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2.
J Infect Dis ; 2022 May 10.
Article in English | MEDLINE | ID: covidwho-1886456
3.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-338346

ABSTRACT

For each of the COVID-19 pandemic waves, hospitals have had to plan for deploying surge capacity and resources to manage large but transient increases in COVID-19 admissions. While a lot of effort has gone into predicting regional trends in COVID-19 cases and hospitalizations, there are far fewer successful tools for creating accurate hospital-level forecasts. At the same time, anonymized phone-collected mobility data proved to correlate well with the number of cases for the first two waves of the pandemic (spring 2020, and fall-winter 2021). In this work, we show how mobility data could bolster hospital-specific COVID-19 admission forecasts for five hospitals in Massachusetts during the initial COVID-19 surge. The high predictive capability of the model was achieved by combining anonymized, aggregated mobile device data about users’ contact patterns, commuting volume, and mobility range with COVID hospitalizations and test-positivity data. We conclude that mobility-informed forecasting models can increase the lead-time of accurate predictions for individual hospitals, giving managers valuable time to strategize how best to allocate resources to manage forthcoming surges.

4.
Intensive Crit Care Nurs ; 70: 103227, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1828574

ABSTRACT

Patients in intensive care units (ICUs) are at high risk for healthcare-acquired infections (HAI) due to the high prevalence of invasive procedures and devices, induced immunosuppression, comorbidity, frailty and increased age. Over the past decade we have seen a successful reduction in the incidence of HAI related to invasive procedures and devices. However, the rate of ICU-acquired infections remains high. Within this context, the ongoing emergence of new pathogens, further complicates treatment and threatens patient outcomes. Additionally, the SARS-CoV-2 (COVID-19) pandemic highlighted the challenge that an emerging pathogen provides in adapting prevention measures regarding both the risk of exposure to caregivers and the need to maintain quality of care. ICU nurses hold a special place in the prevention and management of HAI as they are involved in basic hygienic care, steering and implementing quality improvement initiatives, correct microbiological sampling, and aspects antibiotic stewardship. The emergence of more sensitive microbiological techniques and our increased knowledge about interactions between critically ill patients and their microbiota are leading us to rethink how we define HAIs and best strategies to diagnose, treat and prevent these infections in the ICU. This multidisciplinary expert review, focused on the ICU setting, will summarise the recent epidemiology of ICU-HAI, discuss the place of modern microbiological techniques in their diagnosis, review operational and epidemiological definitions and redefine the place of several controversial preventive measures including antimicrobial-impregnated medical devices, chlorhexidine-impregnated washcloths, catheter dressings and chlorhexidine-based mouthwashes. Finally, general guidance is suggested that may reduce HAI incidence and especially outbreaks in ICUs.


Subject(s)
COVID-19 , Catheter-Related Infections , Cross Infection , Adult , Chlorhexidine , Cross Infection/diagnosis , Cross Infection/epidemiology , Cross Infection/prevention & control , Delivery of Health Care , Humans , Intensive Care Units , SARS-CoV-2
5.
Clin Infect Dis ; 2022 Mar 10.
Article in English | MEDLINE | ID: covidwho-1816038
6.
Ann Intern Med ; 174(9): 1240-1251, 2021 09.
Article in English | MEDLINE | ID: covidwho-1789654

