Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. For the 2021-22 and 2022-23 influenza seasons, 26 forecasting teams provided national and jurisdiction-specific probabilistic predictions of weekly confirmed influenza hospital admissions for one-to-four weeks ahead. Forecast skill is evaluated using the Weighted Interval Score (WIS), relative WIS, and coverage. Six out of 23 models outperform the baseline model across forecast weeks and locations in 2021-22 and 12 out of 18 models in 2022-23. Averaging across all forecast targets, the FluSight ensemble is the 2(nd) most accurate model measured by WIS in 2021-22 and the 5(th) most accurate in the 2022-23 season. Forecast skill and 95% coverage for the FluSight ensemble and most component models degrade over longer forecast horizons. In this work we demonstrate that while the FluSight ensemble was a robust predictor, even ensembles face challenges during periods of rapid change.

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1-4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naïve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making.

BACKGROUND: Because interventions are available to prevent further recurrence in patients with recurrent Clostridioides difficile infection (rCDI), we identified predictors of multiple rCDI (mrCDI) in adults at the time of presentation with initial CDI (iCDI). METHODS: iCDI was defined as a positive C difficile test in any clinical setting during January 2018-August 2019 in a person aged ≥18 years with no known prior positive test. rCDI was defined as a positive test ≥14 days from the previous positive test within 180 days after iCDI; mrCDI was defined as ≥2 rCDI. We performed multivariable logistic regression analysis. RESULTS: Of 18 829 patients with iCDI, 882 (4.7%) had mrCDI; 437 with mrCDI and 7484 without mrCDI had full chart reviews. A higher proportion of patients with mrCDI than without mrCDI were aged ≥65 years (57.2% vs 40.7%; P < .0001) and had healthcare (59.1% vs 46.9%; P < .0001) and antibiotic (77.3% vs 67.3%; P < .0001) exposures in the 12 weeks preceding iCDI. In multivariable analysis, age ≥65 years (adjusted odds ratio [aOR], 1.91; 95% confidence interval [CI], 1.55-2.35), chronic hemodialysis (aOR, 2.28; 95% CI, 1.48-3.51), hospitalization (aOR, 1.64; 95% CI, 1.33-2.01), and nitrofurantoin use (aOR, 1.95; 95% CI, 1.18-3.23) in the 12 weeks preceding iCDI were associated with mrCDI. CONCLUSIONS: Patients with iCDI who are older, on hemodialysis, or had recent hospitalization or nitrofurantoin use had increased risk of mrCDI and may benefit from early use of adjunctive therapy to prevent mrCDI. If confirmed, these findings could aid in clinical decision making and interventional study designs.

OBJECTIVE: Patients tested for Clostridioides difficile infection (CDI) using a 2-step algorithm with a nucleic acid amplification test (NAAT) followed by toxin assay are not reported to the National Healthcare Safety Network as a laboratory-identified CDI event if they are NAAT positive (+)/toxin negative (-). We compared NAAT+/toxin- and NAAT+/toxin+ patients and identified factors associated with CDI treatment among NAAT+/toxin- patients. DESIGN: Retrospective observational study. SETTING: The study was conducted across 36 laboratories at 5 Emerging Infections Program sites. PATIENTS: We defined a CDI case as a positive test detected by this 2-step algorithm during 2018-2020 in a patient aged ≥1 year with no positive test in the previous 8 weeks. METHODS: We used multivariable logistic regression to compare CDI-related complications and recurrence between NAAT+/toxin- and NAAT+/toxin+ cases. We used a mixed-effects logistic model to identify factors associated with treatment in NAAT+/toxin- cases. RESULTS: Of 1,801 cases, 1,252 were NAAT+/toxin-, and 549 were NAAT+/toxin+. CDI treatment was given to 866 (71.5%) of 1,212 NAAT+/toxin- cases versus 510 (95.9%) of 532 NAAT+/toxin+ cases (P < .0001). NAAT+/toxin- status was protective for recurrence (adjusted odds ratio [aOR], 0.65; 95% CI, 0.55-0.77) but not CDI-related complications (aOR, 1.05; 95% CI, 0.87-1.28). Among NAAT+/toxin- cases, white blood cell count ≥15,000/µL (aOR, 1.87; 95% CI, 1.28-2.74), ≥3 unformed stools for ≥1 day (aOR, 1.90; 95% CI, 1.40-2.59), and diagnosis by a laboratory that provided no or neutral interpretive comments (aOR, 3.23; 95% CI, 2.23-4.68) were predictors of CDI treatment. CONCLUSION: Use of this 2-step algorithm likely results in underreporting of some NAAT+/toxin- cases with clinically relevant CDI. Disease severity and laboratory interpretive comments influence treatment decisions for NAAT+/toxin- cases.

After the hurricanes in 2017 in the U.S. Caribbean, it was essential to rebuild, strengthen, and sustain essential environmental health (EH) services and systems. The National Environmental Health Association, in partnership with the Centers for Disease Control and Prevention, developed an online mentorship program for newly hired and existing EH staff and health department leadership in Caribbean health departments. Participants were provided with both practical and didactic learning and were allowed to evaluate the program. Both mentors and mentees were highly satisfied with the knowledge and skills acquired, and mentees expressed it was relevant to their daily work. Based on the findings, we recommend both an online and a hybrid mentorship program for leadership- and inspector-level workforces in EH and potentially in other fields.

Since the initial publication of A Compendium of Strategies to Prevent Healthcare-Associated Infections in Acute Care Hospitals in 2008, the prevention of healthcare-associated infections (HAIs) has continued to be a national priority. Progress in healthcare epidemiology, infection prevention, antimicrobial stewardship, and implementation science research has led to improvements in our understanding of effective strategies for HAI prevention. Despite these advances, HAIs continue to affect ∼1 of every 31 hospitalized patients, leading to substantial morbidity, mortality, and excess healthcare expenditures, and persistent gaps remain between what is recommended and what is practiced.The widespread impact of the coronavirus disease 2019 (COVID-19) pandemic on HAI outcomes in acute-care hospitals has further highlighted the essential role of infection prevention programs and the critical importance of prioritizing efforts that can be sustained even in the face of resource requirements from COVID-19 and future infectious diseases crises.The Compendium: 2022 Updates document provides acute-care hospitals with up-to-date, practical expert guidance to assist in prioritizing and implementing HAI prevention efforts. It is the product of a highly collaborative effort led by the Society for Healthcare Epidemiology of America (SHEA), the Infectious Disease Society of America (IDSA), the Association for Professionals in Infection Control and Epidemiology (APIC), the American Hospital Association (AHA), and The Joint Commission, with major contributions from representatives of organizations and societies with content expertise, including the Centers for Disease Control and Prevention (CDC), the Pediatric Infectious Disease Society (PIDS), the Society for Critical Care Medicine (SCCM), the Society for Hospital Medicine (SHM), the Surgical Infection Society (SIS), and others.

