SummaryBackgroundHealthcare personnel (HCP) are at increased risk of infection with the severe acute respiratory coronavirus 2019 virus (SARS-CoV-2). Between 12 March 2020 and 10 January 2021, >1,170 HCP tested positive for SARS-CoV-2 at a major academic medical institution in the Upper Midwest of the United States. We aimed to understand the sources of infections in HCP and to evaluate the efficacy of infection control procedures used at this institution to protect HCP from healthcare-associated transmission.MethodsIn this retrospective case series, we used viral genomics to investigate the likely source of SARS-CoV-2 infection in 96 HCP where epidemiological data alone could not be used to rule out healthcare-associated transmission. We obtained limited epidemiological data through informal interviews and review of the electronic health record. We combined viral sequence data and available epidemiological information to infer the most likely source of HCP infection.FindingsWe investigated 32 SARS-CoV-2 infection clusters involving 96 HCP, 140 possible patient contacts, and 1 household contact (total n = 237). Of these, 182 sequences met quality standards and were used for downstream analysis. We found the majority of HCP infections could not be linked to a patient or co-worker and therefore likely occurred in the outside community (58/96; 60.4%). We found a smaller percentage could be traced to a coworker (10/96; 10.4%) or were part of a patient-employee cluster (12/96; 12.5%). Strikingly, the smallest proportion of HCP infections could be clearly traced to a patient source (4/96; 4.2%).InterpretationInfection control procedures, consistently followed, offer significant protection to HCP caring for COVID-19 patients in a representative American academic medical institution. Rapid SARS-CoV-2 genome sequencing in healthcare settings can be used retrospectively to reconstruct the likely source of HCP infection when epidemiological data are not available or are inconclusive. Understanding the source of SARS-CoV-2 infection can then be used prospectively to adjust and improve infection control practices and guidelines.FundingThis project was funded in part through a COVID-19 Response grant from the Wisconsin Partnership Program at the University of Wisconsin School of Medicine and Public Health to T.C.F. and D.H.O. Author N.S. is supported by the National Institute of Allergy and Infectious Diseases Institute (NIAID) Grant 1DP2AI144244-01.Research in contextEvidence before this studyOn 16 January 2021 we searched for “SARS-CoV-2” AND “healthcare workers” AND “viral sequencing” in Google Scholar. This search returned 57 results, and included a number of preprint articles. We found two studies that used viral sequencing to investigate healthcare-associated outbreaks in the Netherlands 1 and the United Kingdom 2. To our knowledge, no study has used viral sequencing to specifically investigate the source of SARS-CoV-2 infections in healthcare workers in the United States. Although we and others have written about the potential utility of sequencing as an infection control asset 3–6, few have demonstrated the practical application of such efforts.Added value of this studyOur study suggests infection control measures in place at the institution evaluated in this case series are largely protecting healthcare personnel (HCP) from healthcare-associated SARS-CoV-2 infections. Even so, the majority of healthcare-associated infections we did identify appeared to be linked to HCP-to-HCP spread so additional messaging and guidelines to reduce HCP-to-HCP spread in and out of the workplace may be warranted. In addition, we demonstrated how rapid viral sequencing can be combined with, even limited, epidemiological information to reconstruct healthcare-associated SARS-CoV-2 outbreaks.Implications of all the available evidenceHealthcare-associated SARS-CoV-2 infections negatively affect HCP, patients, and communities. Infections among HCP add further strain to the healthcare system and put patients and other HCP at risk. We found the majority of HCP infections appeared to be acquired through community exposure so measures to reduce community spread are critical. This further emphasizes the importance of mask-wearing, physical distancing, robust testing programs, and the rapid distribution of vaccines.

Model‐informed drug development (MIDD) has a long and rich history in infectious diseases. This review describes foundational principles of translational anti‐infective pharmacology, including choice of appropriate measures of exposure and pharmacodynamic (PD) measures, patient subpopulations, and drug‐drug interactions. Examples are presented for state‐of‐the‐art, empiric, mechanistic, interdisciplinary, and real‐world evidence MIDD applications in the development of antibacterials (review of minimum inhibitory concentration‐based models, mechanism‐based pharmacokinetic/PD (PK/PD) models, PK/PD models of resistance, and immune response), antifungals, antivirals, drugs for the treatment of global health infectious diseases, and medical countermeasures. The degree of adoption of MIDD practices across the infectious diseases field is also summarized. The future application of MIDD in infectious diseases will progress along two planes; “depth” and “breadth” of MIDD methods. “MIDD depth” refers to deeper incorporation of the specific pathogen biology and intrinsic and acquired‐resistance mechanisms; host factors, such as immunologic response and infection site, to enable deeper interrogation of pharmacological impact on pathogen clearance; clinical outcome and emergence of resistance from a pathogen; and patient and population perspective. In particular, improved early assessment of the emergence of resistance potential will become a greater focus in MIDD, as this is poorly mitigated by current development approaches. “MIDD breadth” refers to greater adoption of model‐centered approaches to anti‐infective development. Specifically, this means how various MIDD approaches and translational tools can be integrated or connected in a systematic way that supports decision making by key stakeholders (sponsors, regulators, and payers) across the entire development pathway.

