Last data update: May 13, 2024. (Total: 46773 publications since 2009)
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Recommended adult immunization schedule, United States, 2024
Murthy N , Wodi AP , McNally VV , Daley MF , Cineas S . Ann Intern Med 2024 In October 2023, the Advisory Committee on Immunization Practices (ACIP) voted to approve the Recommended Adult Immunization Schedule for Ages 19 Years or Older, United States, 2024. The 2024 adult immunization schedule, available at www.cdc.gov/vaccines/schedules/hcp/imz/adult.html, summarizes ACIP recommendations in the cover page, tables, notes, appendix, and addendum (Figure). The full ACIP recommendations for each vaccine are available at www.cdc.gov/vaccines/hcp/acip-recs/index.html. The 2024 schedule has also been approved by the director of the Centers for Disease Control and Prevention (CDC) and by the American College of Physicians (www.acponline.org), the American Academy of Family Physicians (www.aafp.org), the American College of Obstetricians and Gynecologists (www.acog.org), the American College of Nurse-Midwives (www.midwife.org), the American Academy of Physician Associates (www.aapa.org), the American Pharmacists Association (www.pharmacist.com), and the Society for Healthcare Epidemiology of America (www.shea-online.org). |
Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty
Howerton E , Contamin L , Mullany LC , Qin M , Reich NG , Bents S , Borchering RK , Jung SM , Loo SL , Smith CP , Levander J , Kerr J , Espino J , van Panhuis WG , Hochheiser H , Galanti M , Yamana T , Pei S , Shaman J , Rainwater-Lovett K , Kinsey M , Tallaksen K , Wilson S , Shin L , Lemaitre JC , Kaminsky J , Hulse JD , Lee EC , McKee CD , Hill A , Karlen D , Chinazzi M , Davis JT , Mu K , Xiong X , Pastore YPiontti A , Vespignani A , Rosenstrom ET , Ivy JS , Mayorga ME , Swann JL , España G , Cavany S , Moore S , Perkins A , Hladish T , Pillai A , Ben Toh K , Longini I Jr , Chen S , Paul R , Janies D , Thill JC , Bouchnita A , Bi K , Lachmann M , Fox SJ , Meyers LA , Srivastava A , Porebski P , Venkatramanan S , Adiga A , Lewis B , Klahn B , Outten J , Hurt B , Chen J , Mortveit H , Wilson A , Marathe M , Hoops S , Bhattacharya P , Machi D , Cadwell BL , Healy JM , Slayton RB , Johansson MA , Biggerstaff M , Truelove S , Runge MC , Shea K , Viboud C , Lessler J . Nat Commun 2023 14 (1) 7260 Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make months ahead projections of SARS-CoV-2 burden, totaling nearly 1.8 million national and state-level projections. Here, we find SMH performance varied widely as a function of both scenario validity and model calibration. We show scenarios remained close to reality for 22 weeks on average before the arrival of unanticipated SARS-CoV-2 variants invalidated key assumptions. An ensemble of participating models that preserved variation between models (using the linear opinion pool method) was consistently more reliable than any single model in periods of valid scenario assumptions, while projection interval coverage was near target levels. SMH projections were used to guide pandemic response, illustrating the value of collaborative hubs for longer-term scenario projections. |
Introduction to A Compendium of Strategies to Prevent Healthcare-Associated Infections In Acute-Care Hospitals: 2022 Updates
Yokoe DS , Advani SD , Anderson DJ , Babcock HM , Bell M , Berenholtz SM , Bryant KA , Buetti N , Calderwood MS , Calfee DP , Deloney VM , Dubberke ER , Ellingson KD , Fishman NO , Gerding DN , Glowicz J , Hayden MK , Kaye KS , Kociolek LK , Landon E , Larson EL , Malani AN , Marschall J , Meddings J , Mermel LA , Patel PK , Perl TM , Popovich KJ , Schaffzin JK , Septimus E , Trivedi KK , Weinstein RA , Maragakis LL . Infect Control Hosp Epidemiol 2023 44 (10) 1533-1539 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 in acute-care hospitals: 2022 Update
Patel PK , Advani SD , Kofman AD , Lo E , Maragakis LL , Pegues DA , Pettis AM , Saint S , Trautner B , Yokoe DS , Meddings J . Infect Control Hosp Epidemiol 2023 44 (8) 1209-1231 The intent of this document is to highlight practical recommendations in a concise format designed to assist physicians, nurses, and infection preventionists at acute-care hospitals in implementing and prioritizing their catheter-associated urinary tract infection (CAUTI) prevention efforts. This document updates the Strategies to Prevent Catheter-Associated Urinary Tract Infections in Acute-Care Hospitals published in 2014. It 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. |
Chromosomal rearrangements and loss of subtelomeric adhesins linked to clade-specific phenotypes in Candida auris (preprint)
Muñoz JF , Welsh RM , Shea T , Batra D , Gade L , Litvintseva AP , Cuomo CA . bioRxiv 2019 754143 Candida auris is an emerging fungal pathogen of rising concern due to its increasing incidence, its ability to cause healthcare-associated outbreaks and antifungal resistance. Genomic analysis revealed that early cases of C. auris that were detected contemporaneously were geographically stratified into four major clades. Clade II, also termed East Asian clade, consists of the initial isolates described from cases of ear infection, is less frequently resistant to antifungal drugs and to date, the isolates from this group have not been associated with outbreaks. Here, we generate nearly complete genomes (“telomere-to-telomere”) of an isolate of this clade and of the more widespread Clade IV. By comparing these to genome assemblies of the other two clades, we find that the Clade II genome appears highly rearranged, with 2 inversions and 9 translocations resulting in a substantially different karyotype. In addition, large subtelomeric regions have been lost from 10 of 14 chromosome ends in the Clade II genomes. We find that shorter telomeres and genome instability might be a consequence of a naturally occurring loss-of-function mutation in DCC1 exclusively found in Clade II isolates, resulting in a hypermutator phenotype. We also determine that deleted subtelomeric regions might be linked to clade-specific adaptation as these regions are enriched in Hyr/Iff-like cell surface proteins, novel candidate cell surface proteins, and an ALS-like adhesin. The presence of these cell surface proteins in the clades responsible for global outbreaks causing invasive infections suggests an explanation for the different phenotypes observed between clades.IMPORTANCE Candida auris was unknown prior to 2009 and since then it has quickly spread around the world, causing outbreaks in healthcare facilities and representing a high fraction of candidemia cases in some regions. The emergence of C. auris is a major concern, since it is often multidrug-resistant, easily spread between patients, and causes invasive infections. While isolates from three global clades cause invasive infections, isolates from Clade II primarily cause ear infections and have not been implicated in outbreaks, though cases of Clade II infections have been reported on different continents. Here, we describe genetic differences between Clade II and Clades I, III and IV, including a loss-of-function mutation in a gene associated with telomere length maintenance and genome stability, and the loss of cell wall proteins involved in adhesion and biofilm formation, that may suggest an explanation for the lower virulence and potential for transmission of Clade II isolates. |
