Trends in infection incidence and antimicrobial resistance in the US Veterans Affairs Healthcare System: a nationwide retrospective cohort study (2007-22).

BACKGROUND: Antimicrobial resistance poses a major threat to public health. There are few comprehensive nationwide studies that quantify long-term trends in infection incidence and antimicrobial resistance for multiple pathogens. We aimed to analyse trends in inpatient infection incidence and antimicrobial resistance for nine pathogens over the past 15 years across the USA. METHODS: In this US nationwide retrospective cohort study, we analysed clinical microbiology data from electronic health records from all patients admitted to all 138 Veterans Affairs (VA) Medical Centers with acute care wards across the USA from Feb 1, 2007, to March 31, 2022. We quantified inpatient antibiotic use as days of therapy (DOT) per 1000 patient-days and antimicrobial resistance by resistance proportion (proportion of incident isolates identified as resistant) and phenotypic incidence (incidence of infections per 1000 admissions classified as resistant, susceptible, or missing). To analyse trends before the COVID-19 pandemic and during the COVID-19 pandemic, we used generalised estimating equation models and reported average annual percentage changes (AAPC). FINDINGS: We collected 991 527 30-day incident isolates from 507 760 patients in 138 VA Medical Centers and 50 states in the USA. Between Feb 1, 2007, and Dec 31, 2019, infection incidence and antimicrobial resistance declined for many pathogens and pathogen-drug combinations. The proportion of methicillin resistance in Staphylococcus aureus decreased from 57·7% (11 876 of 20 584 incident isolates) to 44·6% (5916 of 13 257) over these 13 years (AAPC -1·8%; 95% CI -2·4 to -1·2; p<0·0001), and vancomycin-resistant Enterococcus faecium infections decreased from 77·8% (2555 of 3285) to 65·1% (893 of 1371; AAPC -1·2%; 95% CI -2·5 to 0·0; p=0·052). Fluoroquinolone resistance declined in both proportion and incidence for most pathogens. These trends correlated with substantial reductions in fluoroquinolone use, from 125 DOT per 1000 patient-days to 20 DOT per 1000 patient-days. Third generation cephalosporin resistance increased steeply in Escherichia coli infections from 6·7% (942 of 14 042) in 2007 to 15·3% (2153 of 14 053) in 2019 (AAPC 8·5%; 95% CI 6·2 to 10·7; p<0·0001). Carbapenem resistance proportion increased in Enterobacter cloacae infections from 1·1% (30 of 2852) in 2007 to 7·3% (212 of 2919) in 2019 (AAPC 19·8%; 95% CI 13·7 to 26·2; p<0·0001), but remained low for Klebsiella pneumoniae and E coli. During the COVID-19 pandemic between Jan 1, 2020, and March 31, 2022, several pathogen-drug combinations increased in both incidence and resistance for hospital-associated infections. For some pathogen-drug combinations, trends in incidence of resistant and susceptible infections were divergent, whereas for other combinations, these trends were in the same direction. INTERPRETATION: Significant reductions in methicillin resistance in S aureus, vancomycin-resistant E faecium, and fluoroquinolone resistance across multiple pathogens suggest that control efforts have had an effect on resistance. The rise in extended-spectrum ß-lactamases-producing Enterobacterales and recent surge in hospital-associated infections emphasise the need for ongoing surveillance and interventions. Our study highlights how coupling the analysis of phenotypic incidence with resistance proportion can enhance interpretation of antimicrobial resistance data. FUNDING: US Centers for Disease Control and Prevention.

Personalizing the empiric treatment of gonorrhea using machine learning models.

Despite the emergence of antimicrobial-resistant (AMR) strains of Neisseria gonorrhoeae, the treatment of gonorrhea remains empiric and according to standardized guidelines, which are informed by the national prevalence of resistant strains. Yet, the prevalence of AMR varies substantially across geographic and demographic groups. We investigated whether data from the national surveillance system of AMR gonorrhea in the US could be used to personalize the empiric treatment of gonorrhea. We used data from the Gonococcal Isolate Surveillance Project collected between 2000-2010 to train and validate machine learning models to identify resistance to ciprofloxacin (CIP), one of the recommended first-line antibiotics until 2007. We used these models to personalize empiric treatments based on sexual behavior and geographic location and compared their performance with standardized guidelines, which recommended treatment with CIP, ceftriaxone (CRO), or cefixime (CFX) between 2005-2006, and either CRO or CFX between 2007-2010. Compared with standardized guidelines, the personalized treatments could have replaced 33% of CRO and CFX use with CIP while ensuring that 98% of patients were prescribed effective treatment during 2005-2010. The models maintained their performance over time and across geographic regions. Predictive models trained on data from national surveillance systems of AMR gonorrhea could be used to personalize the empiric treatment of gonorrhea based on patients' basic characteristics at the point of care. This approach could reduce the unnecessary use of newer antibiotics while maintaining the effectiveness of first-line therapy.

