American Journal of Infection Control

BackgroundImplementation strategies are dynamic techniques used to apply evidence-based practices (EBPs) to diverse contexts. Despite their importance, context-specific selection and modification of implementation strategies remain underreported, limiting understanding of how to optimize strategy deployment across heterogeneous healthcare settings. We describe a systematic method to document and analyze modifications to implementation strategies using four diverse hospital sites from the Fluoroquinolone Restriction for the Prevention of Clostridioides difficile infection (FIRST) trial as case studies. MethodsFIRST was a multisite fluoroquinolone pre-prescription restriction intervention delivered via the electronic health record. We partnered with multidisciplinary stakeholders at each site to co-design and adapt the intervention using pre-planned implementation strategies. Multiple data sources (interviews, meeting notes, implementation diaries) collected iteratively over two years were analyzed to identify strategy modifications. Strategies were coded using Expert Recommendations for Implementing Change (ERIC) conceptual clusters, and modifications were documented using the Framework for Reporting Adaptations and Modifications to Evidence-Based Implementation Strategies (FRAME-IS). Modified strategies were categorized as planned or unplanned and contextualized via thematic content analysis. ResultsAcross 458 total modifications, the most modified strategies focused on facilitating stakeholder engagement, adapting to local contexts, and using evaluative approaches to improve EBP uptake/sustainment. Planned modifications (n=330, 72%) outnumbered unplanned modifications (n=157, 34%). Rural and community hospitals required more unplanned modifications (average 41 vs. 31 for academic centers), while sites with prior restrictive intervention experience had higher planned-to-unplanned ratios (3.1:1 vs. 1.6:1). Academic hospitals with trainee rotations required ongoing education and higher strategy modifications. All modifications maintained EBP core fidelity. Site-specific patterns organizational characteristics were linked to modification intensity and type, including absorptive capacity, prior experience, relational coordination, rurality, and educational requirements. ConclusionsIntegrating ERIC and FRAME-IS enabled systematic documentation of implementation strategy modifications across diverse settings. Planned:unplanned modification ratios provided novel insights into organizational absorptive capacity and implementation preparedness. Standardized implementation approaches inadequately address critical organizational differences, requiring context-sensitive strategy selection and intensity calibration. This work advances implementation science methodology by demonstrating how systematic modification documentation can inform tailored implementation support. Trial RegistrationClinicalTrials.gov Identifier: NCT03848689

1.ObjectivesTo assess long-term trends in outdoor heat and wildfire smoke exposure at 410 correctional facilities in California from 2000-2023. MethodsWe used ERA5-Land data to calculate daily wet-bulb globe temperature (WBGT) and identified days exceeding the NIOSH 28{degrees}C threshold. Wildfire smoke exposure was estimated using NOAAs Hazard Mapping System (HMS). Temporal trends in daily heat and smoke exposure were modeled using linear regression for each facility. ResultsSmoke-affected days rose statewide from 4.9% (2006-2010) to 12.5% (2019- 2023), with Northern California experiencing the highest burden and steepest increases. Days above 28{degrees}C WBGT increased from 27.3% to 29.8% statewide, with the Central Valley and desert regions showing the highest current burden and coastal areas experiencing the steepest increases. Coastal facilities show emerging heat risks, and some regions--especially the Central Valley and Sierra foothills--face dual exposure to both hazards. ConclusionsCorrectional officers and incarcerated workers face rising environmental risks, with regional variation in exposure. Facilities with concurrent heat and smoke burdens must balance cooling and filtration needs. Resilience planning and occupational protections must evolve to meet facility- and region-specific challenges.

Nursing homes (NH) continue to struggle with COVID-19 morbidity and mortality with older adult residents at greater risk of infection due to proximity to other residents, advanced aging-related chronic illnesses, and contact with staff. While many states have prioritized COVID-19 vaccinations among older adults, vaccinations among NH staff vary. The purpose of this study was to quantify the relationship between nursing home staff vaccination uptake and COVID-19 infections among residents. A zero-inflated Poisson regression model was constructed to predict the weekly number of COVID-19 cases among Missouri nursing home residents using data from the Centers for Medicaid and Medicare Services. A total of 1,124 COVID-19 infections were reported among 504 NH residents between January 1, 2021 and August 22, 2021. After adjusting for number of total residents, resident vaccine rate, staff quality rating, and respective county COVID-19 rate, for every percent increase in nursing home staff vaccine rate the risk of COVID-19 infections significantly decreased by 13% (IRR 0.87, 95% CI 0.81, 0.93). This study identified that NH staff, likely due to greater mobility, are important to prioritize in vaccination efforts to protect themselves and residents of their facilities from COVID-19 infections. Further, the CMS staff ratings were significant predictors of infection as well, which highlight the structural challenges that exist within and outside the context of a highly infectious and deadly pandemic. These results also provide insights to optimizing vaccination roll-out to best protect our communities most vulnerable residents.

