key: cord-0982636-e4xhitrc
authors: Neilan, Anne M; Losina, Elena; Bangs, Audrey C; Flanagan, Clare; Panella, Christopher; Eskibozkurt, G Ege; Mohareb, Amir; Hyle, Emily P; Scott, Justine A; Weinstein, Milton C; Siedner, Mark J; Reddy, Krishna P; Harling, Guy; Freedberg, Kenneth A; Shebl, Fatma M; Kazemian, Pooyan; Ciaranello, Andrea L
title: Clinical Impact, Costs, and Cost-Effectiveness of Expanded SARS-CoV-2 Testing in Massachusetts
date: 2020-09-18
journal: Clin Infect Dis
DOI: 10.1093/cid/ciaa1418
sha: 96c606ac772c060704f2f743ee1e5f3d7833f634
doc_id: 982636
cord_uid: e4xhitrc

BACKGROUND: We projected the clinical and economic impact of alternative testing strategies on COVID-19 incidence and mortality in Massachusetts using a microsimulation model. METHODS: We compared four testing strategies: 1) Hospitalized: PCR testing only patients with severe/critical symptoms warranting hospitalization; 2) Symptomatic: PCR for any COVID-19-consistent symptoms, with self-isolation if positive; 3) Symptomatic+asymptomatic-once: Symptomatic and one-time PCR for the entire population; and, 4) Symptomatic+asymptomatic-monthly: Symptomatic with monthly re-testing for the entire population. We examined effective reproduction numbers (R(e), 0.9-2.0) at which policy conclusions would change. We assumed homogeneous mixing among the Massachusetts population (excluding those residing in long-term care facilities). We used published data on disease progression and mortality, transmission, PCR sensitivity/specificity (70/100%) and costs. Model-projected outcomes included infections, deaths, tests performed, hospital-days, and costs over 180-days, as well as incremental cost-effectiveness ratios (ICER, $/quality-adjusted life-year [QALY]). RESULTS: At R(e) 0.9, Symptomatic+asymptomatic-monthly vs. Hospitalized resulted in a 64% reduction in infections and a 46% reduction in deaths, but required >66-fold more tests/day with 5-fold higher costs. Symptomatic+asymptomatic-monthly had an ICER <$100,000/QALY only when R(e) ≥1.6; when test cost was ≤$3, every 14-day testing was cost-effective at all R(e) examined. CONCLUSIONS: Testing people with any COVID-19-consistent symptoms would be cost-saving compared to testing only those whose symptoms warrant hospital care. Expanding PCR testing to asymptomatic people would decrease infections, deaths, and hospitalizations. Despite modest sensitivity, low-cost, repeat screening of the entire population could be cost-effective in all epidemic settings.

Massachusetts experienced a major COVID-19 outbreak beginning in March 2020 after a biotechnology convention, which was subsequently fueled by transmission in communities living in multi-generational and multi-family housing [1] . In the United States, restricted testing capacity early in the pandemic led states such as Massachusetts to test only severely symptomatic people and/or those with a known exposure [2] . While some have argued that testing must be highly sensitive in order to be of value to guide reopening [3] , others have argued that sensitivity can be sacrificed if tests are rapid, low-cost, and frequent [4, 5] . Despite the variable clinical sensitivity of SARS-CoV-2 polymerase chain reaction (PCR) testing, expanded testing programs could reduce transmissions by increasing isolation of infectious people, thereby reducing hospitalizations and deaths. Widely available testing could also allow for the safer resumption of economic and social activity by providing surveillance for any -second wave‖ of infection [6] . Such resumptions of public life may also benefit those with non-COVID-related health issues who may avoid seeking care due to concerns about acquiring COVID-19 [7] .

