Reducing Hospitalizations and Multidrug-Resistant Organisms via Regional Decolonization in Hospitals and Nursing Homes.

Importance: Infections due to multidrug-resistant organisms (MDROs) are associated with increased morbidity, mortality, length of hospitalization, and health care costs. Regional interventions may be advantageous in mitigating MDROs and associated infections. Objective: To evaluate whether implementation of a decolonization collaborative is associated with reduced regional MDRO prevalence, incident clinical cultures, infection-related hospitalizations, costs, and deaths. Design, Setting, and Participants: This quality improvement study was conducted from July 1, 2017, to July 31, 2019, across 35 health care facilities in Orange County, California. Exposures: Chlorhexidine bathing and nasal iodophor antisepsis for residents in long-term care and hospitalized patients in contact precautions (CP). Main Outcomes and Measures: Baseline and end of intervention MDRO point prevalence among participating facilities; incident MDRO (nonscreening) clinical cultures among participating and nonparticipating facilities; and infection-related hospitalizations and associated costs and deaths among residents in participating and nonparticipating nursing homes (NHs). Results: Thirty-five facilities (16 hospitals, 16 NHs, 3 long-term acute care hospitals [LTACHs]) adopted the intervention. Comparing decolonization with baseline periods among participating facilities, the mean (SD) MDRO prevalence decreased from 63.9% (12.2%) to 49.9% (11.3%) among NHs, from 80.0% (7.2%) to 53.3% (13.3%) among LTACHs (odds ratio [OR] for NHs and LTACHs, 0.48; 95% CI, 0.40-0.57), and from 64.1% (8.5%) to 55.4% (13.8%) (OR, 0.75; 95% CI, 0.60-0.93) among hospitalized patients in CP. When comparing decolonization with baseline among NHs, the mean (SD) monthly incident MDRO clinical cultures changed from 2.7 (1.9) to 1.7 (1.1) among participating NHs, from 1.7 (1.4) to 1.5 (1.1) among nonparticipating NHs (group × period interaction reduction, 30.4%; 95% CI, 16.4%-42.1%), from 25.5 (18.6) to 25.0 (15.9) among participating hospitals, from 12.5 (10.1) to 14.3 (10.2) among nonparticipating hospitals (group × period interaction reduction, 12.9%; 95% CI, 3.3%-21.5%), and from 14.8 (8.6) to 8.2 (6.1) among LTACHs (all facilities participating; 22.5% reduction; 95% CI, 4.4%-37.1%). For NHs, the rate of infection-related hospitalizations per 1000 resident-days changed from 2.31 during baseline to 1.94 during intervention among participating NHs, and from 1.90 to 2.03 among nonparticipating NHs (group × period interaction reduction, 26.7%; 95% CI, 19.0%-34.5%). Associated hospitalization costs per 1000 resident-days changed from $64 651 to $55 149 among participating NHs and from $55 151 to $59 327 among nonparticipating NHs (group × period interaction reduction, 26.8%; 95% CI, 26.7%-26.9%). Associated hospitalization deaths per 1000 resident-days changed from 0.29 to 0.25 among participating NHs and from 0.23 to 0.24 among nonparticipating NHs (group × period interaction reduction, 23.7%; 95% CI, 4.5%-43.0%). Conclusions and Relevance: A regional collaborative involving universal decolonization in long-term care facilities and targeted decolonization among hospital patients in CP was associated with lower MDRO carriage, infections, hospitalizations, costs, and deaths.

Regional impact of multidrug-resistant organism prevention bundles implemented by facility type: A modeling study.

BACKGROUND: Emerging multidrug-resistant organisms (MDROs), such as carbapenem-resistant Enterobacterales (CRE), can spread rapidly in a region. Facilities that care for high-acuity patients with longer stays may have a disproportionate impact on this spread. OBJECTIVE: We assessed the impact of implementing preventive interventions, directed at a subset of facilities, on regional prevalence. METHODS: We developed a deterministic compartmental model, parametrized using CRE and patient transfer data. The model included the community and healthcare facilities within a US state. Individuals may be either susceptible or infectious with CRE. Individuals determined to be infectious through admission screening, periodic prevalence surveys (PPSs), or interfacility communication were placed in a state of lower transmissibility if enhanced infection prevention and control (IPC) practices were in place at a facility. RESULTS: Intervention bundles that included PPS and enhanced IPC practices at ventilator-capable skilled nursing facilities (vSNFs) and long-term acute-care hospitals (LTACHs) had the greatest impact on regional prevalence. The benefits of including targeted admission screening in acute-care hospitals, LTACHs, and vSNFs, and improved interfacility communication were more modest. Daily transmissions in each facility type were reduced following the implementation of interventions primarily focused at LTACHs and vSNFs. CONCLUSIONS: Our model suggests that interventions that include screening to limit unrecognized MDRO introduction to, or dispersal from, LTACHs and vSNFs slow regional spread. Interventions that pair detection and enhanced IPC practices within LTACHs and vSNFs may substantially reduce the regional burden.