BackgroundIn long-term care facilities (LTCFs), close-contact identification often relies on staff recall and monitoring records because residents may be unable to self-report reliably. How these different record-generation processes relate to proximity-based sensor measurements in routine LTCF workflow remain unclear, and how such differences may influence contact-based decision-making in outbreak response is not well understood. MethodsWe conducted a five-day observational study in a Japanese LTCF using ultra-wideband (UWB) indoor positioning. Twenty-seven participants wore UWB tags, including 16 residents and 11 staff members; 10 staff members completed questionnaires. We compared UWB-derived proximity with questionnaire-derived contacts from staff self-report and monitoring-based proxy records, and assessed directional discrepancies under multiple distance-time thresholds. ResultsQuestionnaire-based records and UWB-derived proximity showed different patterns of discrepancy across contact types. Within this facility, resident-related monitoring-based proxy records showed relatively small directional discrepancies, whereas staff self-reports tended to identify additional resident-staff contacts under the baseline threshold ([≤]1.0 m for [≥]15 min). Several alternative thresholds were associated with discrepancies closer to zero than the baseline, although the apparent ranking varied by summary metric. ConclusionsIn this single-facility observational study, different contact-list generation processes were associated with different patterns of discrepancy relative to a proximity-based operational measure. These findings support interpretation in terms of workflow-specific contact-list generation rather than a single universally optimal threshold and may help inform facility-level review of contact identification practices in LTCFs. These findings support aligning contact identification strategies with facility-specific workflows to improve the feasibility and effectiveness of IPC practices in LTCFs.

BackgroundThe spread of Coronavirus Disease 2019 (COVID-19) across the United States confirms that not all Americans are equally at risk of infection, severe disease, or mortality. A range of intersecting biological, demographic, and socioeconomic factors are likely to determine an individuals susceptibility to COVID-19. These factors vary significantly across counties in the United States, and often reflect the structural inequities in our society. Recognizing this vast inter-county variation in risks will be critical to mounting an adequate response strategy. Methods and FindingsUsing publicly available county-specific data we identified key biological, demographic, and socioeconomic factors influencing susceptibility to COVID-19, guided by international experiences and consideration of epidemiological parameters of importance. We created bivariate county-level maps to summarize examples of key relationships across these categories, grouping age and poverty; comorbidities and lack of health insurance; proximity, density and bed capacity; and race and ethnicity, and premature death. We have also made available an interactive online tool that allows public health officials to query risk factors most relevant to their local context. Our data demonstrate significant inter-county variation in key epidemiological risk factors, with a clustering of counties in certain states, which will result in an increased demand on their public health system. While the East and West coast cities are particularly vulnerable owing to their densities (and travel routes), a large number of counties in the Southeastern states have a high proportion of at-risk populations, with high levels of poverty, comorbidities, and premature death at baseline, and low levels of health insurance coverage. The list of variables we have examined is by no means comprehensive, and several of them are interrelated and magnify underlying vulnerabilities. The online tool allows readers to explore additional combinations of risk factors, set categorical thresholds for each covariate, and filter counties above different population thresholds. ConclusionCOVID-19 responses and decision making in the United States remain decentralized. Both the federal and state governments will benefit from recognizing high intra-state, inter-county variation in population risks and response capacity. Many of the factors that are likely to exacerbate the burden of COVID-19 and the demand on healthcare systems are the compounded result of long-standing structural inequalities in US society. Strategies to protect those in the most vulnerable counties will require urgent measures to better support communities attempts at social distancing and to accelerate cooperation across jurisdictions to supply personnel and equipment to counties that will experience high demand.

