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.

Multidrug-Resistant Bacterial Infections in U.S. Hospitalized Patients, 2012-2017.

BACKGROUND: Multidrug-resistant (MDR) bacteria that are commonly associated with health care cause a substantial health burden. Updated national estimates for this group of pathogens are needed to inform public health action. METHODS: Using data from patients hospitalized in a cohort of 890 U.S. hospitals during the period 2012-2017, we generated national case counts for both hospital-onset and community-onset infections caused by methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant enterococcus (VRE), extended-spectrum cephalosporin resistance in Enterobacteriaceae suggestive of extended-spectrum beta-lactamase (ESBL) production, carbapenem-resistant Enterobacteriaceae, carbapenem-resistant acinetobacter species, and MDR Pseudomonas aeruginosa. RESULTS: The hospital cohort in the study accounted for 41.6 million hospitalizations (>20% of U.S. hospitalizations annually). The overall rate of clinical cultures was 292 cultures per 1000 patient-days and was stable throughout the time period. In 2017, these pathogens caused an estimated 622,390 infections (95% confidence interval [CI], 579,125 to 665,655) among hospitalized patients. Of these infections, 517,818 (83%) had their onset in the community, and 104,572 (17%) had their onset in the hospital. MRSA and ESBL infections accounted for the majority of the infections (52% and 32%, respectively). Between 2012 and 2017, the incidence decreased for MRSA infection (from 114.18 to 93.68 cases per 10,000 hospitalizations), VRE infection (from 24.15 to 15.76 per 10,000), carbapenem-resistant acinetobacter species infection (from 3.33 to 2.47 per 10,000), and MDR P. aeruginosa infection (from 13.10 to 9.43 per 10,000), with decreases ranging from -20.5% to -39.2%. The incidence of carbapenem-resistant Enterobacteriaceae infection did not change significantly (from 3.36 to 3.79 cases per 10,000 hospitalizations). The incidence of ESBL infection increased by 53.3% (from 37.55 to 57.12 cases per 10,000 hospitalizations), a change driven by an increase in community-onset cases. CONCLUSIONS: Health care-associated antimicrobial resistance places a substantial burden on patients in the United States. Further work is needed to identify improved interventions for both the inpatient and outpatient settings. (Funded by the Centers for Disease Control and Prevention.).

Presymptomatic SARS-CoV-2 Infections and Transmission in a Skilled Nursing Facility.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can spread rapidly within skilled nursing facilities. After identification of a case of Covid-19 in a skilled nursing facility, we assessed transmission and evaluated the adequacy of symptom-based screening to identify infections in residents. METHODS: We conducted two serial point-prevalence surveys, 1 week apart, in which assenting residents of the facility underwent nasopharyngeal and oropharyngeal testing for SARS-CoV-2, including real-time reverse-transcriptase polymerase chain reaction (rRT-PCR), viral culture, and sequencing. Symptoms that had been present during the preceding 14 days were recorded. Asymptomatic residents who tested positive were reassessed 7 days later. Residents with SARS-CoV-2 infection were categorized as symptomatic with typical symptoms (fever, cough, or shortness of breath), symptomatic with only atypical symptoms, presymptomatic, or asymptomatic. RESULTS: Twenty-three days after the first positive test result in a resident at this skilled nursing facility, 57 of 89 residents (64%) tested positive for SARS-CoV-2. Among 76 residents who participated in point-prevalence surveys, 48 (63%) tested positive. Of these 48 residents, 27 (56%) were asymptomatic at the time of testing; 24 subsequently developed symptoms (median time to onset, 4 days). Samples from these 24 presymptomatic residents had a median rRT-PCR cycle threshold value of 23.1, and viable virus was recovered from 17 residents. As of April 3, of the 57 residents with SARS-CoV-2 infection, 11 had been hospitalized (3 in the intensive care unit) and 15 had died (mortality, 26%). Of the 34 residents whose specimens were sequenced, 27 (79%) had sequences that fit into two clusters with a difference of one nucleotide. CONCLUSIONS: Rapid and widespread transmission of SARS-CoV-2 was demonstrated in this skilled nursing facility. More than half of residents with positive test results were asymptomatic at the time of testing and most likely contributed to transmission. Infection-control strategies focused solely on symptomatic residents were not sufficient to prevent transmission after SARS-CoV-2 introduction into this facility.