Strategies to prevent catheter-associated urinary tract infections (CAUTIs) | Essential practices | Infrastructure and resources | 1 Perform a CAUTI risk assessment and implement an organization-wide program to identify and remove catheters that are no longer necessary using 1 or | more methods documented to be effective. (Quality of evidence: MODERATE) | 2 Provide appropriate infrastructure for preventing CAUTI. (Quality of evidence: LOW) | 3 Provide and implement evidence-based protocols to address multiple steps of the urinary catheter life cycle: catheter appropriateness (step 0), insertion | technique (step 1), maintenance care (step 2), and prompt removal (step 3) when no longer appropriate. (Quality of evidence: LOW) | 4 Ensure that only trained healthcare personnel (HCP) insert urinary catheters and that competency is assessed regularly. (Quality of evidence: LOW) | 5 Ensure that supplies necessary for aseptic technique for catheter insertion are available and conveniently located. (Quality of evidence: LOW) | 6 Implement a system for documenting the following in the patient record: physician order for catheter placement, indications for catheter insertion, date | and time of catheter insertion, name of individual who inserted catheter, nursing documentation of placement, daily presence of a catheter and | maintenance care tasks, and date and time of catheter removal. Record criteria for removal and justification for continued use. (Quality of evidence: | LOW) | 7 Ensure that sufficiently trained HCP and technology resources are available to support surveillance for catheter use and outcomes. (Quality of evidence: | LOW) | 8 Perform surveillance for CAUTI if indicated based on facility risk assessment or regulatory requirements. (Quality of evidence: LOW) | 9 Standardize urine culturing by adapting an institutional protocol for appropriate indications for urine cultures in patients with and without indwelling | catheters. Consider incorporating these indications into the electronic medical record, and review indications for ordering urine cultures in the CAUTI | risk assessment. (Quality of evidence: LOW) | Education and training | 1 Educate HCP involved in the insertion, care, and maintenance of urinary catheters about CAUTI prevention, including alternatives to indwelling | catheters, and procedures for catheter insertion, management, and removal. (Quality of evidence: LOW) | 2 Assess healthcare professional competency in catheter use, catheter care, and maintenance. (Quality of evidence: LOW) | 3 Educate HCP about the importance of urine-culture stewardship and provide indications for urine cultures. (Quality of evidence: LOW) | 4 Provide training on appropriate collection of urine. Specimens should be collected and should arrive at the microbiology laboratory as soon as possible, | preferably within an hour. If delay in transport to the laboratory is expected, samples should be refrigerated (no more than 24 hours) or collected in | preservative urine transport tubes. (Quality of evidence: LOW) | 5 Train clinicians to consider other methods for bladder management, such as intermittent catheterization or external male or female collection devices, | when appropriate, before placing an indwelling urethral catheter. (Quality of evidence: LOW) | 6 Share data in a timely fashion and report to appropriate stakeholders. (Quality of evidence: LOW) | Insertion of indwelling catheters | 1 Insert urinary catheters only when necessary for patient care and leave in place only as long as indications remain. (Quality of evidence: MODERATE) | 2 Consider other methods for bladder management such as intermittent catheterization, or external male or female collection devices, when appropriate. | (Quality of evidence: LOW) | 3 Use appropriate technique for catheter insertion. (Quality of evidence: MODERATE). | 4 Consider working in pairs to help perform patient positioning and monitor for potential contamination during placement. (Quality of evidence: LOW) | 5 Practice hand hygiene (based on CDC or WHO guidelines) immediately before insertion of the catheter and before and after any manipulation of the | catheter site or apparatus. (Quality of evidence: LOW) | 6 Insert catheters following aseptic technique and using sterile equipment. (Quality of evidence: LOW) | 7 Use sterile gloves, drape, and sponges, a sterile antiseptic solution for cleaning the urethral meatus, and a sterile single-use packet of lubricant jelly for | insertion. (Quality of evidence: LOW) | 8 Use a catheter with the smallest feasible diameter consistent with proper drainage to minimize urethral trauma but consider other catheter types and | sizes when warranted for patients with anticipated difficult catheterization to reduce the likelihood that a patient will experience multiple, sometimes | traumatic, catheterization attempts. (Quality of evidence: LOW) | Management of indwelling catheters | 1 Properly secure indwelling catheters after insertion to prevent movement and urethral traction. (Quality of evidence: LOW) | 2 Maintain a sterile, continuously closed drainage system. (Quality of evidence: LOW) | 3 Replace the catheter and the collecting system using aseptic technique when breaks in aseptic technique, disconnection, or leakage occur. (Quality of | evidence: LOW) | 4 For examination of fresh urine, collect a small sample by aspirating urine from the needleless sampling port with a sterile syringe/cannula adaptor after | cleansing the port with disinfectant. (Quality of evidence: LOW) | (Continued) | 2 Deborah S. Yokoe et al | https://doi.org/10.1017/ice.2023.138 Published online by Cambridge University Press | Strategies to prevent central-line–associated bloodstream infections (CLABSIs) | (Continued ) | 5 Facilitate timely transport of urine samples to laboratory. If timely transport is not feasible, consider refrigerating urine samples or using samplecollection cups with preservatives. Obtain larger volumes of urine for special analyses (eg, 24-hour urine) aseptically from the drainage bag. (Quality of | evidence: LOW) | 6 Maintain unobstructed urine flow. (Quality of evidence: LOW) | 7 Employ routine hygiene. Cleaning the meatal area with antiseptic solutions is an unresolved issue, though emerging literature supports chlorhexidine | use prior to catheter insertion. Alcohol-based products should be avoided given concerns about the alcohol causing drying of the mucosal tissues. | (Quality of evidence: LOW) | Additional approaches | 1 Develop a protocol for standardizing diagnosis and management of postoperative urinary retention, including nurse-directed use of intermittent | catheterization and use of bladder scanners when appropriate as alternatives to indwelling urethral catheterization. (Quality of evidence: MODERATE) | 2 Establish a system for analyzing and reporting data on catheter use and adverse events from catheter use. (Quality of evidence: LOW) | 3 Establish a system for defining, analyzing, and reporting data on non–catheter-associated UTIs, particularly UTIs associated with the use of devices | being used as alternatives to indwelling urethral catheters. (Quality of evidence: LOW) | Essential practices | Before insertion | 1 Provide easy access to an evidence-based list of indications for CVC use to minimize unnecessary CVC placement. (Quality of evidence: LOW) | 2 Require education and competency assessment of healthcare personnel (HCP) involved in insertion, care and maintenance of CVCs about CLABSI | prevention. (Quality of evidence: MODERATE) | 3 Bathe ICU patients aged >2 months with a chlorhexidine preparation on a daily basis. (Quality of evidence: HIGH) | At insertion | 1 In ICU and non-ICU settings, a facility should have a process in place, such as a checklist, to ensure adherence to infection prevention practices at the | time of CVC insertion. (Quality of evidence: MODERATE) | 2 Perform hand hygiene prior to catheter insertion or manipulation. (Quality of evidence: MODERATE) | 3 The subclavian site is preferred to reduce infectious complications when the catheter is placed in the ICU setting. (Quality of evidence: HIGH) | 4 Use an all-inclusive catheter cart or kit. (Quality of evidence: MODERATE) | 5 Use ultrasound guidance for catheter insertion. (Quality of evidence: HIGH) | 6 Use maximum sterile barrier precautions during CVC insertion. (Quality of evidence: MODERATE) | After insertion | 1 Ensure appropriate nurse-to-patient ratio and limit use of float nurses in ICUs. (Quality of evidence: HIGH) | 2 Use chlorhexidine-containing dressings for CVCs in patients aged >2 months. (Quality of evidence: HIGH) | 3 For nontunneled CVCs in adults and children, change transparent dressings and perform site care with a chlorhexidine-based antiseptic at least every 7 | days or immediately if the dressing is soiled, loose, or damp. Change gauze dressings every 2 days or earlier if the dressing is soiled, loose, or damp. | (Quality of evidence: MODERATE) | 4 Disinfect catheter hubs, needleless connectors, and injection ports before accessing the catheter. (Quality of evidence: MODERATE) | 5 Remove nonessential catheters. (Quality of evidence: MODERATE) | 6 Routine replacement of administration sets not used for blood, blood products, or lipid formulations can be performed at intervals up to 7 days. | (Quality of evidence: HIGH) | 7 Perform surveillance for CLABSI in ICU and non-ICU settings. (Quality of evidence: HIGH) | Additional approaches | 1 Use antiseptic or antimicrobial-impregnated CVCs. (Quality of evidence: HIGH in adult patients; MODERATE in pediatric patients) | 2 Use antimicrobial lock therapy for long-term CVCs. (Quality of evidence: HIGH) | 3 Use recombinant tissue plasminogen activating factor (rt-PA) once weekly after hemodialysis in patients undergoing hemodialysis through a CVC. | (Quality of evidence: HIGH) | 4 Utilize infusion or vascular access teams for reducing CLABSI rates. (Quality of evidence: LOW) | 5 Use antimicrobial ointments for hemodialysis catheter-insertion sites. (Quality of evidence: HIGH) | 6 Use an antiseptic-containing hub, connector cap, or port protector to cover connectors. (Quality of evidence: MODERATE) | Infection Control & Hospital Epidemiology 3 | https://doi.org/10.1017/ice.2023.138 Published online by Cambridge University Press | Strategies to prevent Clostridioides difficile infections (CDIs) | Strategies to prevent methicillin-resistant Staphylococcus aureus (MRSA) transmission and infection | Essential practices | 1 Encourage appropriate use of antimicrobials through implementation of an antimicrobial stewardship program. (Quality of evidence: MODERATE) | 2 Implement diagnostic stewardship practices for ensuring appropriate use and interpretation of C. difficile testing. (Quality of evidence: LOW) | 3 Use contact precautions for infected patients, single-patient room preferred. (Quality of evidence: LOW for hand hygiene; MODERATE for gloves; LOW | for gowns; LOW for single-patient room) | 4 Adequately clean and disinfect equipment and the environment of patients with CDI. (Quality of evidence: LOW for equipment; LOW for environment) | 5 Assess the adequacy of room cleaning. (Quality of evidence: LOW) | 6 Implement a laboratory-based alert system to provide immediate notification to infection preventionists and clinical personnel about newly diagnosed | patients with CDI. (Quality of evidence: LOW) | 7 Conduct CDI surveillance and analyze and report CDI data. (Quality of evidence: LOW) | 8 Educate healthcare personnel (HCP), environmental service personnel, and hospital administration about CDI. (Quality of evidence: LOW) | 9 Educate patients and their families about CDI as appropriate. (Quality of evidence: LOW) | 10 Measure compliance with CDC or WHO hand hygiene and contact precaution recommendations. (Quality of evidence: LOW) | Additional approaches | 1 Intensify the assessment of compliance with process measures. (Quality of evidence: LOW) | 2 Perform hand hygiene with soap and water as the preferred method following care of or interacting with the healthcare environment of a patient with | CDI. (Quality of evidence: LOW) | 3 Place patients with diarrhea on contact precautions while C. difficile testing is pending. (Quality of evidence: LOW) | 4 Prolong the duration of contact precautions after the patient becomes asymptomatic until hospital discharge. (Quality of evidence: LOW) | 5 Use an EPA-approved sporicidal disinfectant, such as diluted (1:10) sodium hypochlorite, for environmental cleaning and disinfection. Implement a | system to coordinate with environmental services if it is determined that sodium hypochlorite is needed for environmental disinfection. (Quality of | evidence: LOW) | Essential practices | 1 Implement an MRSA monitoring program. (Quality of evidence: LOW) | 2 Conduct an MRSA risk assessment. (Quality of evidence: LOW) | 3 Promote compliance with CDC or World Health Organization (WHO) hand hygiene recommendations. (Quality of evidence: MODERATE) | 4 Use contact precautions for MRSA-colonized and MRSA-infected patients. A facility that chooses or has already chosen to modify the use of contact | precautions for some or all of these patients should conduct an MRSA-specific risk assessment to evaluate the facility for transmission risks and to | assess the effectiveness of other MRSA risk mitigation strategies (eg, hand hygiene, cleaning and disinfection of the environment, single occupancy | patient rooms) and should establish a process for ongoing monitoring, oversight, and risk assessment. (Quality of evidence: MODERATE) | 5 Ensure cleaning and disinfection of equipment and the environment. (Quality of evidence: MODERATE) | 6 Implement a laboratory-based alert system that notifies healthcare personnel (HCP) of new MRSA-colonized or MRSA-infected patients in a timely | manner. (Quality of evidence: LOW) | 7 Implement an alert system that identifies readmitted or transferred MRSA-colonized or MRSA-infected patients. (Quality of evidence: LOW) | 8 Provide MRSA data and outcome measures to key stakeholders, including senior leadership, physicians, nursing staff, and others. (Quality of evidence: | LOW) | 9 Educate healthcare personnel about MRSA. (Quality of evidence: LOW) | 10 Educate patients and families about MRSA. (Quality of evidence: LOW) | 11 Implement an antimicrobial stewardship program. (Quality of evidence: LOW) | Additional approaches | Active surveillance testing (AST) | 1 Implement an MRSA AST program for select patient populations as part of a multifaceted strategy to control and prevent MRSA. (Quality of evidence: | MODERATE) Note: specific populations may have different evidence ratings. | 2 Active surveillance for MRSA in conjunction with decolonization can be performed in targeted populations prior to surgery to prevent postsurgical | MRSA infection. (Quality of evidence: MODERATE) | (Continued) | 4 Deborah S. Yokoe et al | https://doi.org/10.1017/ice.2023.138 Published online by Cambridge University Press | Strategies to prevent surgical-site infections (SSIs) | (Continued ) | 3 Active surveillance with contact precautions is inferior to universal decolonization for reduction of MRSA clinical isolates in adult ICUs. (Quality of | evidence: HIGH) | 4 Hospital-wide active surveillance for MRSA can be used in conjunction with contact precautions to reduce the incidence of MRSA infection. (Quality of | evidence: MODERATE) | 5 Active surveillance can be performed in the setting of an MRSA outbreak or evidence of ongoing transmission of MRSA within a unit as part of a | multifaceted strategy to halt transmission. (Quality of evidence: MODERATE) | Screen healthcare personnel for MRSA infection or colonization | 1 Screen HCP for MRSA infection or colonization if they are epidemiologically linked to a cluster of MRSA infections. (Quality of evidence: LOW) | MRSA decolonization therapy | 1 Use universal decolonization (ie, daily CHG bathing plus 5 days of nasal decolonization) for all patients in adult ICUs to reduce endemic MRSA clinical | cultures. (Quality of evidence: HIGH) | 2 Perform preoperative nares screening with targeted use of CHG and nasal decolonization in MRSA carriers to reduce MRSA SSI from surgical | procedures involving implantation of hardware. (Quality of evidence: MODERATE) | 3 Screen for MRSA and provide targeted decolonization with CHG bathing and nasal decolonization to MRSA carriers in surgical units to reduce | postoperative MRSA inpatient infections. (Quality of evidence: MODERATE) | 4 Provide CHG bathing plus nasal decolonization to known MRSA carriers outside the ICU with medical devices, specifically central lines, midline | catheters, and lumbar drains to reduce MRSA clinical cultures. (Quality of evidence: MODERATE) | 5 Consider postdischarge decolonization of MRSA carriers to reduce postdischarge MRSA infections and readmissions. (Quality of evidence: HIGH) | 6 Neonatal ICUs should consider targeted or universal decolonization during times of above-average MRSA infection rates or targeted decolonization for | patients at high risk of MRSA infection (eg, low birth weight, indwelling devices, or prior to high-risk surgeries). (Quality of evidence: MODERATE) | 7 Burn units should consider targeted or universal decolonization during times of above-average MRSA infection rates. (Quality of evidence: MODERATE) | 8 Consider targeted or universal decolonization of hemodialysis patients. (Quality of evidence: MODERATE) | 9 Decolonization should be strongly considered as part of a multimodal approach to control MRSA outbreaks. (Quality of evidence: MODERATE) | Universal use of gowns and gloves | 1 Use gowns and gloves when providing care to or entering the room of any adult ICU patient, regardless of MRSA colonization status. (Quality of | evidence: MODERATE) | Essential practices | 1 Administer antimicrobial prophylaxis according to evidence-based standards and guidelines. (Quality of evidence: HIGH) | 2 Use a combination of parenteral and oral antimicrobial prophylaxis prior to elective colorectal surgery to reduce the risk of SSI. (Quality of evidence: | HIGH) | 3 Decolonize surgical patients with an anti-staphylococcal agent in the preoperative setting for orthopedic and cardiothoracic procedures. (Quality of | evidence: HIGH) | Decolonize surgical patients in other procedures at high risk of staphylococcal SSI, such as those involving prosthetic material. (Quality of evidence: | LOW) | 4 Use antiseptic-containing preoperative vaginal preparation agents for patients undergoing cesarean delivery or hysterectomy. (Quality of evidence: | MODERATE) | 5 Do not remove hair at the operative site unless the presence of hair will interfere with the surgical procedure. (Quality of evidence: MODERATE) | 6 Use alcohol-containing preoperative skin preparatory agents in combination with an antiseptic. (Quality of evidence: HIGH) | 7 For procedures not requiring hypothermia, maintain normothermia (temperature >35.5 °C) during the perioperative period. (Quality of evidence: HIGH). | 8 Use impervious plastic wound protectors for gastrointestinal and biliary tract surgery. (Quality of evidence: HIGH) | 9 Perform intraoperative antiseptic wound lavage. (Quality of evidence: MODERATE) | 10 Control blood glucose level during the immediate postoperative period for all patients. (Quality of evidence: HIGH) | 11 Use a checklist and/or bundle to ensure compliance with best practices to improve surgical patient safety. (Quality of evidence: HIGH) | 12 Perform surveillance for SSI. (Quality of evidence: MODERATE) | 13 Increase the efficiency of surveillance by utilizing automated data. (Quality of evidence: MODERATE) | 14 Provide ongoing SSI rate feedback to surgical and perioperative personnel and leadership. (Quality of evidence: MODERATE) | 15 Measure and provide feedback to healthcare personnel (HCP) regarding rates of compliance with process measures. (Quality of evidence: LOW) | (Continued) | Infection Control & Hospital Epidemiology 5 | https://doi.org/10.1017/ice.2023.138 Published online by Cambridge University Press | Strategies to prevent ventilator-associated pneumonia (VAP) and ventilator-associated events (VAEs) | Adult patients | (Continued ) | 16 Educate surgeons and perioperative personnel about SSI prevention measures. (Quality of evidence: LOW) | 17 Educate patients and their families about SSI prevention as appropriate. (Quality of evidence: LOW) | 18 Implement policies and practices to reduce the risk of SSI for patients that align with applicable evidence-based standards, rules and regulations, and | medical device manufacturer instructions for use. (Quality of evidence: MODERATE) | 19 Observe and review operating room personnel and the environment of care in the operating room and in central sterile reprocessing. (Quality of | evidence: LOW) | Additional approaches | 1 Perform an SSI risk assessment. (Quality of evidence: LOW) | 2 Consider use of negative-pressure dressings in patients who may benefit. (Quality of evidence: MODERATE) | 3 Observe and review practices in the preoperative clinic, post-anesthesia care unit, surgical intensive care unit, and/or surgical ward. (Quality of | evidence: MODERATE) | 4 Use antiseptic-impregnated sutures as a strategy to prevent SSI. (Quality of evidence: MODERATE) | Essential practices | Interventions with little risk of harm and that are associated with decreases in duration of mechanical ventilation, length of stay, mortality, antibiotic utilization, | and/or costs | Avoid intubation and prevent reintubation if possible. | 1 Use high flow nasal oxygen or non-invasive positive pressure ventilation (NIPPV) as appropriate, whenever safe and feasible. (Quality of evidence: HIGH) | Minimize sedation. | 1 Minimize sedation of ventilated patients whenever possible. (Quality of evidence: HIGH) | 2 Preferentially use multimodal strategies and medications other than benzodiazepines to manage agitation. (Quality of evidence: HIGH) | 3 Utilize a protocol to minimize sedation. (Quality of evidence: HIGH) | 4 Implement a ventilator liberation protocol. (Quality of evidence: HIGH) | Maintain and improve physical conditioning. | 1 Provide early exercise and mobilization. (Quality of evidence: MODERATE) | Elevate the head of the bed to 30°–45°. (Quality of evidence: LOW) | Provide oral care with toothbrushing but without chlorhexidine. (Quality of evidence: MODERATE) | Provide early enteral rather than parenteral nutrition. (Quality of evidence: HIGH) | Maintain ventilator circuits. | 1 Change the ventilator circuit only if visibly soiled or malfunctioning (or per manufacturers’ instructions) (Quality of evidence: HIGH). | Additional approaches | May decrease duration of mechanical ventilation, length of stay, and/or mortality in some populations but not in others, and they may confer some risk of harm | in some populations. | 1 Consider using selective decontamination of the oropharynx and digestive tract to decrease microbial burden in ICUs with low prevalence of antibiotic | resistant organisms. Antimicrobial decontamination is not recommended in countries, regions, or ICUs with high prevalence of antibiotic-resistant | organisms. (Quality of evidence: HIGH) | Additional approaches | May lower VAP rates, but current data are insufficient to determine their impact on duration of mechanical ventilation, length of stay, and mortality. | 1 Consider using endotracheal tubes with subglottic secretion drainage ports to minimize pooling of secretions above the endotracheal cuff in patients | likely to require >48–72 hours of intubation. (Quality of evidence: MODERATE) | 2 Consider early tracheostomy. (Quality of evidence: MODERATE) | 3 Consider postpyloric feeding tube placement in patients with gastric feeding intolerance at high risk for aspiration. (Quality of evidence: MODERATE) | 6 Deborah S. Yokoe et al | https://doi.org/10.1017/ice.2023.138 Published online by Cambridge University Press | Preterm neonatal patients | Pediatric patients | Essential practices | Confer minimal risk of harm and may lower VAP and/or PedVAE rates. | Avoid intubation. (Quality of evidence: HIGH) | Minimize duration of mechanical ventilation. (Quality of evidence: HIGH) | 1 Manage patients without sedation whenever possible. (Quality of evidence: LOW) | 2 Use caffeine therapy for apnea of prematurity within 72 hours after birth to facilitate extubation. (Quality of evidence: HIGH) | 3 Assess readiness to extubate daily. (Quality of evidence: LOW) | 4 Take steps to minimize unplanned extubation and reintubation. (Quality of evidence: LOW) | 5 Provide regular oral care with sterile water (extrapolated from practice in infants and children, no data in preterm neonates). (Quality of evidence: | LOW) | 6 Change the ventilator circuit only if visibly soiled or malfunctioning or according to the manufacturer’s instructions for use (extrapolated from studies in | adults and children, no data in preterm neonates). (Quality of evidence: LOW) | Additional approaches | Minimal risks of harm, but impact on VAP and VAE rates is unknown. | 1 Lateral recumbent positioning. (Quality of evidence: LOW) | 2 Reverse Trendelenberg positioning. (Quality of evidence: LOW) | 3 Closed or in-line suctioning. (Quality of evidence: LOW) | 4 Oral care with maternal colostrum. (Quality of evidence: MODERATE) | Essential practices | Confer minimal risk of harm and some data suggest that they may lower VAP rates, PedVAE rates, and/or duration of mechanical ventilation. | Avoid intubation. | 1 Use noninvasive positive pressure ventilation (NIPPV) or high-flow oxygen by nasal cannula whenever safe and feasible. (Quality of evidence: | MODERATE) | Minimize duration of mechanical ventilation. | 1 Assess readiness to extubate daily using spontaneous breathing trials in patients without contraindications. (Quality of evidence: MODERATE) | 2 Take steps to minimize unplanned extubations and reintubations. (Quality of evidence: LOW) | 3 Avoid fluid overload. (Quality of evidence: MODERATE) | Provide regular oral care (ie, toothbrushing or gauze if no teeth). (Quality of evidence: LOW) | Elevate the head of the bed unless medically contraindicated. (Quality of evidence: LOW) | Maintain ventilator circuits. | 1 Change ventilator circuits only when visibly soiled or malfunctioning (or per manufacturer’s instructions). (Quality of evidence: MODERATE) | 2 Remove condensate from the ventilator circuit frequently and avoid draining the condensate toward the patient. (Quality of evidence: LOW) | Endotracheal tube selection and management | 1 Use cuffed endotracheal tubes. (Quality of evidence: LOW) | 2 Maintain cuff pressure and volume at the minimal occlusive settings to prevent clinically significant air leaks around the endotracheal tube, typically | 20-25cm H2O. This “minimal leak” approach is associated with lower rates of post-extubation stridor. (Quality of evidence: LOW) | 3 Suction oral secretions before each position change. (Quality of evidence: LOW) | Additional approaches | Minimal risks of harm and some evidence of benefit in adult patients but data in pediatric populations are limited. | 1 Minimize sedation. (Quality of evidence: MODERATE) | 2 Use endotracheal tubes with subglottic secretion drainage ports for patients ≥10 years of age. (Quality of evidence: LOW) | 3 Consider early tracheostomy. (Quality of evidence: LOW) | Infection Control & Hospital Epidemiology 7 | https://doi.org/10.1017/ice.2023.138 Published online by Cambridge University Press | Strategies to prevent nonventilator hospital-acquired pneumonia (NV-HAP) | Strategies to prevent healthcare-associated infections through hand hygiene | Essential practices | Promote the maintenance of healthy hand skin and nails. (Quality of evidence: HIGH) | 1 Promote the preferential use of alcohol-based hand sanitizer (ABHS) in most clinical situations. (Quality of evidence: HIGH) | 2 Perform hand hygiene as indicated by CDC or the WHO Five Moments. (Quality of evidence: HIGH) | 3 Include fingernail care in facility-specific policies related to hand hygiene. (Quality of evidence: HIGH) | a) Healthcare personnel (HCP) should maintain short, natural fingernails. | b) Nails should not extend past the fingertip. | c) HCP who provide direct or indirect care in high-risk areas | (eg, ICU or perioperative) should not wear artificial fingernail extenders. | d) Prohibitions against fingernail polish (standard or gel shellac) are at the discretion of the infection prevention program, except among scrubbed | individuals who interact with the sterile field during surgical procedures; these individuals should not wear fingernail polish or gel shellac. | 4 Engage all HCP in primary prevention of occupational irritant and allergic contact dermatitis. (Quality of evidence: HIGH) | 5 Provide cotton glove liners for HCP with hand irritation and educate these HCP on their use. (Quality of evidence: MODERATE) | Select appropriate products. | 1 For routine hand hygiene, choose liquid, gel, or foam ABHS with at least 60% alcohol. (Quality of evidence: HIGH) | 2 Involve HCP in selection of products. (Quality of evidence: HIGH) | 3 Obtain and consider manufacturers’ product-specific data if seeking ABHS with ingredients that may enhance efficacy against organisms anticipated to | be less susceptible to biocides. (Quality of evidence: MODERATE) | 4 Confirm that the volume of ABHS dispensed is consistent with the volume shown to be efficacious. (Quality of evidence: HIGH) | 5 Educate HCP about an appropriate volume of ABHS and the time required to obtain effectiveness. (Quality of evidence: HIGH) | 6 Provide facility-approved hand moisturizer that is compatible with antiseptics and gloves. (Quality of evidence: HIGH) | 7 For surgical antisepsis, use an FDA-approved surgical hand scrub or waterless surgical hand rub. (Quality of evidence: HIGH) | Ensure the accessibility of hand hygiene supplies. (Quality of evidence: HIGH) | 1 Ensure ABHS dispensers are unambiguous, visible, and accessible within the workflow of HCP. (Quality of evidence: HIGH) | 2 In private rooms, consider 2 ABHS dispensers the minimum threshold for adequate numbers of dispensers: 1 dispenser in the hallway, and 1 in the | patient room. (Quality of evidence: HIGH) | 3 In semiprivate rooms, suites, bays, and other multipatient bed configurations, consider 1 dispenser per 2 beds the minimum threshold for adequate | numbers of dispensers. Place ABHS dispensers in the workflow of HCP. (Quality of evidence: LOW) | 4 Ensure that the placement of hand hygiene supplies (eg, individual pocket-sized dispensers, bed mounted ABHS dispenser, single use pump bottles) is | easily accessible for HCP in all areas where patients receive care. (Quality of evidence: HIGH) | 5 Evaluate for the risk of intentional consumption. Utilize dispensers that mitigate this risk, such as wall-mounted dispensers that allow limited numbers | of activations within short periods (eg, 5 seconds). (Quality of evidence: LOW) | 6 Have surgical hand rub and scrub available in perioperative areas. (Quality of evidence: HIGH) | 7 Consider providing ABHS hand rubs or handwash with FDA-approved antiseptics for use in procedural areas and prior to high-risk bedside procedures | (eg, central-line insertion). (Quality of evidence: LOW) | (Continued) | Practices supported by interventional studies suggesting lower | NV-HAP rates | 1 Provide regular oral care. | 2 Diagnose and manage dysphagia. | 3 Provide early mobilization. | 4 Implement multimodal interventions to prevent viral infections. | 5 Use prevention bundles. | 8 Deborah S. Yokoe et al | https://doi.org/10.1017/ice.2023.138 Published online by Cambridge University Press | Implementing strategies to prevent healthcare-associated infections | Standard approach to implementation | Examples of implementation frameworks | (Continued ) | Ensure appropriate glove use to reduce hand and environmental contamination. (Quality of Evidence: HIGH) | 1 Use gloves for all contact with the patient and environment as indicated by standard and contact precautions during the care of individuals with | organisms confirmed to be less susceptible to biocides (e.g., C. difficile or norovirus) | 2 Educate HCP about the potential for self-contamination and environmental contamination when gloves are worn. (Quality of evidence: HIGH) | 3 Educate and confirm the ability of HCP to doff gloves in a manner that avoids contamination. (Quality of evidence: HIGH) | Take steps to reduce environmental contamination associated with sinks and sink drains. (Quality of evidence: HIGH) | Monitor adherence to hand hygiene. (Quality of evidence: HIGH) | Provide timely and meaningful feedback to enhance a culture of safety. (Quality of evidence: MODERATE) | Additional approaches during outbreaks | 1 Consider educating HCP using a structured approach (eg, WHO Steps) for handwashing or hand sanitizing. Evaluate HCP adherence to technique. | (Quality of evidence: LOW) | 2 For waterborne pathogens of premise plumbing, consider disinfection of sink drains using an EPA-registered disinfectant with claims against biofilms. | Consult with state or local public health for assistance in determining appropriate protocols for use and other actions needed to ensure safe supply. | (Quality of evidence: LOW) | 3 For C. difficile and norovirus, in addition to contact precautions, encourage hand washing with soap and water after the care of patients with known or | suspected infections. (Quality of evidence: LOW) | 1 Assess determinants of change and | classify as follows: | • Facilitators: promote practice or | change, or | • Barriers: hinder practice or change | Individual level: healthcare personnel, leaders, patients, and visitors’ preferences, needs, attitudes, and | knowledge. | Facility level: team composition, communication, culture, capacity, policies, resources. | Partners: degree of support and buy-in. | 2 Choose measures Measurement methods must be appropriate for the question(s) they seek to answer and adhere to the | methods’ data collection and analysis rules: | • Outcome measure: ultimate goal (eg, HAI reduction). | • Process measure: action reliability (eg, bundle adherence). | • Balancing measure: undesired outcome of change (eg, staff absences due to required vaccine side effects). | 3 Select framework(s) See below and “Implementing Strategies to Prevent Infections in Acute Care Settings” (Table 3) | 32 | Framework Published Experience Resources | 4Es Settings | • Healthcare facilities | • Large-scale projects including multiple | sites | Infection prevention and control | • HAI prevention (including mortality | reduction and cost savings) | • 4Es Framework11 | • HAI reduction12–14 | • Mortality reduction15 | • Cost savings16 | Behavior Change Wheel Settings | • Community-based practice | • Healthcare facilities | Healthy behaviors | • Smoking cessation | • Obesity prevention | • Increased physical activity | Infection prevention and control | • Hand hygiene adherence | • Antibiotic prescribing17 | • Behavior Change Wheel: A Guide to Designing Interventions18 | • Stand More at Work (SMArT Work)19 | (Continued) | Infection Control & Hospital Epidemiology 9 | https://doi.org/10.1017/ice.2023.138 Published online by Cambridge University Press | Acknowledgments. The Compendium Partners thank the authors for their | dedication to this work, including maintaining adherence to the rigorous | process for the development of the Compendium: 2022 Updates, involving but | not limited to screening of thousands of articles; achieving multilevel consensus; | and consideration of, response to, and incorporation of many organizations’ | feedback and comments. We acknowledge these efforts especially because they | occurred as the authors handled the demands of the COVID-19 pandemic. The | authors thank Valerie Deloney, MBA, for her organizational expertise in the | development of this manuscript and Janet Waters, MLS, BSN, RN, for her | expertise in developing the strategies used for the literature searches that | informed this manuscript. The authors thank the many individuals and | organizations who gave their time and expertise to review and provide | (Continued ) | Comprehensive Unit-based | Safety Program (CUSP) | Settings | • Intensive care units | • Ambulatory centers | Improvements | • Antibiotic prescribing | • CLABSI prevention | • CAUTI prevention | • CUSP Implementation Toolkit20 | • AHA/HRET: Eliminating CAUTI (Stop CAUTI)21 | • AHRQ Toolkit to Improve Safety in Ambulatory Surgery Centers22 | European Mixed Methods Settings | • European institutions of varied | healthcare systems and cultures | Improvements: | • CLABSI prevention | • Hand hygiene | • PROHIBIT: Description and Materials23 | Getting to Outcomes (GTO)® Settings | • Community programs and services | Improvements | • Sexual health promotion | • Dual-disorder treatment program in | veterans | • Community emergency preparedness | • RAND Guide for Emergency Preparedness24 (illustrated overview of GTO® methodology) | Model for Improvement Settings | • Healthcare (inpatient, perioperative, | ambulatory) | • Public health | Interventions | • PPE use | • HAI prevention | • Public health process evaluation | • Institute for Healthcare Improvement25 | • The Improvement Guide26 | • Deming’s System of Profound Knowledge27 | Reach, Effectiveness, Adoption, | Implementation, Maintenance | (RE-AIM) | Settings | • Healthcare | • Public health | • Community programs | • Sexual health | Evaluations | • Antimicrobial stewardship in the ICU | • Clinical practice guidelines for STIs | • Promotion of vaccination | • Implementation of contact tracing | • RE-AIM.org28 | • Understanding and applying the RE-AIM framework: Clarifications and | resources29 | Replicating Effective Practices | (REP) | Settings | • Healthcare | • Public health | • HIV prevention | Interventions that have produced | positive results are reframed for local | relevance | CDC Compendium of HIV Prevention Interventions with Evidence of | Effectiveness30 (see Section C, Intervention Checklist) | Theoretical Domains Settings | • Healthcare (inpatient, perioperative, | ambulatory) | • Community (individual and communitybased behaviors) | Health maintenance | • Diabetes management in primary care | • Pregnancy weight management | HCP practice | • ICU blood transfusion | • Selective GI tract decontamination | • Preoperative testing | • Spine imaging | • Hand hygiene