BackgroundHealthcare-associated infections (HAIs) constitute a significant financial strain on healthcare systems across the world, with surgical site infections (SSIs) being the costliest form. Despite the existence of diverse sources of infection in the operating room (OR), current literature focuses on human and procedural sources of contamination that could lead to an infection. Comparatively, the OR built environment is understudied as a potential disease transmission interface between the environment, patients, and surgical staff. This systematic literature review aims to investigate how the physical characteristics and components of the built environment impact airflow, infection risk, aerosols, particle counts, contamination, and pathogens in operating rooms. Methods and FindingsLiterature searches were conducted in the PubMed and Web of Science Core Collection databases on December 21, 2020, ultimately retrieving 2,965 articles after duplicates were removed. During abstract screening, all abstracts were independently reviewed by two authors and conflicts were resolved by a third author. All articles published since January 1, 2010, that reported primary data investigating an aspect of the built environment inside an OR in relation to airflow, contamination, and/or infection for which the full text in English was available were included. This resulted in the inclusion of 138 articles, which includes studies conducted in ORs during active surgeries, computer modeling studies, and simulations in which a real OR was used for a mock surgical procedure. Six major built environment categories were identified based on the collected literature: OR layout, disinfection systems, surgical lights, doors, ventilation, and portable airflow devices. A survey created on Qualtrics software was used to record the aspect of the built environment and the outcome of each study, as well as the relationship between the two. ConclusionsWhile OR ventilation has been studied extensively, the OR built environment as a whole is understudied in relation to airflow, contamination, and infection. The current literature is inconsistent in both its findings and subsequent recommendations, making it difficult to inform hospital design in the context of SSIs. No articles were identified that discussed respiratory infection transmission in the OR, and very few addressed healthcare worker (HCW) safety in relation to the OR built environment. The significant discrepancies in the literature identified in this review highlight the need for future studies that assess the quality and bias of these studies before firm recommendations can be made. Future work should also focus on addressing the lack information regarding respiratory infection transmission in the OR, especially in the context of HCW safety.

The medical intake process is usually the first clinical interaction that people have after being incarcerated. In many states, the first vital person conducting this assessment is a nurse. In this project, nursing intake forms from Massachusetts jails were analyzed for the offer of 15 different screening and preventative services (e.g., HIV testing). Then, Health Services Administrators (HSAs) at the jails were asked to review and comment on the assessment. The average agreement rate between the project team members and HSAs was 73%. Twelve of the 14 jails had questions about history of HIV or HCV on the nursing intake form. Only 5 facilities discussed PrEP. There is potential to standardize the nursing intake form and therefore medical intake process. This must be done with key stakeholder groups, in particular nurses, to best understand the logistics of the complex medical intake process.

Healthcare linens act as a vector of microbial transmission through use, storage and handling. In this retrospective multi-year, multi-site study, the impact of an infection prevention program, that included an automated silver ion-based antimicrobial laundry treatment, was studied. A composite reduction of 42% in healthcare associated infection (HAI) rates was observed, with the biggest reductions associated with CAUTI and CDI rates. Although further study is needed to better understand the exact contribution of such an intervention towards prevention of HAIs, ionic silver treatment of healthcare textiles may prove to be a useful tool in HAI reduction strategies.