Spike Gene Target Amplification in a Diagnostic Assay as a Marker for Public Health Monitoring of Emerging SARS-CoV-2 Variants - United States, November 2021-January 2023.

Monitoring emerging SARS-CoV-2 lineages and their epidemiologic characteristics helps to inform public health decisions regarding vaccine policy, the use of therapeutics, and health care capacity. When the SARS-CoV-2 Alpha variant emerged in late 2020, a spike gene (S-gene) deletion (Δ69-70) in the N-terminal region, which might compensate for immune escape mutations that impair infectivity (1), resulted in reduced or failed S-gene target amplification in certain multitarget reverse transcription-polymerase chain reaction (RT-PCR) assays, a pattern referred to as S-gene target failure (SGTF) (2). The predominant U.S. SARS-CoV-2 lineages have generally alternated between SGTF and S-gene target presence (SGTP), which alongside genomic sequencing, has facilitated early monitoring of emerging variants. During a period when Omicron BA.5-related sublineages (which exhibit SGTF) predominated, an XBB.1.5 sublineage with SGTP has rapidly expanded in the northeastern United States and other regions.

Genomic Surveillance for SARS-CoV-2 Variants: Circulation of Omicron Lineages - United States, January 2022-May 2023.

CDC has used national genomic surveillance since December 2020 to monitor SARS-CoV-2 variants that have emerged throughout the COVID-19 pandemic, including the Omicron variant. This report summarizes U.S. trends in variant proportions from national genomic surveillance during January 2022-May 2023. During this period, the Omicron variant remained predominant, with various descendant lineages reaching national predominance (>50% prevalence). During the first half of 2022, BA.1.1 reached predominance by the week ending January 8, 2022, followed by BA.2 (March 26), BA.2.12.1 (May 14), and BA.5 (July 2); the predominance of each variant coincided with surges in COVID-19 cases. The latter half of 2022 was characterized by the circulation of sublineages of BA.2, BA.4, and BA.5 (e.g., BQ.1 and BQ.1.1), some of which independently acquired similar spike protein substitutions associated with immune evasion. By the end of January 2023, XBB.1.5 became predominant. As of May 13, 2023, the most common circulating lineages were XBB.1.5 (61.5%), XBB.1.9.1 (10.0%), and XBB.1.16 (9.4%); XBB.1.16 and XBB.1.16.1 (2.4%), containing the K478R substitution, and XBB.2.3 (3.2%), containing the P521S substitution, had the fastest doubling times at that point. Analytic methods for estimating variant proportions have been updated as the availability of sequencing specimens has declined. The continued evolution of Omicron lineages highlights the importance of genomic surveillance to monitor emerging variants and help guide vaccine development and use of therapeutics.

Impact of Isolation and Exclusion as a Public Health Strategy to Contain Measles Virus Transmission During a Measles Outbreak.

Responding to measles outbreaks in the United States puts a considerable strain on public health resources, and limited research exists about the effectiveness of containment strategies. In this paper we quantify the impact of isolation, contact tracing, and exclusion in reducing transmission during a measles outbreak in an under-vaccinated community.

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.

Genomic Surveillance for SARS-CoV-2 Variants: Predominance of the Delta (B.1.617.2) and Omicron (B.1.1.529) Variants - United States, June 2021-January 2022.

Genomic surveillance is a critical tool for tracking emerging variants of SARS-CoV-2 (the virus that causes COVID-19), which can exhibit characteristics that potentially affect public health and clinical interventions, including increased transmissibility, illness severity, and capacity for immune escape. During June 2021-January 2022, CDC expanded genomic surveillance data sources to incorporate sequence data from public repositories to produce weighted estimates of variant proportions at the jurisdiction level and refined analytic methods to enhance the timeliness and accuracy of national and regional variant proportion estimates. These changes also allowed for more comprehensive variant proportion estimation at the jurisdictional level (i.e., U.S. state, district, territory, and freely associated state). The data in this report are a summary of findings of recent proportions of circulating variants that are updated weekly on CDC's COVID Data Tracker website to enable timely public health action.† The SARS-CoV-2 Delta (B.1.617.2 and AY sublineages) variant rose from 1% to >50% of viral lineages circulating nationally during 8 weeks, from May 1-June 26, 2021. Delta-associated infections remained predominant until being rapidly overtaken by infections associated with the Omicron (B.1.1.529 and BA sublineages) variant in December 2021, when Omicron increased from 1% to >50% of circulating viral lineages during a 2-week period. As of the week ending January 22, 2022, Omicron was estimated to account for 99.2% (95% CI = 99.0%-99.5%) of SARS-CoV-2 infections nationwide, and Delta for 0.7% (95% CI = 0.5%-1.0%). The dynamic landscape of SARS-CoV-2 variants in 2021, including Delta- and Omicron-driven resurgences of SARS-CoV-2 transmission across the United States, underscores the importance of robust genomic surveillance efforts to inform public health planning and practice.

