rebecca K., primary, Mullany, Luke C., additional, Howerton, Emily, additional, Chinazzi, Matteo, additional, Smith, Claire P., additional, Qin, Michelle, additional, Reich, Nicholas G., additional, Contamin, Lucie, additional, Levander, John, additional, Kerr, Jessica, additional, Espino, J., additional, Hochheiser, Harry, additional, Lovett, Kaitlin, additional, Kinsey, Matt, additional, Tallaksen, Kate, additional, Wilson, Shelby, additional, Shin, Lauren, additional, Lemaitre, Joseph C., additional, Hulse, Juan Dent, additional, Kaminsky, Joshua, additional, Lee, Elizabeth C., additional, Hill, Alison L., additional, Davis, Jessica T., additional, Mu, Kunpeng, additional, Xiong, Xinyue, additional, Pastore y Piontti, Ana, additional, Vespignani, Alessandro, additional, Srivastava, Ajitesh, additional, Porebski, Przemyslaw, additional, Venkatramanan, Srini, additional, Adiga, Aniruddha, additional, Lewis, Bryan, additional, Klahn, Brian, additional, Outten, Joseph, additional, Hurt, Benjamin, additional, Chen, Jiangzhuo, additional, Mortveit, Henning, additional, Wilson, Amanda, additional, Marathe, Madhav, additional, Hoops, Stefan, additional, Bhattacharya, Parantapa, additional, Machi, Dustin, additional, Chen, Shi, additional, Paul, Rajib, additional, Janies, Daniel, additional, Thill, Jean-Claude, additional, Galanti, Marta, additional, Yamana, Teresa, additional, Pei, Sen, additional, Shaman, Jeffrey, additional, España, Guido, additional, Cavany, Sean, additional, Moore, Sean, additional, Perkins, Alex, additional, Healy, Jessica M., additional, Slayton, Rachel B., additional, Johansson, Michael A., additional, Biggerstaff, Matthew, additional, Shea, Katriona, additional, Truelove, Shaun A., additional, Runge, Michael C., additional, Viboud, Cécile, additional, and Lessler, Justin, additional

Published
2023
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9. Projected resurgence of COVID-19 in the United States in July—December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination

Author

Truelove, Shaun, primary, Smith, Claire P, primary, Qin, Michelle, additional, Mullany, Luke C, additional, Borchering, Rebecca K, additional, Lessler, Justin, additional, Shea, Katriona, additional, Howerton, Emily, additional, Contamin, Lucie, additional, Levander, John, additional, Kerr, Jessica, additional, Hochheiser, Harry, additional, Kinsey, Matt, additional, Tallaksen, Kate, additional, Wilson, Shelby, additional, Shin, Lauren, additional, Rainwater-Lovett, Kaitlin, additional, Lemairtre, Joseph C, additional, Dent, Juan, additional, Kaminsky, Joshua, additional, Lee, Elizabeth C, additional, Perez-Saez, Javier, additional, Hill, Alison, additional, Karlen, Dean, additional, Chinazzi, Matteo, additional, Davis, Jessica T, additional, Mu, Kunpeng, additional, Xiong, Xinyue, additional, Pastore y Piontti, Ana, additional, Vespignani, Alessandro, additional, Srivastava, Ajitesh, additional, Porebski, Przemyslaw, additional, Venkatramanan, Srinivasan, additional, Adiga, Aniruddha, additional, Lewis, Bryan, additional, Klahn, Brian, additional, Outten, Joseph, additional, Orr, Mark, additional, Harrison, Galen, additional, Hurt, Benjamin, additional, Chen, Jiangzhuo, additional, Vullikanti, Anil, additional, Marathe, Madhav, additional, Hoops, Stefan, additional, Bhattacharya, Parantapa, additional, Machi, Dustin, additional, Chen, Shi, additional, Paul, Rajib, additional, Janies, Daniel, additional, Thill, Jean-Claude, additional, Galanti, Marta, additional, Yamana, Teresa K, additional, Pei, Sen, additional, Shaman, Jeffrey L, additional, Healy, Jessica M, additional, Slayton, Rachel B, additional, Biggerstaff, Matthew, additional, Johansson, Michael A, additional, Runge, Michael C, additional, and Viboud, Cecile, additional

Published
2022
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10. Author response: Projected resurgence of COVID-19 in the United States in July—December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination

Author

Truelove, Shaun, primary, Smith, Claire P, primary, Qin, Michelle, additional, Mullany, Luke C, additional, Borchering, Rebecca K, additional, Lessler, Justin, additional, Shea, Katriona, additional, Howerton, Emily, additional, Contamin, Lucie, additional, Levander, John, additional, Kerr, Jessica, additional, Hochheiser, Harry, additional, Kinsey, Matt, additional, Tallaksen, Kate, additional, Wilson, Shelby, additional, Shin, Lauren, additional, Rainwater-Lovett, Kaitlin, additional, Lemairtre, Joseph C, additional, Dent, Juan, additional, Kaminsky, Joshua, additional, Lee, Elizabeth C, additional, Perez-Saez, Javier, additional, Hill, Alison, additional, Karlen, Dean, additional, Chinazzi, Matteo, additional, Davis, Jessica T, additional, Mu, Kunpeng, additional, Xiong, Xinyue, additional, Pastore y Piontti, Ana, additional, Vespignani, Alessandro, additional, Srivastava, Ajitesh, additional, Porebski, Przemyslaw, additional, Venkatramanan, Srinivasan, additional, Adiga, Aniruddha, additional, Lewis, Bryan, additional, Klahn, Brian, additional, Outten, Joseph, additional, Orr, Mark, additional, Harrison, Galen, additional, Hurt, Benjamin, additional, Chen, Jiangzhuo, additional, Vullikanti, Anil, additional, Marathe, Madhav, additional, Hoops, Stefan, additional, Bhattacharya, Parantapa, additional, Machi, Dustin, additional, Chen, Shi, additional, Paul, Rajib, additional, Janies, Daniel, additional, Thill, Jean-Claude, additional, Galanti, Marta, additional, Yamana, Teresa K, additional, Pei, Sen, additional, Shaman, Jeffrey L, additional, Healy, Jessica M, additional, Slayton, Rachel B, additional, Biggerstaff, Matthew, additional, Johansson, Michael A, additional, Runge, Michael C, additional, and Viboud, Cecile, additional

Published
2022
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11. Impact of SARS-CoV-2 vaccination of children ages 5-11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021-March 2022: a multi-model study

Author

Borchering, Rebecca K., primary, Mullany, Luke C., additional, Howerton, Emily, additional, Chinazzi, Matteo, additional, Smith, Claire P., additional, Qin, Michelle, additional, Reich, Nicholas G., additional, Contamin, Lucie, additional, Levander, John, additional, Kerr, Jessica, additional, Espino, J, additional, Hochheiser, Harry, additional, Lovett, Kaitlin, additional, Kinsey, Matt, additional, Tallaksen, Kate, additional, Wilson, Shelby, additional, Shin, Lauren, additional, Lemaitre, Joseph C., additional, Hulse, Juan Dent, additional, Kaminsky, Joshua, additional, Lee, Elizabeth C., additional, Davis, Jessica T., additional, Mu, Kunpeng, additional, Xiong, Xinyue, additional, Piontti, Ana Pastore y, additional, Vespignani, Alessandro, additional, Srivastava, Ajitesh, additional, Porebski, Przemyslaw, additional, Venkatramanan, Srini, additional, Adiga, Aniruddha, additional, Lewis, Bryan, additional, Klahn, Brian, additional, Outten, Joseph, additional, Hurt, Benjamin, additional, Chen, Jiangzhuo, additional, Mortveit, Henning, additional, Wilson, Amanda, additional, Marathe, Madhav, additional, Hoops, Stefan, additional, Bhattacharya, Parantapa, additional, Machi, Dustin, additional, Chen, Shi, additional, Paul, Rajib, additional, Janies, Daniel, additional, Thill, Jean-Claude, additional, Galanti, Marta, additional, Yamana, Teresa, additional, Pei, Sen, additional, Shaman, Jeffrey, additional, Espana, Guido, additional, Cavany, Sean, additional, Moore, Sean, additional, Perkins, Alex, additional, Healy, Jessica M., additional, Slayton, Rachel B., additional, Johansson, Michael A., additional, Biggerstaff, Matthew, additional, Shea, Katriona, additional, Truelove, Shaun A., additional, Runge, Michael C., additional, Viboud, Cécile, additional, and Lessler, Justin, additional

Published
2022
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12. Projected resurgence of COVID-19 in the United States in July—December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination

Author

Truelove, Shaun, primary, Smith, Claire P., additional, Qin, Michelle, additional, Mullany, Luke C., additional, Borchering, Rebecca K., additional, Lessler, Justin, additional, Shea, Katriona, additional, Howerton, Emily, additional, Contamin, Lucie, additional, Levander, John, additional, Salerno, Jessica, additional, Hochheiser, Harry, additional, Kinsey, Matt, additional, Tallaksen, Kate, additional, Wilson, Shelby, additional, Shin, Lauren, additional, Rainwater-Lovett, Kaitlin, additional, Lemaitre, Joseph C., additional, Dent, Juan, additional, Kaminsky, Joshua, additional, Lee, Elizabeth C., additional, Perez-Saez, Javier, additional, Hill, Alison, additional, Karlen, Dean, additional, Chinazzi, Matteo, additional, Davis, Jessica T., additional, Mu, Kunpeng, additional, Xiong, Xinyue, additional, y Piontti, Ana Pastore, additional, Vespignani, Alessandro, additional, Srivastava, Ajitesh, additional, Porebski, Przemyslaw, additional, Venkatramanan, Srinivasan, additional, Adiga, Aniruddha, additional, Lewis, Bryan, additional, Klahn, Brian, additional, Outten, Joseph, additional, Schlitt, James, additional, Corbett, Patrick, additional, Telionis, Pyrros Alexander, additional, Wang, Lijing, additional, Peddireddy, Akhil Sai, additional, Hurt, Benjamin, additional, Chen, Jiangzhuo, additional, Vullikanti, Anil, additional, Marathe, Madhav, additional, Hoops, Stefan, additional, Bhattacharya, Parantapa, additional, Machi, Dustin, additional, Chen, Shi, additional, Paul, Rajib, additional, Janies, Daniel, additional, Thill, Jean-Claude, additional, Galanti, Marta, additional, Yamana, Teresa, additional, Pei, Sen, additional, Shaman, Jeffrey, additional, Reich, Nicholas G., additional, Healy, Jessica M., additional, Slayton, Rachel B., additional, Biggerstaff, Matthew, additional, Johansson, Michael A., additional, Runge, Michael C., additional, and Viboud, Cécile, additional

Published
2021
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13. Modeling of Future COVID-19 Cases, Hospitalizations, and Deaths, by Vaccination Rates and Nonpharmaceutical Intervention Scenarios — United States, April–September 2021

Author

Borchering, Rebecca K., primary, Viboud, Cécile, additional, Howerton, Emily, additional, Smith, Claire P., additional, Truelove, Shaun, additional, Runge, Michael C., additional, Reich, Nicholas G., additional, Contamin, Lucie, additional, Levander, John, additional, Salerno, Jessica, additional, van Panhuis, Wilbert, additional, Kinsey, Matt, additional, Tallaksen, Kate, additional, Obrecht, R. Freddy, additional, Asher, Laura, additional, Costello, Cash, additional, Kelbaugh, Michael, additional, Wilson, Shelby, additional, Shin, Lauren, additional, Gallagher, Molly E., additional, Mullany, Luke C., additional, Rainwater-Lovett, Kaitlin, additional, Lemaitre, Joseph C., additional, Dent, Juan, additional, Grantz, Kyra H., additional, Kaminsky, Joshua, additional, Lauer, Stephen A., additional, Lee, Elizabeth C., additional, Meredith, Hannah R., additional, Perez-Saez, Javier, additional, Keegan, Lindsay T., additional, Karlen, Dean, additional, Chinazzi, Matteo, additional, Davis, Jessica T., additional, Mu, Kunpeng, additional, Xiong, Xinyue, additional, Pastore y Piontti, Ana, additional, Vespignani, Alessandro, additional, Srivastava, Ajitesh, additional, Porebski, Przemyslaw, additional, Venkatramanan, Srinivasan, additional, Adiga, Aniruddha, additional, Lewis, Bryan, additional, Klahn, Brian, additional, Outten, Joseph, additional, Schlitt, James, additional, Corbett, Patrick, additional, Telionis, Pyrros Alexander, additional, Wang, Lijing, additional, Peddireddy, Akhil Sai, additional, Hurt, Benjamin, additional, Chen, Jiangzhuo, additional, Vullikanti, Anil, additional, Marathe, Madhav, additional, Healy, Jessica M., additional, Slayton, Rachel B., additional, Biggerstaff, Matthew, additional, Johansson, Michael A., additional, Shea, Katriona, additional, and Lessler, Justin, additional

Published
2021
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14. COVID-19 reopening strategies at the county level in the face of uncertainty: Multiple Models for Outbreak Decision Support