Projected resurgence of COVID-19 in the United States in July-December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination (preprint)
Truelove S , Smith CP , Qin M , Mullany LC , Borchering RK , Lessler J , Shea K , Howerton E , Contamin L , Levander J , Salerno J , Hochheiser H , Kinsey M , Tallaksen K , Wilson S , Shin L , Rainwater-Lovett K , Lemaitre JC , Dent J , Kaminsky J , Lee EC , Perez-Saez J , Hill A , Karlen D , Chinazzi M , Davis JT , Mu K , Xiong X , Piontti APY , Vespignani A , Srivastava A , Porebski P , Venkatramanan S , Adiga A , Lewis B , Klahn B , Outten J , Schlitt J , Corbett P , Telionis PA , Wang L , Peddireddy AS , Hurt B , Chen J , Vullikanti A , Marathe M , Hoops S , Bhattacharya P , Machi D , Chen S , Paul R , Janies D , Thill JC , Galanti M , Yamana T , Pei S , Shaman J , Reich NG , Healy JM , Slayton RB , Biggerstaff M , Johansson MA , Runge MC , Viboud C . medRxiv 2021 WHAT IS ALREADY KNOWN ABOUT THIS TOPIC? The highly transmissible SARS-CoV-2 Delta variant has begun to cause increases in cases, hospitalizations, and deaths in parts of the United States. With slowed vaccination uptake, this novel variant is expected to increase the risk of pandemic resurgence in the US in July-December 2021. WHAT IS ADDED BY THIS REPORT? Data from nine mechanistic models project substantial resurgences of COVID-19 across the US resulting from the more transmissible Delta variant. These resurgences, which have now been observed in most states, were projected to occur across most of the US, coinciding with school and business reopening. Reaching higher vaccine coverage in July-December 2021 reduces the size and duration of the projected resurgence substantially. The expected impact of the outbreak is largely concentrated in a subset of states with lower vaccination coverage. WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE? Renewed efforts to increase vaccination uptake are critical to limiting transmission and disease, particularly in states with lower current vaccination coverage. Reaching higher vaccination goals in the coming months can potentially avert 1.5 million cases and 21,000 deaths and improve the ability to safely resume social contacts, and educational and business activities. Continued or renewed non-pharmaceutical interventions, including masking, can also help limit transmission, particularly as schools and businesses reopen. |
COVID-19 reopening strategies at the county level in the face of uncertainty: Multiple Models for Outbreak Decision Support (preprint)
Shea K , Borchering RK , Probert WJM , Howerton E , Bogich TL , Li S , van Panhuis WG , Viboud C , Aguás R , Belov A , Bhargava SH , Cavany S , Chang JC , Chen C , Chen J , Chen S , Chen Y , Childs LM , Chow CC , Crooker I , Valle SYD , España G , Fairchild G , Gerkin RC , Germann TC , Gu Q , Guan X , Guo L , Hart GR , Hladish TJ , Hupert N , Janies D , Kerr CC , Klein DJ , Klein E , Lin G , Manore C , Meyers LA , Mittler J , Mu K , Núñez RC , Oidtman R , Pasco R , Piontti APY , Paul R , Pearson CAB , Perdomo DR , Perkins TA , Pierce K , Pillai AN , Rael RC , Rosenfeld K , Ross CW , Spencer JA , Stoltzfus AB , Toh KB , Vattikuti S , Vespignani A , Wang L , White L , Xu P , Yang Y , Yogurtcu ON , Zhang W , Zhao Y , Zou D , Ferrari M , Pannell D , Tildesley M , Seifarth J , Johnson E , Biggerstaff M , Johansson M , Slayton RB , Levander J , Stazer J , Salerno J , Runge MC . medRxiv 2020 Policymakers make decisions about COVID-19 management in the face of considerable uncertainty. We convened multiple modeling teams to evaluate reopening strategies for a mid-sized county in the United States, in a novel process designed to fully express scientific uncertainty while reducing linguistic uncertainty and cognitive biases. For the scenarios considered, the consensus from 17 distinct models was that a second outbreak will occur within 6 months of reopening, unless schools and non-essential workplaces remain closed. Up to half the population could be infected with full workplace reopening; non-essential business closures reduced median cumulative infections by 82%. Intermediate reopening interventions identified no win-win situations; there was a trade-off between public health outcomes and duration of workplace closures. Aggregate results captured twice the uncertainty of individual models, providing a more complete expression of risk for decision-making purposes. |
Serial interval and incubation period estimates of monkeypox virus infection in 12 U.S. jurisdictions, May - August 2022 (preprint)
Madewell ZJ , Charniga K , Masters NB , Asher J , Fahrenwald L , Still W , Chen J , Kipperman N , Bui D , Shea M , Saathoff-Huber L , Johnson S , Harbi K , Berns AL , Perez T , Gateley E , Spicknall IH , Nakazawa Y , Gift TL . medRxiv 2022 30 Using data collected by 12 U.S. health departments, we report mean estimated serial interval for monkeypox virus infection of 8.5 (95% CrI: 7.3 - 9.9) days for symptom onset from 57 case pairs and mean estimated incubation period of 5.6 (4.3 - 7.8) days from 35 case pairs for symptom onset. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license. |
Impact of SARS-CoV-2 vaccination of children ages 5-11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021-March 2022: a multi-model study (preprint)