To date, no national testing strategy has been articulated [8] . Since new infections peaked in late April [9] , Massachusetts has used test positivity rates as a key indicator to guide gradual re-opening, after implementing strategies to reduce transmission risk [6] . In Massachusetts and elsewhere, planning is essential for utilization of key limited resources, such as testing and hospital beds, since mitigation strategies need to be able to pivot rapidly as epidemic growth scenarios change. Our goal was to examine the clinical and economic impact of screening strategies on COVID-19 in Massachusetts. M a n u s c r i p t 7

We developed a dynamic state-transition microsimulation model, the CEACOV (Clinical and Economic Analysis of COVID-19 Interventions) model, to reflect the natural history, diagnosis, and treatment of COVID-19. We modeled four testing strategies for all Massachusetts residents (excluding those residing in long-term care facilities): 1) Hospitalized: PCR testing only of those who develop severe illness (i.e., warranting hospital care), reflecting common practices in Massachusetts through late April 2020 [2] ; 2) Symptomatic: Hospitalized and PCR for people with any COVID-19-consistent symptoms who self-isolate if positive;

3) Symptomatic+asymptomatic-once: Symptomatic and a one-time PCR for the entire population; 4) Symptomatic+asymptomatic-monthly: Symptomatic+asymptomatic once and retesting every 30 days of those who test negative and remain asymptomatic (Supplementary Figure 1 ). For those who are not hospitalized, we assume a positive PCR test leads to selfisolation in the community. We projected clinical outcomes (infections, COVID-19-related mortality, quality-adjusted life-years [QALYs]), and COVID-19-related resource utilization (tests, hospital and intensive care unit (ICU) beds, self-isolation days), and costs for Massachusetts (6.9 million people, excluding long-term care facility residents) over a 180-day horizon. We report incremental cost-effectiveness ratios (ICER: difference in cost divided by difference in quality-adjusted life-years [$/QALY]) from a healthcare sector perspective (Supplementary Methods). The threshold at which interventions are considered cost-effective is a normative value that varies by setting; for the sake of interpretability, we define a strategy as -cost-effective‖ if its ICER is below $100,000/QALY [10] .

A c c e p t e d M a n u s c r i p t 8

At model start, a closed pre-intervention cohort is seeded with a user-defined proportion of agestratified individuals (0-19, 25-59, ≥60 years) who are either infected with or susceptible to the SARS-CoV-2 virus. If infected, individuals face daily age-stratified probabilities of disease progression through seven health/disease states, including latent infection, asymptomatic illness, mild/moderate illness, severe illness (warranting hospitalization), critical illness (warranting intensive care), recuperation, and recovery (Supplementary Figure 2) . We assume recovered individuals are immune from repeat infection for the 180-day modeled horizon [11] . Susceptible and recovered individuals may also present for testing with symptoms due to non-COVID-19

conditions (-COVID-19-like illness‖).

Individuals can experience a daily probability of undergoing SARS-CoV-2 testing. Each PCR testing strategy includes test sensitivity/specificity, turnaround time, and testing frequency. M a n u s c r i p t 9 

The model tallies tests, COVID-19-related use of hospital and ICU bed-days, as well as days spent self-isolating.

We derived the initial distribution of COVID-19 disease severity by age from the Massachusetts Census and Department of Public Health (Table 1) [12, 13] . Disease progression and COVID-19related mortality are derived from data from China and Massachusetts and calibrated from mid-March to May 1, 2020 to deaths in Massachusetts (excluding those occurring in long-term care facilities) ( Table 1 and Supplementary Table 1 ) [13] [14] [15] [16] [17] [18] .

PCR test sensitivity/specificity are assumed to be 70%/100% (Table 1) [19, 20] . In all strategies, patients with severe or critical illness are eligible for diagnostic testing and are hospitalized regardless of PCR test result. Transmission is reduced by 90% for hospitalized people due to infection control and isolation practices (Table 1 and Supplementary Methods). In the expanded PCR-based strategies, self-isolation among those in the community with a positive PCR test leads to a 65% transmission reduction [21] ; those who test negative do not self-isolate (incorporating the potential for transmissions associated with false-negative tests). PCR test acceptance is assumed to be 80% for those who are asymptomatic or have mild/moderate illness at the time of testing, and 100% for those with severe or critical illness. (Table 1) .

PCR test cost is $51 [22] . Patients requiring hospitalization accrue per-day costs (hospital: $1,640; ICU: $2,680) [23] [24] [25] . We use projected deaths to estimate quality-adjusted discounted life-years lost per strategy (Supplementary Methods) [26] .

