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Background The CLUSTER trial assessed the impact of prospective identification of clusters coupled with a response protocol on the containment of hospital clusters. Methods This 82-hospital CRT in 16 states compared clusters of bacterial and fungal healthcare pathogens using a statistical outbreak detection tool (WHONET-SaTScan) coupled with a standardized response protocol (automated cluster detection arm) compared to routine surveillance with the response protocol (control arm). Trial periods: 24 mo Baseline (2/17–1/19); 5 mo Phase-in (2/19–6/19); 30 mo Intervention (7/19–1/22). The primary outcome was the number of additional cases occurring after initial cluster detection. Analyses used generalized linear mixed models to assess differences in additional cases between the intervention vs baseline periods across arms, clustering by hospital. Results were assessed overall and, to account for the effect of COVID-19 on hospital operations, stratified into pre-COVID-19 (7/19–6/20) and during COVID-19 (7/20–1/22) intervention periods. We also assessed the probability that a patient was in a cluster. Results In the baseline period, the automated cluster detection and control arms had 0.09 and 0.07 additional cluster cases/1000 admissions, respectively. The automated cluster detection arm had a 22% greater relative reduction in additional cluster cases in the intervention vs baseline period compared to control (P=0.5). Within the intervention period, the automated cluster detection arm had a significant 64% relative reduction pre-COVID-19 (P< 0.05) and a non-significant 6% relative reduction during COVID-19 (P=0.9) compared to control (Figure). When evaluating patient risk of being part of a cluster across the entire intervention period, the automated cluster detection arm had a significant 35% relative reduction vs control (P< 0.01). Conclusion A statistical automated tool coupled with a response protocol improved cluster containment by 64% pre-COVID-19 but not during COVID-19; there were no significant differences between the arms when using the entire intervention period. Automated cluster detection may substantially improve outbreak containment in non-pandemic periods when infection prevention programs are able to optimize containment protocols. Disclosures Susan S. Huang, MD, MPH, Medline: Conducted studies in which hospitals and nursing homes received contributed antiseptic and/or environmental cleaning products|Molnlyke: Conducted clinical studies in which hospitals received contributed antiseptic product|Stryker: Conducted clinical studies in which hospitals and nursing homes received contributed antiseptic products|Xttrium Laboratories: Conducted clinical studies in which hospitals and nursing homes received contributed antiseptic product.

Background The profound changes wrought by coronavirus disease 2019 (COVID-19) on routine hospital operations may have influenced performance on hospital measures, including healthcare-associated infections (HAIs). We aimed to evaluate the association between COVID-19 surges and HAI and cluster rates. Methods In 148 HCA Healthcare-affiliated hospitals, from 1 March 2020 to 30 September 2020, and a subset of hospitals with microbiology and cluster data through 31 December 2020, we evaluated the association between COVID-19 surges and HAIs, hospital-onset pathogens, and cluster rates using negative binomial mixed models. To account for local variation in COVID-19 pandemic surge timing, we included the number of discharges with a laboratory-confirmed COVID-19 diagnosis per staffed bed per month. Results Central line-associated blood stream infections (CLABSI), catheter-associated urinary tract infections (CAUTI), and methicillin-resistant Staphylococcus aureus (MRSA) bacteremia increased as COVID-19 burden increased. There were 60% (95% confidence interval [CI]: 23–108%) more CLABSI, 43% (95% CI: 8–90%) more CAUTI, and 44% (95% CI: 10–88%) more cases of MRSA bacteremia than expected over 7 months based on predicted HAIs had there not been COVID-19 cases. Clostridioides difficile infection was not significantly associated with COVID-19 burden. Microbiology data from 81 of the hospitals corroborated the findings. Notably, rates of hospital-onset bloodstream infections and multidrug resistant organisms, including MRSA, vancomycin-resistant enterococcus, and Gram-negative organisms, were each significantly associated with COVID-19 surges. Finally, clusters of hospital-onset pathogens increased as the COVID-19 burden increased. Conclusions COVID-19 surges adversely impact HAI rates and clusters of infections within hospitals, emphasizing the need for balancing COVID-related demands with routine hospital infection prevention.

Background The profound changes wrought by COVID-19 on routine hospital operations may have influenced performance on hospital measures, including healthcare-associated infections (HAIs). Objective Evaluate the association between COVID-19 surges and HAI or cluster rates Methods Design: Prospective cohort study Setting 148 HCA Healthcare-affiliated hospitals, 3/1/2020-9/30/2020, and a subset of hospitals with microbiology and cluster data through 12/31/2020 Patients All inpatients Measurements We evaluated the association between COVID-19 surges and HAIs, hospital-onset pathogens, and cluster rates using negative binomial mixed models. To account for local variation in COVID-19 pandemic surge timing, we included the number of discharges with a laboratory-confirmed COVID-19 diagnosis per staffed bed per month at each hospital. Results Central line-associated blood stream infections (CLABSI), catheter-associated urinary tract infections (CAUTI), and methicillin-resistant Staphylococcus aureus (MRSA) bacteremia increased as COVID-19 burden increased (P ≤ 0.001 for all), with 60% (95% CI, 23 to 108%) more CLABSI, 43% (95% CI, 8 to 90%) more CAUTI, and 44% (95% CI, 10 to 88%) more cases of MRSA bacteremia than expected over 7 months based on predicted HAIs had there not been COVID-19 cases. Clostridioides difficile infection (CDI) was not significantly associated with COVID-19 burden. Microbiology data from 81 of the hospitals corroborated the findings. Notably, rates of hospital-onset bloodstream infections and multidrug resistant organisms, including MRSA, vancomycin-resistant enterococcus and Gram-negative organisms were each significantly associated with COVID-19 surges (P < 0.05 for all). Finally, clusters of hospital-onset pathogens increased as the COVID-19 burden increased (P = 0.02). Limitations Variations in surveillance and reporting may affect HAI data. Table 1. Effect of an increase in number of COVID-19 discharges on HAIs and hospital-onset pathogens Figure 1. Predicted mean HAI rates as COVID-19 discharges increase Predicted mean HAI rate by increasing monthly COVID-19 discharges. Panel a. CLABSI, Panel b, CAUTI Panel c. MRSA Bacteremia, Panel d. CDI. Data are stratified by small, medium and large hospitals. Figure 2. Monthly comparison of COVID discharges to clusters COVID-19 discharges and the number of clusters of hospital-onset pathogens are correlated throughout the pandemic. Conclusion COVID-19 surges adversely impact HAI rates and clusters of infections within hospitals, emphasizing the need for balancing COVID-related demands with routine hospital infection prevention. Disclosures Kenneth Sands, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Susan S. Huang, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Xttrium (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Ken Kleinman, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products) Edward Septimus, MD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products) Eunice J. Blanchard, MSN RN, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Russell Poland, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Micaela H. Coady, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Deborah S. Yokoe, MD, MPH, Nothing to disclose Julia Moody, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Richard Platt, MD, MSc, Medline (Research Grant or Support, Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Jonathan B. Perlin, MD, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)