Author

Shea, Katriona, primary, Borchering, Rebecca K., additional, Probert, William J.M., additional, Howerton, Emily, additional, Bogich, Tiffany L., additional, Li, Shouli, additional, van Panhuis, Willem G., additional, Viboud, Cecile, additional, Aguás, Ricardo, additional, Belov, Artur, additional, Bhargava, Sanjana H., additional, Cavany, Sean, additional, Chang, Joshua C., additional, Chen, Cynthia, additional, Chen, Jinghui, additional, Chen, Shi, additional, Chen, YangQuan, additional, Childs, Lauren M., additional, Chow, Carson C., additional, Crooker, Isabel, additional, Del Valle, Sara Y., additional, España, Guido, additional, Fairchild, Geoffrey, additional, Gerkin, Richard C., additional, Germann, Timothy C., additional, Gu, Quanquan, additional, Guan, Xiangyang, additional, Guo, Lihong, additional, Hart, Gregory R., additional, Hladish, Thomas J., additional, Hupert, Nathaniel, additional, Janies, Daniel, additional, Kerr, Cliff C., additional, Klein, Daniel J., additional, Klein, Eili, additional, Lin, Gary, additional, Manore, Carrie, additional, Meyers, Lauren Ancel, additional, Mittler, John, additional, Mu, Kunpeng, additional, Núñez, Rafael C., additional, Oidtman, Rachel, additional, Pasco, Remy, additional, Piontti, Ana Pastore y, additional, Paul, Rajib, additional, Pearson, Carl A. B., additional, Perdomo, Dianela R., additional, Perkins, T Alex, additional, Pierce, Kelly, additional, Pillai, Alexander N., additional, Rael, Rosalyn Cherie, additional, Rosenfeld, Katherine, additional, Ross, Chrysm Watson, additional, Spencer, Julie A., additional, Stoltzfus, Arlin B., additional, Toh, Kok Ben, additional, Vattikuti, Shashaank, additional, Vespignani, Alessandro, additional, Wang, Lingxiao, additional, White, Lisa, additional, Xu, Pan, additional, Yang, Yupeng, additional, Yogurtcu, Osman N., additional, Zhang, Weitong, additional, Zhao, Yanting, additional, Zou, Difan, additional, Ferrari, Matthew, additional, Pannell, David, additional, Tildesley, Michael, additional, Seifarth, Jack, additional, Johnson, Elyse, additional, Biggerstaff, Matthew, additional, Johansson, Michael, additional, Slayton, Rachel B., additional, Levander, John, additional, Stazer, Jeff, additional, Salerno, Jessica, additional, and Runge, Michael C., additional

Published
2020
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15. Contributors

Author

Anderson, Brigham, primary, Anklekar, T.V. (Sunil), additional, Aryel, Ron M., additional, Brokopp, Charles, additional, Campbell, Murray, additional, Chapman, Wendy W., additional, Cirino, Nick M., additional, Cooper, Gregory F., additional, Cox, Kenneth L., additional, Das, Kaustav, additional, Dash, Denver H., additional, Daswani, Sherry, additional, Dato, Virginia, additional, DeFrancesco, Steve, additional, Egan, Christina, additional, Espino, Jeremy, additional, Gesteland, Per H., additional, Gresham, Louise S., additional, Goodman, Kenneth W., additional, Hogan, William R., additional, Grigoryan, Vahan, additional, Holmes, Harvey, additional, Hutchison, Kevin, additional, Hutman, Judith, additional, Jacobson, Neil, additional, Johnson, Heather A., additional, Johnson, Jeffrey, additional, Kirsh, David, additional, Lee, Bruce Y., additional, Lenert, Leslie, additional, Levander, John D., additional, Moore, Andrew W., additional, Neill, Daniel B., additional, Onisko, Angieszka, additional, Pavlin, Julie, additional, Resultan, Eric, additional, Shaffer, Loren, additional, Shepard, Jason R.E., additional, Shephard, Richard, additional, Szczepaniak, M. Cleat, additional, Tsui, Fu-Chiang, additional, Velikina, Rita, additional, Wagner, Michael M., additional, Wallstrom, Garrick, additional, and Wong, Weng-Keen, additional

Published
2006
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21. Modeling of Future COVID-19 Cases, Hospitalizations, and Deaths, by Vaccination Rates and Nonpharmaceutical Intervention Scenarios - United States, April-September 2021

Author

Borchering, Rebecca K., Viboud, Cecile, Howerton, Emily, Smith, Claire P., Truelove, Shaun, Runge, Michael C., Reich, Nicholas G., Contamin, Lucie, Levander, John, Salerno, Jessica, van Panhuis, Wilbert, Kinsey, Matt, Tallaksen, Kate, Obrecht, R. Freddy, Asher, Laura, Costello, Cash, Kelbaugh, Michael, Wilson, Shelby, Shin, Lauren, Gallagher, Molly E., Mullany, Luke C., Rainwater-Lovett, Kaitlin, Lemaitre, Joseph C., Dent, Juan, Grantz, Kyra H., Kaminsky, Joshua, Lauer, Stephen A., Lee, Elizabeth C., Meredith, Hannah R., Perez-Saez, Javier, Keegan, Lindsay T., Karlen, Dean, Chinazzi, Matteo, Davis, Jessica T., Mu, Kunpeng, Xiong, Xinyue, Pastore y Piontti, Ana, Vespignani, Alessandro, Srivastava, Ajitesh, Porebski, Przemyslaw, Venkatramanan, Srinivasan, Adiga, Aniruddha, Lewis, Bryan, Klahn, Brian, Outten, Joseph, Schlitt, James, Corbett, Patrick, Telionis, Pyrros Alexander, Wang, Lijing, Peddireddy, Akhil Sai, Hurt, Benjamin, Chen, Jiangzhuo, Vullikanti, Anil, Marathe, Madhav, Healy, Jessica M., Slayton, Rachel B., Biggerstaff, Matthew, Johansson, Michael A., Shea, Katriona, and Lessler, Justin