In each of the three epidemic growth scenarios, we vary PCR sensitivity (30-100%), test acceptance (15-100% for asymptomatic or mild/moderate symptoms), transmission reduction after a positive test (33-100%), presentation to hospital with severe disease (50-100%), ICU survival (20-80%), testing program costs (including additional outreach costs of offering PCR testing even if declined, $1-$26), and hospital M a n u s c r i p t 11 care costs ($820-$3,880). In multiway sensitivity analyses, we vary key parameters simultaneously. In additional analyses, we examined implementation of these testing strategies on April 1, 2020 vs. May 1, 2020; the R e threshold at which conclusions about the preferred strategy shifted (R e 1.3-2.0); the frequency of retesting in Symptomatic+asymptomatic-monthly (up to daily); patterns of presenting with COVID-19-like illness; and, the impact of costs associated with lost productivity due to hospitalization or positive PCR test results and averted mortality. Further details of methods, as well as model calibration and validation, are in the Supplementary Material.

All the expanded screening strategies would reduce infections and deaths compared to Hospitalized. In all epidemic scenarios, Symptomatic+asymptomatic-monthly would lead to the most favorable clinical outcomes and Hospitalized would lead to the least favorable outcomes; in the slowing scenario, Symptomatic+asymptomatic-monthly vs. Hospitalized resulted in 209,500 vs. 577,700 infections (64% reduction) and 1,700 vs. 3,100 deaths (46% reduction) (Table 2, top section). As R e increases, compared to Hospitalized, more expansive screening strategies would lead to greater reductions in infections and deaths (Table 2, bottom section). As R e increases, the expanded screening strategies, compared with Hospitalized, would result in a greater reduction in peak prevalence and lower reduction in the susceptible proportion of the population (Figures 1A-C) .

A c c e p t e d M a n u s c r i p t 12

In all epidemic growth scenarios, Symptomatic would lead to lower total costs compared to Hospitalized.

In the slowing scenario, Symptomatic+asymptomatic-monthly would lead to the greatest reduction in cumulative bed-days compared to Hospitalized: 77,300 vs. 126,000 hospital bed-days (39% reduction) and 45,600 vs. 76,600 ICU bed-days (40% reduction) but would require >66-fold times more tests/day (192, 200 vs. 2,900) at 5-fold higher total costs ($2.0 billion vs. $439 million) (Tables 2 and 3 ). In the slowing and intermediate scenarios, peak hospital bed use is similar across all strategies. In the surging scenario, however, all other PCR-based strategies would reduce peak hospital and ICU bed use compared to Hospitalized: hospital beds (7,100 vs. 2,300-4,600) and ICU beds (4,100 vs. 1,200-2,500) ( Table 3, bottom section). Supplementary Table 2 reports results/million people.

Under all epidemic growth scenarios considered, Symptomatic would be clinically superior and costsaving compared to Hospitalized (Table 2) . Symptomatic+asymptomatic-monthly would have an ICER <$100,000/QALY compared to Symptomatic only in the surging scenario ($33,000/QALY). ICERs increase steeply as R e declines ( Table 2) .

The impact of variation in clinical model input parameters on infections and deaths would be greatest in the surging scenario ( Supplementary Figures 3A-F) . Varying rates of presentation to hospital care and ICU survival would lead to large changes in mortality, which remain substantial (slowing scenario: 1,300-A c c e p t e d M a n u s c r i p t 13 2,400 deaths/180-days) even under optimistic assumptions (i.e., 100% presentation to hospital with severe illness or 80% ICU survival) (Supplementary Figures 3D-F) . If expanded PCR testing started April 1, 2020, compared to May 1, 2020, we project that PCR-based strategies would have averted 103,000-176,900 infections ( Supplementary Figures 4A-C) and 90-260 deaths in April alone (4D-F).