ImportanceThis study presents the first set of estimates of predicted health service utilization and deaths due to COVID-19 by day for the next 4 months for each state in the US. ObjectiveTo determine the extent and timing of deaths and excess demand for hospital services due to COVID-19 in the US. Design, Setting, and ParticipantsThis study used data on confirmed COVID-19 deaths by day from WHO websites and local and national governments; data on hospital capacity and utilization for US states; and observed COVID-19 utilization data from select locations to develop a statistical model forecasting deaths and hospital utilization against capacity by state for the US over the next 4 months. Exposure(s)COVID-19. Main outcome(s) and measure(s)Deaths, bed and ICU occupancy, and ventilator use. ResultsCompared to licensed capacity and average annual occupancy rates, excess demand from COVID-19 at the peak of the pandemic in the second week of April is predicted to be 64,175 (95% UI 7,977 to 251,059) total beds and 17,380 (95% UI 2,432 to 57,955) ICU beds. At the peak of the pandemic, ventilator use is predicted to be 19,481 (95% UI 9,767 to 39,674). The date of peak excess demand by state varies from the second week of April through May. We estimate that there will be a total of 81,114 (95% UI 38,242 to 162,106) deaths from COVID-19 over the next 4 months in the US. Deaths from COVID-19 are estimated to drop below 10 deaths per day between May 31 and June 6. Conclusions and RelevanceIn addition to a large number of deaths from COVID-19, the epidemic in the US will place a load well beyond the current capacity of hospitals to manage, especially for ICU care. These estimates can help inform the development and implementation of strategies to mitigate this gap, including reducing non-COVID-19 demand for services and temporarily increasing system capacity. These are urgently needed given that peak volumes are estimated to be only three weeks away. The estimated excess demand on hospital systems is predicated on the enactment of social distancing measures in all states that have not done so already within the next week and maintenance of these measures throughout the epidemic, emphasizing the importance of implementing, enforcing, and maintaining these measures to mitigate hospital system overload and prevent deaths. Data availability statementA full list of data citations are available by contacting the corresponding author. Funding StatementBill & Melinda Gates Foundation and the State of Washington Key PointsO_ST_ABSQuestionC_ST_ABSAssuming social distancing measures are maintained, what are the forecasted gaps in available health service resources and number of deaths from the COVID-19 pandemic for each state in the United States? FindingsUsing a statistical model, we predict excess demand will be 64,175 (95% UI 7,977 to 251,059) total beds and 17,380 (95% UI 2,432 to 57,955) ICU beds at the peak of COVID-19. Peak ventilator use is predicted to be 19,481 (95% UI 9,767 to 39,674) ventilators. Peak demand will be in the second week of April. We estimate 81,114 (95% UI 38,242 to 162,106) deaths in the United States from COVID-19 over the next 4 months. MeaningEven with social distancing measures enacted and sustained, the peak demand for hospital services due to the COVID-19 pandemic is likely going to exceed capacity substantially. Alongside the implementation and enforcement of social distancing measures, there is an urgent need to develop and implement plans to reduce non-COVID-19 demand for and temporarily increase capacity of health facilities.

Independent senior housing is a high risk setting for COVID-19 and should be prioritized for outbreak investigation and response. During a COVID-19 outbreak in Massachusetts from December 2021 to January 2022, 47% of residents in a 31-unit independent senior housing apartment building in Massachusetts were infected. Residents that had received a booster dose of an mRNA COVID-19 vaccine had a lower attack rate than those who had received two doses. Comprehensive response campaigns that include education, testing, treatment referrals, and vaccination can be effective at reducing morbidity and mortality and preventing future outbreaks.

ObjectiveTo estimate the proportion of patients hospitalized with COVID-19 who undergo dialysis, tracheostomy, and extracorporeal membrane oxygenation (ECMO). DesignA network cohort study. SettingSix databases from the United States containing routinely-collected patient data: HealthVerity, Premier, IQVIA Open Claims, Optum EHR, Optum SES, and VA-OMOP. PatientsPatients hospitalized with a clinical diagnosis or a positive test result for COVID-19. InterventionsDialysis, tracheostomy, and ECMO. Measurements and Main Results240,392 patients hospitalized with COVID-19 were included (22,887 from HealthVerity, 139,971 from IQVIA Open Claims, 29,061 from Optum EHR, 4,336 from OPTUM SES, 36,019 from Premier, and 8,118 from VA-OMOP). Across the six databases, 9,703 (4.04% [95% CI: 3.96% to 4.11%]) patients received dialysis, 1,681 (0.70% [0.67% to 0.73%]) had a tracheostomy, and 398 (0.17% [95% CI: 0.15% to 0.18%]) patients underwent ECMO over the 30 days following hospitalization. Use of ECMO was generally concentrated among patients who were younger, male, and with fewer comorbidities except for obesity. Tracheostomy was used for a similar proportion of patients regardless of age, sex, or comorbidity. While dialysis was used for a similar proportion among younger and older patients, it was more frequent among male patients and among those with chronic kidney disease. ConclusionUse of dialysis among those hospitalized with COVID-19 is high at around 4%. Although less than one percent of patients undergo tracheostomy and ECMO, the absolute numbers of patients who have undergone these interventions is substantial and can be expected to continue grow given the continuing spread of the COVID-19.