Modeling the impacts of antiviral prophylaxis strategies in mitigating seasonal influenza outbreaks in nursing homes.

BACKGROUND: Antiviral chemoprophylaxis is recommended for use during influenza outbreaks in nursing homes to prevent transmission and severe disease among non-ill residents. Centers for Disease Control and Prevention (CDC) guidance recommends prophylaxis be initiated for all non-ill residents once an influenza outbreak is detected and be continued for at least 14 days and until seven days after the last laboratory-confirmed influenza case is identified. However, not all facilities strictly adhere to this guidance and the impact of such partial adherence is not fully understood. METHODS: We developed a stochastic compartmental framework to model influenza transmission within an average-sized U.S. nursing home. We compared the number of symptomatic illnesses and hospitalizations under varying prophylaxis implementation strategies, in addition to different levels of prophylaxis uptake and adherence by residents and healthcare personnel (HCP). RESULTS: Prophylaxis implemented according to current guidance reduced total symptomatic illnesses and hospitalizations among residents by an average of 12% and 36%, respectively, compared with no prophylaxis. We did not find evidence that alternative implementations of prophylaxis were more effective: compared to full adoption of current guidance, partial adoption resulted in increased symptomatic illnesses and/or hospitalizations, and longer or earlier adoption offered no additional improvements. In addition, increasing uptake and adherence among nursing home residents was effective in reducing resident illnesses and hospitalizations, but increasing HCP uptake had minimal indirect impacts for residents. CONCLUSIONS: The greatest benefits of influenza prophylaxis during nursing home outbreaks will likely be achieved through increasing uptake and adherence among residents and following current CDC guidance.

Public health impact of the U.S. Scenario Modeling Hub.

Beginning in December 2020, the COVID-19 Scenario Modeling Hub has provided quantitative scenario-based projections for cases, hospitalizations, and deaths, aggregated across up to nine modeling groups. Projections spanned multiple months into the future and provided timely information on potential impacts of epidemiological uncertainties and interventions. Projections results were shared with the public, public health partners, and the Centers for Disease Control COVID-19 Response Team. The projections provided insights on situational awareness and informed decision-making to mitigate COVID-19 disease burden (e.g., vaccination strategies). By aggregating projections from multiple modeling teams, the Scenario Modeling Hub provided rapidly synthesized information in times of great uncertainty and conveyed possible trajectories in the presence of emerging variants. Here we detail several use cases of these projections in public health practice and communication, including assessments of whether modeling results directly or indirectly informed public health communication or guidance. These include multiple examples where comparisons of projected COVID-19 disease outcomes under different vaccination scenarios were used to inform Advisory Committee for Immunization Practices recommendations. We also describe challenges and lessons learned during this highly beneficial collaboration.

Distinct Origins and Transmission Pathways of blaKPC Enterobacterales across Three U.S. States.