23. Potential impact of annual vaccination with reformulated COVID-19 vaccines: lessons from the U.S. COVID-19 Scenario Modeling Hub.

Author

Jung SM, Loo SL, Howerton E, Contamin L, Smith CP, Carcelén EC, Yan K, Bents SJ, Levander J, Espino J, Lemaitre JC, Sato K, McKee CD, Hill AL, Chinazzi M, Davis JT, Mu K, Vespignani A, Rosenstrom ET, Rodriguez-Cartes SA, Ivy JS, Mayorga ME, Swann JL, España G, Cavany S, Moore SM, Perkins A, Chen S, Paul R, Janies D, Thill JC, Srivastava A, Al Aawar M, Bi K, Bandekar SR, Bouchnita A, Fox SJ, Meyers LA, Porebski P, Venkatramanan S, Adiga A, Hurt B, Klahn B, Outten J, Chen J, Mortveit H, Wilson A, Hoops S, Bhattacharya P, Machi D, Vullikanti A, Lewis B, Marathe M, Hochheiser H, Runge MC, Shea K, Truelove S, Viboud C, and Lessler J

Abstract

Importance: COVID-19 continues to cause significant hospitalizations and deaths in the United States. Its continued burden and the impact of annually reformulated vaccines remain unclear., Objective: To project COVID-19 hospitalizations and deaths from April 2023-April 2025 under two plausible assumptions about immune escape (20% per year and 50% per year) and three possible CDC recommendations for the use of annually reformulated vaccines (no vaccine recommendation, vaccination for those aged 65+, vaccination for all eligible groups)., Design: The COVID-19 Scenario Modeling Hub solicited projections of COVID-19 hospitalization and deaths between April 15, 2023-April 15, 2025 under six scenarios representing the intersection of considered levels of immune escape and vaccination. State and national projections from eight modeling teams were ensembled to produce projections for each scenario., Setting: The entire United States., Participants: None., Exposure: Annually reformulated vaccines assumed to be 65% effective against strains circulating on June 15 of each year and to become available on September 1. Age and state specific coverage in recommended groups was assumed to match that seen for the first (fall 2021) COVID-19 booster., Main Outcomes and Measures: Ensemble estimates of weekly and cumulative COVID-19 hospitalizations and deaths. Expected relative and absolute reductions in hospitalizations and deaths due to vaccination over the projection period., Results: From April 15, 2023-April 15, 2025, COVID-19 is projected to cause annual epidemics peaking November-January. In the most pessimistic scenario (high immune escape, no vaccination recommendation), we project 2.1 million (90% PI: 1,438,000-4,270,000) hospitalizations and 209,000 (90% PI: 139,000-461,000) deaths, exceeding pre-pandemic mortality of influenza and pneumonia. In high immune escape scenarios, vaccination of those aged 65+ results in 230,000 (95% CI: 104,000-355,000) fewer hospitalizations and 33,000 (95% CI: 12,000-54,000) fewer deaths, while vaccination of all eligible individuals results in 431,000 (95% CI: 264,000-598,000) fewer hospitalizations and 49,000 (95% CI: 29,000-69,000) fewer deaths., Conclusion and Relevance: COVID-19 is projected to be a significant public health threat over the coming two years. Broad vaccination has the potential to substantially reduce the burden of this disease., Competing Interests: Conflict of Interest Disclosures J. Espino is president of General Biodefense LLC, a private consulting group for public health informatics, and has interest in READE.ai, a medical artificial intelligence solutions company. M. Runge reports stock ownership in Becton Dickinson & Co., which manufactures medical equipment used in COVID-19 testing, vaccination, and treatment. J. Lessler has served as an expert witness on cases where the likely length of the pandemic was of issue.

Published
2023
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24. Informing pandemic response in the face of uncertainty. An evaluation of the U.S. COVID-19 Scenario Modeling Hub .