Background Up to 40% of hospitalized patients receive unnecessary or inappropriately broad antibiotics despite a low risk of multidrug-resistant organism (MDRO) infection. Empiric standard spectrum antibiotic use would reduce extended-spectrum (ES) antibiotic exposure and future resistance. We evaluated whether computerized prescriber order entry prompts providing patient-specific MDRO risk estimates could reduce ES antibiotic use compared to routine stewardship practices in patients hospitalized with urinary tract infection (UTI). Methods This 59-hospital cluster randomized trial compared: 1) INSPIRE prompts providing patient-specific MDRO UTI risk estimates at order entry and recommended standard spectrum antibiotics for risk < 10% versus 2) routine stewardship practices. Prompt used an absolute MDRO risk algorithm based on a 140 hospital data set. Trial population included adults treated with antibiotics for UTI in ED or non-ICU wards in first 3 days of admission (empiric days); prompt was triggered if ES antibiotics were ordered. Prescribers received feedback on prompt response. Trial periods: 18-month Baseline (Apr 2017–Sept 2018); 6-month Phase-in (Oct 2018–Mar 2019); 15-month Intervention (Apr 2019 – June 2020). Primary outcome was ES antibiotic days of therapy (ES-DOT) per empiric day; secondary outcomes were a) vancomycin and b) anti-pseudomonal DOT per empiric day. Unadjusted, as-randomized analyses used generalized linear mixed effects models to assess differences in ES-DOT rates between the intervention vs baseline period across arms (difference in differences), while clustering by patient and hospital. Results Results: We randomized 59 hospitals in 12 states, with 87,749 and 66,996 non-ICU UTI admissions in baseline and intervention periods, respectively. Intervention group had a a 21% reduction in ES-DOT compared to routine care. Vancomycin and anti-pseudomonal DOT were similarly reduced in the intervention group by 17% and 23%, respectively (Table). Conclusion Conclusion: INSPIRE order entry prompts providing real-time, patient-specific MDRO risk estimates with recommendation to use standard spectrum antibiotics in low risk patients significantly reduced empiric ES prescribing in adults admitted with UTI. Disclosures Shruti K. Gohil, MD, MPH, Medline (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnycke (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Edward Septimus, MD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products) Ken Kleinman, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products) Lauren Heim, MPH, Medline (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Stryker (Sage) (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic product)Xttrium (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic product) Syma Rashid, MD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Stryker (Sage) (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic product)Xttrium (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic product) Taliser R. Avery, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Kenneth Sands, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Julia Moody, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Kimberly N. Smith, MBA, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Brandon Carver, BA, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Caren Spencer-Smith, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Russell Poland, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Jason Hickok, MBA, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Arjun Srinivasan, MD, Nothing to disclose John A. Jernigan, MD, MS, Nothing to disclose Jonathan B. Perlin, MD, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Richard Platt, MD, MSc, Medline (Research Grant or Support, Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Susan S. Huang, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Xttrium (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)

Background Up to 40% of hospitalized patients receive unnecessary or inappropriately broad antibiotics despite a low risk of multidrug-resistant organism (MDRO) infection. Empiric standard spectrum antibiotic use would reduce extended-spectrum (ES) antibiotic exposure and future resistance. We evaluated whether computerized prescriber order entry prompts providing patient-specific MDRO risk estimates could reduce ES antibiotic use compared to routine stewardship practices in patients hospitalized with pneumonia. Methods This 59 hospital cluster-randomized trial compared: 1) INSPIRE prompts providing patient-specific MDRO pneumonia risk estimates at order entry and recommended standard spectrum antibiotics for risk < 10% versus 2) routine stewardship practices. Prompt used an absolute MDRO risk algorithm based on a 140 hospital data set. Trial population included adults treated with antibiotics for pneumonia in ED or non-ICU wards in first 3 days of admission (empiric days); prompt was triggered if ES antibiotics were ordered. Prescribers received feedback on prompt response. Trial periods: 18-month Baseline (Apr 2017–Sept 2018); 6-month Phase-in (Oct 2018–Mar 2019); 15-month Intervention (Apr 2019 – June 2020). Primary outcome was ES antibiotic days of therapy (ES-DOT) per empiric day; secondary outcomes were a) vancomycin and b) anti-pseudomonal DOT per empiric day. Unadjusted, as-randomized analyses used generalized linear mixed effects models to assess differences in ES-DOT rates between the intervention vs baseline period across arms (difference in differences), while clustering by patient and hospital. Results We randomized 59 hospitals in 12 states, with 59,897 and 51,486 non-ICU pneumonia admissions in baseline and intervention periods, respectively. Intervention group had a 33% reduction in ES-DOT compared to routine care. Vancomycin and anti-pseudomonal DOT were similarly reduced in the intervention group by 27% and 33%, respectively (Table). Conclusion INSPIRE order entry prompts providing real-time, patient-specific MDRO risk estimates with recommendation to use standard spectrum antibiotics in low risk patients significantly reduced empiric ES prescribing in adults admitted with pneumonia. Disclosures Shruti K. Gohil, MD, MPH, Medline (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnycke (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Edward Septimus, MD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products) Ken Kleinman, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products) Lauren Heim, MPH, Medline (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Stryker (Sage) (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic product)Xttrium (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic product) Syma Rashid, MD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Stryker (Sage) (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic product)Xttrium (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic product) Taliser R. Avery, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Kenneth Sands, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Julia Moody, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Micaela H. Coady, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Kimberly N. Smith, MBA, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Brandon Carver, BA, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Caren Spencer-Smith, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Russell Poland, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Jason Hickok, MBA, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Arjun Srinivasan, MD, Nothing to disclose John A. Jernigan, MD, MS, Nothing to disclose Jonathan B. Perlin, MD, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Richard Platt, MD, MSc, Medline (Research Grant or Support, Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Susan S. Huang, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Xttrium (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)