Borchering RK , Mullany LC , Howerton E , Chinazzi M , Smith CP , Qin M , Reich NG , Contamin L , Levander J , Kerr J , Espino J , Hochheiser H , Lovett K , Kinsey M , Tallaksen K , Wilson S , Shin L , Lemaitre JC , Hulse JD , Kaminsky J , Lee EC , Davis JT , Mu K , Xiong X , Pastore y Piontti A , Vespignani A , Srivastava A , Porebski P , Venkatramanan S , Adiga A , Lewis B , Klahn B , Outten J , Hurt B , Chen J , Mortveit H , Wilson A , Marathe M , Hoops S , Bhattacharya P , Machi D , Chen S , Paul R , Janies D , Thill JC , Galanti M , Yamana T , Pei S , Shaman J , Espana G , Cavany S , Moore S , Perkins A , Healy JM , Slayton RB , Johansson MA , Biggerstaff M , Shea K , Truelove SA , Runge MC , Viboud C , Lessler J . medRxiv 2022 10 Background SARS-CoV-2 vaccination of persons aged 12 years and older has reduced disease burden in the United States. The COVID-19 Scenario Modeling Hub convened multiple modeling teams in September 2021 to project the impact of expanding vaccine administration to children 5-11 years old on anticipated COVID-19 burden and resilience against variant strains. Methods Nine modeling teams contributed state- and national-level projections for weekly counts of cases, hospitalizations, and deaths in the United States for the period September 12, 2021 to March 12, 2022. Four scenarios covered all combinations of: 1) presence vs. absence of vaccination of children ages 5-11 years starting on November 1, 2021; and 2) continued dominance of the Delta variant vs. emergence of a hypothetical more transmissible variant on November 15, 2021. Individual team projections were combined using linear pooling. The effect of childhood vaccination on overall and age-specific outcomes was estimated by meta-analysis approaches. Findings Absent a new variant, COVID-19 cases, hospitalizations, and deaths among all ages were projected to decrease nationally through mid-March 2022. Under a set of specific assumptions, models projected that vaccination of children 5-11 years old was associated with reductions in all-age cumulative cases (7.2%, mean incidence ratio [IR] 0.928, 95% confidence interval [CI] 0.880-0.977), hospitalizations (8.7%, mean IR 0.913, 95% CI 0.834-0.992), and deaths (9.2%, mean IR 0.908, 95% CI 0.797-1.020) compared with scenarios where children were not vaccinated. This projected effect of vaccinating children 5-11 years old increased in the presence of a more transmissible variant, assuming no change in vaccine effectiveness by variant. Larger relative reductions in cumulative cases, hospitalizations, and deaths were observed for children than for the entire U.S. population. Substantial state-level variation was projected in epidemic trajectories, vaccine benefits, and variant impacts. Conclusions Results from this multi-model aggregation study suggest that, under a specific set of scenario assumptions, expanding vaccination to children 5-11 years old would provide measurable direct benefits to this age group and indirect benefits to the all-age U.S. population, including resilience to more transmissible variants. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license. |
Implementing strategies to prevent infections in acute-care settings
Trivedi KK , Schaffzin JK , Deloney VM , Aureden K , Carrico R , Garcia-Houchins S , Garrett JH Jr , Glowicz J , Lee GM , Maragakis LL , Moody J , Pettis AM , Saint S , Schweizer ML , Yokoe DS , Berenholtz S . Infect Control Hosp Epidemiol 2023 44 (8) 1-15 This document introduces and explains common implementation concepts and frameworks relevant to healthcare epidemiology and infection prevention and control and can serve as a stand-alone guide or be paired with the "SHEA/IDSA/APIC Compendium of Strategies to Prevent Healthcare-Associated Infections in Acute Care Hospitals: 2022 Updates," which contain technical implementation guidance for specific healthcare-associated infections. This Compendium article focuses on broad behavioral and socio-adaptive concepts and suggests ways that infection prevention and control teams, healthcare epidemiologists, infection preventionists, and specialty groups may utilize them to deliver high-quality care. Implementation concepts, frameworks, and models can help bridge the "knowing-doing" gap, a term used to describe why practices in healthcare may diverge from those recommended according to evidence. It aims to guide the reader to think about implementation and to find resources suited for a specific setting and circumstances by describing strategies for implementation, including determinants and measurement, as well as the conceptual models and frameworks: 4Es, Behavior Change Wheel, CUSP, European and Mixed Methods, Getting to Outcomes, Model for Improvement, RE-AIM, REP, and Theoretical Domains. |
SHEA/IDSA/APIC Practice Recommendation: Strategies to prevent methicillin-resistant Staphylococcus aureus transmission and infection in acute-care hospitals: 2022 Update
Popovich KJ , Aureden K , Ham DC , Harris AD , Hessels AJ , Huang SS , Maragakis LL , Milstone AM , Moody J , Yokoe D , Calfee DP . Infect Control Hosp Epidemiol 2023 44 (7) 1-29 Previously published guidelines have 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 in implementing and prioritizing efforts to prevent methicillin-resistant Staphylococcus aureus (MRSA) transmission and infection. This document updates the "Strategies to Prevent Methicillin-Resistant Staphylococcus aureus Transmission and Infection in Acute Care Hospitals" published in 2014.(1) This expert guidance document is sponsored by the Society for Healthcare Epidemiology of America (SHEA). It 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, with major contributions from representatives of a number of organizations and societies with content expertise. |
Multiple models for outbreak decision support in the face of uncertainty
Shea K , Borchering RK , Probert WJM , Howerton E , Bogich TL , Li SL , van Panhuis WG , Viboud C , Aguás R , Belov AA , Bhargava SH , Cavany SM , Chang JC , Chen C , Chen J , Chen S , Chen Y , Childs LM , Chow CC , Crooker I , Del Valle SY , España G , Fairchild G , Gerkin RC , Germann TC , Gu Q , Guan X , Guo L , Hart GR , Hladish TJ , Hupert N , Janies D , Kerr CC , Klein DJ , Klein EY , Lin G , Manore C , Meyers LA , Mittler JE , Mu K , Núñez RC , Oidtman RJ , Pasco R , Pastore YPiontti A , Paul R , Pearson CAB , Perdomo DR , Perkins TA , Pierce K , Pillai AN , Rael RC , Rosenfeld K , Ross CW , Spencer JA , Stoltzfus AB , Toh KB , Vattikuti S , Vespignani A , Wang L , White LJ , Xu P , Yang Y , Yogurtcu ON , Zhang W , Zhao Y , Zou D , Ferrari MJ , Pannell D , Tildesley MJ , Seifarth J , Johnson E , Biggerstaff M , Johansson MA , Slayton RB , Levander JD , Stazer J , Kerr J , Runge MC . Proc Natl Acad Sci U S A 2023 120 (18) e2207537120 Policymakers must make management decisions despite incomplete knowledge and conflicting model projections. Little guidance exists for the rapid, representative, and