Animal infection models serve a critical role in the pre-clinical development of antimicrobials. Thoughtful use of these tools can be useful to design and de-risk subsequent clinical trials. Specifically, pharmacokinetic/pharmacodynamic (PK/PD) evaluation of antimicrobials can define the PK/PD driver and target magnitude. In doing so they provide guidance for dosing regimen design and forecast the likelihood of success against target pathogens at the infection site of interest. This review outlines the key design features to consider for successful assessment of experimental output.

Published Ahead of Print 9 December 2013. 10.1128/AAC.01877-13. 2014, 58(3):1327. DOI: Antimicrob. Agents Chemother. and James H. Jorgensen Sabol-Dzintars William A. Craig, David R. Andes, Kathryn E. James S. Lewis II, Alex J. Lepak, George R. Thompson III, Animal Model and in Human Infections Inducibly Resistant to Clindamycin in an Infection with Beta-Hemolytic Streptococci Failure of Clindamycin To Eradicate

Inducible clindamycin resistance in beta-hemolytic streptococci remains an underrecognized phenomenon of unknown clinical significance. We performed an evaluation of inducible clindamycin resistance using an animal model as well as retrospectively reviewing the charts of patients treated with clindamycin monotherapy who were infected with beta-hemolytic streptococci inducibly resistant to clindamycin. The neutropenic mouse thigh model of infection was used to evaluate the in vivo activity of clindamycin against beta-hemolytic streptococci, including isolates susceptible, inducibly resistant, or constitutively resistant to clindamycin. The clinical microbiology laboratory information system and pharmacy databases were cross-referenced to identify patients with infections due to inducibly clindamycin-resistant beta-hemolytic streptococci who were treated with clindamycin monotherapy. Medical records of these patients were reviewed to evaluate microbiologic and clinical outcomes. Inducible clindamycin resistance resulted in impaired killing of beta-hemolytic streptococci in the animal model. Though suppressed initially, compared to those with constitutive resistance (P=0.0429), by 48 h, colony counts of inducibly clindamycin-resistant organisms were similar to those of constitutively resistant isolates (P=0.1142). In addition, we identified 8 patients infected with inducibly clindamycin-resistant beta-hemolytic streptococci who experienced clinical and microbiologic failure when treated with clindamycin monotherapy. These patients either improved initially and subsequently failed or never responded to clindamycin therapy. We have demonstrated in a murine model of infection and from human cases that inducible clindamycin resistance in beta-hemolytic streptococci is clinically significant. Routine testing and reporting by clinical laboratories should be encouraged and alternative antimicrobial agents considered when these organisms are encountered in clinical care.

ABSTRACT Previous pharmacodynamic studies using in vivo candidiasis models have demonstrated that the 24-h area under the concentration-time curve (AUC)/MIC is a good descriptor of the echinocandin exposure-response relationship. Further studies investigating the 24-h AUC/MIC target for a stasis endpoint identified free-drug 24-h AUC/MIC against Candida albicans and were similar for two echinocandins, anidulafungin and micafungin. The current studies expand investigation of a third echinocandin (caspofungin) and compare the pharmacodynamic target among C. albicans, Candida glabrata, and Candida parapsilosis. Treatment studies were conducted with six C. albicans, nine C. glabrata, and 15 C. parapsilosis strains with various MICs (anidulafungin, 0.015 to 4.0 μg/ml; caspofungin, 0.03 to 4.0 μg/ml; and micafungin, 0.008 to 1.0 μg/ml). Efficacy was closely tied to MIC and the 24-h AUC/MIC. Therapy against C. parapsilosis required more of each echinocandin on a mg/kg basis. Caspofungin required less drug on a mg/kg basis for efficacy against all of the organisms than did the other two drugs. However, the 24-h AUC/MIC targets were similar among the echinocandins when free drug concentrations were considered, suggesting the relevance of protein binding. The targets for C. parapsilosis (mean, 7) and C. glabrata (mean, 7) were significantly lower than those for C. albicans (mean, 20) for each echinocandin. The results suggest that current susceptibility breakpoints and the consideration of organism species in these determinations should be reexplored.

