key: cord-0881895-19sedi8f
authors: Holmdahl, I.; Kahn, R.; Hay, J.; Buckee, C. O.; Mina, M.
title: Frequent testing and immunity-based staffing will help mitigate outbreaks in nursing home settings
date: 2020-11-06
journal: nan
DOI: 10.1101/2020.11.04.20224758
sha: e0088846f2fe8f589803e85bdbaad0439d50164a
doc_id: 881895
cord_uid: 19sedi8f

Background: Nursing homes and other long term care facilities have been disproportionately impacted by the COVID-19 pandemic. Strategies are urgently needed to reduce transmission in these vulnerable populations. We aimed to evaluate the reduction in transmission in nursing homes achieved through contact-targeted interventions and testing and to evaluate the effectiveness of two types of screening tests conducted with varying frequency: 1) rapid antigen testing and 2) PCR testing. Methods: We developed an agent-based Susceptible-Exposed-Infectious(Asymptomatic/Symptomatic)-Recovered (SEIR) model to examine SARS-CoV-2 transmission in nursing homes. Residents and staff are modelled individually; residents are split into two cohorts based on COVID-19 diagnosis. In the resident cohorting intervention, recovered residents are moved back from the COVID (infected) cohort to the non-COVID (susceptible/uninfected) cohort. In the immunity-based staffing intervention, recovered staff, who we assume have protective immunity, are assigned to work in the non-COVID cohort, while susceptible staff work in the COVID cohort and are assumed to have high levels of protection from personal protective equipment. These interventions aim to reduce the fraction of people's contacts that are presumed susceptible (and therefore potentially infected) and replace them with recovered (immune) contacts. Results: The frequency and type of testing has a larger impact on the size of outbreaks than the cohorting and staffing interventions. The most effective testing strategies modeled are daily antigen testing of everyone and daily antigen testing of staff with weekly PCR testing for residents. Under all screening testing strategies, the immunity-based staffing intervention reduces the final size of the outbreak. The resident cohorting intervention reduces the final outbreak size under some, but not all, testing scenarios. Conclusions: Increasing the frequency of screening testing of all residents and staff, or even staff alone, in nursing homes has the potential to greatly reduce outbreaks in this vulnerable setting. Immunity-based staffing can further reduce spread at little or no additional cost and becomes particularly important when daily testing is not feasible.

In the United States, nursing homes and other long term care (LTC) facilities have been disproportionately affected by the COVID-19 pandemic. 1, 2 As of September 2020, 40% of COVID deaths nationwide are linked to nursing homes. 3 Residents of nursing homes are particularly high-risk due to their older age and high prevalence of underlying medical conditions that increase COVID risk. In addition to increased risk of severe symptoms and mortality, nursing homes have a high risk of transmission because residents live together in close quarters-often with at least two people in a room-and have frequent close contact with staff. 4 Furthermore, many facilities suffer from understaffing, which may lead to even higher contact rates between staff and residents, and larger COVID outbreaks. 5 The ability to develop evidence-based responses to this crisis has been constrained by limited data and a shortage of research in these facilities prior to the COVID-19 pandemic. So far, infection control in many nursing homes has relied on moving infected residents into new rooms in a "COVID cohort." separated from other residents in the facility, as recommended. 5, 6 Longterm separation after recovery keeps the susceptible cohorts at or near 100% susceptible, and thus has the potential unintended effect of preventing development of institutional herd immunity that could help slow outbreaks. Additionally, relatively little evidence has been built to understand the role of strategies that focus on staffing, based on infection histories.

Although guidelines require testing in nursing homes, 6 the frequency and type of testing varies.

In many cases, both cohorting efforts and testing strategies have failed to control outbreaks, likely due in part to identification of infected individuals after transmission has already occurred.

. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted November 6, 2020. ; https://doi.org/10.1101/2020.11.04.20224758 doi: medRxiv preprint A primary driver of these outbreaks is pre-symptomatic and asymptomatic transmission, the latter of which occurs in an estimated 40% of infections, 7,8 on average. Infected individuals who do end up developing symptoms appear to become infectious either at or before the time of symptom onset. For this reason, public health screening testing (i.e. testing of those who are non-symptomatic) is expected to be an important intervention to control transmission. In addition, control measures that reduce the frequency of contacts among those who are still susceptible and those infected but not yet identified could reduce the occurrence of transmission by those who are infectious without symptoms. Due to a lack of resources and continued difficulty accessing sufficient testing, it will be critical to identify interventions that will most effectively control infection in nursing homes at minimal cost.

Here, we use an agent-based model parameterized specifically for the nursing home context to examine how a range of interventions may impact the risk and size of COVID-19 outbreaks in this setting. We focus on two contact-based interventions to group staff and residents based on their infection and immunity status and examine testing interventions to reflect currently available virological tests. We propose strategies that involve co-locating susceptible nursing home residents with people -staff and residents -who have recovered and are assumed to be immune, and show that screening with frequent rapid antigen testing outperforms most PCRbased testing strategies.

We developed a stochastic, agent-based Susceptible-Exposed-Infectious(Asymptomatic/Symptomatic)-Recovered (SEIR) model to examine SARS-CoV-2 transmission in nursing home residents and staff. The model uses a cohorted framework, . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

The copyright holder for this preprint this version posted November 6, 2020. ; https://doi.org/10.1101/2020.11.04.20224758 doi: medRxiv preprint wherein nursing home residents who become infected with SARS-CoV-2 are separated into a distinct population after showing symptoms or testing positive, where they have no interactions with susceptible (or undiagnosed) residents ( Figure 1 ). Infected residents may be asymptomatic, in which case they can only be identified through testing, or symptomatic, in which case they are identified either by symptom onset or testing, whichever occurs first. Due to continued demands on nursing home capacity, we assume that new residents continue to move into the facility to replace those who have died throughout the outbreak, keeping capacity at 100% through the entire simulation, leading to a constant inflow of susceptible residents.

Staffing remains constant throughout the outbreak but is split between COVID and non-COVID cohorts in proportion to residents. Staff who become infected are sent home to recover before coming back to work, and are replaced by temporary workers while they recover. Daily contact rates are modeled between residents, staff, and between the two populations (i.e. staff-resident contacts). The manner and frequency of potentially infectious contacts between residents and staff are based on contact rates in a Massachusetts network of nursing home facilities, 10 and the impact of these assumptions are examined in our sensitivity analyses. In addition, we model a constant community prevalence (varying this prevalence in our sensitivity analysis), which impacts the daily probability of staff becoming infected outside of the LTC facility. Detailed parameters can be found in Table S1 .

For each individual, viral load is modeled as a tent-function approximating current data on viral shedding as described in the literature ( Figure 1C ) 9, 11 . Following a three to five day latent period, viral load increases rapidly for two to five days before peaking. Viral load then immediately begins to decline. For symptomatic individuals, onset of symptoms occurs after two days of increasing viral load, at which point they can be identified, resulting in an incubation period of 5-. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

The copyright holder for this preprint this version posted November 6, 2020. ; https://doi.org/10.1101/2020.11.04.20224758 doi: medRxiv preprint symptomatic infections. 14 The peak viral load varies between individuals, and is drawn from a normal distribution on the log scale around the estimated mean peak viral load. 15 The duration of detectable viral load varies between individuals and is normally distributed. Viral load can be detected after individuals are no longer infectious. 16 Infectiousness of individuals is based on viral load and is modeled categorically: not infectious, moderate infectiousness, and high infectiousness (Table S1 and Figure 1C ). We set the probability of infection given an infectious contact so as to get a plausible R0 in the absence of interventions in our simulations (Table   S1 ). 17