unbiased collection of policy-relevant scientific input from independent modeling teams. Integrating approaches from decision analysis, expert judgment, and model aggregation, we convened multiple modeling teams to evaluate COVID-19 reopening strategies for a mid-sized United States county early in the pandemic. Projections from seventeen distinct models were inconsistent in magnitude but highly consistent in ranking interventions. The 6-mo-ahead aggregate projections were well in line with observed outbreaks in mid-sized US counties. The aggregate results showed that up to half the population could be infected with full workplace reopening, while workplace restrictions reduced median cumulative infections by 82%. Rankings of interventions were consistent across public health objectives, but there was a strong trade-off between public health outcomes and duration of workplace closures, and no win-win intermediate reopening strategies were identified. Between-model variation was high; the aggregate results thus provide valuable risk quantification for decision making. This approach can be applied to the evaluation of management interventions in any setting where models are used to inform decision making. This case study demonstrated the utility of our approach and was one of several multimodel efforts that laid the groundwork for the COVID-19 Scenario Modeling Hub, which has provided multiple rounds of real-time scenario projections for situational awareness and decision making to the Centers for Disease Control and Prevention since December 2020. |
Serial interval and incubation period estimates of monkeypox virus infection in 12 jurisdictions, United States, May-August 2022
Madewell ZJ , Charniga K , Masters NB , Asher J , Fahrenwald L , Still W , Chen J , Kipperman N , Bui D , Shea M , Saunders K , Saathoff-Huber L , Johnson S , Harbi K , Berns AL , Perez T , Gateley E , Spicknall IH , Nakazawa Y , Gift TL . Emerg Infect Dis 2023 29 (4) 818-821 Using data from 12 US health departments, we estimated mean serial interval for monkeypox virus infection to be 8.5 (95% credible interval 7.3-9.9) days for symptom onset, based on 57 case pairs. Mean estimated incubation period was 5.6 (95% credible interval 4.3-7.8) days for symptom onset, based on 35 case pairs. |
Outbreaks of SARS-CoV-2 infections in nursing homes during periods of Delta and Omicron predominance, United States, July 2021-March 2022
Wilson WW , Keaton AA , Ochoa LG , Hatfield KM , Gable P , Walblay KA , Teran RA , Shea M , Khan U , Stringer G , Ganesan M , Gilbert J , Colletti JG , Grogan EM , Calabrese C , Hennenfent A , Perlmutter R , Janiszewski KA , Brandeburg C , Kamal-Ahmed I , Strand K , Donahue M , Ashraf MS , Berns E , MacFarquhar J , Linder ML , Tran DJ , Kopp P , Walker RM , Ess R , Baggs J , Jernigan JA , Kallen A , Hunter JC . Emerg Infect Dis 2023 29 (4) 761-770 SARS-CoV-2 infections among vaccinated nursing home residents increased after the Omicron variant emerged. Data on booster dose effectiveness in this population are limited. During July 2021-March 2022, nursing home outbreaks in 11 US jurisdictions involving >3 infections within 14 days among residents who had received at least the primary COVID-19 vaccine(s) were monitored. Among 2,188 nursing homes, 1,247 outbreaks were reported in the periods of Delta (n = 356, 29%), mixed Delta/Omicron (n = 354, 28%), and Omicron (n = 536, 43%) predominance. During the Omicron-predominant period, the risk for infection within 14 days of an outbreak start was lower among boosted residents than among residents who had received the primary vaccine series alone (risk ratio [RR] 0.25, 95% CI 0.19-0.33). Once infected, boosted residents were at lower risk for all-cause hospitalization (RR 0.48, 95% CI 0.40-0.49) and death (RR 0.45, 95% CI 0.34-0.59) than primary vaccine-only residents. |
Strategies to prevent surgical site infections in acute-care hospitals: 2022 Update
Calderwood MS , Anderson DJ , Bratzler DW , Dellinger EP , Garcia-Houchins S , Maragakis LL , Nyquist AC , Perkins KM , Preas MA , Saiman L , Schaffzin JK , Schweizer M , Yokoe DS , Kaye KS . Infect Control Hosp Epidemiol 2023 44 (5) 1-26 The intent of this document is to highlight practical recommendations in a concise format designed to assist acute-care hospitals in implementing and prioritizing their surgical-site infection (SSI) prevention efforts. This document updates the Strategies to Prevent Surgical Site Infections in Acute Care Hospitals published in 2014. This expert guidance document is sponsored by the Society for Healthcare Epidemiology of America (SHEA). It 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, with major contributions from representatives of a number of organizations and societies with content expertise. |
Strategies to prevent Clostridioides difficile infections in acute-care hospitals: 2022 update
Kociolek LK , Gerding DN , Carrico R , Carling P , Donskey CJ , Dumyati G , Kuhar DT , Loo VG , Maragakis LL , Pogorzelska-Maziarz M , Sandora TJ , Weber DJ , Yokoe D , Dubberke ER . Infect Control Hosp Epidemiol 2023 44 (4) 527-549 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. |
Advisory Committee on Immunization Practices recommended immunization schedule for adults aged 19 years or older - United States, 2023
Murthy N , Wodi AP , McNally V , Cineas S , Ault K . MMWR Morb Mortal Wkly Rep 2023 72 (6) 141-144 At its October 2022 meeting, the Advisory Committee on Immunization Practices* (ACIP) approved the Recommended Adult Immunization Schedule for Ages 19 Years or Older, United States, 2023. The 2023 adult immunization schedule summarizes ACIP recommendations, including several changes to the cover page, tables, notes, and appendix from the 2022 immunization schedule.(†) This schedule can be found on the CDC immunization schedule website (https://www.cdc.gov/vaccines/schedules). Health care providers are advised to use the cover page, tables, notes, and appendix together to determine recommended vaccinations for patient populations. This adult immunization schedule is recommended by ACIP (https://www.cdc.gov/vaccines/acip) and approved by CDC (https://www.cdc.gov), the American College of Physicians (https://www.acponline.org), the American Academy of Family Physicians (https://www.aafp.org), the American College of Obstetricians and Gynecologists (https://www.acog.org), the American College of Nurse-Midwives (https://www.midwife.org), the American Academy of Physician Associates (https://www.aapa.org), the American Pharmacists Association (https://www.pharmacist.com), and the Society for Healthcare Epidemiology of America (https://shea-online.org). |