Assessing thresholds of resistance prevalence at which empiric treatment of gonorrhea should change among men who have sex with men in the US: A cost-effectiveness analysis.

BACKGROUND: Since common diagnostic tests for gonorrhea do not provide information about susceptibility to antibiotics, treatment of gonorrhea remains empiric. Antibiotics used for empiric therapy are usually changed once resistance prevalence exceeds a certain threshold (e.g., 5%). A low switch threshold is intended to increase the probability that an infection is successfully treated with the first-line antibiotic, but it could also increase the pace at which recommendations are switched to newer antibiotics. Little is known about the impact of changing the switch threshold on the incidence of gonorrhea, the rate of treatment failure, and the overall cost and quality-adjusted life-years (QALYs) associated with gonorrhea. METHODS AND FINDINGS: We developed a transmission model of gonococcal infection with multiple resistant strains to project gonorrhea-associated costs and loss in QALYs under different switch thresholds among men who have sex with men (MSM) in the United States. We accounted for the costs and disutilities associated with symptoms, diagnosis, treatment, and sequelae, and combined costs and QALYs in a measure of net health benefit (NHB). Our results suggest that under a scenario where 3 antibiotics are available over the next 50 years (2 suitable for the first-line therapy of gonorrhea and 1 suitable only for the retreatment of resistant infections), changing the switch threshold between 1% and 10% does not meaningfully impact the annual number of gonorrhea cases, total costs, or total QALY losses associated with gonorrhea. However, if a new antibiotic is to become available in the future, choosing a lower switch threshold could improve the population NHB. If in addition, drug-susceptibility testing (DST) is available to inform retreatment regimens after unsuccessful first-line therapy, setting the switch threshold at 1% to 2% is expected to maximize the population NHB. A limitation of our study is that our analysis only focuses on the MSM population and does not consider the influence of interventions such as vaccine and common use of rapid drugs susceptibility tests to inform first-line therapy. CONCLUSIONS: Changing the switch threshold for first-line antibiotics may not substantially change the health and financial outcomes associated with gonorrhea. However, the switch threshold could be reduced when newer antibiotics are expected to become available soon or when in addition to future novel antibiotics, DST is also available to inform retreatment regimens.

Infectious disease surveillance needs for the United States: lessons from Covid-19.

The COVID-19 pandemic has highlighted the need to upgrade systems for infectious disease surveillance and forecasting and modeling of the spread of infection, both of which inform evidence-based public health guidance and policies. Here, we discuss requirements for an effective surveillance system to support decision making during a pandemic, drawing on the lessons of COVID-19 in the U.S., while looking to jurisdictions in the U.S. and beyond to learn lessons about the value of specific data types. In this report, we define the range of decisions for which surveillance data are required, the data elements needed to inform these decisions and to calibrate inputs and outputs of transmission-dynamic models, and the types of data needed to inform decisions by state, territorial, local, and tribal health authorities. We define actions needed to ensure that such data will be available and consider the contribution of such efforts to improving health equity.

Molecular surveillance to monitor the prevalence of tetracycline resistance in Neisseria gonorrhoeae.

Doxycycline post-exposure prophylaxis (Doxy-PEP) reduces bacterial sexually transmitted infections (STIs) but may select for tetracycline resistance in Neisseria gonorrhoeae and co-resistance to other antibiotics, including ceftriaxone.. The implementation of doxy-PEP should be accompanied by monitoring doxycycline resistance, but the optimal strategy to detect changes in the prevalence of resistance has not been established. We used a deterministic compartmental model of gonorrhea transmission to evaluate the performance of two strategies in providing early warning signals for rising resistance: (1) phenotypic testing of cultured isolates and (2) PCR for tetM in remnants from positive Nucleic Acid Amplification Tests (NAATs) used for gonorrhea diagnosis. For each strategy, we calculated the resistance proportion with 90% simulation intervals as well as the time under each sampling strategy to achieve 95% confidence that the resistance proportion exceeded a resistance threshold ranging from 11-30%. Given the substantially larger available sample size, PCR for tetM in remnant NAATs detected increased high-level tetracycline resistance with high confidence faster than phenotypic testing of cultured specimens. Our results suggest that population surveillance using molecular testing for tetM can complement culturebased surveillance of tetracycline resistance in N. gonorrhoeae and inform policy considerations for doxy-PEP.