Background ICU universal decolonization with daily chlorhexidine (CHG) baths plus mupirocin nasal decolonization reduces all-cause bloodstream infections (BSI) and MRSA clinical cultures. We assessed nasal iodophor, an antiseptic less susceptible to resistance, in place of mupirocin. Methods We conducted a cluster randomized non-inferiority trial in ICUs, comparing universal decolonization with: 1) Mupirocin-CHG: daily CHG baths and 5 days of twice daily nasal mupirocin, to 2) Iodophor-CHG: same regimen, substituting twice daily 10% povidone-iodine for mupirocin. All adult ICUs in a hospital were assigned to the same strategy. We compared each hospital’s outcomes during the 18-month intervention (Nov 2017-Apr 2019) to its own baseline (May 2015-Apr 2017), during which all hospitals used mupirocin-CHG. The primary outcome was ICU-attributable S. aureus clinical isolates. Secondary outcomes included ICU-attributable MRSA clinical isolates and all-cause BSI. As randomized and as treated analyses used unadjusted proportional hazards models assessing differences in outcomes between baseline and intervention periods across the two groups, accounting for clustering by hospital and patient. Results We randomized 137 hospitals with 233 ICUs in 18 states. There were 442,544 admissions in the baseline period and 349,262 in the intervention period. Median ICU length of stay was 4 days. ICU types included mixed medical surgical (56%), medical (9%), surgical (11%), cardiac (15%), and neurologic (9%). CHG adherence was similar in both arms (85%), but adherence was greater for mupirocin (90%) than iodophor (82%). Primary as-randomized results (Table, Figure) exceeded the non-inferiority margin in favor of mupirocin, for S. aureus clinical cultures (21% superiority, P< 0.001) and for MRSA clinical cultures (20% superiority, P< 0.001). The regimens had similar BSI hazards. Analyses of fully adherent patients are in progress. Figure - Primary and Secondary Outcomes of Mupirocin Iodophor Swap Out Trial Conclusion Universal iodophor-CHG was equivalent to mupirocin-CHG for ICU BSI prevention. Mupirocin-CHG was superior to iodophor-CHG for S. aureus and MRSA clinical isolates, potentially due to greater adherence to mupirocin. Disclosures Susan S. Huang, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Xttrium (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Edward Septimus, MD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products) Ken Kleinman, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products) Lauren Heim, MPH, Medline (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Stryker (Sage) (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic product)Xttrium (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic product) Julia Moody, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Taliser R. Avery, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Syma Rashid, MD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Stryker (Sage) (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic product)Xttrium (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic product) Katherine Haffenreffer, BS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Lauren Shimelman, BA, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Caren Spencer-Smith, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Selsebil Sljivo, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Ed Rosen, BS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Russell Poland, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Micaela H. Coady, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Eunice J. Blanchard, MSN RN, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Kimberly Reddish, DNP, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Brandon Carver, BA, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Kimberly N. Smith, MBA, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Jason Hickok, MBA, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Karen Lolans, BS, Medline (Research Grant or Support) Nadia Khan, BS, Medline (Research Grant or Support) John A. Jernigan, MD, MS, Nothing to disclose Kenneth Sands, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Jonathan B. Perlin, MD, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Richard Platt, MD, MSc, Medline (Research Grant or Support, Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)

Objective:To assess the utility of an automated, statistically-based outbreak detection system to identify clusters of hospital-acquired microorganisms.Design:Multicenter retrospective cohort study.Setting:The study included 43 hospitals using a common infection prevention surveillance system.Methods:A space–time permutation scan statistic was applied to hospital microbiology, admission, discharge, and transfer data to identify clustering of microorganisms within hospital locations and services. Infection preventionists were asked to rate the importance of each cluster. A convenience sample of 10 hospitals also provided information about clusters previously identified through their usual surveillance methods.Results:We identified 230 clusters in 43 hospitals involving Gram-positive and -negative bacteria and fungi. Half of the clusters progressed after initial detection, suggesting that early detection could trigger interventions to curtail further spread. Infection preventionists reported that they would have wanted to be alerted about 81% of these clusters. Factors associated with clusters judged to be moderately or highly concerning included high statistical significance, large size, and clusters involving Clostridioides difficile or multidrug-resistant organisms. Based on comparison data provided by the convenience sample of hospitals, only 9 (18%) of 51 clusters detected by usual surveillance met statistical significance, and of the 70 clusters not previously detected, 58 (83%) involved organisms not routinely targeted by the hospitals’ surveillance programs. All infection prevention programs felt that an automated outbreak detection tool would improve their ability to detect outbreaks and streamline their work.Conclusions:Automated, statistically-based outbreak detection can increase the consistency, scope, and comprehensiveness of detecting hospital-associated transmission.

BACKGROUND:Universal skin and nasal decolonisation reduces multidrug-resistant pathogens and bloodstream infections in intensive care units. The effect of universal decolonisation on pathogens and infections in non-critical-care units is unknown. The aim of the ABATE Infection trial was to evaluate the use of chlorhexidine bathing in non-critical-care units, with an intervention similar to one that was found to reduce multidrug-resistant organisms and bacteraemia in intensive care units. METHODS:The ABATE Infection (active bathing to eliminate infection) trial was a cluster-randomised trial of 53 hospitals comparing routine bathing to decolonisation with universal chlorhexidine and targeted nasal mupirocin in non-critical-care units. The trial was done in hospitals affiliated with HCA Healthcare and consisted of a 12-month baseline period from March 1, 2013, to Feb 28, 2014, a 2-month phase-in period from April 1, 2014, to May 31, 2014, and a 21-month intervention period from June 1, 2014, to Feb 29, 2016. Hospitals were randomised and their participating non-critical-care units assigned to either routine care or daily chlorhexidine bathing for all patients plus mupirocin for known methicillin-resistant Staphylococcus aureus (MRSA) carriers. The primary outcome was MRSA or vancomycin-resistant enterococcus clinical cultures attributed to participating units, measured in the unadjusted, intention-to-treat population as the HR for the intervention period versus the baseline period in the decolonisation group versus the HR in the routine care group. Proportional hazards models assessed differences in outcome reductions across groups, accounting for clustering within hospitals. This trial is registered with ClinicalTrials.gov, number NCT02063867. FINDINGS:There were 189 081 patients in the baseline period and 339 902 patients (156 889 patients in the routine care group and 183 013 patients in the decolonisation group) in the intervention period across 194 non-critical-care units in 53 hospitals. For the primary outcome of unit-attributable MRSA-positive or VRE-positive clinical cultures (figure 2), the HR for the intervention period versus the baseline period was 0·79 (0·73-0·87) in the decolonisation group versus 0·87 (95% CI 0·79-0·95) in the routine care group. No difference was seen in the relative HRs (p=0·17). There were 25 (