Recommended adult immunization schedule, United States, 2023
Murthy N , Wodi AP , Cineas S , Ault KA . Ann Intern Med 2023 176 (3) 367-380 In October 2022, the Advisory Committee on Immunization Practices (ACIP) voted to approve the Recommended Adult Immunization Schedule for Ages 19 Years or Older, United States, 2023. The 2023 adult immunization schedule, available at www.cdc.gov/vaccines/schedules/hcp/imz/adult.html, summarizes ACIP recommendations in the cover page, tables, notes, and appendix (Figure). The full ACIP recommendations for each vaccine are available at www.cdc.gov/vaccines/hcp/acip-recs/index.html. The 2023 schedule has also been approved by the director of the Centers for Disease Control and Prevention (CDC) and by the American College of Physicians (www.acponline.org), the American Academy of Family Physicians (www.aafp.org), the American College of Obstetricians and Gynecologists (www.acog.org), the American College of Nurse-Midwives (www.midwife.org), the American Academy of Physician Associates (www.aapa.org), the American Pharmacists Association (www.pharmacist.com), and the Society for Healthcare Epidemiology of America (www.shea-online.org). |
SHEA/IDSA/APIC Practice Recommendation: Strategies to prevent healthcare-associated infections through hand hygiene: 2022 Update
Glowicz JB , Landon E , Sickbert-Bennett EE , Aiello AE , deKay K , Hoffmann KK , Maragakis L , Olmsted RN , Polgreen PM , Trexler PA , VanAmringe MA , Wood AR , Yokoe D , Ellingson KD . Infect Control Hosp Epidemiol 2023 44 (3) 1-22 The purpose of this document is to highlight practical recommendations to assist acute-care hospitals in prioritization and implementation of strategies to prevent healthcare-associated infections through hand hygiene. This document updates the Strategies to Prevent Healthcare-Associated Infections in Acute Care Hospitals through Hand Hygiene, published in 2014. This expert guidance document is sponsored by the Society for Healthcare Epidemiology (SHEA). It is the product of a collaborative effort led by SHEA, the Infectious Diseases Society of America, the Association for Professionals in Infection Control and Epidemiology, the American Hospital Association, and The Joint Commission, with major contributions from representatives of a number of organizations and societies with content expertise. |
Severe acute respiratory coronavirus virus 2 (SARS-CoV-2) outbreaks in nursing homes involving residents who had completed a primary coronavirus disease 2019 (COVID-19) vaccine series-13 US jurisdictions, July-November 2021.
Wyatt Wilson W , Keaton AA , Ochoa LG , Hatfield KM , Gable P , Walblay KA , Teran RA , Shea M , Khan U , Stringer G , Colletti JG , Grogan EM , Calabrese C , Hennenfent A , Perlmutter R , Janiszewski KA , Kamal-Ahmed I , Strand K , Berns E , MacFarquhar J , Linder M , Tran DJ , Kopp P , Walker RM , Ess R , Read JS , Yingst C , Baggs J , Jernigan JA , Kallen A , Hunter JC . Infect Control Hosp Epidemiol 2023 44 (6) 1-5 Among nursing home outbreaks of coronavirus disease 2019 (COVID-19) with ≥3 breakthrough infections when the predominant severe acute respiratory coronavirus virus 2 (SARS-CoV-2) variant circulating was the SARS-CoV-2 δ (delta) variant, fully vaccinated residents were 28% less likely to be infected than were unvaccinated residents. Once infected, they had approximately half the risk for all-cause hospitalization and all-cause death compared with unvaccinated infected residents. |
Impact of SARS-CoV-2 vaccination of children ages 5-11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021-March 2022: A multi-model study.
Borchering RK , Mullany LC , Howerton E , Chinazzi M , Smith CP , Qin M , Reich NG , Contamin L , Levander J , Kerr J , Espino J , Hochheiser H , Lovett K , Kinsey M , Tallaksen K , Wilson S , Shin L , Lemaitre JC , Hulse JD , Kaminsky J , Lee EC , Hill AL , Davis JT , Mu K , Xiong X , Pastore YPiontti A , Vespignani A , Srivastava A , Porebski P , Venkatramanan S , Adiga A , Lewis B , Klahn B , Outten J , Hurt B , Chen J , Mortveit H , Wilson A , Marathe M , Hoops S , Bhattacharya P , Machi D , Chen S , Paul R , Janies D , Thill JC , Galanti M , Yamana T , Pei S , Shaman J , España G , Cavany S , Moore S , Perkins A , Healy JM , Slayton RB , Johansson MA , Biggerstaff M , Shea K , Truelove SA , Runge MC , Viboud C , Lessler J . Lancet Reg Health Am 2023 17 100398 BACKGROUND: The COVID-19 Scenario Modeling Hub convened nine modeling teams to project the impact of expanding SARS-CoV-2 vaccination to children aged 5-11 years on COVID-19 burden and resilience against variant strains. METHODS: Teams contributed state- and national-level weekly projections of cases, hospitalizations, and deaths in the United States from September 12, 2021 to March 12, 2022. Four scenarios covered all combinations of 1) vaccination (or not) of children aged 5-11 years (starting November 1, 2021), and 2) emergence (or not) of a variant more transmissible than the Delta variant (emerging November 15, 2021). Individual team projections were linearly pooled. The effect of childhood vaccination on overall and age-specific outcomes was estimated using meta-analyses. FINDINGS: Assuming that a new variant would not emerge, all-age COVID-19 outcomes were projected to decrease nationally through mid-March 2022. In this setting, vaccination of children 5-11 years old was associated with reductions in projections for all-age cumulative cases (7.2%, mean incidence ratio [IR] 0.928, 95% confidence interval [CI] 0.880-0.977), hospitalizations (8.7%, mean IR 0.913, 95% CI 0.834-0.992), and deaths (9.2%, mean IR 0.908, 95% CI 0.797-1.020) compared with scenarios without childhood vaccination. Vaccine benefits increased for scenarios including a hypothesized more transmissible variant, assuming similar vaccine effectiveness. Projected relative reductions in cumulative outcomes were larger for children than for the entire population. State-level variation was observed. INTERPRETATION: Given the scenario assumptions (defined before the emergence of Omicron), expanding vaccination to children 5-11 years old would provide measurable direct benefits, as well as indirect benefits to the all-age U.S. population, including resilience to more transmissible variants. FUNDING: Various (see acknowledgments). |
Projected resurgence of COVID-19 in the United States in July-December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination.