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident hospitalizations, incident cases, incident deaths, and cumulative deaths due to COVID-19 at national, state, and county levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages.Competing Interest StatementAV, MC, and APP report grants from Metabiota Inc outside the submitted work. Funding StatementFor teams that reported receiving funding for their work, we report the sources and disclosures below: AIpert-pwllnod: Natural Sciences and Engineering Research Council of Canada; Caltech-CS156: Gary Clinard Innovation Fund; CEID-Walk: University of Georgia; CMU-TimeSeries: CDC Center of Excellence, gifts from Google and Facebook; COVIDhub: This work has been supported by the US Centers for Disease Control and Prevention (1U01IP001122) and the National Institutes of General Medical Sciences (R35GM119582). The content is solely the responsibility of the authors and does not necessarily represent the official views of CDC, NIGMS or the National Institutes of Health; Johannes Bracher was supported by the Helmholtz Foundation via the SIMCARD Information &amp; Data Science Pilot Project; Tilmann Gneiting gratefully acknowledges support by the Klaus Tschira Foundation; CU-select: NSF DMS-2027369 and a gift from the Morris-Singer Foundation; DDS-NBDS: NSF III-1812699; epiforecasts-ensemble1: Wellcome Trust (210758/Z/18/Z) FDANIHASU: supported by the Intramural Research Program of the NIH/NIDDK; GT_CHHS-COVID19: William W. George Endowment, Virginia C. and Joseph C. Mello Endowment, NSF DGE-1650044, NSF MRI 1828187, research cyberinfrastructure resources and services provided by the Partnership for an Advanced Computing Environment (PACE) at Georgia Tech, and the following benefactors at Georgia Tech: Andrea Laliberte, Joseph C. Mello, Richard Rick E. &amp; Charlene Zalesky, and Claudia &amp; Paul Raines, CDC MInD-Healthcare U01CK000531-Supplement; IHME: This work was supported by the Bill &amp; Melinda Gates Foundation, as well as funding from the state of Washington and the National Science Foundation (award no. FAIN: 2031096); Imperial-ensemble1: SB acknowledges funding from the Wellcome Trust (219415); Institute of Business Forecasting: IBF; IowaStateLW-STEM: NSF DMS-1916204, Iowa State University Plant Sciences Institute Scholars Program, NSF DMS-1934884, Laurence H. Baker Center for Bioinformatics and Biological Statistics; IUPUI CIS: NSF; JHU_CSSE-DECOM: JHU CSSE: National Science Foundation (NSF) RAPID Real-time Forecasting of COVID-19 risk in the USA. 2021-2022. Award ID: 2108526. National Science Foundation (NSF) RAPID Development of an interactive web-based dashboard to track COVID-19 in real-time. 2020. Award ID: 2028604; JHU_IDD-CovidSP: State of California, US Dept of Health and Human Services, US Dept of Homeland Security, Johns Hopkins Health System, Office of the Dean at Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University Modeling and Policy Hub, Centers for Disease Control and Prevention (5U01CK000538-03), University of Utah Immunology, Inflammation, &amp; Infectious Disease Initiative (26798 Seed Grant); JHU_UNC_GAS-StatMechP ol: NIH NIGMS: R01GM140564; JHUAPL-Bucky: US Dept of Health and Human Services; KITmetricslab-select_ensemble: Daniel Wolffram gratefully acknowledges support by the Klaus Tschira Foundation; LANL-GrowthRate: LANL LDRD 20200700ER; MIT-Cassandra: MIT Quest for Intelligence; MOBS-GLEAM_COVID: COVID Supplement CDC-HHS-6U01IP001137-01; CA NU38OT000297 from the Council of State and Territorial Epidemiologists (CSTE); NotreDame-FRED: NSF RAPID DEB 2027718; NotreDame-mobility: NSF RAPID DEB 2027718; PSI-DRAFT: NSF RAPID Grant # 2031536; QJHong-Encounter: NSF DMR-2001411 and DMR-1835939; SDSC_ISG-TrendModel: The development of the dashboard was partly funded by the Fondation Privee des Hopitaux Universitaires de Geneve; UA-EpiCovDA: NSF RAPID Grant # 2028401; UChicagoCHATTOPADHYAY-UnIT: Defense Advanced Research Projects Agency (DARPA) #HR00111890043/P00004 (I. Chattopadhyay, University of Chicago); UCSB-ACTS: NSF RAPID IIS 2029626; UCSD_NEU-DeepGLEAM: Google Faculty Award, W31P4Q-21-C-0014; UMass-MechBayes: NIGMS #R35GM119582, NSF #1749854, NIGMS #R35GM119582; UMich-RidgeTfReg: This project is funded by the University of Michigan Physics Department and the University of Michigan Office of Research; UVA-Ensemble: National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and Virginia Dept of Health Grant VDH-21-501-0141; Wadnwani_AI-BayesOpt: This study is made possible by the generous support of the American People through the United States Agency for International Development (USAID). The work described in this article was implemented under the TRACETB Project, managed by WIAI under the terms of Cooperative Agreement Number 72038620CA00006. The contents of this manuscript are the sole responsibility of the authors and do not necessarily reflect the views of USAID or the United States Government; WalmartLabsML-LogForecasting: Team acknowledges Walmart to support this study Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesI confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data produced are available online at https://github.com/reichlab/covid19-forecast-hub https://github.com/reichlab/covid19-forecast-hub

