Integrated Genomic and Social Network Analyses of SARS-CoV-2 Transmission in the Healthcare Setting.

BACKGROUND: Infection prevention (IP) measures are designed to mitigate the transmission of pathogens in healthcare. Using large-scale viral genomic and social network analyses, we determined if IP measures used during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic were adequate in protecting healthcare workers (HCWs) and patients from acquiring SARS-CoV-2. METHODS: We performed retrospective cross-sectional analyses of viral genomics from all available SARS-CoV-2 viral samples collected at UC San Diego Health and social network analysis using the electronic medical record to derive temporospatial overlap of infections among related viromes and supplemented with contact tracing data. The outcome measure was any instance of healthcare transmission, defined as cases with closely related viral genomes and epidemiological connection within the healthcare setting during the infection window. Between November 2020 through January 2022, 12 933 viral genomes were obtained from 35 666 patients and HCWs. RESULTS: Among 5112 SARS-CoV-2 viral samples sequenced from the second and third waves of SARS-CoV-2 (pre-Omicron), 291 pairs were derived from persons with a plausible healthcare overlap. Of these, 34 pairs (12%) were phylogenetically linked: 19 attributable to household and 14 to healthcare transmission. During the Omicron wave, 2106 contact pairs among 7821 sequences resulted in 120 (6%) related pairs among 32 clusters, of which 10 were consistent with healthcare transmission. Transmission was more likely to occur in shared spaces in the older hospital compared with the newer hospital (2.54 vs 0.63 transmission events per 1000 admissions, P < .001). CONCLUSIONS: IP strategies were effective at identifying and preventing healthcare SARS-CoV-2 transmission.

A Risk-Based Clinical Decision Support System for Patient-Specific Antimicrobial Therapy (iBiogram): Design and Retrospective Analysis.

BACKGROUND: There is a pressing need for digital tools that can leverage big data to help clinicians select effective antibiotic treatments in the absence of timely susceptibility data. Clinical presentation and local epidemiology can inform therapy selection to balance the risk of antimicrobial resistance and patient risk. However, data and clinical expertise must be appropriately integrated into clinical workflows. OBJECTIVE: The aim of this study is to leverage available data in electronic health records, to develop a data-driven, user-centered, clinical decision support system to navigate patient safety and population health. METHODS: We analyzed 5 years of susceptibility testing (1,078,510 isolates) and patient data (30,761 patients) across a large academic medical center. After curating the data according to the Clinical and Laboratory Standards Institute guidelines, we analyzed and visualized the impact of risk factors on clinical outcomes. On the basis of this data-driven understanding, we developed a probabilistic algorithm that maps these data to individual cases and implemented iBiogram, a prototype digital empiric antimicrobial clinical decision support system, which we evaluated against actual prescribing outcomes. RESULTS: We determined patient-specific factors across syndromes and contexts and identified relevant local patterns of antimicrobial resistance by clinical syndrome. Mortality and length of stay differed significantly depending on these factors and could be used to generate heuristic targets for an acceptable risk of underprescription. Combined with the developed remaining risk algorithm, these factors can be used to inform clinicians' reasoning. A retrospective comparison of the iBiogram-suggested therapies versus the actual prescription by physicians showed similar performance for low-risk diseases such as urinary tract infections, whereas iBiogram recognized risk and recommended more appropriate coverage in high mortality conditions such as sepsis. CONCLUSIONS: The application of such data-driven, patient-centered tools may guide empirical prescription for clinicians to balance morbidity and mortality with antimicrobial stewardship.

Public Health Role of Academic Medical Center in Community Outbreak of Hepatitis A, San Diego County, California, USA, 2016-2018.

During 2016-2018, San Diego County, California, USA, experienced one of the largest hepatitis A outbreaks in the United States in 2 decades. In close partnership with local healthcare systems, San Diego County Public Health led a public health response to the outbreak that focused on a 3-pronged strategy to vaccinate, sanitize, and educate. Healthcare systems administered nearly half of the vaccinations delivered in San Diego County. At University of California San Diego Health, the use of informatics tools assisted with the identification of at-risk populations and with vaccine delivery across outpatient and inpatient settings. In addition, acute care facilities helped prevent further disease transmission by delaying the discharge of patients with hepatitis A who were experiencing homelessness. We assessed the public health roles that acute care hospitals can play during a large community outbreak and the critical nature of ongoing collaboration between hospitals and public health systems in controlling such outbreaks.