Author

Howerton E, Contamin L, Mullany LC, Qin M, Reich NG, Bents S, Borchering RK, Jung SM, Loo SL, Smith CP, Levander J, Kerr J, Espino J, van Panhuis WG, Hochheiser H, Galanti M, Yamana T, Pei S, Shaman J, Rainwater-Lovett K, Kinsey M, Tallaksen K, Wilson S, Shin L, Lemaitre JC, Kaminsky J, Hulse JD, Lee EC, McKee C, Hill A, Karlen D, Chinazzi M, Davis JT, Mu K, Xiong X, Piontti APY, Vespignani A, Rosenstrom ET, Ivy JS, Mayorga ME, Swann JL, España G, Cavany S, Moore S, Perkins A, Hladish T, Pillai A, Toh KB, Longini I Jr, Chen S, Paul R, Janies D, Thill JC, Bouchnita A, Bi K, Lachmann M, Fox S, Meyers LA, Srivastava A, Porebski P, Venkatramanan S, Adiga A, Lewis B, Klahn B, Outten J, Hurt B, Chen J, Mortveit H, Wilson A, Marathe M, Hoops S, Bhattacharya P, Machi D, Cadwell BL, Healy JM, Slayton RB, Johansson MA, Biggerstaff M, Truelove S, Runge MC, Shea K, Viboud C, and Lessler J

Abstract

Our ability to forecast epidemics more than a few weeks into the future is constrained by the complexity of disease systems, our limited ability to measure the current state of an epidemic, and uncertainties in how human action will affect transmission. Realistic longer-term projections (spanning more than a few weeks) may, however, be possible under defined scenarios that specify the future state of critical epidemic drivers, with the additional benefit that such scenarios can be used to anticipate the comparative effect of control measures. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make 6-month ahead projections of the number of SARS-CoV-2 cases, hospitalizations and deaths. The SMH released nearly 1.8 million national and state-level projections between February 2021 and November 2022. SMH performance varied widely as a function of both scenario validity and model calibration. Scenario assumptions were periodically invalidated by the arrival of unanticipated SARS-CoV-2 variants, but SMH still provided projections on average 22 weeks before changes in assumptions (such as virus transmissibility) invalidated scenarios and their corresponding projections. During these periods, before emergence of a novel variant, a linear opinion pool ensemble of contributed models was consistently more reliable than any single model, and projection interval coverage was near target levels for the most plausible scenarios (e.g., 79% coverage for 95% projection interval). SMH projections were used operationally to guide planning and policy at different stages of the pandemic, illustrating the value of the hub approach for long-term scenario projections.

Published
2023
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25. Impact of SARS-CoV-2 vaccination of children ages 5-11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021-March 2022: A multi-model study.

Author

Borchering RK, Mullany LC, Howerton E, Chinazzi M, Smith CP, Qin M, Reich NG, Contamin L, Levander J, Kerr J, Espino J, Hochheiser H, Lovett K, Kinsey M, Tallaksen K, Wilson S, Shin L, Lemaitre JC, Hulse JD, Kaminsky J, Lee EC, Hill AL, Davis JT, Mu K, Xiong X, Pastore Y Piontti A, Vespignani A, Srivastava A, Porebski P, Venkatramanan S, Adiga A, Lewis B, Klahn B, Outten J, Hurt B, Chen J, Mortveit H, Wilson A, Marathe M, Hoops S, Bhattacharya P, Machi D, Chen S, Paul R, Janies D, Thill JC, Galanti M, Yamana T, Pei S, Shaman J, España G, Cavany S, Moore S, Perkins A, Healy JM, Slayton RB, Johansson MA, Biggerstaff M, Shea K, Truelove SA, Runge MC, Viboud C, and Lessler J

Abstract

Background: The COVID-19 Scenario Modeling Hub convened nine modeling teams to project the impact of expanding SARS-CoV-2 vaccination to children aged 5-11 years on COVID-19 burden and resilience against variant strains., Methods: Teams contributed state- and national-level weekly projections of cases, hospitalizations, and deaths in the United States from September 12, 2021 to March 12, 2022. Four scenarios covered all combinations of 1) vaccination (or not) of children aged 5-11 years (starting November 1, 2021), and 2) emergence (or not) of a variant more transmissible than the Delta variant (emerging November 15, 2021). Individual team projections were linearly pooled. The effect of childhood vaccination on overall and age-specific outcomes was estimated using meta-analyses., Findings: Assuming that a new variant would not emerge, all-age COVID-19 outcomes were projected to decrease nationally through mid-March 2022. In this setting, vaccination of children 5-11 years old was associated with reductions in projections for all-age cumulative cases (7.2%, mean incidence ratio [IR] 0.928, 95% confidence interval [CI] 0.880-0.977), hospitalizations (8.7%, mean IR 0.913, 95% CI 0.834-0.992), and deaths (9.2%, mean IR 0.908, 95% CI 0.797-1.020) compared with scenarios without childhood vaccination. Vaccine benefits increased for scenarios including a hypothesized more transmissible variant, assuming similar vaccine effectiveness. Projected relative reductions in cumulative outcomes were larger for children than for the entire population. State-level variation was observed., Interpretation: Given the scenario assumptions (defined before the emergence of Omicron), expanding vaccination to children 5-11 years old would provide measurable direct benefits, as well as indirect benefits to the all-age U.S. population, including resilience to more transmissible variants., Funding: Various (see acknowledgments)., Competing Interests: JL has served as an expert witness on cases where the likely length of the pandemic was of issue. MCR reports stock ownership in Becton Dickinson & Co., which manufactures medical equipment used in COVID-19 testing, vaccination, and treatment. JS and Columbia University disclose partial ownership of SK Analytics. JS discloses consulting for BNI. There are no other competing interests to declare.