Truelove S , Smith CP , Qin M , Mullany LC , Borchering RK , Lessler J , Shea K , Howerton E , Contamin L , Levander J , Salerno J , Hochheiser H , Kinsey M , Tallaksen K , Wilson S , Shin L , Rainwater-Lovett K , Lemairtre JC , Dent Hulse J , Kaminsky J , Lee EC , Perez-Saez J , Hill A , Karlen D , Chinazzi M , Davis JT , Mu K , Xiong X , Pastore YPiontti A , Vespignani A , Srivastava A , Porebski P , Venkatramanan S , Adiga A , Lewis B , Klahn B , Outten J , Orr M , Harrison G , Hurt B , Chen J , Vullikanti A , Marathe M , Hoops S , Bhattacharya P , Machi D , Chen S , Paul R , Janies D , Thill JC , Galanti M , Yamana TK , Pei S , Shaman JL , Healy JM , Slayton RB , Biggerstaff M , Johansson MA , Runge MC , Viboud C . Elife 2022 11 In Spring 2021, the highly transmissible SARS-CoV-2 Delta variant began to cause increases in cases, hospitalizations, and deaths in parts of the United States. At the time, with slowed vaccination uptake, this novel variant was expected to increase the risk of pandemic resurgence in the US in summer and fall 2021. As part of the COVID-10 Scenario Modeling Hub, an ensemble of nine mechanistic models produced six-month scenario projections for July-December 2021 for the United States. These projections estimated substantial resurgences of COVID-19 across the US resulting from the more transmissible Delta variant, projected to occur across most of the US, coinciding with school and business reopening. The scenarios revealed that reaching higher vaccine coverage in July-December 2021 reduced the size and duration of the projected resurgence substantially, with the expected impacts was largely concentrated in a subset of states with lower vaccination coverage. Despite accurate projection of COVID-19 surges occurring and timing, the magnitude was substantially underestimated 2021 by the models compared with the of the reported cases, hospitalizations, and deaths occurring during July-December, highlighting the continued challenges to predict the evolving COVID-19 pandemic. Vaccination uptake remains critical to limiting transmission and disease, particularly in states with lower vaccination coverage. Higher vaccination goals at the onset of the surge of the new variant were estimated to avert over 1.5 million cases and 21,000 deaths, though may have had even greater impacts, considering the underestimated resurgence magnitude from the model. |
Strategies to prevent ventilator-associated pneumonia, ventilator-associated events, and nonventilator hospital-acquired pneumonia in acute-care hospitals: 2022 Update
Klompas M , Branson R , Cawcutt K , Crist M , Eichenwald EC , Greene LR , Lee G , Maragakis LL , Powell K , Priebe GP , Speck K , Yokoe DS , Berenholtz SM . Infect Control Hosp Epidemiol 2022 43 (6) 1-27 The purpose of this document is to highlight practical recommendations to assist acute care hospitals to prioritize and implement strategies to prevent ventilator-associated pneumonia (VAP), ventilator-associated events (VAE), and non-ventilator hospital-acquired pneumonia (NV-HAP) in adults, children, and neonates. This document updates the Strategies to Prevent Ventilator-Associated Pneumonia in Acute Care Hospitals published in 2014. This expert guidance document is sponsored by the Society for Healthcare Epidemiology (SHEA), and is the product of a collaborative effort led by SHEA, the Infectious Diseases Society of America, the American Hospital Association, the Association for Professionals in Infection Control and Epidemiology, and The Joint Commission, with major contributions from representatives of a number of organizations and societies with content expertise. |
Collaborative Hubs: Making the Most of Predictive Epidemic Modeling.
Reich NG , Lessler J , Funk S , Viboud C , Vespignani A , Tibshirani RJ , Shea K , Schienle M , Runge MC , Rosenfeld R , Ray EL , Niehus R , Johnson HC , Johansson MA , Hochheiser H , Gardner L , Bracher J , Borchering RK , Biggerstaff M . Am J Public Health 2022 112 (6) e1-e4 The COVID-19 pandemic has made it clear that epidemic models play an important role in how governments and the public respond to infectious disease crises. Early in the pandemic, models were used to estimate the true number of infections. Later, they estimated key parameters, generated short-term forecasts of outbreak trends, and quantified possible effects of interventions on the unfolding epidemic.1,2 In contrast to the coordinating role played by major national or international agencies in weather-related emergencies, pandemic modeling efforts were initially scattered across many research institutions. Differences in modeling approaches led to contrasting results, contributing to confusion in public perception of the pandemic. Efforts to coordinate modeling efforts in so-called hubs have provided governments, healthcare agencies, and the public with assessments and forecasts that reflect the consensus in the modeling community.36 This has been achieved by openly synthesizing uncertainties across different modeling approaches and facilitating comparisons between them. |
Strategies to prevent central line-associated bloodstream infections in acute-care hospitals: 2022 Update
Buetti N , Marschall J , Drees M , Fakih MG , Hadaway L , Maragakis LL , Monsees E , Novosad S , O'Grady NP , Rupp ME , Wolf J , Yokoe D , Mermel LA . Infect Control Hosp Epidemiol 2022 43 (5) 1-17 Previously published guidelines provide 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 in implementing and prioritizing their central line-associated bloodstream infection (CLABSI) prevention efforts. This document updates the Strategies to Prevent Central Line-Associated Bloodstream Infections in Acute-Care Hospitals published in 2014. 1 This expert guidance document is sponsored by the Society for Healthcare Epidemiology of America (SHEA). It 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, with major contributions from representatives of a number of organizations and societies with content expertise. |
The 2021 WHO catalogue of Mycobacterium tuberculosis complex mutations associated with drug resistance: a genotypic analysis
Walker TM , Fowler PW , Knaggs J , Hunt M , Peto TE , Walker AS , Crook DW , Walker TM , Miotto P , Cirillo DM , Kser CU , Knaggs J , Iqbal Z , Hunt M , Chindelevitch L , Farhat MR , Comas I , Comas I , Posey J , Omar SV , Peto TE , Walker AS , Crook DW , Suresh A , Uplekar S , Laurent S , Colman RE , Rodwell TC , Nathanson CM , Zignol M , Ismail N , Rodwell TC , Walker AS , Steyn AJC , Lalvani A , Baulard A , Christoffels A , Mendoza-Ticona A , Trovato A , Skrahina A , Lachapelle AS , Brankin A , Piatek A , GibertoniCruz A , Koch A , Cabibbe AM , Spitaleri A , Brandao AP , Chaiprasert A , Suresh A , Barbova A , VanRie A , Ghodousi A , Bainomugisa A , Mandal A , Roohi A , Javid B , Zhu B , Letcher B , Rodrigues C , Nimmo C , Nathanson CM , Duncan C , Coulter C , Utpatel C , Liu C , Grazian C , Kong C , Kser CU , Wilson DJ , Cirillo DM , Matias D , Jorgensen D , Zimenkov D , Chetty D , Moore DA , Clifton DA , Crook DW , vanSoolingen D , Liu D , Kohlerschmidt D , Barreira D , Ngcamu D , SantosLazaro ED , Kelly E , Borroni E , Roycroft E , Andre E , Bttger EC , Robinson E , Menardo F , Mendes FF , Jamieson FB , Coll F , Gao GF , Kasule GW , Rossolini GM , Rodger G , Smith EG , Meintjes G , Thwaites G , Hoffmann H , Albert H , Cox H , Laurenson IF , Comas I , Arandjelovic I , Barilar I , Robledo J , Millard J , Johnston J , Posey J , Andrews JR , Knaggs J , Gardy