Tuberculosis infection risk, preventive therapy care cascade and incidence of tuberculosis disease in healthcare workers at Maputo Central Hospital.

BACKGROUND: Mozambican healthcare workers have high rates of latent and active tuberculosis, but occupational screening for tuberculosis is not routine in this setting. Furthermore, the specificity of tuberculin skin testing in this population compared with interferon gamma release assay testing has not been established. METHODS: This study was conducted among healthcare workers at Maputo Central Hospital, a public teaching quaternary care hospital in Mozambique. With a cross sectional study design, risk factors for tuberculosis were assessed using multivariable logistic regression. The care cascade is reported for participants who were prescribed six months of isoniazid preventive therapy for HIV or highly reactive testing for latent tuberculosis infection. The agreement of interferon-gamma release assay results with positive tuberculin skin testing was calculated. RESULTS: Of 690 screened healthcare workers, three (0.4%) had active tuberculosis and 426 (61.7%) had latent tuberculosis infection. Less education, age 35-49, longer hospital service, and work in the surgery department were associated with increased likelihood of being tuberculosis infected at baseline (p < 0.05). Sex, Bacillus Calmette-Guerin vaccination, HIV, outside tuberculosis contacts, and professional category were not. Three new cases of active tuberculosis developed during the follow-up period, two while on preventive therapy. Among 333 participants offered isoniazid preventive therapy, five stopped due to gastrointestinal side effects and 181 completed treatment. For HIV seropositive individuals, the agreement of interferon gamma release assay positivity with positive tuberculin skin testing was 50% among those with a quantitative skin test result of 5-10 mm, and among those with a skin test result ≥10 mm it was 87.5%. For HIV seronegative individuals, the agreement of interferon gamma release assay positivity with a tuberculin skin test result of 10-14 mm was 63.6%, and for those with a quantitative skin test result ≥15 mm it was 82.2%. CONCLUSIONS: There is a high prevalence of tuberculosis infected healthcare workers at Maputo Central Hospital. The surgery department was most heavily affected, suggesting occupational risk. Isoniazid preventive therapy initiation was high and just over half completed therapy. An interferon gamma release assay was useful to discern LTBI from false positives among those with lower quantitative tuberculin skin test results.

Validation of a questionnaire to monitor symptoms in HIV-infected patients during hepatitis C treatment.

BACKGROUND: Clinicians are incorporating patient-reported outcomes in the management of HIV-infected persons co-infected with hepatitis C virus (HCV), but there are no validated inventories to monitor symptoms of patients during HCV therapy. DESIGN: Five-year retrospective cohort analysis of persons living with HIV (PLWH) treated for HCV. METHODS: The HCV symptom-inventory (HCV-SI) was administered before, during, and after HCV treatment. Discriminant validity was assessed, separately, in mixed model linear regression of HCV-SI T-scores on treatment regimens (pegylated-interferon and ribavirin; pegylated-interferon, ribavirin, and telaprevir; and interferon-free antivirals); and side effect-related premature treatment discontinuation (SE-DC). RESULTS: From the 103 patients who completed the HCV-SI, 7% were female, 26% non-white, 32% cirrhotics and 91% had undetectable HIV viral loads. Most had genotype 1 (83%) and were HCV treatment-naïve (78%). We treated 19% of patients with pegylated-interferon and ribavirin, 22% with pegylated-interferon, ribavirin, and telaprevir and 59% received interferon-free antivirals. Overall, 77% achieved a sustained virologic response, and 6% discontinued HCV treatment due to side effects. In the treatment discrimination model, compared to the no treatment period, HCV-SI scores were significantly (p < 0.01) lower for interferon-free antivirals and higher for interferon-containing regimens. In the SE-DC model, the total HCV-SI, somatic and neuropsychiatric scores significantly predicted those patients who prematurely discontinued HCV treatment (P < 0.05). CONCLUSIONS: The HCV-SI effectively differentiated among treatment regimens known to vary by side effect profiles and between patients with and without treatment discontinuation due to side effects. The HCV-SI may have value as a patient-reported outcome instrument predicting the risk of HCV treatment discontinuation.