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.

National Estimates of Healthcare Costs Associated With Multidrug-Resistant Bacterial Infections Among Hospitalized Patients in the United States.

BACKGROUND: Treating patients with infections due to multidrug-resistant pathogens often requires substantial healthcare resources. The purpose of this study was to report estimates of the healthcare costs associated with infections due to multidrug-resistant bacteria in the United States (US). METHODS: We performed retrospective cohort studies of patients admitted for inpatient stays in the Department of Veterans Affairs healthcare system between January 2007 and October 2015. We performed multivariable generalized linear models to estimate the attributable cost by comparing outcomes in patients with and without positive cultures for multidrug-resistant bacteria. Finally, we multiplied these pathogen-specific, per-infection attributable cost estimates by national counts of infections due to each pathogen from patients hospitalized in a cohort of 722 US hospitals from 2017 to generate estimates of the population-level healthcare costs in the US attributable to these infections. RESULTS: Our analysis cohort consisted of 16 676 patients with community-onset infections and 172 712 matched controls and 8246 patients with hospital-onset infections and 66 939 matched controls. The highest cost was seen in hospital-onset invasive infections, with attributable costs (95% confidence intervals) ranging from $30 998 ($25 272-$36 724) for methicillin-resistant Staphylococcus aureus to $74 306 ($20 377-$128 235) for carbapenem-resistant (CR) Acinetobacter. The highest attributable costs for community-onset invasive infections were seen in CR Acinetobacter ($62 396; $20 370-$104 422). Treatment of these infections cost an estimated $4.6 billion ($4.1 billion-$5.1 billion) in 2017 in the US for community- and hospital-onset infections combined. CONCLUSIONS: We found that antimicrobial-resistant infections led to substantial healthcare costs.

Reducing travel-related SARS-CoV-2 transmission with layered mitigation measures: symptom monitoring, quarantine, and testing.

BACKGROUND: Balancing the control of SARS-CoV-2 transmission with the resumption of travel is a global priority. Current recommendations include mitigation measures before, during, and after travel. Pre- and post-travel strategies including symptom monitoring, antigen or nucleic acid amplification testing, and quarantine can be combined in multiple ways considering different trade-offs in feasibility, adherence, effectiveness, cost, and adverse consequences. METHODS: We used a mathematical model to analyze the expected effectiveness of symptom monitoring, testing, and quarantine under different estimates of the infectious period, test-positivity relative to time of infection, and test sensitivity to reduce the risk of transmission from infected travelers during and after travel. RESULTS: If infection occurs 0-7 days prior to travel, immediate isolation following symptom onset prior to or during travel reduces risk of transmission while traveling by 30-35%. Pre-departure testing can further reduce risk, with testing closer to the time of travel being optimal even if test sensitivity is lower than an earlier test. For example, testing on the day of departure can reduce risk while traveling by 44-72%. For transmission risk after travel with infection time up to 7 days prior to arrival at the destination, isolation based on symptom monitoring reduced introduction risk at the destination by 42-56%. A 14-day quarantine after arrival, without symptom monitoring or testing, can reduce post-travel risk by 96-100% on its own. However, a shorter quarantine of 7 days combined with symptom monitoring and a test on day 5-6 after arrival is also effective (97--100%) at reducing introduction risk and is less burdensome, which may improve adherence. CONCLUSIONS: Quarantine is an effective measure to reduce SARS-CoV-2 transmission risk from travelers and can be enhanced by the addition of symptom monitoring and testing. Optimal test timing depends on the effectiveness of quarantine: with low adherence or no quarantine, optimal test timing is close to the time of arrival; with effective quarantine, testing a few days later optimizes sensitivity to detect those infected immediately before or while traveling. These measures can complement recommendations such as social distancing, using masks, and hand hygiene, to further reduce risk during and after travel.