Assessment of sewer connectivity in the United States and its implications for equity in wastewater-based epidemiology.

Wastewater-based epidemiology is a promising public health tool that can yield a more representative view of the population than case reporting. However, only about 80% of the U.S. population is connected to public sewers, and the characteristics of populations missed by wastewater-based epidemiology are unclear. To address this gap, we used publicly available datasets to assess sewer connectivity in the U.S. by location, demographic groups, and economic groups. Data from the U.S. Census' American Housing Survey revealed that sewer connectivity was lower than average when the head of household was American Indian and Alaskan Native, White, non-Hispanic, older, and for larger households and those with higher income, but smaller geographic scales revealed local variations from this national connectivity pattern. For example, data from the U.S. Environmental Protection Agency showed that sewer connectivity was positively correlated with income in Minnesota, Florida, and California. Data from the U.S. Census' American Community Survey and Environmental Protection Agency also revealed geographic areas with low sewer connectivity, such as Alaska, the Navajo Nation, Minnesota, Michigan, and Florida. However, with the exception of the U.S. Census data, there were inconsistencies across datasets. Using mathematical modeling to assess the impact of wastewater sampling inequities on inferences about epidemic trajectory at a local scale, we found that in some situations, even weak connections between communities may allow wastewater monitoring in one community to serve as a reliable proxy for an interacting community with no wastewater monitoring, when cases are widespread. A systematic, rigorous assessment of sewer connectivity will be important for ensuring an equitable and informed implementation of wastewater-based epidemiology as a public health monitoring system.

Drivers of Geographic Patterns in Outpatient Antibiotic Prescribing in the United States.

In a retrospective, ecological analysis of US medical claims, visit rates explained more of the geographic variation in outpatient antibiotic prescribing rates than per-visit prescribing. Efforts to reduce antibiotic use may benefit from addressing the factors that drive higher rates of outpatient visits, in addition to continued focus on stewardship.

Low antibody levels associated with significantly increased rate of SARS-CoV-2 infection in a highly vaccinated population from the US National Basketball Association.

SARS-CoV-2 antibody levels may serve as a correlate for immunity and could inform optimal booster timing. The relationship between antibody levels and protection from infection was evaluated in vaccinated individuals from the US National Basketball Association who had antibody levels measured at a single time point from September 12, 2021, to December 31, 2021. Cox proportional hazards models were used to estimate the risk of infection within 90 days of serologic testing by antibody level (<250, 250-800, and >800 AU/mL1 ), adjusting for age, time since last vaccine dose, and history of SARS-CoV-2 infection. Individuals were censored on date of booster receipt. The analytic cohort comprised 2323 individuals and was 78.2% male, 68.1% aged ≤40 years, and 56.4% vaccinated (primary series) with the Pfizer-BioNTech mRNA vaccine. Among the 2248 (96.8%) individuals not yet boosted at antibody testing, 77% completed their primary vaccine series 4-6 months before testing and the median (interquartile range) antibody level was 293.5 (interquartile range: 121.0-740.5) AU/mL. Those with levels <250 AU/mL (adj hazard ratio [HR]: 2.4; 95% confidence interval [CI]: 1.5-3.7) and 250-800 AU/mL (adj HR: 1.5; 95% CI: 0.98-2.4) had greater infection risk compared to those with levels >800 AU/mL. Antibody levels could inform individual COVID-19 risk and booster scheduling.

Evidence-based Decision Making: Infectious Disease Modeling Training for Policymakers in East Africa.