Published
2023
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26. Impact of SARS-CoV-2 vaccination of children ages 5-11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021-March 2022: a multi-model study.

Author

Borchering RK, Mullany LC, Howerton E, Chinazzi M, Smith CP, Qin M, Reich NG, Contamin L, Levander J, Kerr J, Espino J, Hochheiser H, Lovett K, Kinsey M, Tallaksen K, Wilson S, Shin L, Lemaitre JC, Hulse JD, Kaminsky J, Lee EC, Davis JT, Mu K, Xiong X, Piontti APY, Vespignani A, Srivastava A, Porebski P, Venkatramanan S, Adiga A, Lewis B, Klahn B, Outten J, Hurt B, Chen J, Mortveit H, Wilson A, Marathe M, Hoops S, Bhattacharya P, Machi D, Chen S, Paul R, Janies D, Thill JC, Galanti M, Yamana T, Pei S, Shaman J, Espana G, Cavany S, Moore S, Perkins A, Healy JM, Slayton RB, Johansson MA, Biggerstaff M, Shea K, Truelove SA, Runge MC, Viboud C, and Lessler J

Abstract

Background: SARS-CoV-2 vaccination of persons aged 12 years and older has reduced disease burden in the United States. The COVID-19 Scenario Modeling Hub convened multiple modeling teams in September 2021 to project the impact of expanding vaccine administration to children 5-11 years old on anticipated COVID-19 burden and resilience against variant strains., Methods: Nine modeling teams contributed state- and national-level projections for weekly counts of cases, hospitalizations, and deaths in the United States for the period September 12, 2021 to March 12, 2022. Four scenarios covered all combinations of: 1) presence vs. absence of vaccination of children ages 5-11 years starting on November 1, 2021; and 2) continued dominance of the Delta variant vs. emergence of a hypothetical more transmissible variant on November 15, 2021. Individual team projections were combined using linear pooling. The effect of childhood vaccination on overall and age-specific outcomes was estimated by meta-analysis approaches., Findings: Absent a new variant, COVID-19 cases, hospitalizations, and deaths among all ages were projected to decrease nationally through mid-March 2022. Under a set of specific assumptions, models projected that vaccination of children 5-11 years old was associated with reductions in all-age cumulative cases (7.2%, mean incidence ratio [IR] 0.928, 95% confidence interval [CI] 0.880-0.977), hospitalizations (8.7%, mean IR 0.913, 95% CI 0.834-0.992), and deaths (9.2%, mean IR 0.908, 95% CI 0.797-1.020) compared with scenarios where children were not vaccinated. This projected effect of vaccinating children 5-11 years old increased in the presence of a more transmissible variant, assuming no change in vaccine effectiveness by variant. Larger relative reductions in cumulative cases, hospitalizations, and deaths were observed for children than for the entire U.S. population. Substantial state-level variation was projected in epidemic trajectories, vaccine benefits, and variant impacts., Conclusions: Results from this multi-model aggregation study suggest that, under a specific set of scenario assumptions, expanding vaccination to children 5-11 years old would provide measurable direct benefits to this age group and indirect benefits to the all-age U.S. population, including resilience to more transmissible variants.

Published
2022
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27. Projected resurgence of COVID-19 in the United States in July-December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination.