Carbapenem-resistant Enterobacterales (CRE) are among the most concerning antibiotic resistance threats due to high rates of multidrug resistance, transmissibility in health care settings, and high mortality rates. We evaluated the potential for regional genomic surveillance to track the spread of blaKPC-carrying CRE (KPC-CRE) by using isolate collections from health care facilities in three U.S. states. Clinical isolates were collected from Connecticut (2017 to 2018), Minnesota (2012 to 2018), and Tennessee (2016 to 2017) through the U.S. Centers for Disease Control and Prevention's Multi-site Gram-negative Surveillance Initiative (MuGSI) and additional surveillance. KPC-CRE isolates were whole-genome sequenced, yielding 255 isolates from 214 patients across 96 facilities. Case report data on patient comorbidities, facility exposures, and interfacility patient transfer were extracted. We observed that in Connecticut, most KPC-CRE isolates showed evidence of importation from outside the state, with limited local transmission. In Minnesota, cases were mainly from sporadic importation and transmission of blaKPC-carrying Klebsiella pneumoniae ST258, and clonal expansion of blaKPC-carrying Enterobacter hormaechei ST171, primarily at a single focal facility and its satellite facilities. In Tennessee, we observed transmission of diverse strains of blaKPC-carrying Enterobacter and Klesbiella, with evidence that most derived from the local acquisition of blaKPC plasmids circulating in an interconnected regional health care network. Thus, the underlying processes driving KPC-CRE burden can differ substantially across regions and can be discerned through regional genomic surveillance. This study provides proof of concept that integrating genomic data with information on interfacility patient transfers can provide insights into locations and drivers of regional KPC-CRE burden that can enable targeted interventions.

Accounting for assay performance when estimating the temporal dynamics in SARS-CoV-2 seroprevalence in the U.S.

Reconstructing the incidence of SARS-CoV-2 infection is central to understanding the state of the pandemic. Seroprevalence studies are often used to assess cumulative infections as they can identify asymptomatic infection. Since July 2020, commercial laboratories have conducted nationwide serosurveys for the U.S. CDC. They employed three assays, with different sensitivities and specificities, potentially introducing biases in seroprevalence estimates. Using models, we show that accounting for assays explains some of the observed state-to-state variation in seroprevalence, and when integrating case and death surveillance data, we show that when using the Abbott assay, estimates of proportions infected can differ substantially from seroprevalence estimates. We also found that states with higher proportions infected (before or after vaccination) had lower vaccination coverages, a pattern corroborated using a separate dataset. Finally, to understand vaccination rates relative to the increase in cases, we estimated the proportions of the population that received a vaccine prior to infection.

Assessing Pathogen Transmission Opportunities: Variation in Nursing Home Staff-Resident Interactions.

OBJECTIVES: The Centers for Disease Control and Prevention (CDC) recommends implementing Enhanced Barrier Precautions (EBP) for all nursing home (NH) residents known to be colonized with targeted multidrug-resistant organisms (MDROs), wounds, or medical devices. Differences in health care personnel (HCP) and resident interactions between units may affect risk of acquiring and transmitting MDROs, affecting EBP implementation. We studied HCP-resident interactions across a variety of NHs to characterize MDRO transmission opportunities. DESIGN: 2 cross-sectional visits. SETTING AND PARTICIPANTS: Four CDC Epicenter sites and CDC Emerging Infection Program sites in 7 states recruited NHs with a mix of unit care types (≥30 beds or ≥2 units). HCP were observed providing resident care. METHODS: Room-based observations and HCP interviews assessed HCP-resident interactions, care type provided, and equipment use. Observations and interviews were conducted for 7-8 hours in 3-6-month intervals per unit. Chart reviews collected deidentified resident demographics and MDRO risk factors (eg, indwelling devices, pressure injuries, and antibiotic use). RESULTS: We recruited 25 NHs (49 units) with no loss to follow-up, conducted 2540 room-based observations (total duration: 405 hours), and 924 HCP interviews. HCP averaged 2.5 interactions per resident per hour (long-term care units) to 3.4 per resident per hour (ventilator care units). Nurses provided care to more residents (n = 12) than certified nursing assistants (CNAs) and respiratory therapists (RTs) (CNA: 9.8 and RT: 9) but nurses performed significantly fewer task types per interaction compared to CNAs (incidence rate ratio (IRR): 0.61, P < .05). Short-stay (IRR: 0.89) and ventilator-capable (IRR: 0.94) units had less varied care compared with long-term care units (P < .05), although HCP visited residents in these units at similar rates. CONCLUSIONS AND IMPLICATIONS: Resident-HCP interaction rates are similar across NH unit types, differing primarily in types of care provided. Current and future interventions such as EBP, care bundling, or targeted infection prevention education should consider unit-specific HCP-resident interaction patterns.

Modeling the Effectiveness of Healthcare Personnel Reactive Testing and Screening for the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Omicron Variant Within Nursing Homes.