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. In 2020, the COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized hundreds of thousands of specific predictions from more than 50 different academic, industry, and independent research groups. This manuscript systematically evaluates 23 models that regularly submitted forecasts of reported weekly incident COVID-19 mortality counts in the US at the state and national level. One of these models was a multi-model ensemble that combined all available forecasts each week. The performance of individual models showed high variability across time, geospatial units, and forecast horizons. Half of the models evaluated showed better accuracy than a naïve baseline model. In combining the forecasts from all teams, the ensemble showed the best overall probabilistic accuracy of any model. Forecast accuracy degraded as models made predictions farther into the future, with probabilistic accuracy at a 20-week horizon more than 5 times worse than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.Competing Interest StatementAV, MC, and APP report grants from Metabiota Inc outside the submitted work.Funding StatementFor teams that reported receiving funding for their work, we report the sources and disclosures below. CMU-TimeSeries: CDC Center of Excellence, gifts from Google and Facebook. CU-select: NSF DMS-2027369 and a gift from the Morris-Singer Foundation. COVIDhub: This work has been supported by the US Centers for Disease Control and Prevention (1U01IP001122) and the National Institutes of General Medical Sciences (R35GM119582). The content is solely the responsibility of the authors and does not necessarily represent the official views of CDC, NIGMS or the National Institutes of Health. Johannes Bracher was supported by the Helmholtz Foundation via the SIMCARD Information&amp; Data Science Pilot Project. Tilmann Gneiting gratefully acknowledges support by the Klaus Tschira Foundation. DDS-NBDS: NSF III-1812699. EPIFORECASTS-ENSEMBLE1: Wellcome Trust (210758/Z/18/Z) GT_CHHS-COVID19: William W. George Endowment, Virginia C. and Joseph C. Mello Endowments, NSF DGE-1650044, NSF MRI 1828187, research cyberinfrastructure resources and services provided by the Partnership for an Advanced Computing Environment (PACE) at Georgia Tech, and the following benefactors at Georgia Tech: Andrea Laliberte, Joseph C. Mello, Richard Rick E. &amp; Charlene Zalesky, and Claudia &amp; Paul Raines GT-DeepCOVID: CDC MInD-Healthcare U01CK000531-Supplement. NSF (Expeditions CCF-1918770, CAREER IIS-2028586, RAPID IIS-2027862, Medium IIS-1955883, NRT DGE-1545362), CDC MInD program, ORNL and funds/computing resources from Georgia Tech and GTRI. IHME: This work was supported by the Bill &amp; Melinda Gates Foundation, as well as funding from the state of Washington and the National Science Foundation (award no. FAIN: 2031096). IowaStateLW-STEM: Iowa State University Plant Sciences Institute Scholars Program, NSF DMS-1916204, NSF CCF-1934884, Laurence H. Baker Center for Bioinformatics and Biological Statistics. JHU_IDD-CovidSP: State of California, US Dept of Health and Human Services, US Dept of Homeland Security, US Office of Foreign Disaster Assistance, Johns Hopkins Health System, Office of the Dean at Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University Modeling and Policy Hub, Centers fo Disease Control and Prevention (5U01CK000538-03), University of Utah Immunology, Inflammation, &amp; Infectious Disease Initiative (26798 Seed Grant). LANL-GrowthRate: LANL LDRD 20200700ER. MOBS-GLEAM_COVID: COVID Supplement CDC-HHS-6U01IP001137-01. NotreDame-mobility and NotreDame-FRED: NSF RAPID DEB 2027718 UA-EpiCovDA: NSF RAPID Grant # 2028401. UCSB-ACTS: NSF RAPID IIS 2029626. UCSD-NEU: Google Faculty Award, DARPA W31P4Q-21-C-0014, COVID Supplement CDC-HHS-6U01IP001137-01. UMass-MechBayes: NIGMS R35GM119582, NSF 1749854. UMich-RidgeTfReg: The University of Michigan Physics Department and the University of Michigan Office of Research.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:UMass-Amherst IRBAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data and code referred to in the manuscript are publicly available. https://github.com/reichlab/covid19-forecast-hub/ https://github.com/reichlab/covidEnsembles https://zoltardata.com/project/44