Author

Truelove S, Smith CP, Qin M, Mullany LC, Borchering RK, Lessler J, Shea K, Howerton E, Contamin L, Levander J, Salerno J, Hochheiser H, Kinsey M, Tallaksen K, Wilson S, Shin L, Rainwater-Lovett K, Lemaitre JC, Dent J, Kaminsky J, Lee EC, Perez-Saez J, Hill A, Karlen D, Chinazzi M, Davis JT, Mu K, Xiong X, Piontti APY, Vespignani A, Srivastava A, Porebski P, Venkatramanan S, Adiga A, Lewis B, Klahn B, Outten J, Schlitt J, Corbett P, Telionis PA, Wang L, Peddireddy AS, Hurt B, Chen J, Vullikanti A, Marathe M, Hoops S, Bhattacharya P, Machi D, Chen S, Paul R, Janies D, Thill JC, Galanti M, Yamana T, Pei S, Shaman J, Reich NG, Healy JM, Slayton RB, Biggerstaff M, Johansson MA, Runge MC, and Viboud C

Abstract

What Is Already Known About This Topic?: The highly transmissible SARS-CoV-2 Delta variant has begun to cause increases in cases, hospitalizations, and deaths in parts of the United States. With slowed vaccination uptake, this novel variant is expected to increase the risk of pandemic resurgence in the US in July-December 2021., What Is Added by This Report?: Data from nine mechanistic models project substantial resurgences of COVID-19 across the US resulting from the more transmissible Delta variant. These resurgences, which have now been observed in most states, were projected to occur across most of the US, coinciding with school and business reopening. Reaching higher vaccine coverage in July-December 2021 reduces the size and duration of the projected resurgence substantially. The expected impact of the outbreak is largely concentrated in a subset of states with lower vaccination coverage., What Are the Implications for Public Health Practice?: Renewed efforts to increase vaccination uptake are critical to limiting transmission and disease, particularly in states with lower current vaccination coverage. Reaching higher vaccination goals in the coming months can potentially avert 1.5 million cases and 21,000 deaths and improve the ability to safely resume social contacts, and educational and business activities. Continued or renewed non-pharmaceutical interventions, including masking, can also help limit transmission, particularly as schools and businesses reopen.

Published
2021
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28. COVID-19 reopening strategies at the county level in the face of uncertainty: Multiple Models for Outbreak Decision Support.

Author

Shea K, Borchering RK, Probert WJM, Howerton E, Bogich TL, Li S, van Panhuis WG, Viboud C, Aguás R, Belov A, Bhargava SH, Cavany S, Chang JC, Chen C, Chen J, Chen S, Chen Y, Childs LM, Chow CC, Crooker I, Valle SYD, España G, Fairchild G, Gerkin RC, Germann TC, Gu Q, Guan X, Guo L, Hart GR, Hladish TJ, Hupert N, Janies D, Kerr CC, Klein DJ, Klein E, Lin G, Manore C, Meyers LA, Mittler J, Mu K, Núñez RC, Oidtman R, Pasco R, Piontti APY, Paul R, Pearson CAB, Perdomo DR, Perkins TA, Pierce K, Pillai AN, Rael RC, Rosenfeld K, Ross CW, Spencer JA, Stoltzfus AB, Toh KB, Vattikuti S, Vespignani A, Wang L, White L, Xu P, Yang Y, Yogurtcu ON, Zhang W, Zhao Y, Zou D, Ferrari M, Pannell D, Tildesley M, Seifarth J, Johnson E, Biggerstaff M, Johansson M, Slayton RB, Levander J, Stazer J, Salerno J, and Runge MC

Abstract

Policymakers make decisions about COVID-19 management in the face of considerable uncertainty. We convened multiple modeling teams to evaluate reopening strategies for a mid-sized county in the United States, in a novel process designed to fully express scientific uncertainty while reducing linguistic uncertainty and cognitive biases. For the scenarios considered, the consensus from 17 distinct models was that a second outbreak will occur within 6 months of reopening, unless schools and non-essential workplaces remain closed. Up to half the population could be infected with full workplace reopening; non-essential business closures reduced median cumulative infections by 82%. Intermediate reopening interventions identified no win-win situations; there was a trade-off between public health outcomes and duration of workplace closures. Aggregate results captured twice the uncertainty of individual models, providing a more complete expression of risk for decision-making purposes.

Published
2020
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29. Apollo: giving application developers a single point of access to public health models using structured vocabularies and Web services.

Author

Wagner MM, Levander JD, Brown S, Hogan WR, Millett N, and Hanna J

Subjects
Algorithms, Computer Graphics, Humans, Internet, Public Health Informatics, Biological Ontologies, Communicable Diseases, Emerging, Computer Simulation, Epidemics, Software
Abstract

This paper describes the Apollo Web Services and Apollo-SV, its related ontology. The Apollo Web Services give an end-user application a single point of access to multiple epidemic simulators. An end user can specify an analytic problem-which we define as a configuration and a query of results-exactly once and submit it to multiple epidemic simulators. The end user represents the analytic problem using a standard syntax and vocabulary, not the native languages of the simulators. We have demonstrated the feasibility of this design by implementing a set of Apollo services that provide access to two epidemic simulators and two visualizer services.

Published
2013

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