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Omicron variant has been hypothesized to exhibit faster clearance (time from peak viral concentration to clearance of acute infection), decreased sensitivity of antigen tests, and increased immune escape (the ability of the variant to evade immunity conferred by past infection or vaccination) compared to prior variants. These factors necessitate reevaluation of prevention and control strategies, particularly in high-risk, congregate settings like nursing homes that have been heavily impacted by other coronavirus disease 2019 (COVID-19) variants. We used a simple model representing individual-level viral shedding dynamics to estimate the optimal strategy for testing nursing home healthcare personnel and quantify potential reduction in transmission of COVID-19. This provides a framework for prospectively evaluating testing strategies in emerging variant scenarios when data are limited. We find that case-initiated testing prevents 38% of transmission within a facility if implemented within a day of an index case testing positive, and screening testing strategies could prevent 30% to 78% of transmission within a facility if implemented daily, depending on test sensitivity.

Evaluation of different types of face masks to limit the spread of SARS-CoV-2: a modeling study.

We expanded a published mathematical model of SARS-CoV-2 transmission with complex, age-structured transmission and with laboratory-derived source and wearer protection efficacy estimates for a variety of face masks to estimate their impact on COVID-19 incidence and related mortality in the United States. The model was also improved to allow realistic age-structured transmission with a pre-specified R0 of transmission, and to include more compartments and parameters, e.g. for groups such as detected and undetected asymptomatic infectious cases who mask up at different rates. When masks are used at typically-observed population rates of 80% for those ≥ 65 years and 60% for those < 65 years, face masks are associated with 69% (cloth) to 78% (medical procedure mask) reductions in cumulative COVID-19 infections and 82% (cloth) to 87% (medical procedure mask) reductions in related deaths over a 6-month timeline in the model, assuming a basic reproductive number of 2.5. If cloth or medical procedure masks' source control and wearer protection efficacies are boosted about 30% each to 84% and 60% by cloth over medical procedure masking, fitters, or braces, the COVID-19 basic reproductive number of 2.5 could be reduced to an effective reproductive number ≤ 1.0, and from 6.0 to 2.3 for a variant of concern similar to delta (B.1.617.2). For variants of concern similar to omicron (B.1.1.529) or the sub-lineage BA.2, modeled reductions in effective reproduction number due to similar high quality, high prevalence mask wearing is more modest (to 3.9 and 5.0 from an R0 = 10.0 and 13.0, respectively). None-the-less, the ratio of incident risk for masked vs. non-masked populations still shows a benefit of wearing masks even with the higher R0 variants.

De-escalation of asymptomatic testing and potential of future COVID-19 outbreaks in US nursing homes amidst rising community vaccination coverage: A modeling study.

As of 2 September 2021, United States nursing homes have reported >675,000 COVID-19 cases and >134,000 deaths according to the Centers for Medicare & Medicaid Services (CMS). More than 205,000,000 persons in the United States had received at least one dose of a COVID-19 vaccine (62% of total population) as of 2 September 2021. We investigate the role of vaccination in controlling future COVID-19 outbreaks. We developed a stochastic, compartmental model of SARS-CoV-2 transmission in a 100-bed nursing home with a staff of 99 healthcare personnel (HCP) in a community of 20,000 people. We parameterized admission and discharge of residents in the model with CMS data, for a within-facility basic reproduction number (R0) of 3.5 and a community R0 of 2.5. The model also included: importation of COVID-19 from the community, isolation of SARS-CoV-2 positive residents, facility-wide adherence to personal protective equipment (PPE) use by HCP, and testing. We systematically varied coverage of mRNA vaccine among residents, HCP, and the community. Simulations were run for 6 months after the second dose in the facility, with results summarized over 1,000 simulations. Expected resident cases decreased as community vaccination increased, with large reductions at high HCP coverage. The probability of a COVID-19 outbreak was lower as well: at HCP vaccination coverage of 60%, probability of an outbreak was below 20% for community coverage of 50% or above. At high coverage, stopping asymptomatic screening and facility-wide testing yielded similar results. Results suggest that high coverage among HCP and in the community can prevent infections in residents. When vaccination is high in nursing homes, but not in their surrounding communities, asymptomatic and facility-wide testing remains necessary to prevent the spread of COVID-19. High adherence to PPE may increase the likelihood of containing future COVID-19 outbreaks if they occur.

Modeling strategies for the allocation of SARS-CoV-2 vaccines in the United States.