Emergence of SARS-CoV-2 B.1.1.7 Lineage - United States, December 29, 2020-January 12, 2021.

On December 14, 2020, the United Kingdom reported a SARS-CoV-2 variant of concern (VOC), lineage B.1.1.7, also referred to as VOC 202012/01 or 20I/501Y.V1.* The B.1.1.7 variant is estimated to have emerged in September 2020 and has quickly become the dominant circulating SARS-CoV-2 variant in England (1). B.1.1.7 has been detected in over 30 countries, including the United States. As of January 13, 2021, approximately 76 cases of B.1.1.7 have been detected in 12 U.S. states.† Multiple lines of evidence indicate that B.1.1.7 is more efficiently transmitted than are other SARS-CoV-2 variants (1-3). The modeled trajectory of this variant in the U.S. exhibits rapid growth in early 2021, becoming the predominant variant in March. Increased SARS-CoV-2 transmission might threaten strained health care resources, require extended and more rigorous implementation of public health strategies (4), and increase the percentage of population immunity required for pandemic control. Taking measures to reduce transmission now can lessen the potential impact of B.1.1.7 and allow critical time to increase vaccination coverage. Collectively, enhanced genomic surveillance combined with continued compliance with effective public health measures, including vaccination, physical distancing, use of masks, hand hygiene, and isolation and quarantine, will be essential to limiting the spread of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19). Strategic testing of persons without symptoms but at higher risk of infection, such as those exposed to SARS-CoV-2 or who have frequent unavoidable contact with the public, provides another opportunity to limit ongoing spread.

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.

Quantifying the roles of vomiting, diarrhea, and residents vs. staff in norovirus transmission in U.S. nursing home outbreaks.

The role of individual case characteristics, such as symptoms or demographics, in norovirus transmissibility is poorly understood. Six nursing home norovirus outbreaks occurring in South Carolina, U.S. from 2014 to 2016 were examined. We aimed to quantify the contribution of symptoms and other case characteristics in norovirus transmission using the reproduction number (REi) as an estimate of individual case infectivity and to examine how transmission changes over the course of an outbreak. Individual estimates of REi were calculated using a maximum likelihood procedure to infer the average number of secondary cases generated by each case. The associations between case characteristics and REi were estimated using a weighted multivariate mixed linear model. Outbreaks began with one to three index case(s) with large estimated REi's (range: 1.48 to 8.70) relative to subsequent cases. Of the 209 cases, 155 (75%) vomited, 164 (79%) had diarrhea, and 158 (76%) were nursing home residents (vs. staff). Cases who vomited infected 2.12 (95% CI: 1.68, 2.68) times the number of individuals as non-vomiters, cases with diarrhea infected 1.39 (95% CI: 1.03, 1.87) times the number of individuals as cases without diarrhea, and resident-cases infected 1.53 (95% CI: 1.15, 2.02) times the number of individuals as staff-cases. Index cases tended to be residents (vs. staff) who vomited and infected considerably more secondary cases compared to non-index cases. Results suggest that individuals, particularly residents, who vomit are more infectious and tend to drive norovirus transmission in U.S. nursing home norovirus outbreaks. While diarrhea also plays a role in norovirus transmission, it is to a lesser degree than vomiting in these settings. Results lend support for prevention and control measures that focus on cases who vomit, particularly if those cases are residents.

Multi-country cross-sectional study of colonization with multidrug-resistant organisms: protocol and methods for the Antibiotic Resistance in Communities and Hospitals (ARCH) studies.