Background: Mathematical modeling of infectious diseases is an important decision-making tool for outbreak control. However, in Africa, limited expertise reduces the use and impact of these tools on policy. Therefore, there is a need to build capacity in Africa for the use of mathematical modeling to inform policy. Here we describe our experience implementing a mathematical modeling training program for public health professionals in East Africa. Methods: We used a deliverable-driven and learning-by-doing model to introduce trainees to the mathematical modeling of infectious diseases. The training comprised two two-week in-person sessions and a practicum where trainees received intensive mentorship. Trainees evaluated the content and structure of the course at the end of each week, and this feedback informed the strategy for subsequent weeks. Findings: Out of 875 applications from 38 countries, we selected ten trainees from three countries - Rwanda (6), Kenya (2), and Uganda (2) - with guidance from an advisory committee. Nine trainees were based at government institutions and one at an academic organization. Participants gained skills in developing models to answer questions of interest and critically appraising modeling studies. At the end of the training, trainees prepared policy briefs summarizing their modeling study findings. These were presented at a dissemination event to policymakers, researchers, and program managers. All trainees indicated they would recommend the course to colleagues and rated the quality of the training with a median score of 9/10. Conclusions: Mathematical modeling training programs for public health professionals in Africa can be an effective tool for research capacity building and policy support to mitigate infectious disease burden and forecast resources. Overall, the course was successful, owing to a combination of factors, including institutional support, trainees' commitment, intensive mentorship, a diverse trainee pool, and regular evaluations.

Spatiotemporal Trends in Group A Streptococcal Pharyngitis in the United States.

BACKGROUND: Group A Streptococcus (GAS) causes an estimated 5.2 million outpatient visits for pharyngitis annually in the United States, with incidence peaking in winter, but the annual spatiotemporal pattern of GAS pharyngitis across the United States is poorly characterized. METHODS: We used outpatient claims data from individuals with private medical insurance between 2010 and 2018 to quantify GAS pharyngitis visit rates across U.S. census regions, subregions, and states. We evaluated seasonal and age-based patterns of geographic spread and the association between school start dates and the summertime upward inflection in GAS visits. RESULTS: The South had the most visits per person (yearly average, 39.11 visits per 1000 people; 95% confidence interval, 36.21-42.01) and the West had the fewest (yearly average, 17.63 visits per 1000 people; 95% confidence interval, 16.76-18.49). Visits increased earliest in the South and in school-age children. Differences in visits between the South and other regions were most pronounced in the late summer through early winter. Visits peaked earliest in central southern states, in December to January, and latest on the coasts, in March. The onset of the rise in GAS pharyngitis visits correlated with, but preceded, average school start times. CONCLUSIONS: The burden and timing of GAS pharyngitis varied across the continental United States, with the South experiencing the highest overall rates and earliest onset and peak in outpatient visits. Understanding the drivers of these regional differences in GAS pharyngitis will help in identifying and targeting prevention measures.

Optimal environmental testing frequency for outbreak surveillance.

Public health surveillance for pathogens presents an optimization problem: we require enough sampling to identify intervention-triggering shifts in pathogen epidemiology, such as new introductions or sudden increases in prevalence, but not so much that costs due to surveillance itself outweigh those from pathogen-associated illness. To determine this optimal sampling frequency, we developed a general mathematical model for the introduction of a new pathogen that, once introduced, increases in prevalence exponentially. Given the relative cost of infection vs. sampling, we derived equations for the expected combined cost per unit time of disease burden and surveillance for a specified sampling frequency, and thus the sampling frequency for which the expected total cost per unit time is lowest.

Clinical Risk and Outpatient Therapy Utilization for COVID-19 in the Medicare Population.

Importance: Multiple therapies are available for outpatient treatment of COVID-19 that are highly effective at preventing hospitalization and mortality. Although racial and socioeconomic disparities in use of these therapies have been documented, limited evidence exists on what factors explain differences in use and the potential public health relevance of these differences. Objective: To assess COVID-19 outpatient treatment utilization in the Medicare population and simulate the potential outcome of allocating treatment according to patient risk for severe COVID-19. Design, Setting, and Participants: This cross-sectional study included patients enrolled in Medicare in 2022 across the US, identified with 100% Medicare fee-for-service claims. Main Outcomes and Measures: The primary outcome was any COVID-19 outpatient therapy utilization. Secondary outcomes included COVID-19 testing, ambulatory visits, and hospitalization. Differences in outcomes were estimated based on patient demographics, treatment contraindications, and a composite risk score for mortality after COVID-19 based on demographics and comorbidities. A simulation of reallocating COVID-19 treatment, particularly with nirmatrelvir, to those at high risk of severe disease was performed, and the potential COVID-19 hospitalizations and mortality outcomes were assessed. Results: In 2022, 6.0% of 20 026 910 beneficiaries received outpatient COVID-19 treatment, 40.5% of which had no associated COVID-19 diagnosis within 10 days. Patients with higher risk for severe disease received less outpatient treatment, such as 6.4% of those aged 65 to 69 years compared with 4.9% of those 90 years and older (adjusted odds ratio [aOR], 0.64 [95% CI, 0.62-0.65]) and 6.4% of White patients compared with 3.0% of Black patients (aOR, 0.56 [95% CI, 0.54-0.58]). In the highest COVID-19 severity risk quintile, 2.6% were hospitalized for COVID-19 and 4.9% received outpatient treatment, compared with 0.2% and 7.5% in the lowest quintile. These patterns were similar among patients with a documented COVID-19 diagnosis, those with no claims for vaccination, and patients who are insured with Medicare Advantage. Differences were not explained by variable COVID-19 testing, ambulatory visits, or treatment contraindications. Reallocation of 2022 outpatient COVID-19 treatment, particularly with nirmatrelvir, based on risk for severe COVID-19 would have averted 16 503 COVID-19 deaths (16.3%) in the sample. Conclusion: In this cross-sectional study, outpatient COVID-19 treatment was disproportionately accessed by beneficiaries at lower risk for severe infection, undermining its potential public health benefit. Undertreatment was not driven by lack of clinical access or treatment contraindications.