In one-way sensitivity analyses, the economically preferred strategy in each epidemic scenario was most sensitive to test acceptance, the transmission reduction after a positive PCR test, and PCR test costs Holding other parameters equal to the base case, Symptomatic+asymptomatic-monthly would become cost-effective at an R e value ≥1.6 (Supplementary Table 12 ). The frequency of repeat testing with Symptomatic+asymptomatic-monthly is also influential; in the surging scenario, Symptomatic+asymptomatic-monthly would no longer be cost-effective if tests occur more frequently than every 30 days (Supplementary Table 13 ), however if test costs were ≤$3, then testing as frequently as every 14-days would be cost-effective in all epidemic scenarios (Figure 2 ). While total costs would vary widely with rates of COVID-19-like illness, cost-effectiveness conclusions would not change Table 14 ). Conclusions are similar even when costs associated with lost productivity or averted COVID-related mortality are included (Supplementary Table 15 ).

Using a microsimulation model, we projected the COVID-19 epidemic in Massachusetts from May 1, 2020 to November 1, 2020 under slowing, intermediate, and surging epidemic growth scenarios, to examine the clinical and economic impact of four testing strategies.

Expanded PCR testing beyond those with severe symptoms would reduce morbidity and mortality across a range of epidemic scenarios. In all R e scenarios, we estimate substantial reductions in mortality (1.8-to 2.6-fold lower) with Symptomatic+asymptomatic-monthly compared to Hospitalized. Our R e values encompass published estimates for Massachusetts during the study period [27] [28] [29] . Importantly, the slowing scenario likely reflects Massachusetts's response through June 2020 [9] , and the surging scenario provides important insight for elsewhere in the United States where infections are increasing.

We further estimate that if expanded PCR testing had been widely available in Massachusetts from April 1, 2020 to May 1, 2020, 103,000-176,900 infections and 90-260 deaths would have been averted during that one month alone. Given the average time from infection to hospitalization and death (~9 days and ~28 days, respectively), earlier expanded testing might also have facilitated timely recognition of epidemic trends and closure policies. Policies that reduce R e at scale (e.g., stay-at-home advisories), as occurred in Massachusetts even while PCR testing was scarce, are likely to be more effective than any of the modeled testing strategies [30, 31] . Similar to conclusions from other studies [27, [32] [33] [34] [35] , our findings suggest that looser restrictions on social distancing regulations (which can lead to a higher R e ) would require more aggressive testing, paired with individual behavioral measures, to control the epidemic.

A c c e p t e d M a n u s c r i p t 15 All the expanded screening strategies would lead to reductions in key hospital resource use as well as fewer days spent self-isolating compared to Hospitalized. In Massachusetts, an estimated 9,500 hospital beds and 1,500 ICU beds were available at the peak of the surge capacity, of which 3,800 and 1,440 were used [9, 36] . None of the modeled scenarios exceeded peak hospital bed capacity; however, we projected 23-75% of available hospital beds would be needed by people with COVID-19. In all scenarios, we projected peak ICU bed use close to or exceeding capacity (1, 100) . While some assumptions are uncertain (e.g. proportion of people presenting to the hospital with severe disease, probability of ICU survival) the substantial burden of severe and critical illness we project in all scenarios has important implications for healthcare globallyresources redirected for COVID-related illness may jeopardize the ability to care for other diseases.

In all examined epidemic growth scenarios, Symptomatic testing would be cost-saving compared to Hospitalized. At any R e above 1.6, Symptomatic+asymptomatic-monthly would be the most efficient use of resources, unless test acceptance is very low (15%). Importantly, at these higher R e values, screening the entire population only one time would be an inefficient strategy without repeat screening for those testing negative. ICERs were highly sensitive to PCR test costs. If low-cost testing were available at $5/test, it would be cost-effective or cost-saving to offer repeat testing in all epidemic scenarios. In the absence of rapid, low-cost, widely available testing, states will also need to prepare themselves to pivot testing strategies as the epidemic shifts.