Background Universal decolonization with daily chlorhexidine (CHG) bathing with and without nasal decolonization has significantly reduced positive MRSA clinical cultures and bloodstream infections in adult ICUs in several clinical trials. We evaluated whether decolonization was similarly effective in a lower risk hospitalized population. Methods We conducted a 2 arm cluster-randomized trial involving a 1-year baseline period (April 2013–March 2014) and a 21-month intervention period (June 2014–February 2016). All noncritical care units in a hospital were assigned to the same strategy. These were (1) Routine Care: routine bathing product and frequency and (2) Decolonization: CHG for routine daily bathing (2% leave-on CHG) or showering (4% rinse-off CHG) for all patients plus mupirocin for 5 days for known MRSA. Universal ICU decolonization was in place in both arms by September 2013. Differences between the arms in the outcome rates between the baseline and intervention periods were assessed with proportional hazards models, using shared frailties to account for clustering by hospital. The primary analysis was as-randomized and unadjusted. Primary outcome was any MRSA or VRE clinical isolate attributable to the unit. Secondary outcome was all-cause bloodstream infections. Additional analyses adjusted for age, gender, race, Medicaid insurer, surgery, and comorbidities. Results We randomized 53 hospitals in 15 states. There were 194 adult units with 189,616 admissions in the baseline period and 340,350 in the intervention period. Common unit types included mixed medical surgical (30%), cardiac (20%), step-down (11%), medical (10%), surgical (10%), and oncology (4%). There were no significant differences between arms in the relative hazards for intervention vs. baseline for either outcome (Table and Figure). Adjusted analyses yielded similar results. Conclusion Universal daily CHG bathing or showering plus targeted mupirocin for MRSA+ patients in non-critical care units did not reduce the combination of positive MRSA and VRE clinical cultures or bloodstream infections due to all pathogens. Further analyses to assess for any differential effects in high-risk subpopulations will be important. Disclosures S. S. Huang, Sage Products: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; Clorox: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; 3M: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; E. Septimus, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; K. Kleinman, Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; J. Moody, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; J. Hickok, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; L. Heim, Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; A. Gombosev, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; T. Avery, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; received research funds from Clorox, but Clorox has no role in the design K. Haffenreffer, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; receive research funds from Clorox, but Clorox has no role in the design; L. Shimelman, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; receive research funds from Clorox, but Clorox has no role in the design; M. K. Hayden, OpGen, Inc.: Receipt of donated laboratory services for project, Research support; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; R. A. Weinstein, Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; OpGen Inc.: Receipt of donated laboratory services for project, Research support; C. Spencer-Smith, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; R. E. Kaganov, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; M. V. Murphy, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; T. Forehand, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; J. Lankiewicz, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; M. H. Coady, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; received research funds from Clorox, but Clorox has no role in the design.; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; L. M. Portillo, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; J. Patel Sarup, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; J. Perlin, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; R. Platt, Clorox: Receipt of contributed product, Conducting clinical studies in which participating healthcare facilities are receiving contributed product; receive research funds from Clorox, but Clorox has no role in the design; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product

Author(s): McKinnell, James A; Singh, Raveena D; Miller, Loren G; Kleinman, Ken; Gussin, Gabrielle; He, Jiayi; Saavedra, Raheeb; Dutciuc, Tabitha D; Estevez, Marlene; Chang, Justin; Heim, Lauren; Yamaguchi, Stacey; Custodio, Harold; Gohil, Shruti K; Park, Steven; Tam, Steven; Robinson, Philip A; Tjoa, Thomas; Nguyen, Jenny; Evans, Kaye D; Bittencourt, Cassiana E; Lee, Bruce Y; Mueller, Leslie E; Bartsch, Sarah M; Jernigan, John A; Slayton, Rachel B; Stone, Nimalie D; Zahn, Matthew; Mor, Vincent; McConeghy, Kevin; Baier, Rosa R; Janssen, Lynn; O'Donnell, Kathleen; Weinstein, Robert A; Hayden, Mary K; Coady, Micaela H; Bhattarai, Megha; Peterson, Ellena M; Huang, Susan S | Abstract: BackgroundMultidrug-resistant organisms (MDROs) spread between hospitals, nursing homes (NHs), and long-term acute care facilities (LTACs) via patient transfers. The Shared Healthcare Intervention to Eliminate Life-threatening Dissemination of MDROs in Orange County is a regional public health collaborative involving decolonization at 38 healthcare facilities selected based on their high degree of patient sharing. We report baseline MDRO prevalence in 21 NHs/LTACs.MethodsA random sample of 50 adults for 21 NHs/LTACs (18 NHs, 3 LTACs) were screened for methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus spp. (VRE), extended-spectrum β-lactamase-producing organisms (ESBL), and carbapenem-resistant Enterobacteriaceae (CRE) using nares, skin (axilla/groin), and peri-rectal swabs. Facility and resident characteristics associated with MDRO carriage were assessed using multivariable models clustering by person and facility.ResultsPrevalence of MDROs was 65% in NHs and 80% in LTACs. The most common MDROs in NHs were MRSA (42%) and ESBL (34%); in LTACs they were VRE (55%) and ESBL (38%). CRE prevalence was higher in facilities that manage ventilated LTAC patients and NH residents (8% vs l1%, P l .001). MDRO status was known for 18% of NH residents and 49% of LTAC patients. MDRO-colonized adults commonly harbored additional MDROs (54% MDRO+ NH residents and 62% MDRO+ LTACs patients). History of MRSA (odds ratio [OR] = 1.7; confidence interval [CI]: 1.2, 2.4; P = .004), VRE (OR = 2.1; CI: 1.2, 3.8; P = .01), ESBL (OR = 1.6; CI: 1.1, 2.3; P = .03), and diabetes (OR = 1.3; CI: 1.0, 1.7; P = .03) were associated with any MDRO carriage.ConclusionsThe majority of NH residents and LTAC patients harbor MDROs. MDRO status is frequently unknown to the facility. The high MDRO prevalence highlights the need for prevention efforts in NHs/LTACs as part of regional efforts to control MDRO spread.