The Advisory Committee on Immunization Practices (ACIP) recommended phased allocation of SARS-CoV-2 vaccines in December 2020. To support the development of this guidance, we used a mathematical model of SARS-CoV-2 transmission to evaluate the relative impact of three vaccine allocation strategies on infections, hospitalizations, and deaths. All three strategies initially prioritized healthcare personnel (HCP) for vaccination. Strategies of subsequently prioritizing adults aged ≥65 years, or a combination of essential workers and adults aged ≥75 years, prevented the most deaths. Meanwhile, prioritizing adults with high-risk medical conditions immediately after HCP prevented the most infections. All three strategies prevented a similar fraction of hospitalizations. While no model is capable of fully capturing the complex social dynamics which shape epidemics, exercises such as this one can be a useful way for policy makers to formalize their assumptions and explore the key features of a problem before making decisions.

Improving mathematical modeling of interventions to prevent healthcare-associated infections by interrupting transmission or pathogens: How common modeling assumptions about colonized individuals impact intervention effectiveness estimates.

Mathematical models are used to gauge the impact of interventions for healthcare-associated infections. As with any analytic method, such models require many assumptions. Two common assumptions are that asymptomatically colonized individuals are more likely to be hospitalized and that they spend longer in the hospital per admission because of their colonization status. These assumptions have no biological basis and could impact the estimated effects of interventions in unintended ways. Therefore, we developed a model of methicillin-resistant Staphylococcus aureus transmission to explicitly evaluate the impact of these assumptions. We found that assuming that asymptomatically colonized individuals were more likely to be admitted to the hospital or spend longer in the hospital than uncolonized individuals biased results compared to a more realistic model that did not make either assumption. Results were heavily biased when estimating the impact of an intervention that directly reduced transmission in a hospital. In contrast, results were moderately biased when estimating the impact of an intervention that decolonized hospital patients. Our findings can inform choices modelers face when constructing models of healthcare-associated infection interventions and thereby improve their validity.

Modeling the Impact of Vaccination Strategies for Nursing Homes in the Context of Increased Severe Acute Respiratory Syndrome Coronavirus 2 Community Transmission and Variants.

Using an agent-based model, we examined the impact of community prevalence, the Delta variant, staff vaccination coverage, and booster vaccines for residents on outbreak dynamics in nursing homes. Increased staff coverage and high booster vaccine effectiveness leads to fewer infections, but cumulative incidence is highly dependent on community transmission.

Improving Pandemic Response: Employing Mathematical Modeling to Confront Coronavirus Disease 2019.

Modeling complements surveillance data to inform coronavirus disease 2019 (COVID-19) public health decision making and policy development. This includes the use of modeling to improve situational awareness, assess epidemiological characteristics, and inform the evidence base for prevention strategies. To enhance modeling utility in future public health emergencies, the Centers for Disease Control and Prevention (CDC) launched the Infectious Disease Modeling and Analytics Initiative. The initiative objectives are to: (1) strengthen leadership in infectious disease modeling, epidemic forecasting, and advanced analytic work; (2) build and cultivate a community of skilled modeling and analytics practitioners and consumers across CDC; (3) strengthen and support internal and external applied modeling and analytic work; and (4) working with partners, coordinate government-wide advanced data modeling and analytics for infectious diseases. These efforts are critical to help prepare the CDC, the country, and the world to respond effectively to present and future infectious disease threats.

Mathematical Modeling to Inform Vaccination Strategies and Testing Approaches for Coronavirus Disease 2019 (COVID-19) in Nursing Homes.

BACKGROUND: Nursing home residents and staff were included in the first phase of coronavirus disease 2019 vaccination in the United States. Because the primary trial endpoint was vaccine efficacy (VE) against symptomatic disease, there are limited data on the extent to which vaccines protect against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the ability to infect others (infectiousness). Assumptions about VE against infection and infectiousness have implications for changes to infection prevention guidance for vaccinated populations, including testing strategies. METHODS: We use a stochastic agent-based Susceptible-Exposed-Infectious (Asymptomatic/Symptomatic)-Recovered model of a nursing home to simulate SARS-CoV-2 transmission. We model 3 scenarios, varying VE against infection, infectiousness, and symptoms, to understand the expected impact of vaccination in nursing homes, increasing staff vaccination coverage, and different screening testing strategies under each scenario. RESULTS: Increasing vaccination coverage in staff decreases total symptomatic cases in the nursing home (among staff and residents combined) in each VE scenario. In scenarios with 50% and 90% VE against infection and infectiousness, increasing staff coverage reduces symptomatic cases among residents. If vaccination only protects against symptoms, and asymptomatic cases remain infectious, increased staff coverage increases symptomatic cases among residents. However, this is outweighed by the reduction in symptomatic cases among staff. Higher frequency testing-more than once weekly-is needed to reduce total symptomatic cases if the vaccine has lower efficacy against infection and infectiousness, or only protects against symptoms. CONCLUSIONS: Encouraging staff vaccination is not only important for protecting staff, but might also reduce symptomatic cases in residents if a vaccine confers at least some protection against infection or infectiousness.