BACKGROUND: Antimicrobial resistance is a global health emergency. Persons colonized with multidrug-resistant organisms (MDROs) are at risk for developing subsequent multidrug-resistant infections, as colonization represents an important precursor to invasive infection. Despite reports documenting the worldwide dissemination of MDROs, fundamental questions remain regarding the burden of resistance, metrics to measure prevalence, and determinants of spread. We describe a multi-site colonization survey protocol that aims to quantify the population-based prevalence and associated risk factors for colonization with high-threat MDROs among community dwelling participants and patients admitted to hospitals within a defined population-catchment area. METHODS: Researchers in five countries (Bangladesh, Chile, Guatemala, Kenya, and India) will conduct a cross-sectional, population-based prevalence survey consisting of a risk factor questionnaire and collection of specimens to evaluate colonization with three high-threat MDROs: extended-spectrum cephalosporin-resistant Enterobacteriaceae (ESCrE), carbapenem-resistant Enterobacteriaceae (CRE), and methicillin-resistant Staphylococcus aureus (MRSA). Healthy adults residing in a household within the sampling area will be enrolled in addition to eligible hospitalized adults. Colonizing isolates of these MDROs will be compared by multilocus sequence typing (MLST) to routinely collected invasive clinical isolates, where available, to determine potential pathogenicity. A colonizing MDRO isolate will be categorized as potentially pathogenic if the MLST pattern of the colonizing isolate matches the MLST pattern of an invasive clinical isolate. The outcomes of this study will be estimates of the population-based prevalence of colonization with ESCrE, CRE, and MRSA; determination of the proportion of colonizing ESCrE, CRE, and MRSA with pathogenic characteristics based on MLST; identification of factors independently associated with ESCrE, CRE, and MRSA colonization; and creation an archive of ESCrE, CRE, and MRSA isolates for future study. DISCUSSION: This is the first study to use a common protocol to evaluate population-based prevalence and risk factors associated with MDRO colonization among community-dwelling and hospitalized adults in multiple countries with diverse epidemiological conditions, including low- and middle-income settings. The results will be used to better describe the global epidemiology of MDROs and guide the development of mitigation strategies in both community and healthcare settings. These standardized baseline surveys can also inform future studies seeking to further characterize MDRO epidemiology globally.

Modeling Regional Transmission and Containment of a Healthcare-associated Multidrug-resistant Organism.

BACKGROUND: The Centers for Disease Control and Prevention (CDC) recently published interim guidance for a public health response to contain novel or targeted multidrug-resistant organisms (MDROs). We assessed the impact of implementing the strategy in a US state using a mathematical model. METHODS: We used a deterministic compartmental model, parametrized via a novel analysis of carbapenem-resistant Enterobacteriaceae data reported to the National Healthcare Safety Network and patient transfer data from the Centers for Medicare and Medicaid Services. The simulations assumed that after the importation of the MDRO and its initial detection by clinical culture at an index hospital, fortnightly prevalence surveys for colonization and additional infection control interventions were implemented at the index facility; similar surveys were then also implemented at those facilities known to be connected most strongly to it as measured by patient transfer data; and prevalence surveys were discontinued after 2 consecutive negative surveys. RESULTS: If additional infection-control interventions are assumed to lead to a 20% reduction in transmissibility in intervention facilities, prevalent case count in the state 3 years after importation would be reduced by 76% (interquartile range: 73-77%). During the third year, these additional infection-control measures would be applied in facilities accounting for 42% (37-46%) of inpatient days. CONCLUSIONS: CDC guidance for containing MDROs, when used in combination with information on transfer of patients among hospitals, is predicted to be effective, enabling targeted and efficient use of prevention resources during an outbreak response. Even modestly effective infection-control measures may lead to a substantial reduction in transmission events.

Modeling Infectious Diseases in Healthcare Network (MInD-Healthcare) Framework for Describing and Reporting Multidrug-resistant Organism and Healthcare-Associated Infections Agent-based Modeling Methods.

Mathematical modeling of healthcare-associated infections and multidrug-resistant organisms improves our understanding of pathogen transmission dynamics and provides a framework for evaluating prevention strategies. One way of improving the communication among modelers is by providing a standardized way of describing and reporting models, thereby instilling confidence in the reproducibility and generalizability of such models. We updated the Overview, Design concepts, and Details protocol developed by Grimm et al [11] for describing agent-based models (ABMs) to better align with elements commonly included in healthcare-related ABMs. The Modeling Infectious Diseases in Healthcare Network (MInD-Healthcare) framework includes the following 9 key elements: (1) Purpose and scope; (2) Entities, state variables, and scales; (3) Initialization; (4) Process overview and scheduling; (5) Input data; (6) Agent interactions and organism transmission; (7) Stochasticity; (8) Submodels; and (9) Model verification, calibration, and validation. Our objective is that this framework will improve the quality of evidence generated utilizing these models.

Impact of Public Health Responses During a Measles Outbreak in an Amish Community in Ohio: Modeling the Dynamics of Transmission.