The Impact of Rapid Drug Susceptibility Tests on Gonorrhea Burden and the Life Span of Antibiotic Treatments: A Modeling Study Among Men Who Have Sex With Men in the United States.

Rapid point-of-care tests that diagnose gonococcal infections and identify susceptibility to antibiotics enable individualized treatment. This could improve patient outcomes and slow the emergence and spread of antibiotic resistance. However, little is known about the long-term impact of such diagnostics on the burden of gonorrhea and the effective life span of antibiotics. We used a mathematical model of gonorrhea transmission among men who have sex with men in the United States to project the annual rate of reported gonorrhea cases and the effective life span of ceftriaxone, the recommended antibiotic for first-line treatment of gonorrhea, as well as 2 previously recommended antibiotics, ciprofloxacin and tetracycline, when a rapid drug susceptibility test that estimates susceptibility to ciprofloxacin and tetracycline is available. The use of a rapid drug susceptibility test with ≥50% sensitivity and ≥95% specificity, defined in terms of correct ascertainment of drug susceptibility and nonsusceptibility status, could increase the combined effective life span of ciprofloxacin, tetracycline, and ceftriaxone by at least 2 years over 25 years of simulation. If test specificity is imperfect, however, the increase in the effective life span of antibiotics is accompanied by an increase in the rate of reported gonorrhea cases even under perfect sensitivity.

Spatiotemporal Trends in Group A Streptococcal Pharyngitis in the United States.

Background: Group A Streptococcus (GAS) causes an estimated 5.2 million outpatient visits for pharyngitis annually in the United States (U.S.) with incidence peaking in winter, but the annual spatiotemporal pattern of GAS pharyngitis across the U.S. is poorly characterized. Methods: We used outpatient claims data from individuals with private medical insurance between 2010-2018 to quantify GAS pharyngitis visit rates across U.S. census regions, subregions, and states. We evaluated seasonal and age-based patterns of geographic spread and the association between school start dates and the summertime upward inflection in GAS visits. Results: The South had the most visits per person (yearly average 39.11 visits per 1000 people, 95% CI: 36.21-42.01), and the West had the fewest (yearly average 17.63 visits per 1000 people, 95% CI: 16.76-18.49). Visits increased earliest in the South and in school-age children. Differences in visits between the South and other regions were most pronounced in the late summer through early winter. Visits peaked earliest in central southern states, in December to January, and latest on the coasts, in March. The onset of the rise in GAS pharyngitis visits correlated with, but preceded, average school start times. Conclusions: The burden and timing of GAS pharyngitis varied across the continental U.S., with the South experiencing the highest overall rates and earliest onset and peak in outpatient visits. Understanding the drivers of these regional differences in GAS pharyngitis will help in identifying and targeting prevention measures.

Estimating changes in antibiotic consumption with the introduction of doxycycline post-exposure prophylaxis in the United States.