ABSTRACT

BACKGROUND: Several U.S. hospitals had surges in COVID-19 caseload, but their effect on COVID-19 survival rates remains unclear, especially independent of temporal changes in survival. OBJECTIVE: To determine the association between hospitals' severity-weighted COVID-19 caseload and COVID-19 mortality risk and identify effect modifiers of this relationship. DESIGN: Retrospective cohort study. (ClinicalTrials.gov: NCT04688372). SETTING: 558 U.S. hospitals in the Premier Healthcare Database. PARTICIPANTS: Adult COVID-19-coded inpatients admitted from March to August 2020 with discharge dispositions by October 2020. MEASUREMENTS: Each hospital-month was stratified by percentile rank on a surge index (a severity-weighted measure of COVID-19 caseload relative to pre-COVID-19 bed capacity). The effect of surge index on risk-adjusted odds ratio (aOR) of in-hospital mortality or discharge to hospice was calculated using hierarchical modeling; interaction by surge attributes was assessed. RESULTS: Of 144 116 inpatients with COVID-19 at 558 U.S. hospitals, 78 144 (54.2%) were admitted to hospitals in the top surge index decile. Overall, 25 344 (17.6%) died; crude COVID-19 mortality decreased over time across all surge index strata. However, compared with nonsurging (<50th surge index percentile) hospital-months, aORs in the 50th to 75th, 75th to 90th, 90th to 95th, 95th to 99th, and greater than 99th percentiles were 1.11 (95% CI, 1.01 to 1.23), 1.24 (CI, 1.12 to 1.38), 1.42 (CI, 1.27 to 1.60), 1.59 (CI, 1.41 to 1.80), and 2.00 (CI, 1.69 to 2.38), respectively. The surge index was associated with mortality across ward, intensive care unit, and intubated patients. The surge-mortality relationship was stronger in June to August than in March to May (slope difference, 0.10 [CI, 0.033 to 0.16]) despite greater corticosteroid use and more judicious intubation during later and higher-surging months. Nearly 1 in 4 COVID-19 deaths (5868 [CI, 3584 to 8171]; 23.2%) was potentially attributable to hospitals strained by surging caseload. LIMITATION: Residual confounding. CONCLUSION: Despite improvements in COVID-19 survival between March and August 2020, surges in hospital COVID-19 caseload remained detrimental to survival and potentially eroded benefits gained from emerging treatments. Bolstering preventive measures and supporting surging hospitals will save many lives. PRIMARY FUNDING SOURCE: Intramural Research Program of the National Institutes of Health Clinical Center, the National Institute of Allergy and Infectious Diseases, and the National Cancer Institute.


Subject(s)
COVID-19/mortality , Hospitalization/statistics & numerical data , Adrenal Cortex Hormones/therapeutic use , Adult , COVID-19/therapy , Critical Care/statistics & numerical data , Female , Hospital Bed Capacity/statistics & numerical data , Hospital Mortality , Humans , Male , Odds Ratio , Respiration, Artificial , Retrospective Studies , Risk Assessment , Risk Factors , SARS-CoV-2 , Survival Rate , United States/epidemiology
7.
Clin Infect Dis ; 2022 Feb 07.
Article in English | MEDLINE | ID: covidwho-1769233

ABSTRACT

The highly contagious SARS-CoV-2 Omicron variant increases risk for nosocomial transmission despite universal masking, admission testing, and symptom screening. We report large increases in hospital-onset infections and 2 unit-based clusters. The clusters rapidly abated after instituting universal N95 respirators and daily testing. Broader use of these strategies may prevent nosocomial transmissions.

9.
Clin Infect Dis ; 74(6): 1097-1100, 2022 03 23.
Article in English | MEDLINE | ID: covidwho-1705124

ABSTRACT

We assessed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission between patients in shared rooms in an academic hospital between September 2020 and April 2021. In total, 11 290 patients were admitted to shared rooms, of whom 25 tested positive. Among 31 exposed roommates, 12 (39%) tested positive within 14 days. Transmission was associated with polymerase chain reaction (PCR) cycle thresholds ≤21.


Subject(s)
COVID-19 , SARS-CoV-2 , Academic Medical Centers , Hospitalization , Humans , Risk Factors
10.
Clin Infect Dis ; 74(8): 1489-1492, 2022 Apr 28.
Article in English | MEDLINE | ID: covidwho-1704507

ABSTRACT

In a retrospective cohort study, among 131 773 patients with previous coronavirus disease 2019 (COVID-19), reinfection with severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) was suspected in 253 patients (0.2%) at 238 US healthcare facilities between 1 June 2020 and 28 February 2021. Women displayed a higher cumulative reinfection risk. Healthcare burden and illness severity were similar between index and reinfection encounters.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Delivery of Health Care , Female , Humans , Incidence , Reinfection , Retrospective Studies
11.
Clin Infect Dis ; 74(3): 529-531, 2022 02 11.
Article in English | MEDLINE | ID: covidwho-1684549

ABSTRACT

The Centers for Disease Control and Prevention recommends N95 respirators for all providers who see patients with possible or confirmed coronavirus disease 2019 (COVID-19). We suggest that N95 respirators may be just as important for the care of patients without suspected COVID-19 when community incidence rates are high. This is because severe acute respiratory syndrome coronavirus 2 is most contagious before symptom onset. Ironically, by the time patients are sick enough to be admitted to the hospital with COVID-19, they tend to be less contagious. The greatest threat of transmission in healthcare facilities may therefore be patients and healthcare workers with early occult infection. N95 respirators' superior fit and filtration provide superior exposure protection for healthcare providers seeing patients with early undiagnosed infection and superior source control to protect patients from healthcare workers with early undiagnosed infection. The probability of occult infection in patients and healthcare workers is greatest when community incidence rates are high. Universal use of N95 respirators may help decrease nosocomial transmission at such times.