Background: Universal skin and nasal decolonization reduces multidrug-resistant pathogens and bloodstream infections in intensive care units. The effect of universal decolonization on pathogens and infections in non-critical care units is unknown. Methods: A two-arm cluster-randomized trial was conducted in 53 hospitals in the Hospital Corporation of America Healthcare system. Hospitals were randomized and their participating non-critical care units assigned to either routine care or daily chlorhexidine bathing for all patients plus mupirocin for known methicillin-resistant Staphylococcus aureus (MRSA) carriers. The trial involved a 12-month baseline (Mar 2013-Feb 2014) and 21-month intervention (Jun 2014-Feb 2016). Primary outcome was MRSA or vancomycin-resistant enterococcus (VRE) clinical cultures attributed to participating units, and secondary outcome was all-pathogen bloodstream infection. Proportional hazards models assessed differences in outcome reductions across arms, accounting for clustering by hospital. Post-hoc subgroup analyses were performed. Findings: There were 189,081 patients in the baseline period and 339,902 patients in the intervention period across 194 non-critical care units in 53 hospitals. Hazard ratios for MRSA/VRE clinical isolates during intervention vs. baseline periods were 0·87 (CI:0·79, 0·95) for routine care, and 0·79 (CI:0·73, 0·87) for decolonization (p=0·17), and 0·96 (CI:0·85, 1·08) and 0·90 (0·81, 1·01) for all-pathogen bloodstream infection, respectively (p=0·44). Among patients with central venous catheters, midline catheters, or lumbar drains, the hazard ratio for MRSA/VRE clinical cultures was 1·17 (CI:1·00, 1·37) for routine care and 0·80 (CI:0·69, 0·92) for decolonization, (p=0·0004), and the hazard ratio for all-pathogen bloodstream infections was 1·13 (CI:0·96, 1·33) for routine care and 0·82 (CI:0·71, 0·94) for decolonization, p=0·004. Interpretation: Decolonization with universal chlorhexidine bathing and targeted mupirocin for MRSA carriers did not reduce multidrug-resistant organisms or all-pathogen bloodstream infection in all non-critical care patients, but patients with invasive devices experienced 37% reduction in MRSA/VRE and 31% reduction in bloodstream infections. Clinical Trial Registration Number: clinicaltrials.gov Identifier: NCT0206386 Funding Statement: This project was funded by the National Institutes of Health Common Fund and administered by the National Institute of Allergy and Infectious Diseases (UH2/UH3 AT007769‐01 (Huang)). Declaration of Interest: Sage Products and Molnlycke contributed antiseptic chlorhexidine product to this trial. Investigators are also conducting other studies in which contributed antiseptic product is provided to participating hospitals and nursing homes from Stryker (Sage Products) (KK, LH, MHC, MKH, RAW, SSH), 3M (LH, SSH), Clorox (CS, ES, JH, JM, JP, KH, KK, LH, LS, MHC, MKH, RAW, RP, SSH, TRA), Xttrium (LH, SSH), and Medline (CS, ES, JH, JM, JP, KH, KK, LH, LS, MHC, MKH, RAW, RP, SSH, TRA). Investigator-initiated grant funds were received from Clorox (MKH, MHC, LS, KH, RP). Companies contributing product or providing grant funds have no role in the design, conduct, analysis, or publication of the ABATE Infection Trial or other studies conducted by these investigators. All other authors have no disclosures. Ethics Approval Statement: Central IRB approval was obtained from Harvard Pilgrim Health Care with a waiver of informed consent. All participating hospitals formally ceded IRB oversight to the HPHC IRB, except for the designated medical center IRB (Chippenham & Johnston Willis Hospitals) that provided prisoner oversight for the trial.

In 2002, New York City implemented a comprehensive tobacco control plan that discouraged smoking through excise taxes and smoke-free air laws and facilitated quitting through population-wide cessation services and hard-hitting media campaigns. Following the implementation of these activities through a well-funded and politically supported program, the adult smoking rate declined by 28% from 2002 to 2012, and the youth smoking rate declined by 52% from 2001 to 2011. These improvements indicate that local jurisdictions can have a significant positive effect on tobacco control.

While tobacco taxes and smoke-free air regulations have significantly decreased tobacco use, tobacco-related illness accounts for hundreds of thousands of annual deaths. Experts are considering additional strategies to further reduce tobacco consumption.We investigated smokers' (n=2118) and non-smokers' (n=2210) opinions on existing and theoretical strategies, including tax and retailer-based strategies in New York City, across three cross-sectional surveys.Compared with smokers, non-smokers were significantly more likely (p0.05) to favour all tobacco control strategies. Overall, 25% of smokers surveyed favoured increasing taxes on cigarettes, climbing to 60% if taxes were used to fund healthcare programmes. Among non-smokers, 72% favoured raising taxes, increasing to 83% if taxes were used to fund healthcare programmes. 54% of non-smoking New Yorkers favoured limiting the number of tobacco retail licences, as did 30% of smokers. The most popular retail-based strategies were raising the minimum age to purchase cigarettes from 18 to 21, with 60% of smokers and 69% of non-smokers in favour, and prohibiting retailers near schools from selling tobacco, with 51% of smokers and 69% of non-smokers in favour. Keeping tobacco products out of customers' view, prohibiting tobacco companies from paying retailers to display or advertise tobacco products and prohibiting price promotions were favoured by more than half of non-smokers surveyed, and almost half of smokers.While the support level varied between smokers and non-smokers, price and retail-based tobacco control strategies were consistently supported by the public, providing useful information for jurisdictions examining emerging tobacco control strategies.

Background To increase knowledge of smoking-related health risks and provide smoking cessation information at the point of sale, in 2009, New York City required the posting of graphic point-of-sale tobacco health warnings in tobacco retailers. This study is the first to evaluate the impact of such a policy in the USA. Methods Cross-sectional street-intercept surveys conducted among adult current smokers and recent quitters before and after signage implementation assessed the awareness and impact of the signs. Approximately 10 street-intercept surveys were conducted at each of 50 tobacco retailers in New York City before and after policy implementation. A total of 1007 adults who were either current smokers or recent quitters were surveyed about the awareness and impact of tobacco health warning signs. Multivariate risk ratios (RR) were calculated to estimate awareness and impact of the signs. Results Most participants (86%) were current smokers, and the sample was 28% African–American, 32% Hispanic/Latino and 27% non-Hispanic white. Awareness of tobacco health warning signs more than doubled after the policy implementation (adjusted RR =2.01, 95% CI 1.74 to 2.33). Signage posting was associated with an 11% increase in the extent to which signs made respondents think about quitting smoking (adjusted RR =1.11, 95% CI 1.01 to 1.22). Conclusions A policy requiring tobacco retailers to display graphic health warning signs increased awareness of health risks of smoking and stimulated thoughts about quitting smoking. Additional research aimed at evaluating the effect of tobacco control measures in the retail environment is necessary to provide further rationale for implementing these changes.

This article describes the evaluation of the law banning smoking in New York City's parks and beaches that went into effect in 2011. We discuss the practical and methodological challenges that emerged in evaluating this law, and describe how we applied the principles of critical multiplism to address these issues. The evaluation uses data from three complementary studies, each with a unique set of strengths and weaknesses that can provide converging evidence for the effectiveness of the law. Results from a litter audit and an observational study suggest the ban reduced smoking in parks and beaches. The purpose, methodology and baseline results from an ongoing survey that measures how frequently adults in NYC and across New York State notice people smoking in parks and on beaches are presented and discussed. Limitations are considered and suggestions are offered for future evaluations of similar policies.