Using this transmission framework, we evaluate interventions that could be implemented in individual nursing homes: two interventions targeting contact patterns (between residents and/or staff) combined with variations on two primary testing interventions-PCR and rapid antigen tests (Table 1) . We assume that at baseline, under current guidelines, 6 residents who are identified as infected move into isolation in a separate COVID cohort; based on information from a Massachusetts network of nursing home facilities, 10 we further assume that these residents are not moved back into the non-COVID cohort once they have recovered. Under our resident cohorting intervention, recovered residents are instead moved back to the non-COVID cohort after they have recovered and are prioritized as roommates for new incoming residents, who are presumed to be susceptible. The immunity-based staffing intervention prioritizes placing available recovered staff, who we assume are immune over the short term, in the non-COVID cohort, leaving susceptible staff to work in the COVID cohort. Importantly, we assume staff working in the COVID cohort are provided adequate personal protective equipment (PPE).

Because we assume that the contacts that are happening in nursing homes are necessary, our interventions do not reduce contacts, but rather change with whom those contacts occur.

Whenever possible, these interventions reduce the fraction of people's contacts that are . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted November 6, 2020. ; https://doi.org/10.1101/2020.11.04.20224758 doi: medRxiv preprint presumed susceptible (and therefore potentially infected) and replace them with recovered (immune) contacts.

In the testing interventions, we evaluate two types of screening tests: 1) rapid antigen testing, and 2) PCR testing. We evaluate nine different combinations and frequencies of these two tests (Table 1) . Based on the current parameters of these tests, antigen testing is assumed to have a higher limit of detection (LOD) and consequently lower sensitivity than PCR (10^5 vs. 10^3 copies/mL LOD) but returns results immediately, whereas PCR has a two day delay (Table S1 and Table 1 ). Individuals who are waiting on test results are assumed to behave as normal unless they experience symptoms before receiving results, in which case residents are moved to the COVID cohort and staff are sent home. We further explore variations in the sensitivity of the antigen tests and the turnaround time of the PCR tests. Testing interventions begin immediately, while cohorting interventions start three weeks into the outbreak. We measure cumulative infections after six months and calculate the mean of 100 stochastic simulations under each combination of cohorting and testing interventions.

In our sensitivity analyses, we explore the impact of the ratio of staff to residents and resulting contact patterns, contact rates between residents, the prevalence of COVID transmission in the community, and the efficacy of PPE (Table S1) . We further examine variations in the relationship between viral load and infectiousness.

We find that under all screening testing strategies, the immunity-based staffing intervention, which involves susceptible staff working with infected residents, assuming appropriate PPE, and recovered staff working with susceptible residents, reduces the final size of the epidemic within . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted November 6, 2020. ; https://doi.org/10.1101/2020.11.04.20224758 doi: medRxiv preprint the facility ( Figure 2 , Table 2 ). The resident cohorting intervention reduces the final outbreak size under some, but not all, testing scenarios. Combining the cohorting and staffing interventions provides little added benefit over the staff intervention alone. Results of each cohorting and testing scenario were qualitatively consistent across all 100 simulations ( Figure   S1 ).

The cohorting and staffing interventions primarily impact cumulative incidence in residents.

Because we assume a constant rate of introduction from the community over the 6 month period, the reduction in staff infections within the nursing home due to these interventions is often undermined by infections due to ongoing community transmission.

The frequency and type of testing had a much larger impact on the size and dynamics of COVID-19 epidemics than the cohorting and staffing interventions ( Figure 2 ). We examine both frequency and "quality" of testing: for antigen tests we explore different sensitivities and for PCR testing we examine the impact of turnaround time, since these are the most important limitations of each type of test. For each test we model different combinations of daily, weekly, or twice weekly testing of staff and residents. In all simulations, we assume perfect specificity, for example through the use of rapid orthogonal molecular or antigen based confirmatory tests used whenever a rapid antigen test turns positive.

The most effective testing strategies modeled are daily antigen testing of everyone and daily antigen testing of staff only with weekly PCR testing for residents. These two approaches reduce the final outbreak size relative to weekly or even daily PCR testing of everyone, and result in the fewest overall infections. Under our baseline testing parameters, despite lower sensitivity (i.e. only detecting infections with higher viral load), rapid antigen testing proves more effective than PCR testing done at the same frequency due to its faster turnaround time.

. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted November 6, 2020. ; https://doi.org/10.1101/2020.11.04.20224758 doi: medRxiv preprint However, if antigen tests have a very low sensitivity (LOD = 10^7 vs. baseline assumption of 10^5 copies/mL) then daily antigen testing is less effective than daily PCR testing.

To examine the impact of ongoing issues with testing delays, we compare a scenario with weekly PCR testing in which individuals receive results after 7 days, rather than our baseline assumption of 2 days. In these "test delay" simulations, more residents are infected after 6 months than in simulations with no testing at all. This occurs because outbreaks without testing are faster and peak more rapidly than those with testing, leading to herd immunity in the facility that prevents new residents who enter the facility later on from getting infected. In contrast, testing with very long delays draws out the outbreak over a longer duration, allowing more incoming susceptible residents to become infected ( Figure 3 ). Under more effective testing strategies, such as daily antigen testing for both residents and staff, outbreaks are effectively prevented and cumulative incidence primarily reflects continued introductions from the community over time (Figure 3 ).

Community prevalence has an important impact on the total outbreak size and the efficacy of the interventions ( Figure S2 ). When community prevalence is lower, intervention efficacy follows the same general trends but is reduced for cohorting and staffing interventions, particularly when combined with more effective testing strategies. In addition, reducing the frequency of testing has a smaller effect on final size. In this setting, weekly antigen testing is approximately as effective as daily antigen testing, and twice weekly PCR is not clearly different from daily PCR-suggesting that in settings with lower prevalence, lower frequency testing strategies may be sufficient. The differences between testing strategies are much smaller than in the baseline scenario with higher community prevalence.

. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted November 6, 2020. ; https://doi.org/10.1101/2020.11.04.20224758 doi: medRxiv preprint

The efficacy of PPE impacts the cumulative incidence among healthcare workers, as expected ( Figure S3) , with lower efficacy leading to larger outbreaks. Increasing contact rates, either through more interactions between residents in addition to between roommates ( Figure S4 ) or decreasing the staff to resident ratio and therefore increasing the number of resident contacts for each staff member ( Figure S5) , also leads to larger outbreaks. Although the overall cumulative incidence is sensitive to these parameters, the relative efficacy of testing and cohorting and staffing interventions does not change.

Increasing the frequency of screening testing of all residents and staff, or even staff alone, in nursing homes has the potential to greatly reduce outbreaks in this vulnerable setting. Our results provide further support to other models' findings that increased frequency of testing should be prioritized over high test sensitivity, 11,18 even in small congregate settings like nursing homes. While rapid antigen testing generally performs better than PCR testing-which is more sensitive, but has a longer turnaround and may be prohibitively expensive-we do see that when the limit of detection is very high for antigen testing, this does not hold. This suggests that there may be a threshold effect at which point low sensitivity results in ineffective testing strategies.

The staffing intervention that we propose here can further reduce spread at little or no additional cost and becomes particularly important when daily testing is not feasible. It may have the additional advantage of being more straightforward to implement than an intervention that involves moving residents between rooms or floors of a facility, as in the cohorting intervention.

The staffing intervention works by reducing the risk that staff could infect susceptible residents by prioritizing recovered (and therefore immune) staff to work with them, lowering the effective reproduction number in the non-COVID cohort. While intuitively, this intervention may appear to . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted November 6, 2020. ; https://doi.org/10.1101/2020.11.04.20224758 doi: medRxiv preprint put staff at a higher risk, the final size of the epidemic due to transmission within the nursing home is lower among staff when this intervention is in place, due to the overall decrease in transmission in the facility. Access to appropriate PPE is required for this intervention to be feasible, and hinges on the assumption that recovered staff are protected against reinfection.