Genome of the pathogen Porphyromonas gingivalis recovered from a biofilm in a hospital sink using a high-throughput single-cell genomics platform.

Although biofilms have been shown to be reservoirs of pathogens, our knowledge of the microbial diversity in biofilms within critical areas, such as health care facilities, is limited. Available methods for pathogen identification and strain typing have some inherent restrictions. In particular, culturing will yield only a fraction of the species present, PCR of virulence or marker genes is mainly focused on a handful of known species, and shotgun metagenomics is limited in the ability to detect strain variations. In this study, we present a single-cell genome sequencing approach to address these limitations and demonstrate it by specifically targeting bacterial cells within a complex biofilm from a hospital bathroom sink drain. A newly developed, automated platform was used to generate genomic DNA by the multiple displacement amplification (MDA) technique from hundreds of single cells in parallel. MDA reactions were screened and classified by 16S rRNA gene PCR sequence, which revealed a broad range of bacteria covering 25 different genera representing environmental species, human commensals, and opportunistic human pathogens. Here we focus on the recovery of a nearly complete genome representing a novel strain of the periodontal pathogen Porphyromonas gingivalis (P. gingivalis JCVI SC001) using the single-cell assembly tool SPAdes. Single-cell genomics is becoming an accepted method to capture novel genomes, primarily in the marine and soil environments. Here we show for the first time that it also enables comparative genomic analysis of strain variation in a pathogen captured from complex biofilm samples in a healthcare facility.

Annual N95 respirator fit-testing: an unnecessary burden on healthcare.

US regulations mandate annual N95 mask fit testing for healthcare workers, but the optimal testing interval is unknown. In our study using data from 12,565 healthcare workers, the probability of survival free from fit-test failure after 3 years was 99.4%, suggesting that less frequent fit testing every 3 years would be safe.

Distribution of COVID-19 Home Testing Through Community Health Centers: Results of the COVID CoNOce MÁS Study.

OBJECTIVE: To assess acceptability and feasibility of rapid at-home COVID-19 testing and reporting of test results among individuals seeking care at community health centers (CHCs) and their household members. METHODS: Participants were recruited from 2 Community Health Centers during a clinic visit or a community event. Over-the-counter COVID-19 tests were distributed to participants for self-testing and to offer testing to household members. Separate surveys were administered to collect baseline information on the study participant and to collect test results on the study participant and household members. We calculated the proportion of individuals who agreed to complete COVID home testing, those who reported test results, and the test positivity. For household members, we calculated the proportion who completed and reported results and the positivity rate. We assessed reasons for undergoing COVID-19 testing and the action taken by participants who reported positive tests. RESULTS: A total of 2189 individuals were approached by CHC staff for participation and 1013 (46.3%) agreed to participate. Among the 959 participants with complete sociodemographic data, 88% were Hispanic and 82.6% were female. The proportion providing test results was 36.2% and the test positivity was 4.2%. Among the 1927 test reports, 35.3% for the index participant and 64.4% were for household members. The largest proportion of test results were for index participants (35.3%) and the second largest was for the participant's children (32.1%), followed by parents (16.9%), and spouse/partner (13.2%). The 2 most common reasons for testing were symptoms (29%) and attending family gatherings (26%). Among test-positive individuals (n = 80), most (83.3%) noted that they isolated but only 16.3% called their provider and 1.3% visited a clinic. CONCLUSION: Our results show interest in at-home COVID-19 testing of multiple household members, as we headed into the endemic phase of the pandemic. However, reporting of test results was modest and among test-positive individuals, reporting results to a provider was very low. These results underscore the challenges with reporting and following guidelines among people undergoing home testing for COVID-19, which may have implications for future pandemics.

Assessing past versus present severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection: A survey of criteria for discontinuing precautions in asymptomatic patients testing positive on admission.

Infection prevention program leaders report frequent use of criteria to distinguish recently recovered coronavirus disease 2019 (COVID-19) cases from actively infectious cases when incidentally positive asymptomatic patients were identified on routine severe acute respiratory coronavirus virus 2 (SARS-CoV-2) polymerase chain reaction (PCR) testing. Guidance on appropriate interpretation of high-sensitivity molecular tests can prevent harm from unnecessary precautions that delay admission and impede medical care.