One major concern in hospitalized patients is infections with pathogens borne on surfaces, patients, and healthcare workers. Fundamental to controlling nosocomial infections is identifying the sources of pathogens, monitoring the processes responsible for their transmission, and evaluating the efficacy of the procedures employed for restricting their transmission. Here we present a method using the bacteriophage Lambda ({lambda}) to achieve these ends. Defined densities of multiple genetically marked {lambda} phages were inoculated at known hotspots for contamination on high-fidelity mannequins. Healthcare workers (HCWs) then entered a pre-sanitized simulated hospital room and performed a series of patient care tasks on the mannequins. Sampling occurred on the scrubs and hands of the HCWs, as well as previously defined high-touch surfaces in hospital rooms. Following sampling, the rooms were decontaminated using procedures designed and demonstrated to be effective. Following the conclusion of the simulation, the samples were tested for the presence, identity, and densities of these Lambda phages. The data generated enabled the determination of the sources and magnitude of contamination caused by the breakdown of established infection prevention practices by HCW. This technique enabled the standardized tracking of multiple contaminants during a single episode of patient care. While our application of these methods focused on nosocomial infections and the role of HCW behaviors in their spread, these methods could be employed for identifying the sources and sites of microbial contamination in other settings.

COVID-19 has demonstrated the devastating consequences of the rapid spread of an airborne virus in residential aged care. We report the use of CO2-based ventilation assessment to empirically identify potential "super-spreader" zones within an aged care facility, and determine the efficacy of rapidly implemented, inexpensive, risk reduction measures.

ObjectiveTo describe four unique models of implementing Wastewater Based Surveillance (WBS) for SARS-CoV-2 in jails of graduated sizes and differing architectural designs. MethodsThis study summarizes how jails of Cook County (Illinois, average daily population [ADP] 6000), Fulton County (Georgia, ADP 3000, Washington DC (ADP 1600) and Middlesex County (Massachusetts, ADP 875) initiated WBS between 2020 and 2023. ResultsPositive signal for SARS-CoV-2 via WBS can herald new onset of infection in a previously uninfected housing unit of a jail. Challenges in implementing WBS included political will and realized value, funding, understanding of the building architecture, and the need for granularity in the findings. ConclusionsWBS has been effective for detecting outbreaks of SARS-CoV-2 in differing sized jails, both those with dorm-based and cell-based architectural design. Policy implicationsGiven its effectiveness in monitoring SARS-CoV-2, WBS provides a model for population-based surveillance in carceral facilities for future infectious disease outbreaks.

A number of methods for decontaminating disposable filtering face piece respirators have been explored for use in health care settings during epidemics where respirators are in short supply, such as the current Covid-19 pandemic. Heating to temperatures above 65{degrees}C has been shown to successfully inactivate the SARS-CoV-2 virus on various surfaces. Ovens or similar heating devices are likely already widely available in hospitals globally. We did a quantitative fit test on nine models of FFP2 and FFP3 respirators before and after heat treatment in an oven. These included both flat fold and moulded cup styles. All passed the initial fit test, and all but two passed the post-treatment fit test. This study demonstrates that FFP respirators can still retain both filtration efficiency and fit after wear and heat treatment, but that it is necessary to understand the probability for failure of fit after decontamination. Heat shows promise as a simple and effective way of treating FFP respirators. Further evaluation of longer-term wear and disinfection effectiveness of heat treatment should be done before widespread use.

BackgroundPeople who are incarcerated or detained are at a high risk of infection and death due to viruses spread through droplets, including SARS-CoV-2 (COVID-19) and influenza. Increased risk is largely associated with structural and institutional conditions of detainment, including but not limited to congregate settings, poor ventilation, and barriers to accessing care. The lessons learned from managing previous infectious outbreaks can inform preventative measures for future emerging outbreaks. AimsOur project aims to analyze infection prevention and control measures for COVID-19 and influenza in U.S. correctional facilities. MethodsWe searched the PubMed and Embase databases for manuscripts evaluating the effectiveness of influenza or COVID-19 mitigation measures. Then, we reviewed the reference lists from our results to identify manuscripts not captured by the initial search. ResultsOut of the 553 articles initially found, only 28 met the inclusion criteria, with 27 focusing on COVID-19. Two additional studies were added after reviewing reference lists. Effective measures to prevent the spread of both infections included vaccines, testing, de-densification, limiting movement, masks, and contact tracing. ConclusionImproved infrastructure, stakeholder collaboration, and research on sustainable responses are needed to address disproportionate impacts on people who are incarcerated or detained.