Background MDROs can spread between hospitals, nursing homes (NH), and long-term acute care facilities (LTACs) via shared patients. SHIELD OC is a regional decolonization collaborative involving 38 of 104 countywide adult facilities identified by their high degree of direct and indirect patient sharing with one another. We report baseline MDRO prevalence in these facilities. Methods Adult patients in 38 facilities (17 hospitals, 18 NHs, 3 LTACs) underwent point-prevalence screening between September 2016–April 2017 for MRSA, VRE, ESBL, and CRE using nares, skin (axilla/groin), and peri-rectal swabs. In NHs and LTACs, residents were randomly selected until 50 sets of swabs were obtained. Swabbing in hospitals involved all patients in contact precautions. An additional set of swabs were also performed for all LTAC admissions from November 2016–February 2017. Results The overall prevalence of any MDRO among patients was 64% (44%–88%) in NHs, 80% (range 72%–86%) in LTACs, and 64% (54–84%) in hospitals (contact precaution patients) (Table 1). Only 25%, 64%, and 81% of patients were already known to harbor an MDRO in NHs, LTACs, and hospitals, respectively. Known MDRO patients also harbored another MDRO 49%, 63%, and 34% of the time for NHs, LTACs, and hospitals, respectively. In LTACs, MDRO point prevalence was 38% higher than the usual admission prevalence (65% higher for MRSA, 34% higher for VRE, 95% higher for ESBL, and 50% higher for CRE). Conclusion MDRO carriage in highly inter-connected NHs and LTACs was widespread, rivaling that found in hospitalized patients on contact precautions. MRSA, VRE, and ESBL carriage far outnumbered CRE carriage. A history of MDRO was insensitive for identifying MDRO carriers, and many patients carried multiple MDROs. The extensive MDRO burden and transmission in long-term care settings suggests that regional MDRO prevention efforts must include MDRO control in long-term care facilities. Disclosures R. D. Singh, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; J. A. McKinnell, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; L. G. Miller, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; K. Kleinman, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; L. Heim, Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; T. D. Dutciuc, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; M. Estevez, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; G. Gussin, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; L’Oreal: Consultant, Consulting fee; J. Chang, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; E. M. Peterson, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; B. Y. Lee, GSK: Consultant, Consulting fee; R. A. Weinstein, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; OpGen Company: Study support, Provided services at no charge; M. K. Hayden, Sage Products: Receipt of contributed product, Sage is contributing product to healthcare facilities participating in a regional collaborative on which I am a co-investigator. Neither I nor my hospital receive product.; Clorox: Receipt of contributed product, Research support; CDC: Grant Investigator and Receipt of contributed product, Research grant; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; OpGen Company: Study support, Provided services at no charge for studies; S. K. Gohil, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; S. Park, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; S. Tam, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; R. Saavedra, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; S. Yamaguchi, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; H. Custodio, Xttrium Laboratories: Study coordination, Conducting studies in healthcare facilities that are receiving contributed product; Sage Products: Study coordination, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Study coordination, Conducting studies in healthcare facilities that are receiving contributed product; J. Nguyen, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; T. Tjoa, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; J. He, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; M. H. Coady, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; R. Platt, Sage Products: Receipt of contributed product, Conducting clinical studies in which participating healthcare facilities are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting clinical studies in which participating healthcare facilities are receiving contributed product; Clorox: Receipt of contributed product, Conducting clinical studies in which participating healthcare facilities are receiving contributed product; receive research funds from Clorox, but Clorox has no role in the design; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; S. S. Huang, Sage Products: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; Clorox: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; 3M: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; Molnlycke: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product

Objectives. We sought to determine whether the work of a community-based participatory research partnership increased interest in influenza vaccination among hard-to-reach individuals in urban settings. Methods. A partnership of researchers and community members carried out interventions for increasing acceptance of influenza vaccination in disadvantaged urban neighborhoods, focusing on hard-to-reach populations (e.g., substance abusers, immigrants, elderly, sex workers, and homeless persons) in East Harlem and the Bronx in New York City. Activities targeted the individual, community organization, and neighborhood levels and included dissemination of information, presentations at meetings, and provision of street-based and door-to-door vaccination during 2 influenza vaccine seasons. Participants were recruited via multiple modalities. Multivariable analyses were performed to compare interest in receiving vaccination pre- and postintervention. Results. There was increased interest in receiving the influenza vaccine postintervention (P Conclusions. Targeting underserved neighborhoods through a multilevel community-based participatory research intervention significantly increased interest in influenza vaccination, particularly among hard-to-reach populations. Such interventions hold promise for increasing vaccination rates annually and in pandemic situations.

Objectives. We evaluated the efficacy of a peer-mentoring behavioral intervention designed to reduce risky distributive injection practices (e.g., syringe lending, unsafe drug preparation) among injection drug users with hepatitis C virus (HCV) infection. Methods. A randomized trial with a time-equivalent attention-control group was conducted among 418 HCV-positive injection drug users aged 18 to 35 years in 3 US cities. Participants reported their injection-related behaviors at baseline and at 3- and 6-month follow-ups. Results. Compared with the control group, intervention-group participants were less likely to report distributive risk behaviors at 3 months (odds ratio [OR]=0.46; 95% confidence interval [CI]=0.27, 0.79) and 6 months (OR=0.51; 95% CI=0.31, 0.83), a 26% relative risk reduction, but were no more likely to cite their HCV-positive status as a reason for refraining from syringe lending. Effects were strongest among intervention-group participants who had known their HCV-positive status for at least 6 months. Peer mentoring and self-efficacy were significantly increased among intervention-group participants, and intervention effects were mediated through improved self-efficacy. Conclusions. This behavioral intervention reduced unsafe injection practices that may propagate HCV among injection drug users.

Whereas considerable attention has been devoted to achieving high levels of influenza immunization, the importance of this issue is magnified by concern over pandemic influenza. Most recommendations for vaccine administration address high risk groups such as the elderly and those with chronic diseases, but coverage for hard-to-reach (HTR) populations has had less attention. HTR populations include minorities but also include other primarily urban groups such as undocumented immigrants, substance users, the homeless, and homebound elderly. Obstacles to the provision of immunization to HTR populations are present at the patient, provider, and structural levels. Strategies at the individual level for increasing immunization coverage include community-based educational campaigns to improve attitudes and increase motivation for receiving vaccine; at the provider level, education of providers to encourage immunizations, improving patient–provider interactions, broadening the provider base to include additional nurses and pharmacists, and adoption of standing orders for immunization administration; and at the structural level, promoting wider availability of and access to vaccine. The planning process for an influenza pandemic should include community engagement and extension of strategies beyond traditional providers to involve community-based organizations addressing HTR populations.

Using cross-sectional analysis we examined residential status and associated differences in HIV risk behaviors among 3266 young IDUs enrolled in an HIV prevention trial. A three-level outcome (homeless (37%), equivocally housed (17%), housed (46%)) was defined based on responses to two questions assessing subjective and objective criteria for homelessness: "equivocally housed" participants were discordant on these measures. In multivariate analysis, antecedents of homelessness were having lived in an out-of-home placement, been thrown out of the home or in juvenile detention, and experienced childhood abuse; while correlates included receiving income from other and illegal sources, drinking alcohol or using methamphetamine at least daily, using shooting galleries, backloading, and sex work. A subset of these variables was associated with being equivocally housed. HIV risk varies by housing status, with homeless IDUs at highest risk. Programs for IDUs should utilize a more specific definition of residential status to target IDUs needing intervention.