Cruise Ship Travel in the Era of Coronavirus Disease 2019 (COVID-19): A Summary of Outbreaks and a Model of Public Health Interventions.

BACKGROUND: Cruise travel contributed to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission when there were relatively few cases in the United States. By 14 March 2020, the Centers for Disease Control and Prevention (CDC) issued a No Sail Order suspending US cruise operations; the last US passenger ship docked on 16 April. METHODS: We analyzed SARS-CoV-2 outbreaks on cruises in US waters or carrying US citizens and used regression models to compare voyage characteristics. We used compartmental models to simulate the potential impact of 4 interventions (screening for coronavirus disease 2019 (COVID-19) symptoms; viral testing on 2 days and isolation of positive persons; reduction of passengers by 40%, crew by 20%, and reducing port visits to 1) for 7-day and 14-day voyages. RESULTS: During 19 January to 16 April 2020, 89 voyages on 70 ships had known SARS-CoV-2 outbreaks; 16 ships had recurrent outbreaks. There were 1669 reverse transcription polymerase chain reaction (RT-PCR)-confirmed SARS-CoV-2 infections and 29 confirmed deaths. Longer voyages were associated with more cases (adjusted incidence rate ratio, 1.10, 95% confidence interval [CI]: 1.03-1.17, P < .003). Mathematical models showed that 7-day voyages had about 70% fewer cases than 14-day voyages. On 7-day voyages, the most effective interventions were reducing the number of individuals onboard (43.3% reduction in total infections) and testing passengers and crew (42% reduction in total infections). All four interventions reduced transmission by 80.1%, but no single intervention or combination eliminated transmission. Results were similar for 14-day voyages. CONCLUSIONS: SARS-CoV-2 outbreaks on cruises were common during January-April 2020. Despite all interventions modeled, cruise travel still poses a significant SARS-CoV-2 transmission risk.

Modeling the impact of vaccination strategies for nursing homes in the context of increased SARS-CoV-2 community transmission and variants.

Nursing homes (NH) were among the first settings to receive COVID-19 vaccines in the United States, but staff vaccination coverage remains low at an average of 64%. Using an agent-based model, we examined the impact of community prevalence, the Delta variant, staff vaccination coverage, and boosters for residents on outbreak dynamics in nursing homes. We found that increased staff primary series coverage and high booster vaccine effectiveness (VE) in residents leads to fewer infections and that the cumulative incidence is highly dependent on community transmission. Despite high VE, high community transmission resulted in continued symptomatic infections in NHs.

Genomic Surveillance for SARS-CoV-2 Variants Circulating in the United States, December 2020-May 2021.

SARS-CoV-2, the virus that causes COVID-19, is constantly mutating, leading to new variants (1). Variants have the potential to affect transmission, disease severity, diagnostics, therapeutics, and natural and vaccine-induced immunity. In November 2020, CDC established national surveillance for SARS-CoV-2 variants using genomic sequencing. As of May 6, 2021, sequences from 177,044 SARS-CoV-2-positive specimens collected during December 20, 2020-May 6, 2021, from 55 U.S. jurisdictions had been generated by or reported to CDC. These included 3,275 sequences for the 2-week period ending January 2, 2021, compared with 25,000 sequences for the 2-week period ending April 24, 2021 (0.1% and 3.1% of reported positive SARS-CoV-2 tests, respectively). Because sequences might be generated by multiple laboratories and sequence availability varies both geographically and over time, CDC developed statistical weighting and variance estimation methods to generate population-based estimates of the proportions of identified variants among SARS-CoV-2 infections circulating nationwide and in each of the 10 U.S. Department of Health and Human Services (HHS) geographic regions.* During the 2-week period ending April 24, 2021, the B.1.1.7 and P.1 variants represented an estimated 66.0% and 5.0% of U.S. SARS-CoV-2 infections, respectively, demonstrating the rise to predominance of the B.1.1.7 variant of concern† (VOC) and emergence of the P.1 VOC in the United States. Using SARS-CoV-2 genomic surveillance methods to analyze surveillance data produces timely population-based estimates of the proportions of variants circulating nationally and regionally. Surveillance findings demonstrate the potential for new variants to emerge and become predominant, and the importance of robust genomic surveillance. Along with efforts to characterize the clinical and public health impact of SARS-CoV-2 variants, surveillance can help guide interventions to control the COVID-19 pandemic in the United States.

