A David Paltiel1, Amy Zheng2, Paul E Sax3. 1. Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut (A.D.P.). 2. Harvard Medical School, Boston, Massachusetts (A.Z.). 3. Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts (P.E.S.).
Abstract
BACKGROUND: The value of frequent, rapid testing to reduce community transmission of SARS-CoV-2 is poorly understood. OBJECTIVE: To define performance standards and predict the clinical, epidemiologic, and economic outcomes of nationwide, home-based antigen testing. DESIGN: A simple compartmental epidemic model that estimated viral transmission, portrayed disease progression, and forecast resource use, with and without testing. DATA SOURCES: Parameter values and ranges as informed by Centers for Disease Control and Prevention guidance and published literature. TARGET POPULATION: U.S. population. TIME HORIZON: 60 days. PERSPECTIVE: Societal; costs included testing, inpatient care, and lost workdays. INTERVENTION: Home-based SARS-CoV-2 antigen testing. OUTCOME MEASURES: Cumulative infections and deaths, number of persons isolated and hospitalized, and total costs. RESULTS OF BASE-CASE ANALYSIS: Without a testing intervention, the model anticipates 11.6 million infections, 119 000 deaths, and $10.1 billion in costs ($6.5 billion in inpatient care and $3.5 billion in lost productivity) over a 60-day horizon. Weekly availability of testing would avert 2.8 million infections and 15 700 deaths, increasing costs by $22.3 billion. Lower inpatient outlays ($5.9 billion) would partially offset additional testing expenditures ($12.5 billion) and workdays lost ($14.0 billion), yielding incremental cost-effectiveness ratios of $7890 per infection averted and $1 430 000 per death averted. RESULTS OF SENSITIVITY ANALYSIS: Outcome estimates vary widely under different behavioral assumptions and testing frequencies. However, key findings persist across all scenarios, with large reductions in infections, mortality, and hospitalizations. Costs per death averted are roughly an order of magnitude lower than commonly accepted willingness-to-pay values per statistical life saved ($5 to $17 million). LIMITATIONS: Analysis was restricted to at-home testing. There are uncertainties concerning test performance. CONCLUSION: High-frequency home testing for SARS-CoV-2 with an inexpensive, imperfect test could contribute to pandemic control at justifiable cost and warrants consideration as part of a national containment strategy. PRIMARY FUNDING SOURCE: National Institutes of Health.
BACKGROUND: The value of frequent, rapid testing to reduce community transmission of SARS-CoV-2 is poorly understood. OBJECTIVE: To define performance standards and predict the clinical, epidemiologic, and economic outcomes of nationwide, home-based antigen testing. DESIGN: A simple compartmental epidemic model that estimated viral transmission, portrayed disease progression, and forecast resource use, with and without testing. DATA SOURCES: Parameter values and ranges as informed by Centers for Disease Control and Prevention guidance and published literature. TARGET POPULATION: U.S. population. TIME HORIZON: 60 days. PERSPECTIVE: Societal; costs included testing, inpatient care, and lost workdays. INTERVENTION: Home-based SARS-CoV-2 antigen testing. OUTCOME MEASURES: Cumulative infections and deaths, number of persons isolated and hospitalized, and total costs. RESULTS OF BASE-CASE ANALYSIS: Without a testing intervention, the model anticipates 11.6 million infections, 119 000 deaths, and $10.1 billion in costs ($6.5 billion in inpatient care and $3.5 billion in lost productivity) over a 60-day horizon. Weekly availability of testing would avert 2.8 million infections and 15 700 deaths, increasing costs by $22.3 billion. Lower inpatient outlays ($5.9 billion) would partially offset additional testing expenditures ($12.5 billion) and workdays lost ($14.0 billion), yielding incremental cost-effectiveness ratios of $7890 per infection averted and $1 430 000 per death averted. RESULTS OF SENSITIVITY ANALYSIS: Outcome estimates vary widely under different behavioral assumptions and testing frequencies. However, key findings persist across all scenarios, with large reductions in infections, mortality, and hospitalizations. Costs per death averted are roughly an order of magnitude lower than commonly accepted willingness-to-pay values per statistical life saved ($5 to $17 million). LIMITATIONS: Analysis was restricted to at-home testing. There are uncertainties concerning test performance. CONCLUSION: High-frequency home testing for SARS-CoV-2 with an inexpensive, imperfect test could contribute to pandemic control at justifiable cost and warrants consideration as part of a national containment strategy. PRIMARY FUNDING SOURCE: National Institutes of Health.
Authors: Kristina L Bajema; Ryan E Wiegand; Kendra Cuffe; Sadhna V Patel; Ronaldo Iachan; Travis Lim; Adam Lee; Davia Moyse; Fiona P Havers; Lee Harding; Alicia M Fry; Aron J Hall; Kelly Martin; Marjorie Biel; Yangyang Deng; William A Meyer; Mohit Mathur; Tonja Kyle; Adi V Gundlapalli; Natalie J Thornburg; Lyle R Petersen; Chris Edens Journal: JAMA Intern Med Date: 2021-04-01 Impact factor: 21.873
Authors: Tuna Toptan; Lisa Eckermann; Annika E Pfeiffer; Sebastian Hoehl; Sandra Ciesek; Christian Drosten; Victor M Corman Journal: J Clin Virol Date: 2020-12-05 Impact factor: 3.168
Authors: Andrew T Levin; William P Hanage; Nana Owusu-Boaitey; Kensington B Cochran; Seamus P Walsh; Gideon Meyerowitz-Katz Journal: Eur J Epidemiol Date: 2020-12-08 Impact factor: 8.082
Authors: Alyssa Bilinski; Andrea Ciaranello; Meagan C Fitzpatrick; John Giardina; Maunank Shah; Joshua A Salomon; Emily A Kendall Journal: medRxiv Date: 2021-08-10
Authors: Anna Kristina Witte; Janina Grosch; Beate Conrady; Lena Schomakers; Marcus Grohmann Journal: Int J Environ Res Public Health Date: 2022-04-13 Impact factor: 4.614
Authors: Patrick Kierkegaard; Timothy Hicks; A Joy Allen; Yaling Yang; Gail Hayward; Margaret Glogowska; Brian D Nicholson; Peter Buckle Journal: Implement Sci Commun Date: 2021-12-18