J , Guthrie J , Taylor J , Werngren J , Metcalfe J , Coronel J , Shea J , Carter J , Pinhata JM , Kus JV , Todt K , Holt K , Nilgiriwala KS , Ghisi KT , Malone KM , Faksri K , Musser KA , Joseph L , Rigouts L , Chindelevitch L , Jarrett L , Grandjean L , Ferrazoli L , Rodrigues M , Farhat M , Schito M , Fitzgibbon MM , Loemb MM , Wijkander M , Ballif M , Rabodoarivelo MS , Mihalic M , Wilcox M , Hunt M , Zignol M , Merker M , Egger M , O'Donnell M , Caws M , Wu MH , Whitfield MG , Inouye M , Mansj M , DangThi MH , Joloba M , Kamal SM , Okozi N , Ismail N , Mistry N , Hoang NN , Rakotosamimanana N , Paton NI , Rancoita PMV , Miotto P , Lapierre P , Hall PJ , Tang P , Claxton P , Wintringer P , Keller PM , Thai PVK , Fowler PW , Supply P , Srilohasin P , Suriyaphol P , Rathod P , Kambli P , Groenheit R , Colman RE , Ong RTH , Warren RM , Wilkinson RJ , Diel R , Oliveira RS , Khot R , Jou R , Tahseen S , Laurent S , Gharbia S , Kouchaki S , Shah S , Plesnik S , Earle SG , Dunstan S , Hoosdally SJ , Mitarai S , Gagneux S , Omar SV , Yao SY , GrandjeanLapierre S , Battaglia S , Niemann S , Pandey S , Uplekar S , Halse TA , Cohen T , Cortes T , Prammananan T , Kohl TA , Thuong NTT , Teo TY , Peto TEA , Rodwell TC , William T , Walker TM , Rogers TR , Surve U , Mathys V , Furi V , Cook V , Vijay S , Escuyer V , Dreyer V , Sintchenko V , Saphonn V , Solano W , Lin WH , vanGemert W , He W , Yang Y , Zhao Y , Qin Y , Xiao YX , Hasan Z , Iqbal Z , Puyen ZM , CryPticConsortium theSeq , Treat Consortium . Lancet Microbe 2022 3 (4) e265-e273 Background: Molecular diagnostics are considered the most promising route to achievement of rapid, universal drug susceptibility testing for Mycobacterium tuberculosis complex (MTBC). We aimed to generate a WHO-endorsed catalogue of mutations to serve as a global standard for interpreting molecular information for drug resistance prediction. Methods: In this systematic analysis, we used a candidate gene approach to identify mutations associated with resistance or consistent with susceptibility for 13 WHO-endorsed antituberculosis drugs. We collected existing worldwide MTBC whole-genome sequencing data and phenotypic data from academic groups and consortia, reference laboratories, public health organisations, and published literature. We categorised phenotypes as follows: methods and critical concentrations currently endorsed by WHO (category 1); critical concentrations previously endorsed by WHO for those methods (category 2); methods or critical concentrations not currently endorsed by WHO (category 3). For each mutation, we used a contingency table of binary phenotypes and presence or absence of the mutation to compute positive predictive value, and we used Fisher's exact tests to generate odds ratios and Benjamini-Hochberg corrected p values. Mutations were graded as associated with resistance if present in at least five isolates, if the odds ratio was more than 1 with a statistically significant corrected p value, and if the lower bound of the 95% CI on the positive predictive value for phenotypic resistance was greater than 25%. A series of expert rules were applied for final confidence grading of each mutation. Findings: We analysed 41 137 MTBC isolates with phenotypic and whole-genome sequencing data from 45 countries. 38 215 MTBC isolates passed quality control steps and were included in the final analysis. 15 667 associations were computed for 13 211 unique mutations linked to one or more drugs. 1149 (73%) of 15 667 mutations were classified as associated with phenotypic resistance and 107 (07%) were deemed consistent with susceptibility. For rifampicin, isoniazid, ethambutol, fluoroquinolones, and streptomycin, the mutations' pooled sensitivity was more than 80%. Specificity was over 95% for all drugs except ethionamide (914%), moxifloxacin (916%) and ethambutol (933%). Only two resistance mutations were identified for bedaquiline, delamanid, clofazimine, and linezolid as prevalence of phenotypic resistance was low for these drugs. Interpretation: We present the first WHO-endorsed catalogue of molecular targets for MTBC drug susceptibility testing, which is intended to provide a global standard for resistance interpretation. The existence of this catalogue should encourage the implementation of molecular diagnostics by national tuberculosis programmes. Funding: Unitaid, Wellcome Trust, UK Medical Research Council, and Bill and Melinda Gates Foundation. 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license |
Zootherapy as a potential pathway for zoonotic spillover: a mixed-methods study of the use of animal products in medicinal and cultural practices in Nigeria.
Friant S , Bonwitt J , Ayambem WA , Ifebueme NM , Alobi AO , Otukpa OM , Bennett AJ , Shea C , Rothman JM , Goldberg TL , Jacka JK . One Health Outlook 2022 4 (1) 5 BACKGROUND: Understanding how and why people interact with animals is important for the prevention and control of zoonoses. To date, studies have primarily focused on the most visible forms of human-animal contact (e.g., hunting and consumption), thereby blinding One Health researchers and practitioners to the broader range of human-animal interactions that can serve as cryptic sources of zoonotic diseases. Zootherapy, the use of animal products for traditional medicine and cultural practices, is widespread and can generate opportunities for human exposure to zoonoses. Existing research examining zootherapies omits details necessary to adequately assess potential zoonotic risks. METHODS: We used a mixed-methods approach, combining quantitative and qualitative data from questionnaires, key informant interviews, and field notes to examine the use of zootherapy in nine villages engaged in wildlife hunting, consumption, and trade in Cross River State, Nigeria. We analyzed medicinal and cultural practices involving animals from a zoonotic disease perspective, by including details of animal use that may generate pathways for zoonotic transmission. We also examined the sociodemographic, cultural, and environmental contexts of zootherapeutic practices that can further shape the nature and frequency of human-animal interactions. RESULTS: Within our study population, people reported using 44 different animal species for zootherapeutic practices, including taxonomic groups considered to be "high risk" for zoonoses and threatened with extinction. Variation in use of animal parts, preparation norms, and administration practices generated a highly diverse set of zootherapeutic practices (n = 292) and potential zoonotic exposure risks. Use of zootherapy was patterned by demographic and environmental contexts, with zootherapy more commonly practiced by hunting households (OR = 2.47, p < 0.01), and prescriptions that were gender and age specific (e.g., maternal and pediatric care) or highly seasonal (e.g., associated with annual festivals and seasonal illnesses). Specific practices were informed by species availability and theories of healing (i.e., "like cures like" and sympathetic healing and magic) that further shaped the nature of human-animal interactions via zootherapy. CONCLUSIONS: Epidemiological investigations of zoonoses and public health interventions that aim to reduce zoonotic exposures should explicitly consider zootherapy as a potential pathway for disease transmission and consider the sociocultural and environmental contexts of their use in health messaging and interventions. |
Recommended Adult Immunization Schedule, United States, 2022.