Decontamination of N95 respirators has become critical to alleviate PPE shortages for healthcare workers in the current COVID-19 emergency. The factors that are considered for the effective reuse of these masks are the fit, filter efficiency and decontamination/disinfection level both for SARS-CoV2, which is the causative virus for COVID-19, and for other organisms of concern in the hospital environment such as Staphylococcus aureus or Clostridium difficile. The efficacy of inactivation or eradication against various pathogens should be evaluated thoroughly to understand the level of afforded disinfection. Methods commonly used in the sterilization of medical devices such as ionizing radiation, vaporized hydrogen peroxide, and ethylene oxide can provide a high level of disinfection, defined as a 6 log10 reduction, against bacterial spores, considered the most resistant microorganisms. CDC guidance on the decontamination and reuse of N95s also includes the use of moist heat (60{degrees}C, 80% relative humidity, 15-30 min) as a possible recommendation based on literature showing preservation of fit efficiency and inactivation of H1N1 on spiked masks. Here, we explored the efficacy of using moist heat under these conditions as a decontamination method for an N95 respirator (3M 1860S, St. Paul, MN) against various pathogens with different resistance; enveloped RNA viruses, Gram (+/-) bacteria, and non-enveloped viruses.

The COVID-19 pandemic highlighted the lack of understanding around effective public health interventions to curtail the spread of an emerging respiratory virus. Here, we examined the public health approaches implemented by each state to limit the spread and burden of COVID-19. Our analysis revealed that stronger statewide interventions positively correlated with fewer COVID-19 deaths, but some neighboring states with distinct intervention strategies had similar SARS-CoV-2 case trajectories. Additionally, more than two weeks is needed to observe an impact on SARS-CoV-2 cases after an intervention is implemented. These data provide a critical framework to inform future interventions during emerging pandemics.

BackgroundThe 2024 blood culture bottle shortage brought diagnostic resource allocation to the forefront, reflecting persistent, foundational challenges with low-value testing and empiric treatment approaches under clinical uncertainty. ObjectiveTo determine whether a machine learning approach using electronic medical record data can predict bacteremia more effectively than existing systems and practices to guide diagnostic testing and empiric treatment strategies. MethodsIn a retrospective cohort of 101,812 adult emergency department encounters (2015-2025), we first established an idealized cognitive baseline by evaluating physician and generative AI (GPT-5) application of the professional society-endorsed Fabre framework on a validation subset. We then trained an XGBoost model (Cultryx) on the full cohort to predict bacteremia, benchmarking its performance against real-world clinical heuristics (SIRS, Shapiro Rule). ResultsFor the idealized baseline, physicians applying the Fabre framework achieved 95.7% sensitivity, but GPT-5 automation failed to replicate this standard (71.6% sensitivity). In real-world benchmarking, Cultryx outperformed all clinical heuristics (AUROC 0.810). SIRS lacked specificity (41.2%), driving diagnostic overuse, while the Shapiro Rule lacked sensitivity (70.2%), missing ~30% of bacteremia cases. In contrast, when calibrated to a strict 95% sensitivity target, Cultryx achieved the highest culture volume deferral rate (26.2%, deferring ~ 15,872 bottles with predicted negative results) while maintaining a 98.9% negative predictive value. Cultryxscore, a simplified bedside tool, retained a 20.8% deferral rate. ConclusionsMachine learning provides a superior, data-driven alternative to mainstream clinical heuristics for predicting bacteremia. By maximizing culture deferment without compromising pathogen detection, Cultryx can conserve diagnostic resources, reduce unnecessary empiric antibiotic exposure, and systematically elevate patient safety. SummaryCultryx, a machine learning model for blood culture stewardship, outperforms standard clinical heuristics in predicting bacteremia. This approach could reduce culture utilization by over 26% while preserving pathogen detection, conserving diagnostic resources, reducing unnecessary antibiotic exposure, and elevating patient safety.

BackgroundAs the number of suspected and confirmed COVID-19 cases in the US continues to rise, the US surgeon general, Centers for Disease Control and Prevention, and several specialty societies have issued recommendations to consider canceling elective surgeries. However, these recommendations have also faced controversy and opposition. MethodsUsing previously published information and publicly available data on COVID-19 infections, we calculated a transmission rate and generated a mathematical model to predict a lower bound for the number of healthcare-acquired COVID-19 infections that could be prevented by canceling or postponing elective outpatient surgeries in Washington state. ResultsOur model predicts that over the course of 30 days, at least 75.9 preventable patient infections and at least 69.3 preventable healthcare worker (HCW) infections would occur in WA state alone if elective outpatient procedures were to continue as usual. ConclusionCanceling elective outpatient surgeries during the COVID-19 pandemic could prevent a large number of patient and healthcare worker infections.