Pharmacodynamic studies examine the relationship between drug pharmacokinetics and outcome. These investigations have been shown to be helpful for the design of dosing intervals, choice of optimal dose levels, and the development of susceptibility breakpoints. Pharmacodynamic studies with available antifungal agents have been useful in developing optimal dosing regimens to improve efficacy and reduce treatment-associated toxicities. This review summarizes accepted antifungal concepts and discusses recent advances in the field.

ABSTRACT Pharmacodynamics (PD) considers the relationship between drug exposure and effect. The two factors that have been used to distinguish the PD behaviors of antimicrobials are the impact of concentration on the extent of organism killing and the duration of persistent microbiologic suppression (postantibiotic effect). The goals of these studies were (i) to examine the relationship between antimicrobial PD and gene expression and (ii) to gain insight into the mechanism of fluconazole effects persisting following exposure. Microarrays were used to estimate the transcriptional response of Candida albicans to a supra-MIC F exposure over time in vitro. Fluconazole at four times the MIC was added to a log-phase C. albicans culture, and cells were collected to determine viable growth and for microarray analyses. We identified differential expression of 18% of all genes for at least one of the time points. More genes were upregulated ( n = 1,053 [16%]) than downregulated (174 [3%]). Of genes with known function that were upregulated during exposure, most were related to plasma membrane/cell wall synthesis (18%), stress responses (7%), and metabolism (6%). The categories of downregulated genes during exposure included protein synthesis (15%), DNA synthesis/repair (7%), and transport (7%) genes. The majority of genes identified at the postexposure time points were from the protein (17%) and DNA (7%) synthesis categories. In subsequent studies, three genes ( CDR1 , CDR2 , and ERG11 ) were examined in greater detail (more concentration and time points) following fluconazole exposure in vitro and in vivo. Expression levels from the in vitro and in vivo studies were congruent. CDR1 and CDR2 transcripts were reduced during in vitro fluconazole exposure and during supra-MIC exposure in vivo. However, in the postexposure period, the mRNA abundance of both pumps increased. ERG11 expression increased during exposure and fell in the postexposure period. The expression of the three genes responded in a dose-dependent manner. In sum, the microarray data obtained during and following fluconazole exposure identified genes both known and unknown to be affected by this drug class. The expanded in vitro and in vivo expression data set underscores the importance of considering the time course of exposure in pharmacogenomic investigations.

ABSTRACTAntimicrobial drug resistance can limit the ability to effectively treat patients. Numerous factors have been proposed to impact the development of antimicrobial resistance, including those specific to the drug and the dosing regimen. The field of investigation that examines the relationship between dosing regimen and outcome is termed antimicrobial pharmacokinetics and pharmacodynamics. Our prior in vivo investigations examined the relationship between fluconazole pharmacodynamics and the modulation of isogenic resistant and susceptibleCandida albicanspopulations in a mixed-inoculum design (1). The goal of the current studies was to examine the impact of fluconazole pharmacodynamics on resistance emergence from a susceptible parent population over time using a murine systemic-candidiasis model. Both microbiologic and transcriptional endpoints were examined during the evolution of cell populations. As in our previous investigation, the more frequently administered dosing regimen prevented the emergence of a resistant cell phenotype. Conversely, dosing regimens that produced prolonged sub-MIC concentrations were associated with resistance development. The studies also demonstrated a striking relationship between fluconazole pharmacodynamic exposures and the mRNA abundance of drug resistance-associated efflux pumps. Global transcriptional profiling of cell populations during the progressive emergence of a resistance phenotype provides insight into the mechanisms underlying this complex physiologic process.

Gene expression analysis after the host-pathogen interaction is revolutionizing our understanding of the host response to infection. Numerous studies have utilized microarray analysis to follow host cell transcriptome alterations in response to interactions with infectious pathogens. However, similar analyses of pathogen transcriptional adaptation at the infection site have been limited. Understanding the nature of this interaction from the pathogen perspective at different sites and stages of infection is central to strategies for development of new anti-infective therapies. Toward this end, we developed a protocol to analyze changes in gene expression for a eukaryotic pathogen, Candida albicans, during systemic infection in mice. The experimental approach takes advantage of the resistance of the cell wall of many fungal pathogens to cell lysis, relative to mammalian cells. After lysis of mammalian cells, the tissue mixture containing fungal cells is depleted of mammalian RNA by centrifugation, followed by enzymatic digestion. RNA-digesting enzymes are then inhibited before eukaryotic cell lysis and RNA isolation. The protocol provides a reproducible quantity of RNA based on pathogen cell number. The quality of the RNA allowed reliable downstream transcriptional analysis using reverse-transcription polymerase chain reaction and microarrays. The in vivo gene expression data confirmed involvement of several putative pathogenesis genes. More importantly, the results provided a wealth of biologically interesting hypotheses to direct future investigation.