Murthy N , Wodi AP , Bernstein H , Ault KA . Ann Intern Med 2022 175 (3) 432-443 In November 2021, the Advisory Committee on Immunization Practices (ACIP) voted to approve the Recommended Adult Immunization Schedule for Ages 19 Years or Older, United States, 2022. The 2022 adult immunization schedule, available at www.cdc.gov/vaccines/schedules/hcp/imz/adult.html, summarizes ACIP recommendations in the cover page, tables, notes, and appendix (Figure). The appendix lists the contraindications and precautions for all routinely recommended vaccines on the adult immunization schedule (Figure). The full ACIP recommendations for each vaccine are available at www.cdc.gov/vaccines/hcp/acip-recs/index.html. The 2022 schedule has also been approved by the director of the Centers for Disease Control and Prevention (CDC) and by the American College of Physicians (www.acponline.org), the American Academy of Family Physicians (www.aafp.org), the American College of Obstetricians and Gynecologists (www.acog.org), the American College of Nurse-Midwives (www.midwife.org), the American Academy of Physician Associates (www.aapa.org), and the Society for Healthcare Epidemiology of America (www.shea-online.org). |
Advisory Committee on Immunization Practices recommended immunization schedule for adults aged 19 years or older - United States, 2022
Murthy N , Wodi AP , Bernstein H , McNally V , Cineas S , Ault K . MMWR Morb Mortal Wkly Rep 2022 71 (7) 229-233 At its November 2021 meeting, the Advisory Committee on Immunization Practices* (ACIP) approved the Recommended Adult Immunization Schedule for Ages 19 Years or Older, United States, 2022. The 2022 adult immunization schedule summarizes ACIP recommendations, including several changes to the cover page, tables, and notes from the 2021 immunization schedule.() In addition, the 2022 adult immunization schedule provides an appendix that lists the contraindications to and precautions for all routinely recommended vaccines in the schedule. This schedule can be found on the CDC immunization schedule website (https://www.cdc.gov/vaccines/schedules). Health care providers are advised to use the cover page, tables, notes, and appendix together. This adult immunization schedule is recommended by ACIP (https://www.cdc.gov/vaccines/acip) and approved by CDC (https://www.cdc.gov), the American College of Physicians (https://www.acponline.org), the American Academy of Family Physicians (https://www.aafp.org), the American College of Obstetricians and Gynecologists (https://www.acog.org), the American College of Nurse-Midwives (https://www.midwife.org), the American Academy of Physician Associates (https://www.aapa.org), and the Society for Healthcare Epidemiology of America (https://www.shea-online.org). |
How infection present at time of surgery (PATOS) data impacts your surgical site infection (SSI) standardized infection ratios (SIR), with focus on the complex 30-day SSI SIR model
Konnor R , Russo V , Leaptrot D , Allen-Bridson K , Dudeck MA , Hebden JN , Wright MO . Am J Infect Control 2021 49 (11) 1423-1426 This case study is part of a series centered on the Centers for Disease Control and Prevention's National Healthcare Safety Network's (NHSN) health care-associated infection (HAI) surveillance definitions. This is the first analytic case study published in AJIC since the CDC/ NHSN updated its HAI risk adjustment models and rebaselined the standardized infection ratios (SIRs) in 2015. This case describes a scenario that Infection Preventionists (IPs) have encountered during their analysis of surgical site infection (SSI) surveillance data. The case study is intended to illustrate how specific models can impact the SIR results by highlighting differences in the criteria for NHSN's older and newer risk models: the original versions and the updated models introduced in 2015. Understanding these differences provides insight into how SSI SIR calculations differ between the older and newer NHSN baseline models. NHSN plans to produce another set of HAI risk adjustment models in the future, using newer HAI incidence and risk factor data. While the timetable for these changes remains to be determined, the statistical methods used to produce future models and SIR calculations will continue the precedents that NHSN has established. An online survey link is provided where participants may confidentially answer questions related to the case study and receive immediate feedback in the form of correct answers, explanations, rationales, and summary of teaching points. Details of the case study, answers, and explanations have been reviewed and approved by NHSN staff. We hope that participants take advantage of this educational offering and thereby gain a greater understanding of the NHSN's HAI data analysis. There are 2 baselines available for SSI standardized infection ration (SIRs) in the National Healthcare Safety Network (NHSN); one based on the 2006-2008 national aggregate data and another based on the 2015 data. Each of the 2 baselines has a different set of inclusion criteria for the SSI data, which impact the calculation of the SIR. In this case study, we focused on the impact of the inclusion of PATOS in the calculation of the 2006-2008 baseline SSI SIR and the exclusion of PATOS from the calculation of the 2015 baseline SSI SIR. In the 2006-2008 baseline SSI SIRs, PATOS events and the procedures to which they are linked are included in the calculation of the SSI SIR whereas in the 2015 baseline SSI SIRs, PATOS events and the procedures to which they are linked are excluded from the calculation of the SSI SIR. Meaning, if we control for all other inclusion criteria other than PATOS data for both baselines, we will notice differences in the number of observed events as well as the number of predicted infections for the 2 baselines. For details of the 2015 baseline and risk adjustment calculation, please review the NHSN Guide to the SIR referenced below. For details of the 2006-2008 baseline4 and risk adjustment, please see the SHEA paper "Improving Risk-Adjusted Measures of Surgical Site Infection for the National Healthcare Safety Network" by author Yi Mu. |
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