We quantified measles transmissibility during a measles outbreak in Ohio in 2014 to evaluate the impact of public health responses. Case incidence and the serial interval (time between symptom onset in primary cases and secondary cases) were used to assess trends in the effective reproduction number R (the average number of secondary cases generated per case). A mathematical model was parameterized using early R values to determine the size and duration of the outbreak that would have occurred if containment measures had not been initiated, as well as the impact of vaccination. As containment started, we found a 4-fold decline in R (from approximately 4 to 1) over the course of 2 weeks and maintenance of R < 1 as control measures continued. Under a conservative scenario, the model estimated 8,472 cases (90% confidence interval (CI): 8,447, 8,489) over 195 days (90% CI: 179, 223) without control efforts and 715 cases (90% CI: 103, 1,338) over 128 days (90% CI: 117, 139) when vaccination was included; 7,757 fewer cases (90% CI: 7,130, 8,365) and 67 fewer outbreak days (90% CI: 48, 98) were attributed to vaccination. Vaccination may not account entirely for transmission reductions, suggesting that changes in community behavior (social distancing) and other control efforts (isolation, quarantining) are important. Our findings highlight the benefits of measles outbreak response and of understanding behavior change dynamics.

Community and Street-Scale Supports for Walking in the US Virgin Islands Before the 2017 Hurricanes.

OBJECTIVES: To determine the prevalence of community and street-scale design features that promote walking across the US Virgin Islands (USVI). METHODS: In May 2016, the USVI Department of Health, with technical assistance from the Centers for Disease Control and Prevention, conducted a territory-wide audit with a validated tool. We selected street segments (n = 1114) via a 2-stage sampling method, and estimates were weighted to be representative of publicly accessible street length. RESULTS: Overall, 10.7% of the street length contained a transit stop, 11.3% had sidewalks, 21.7% had at least 1 destination (e.g., stores, restaurants), 27.4% had a traffic calming feature (e.g., speed humps), and 53.2% had at least some street lighting. Several features were less prevalent on residential streets compared with commercial streets, including transit stops, sidewalks, destinations, and street lighting (P < .01). CONCLUSIONS: Across the USVI, community and street-scale features supportive of walking were uncommon. Improving community and street-scale design in the USVI, particularly in residential areas, could increase physical activity by enhancing walkability and therefore improve public health. These data can be used to inform community planning in the USVI.

Vital Signs: Containment of Novel Multidrug-Resistant Organisms and Resistance Mechanisms - United States, 2006-2017.

BACKGROUND: Approaches to controlling emerging antibiotic resistance in health care settings have evolved over time. When resistance to broad-spectrum antimicrobials mediated by extended-spectrum ß-lactamases (ESBLs) arose in the 1980s, targeted interventions to slow spread were not widely promoted. However, when Enterobacteriaceae with carbapenemases that confer resistance to carbapenem antibiotics emerged, directed control efforts were recommended. These distinct approaches could have resulted in differences in spread of these two pathogens. CDC evaluated these possible changes along with initial findings of an enhanced antibiotic resistance detection and control strategy that builds on interventions developed to control carbapenem resistance. METHODS: Infection data from the National Healthcare Safety Network from 2006-2015 were analyzed to calculate changes in the annual proportion of selected pathogens that were nonsusceptible to extended-spectrum cephalosporins (ESBL phenotype) or resistant to carbapenems (carbapenem-resistant Enterobacteriaceae [CRE]). Testing results for CRE and carbapenem-resistant Pseudomonas aeruginosa (CRPA) are also reported. RESULTS: The percentage of ESBL phenotype Enterobacteriaceae decreased by 2% per year (risk ratio [RR] = 0.98, p<0.001); by comparison, the CRE percentage decreased by 15% per year (RR = 0.85, p<0.01). From January to September 2017, carbapenemase testing was performed for 4,442 CRE and 1,334 CRPA isolates; 32% and 1.9%, respectively, were carbapenemase producers. In response, 1,489 screening tests were performed to identify asymptomatic carriers; 171 (11%) were positive. CONCLUSIONS: The proportion of Enterobacteriaceae infections that were CRE remained lower and decreased more over time than the proportion that were ESBL phenotype. This difference might be explained by the more directed control efforts implemented to slow transmission of CRE than those applied for ESBL-producing strains. Increased detection and aggressive early response to emerging antibiotic resistance threats have the potential to slow further spread.