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Hospital-based transmission had a dominant role in Middle East respiratory syndrome coronavirus (MERS-CoV) and severe acute respiratory syndrome coronavirus (SARS-CoV) epidemics1,2, but large-scale studies of its role in the SARS-CoV-2 pandemic are lacking. Such transmission risks spreading the virus to the most vulnerable individuals and can have wider-scale impacts through hospital-community interactions. Using data from acute hospitals in England, we quantify within-hospital transmission, evaluate likely pathways of spread and factors associated with heightened transmission risk, and explore the wider dynamical consequences. We estimate that between June 2020 and March 2021 between 95,000 and 167,000 inpatients acquired SARS-CoV-2 in hospitals (1% to 2% of all hospital admissions in this period). Analysis of time series data provided evidence that patients who themselves acquired SARS-CoV-2 infection in hospital were the main sources of transmission to other patients. Increased transmission to inpatients was associated with hospitals having fewer single rooms and lower heated volume per bed. Moreover, we show that reducing hospital transmission could substantially enhance the efficiency of punctuated lockdown measures in suppressing community transmission. These findings reveal the previously unrecognized scale of hospital transmission, have direct implications for targeting of hospital control measures and highlight the need to design hospitals better equipped to limit the transmission of future high-consequence pathogens.
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COVID-19 , Infecção Hospitalar , Transmissão de Doença Infecciosa , Pacientes Internados , Pandemias , Humanos , Controle de Doenças Transmissíveis , COVID-19/epidemiologia , COVID-19/transmissão , Infecção Hospitalar/epidemiologia , Infecção Hospitalar/prevenção & controle , Infecção Hospitalar/transmissão , Transmissão de Doença Infecciosa/prevenção & controle , Transmissão de Doença Infecciosa/estatística & dados numéricos , Inglaterra/epidemiologia , Hospitais , Pandemias/prevenção & controle , Pandemias/estatística & dados numéricos , Quarentena/estatística & dados numéricos , SARS-CoV-2RESUMO
Hand hygiene is a simple, low-cost intervention that may lead to substantial population-level effects in suppressing acute respiratory infection epidemics. However, quantification of the efficacy of hand hygiene on respiratory infection in the community is lacking. We searched PubMed for randomised controlled trials on the effect of hand hygiene for reducing acute respiratory infections in the community published before 11 March 2021. We performed a meta-regression analysis using a Bayesian mixed-effects model. A total of 105 publications were identified, out of which six studies reported hand hygiene frequencies. Four studies were performed in household settings and two were in schools. The average number of handwashing events per day ranged from one to eight in the control arms, and four to 17 in the intervention arms. We estimated that a single hand hygiene event is associated with a 3% (80% credible interval (-1% to 7%)) decrease in the daily probability of an acute respiratory infection. Three of these six studies were potentially at high risk of bias because the primary outcome depended on self-reporting of upper respiratory tract symptoms. Well-designed trials with an emphasis on monitoring hand hygiene adherence are needed to confirm these findings.
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Epidemias , Higiene das Mãos , Infecções Respiratórias , Teorema de Bayes , Desinfecção das Mãos , Humanos , Infecções Respiratórias/epidemiologia , Infecções Respiratórias/prevenção & controleRESUMO
BACKGROUND: SARS-CoV-2 is known to transmit in hospital settings, but the contribution of infections acquired in hospitals to the epidemic at a national scale is unknown. METHODS: We used comprehensive national English datasets to determine the number of COVID-19 patients with identified hospital-acquired infections (with symptom onset > 7 days after admission and before discharge) in acute English hospitals up to August 2020. As patients may leave the hospital prior to detection of infection or have rapid symptom onset, we combined measures of the length of stay and the incubation period distribution to estimate how many hospital-acquired infections may have been missed. We used simulations to estimate the total number (identified and unidentified) of symptomatic hospital-acquired infections, as well as infections due to onward community transmission from missed hospital-acquired infections, to 31st July 2020. RESULTS: In our dataset of hospitalised COVID-19 patients in acute English hospitals with a recorded symptom onset date (n = 65,028), 7% were classified as hospital-acquired. We estimated that only 30% (range across weeks and 200 simulations: 20-41%) of symptomatic hospital-acquired infections would be identified, with up to 15% (mean, 95% range over 200 simulations: 14.1-15.8%) of cases currently classified as community-acquired COVID-19 potentially linked to hospital transmission. We estimated that 26,600 (25,900 to 27,700) individuals acquired a symptomatic SARS-CoV-2 infection in an acute Trust in England before 31st July 2020, resulting in 15,900 (15,200-16,400) or 20.1% (19.2-20.7%) of all identified hospitalised COVID-19 cases. CONCLUSIONS: Transmission of SARS-CoV-2 to hospitalised patients likely caused approximately a fifth of identified cases of hospitalised COVID-19 in the "first wave" in England, but less than 1% of all infections in England. Using time to symptom onset from admission for inpatients as a detection method likely misses a substantial proportion (> 60%) of hospital-acquired infections.