In October 2004, one of the major producers of the U.S. influenza vaccine supply announced that their vaccine would not be available because of production problems, resulting in approximately half of the anticipated supply suddenly becoming unavailable. This study was part of a larger effort using community-based participatory research (CBPR) principles to distribute influenza vaccine to hard-to-reach populations. Given the extant literature suggesting economic and racial disparities in influenza vaccine access in times of adequate supply and our inability to distribute vaccine due to the shortage, we sought to examine vaccine access as well as awareness of the vaccine shortage and its impact on health-seeking behaviors in eight racially-diverse and economically-disadvantaged neighborhoods in New York City (NYC) during the shortage. In our study few people had been vaccinated, both among the general community and among high risk groups; vaccination rates for adults in priority groups and non-priority groups were 21.0% and 3.5%. Awareness of the 2004 vaccine shortage was widespread with over 90% being aware of the shortage. While most attributed the shortage to production problems, almost 20% said that it was due to the government not wanting to make the vaccine available. Many respondents said they would be more likely to seek vaccination during the current and subsequent influenza seasons because of the shortage. The target neighborhoods were significantly affected by the national influenza vaccine shortage. This study highlights the challenges of meeting the preventive health care needs of hard-to-reach populations in times of public health crisis.

Hepatitis C virus (HCV) is hyperendemic among injection drug users (IDUs). However, few scientifically proven interventions to prevent secondary transmission of HCV from infected IDUs to others exist. This report describes the design, feasibility, and baseline characteristics of participants enrolled in the Study to Reduce Intravenous Exposure (STRIVE). STRIVE was a multisite, randomized-control trial to test a behavioral intervention developed to reduce distribution of used injection equipment (needles, cookers, cottons, and rinse water) and increase health-care utilization among antibody HCV (anti-HCV) positive IDUs. STRIVE enrolled anti-HCV positive IDU in Baltimore, New York City, and Seattle; participants completed behavioral assessments and venipuncture for HIV, HCV-RNA, and liver function tests (LFTs) and were randomized to attend either a six-session, small-group, peer-mentoring intervention workshop or a time-matched, attention-control condition. Follow-up visits were conducted at 3 and 6 months. At baseline, of the 630 HCV-positive IDUs enrolled (mean age of 26 years, 60% white, 76% male), 55% reported distributive needle sharing, whereas 74, 69, and 69% reported sharing cookers, cottons, and rinse water, respectively. Health-care access was low, with 41% reporting an emergency room as their main source of medical care. Among those enrolled, 66% (418/630) were randomized: 53% (222/418) and 47% (196/418) to the intervention and control conditions, respectively. Follow-up rates were 70 and 73% for the 3- and 6-month visits, respectively. As distributive sharing of used injection equipment was common while reports of receiving HCV care were low, these findings indicate an urgent need for HCV-related interventions with IDUs and demonstrate the acceptability and feasibility to do so.

Secondhand smoke exposure is a concern in multiunit housing, where smoke can migrate between apartments. In 2012, the New York City (NYC) Department of Health and Mental Hygiene conducted a cross-sectional mail and phone survey among a random sample of low-income and market-rate multiunit housing owners and managers in NYC. The study compared experiences and attitudes regarding smoke-free policies between owners/managers (owners) with and without low-income units. Logistic regression analysis was used to assess the correlates of smoke-free residential unit rules and interest in adopting new smoke-free rules. Perceived benefits and challenges of implementing smoke-free rules were also examined. Overall, one-third of owners prohibited smoking in individual units. Among owners, nearly one-third owned or managed buildings with designated certified low-income units. Owners with low-income units were less likely than those without to have a smoke-free unit policy (26 vs. 36 %, p

Background Cigarette taxation is effective in reducing tobacco use in the USA. However, these benefits are reduced when taxes are unpaid. Cigarette trafficking (ie, the illegal importation of cigarettes into a high-tax jurisdiction from a lower-tax jurisdiction) is well documented in high-tax places like New York City (NYC), but the extent of trafficking in other northeastern cities is relatively unknown. Objective To estimate the extent of cigarette trafficking in Boston, NYC, Philadelphia, Providence and Washington, DC, and project the benefits of reducing cigarette trafficking for recouping lost taxes and reducing smoking in these cities. Methods Littered cigarette packs were collected from a random sample of Census tracts in five US cities. Data collection yielded 1439 total littered packs. The share of cigarette packs bearing proper local, known non-local, foreign or unknown, or no tax stamp was calculated for each city. These data were used to estimate tax revenue recovery if cigarette trafficking could be eliminated. We also estimated the extent to which eliminating cigarette trafficking would reduce cigarette consumption. Results Overall, 58.7% of packs did not have a proper local tax stamp, and 30.5–42.1% were attributed to trafficking. We estimate that eliminating cigarette trafficking would result in declines in youth smoking prevalence ranging from negligible in low-tax cities like Philadelphia to up to 9.3% in higher-tax NYC. We estimate that these five cities could recoup $680–729 million annually in cigarette tax revenue if cigarette trafficking was eliminated. Conclusions Reducing cigarette trafficking would increase the effectiveness of tobacco taxes in reducing smoking and generate additional tax revenue, particularly in higher-taxed cities. Federal action to reduce cigarette trafficking, such as a track-and-trace system, is needed.

Objectives. We examined the relationship between cigarette excise tax increases and tax-avoidant purchasing behaviors among New York City adult smokers. Methods. We analyzed data from the city’s annual Community Health Survey to assess changes in rates of tax avoidance over time (2003–2010) and smokers’ responses to the 2008 state cigarette tax increase. Multivariable logistic regression analysis identified correlates of buying more cigarettes on the street in response to the increase. Results. After the 2002 tax increase, the percentage of smokers engaged in tax-avoidant behavior decreased with time from 30% in 2003 to 13% in 2007. Following the 2008 tax increase, 21% of smokers reported buying more cigarettes from another person on the street. Low-income, younger, Black, and Hispanic smokers were more likely than respondents with other sociodemographic characteristics to purchase more cigarettes on the street. Conclusions. To maximize public health impact, cigarette tax increases should be paired with efforts to limit the flow of untaxed cigarettes entering jurisdictions with high cigarette pack prices.