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages.

Previously published guidelines provided comprehensive recommendations for detecting and preventing healthcare-associated infections (HAIs). The intent of this document is to highlight practical recommendations in a concise format designed to assist acute-care hospitals to implement and prioritize their Clostridioides difficile infection (CDI) prevention efforts. This document updates the Strategies to Prevent Clostridium difficile Infections in Acute Care Hospitals published in 2014.Reference Dubberke, Carling and Carrico1 This expert guidance document is sponsored by the Society for Healthcare Epidemiology of America (SHEA) and is the product of a collaborative effort led by SHEA, the Infectious Diseases Society of America (IDSA), the Association for Professionals in Infection Control and Epidemiology (APIC), the American Hospital Association (AHA), and The Joint Commission.

Among persons with an initial Clostridioides difficile infection (CDI) across 10 US sites in 2018 compared with 2013, 18.3% versus 21.1% had 1 recurrent CDI (rCDI) within 180 days. We observed a 16% lower adjusted risk of rCDI in 2018 versus 2013 (P<.0001).

The U.S. COVID-19 Forecast Hub aggregates forecasts of the short-term burden of COVID-19 in the United States from many contributing teams. We study methods for building an ensemble that combines forecasts from these teams. These experiments have informed the ensemble methods used by the Hub. To be most useful to policy makers, ensemble forecasts must have stable performance in the presence of two key characteristics of the component forecasts: (1) occasional misalignment with the reported data, and (2) instability in the relative performance of component forecasters over time. Our results indicate that in the presence of these challenges, an untrained and robust approach to ensembling using an equally weighted median of all component forecasts is a good choice to support public health decision makers. In settings where some contributing forecasters have a stable record of good performance, trained ensembles that give those forecasters higher weight can also be helpful.

SignificanceThis paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the United States. Results show high variation in accuracy between and within stand-alone models and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public-health action.

On September 6 and 20, 2017, Hurricanes Irma and Maria made landfall as major hurricanes in the US Caribbean Territories of the Virgin Islands and Puerto Rico with devastating effects. As part of the initial response, a public health team (PHT) was initially deployed as part of the US Department of Health and Human Services Incident Response Coordination Team. As a result of increased demands for additional expertise and resources, a public health branch (PHB) was established for coordinating a broad spectrum of public health response activities in support of the affected territories. This paper describes the conceptual framework for organizing these activities; summarizes some key public health activities and roles; outlines partner support and coordination with key agencies; and defines best practices and areas for improvement in disaster future operations. © 2021 Weston Medical Publishing. All rights reserved.

Hurricanes and other natural disasters leave behind multifaceted and complex environmental challenges that may contribute to adverse health outcomes, such as increased potential for exposure to vector-borne disease. Through an incident management system tailored for the Centers for Disease Control and Prevention (CDC), the National Center for Environmental Health/Agency for Toxic Substances and Disease Registry (NCEH/ATSDR) fulfills a leadership role in facilitating the agency's natural disaster emergency response activities through coordination with other CDC programs, liaising with other government agencies and impacted jurisdictions, and responding to requests for technical assistance. On the ground, NCEH/ATSDR deploys environmental health (EH) practitioners who provide consultation and inform mosquito control efforts from a systematic perspective. In the wake of recent hurricanes, NCEH staff mobilized to manage critical elements of the responses and to provide assets for addressing environmental hazards and conditions that contributed to the presence of mosquitoes. In this article, we describe NCEH/ATSDR's emergency response roles and responsibilities, interactions within the national emergency response framework, and provision of EH technical assistance and resources, particularly in the context of postdisaster mosquito control.