In the slowing and intermediate scenarios, as of July 2020, Massachusetts would have test capacity to conduct the economically preferred Symptomatic strategy (approximately 12,000/day A c c e p t e d M a n u s c r i p t 16 estimated tests conducted statewide vs. 4,800-5,900 model-projected tests) [9] . However, in the surging scenario, the projected average of 203,100 tests/day (36.6 million/180 days) required to conduct the cost-effective Symptomatic+asymptomatic-monthly strategy would greatly exceed current capacity; notably, daily testing of the entire population in this scenario led to >3 million projected tests/day. Large-scale testing has been achieved early in the epidemic in some settings:

in March 2020, South Korea was testing 20,000 people/day [37] . Newer high throughput machines may process thousands of tests per day, rendering such an approach potentially feasible in the near future [38] . Additionally, the number of tests used for people without COVID-19 is uncertain; we assumed high rates of COVID-like-illness (adding approximately 2,800 tests/day) in the base case, however, it is likely, particularly in summer months, that fewer people would seek testing. Given that the economically preferred strategy changes depending on R e , implementation of the most cost-effective testing strategy will require careful planning and realtime epidemic monitoring in each setting to adapt to changing R e . Furthermore, while currently an aspiration, low-cost, rapid turnaround testing, even with current imperfect test sensitivity would be cost-effective even in low R e settings. While critical supply chain issues and other factors precluded widespread testing in the US early in the pandemic, even now, expanding testing capacity must remain a focus of national efforts. Given that scaling current technologies may not be feasible in all settings, additional innovative strategies including pooled-, rapid antigen-and home self-testing, should be examined [39, 40] .

The impact of any testing strategy depends on the actions that policymakers, employers, and individuals take in response. Compared to testing only those with severe symptoms, monthly routine testing averted only 58-64% of infections, whereas daily testing averted 75-91% of A c c e p t e d M a n u s c r i p t 17 infections. Our results emphasize how policies that support isolating people infected with COVID-19 are essential; when an individual is less adherent to self-isolation after a positive test (i.e., lower transmission reduction), the benefits of testing are greatly reduced. In Iceland, broad testing led to only 6% of the population being tested, with 34% of an invited random sample presenting for testing [41] . In the surging scenario, at low test acceptance rates (15%) among those with no or mild symptoms, Symptomatic+asymptomatic-monthly would no longer be costeffective. In Massachusetts, SARS-CoV-2 testing often does not require co-pays, and sufficient personal protective equipment permits safe testing [1, 2] . Nevertheless, people may avoid testing due to concerns such as physical discomfort, missing work, or stigma. While the Family Medical and Leave Act may provide support for those eligible who test positive (or if family members test positive), not all workers may be aware of their rights or have compliant employers [42] .

Federal and setting-specific incentives for infected people to self-isolate should be considered (e.g., childcare or workplace incentives) [43] . This analysis has important limitations. First, we assume homogenous population mixing. This assumption may over-or under-estimate the benefits of PCR testing; however, we have calibrated our model to reflect observed data, using a transmission multiplier. When relevant, we selected values or made assumptions which would provide a conservative estimate of the benefits of testing (PCR sensitivity, test cost, transmission reduction after a negative test), and then varied these values widely in sensitivity analyses. Second, we do not address supply chain lapses which could impact the feasibility of implementing these strategies. Third, we exclude several factors that may result from expanded testing that would render these strategies even more cost-effective, including averting quality-of-life reductions due to COVID-related morbidity or self-quarantine-related mental health issues [44] , preventing school closure-related workforce gaps [45] , increasing economic purchasing, and enabling economic activity to A c c e p t e d M a n u s c r i p t 18 reopen due to reduced COVID incidence [33] . We also assume that transmissions vary with a constant daily rate by disease state; emerging data suggest that infectivity may be highest early after acquisition of the virus [46] . If true, testing strategies which diagnose people in early or asymptomatic stages of infection would be of higher value. Finally, we do not model contact tracing, which is likely to be a critical tool to respond to a patchwork of surging outbreaks over time.

Testing people with any COVID-19-consistent symptoms would be cost-saving compared to testing only those whose symptoms warrant hospital care. Expanding SARS-CoV-2 PCR testing to asymptomatic people would reduce infections, deaths, and hospital resource use. Despite modest sensitivity, low-cost, repeat screening of the entire population could be cost-effective in all epidemic settings. 

The authors gratefully acknowledge Christopher Alba, Giulia Park, and Tijana Stanic for their assistance in preparing the manuscript for publication. 

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ICER for Symptomatic+asymptomatic-monthly strategy compared to the next less costly strategy in slowing scenario (June 1, 2020 Re 0.9)