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COVID-19 , Infecção Hospitalar , COVID-19/epidemiologia , Infecção Hospitalar/epidemiologia , Hospitalização , Hospitais , Humanos , SARS-CoV-2RESUMO
BACKGROUND: Emergence of more transmissible SARS-CoV-2 variants requires more efficient control measures to limit nosocomial transmission and maintain healthcare capacities during pandemic waves. Yet the relative importance of different strategies is unknown. METHODS: We developed an agent-based model and compared the impact of personal protective equipment (PPE), screening of healthcare workers (HCWs), contact tracing of symptomatic HCWs and restricting HCWs from working in multiple units (HCW cohorting) on nosocomial SARS-CoV-2 transmission. The model was fit on hospital data from the first wave in the Netherlands (February until August 2020) and assumed that HCWs used 90% effective PPE in COVID-19 wards and self-isolated at home for 7 days immediately upon symptom onset. Intervention effects on the effective reproduction number (RE), HCW absenteeism and the proportion of infected individuals among tested individuals (positivity rate) were estimated for a more transmissible variant. RESULTS: Introduction of a variant with 56% higher transmissibility increased - all other variables kept constant - RE from 0.4 to 0.65 (+ 63%) and nosocomial transmissions by 303%, mainly because of more transmissions caused by pre-symptomatic patients and HCWs. Compared to baseline, PPE use in all hospital wards (assuming 90% effectiveness) reduced RE by 85% and absenteeism by 57%. Screening HCWs every 3 days with perfect test sensitivity reduced RE by 67%, yielding a maximum test positivity rate of 5%. Screening HCWs every 3 or 7 days assuming time-varying test sensitivities reduced RE by 9% and 3%, respectively. Contact tracing reduced RE by at least 32% and achieved higher test positivity rates than screening interventions. HCW cohorting reduced RE by 5%. Sensitivity analyses show that our findings do not change significantly for 70% PPE effectiveness. For low PPE effectiveness of 50%, PPE use in all wards is less effective than screening every 3 days with perfect sensitivity but still more effective than all other interventions. CONCLUSIONS: In response to the emergence of more transmissible SARS-CoV-2 variants, PPE use in all hospital wards might still be most effective in preventing nosocomial transmission. Regular screening and contact tracing of HCWs are also effective interventions but critically depend on the sensitivity of the diagnostic test used.
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COVID-19 , Infecção Hospitalar , COVID-19/prevenção & controle , COVID-19/transmissão , Infecção Hospitalar/epidemiologia , Infecção Hospitalar/prevenção & controle , Pessoal de Saúde , Humanos , Transmissão de Doença Infecciosa do Paciente para o Profissional/prevenção & controle , Países Baixos/epidemiologia , SARS-CoV-2RESUMO
BACKGROUND: The coronavirus disease (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread to nearly every country in the world since it first emerged in China in December 2019. Many countries have implemented social distancing as a measure to "flatten the curve" of the ongoing epidemics. Evaluation of the impact of government-imposed social distancing and of other measures to control further spread of COVID-19 is urgent, especially because of the large societal and economic impact of the former. The aim of this study was to compare the individual and combined effectiveness of self-imposed prevention measures and of short-term government-imposed social distancing in mitigating, delaying, or preventing a COVID-19 epidemic. METHODS AND FINDINGS: We developed a deterministic compartmental transmission model of SARS-CoV-2 in a population stratified by disease status (susceptible, exposed, infectious with mild or severe disease, diagnosed, and recovered) and disease awareness status (aware and unaware) due to the spread of COVID-19. Self-imposed measures were assumed to be taken by disease-aware individuals and included handwashing, mask-wearing, and social distancing. Government-imposed social distancing reduced the contact rate of individuals irrespective of their disease or awareness status. The model was parameterized using current best estimates of key epidemiological parameters from COVID-19 clinical studies. The model outcomes included the peak number of diagnoses, attack rate, and time until the peak number of diagnoses. For fast awareness spread in the population, self-imposed measures can significantly reduce the attack rate and diminish and postpone the peak number of diagnoses. We estimate that a large epidemic can be prevented if the efficacy of these measures exceeds 50%. For slow awareness spread, self-imposed measures reduce the peak number of diagnoses and attack rate but do not affect the timing of the peak. Early implementation of short-term government-imposed social distancing alone is estimated to delay (by at most 7 months for a 3-month intervention) but not to reduce the peak. The delay can be even longer and the height of the peak can be additionally reduced if this intervention is combined with self-imposed measures that are continued after government-imposed social distancing has been lifted. Our analyses are limited in that they do not account for stochasticity, demographics, heterogeneities in contact patterns or mixing, spatial effects, imperfect isolation of individuals with severe disease, and reinfection with COVID-19. CONCLUSIONS: Our results suggest that information dissemination about COVID-19, which causes individual adoption of handwashing, mask-wearing, and social distancing, can be an effective strategy to mitigate and delay the epidemic. Early initiated short-term government-imposed social distancing can buy time for healthcare systems to prepare for an increasing COVID-19 burden. We stress the importance of disease awareness in controlling the ongoing epidemic and recommend that, in addition to policies on social distancing, governments and public health institutions mobilize people to adopt self-imposed measures with proven efficacy in order to successfully tackle COVID-19.