Doxycycline as post-exposure prophylaxis (doxy-PEP) reduces the risk of gonorrhea, chlamydia, and syphilis in studies of men who have sex with men (MSM) and transgender women (TGW) on HIV Pre-exposure Prophylaxis (PrEP) and people living with HIV (PLWH)). Doxy-PEP is an important tool to address the increasing burden of sexually transmitted infections (STIs), but there is concern that increased consumption of doxycycline may drive antimicrobial resistance. We estimated the expected increase in antibiotic use in the US under several doxy-PEP prescribing scenarios. We accounted for doses of antibiotics that may be averted due to the prevention of chlamydia, gonorrhea, and syphilis infections by doxy-PEP. Under a scenario of 75% adoption among the eligible population, with rates of consumption similar to the DoxyPEP trial population, monthly antibiotic consumption would increase by around 2.52 million doses, driven by doxy-PEP consumption of 2.58 million doses and less 62.1 thousand antibiotic doses that would otherwise have been used for chlamydia, gonorrhea, and syphilis treatment.

Bayesian modeling of the impact of antibiotic resistance on the efficiency of MRSA decolonization.

Methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of morbidity and mortality. Colonization by MRSA increases the risk of infection and transmission, underscoring the importance of decolonization efforts. However, success of these decolonization protocols varies, raising the possibility that some MRSA strains may be more persistent than others. Here, we studied how the persistence of MRSA colonization correlates with genomic presence of antibiotic resistance genes. Our analysis using a Bayesian mixed effects survival model found that genetic determinants of high-level resistance to mupirocin was strongly associated with failure of the decolonization protocol. However, we did not see a similar effect with genetic resistance to chlorhexidine or other antibiotics. Including strain-specific random effects improved the predictive performance, indicating that some strain characteristics other than resistance also contributed to persistence. Study subject-specific random effects did not improve the model. Our results highlight the need to consider the properties of the colonizing MRSA strain when deciding which treatments to include in the decolonization protocol.

Viral kinetics of sequential SARS-CoV-2 infections.

The impact of a prior SARS-CoV-2 infection on the progression of subsequent infections has been unclear. Using a convenience sample of 94,812 longitudinal RT-qPCR measurements from anterior nares and oropharyngeal swabs, we identified 71 individuals with two well-sampled SARS-CoV-2 infections between March 11th, 2020, and July 28th, 2022. We compared the SARS-CoV-2 viral kinetics of first vs. second infections in this group, adjusting for viral variant, vaccination status, and age. Relative to first infections, second infections usually featured a faster clearance time. Furthermore, a person's relative (rank-order) viral clearance time, compared to others infected with the same variant, was roughly conserved across first and second infections, so that individuals who had a relatively fast clearance time in their first infection also tended to have a relatively fast clearance time in their second infection (Spearman correlation coefficient: 0.30, 95% credible interval (0.12, 0.46)). These findings provide evidence that, like vaccination, immunity from a prior SARS-CoV-2 infection shortens the duration of subsequent acute SARS-CoV-2 infections principally by reducing viral clearance time. Additionally, there appears to be an inherent element of the immune response, or some other host factor, that shapes a person's relative ability to clear SARS-CoV-2 infection that persists across sequential infections.

The "Bubble": What Can Be Learned from the National Basketball Association (NBA)'s 2019-20 Season Restart in Orlando during the COVID-19 Pandemic.

BACKGROUND: The National Basketball Association (NBA) suspended operations in response to the COVID-19 pandemic in March 2020. To safely complete the 2019-20 season, the NBA created a closed campus in Orlando, Florida, known as the NBA "Bubble." More than 5000 individuals lived, worked, and played basketball at a time of high local prevalence of SARS-CoV-2. METHODS: Stringent protocols governed campus life to protect NBA and support personnel from contracting COVID-19. Participants quarantined before departure and upon arrival. Medical and social protocols required that participants remain on campus, test regularly, physically distance, mask, use hand hygiene, and more. Cleaning, disinfection, and air filtration was enhanced. Campus residents were screened daily and confirmed cases of COVID-19 were investigated. RESULTS: In the Bubble population, 148 043 COVID-19 reverse transcriptase PCR (RT-PCR) tests were performed across approximately 5000 individuals; Orlando had a 4% to 15% test positivity rate in this timeframe. There were 44 COVID-19 cases diagnosed either among persons during arrival quarantine or in non-team personnel while working on campus after testing but before receipt of a positive result. No cases of COVID-19 were identified among NBA players or NBA team staff living in the Bubble once cleared from quarantine. CONCLUSIONS: Drivers of success included the requirement for players and team staff to reside and remain on campus, well-trained compliance monitors, unified communication, layers of protection between teams and the outside, activation of high-quality laboratory diagnostics, and available mental health services. An emphasis on data management, evidence-based decision-making, and the willingness to evolve protocols were instrumental to successful operations. These lessons hold broad applicability for future pandemic preparedness efforts.