Subject(s)
COVID-19 , Delivery of Health Care , Humans , Masks , N95 Respirators , SARS-CoV-2
12.
Curr Opin Crit Care ; 28(1): 74-82, 2022 02 01.
Article in English | MEDLINE | ID: covidwho-1672366

ABSTRACT

PURPOSE OF REVIEW: We conducted a systematic literature review to summarize the available evidence regarding the incidence, risk factors, and clinical characteristics of ventilator-associated pneumonia (VAP) in patients undergoing mechanical ventilation because of acute respiratory distress syndrome secondary to SARS-CoV-2 infection (C-ARDS). RECENT FINDINGS: Sixteen studies (6484 patients) were identified. Bacterial coinfection was uncommon at baseline (<15%) but a high proportion of patients developed positive bacterial cultures thereafter leading to a VAP diagnosis (range 21-64%, weighted average 50%). Diagnostic criteria varied between studies but most signs of VAP have substantial overlap with the signs of C-ARDS making it difficult to differentiate between bacterial colonization versus superinfection. Most episodes of VAP were associated with Gram-negative bacteria. Occasional cases were also attributed to herpes virus reactivations and pulmonary aspergillosis. Potential factors driving high VAP incidence rates include immunoparalysis, prolonged ventilation, exposure to immunosuppressants, understaffing, lapses in prevention processes, and overdiagnosis. SUMMARY: Covid-19 patients who require mechanical ventilation for ARDS have a high risk (>50%) of developing VAP, most commonly because of Gram-negative bacteria. Further work is needed to elucidate the disease-specific risk factors for VAP, strategies for prevention, and how best to differentiate between bacterial colonization versus superinfection.


Subject(s)
COVID-19 , Pneumonia, Ventilator-Associated , Respiratory Distress Syndrome , Humans , Pneumonia, Ventilator-Associated/epidemiology , Respiration, Artificial , Respiratory Distress Syndrome/epidemiology , Respiratory Distress Syndrome/etiology , SARS-CoV-2
15.
Semin Respir Crit Care Med ; 43(2): 295-303, 2022 04.
Article in English | MEDLINE | ID: covidwho-1634122

ABSTRACT

A fifth or more of hospital-acquired pneumonias may be attributable to respiratory viruses. The SARS-CoV-2 pandemic has clearly demonstrated the potential morbidity and mortality of respiratory viruses and the constant threat of nosocomial transmission and hospital-based clusters. Data from before the pandemic suggest the same can be true of influenza, respiratory syncytial virus, and other respiratory viruses. The pandemic has also helped clarify the primary mechanisms and risk factors for viral transmission. Respiratory viruses are primarily transmitted by respiratory aerosols that are routinely emitted when people exhale, talk, and cough. Labored breathing and coughing increase aerosol generation to a much greater extent than intubation, extubation, positive pressure ventilation, and other so-called aerosol-generating procedures. Transmission risk is proportional to the amount of viral exposure. Most transmissions take place over short distances because respiratory emissions are densest immediately adjacent to the source but then rapidly dilute and diffuse with distance leading to less viral exposure. The primary risk factors for transmission then are high viral loads, proximity, sustained exposure, and poor ventilation as these all increase net viral exposure. Poor ventilation increases the risk of long-distance transmission by allowing aerosol-borne viruses to accumulate over time leading to higher levels of exposure throughout an enclosed space. Surgical and procedural masks reduce viral exposure but do not eradicate it and thus lower but do not eliminate transmission risk. Most hospital-based clusters have been attributed to delayed diagnoses, transmission between roommates, and staff-to-patient infections. Strategies to prevent nosocomial respiratory viral infections include testing all patients upon admission, preventing healthcare providers from working while sick, assuring adequate ventilation, universal masking, and vaccinating both patients and healthcare workers.