Internships are an essential component of preparing prospective college graduates for entering the practice-based field of environmental health (EH). EH professionals continually encounter events or hazards of high complexity and impact, and many experienced EH professionals are expected to retire within the next several years. Efforts are needed to ensure a supply of highly qualified and prepared graduates is available to sustain and strengthen the EH workforce. The National Environmental Public Health Internship Program (NEPHIP) addresses this need by supporting health department internships for EH students of academic programs accredited by the National Environmental Health Science and Protection Accreditation Council. We conducted an assessment to examine former NEPHIP intern and mentor experiences and perspectives on 1) how well the internships prepared interns for careers in EH and 2) to what extent the internships provided value to the host health department. Overall, the internships appeared to provide EH students with a well-rounded professional and practice-based experience, while health departments benefited from hosting interns with a foundational knowledge and college education in EH. Promoting the value of public health department EH internships could encourage more students and graduates to seek internship or employment opportunities with health departments, ultimately strengthening the EH workforce.

Mosquitoborne disease outbreaks occur every year in the United States from one or more of the arboviral diseases dengue, West Nile, LaCrosse, Eastern equine encephalitis, and Zika (1). Public opinion communicated through traditional and social media and the Internet, competing public health and resource priorities, and local conditions can impede the ability of vector control organizations to prevent and respond to outbreaks of mosquitoborne disease. The Environmental Protection Agency (EPA) and CDC performed a coordinated review of the concerns and challenges associated with continuation of mosquito surveillance and control during public health emergencies and disasters. This report highlights the first joint recommendation from EPA and CDC. Mosquito surveillance and control should be maintained by state and local mosquito control organizations to the extent that local conditions and resources will allow during public health emergencies and natural disasters. Integrated pest management (IPM) is the best approach for mosquito control (2). IPM uses a combination of methods, including both physical and chemical means of control (3). For chemical means of control, CDC and EPA recommend the use of larvicides and adulticides following the EPA label. It is imperative that public health recommendations be followed to ensure the safety of the pesticide applicator and the public.

BACKGROUND: Efforts to prevent Clostridioides difficile infection continue to expand across the health care spectrum in the United States. Whether these efforts are reducing the national burden of C. difficile infection is unclear. METHODS: The Emerging Infections Program identified cases of C. difficile infection (stool specimens positive for C. difficile in a person >/=1 year of age with no positive test in the previous 8 weeks) in 10 U.S. sites. We used case and census sampling weights to estimate the national burden of C. difficile infection, first recurrences, hospitalizations, and in-hospital deaths from 2011 through 2017. Health care-associated infections were defined as those with onset in a health care facility or associated with recent admission to a health care facility; all others were classified as community-associated infections. For trend analyses, we used weighted random-intercept models with negative binomial distribution and logistic-regression models to adjust for the higher sensitivity of nucleic acid amplification tests (NAATs) as compared with other test types. RESULTS: The number of cases of C. difficile infection in the 10 U.S. sites was 15,461 in 2011 (10,177 health care-associated and 5284 community-associated cases) and 15,512 in 2017 (7973 health care-associated and 7539 community-associated cases). The estimated national burden of C. difficile infection was 476,400 cases (95% confidence interval [CI], 419,900 to 532,900) in 2011 and 462,100 cases (95% CI, 428,600 to 495,600) in 2017. With accounting for NAAT use, the adjusted estimate of the total burden of C. difficile infection decreased by 24% (95% CI, 6 to 36) from 2011 through 2017; the adjusted estimate of the national burden of health care-associated C. difficile infection decreased by 36% (95% CI, 24 to 54), whereas the adjusted estimate of the national burden of community-associated C. difficile infection was unchanged. The adjusted estimate of the burden of hospitalizations for C. difficile infection decreased by 24% (95% CI, 0 to 48), whereas the adjusted estimates of the burden of first recurrences and in-hospital deaths did not change significantly. CONCLUSIONS: The estimated national burden of C. difficile infection and associated hospitalizations decreased from 2011 through 2017, owing to a decline in health care-associated infections. (Funded by the Centers for Disease Control and Prevention.).

During a surveillance study of patients in a long-term care facility and the affiliated acute care hospital in the United States, we identified a Clostridioides difficile strain related to the epidemic PCR ribotype (RT) 027 strain associated with hospital outbreaks of severe disease. Fifteen patients were infected with this strain, characterized as restriction endonuclease analysis group DQ and RT591. Like RT027, DQ/RT591 contained genes for toxin B and binary toxin CDT and a tcdC gene of identical sequence. Whole-genome sequencing and multilocus sequence typing showed that DQ/RT591 is a member of the same multilocus sequence typing clade 2 as RT027 but in a separate cluster. DQ/RT591 produced a similar cytopathic effect as RT027 but showed delayed toxin production in vitro. DQ/RT591 was susceptible to moxifloxacin but highly resistant to clindamycin. Continued surveillance is warranted for this clindamycin-resistant strain that is related to the fluoroquinolone-resistant epidemic RT027 strain.

An ever-changing landscape for environmental health (EH) requires in-depth assessment and analysis of the current challenges and emerging issues faced by EH professionals. The Understanding the Needs, Challenges, Opportunities, Vision, and Emerging Roles in Environmental Health initiative addressed this need.After receiving responses from more than 1700 practitioners, during an in-person workshop, focus groups identified and described priority problems and supplied context on addressing the significant challenges facing EH professionals with state health agencies and local health departments. The focus groups developed specific problem statements detailing the EH profession and workforce's prevailing challenges and needs according to 6 themes, including effective leadership, workforce development, equipment and technology, information systems and data, garnering support, and partnerships and collaboration.We describe the identified priority problems and needs and provide recommendations for ensuring a strong and robust EH profession and workforce ready to address tomorrow's challenges. (Am J Public Health. Published online ahead of print January 16, 2020: e1-e7. doi:10.2105/AJPH.2019.305441).

BACKGROUND: Clostridioides difficile infection (CDI) causes significant morbidity in nursing home residents. Our aim was to describe adherence to a bundled CDI prevention initiative, which had previously been deployed nationwide in Veterans Health Administration (VA) long-term care facilities (LTCFs), and to improve compliance with reinforcement. METHODS: A multicenter pre- and post-reinforcement of the VA bundle consisting of environmental management, hand hygiene, and contact precautions was conducted in 6 VA LTCFs. A campaign to reinforce VA bundle components, as well as to promote select antimicrobial stewardship recommendations and contact precautions for 30 days, was employed. Hand hygiene, antimicrobial usage, and environmental contamination, before and after bundle reinforcement, were assessed. RESULTS: All LTCFs reported following the guidelines for cleaning and contact precautions until diarrhea resolution pre-reinforcement. Environmental specimens rarely yielded C difficile pre- or post-reinforcement. Proper hand hygiene across all facilities did not change with reinforcement (pre 52.51%, post 52.18%), nor did antimicrobial use (pre 87-197 vs. post 84-245 antibiotic days per 1,000 resident-days). LTCFs found it challenging to maintain prolonged contact precautions. DISCUSSION: Variation in infection prevention and antimicrobial prescribing practices across LTCFs were identified and lessons learned. CONCLUSIONS: Introducing bundled interventions in LTCFs is challenging, given the available resources, and may be more successful with fewer components and more intensive execution with feedback.

BACKGROUND: Environmental health (EH) professionals, one of the largest segments of the public health workforce, are responsible for delivery of essential environmental public health services. The challenges facing these professionals and research needs to improve EH practice are not fully understood, but 26% of EH professionals working in health departments of the United States plan to retire in 5 y, while only 6% of public health students are currently pursuing EH concentrations. OBJECTIVES: A groundbreaking initiative was recently launched to understand EH practice in health departments of the United States. This commentary article aims to identify priority EH practice challenges and related research needs for health departments. METHODS: A horizon scanning approach was conducted in which challenges facing EH professionals were provided by 1,736 respondents working at health departments who responded to a web-based survey fielded in November 2017. Thematic analyses of the responses and determining the frequency at which respondents reported specific issues and opportunities identified primary EH topic areas. These topic areas and related issues informed focus group discussions at an in-person workshop held in Anaheim, California. The purpose of the in-person workshop was to engage each of the topic areas and issues, through facilitated focus groups, leading to the formation of four to five related problem statements for each EH topic. DISCUSSION: EH professionals are strategically positioned to diagnose, intervene, and prevent public health threats. Focus group engagement resulted in 29 priority problem statements partitioned among 6 EH topic areas: a) drinking water quality, b) wastewater management, c) healthy homes, d) food safety, e) vectors and public health pests, and f) emerging issues. This commentary article identifies priority challenges and related research needs to catalyze effective delivery of essential environmental public health services for common EH program areas in health departments. An unprecedented initiative to revitalize EH practice with timely and strategic recommendations for student and professional training, nontraditional partnerships, and basic and translational research activities is recommended. https://doi.org/10.1289/EHP5161.