Stethoscope barriers narrative review; It's time for a strategy unfriendly to multi-drug resistant organisms (MDROs).

The current standard of stethoscope hygiene doesn't eliminate the transmission of harmful pathogens, including multi-drug resistant organisms (MDROs). In the era of the increasing prevalence of MDRO infections, the use of new systems providing touch free barriers may improve patient safety versus traditional stethoscope cleaning practices with chemical agents. Our purpose was to provide a narrative literature review regarding barriers as an improvement over the current standard of care for stethoscope hygiene. Searching PubMed, articles were identified if they were in English and published after 1990, using the search term "stethoscope barrier", or if they were from a previously published stethoscope hygiene article using "author's name + stethoscope". Included articles evaluated or discussed stethoscope barriers. Of 28 manuscripts identified, 15 met the inclusion criteria. Barriers were considered superior to alternatives if they were single use, disposable, applied in a touch free fashion, were impervious to pathogens, provided an aseptic patient contact, and were acoustically invisible. Use of a practitioner's personal stethoscope with a disposable diaphragm barrier should be recommended as a new standard of care as this represents an improvement in patient safety and patient experience when compared to the disposable stethoscope or isopropyl alcohol stethoscope diaphragm cleaning.

Increasing Hepatitis C treatment uptake among HIV-infected patients using an HIV primary care model.

BACKGROUND: Access to Hepatitis C (HCV) care is low among HIV-infected individuals, highlighting the need for new models to deliver care for this population. METHODS: Retrospective cohort analysis that compared the number of HIV patients who initiated HCV therapy: hepatology (2005-2008) vs. HIV primary care model (2008-2011). Logistic-regression modeling was used to ascertain factors associated with HCV therapy initiation and achievement of sustained viral response (SVR). RESULTS: Of 196 and 163 patients that were enrolled in the HIV primary care and hepatology models, 48 and 26 were treated for HCV, respectively (p = 0.043). The HIV/HCV-patient referral rate did not differ during the two study periods (0.10 vs. 0.12/patient-yr, p = 0.18). In unadjusted analysis, predictors (p < 0.05) of HCV treatment initiation included referral to the HIV primary care model (OR: 1.7), a CD4+ count ≥400/mm3 (OR: 1.8) and alanine aminotranferase level ≥63U/L (OR: 1.9). Prior psychiatric medication use correlated negatively with HCV treatment initiation (OR: 0.6, p = 0.045). In adjusted analysis the strongest predictor of HCV treatment initiation was CD4+ count (≥400/mm3, OR: 2.1, p = 0.01). There was no significant difference in either clinic model (primary care vs. hepatology) in the rates of treatment discontinuation due to adverse events (29% vs. 16%), loss to follow-up (8 vs. 8%), or HCV SVR (44 vs. 35%). CONCLUSIONS: Using a HIV primary care model increased the number of HIV patients who initiate HCV therapy with comparable outcomes to a hepatology model.

Hepatitis C Virus Micro-elimination Among People With HIV in San Diego: Are We on Track?

Background: Rising incidence of hepatitis C virus (HCV) among people with HIV (PWH) in San Diego County (SDC) was reported. In 2018, the University of California San Diego (UCSD) launched a micro-elimination initiative among PWH, and in 2020 SDC launched an initiative to reduce HCV incidence by 80% across 2015-2030. We model the impact of observed treatment scale-up on HCV micro-elimination among PWH in SDC. Methods: A model of HCV transmission among people who inject drugs (PWID) and men who have sex with men (MSM) was calibrated to SDC. The model was additionally stratified by age, gender, and HIV status. The model was calibrated to HCV viremia prevalence among PWH in 2010, 2018, and 2021 (42.1%, 18.5%, and 8.5%, respectively), and HCV seroprevalence among PWID aged 18-39 years, MSM, and MSM with HIV in 2015. We simulate treatment among PWH, weighted by UCSD Owen Clinic (reaching 26% of HCV-infected PWH) and non-UCSD treatment, calibrated to achieve the observed HCV viremia prevalence. We simulated HCV incidence with observed and further treatment scale-up (+/- risk reductions) among PWH. Results: Observed treatment scale-up from 2018 to 2021 will reduce HCV incidence among PWH in SDC from a mean of 429 infections/year in 2015 to 159 infections/year in 2030. County-wide scale-up to the maximum treatment rate achieved at UCSD Owen Clinic (in 2021) will reduce incidence by 69%, missing the 80% incidence reduction target by 2030 unless accompanied by behavioral risk reductions. Conclusions: As SDC progresses toward HCV micro-elimination among PWH, a comprehensive treatment and risk reduction approach is necessary to reach 2030 targets.