Our results suggest that, given limited resources, the choice of interventions could be guided by prevalence in the community. When prevalence is lower, cohorting and staffing interventions have a much smaller effect on the cumulative incidence. This is because the fraction of each person's contacts who are infected is already low, so the marginal benefits of the cohorting interventions at reducing that fraction is small. There is also less of a tradeoff between testing frequency and sensitivity-suggesting that when community prevalence is low and testing resources are limited, nursing homes could consider using weekly testing until an outbreak is detected either inside or outside of the facility. Models of similar settings have also found the frequency of testing required to control outbreaks can be dependent on community prevalence. 19 The timing of this transition, and how it should be implemented, may be an important area for future work.

We have made several simplifying assumptions in our model. We assume transmission only occurs upon contact, including close proximity, and do not take into account the possibility of strictly airborne transmission or the role of ventilation. As with other viruses, 20 the relationships between viral load and infectiousness and viral load and the sensitivity of the antigen tests for SARS-CoV-2 are still not fully understood. We have used a simplification of this complex process, which can be updated as more data become available. Sensitivity analyses that remove this relationship between viral load and infectiousness result in similar findings regarding relative infectiousness of different interventions ( Figure S6 ). Our representation of viral load dynamics is also simplified, assuming no differences between symptomatic and . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted November 6, 2020. ; https://doi.org/10.1101/2020.11.04.20224758 doi: medRxiv preprint asymptomatic individuals and ignoring persistent low detectable viral loads that have been described in SARS-CoV-2 infections. 16 Because we are looking at relatively frequent screening testing strategies, we do not expect dynamics on the tail of the viral load to impact our results. In addition, we are assuming that test specificity is high; ideally, for lower specificity tests, a positive test under either testing strategy would be confirmed by a second rapidly available test.

We have also made the assumption that staff have random schedules on a given day, and do not have repeated resident assignments over time.

We have shown how simple interventions involving testing and staffing can greatly reduce the burden of SARS-CoV-2 in nursing homes. Our model further underscores the importance of frequent testing, as well as providing adequate PPE to staff.

We thank Ron Anglo for helpful discussions and insights into Massachusetts' nursing homes.

MJM has received ad hoc speaking fees from Abbott Diagnostics and Roche Diagnostics.

Resident: Return recovered residents to rooms in the non-COVID cohort Immunity-based staffing: Place recovered staff in the non-COVID cohort and susceptible staff in the COVID cohort with PPE

. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted November 6, 2020. • PCR tests limit of detection = 0 and turnaround time = 2 days • Antigen tests limit of detection = 10^5 and turnaround time = same day is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted November 6, 2020. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted November 6, 2020. ; Figure S4 ). C) Following a three to five day latent period, viral load is modeled to increase rapidly for two to five 9 days before peaking. Viral load then immediately begins to decline. Infectiousness of individuals is based on viral load and is modeled categorically: not infectious, moderate infectiousness, and high infectiousness. LOD = limit of detection.

. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted November 6, 2020. ; https://doi.org/10.1101/2020.11.04.20224758 doi: medRxiv preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted November 6, 2020. ; https://doi.org/10.1101/2020.11.04.20224758 doi: medRxiv preprint out to distinguish between cases arising in the community and those that are a result of transmission within the nursing home. The staffing intervention reduces the final size of the outbreaks more than the resident intervention. Because we assume a constant rate of introduction from the community, the reduction in staff infections within the nursing home due to these contact-targeted interventions is compensated for with infections due to ongoing community transmission. Despite lower sensitivity (LOD = 10^5 unless otherwise specified), rapid antigen testing proves more effective than PCR testing (LOD = 10^3) done at the same frequency due to its faster turnaround time. Antigen test results are returned the same day, while PCR tests are assumed to take 2 days, unless otherwise specified. LOD = limit of detection.

. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted November 6, 2020. ; . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted November 6, 2020. ; https://doi.org/10.1101/2020.11.04.20224758 doi: medRxiv preprint . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted November 6, 2020. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted November 6, 2020. ; https://doi.org/10.1101/2020.11.04.20224758 doi: medRxiv preprint Supplementary Material Figure S1 .

. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted November 6, 2020. ; https://doi.org/10.1101/2020.11.04.20224758 doi: medRxiv preprint Figure S2 .

When community prevalence is lower, intervention efficacy follows the same general trends but is reduced for cohorting interventions, particularly for more effective testing strategies.

. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted November 6, 2020. ; https://doi.org/10.1101/2020.11.04.20224758 doi: medRxiv preprint Figure S3 .

When PPE efficacy is lower, intervention and testing efficacy follows the same general trends, but with slightly higher cumulative incidence among staff.

. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted November 6, 2020. ; https://doi.org/10.1101/2020.11.04.20224758 doi: medRxiv preprint Figure S4 .

. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted November 6, 2020. ; https://doi.org/10.1101/2020.11.04.20224758 doi: medRxiv preprint Figure S5 .

When the ratio of staff to residents is decreased, intervention efficacy does not change.

. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

The copyright holder for this preprint this version posted November 6, 2020. ; https://doi.org/10.1101/2020.11.04.20224758 doi: medRxiv preprint Figure S6 .

When infectiousness begins as soon as VL is detectable, and is not related to VL, we do not see a change in the relative efficacy of our staffing and resident cohorting interventions, although testing is less effective overall.

. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

The copyright holder for this preprint this version posted November 6, 2020. ; https://doi.org/10.1101/2020.11.04.20224758 doi: medRxiv preprint Daily contacts residents -staff 6 10

Daily contacts staff -residents 6, 12 10 Daily contacts residents -residents (non roommates) 0, 2 10 Proportion of staff asymptomatic 0.4 8 Proportion of residents asymptomatic 0.2 7,20

Duration of presymptomatic transmission (days) 2 12, 13 Reduction in force of infection per contact from PPE 95%, 21 25%

Proportion of temporary healthcare workers recovered upon entry into nursing home 0.2 . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

The copyright holder for this preprint this version posted November 6, 2020. . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

The copyright holder for this preprint this version posted November 6, 2020. ; https://doi.org/10.1101/2020.11.04.20224758 doi: medRxiv preprint

Nursing Homes Are Ground Zero for COVID-19 Pandemic

COVID-19 risk factors vary for nursing home staff, residents

The New York Times. About 40% of U.S. Coronavirus Deaths Are Linked to Nursing Homes. The New York Times

Increased risk of SARS-CoV-2 infection in staff working across different care homes enchanced CoVID-19 outbreak investigations in London care Homes

Mortality Rates From COVID-19 Are Lower In Unionized Nursing Homes. Health Aff

Prevalence of Asymptomatic SARS-CoV-2 Infection : A Narrative Review

Viral dynamics of SARS-CoV-2 infection and the predictive value of repeat testing. medRxiv

Chief Clinical Officer, Chelsea Jewish Life Care

Test sensitivity is secondary to frequency and turnaround time for COVID-19 surveillance. medRxiv

Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia

SARS-CoV-2 (COVID-19) by the numbers

Comparison of viral levels in individuals with or without symptoms at time of COVID-19 testing among 32,480 residents and staff of nursing homes and assisted living facilities in Massachusetts. Public and Global Health

Virological assessment of hospitalized patients with COVID-2019

Frequency and accuracy of proactive testing for COVID-19. medRxiv

Frequency of Routine Testing for Coronavirus Disease 2019 (COVID-19) in High-risk Healthcare Environments to Reduce Outbreaks

Influenza A Virus Shedding and Infectivity in Households

Estimating the extent of asymptomatic COVID-19 and its potential for community transmission: systematic review and meta-analysis. medRxiv

Sourcing Personal Protective Equipment During the COVID-19 Pandemic

Shotgun Transcriptome and Isothermal Profiling of SARS-CoV-2 Infection Reveals Unique Host Responses, Viral Diversification, and Drug Interactions. bioRxiv

A colorimetric RT-LAMP assay and LAMPsequencing for detecting SARS-CoV-2 RNA in clinical samples

A community-deployable SARS-CoV-2 screening test using raw saliva with 45 minutes sample-to-results turnaround