Subject(s)
COVID-19 , Pneumonia, Ventilator-Associated , Aerosols , COVID-19/prevention & control , Hospitals , Humans , SARS-CoV-2
16.
Critical Care Medicine ; 50:50-50, 2022.
Article in English | Academic Search Complete | ID: covidwho-1592237

ABSTRACT

B Introduction/Hypothesis: b Clinical practice has evolved from early intubation for COVID-19 patients with acute respiratory distress syndrome (ARDS) to preferential trialing of ventilator-sparing oxygen support. These data support trialing non-invasive oxygen support in most COVID-19 patients with ARDS and proceeding to intubation when clinically necessary. B Conclusions: b After rigorous accounting for time-varying confounding by severity-of-illness, intubation was associated with a similar risk of mortality as ventilator-sparing oxygen support in COVID-19 patients with ARDS. [Extracted from the article] Copyright of Critical Care Medicine is the property of Lippincott Williams & Wilkins and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

19.
Open forum infectious diseases ; 8(Suppl 1):S695-S695, 2021.
Article in English | EuropePMC | ID: covidwho-1565006

ABSTRACT

Background We developed a syndromic algorithm for COVID-19 like illness (CLI) to provide supplementary surveillance data on COVID-19 activity. Methods The CLI algorithm was developed using the Electronic Medical Record Support for Public Health platform (esphealth.org) and data from five clinical practice groups in Massachusetts that collectively care for 25% of the state’s population. Signs and symptoms of CLI were identified using ICD-10 diagnosis codes and measured temperature. The algorithm originally included three categories: Category 1 required codes for coronavirus infection and lower respiratory tract infections (LRTI);Category 2 required an LRTI-related diagnosis and fever;Category 3 required an upper or lower RTI and fever. The three categories mirrored statewide laboratory-confirmed case trends during spring and summer 2020 but did not detect the increase in late fall. We hypothesized this was due to the requirements for fever and LRTI. Therefore, we added three new categories defined by milder symptoms without fever: Category 4 requires LRTI-related diagnoses only;Category 5 requires upper or lower RTI or olfactory/taste disorders;and Category 6 requires at least one sign of CLI not identified by another category. Results The six-category algorithm detected the initial surge in April 2020, the summer lull, and the second surge in late fall (see figure). Category 1 cases were not identified until mid-March, which coincides with the first laboratory-confirmed cases in Massachusetts. Categories 2 and 3, which required fever, were prominent during the initial surge but declined over time. Category 5, the broadest category, declined during February and March 2020, likely capturing the end of the influenza season, and successfully detected the spring surge and fall resurgence. Weekly number of COVID-19 like illnesses by category, February 2, 2020 through May 8, 2021 Conclusion A syndromic definition that included mild upper RTI and olfactory/taste disorders, with or without fever or LRTI, mirrored changes in laboratory-confirmed COVID-19 cases better than definitions that required fever and LRTI. This suggests a shift in medically attended care and/or coding practices during initial vs subsequent surges of COVID-19, and the importance of using a broad definition of CLI for ongoing surveillance. Disclosures Michael Klompas, MD, MPH, UpToDate (Other Financial or Material Support, Chapter Author)

20.
Infect Control Hosp Epidemiol ; : 1-5, 2021 Nov 10.
Article in English | MEDLINE | ID: covidwho-1555621

ABSTRACT

OBJECTIVE: To investigate the effectiveness of a daily attestation system used by employees of a multi-institutional academic medical center, which comprised of symptom-screening, self-referrals to the Occupational Health Services team, and/or a severe acute respiratory coronavirus virus 2 (SARS-CoV-2) test. DESIGN: We conducted a retrospective cohort study of all employee attestations and SARS-CoV-2 tests performed between March and June 2020. SETTING: A large multi-institutional academic medical center, including both inpatient and ambulatory settings. PARTICIPANTS: All employees who worked at the study site. METHODS: Data were combined from the attestation system (COVIDPass), the employee database, and the electronic health records and were analyzed using descriptive statistics including χ2, Wilcoxon, and Kruskal-Wallis tests. We investigated whether an association existed between symptomatic attestations by the employees and the employee testing positive for SARS-CoV-2. RESULTS: After data linkage and cleaning, there were 2,117,298 attestations submitted by 65,422 employees between March and June 2020. Most attestations were asymptomatic (99.9%). The most commonly reported symptoms were sore throat (n = 910), runny nose (n = 637), and cough (n = 570). Among the 2,026 employees who ever attested that they were symptomatic, 905 employees were tested within 14 days of a symptomatic attestation, and 114 (13%) of these tests were positive. The most common symptoms associated with a positive SARS-CoV-2 test were anosmia (23% vs 4%) and fever (46% vs 19%). CONCLUSIONS: Daily symptom attestations among healthcare workers identified a handful of employees with COVID-19. Although the number of positive tests was low, attestations may help keep unwell employees off campus to prevent transmissions.

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