The dose-response relationship of peginterferon alfa-2a and ribavirin in the treatment of patients coinfected with HIV-HCV.

PURPOSE: The relationship between peginterferon/ribavirin exposure and the probability of achieving a sustained virologic response (SVR) in HIV-HCV coinfected patients is not well described. We conducted a retrospective analysis of HIV-HCV coinfected patients randomized to 48 weeks of treatment with peginterferon alfa-2a (40 kD) 180 µg/week and ribavirin 800 mg/day in the multinational APRICOT study to define optimal exposure thresholds. METHOD: Actual drug exposure was estimated in 287 patients, taking into consideration dose reductions for adverse events or laboratory abnormalities. RESULTS: SVR overall and SVR in those completing treatment was, respectively, 29% and 37% among HCV genotype-1 patients and 59% and 68% among genotype non-1 patients. No patients with ≤40% exposure to ribavirin achieved an SVR. Receiver operating characteristic analysis identified that threshold exposures to both drugs of >75% (genotype-1) and >60% (genotype non-1) are associated with SVR. An existing generalized additive model populated with data from HCV monoinfected patients was updated to predict an overall SVR of 37% if genotype-1 patients received ribavirin 1000 or 1200 mg/day but at the cost of a higher incidence of anemia (23%). CONCLUSION: Completion of scheduled treatment and exceeding certain thresholds for exposure to peginterferon alfa 2a (40 kD) and ribavirin is associated with higher SVR rates.

Reliability and predictive validity of a hepatitis-related symptom inventory in HIV-infected individuals referred for Hepatitis C treatment.

BACKGROUND: We aimed to determine the reliability and validity of a hepatitis symptom inventory and to identify predictors of hepatitis C (HCV) treatment initiation in a cohort of HIV-infected patients. METHODS: Prospective clinic based study that enrolled patients referred for HCV therapy consideration. A hepatitis symptom inventory and the Center for Epidemiologic Studies Depression Scale (CES-D) were administered to HIV/HCV individuals. The symptom inventory was factor analyzed and subscale reliability estimated with Cronbach's alpha. Predictive validity was evaluated using generalized estimating equations (GEE). Predictors of HCV treatment were identified using logistic regression. RESULTS: Between April 2008 to July 2010, 126 HIV/HCV co-infected patients were enrolled in the study. Factor analysis using data from 126 patients yielded a three-factor structure explaining 60% of the variance for the inventory. Factor 1 (neuropsychiatric symptoms) had 14 items, factor 2 (somatic symptoms) had eleven items, and factor 3 (sleep symptoms) had two items, explaining 28%, 22% and 11% of the variance, respectively. The three factor subscales demonstrated high intrinsic consistency reliability. GEE modeling of the 32 patients who initiated HCV therapy showed that patients developed worsening neuropsychiatric and somatic symptoms following HCV therapy with stable sleep symptoms. Bivariate analyses identified the following as predictors of HCV therapy initiation: lower HIV log10 RNA, lower scores for neuropsychiatric, somatic and sleep symptoms, lower CES-D scores and white ethnicity. In stepwise multiple logistic regression analysis, low neuropsychiatric symptom score was the strongest independent predictor of HCV therapy initiation and HIV log10 RNA was inversely associated with a decision to initiate HCV treatment. CONCLUSIONS: A 41-item hepatitis-related symptom inventory was found to have a clinically meaningful 3-factor structure with excellent internal consistency reliability and predictive validity. In adjusted analysis, low neuropsychiatric symptom scores and controlled HIV infection were independent predictors of HCV treatment initiation. The usefulness of the HCV symptom inventory in monitoring HCV treatment should be evaluated prospectively.