BACKGROUND: Infectious Diseases Society of America/Society for Healthcare Epidemiology of America (IDSA/SHEA) guidelines describe recommended therapy for Clostridioides difficile infection (CDI). OBJECTIVE: To describe CDI treatment and, among those with severe CDI, determine predictors of adherence to the 2010 IDSA/SHEA treatment guidelines. DESIGN: We analyzed 2013-2015 CDI treatment data collected through the Centers for Disease Control and Prevention's Emerging Infections Program. Generalized linear mixed models were used to identify predictors of guideline-adherent therapy. PATIENTS: A CDI case was defined as a positive stool specimen in a person aged >/= 18 years without a positive test in the prior 8 weeks; severe CDI cases were defined as having a white blood cell count >/= 15,000 cells/mul. MAIN MEASURES: Prescribing and predictors of guideline-adherent CDI therapy for severe disease. KEY RESULTS: Of 18,243 cases, 14,257 (78%) were treated with metronidazole, 7683 (42%) with vancomycin, and 313 (2%) with fidaxomicin. The median duration of therapy was 14 (interquartile range, 11-15) days. Severe CDI was identified in 3250 (18%) cases; of 3121 with treatment data available, 1480 (47%) were prescribed guideline-adherent therapy. Among severe CDI cases, hospital admission (adjusted odds ratio [aOR] 2.48; 95% confidence interval [CI] 1.90, 3.24), age >/= 65 years (aOR 1.37; 95% CI 1.10, 1.71), Charlson comorbidity index >/= 3 (aOR 1.27; 95% CI 1.04, 1.55), immunosuppressive therapy (aOR 1.21; 95% CI 1.02, 1.42), and inflammatory bowel disease (aOR 1.56; 95% CI 1.13, 2.17) were associated with being prescribed guideline-adherent therapy. CONCLUSIONS: Provider adherence to the 2010 treatment guidelines for severe CDI was low. Although the updated 2017 CDI guidelines, which expand the use of oral vancomycin for all CDI, might improve adherence by removing the need to apply severity criteria, other efforts to improve adherence are likely needed, including educating providers and addressing barriers to prescribing guideline-adherent therapy, particularly in outpatient settings.

Environmental health (EH) professionals provide critical services and respond to complex and multifaceted public health threats. The role of these professionals is continually re-emphasized by emergencies requiring rapid and effective responses to address environmental issues and ensure protection of the public’s health. Given the prominence of the EH profession within the public health framework, assessing the governmental health department workforce, practice, and current and future challenges is crucial to ensure EH professionals are fully equipped and prepared to protect the nation’s health. Such an understanding of the EH profession is lacking; therefore, we initiated Understanding the Needs, Challenges, Opportunities, Vision, and Emerging Roles in Environmental Health (UNCOVER EH). Through a webbased survey, we identifi ed EH professional demographics, characteristics, education, practice areas, and aspects of leadership and satisfaction. We distributed the survey to a convenience sample of EH professionals working in health departments, limiting the generalizability of results to the entire EH workforce. The results were strengthened, however, by purposive sampling strategies to represent varied professional and workforce characteristics in the respondent universe. The UNCOVER EH initiative provides a primary source of data to inform EH workforce development initiatives, improve the practice, and establish uniform benchmarks and professional competencies.

Background: Few data suggest Clostridioides difficile infections (CDI) detected by toxin enzyme immunoassays (EIA) are more severe and have worse outcomes than those detected by nucleic acid amplification tests (NAAT) only. We compared toxin-positive and NAAT-positive only CDI across geographically-diverse sites. Methods: A case was defined as a positive C. difficile test in a person >/=1 year old with no positive tests in the prior 8 weeks. Cases were detected during 2014-15 by a testing algorithm (specimens initially tested by glutamate dehydrogenase [GDH] and toxin EIA; if discordant results, specimens were reflexed to NAAT) and classified as toxin-positive or NAAT-positive only. Medical charts were reviewed. Multivariable logistic regression models were used to compare CDI-related complications, recurrence, and 30-day mortality between the two groups. Results: Of 4878 cases, 2160 (44.3%) were toxin-positive and 2718 (55.7%) were NAAT-positive only. More toxin-positive than NAAT-positive only cases were aged >/=65 years (48.2% vs 38.0%; P<0.0001), had >/=3 unformed stool for >/=1 day (43.9% vs 36.6%; P<0.0001), and had white blood cells >/=15,000/microl (31.4% versus 21.4%; P<0.0001). In multivariable analysis, toxin-positivity was associated with recurrence (adjusted odds ratio [aOR]: 1.89, 95% CI: 1.61-2.23), but not with CDI-related complications (aOR: 0.91, 95% CI: 0.67-1.23) or 30-day mortality (aOR: 0.95; 95% CI: 0.73-1.24). Conclusions: Toxin-positive CDI is more severe, but there were no differences in adjusted CDI-related complication and mortality rates between toxin-positive and NAAT-positive only CDI that were detected by an algorithm that utilized an initial GDH screening test.

INTRODUCTIONIn 2017, the Journal of Clinical Microbiology published a Point-Counterpoint on the laboratory diagnosis of Clostridium difficile infection (CDI). At that time, Ferric C. Fang, Christopher R. Polage, and Mark H. Wilcox discussed the strategies for diagnosing Clostridium difficile colitis in symptomatic patients (J Clin Microbiol 55:670-680, 2017, https://doi.org/10.1128/JCM.02463-16). Since that paper, new guidelines from the Infectious Diseases Society of America and the Society for Health Care Epidemiology have been published (L. C. McDonald, D. N. Gerding, S. Johnson, J. S. Bakken, K. C. Carroll, et al., Clin Infect Dis 66:987-994, 2018, https://doi.org/10.1093/cid/ciy149) and health care systems have begun to explore screening asymptomatic patients for C. difficile colonization. The theory behind screening selected patient populations for C. difficile colonization is that these patients represent a substantial reservoir of the bacteria and can transfer the bacteria to other patients. Hospital administrators are taking note of institutional CDI rates because they are publicly reported. They have become an important metric impacting hospital safety ratings and value-based purchasing, and hospitals may have millions of dollars of reimbursement at risk. In this Point-Counterpoint, Cliff McDonald of the U.S. Centers for Disease Control and Prevention discusses the value of asymptomatic C. difficile screening, while Dan Diekema of the University of Iowa discusses why caution should be used.

OBJECTIVE: To test the hypothesis that long-term care facility (LTCF) residents with Clostridium difficile infection (CDI) or asymptomatic carriage of toxigenic strains are an important source of transmission in the LTCF and in the hospital during acute-care admissions. DESIGN: A 6-month cohort study with identification of transmission events was conducted based on tracking of patient movement combined with restriction endonuclease analysis (REA) and whole-genome sequencing (WGS). SETTING: Veterans Affairs hospital and affiliated LTCF.ParticipantsThe study included 29 LTCF residents identified as asymptomatic carriers of toxigenic C. difficile based on every other week perirectal screening and 37 healthcare facility-associated CDI cases (ie, diagnosis >3 days after admission or within 4 weeks of discharge to the community), including 26 hospital-associated and 11 LTCF-associated cases. RESULTS: Of the 37 CDI cases, 7 (18.9%) were linked to LTCF residents with LTCF-associated CDI or asymptomatic carriage, including 3 of 26 hospital-associated CDI cases (11.5%) and 4 of 11 LTCF-associated cases (36.4%). Of the 7 transmissions linked to LTCF residents, 5 (71.4%) were linked to asymptomatic carriers versus 2 (28.6%) to CDI cases, and all involved transmission of epidemic BI/NAP1/027 strains. No incident hospital-associated CDI cases were linked to other hospital-associated CDI cases. CONCLUSIONS: Our findings suggest that LTCF residents with asymptomatic carriage of C. difficile or CDI contribute to transmission both in the LTCF and in the affiliated hospital during acute-care admissions. Greater emphasis on infection control measures and antimicrobial stewardship in LTCFs is needed, and these efforts should focus on LTCF residents during hospital admissions.Infection Control & Hospital Epidemiology (2018), 0 1-8.

This study used a unique approach to examine Florida county health department environmental health (EH) program performance of the 10 Essential Environmental Public Health Services (EEPHS) and its relationship with environment-related disease, described by enteric disease rates. Correlation analysis tested the association between performance of each EEPHS and five different enteric disease rates, while multivariate regression analysis further examined the relationships while considering program organizational characteristics as potential confounders. Correlation analyses revealed cryptosporidiosis was associated with EEPHS 2 diagnose (Tb = .195, p = .027) and EEPHS 8 workforce (Tb = .234, p = .006), and salmonellosis with EEPHS 4 mobilize (Tb = .179, p = .042) and EEPHS 6 enforce (Tb = .201, p = .020). Multivariate regression results showed EEPHS 2 diagnose (p = .04) and EEPHS 4 mobilize (p = .00) had statistically significant associations with cryptosporidiosis and salmonellosis, respectively, and suggested that improved performance of these two EEPHS may have decreased disease incidence. EH programs may benefit from improving the performance of EEPHS to address the incidence of certain enteric diseases. Continued efforts to develop a robust understanding of EH program performance and its impact on environment-related disease could enhance EH services delivery and ability to improve health outcomes.

The main objective of this research was to ascertain the association between organizational characteristics of local health departments (LHDs) and environmental health (EH) services rendered in the community. Data used for the analysis were collected from LHDs by the National Association of County and City Health Officials for its 2013 national profile study of LHDs. We analyzed the data during 2016. Apart from understanding basic characteristics of LHDs in the nation, we introduced new measures of these characteristics, including "EH full-time equivalents" per 100,000 population and "other revenue" (revenues from fees and fines) per capita. The association of these and other organizational characteristics with EH services were measured using likelihood ratio §² and t-tests. Out of 34 EH services considered, LHDs directly provided an average of 12 different services. As many as 41% of the 34 EH services were not available in more than 10% of the communities served by LHDs. About 70% of communities received some services from organizations other than LHDs. All the available organizational characteristics of LHDs had association with some of the EH services. Although we might assume an increase in per capita expenditure could result in an increase in LHDs' direct involvement in providing EH services, we found it to be true only for five (15%) of the EH services. The variation of EH services provided in communities could be explained by a combination of factors such as fee generation, community needs, type of governance, and population size.