Mathematical modeling to inform vaccination strategies and testing approaches for COVID-19 in nursing homes.

BACKGROUND: Nursing home residents and staff were included in the first phase of COVID-19 vaccination in the United States. Because the primary trial endpoint was vaccine efficacy (VE) against symptomatic disease, there are limited data on the extent to which vaccines protect against SARS-CoV-2 infection and the ability to infect others (infectiousness). Assumptions about VE against infection and infectiousness have implications for possible changes to infection prevention guidance for vaccinated populations, including testing strategies. METHODS: We use a stochastic agent-based SEIR model of a nursing home to simulate SARS-CoV-2 transmission. We model three scenarios, varying VE against infection, infectiousness, and symptoms, to understand the expected impact of vaccination in nursing homes, increasing staff vaccination coverage, and different screening testing strategies under each scenario. RESULTS: Increasing vaccination coverage in staff decreases total symptomatic cases in each scenario. When there is low VE against infection and infectiousness, increasing staff coverage reduces symptomatic cases among residents. If vaccination only protects against symptoms, but asymptomatic cases remain infectious, increased staff coverage increases symptomatic cases among residents through exposure to asymptomatic but infected staff. High frequency testing is needed to reduce total symptomatic cases if the vaccine has low efficacy against infection and infectiousness, or only protects against symptoms. CONCLUSIONS: Encouraging staff vaccination is not only important for protecting staff, but might also reduce symptomatic cases in residents if a vaccine confers at least some protection against infection or infectiousness. SUMMARY: The extent of efficacy of SARS-CoV-2 vaccines against infection, infectiousness, or disease, impacts strategies for vaccination and testing in nursing homes. If vaccines confer some protection against infection or infectiousness, encouraging vaccination in staff may reduce symptomatic cases in residents.

Modeling Effectiveness of Testing Strategies to Prevent Coronavirus Disease 2019 (COVID-19) in Nursing Homes-United States, 2020.

BACKGROUND: Identifying asymptomatic individuals early through serial testing is recommended to control coronavirus disease 2019 (COVID-19) in nursing homes, both in response to an outbreak ("outbreak testing" of residents and healthcare personnel) and in facilities without outbreaks ("nonoutbreak testing" of healthcare personnel). The effectiveness of outbreak testing and isolation with or without nonoutbreak testing was evaluated. METHODS: Using published SARS-CoV-2 transmission parameters, the fraction of SARS-CoV-2 transmissions prevented through serial testing (weekly, every 3 days, or daily) and isolation of asymptomatic persons compared with symptom-based testing and isolation was evaluated through mathematical modeling using a Reed-Frost model to estimate the percentage of cases prevented (ie, "effectiveness") through either outbreak testing alone or outbreak plus nonoutbreak testing. The potential effect of simultaneous decreases (by 10%) in the effectiveness of isolating infected individuals when instituting testing strategies was also evaluated. RESULTS: Modeling suggests that outbreak testing could prevent 54% (weekly testing with 48-hour test turnaround) to 92% (daily testing with immediate results and 50% relative sensitivity) of SARS-CoV-2 infections. Adding nonoutbreak testing could prevent up to an additional 8% of SARS-CoV-2 infections (depending on test frequency and turnaround time). However, added benefits of nonoutbreak testing were mostly negated if accompanied by decreases in infection control practice. CONCLUSIONS: When combined with high-quality infection control practices, outbreak testing could be an effective approach to preventing COVID-19 in nursing homes, particularly if optimized through increased test frequency and use of tests with rapid turnaround.