Since 2006, the New York City (NYC) Department of Health and Mental Hygiene has conducted the Nicotine Patch and Gum Program (NPGP) in collaboration with 311, NYC’s non-emergency information line. In two prior years, the program was conducted in collaboration with the New York State (NYS) Smokers’ Quitline and with community-based organizations. The NPGP is an annual, brief, population-based nicotine replacement therapy (NRT) giveaway for NYC residents, complementing the NYS Quitline’s year-round NRT distribution program. Since 2006, 168,000 smokers have enrolled, with the largest number of enrollees in 2010 (n = 40,000) and the smallest number in 2009 (n = 28,000). A 2003 program evaluation demonstrated that smokers who received NRT through the NPGP had higher quit rates than smokers who did not receive NRT; these results were replicated in 2006 and 2008. Lessons learned from implementing the NPGP include: 1) time-limited NRT interventions are important complements to year-round NRT distribution; 2) expanding NRT distribution to light smokers increases treatment reach; and 3) employing multiple enrollment mechanisms, including telephone and online options, extends program reach to diverse groups of smokers. The NPGP provides a model for other jurisdictions considering implementing time-limited, population-based NRT programs as a complementary strategy to enhance ongoing tobacco control efforts.

The New York City (NYC) Health Department has implemented a comprehensive tobacco control plan since 2002, and there was a 27% decline in adult smoking prevalence in NYC from 2002 to 2008. There are conflicting reports in the literature on whether residual smoker populations have a larger or smaller share of “hardcore” smokers. Changes in daily consumption and daily and nondaily smoking prevalence, common components used to define hardcore smokers, were evaluated in the context of the smoking prevalence decline. Using the NYC Community Health Survey, an annual random digit dial, cross-sectional survey that samples approximately 10,000 adults, the prevalence of current heavy daily, light daily, and nondaily smokers among NYC adults was compared between 2002 and 2008. A five-level categorical cigarettes per day (CPD) variable was also used to compare the population of smokers between the 2 years. From 2002 to 2008, significant declines were seen in the prevalence of daily smoking, heavy daily smoking, and nondaily smoking. Among daily smokers, there is also evidence of population declines in all but the lowest smoking category (one to five CPD). The mean CPD among daily smokers declined significantly, from 14.6 to 12.5. After an overall decline in smoking since 2002, the remaining smokers may be less nicotine dependent, based on changes in daily consumption and daily and nondaily smoking prevalence. These findings suggest the need to increase media and cessation efforts targeted towards lighter smokers.

Objective. Among current smokers, the proportion of Nondaily smokers is increasing. A better understanding of the characteristics and smoking behaviors of Nondaily smokers is needed.Methods. We analyzed data from the New York City (NYC) Community Health Survey to explore Nondaily smoking among NYC adults. Univariate analyses assessed changes in Nondaily smoking over time (2002–2010) and identified unique characteristics of Nondaily smokers; multivariable logistic regression analysis identified correlates of Nondaily smoking in 2010.Results. The proportion of smokers who engage in Nondaily smoking significantly increased between 2002 and 2010, from 31% to 36% (P=0.05). A larger proportion of Nondaily smokers in 2010 were low income and made tax-avoidant cigarette purchases compared to 2002. Smoking behaviors significantly associated with Nondaily smoking in 2010 included smoking more than one hour after waking (AOR=8.8, 95% CI (5.38–14.27)); buying “loosies” (AOR=3.5, 95% CI (1.72–7.08)); attempting to quit (AOR=2.3, 95% CI (1.36–3.96)).Conclusion. Nondaily smokers have changed over time and have characteristics distinct from daily smokers. Tobacco control efforts should be targeted towards “ready to quit” Nondaily smokers.

Objective Since 2003, the New York City Department of Health and Mental Hygiene has distributed nicotine replacement therapy nicotine replacement therapy to adult smokers through annual large-scale distribution programs. Methods In 2008, the New York City Department of Health and Mental Hygiene formally integrated geographic information system analyses to track program enrollment, map the geographic density of enrollees, and assess the effects of outreach strategies. Results Geographic information system analyses provided a unique, near real-time visual method of assessing participation patterns as well as the impact of media and outreach strategies. Among neighborhoods with high smoking prevalence, lower income neighborhoods had higher enrollment compared to higher income neighborhoods. Mapping before and after a press release demonstrated that program interest increased over 700% in one area. Conclusion Although geographic information system analysis is traditionally utilized for large-scale infectious disease surveillance, the New York City Department of Health and Mental Hygiene used GIS to inform and improve an annual large-scale smoking cessation program. These analyses provide unique feedback that can aid public health program planners in improving efficiency and efficacy of service delivery.

The Inspire education program, with nine modules, was developed to improve medical management of asthma and was piloted among parents of preschool children in an economically disadvantaged community of color with high asthma prevalence. Program flexibility, individualized educational modules, a case management approach, and institutional involvement were key elements.

With growing fear of a worldwide influenza pandemic, programs that can rapidly vaccinate a broad range of persons are urgently needed. Vaccination rates are low among disadvantaged and hard-to-reach populations living within urban communities, and delivering vaccines to these groups may prove challenging. Project VIVA1 (Venue-Intensive Vaccination for Adults), staffed by teams of nurses and outreach workers, aimed to deliver vaccines rapidly within disadvantaged neighborhoods in New York City. Project VIVA nurses offered free influenza vaccine door-to-door and on street corners over 10 days in October, 2005. A total of 1,648 people were vaccinated, exceeding expectation. Careful selection and training of project staff, community involvement in project development, community outreach, and prioritizing street-based distribution may be key factors in an effective rapid vaccination program. In conclusion, this project may be replicated in other communities and utilized for annual vaccination campaigns and in the event of a pandemic.

Injection drug users (IDUs) acquire the majority of new hepatitis C virus (HCV) infections and frequently use alcohol. Alcohol abuse accelerates liver disease among HCV-infected persons, can reduce the effectiveness of treatment for HCV infection and may be a contraindication for HCV treatment. HCV seropositive, HIV-negative IDUs aged 18-35 years in Baltimore, New York City and Seattle who were enrolled in a behavioral risk-reduction intervention trial underwent computerized self-interviews to assess baseline alcohol use and dependence and medical history. We measured problem alcohol use using the 10-item Alcohol Use Disorders Identification Test (AUDIT) scale. Of 598 participants, 84% responded "false" to: "it is safe for a person with HCV to drink alcohol". Problem drinking, defined as score > or =8 on AUDIT, was identified in 37%. Correlates of scoring > or =8 on AUDIT included homelessness, male gender, primarily injecting speedballs, having injected with used needles, prior alcohol treatment and depression. Although most HCV seropositive IDUs in our sample appear informed about their increased risk of liver disease from alcohol, two-fifths screened positive for problem alcohol use. These findings underscore the importance of referring HCV-positive persons to effective alcohol treatment programs to reduce future liver damage and improve eligibility for and effectiveness of treatment of HCV.