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Controle de Doenças Transmissíveis/métodos , Infecções por Coronavirus/prevenção & controle , Epidemias/prevenção & controle , Desinfecção das Mãos , Máscaras , Pandemias/prevenção & controle , Pneumonia Viral/prevenção & controle , Política Pública , Quarentena , Conscientização , Betacoronavirus , COVID-19 , Participação da Comunidade , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/transmissão , Governo , Educação em Saúde , Humanos , Modelos Estatísticos , Pneumonia Viral/epidemiologia , Pneumonia Viral/transmissão , SARS-CoV-2 , Fatores de TempoRESUMO
Pseudomonas aeruginosa (P. aeruginosa) is an important cause of healthcare-associated infections, particularly in immunocompromised patients. Understanding how this multi-drug resistant pathogen is transmitted within intensive care units (ICUs) is crucial for devising and evaluating successful control strategies. While it is known that moist environments serve as natural reservoirs for P. aeruginosa, there is little quantitative evidence regarding the contribution of environmental contamination to its transmission within ICUs. Previous studies on other nosocomial pathogens rely on deploying specific values for environmental parameters derived from costly and laborious genotyping. Using solely longitudinal surveillance data, we estimated the relative importance of P. aeruginosa transmission routes by exploiting the fact that different routes cause different pattern of fluctuations in the prevalence. We developed a mathematical model including background transmission, cross-transmission and environmental contamination. Patients contribute to a pool of pathogens by shedding bacteria to the environment. Natural decay and cleaning of the environment lead to a reduction of that pool. By assigning the bacterial load shed during an ICU stay to cross-transmission, we were able to disentangle environmental contamination during and after a patient's stay. Based on a data-augmented Markov Chain Monte Carlo method the relative importance of the considered acquisition routes is determined for two ICUs of the University hospital in Besançon (France). We used information about the admission and discharge days, screening days and screening results of the ICU patients. Both background and cross-transmission play a significant role in the transmission process in both ICUs. In contrast, only about 1% of the total transmissions were due to environmental contamination after discharge. Based on longitudinal surveillance data, we conclude that cleaning improvement of the environment after discharge might have only a limited impact regarding the prevention of P.A. infections in the two considered ICUs of the University hospital in Besançon. Our model was developed for P. aeruginosa but can be easily applied to other pathogens as well.
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Infecção Hospitalar/transmissão , Unidades de Terapia Intensiva , Infecções por Pseudomonas/transmissão , Pseudomonas aeruginosa , Biologia Computacional , Infecção Hospitalar/epidemiologia , Infecção Hospitalar/prevenção & controle , Reservatórios de Doenças/microbiologia , Farmacorresistência Bacteriana Múltipla , Microbiologia Ambiental , França/epidemiologia , Humanos , Estudos Longitudinais , Cadeias de Markov , Modelos Biológicos , Método de Monte Carlo , Alta do Paciente , Prevalência , Infecções por Pseudomonas/epidemiologia , Infecções por Pseudomonas/prevenção & controle , Pseudomonas aeruginosa/efeitos dos fármacos , Pseudomonas aeruginosa/patogenicidadeRESUMO
BACKGROUND: Antimicrobial resistance poses a major threat to public health. There are few comprehensive nationwide studies that quantify long-term trends in infection incidence and antimicrobial resistance for multiple pathogens. We aimed to analyse trends in inpatient infection incidence and antimicrobial resistance for nine pathogens over the past 15 years across the USA. METHODS: In this US nationwide retrospective cohort study, we analysed clinical microbiology data from electronic health records from all patients admitted to all 138 Veterans Affairs (VA) Medical Centers with acute care wards across the USA from Feb 1, 2007, to March 31, 2022. We quantified inpatient antibiotic use as days of therapy (DOT) per 1000 patient-days and antimicrobial resistance by resistance proportion (proportion of incident isolates identified as resistant) and phenotypic incidence (incidence of infections per 1000 admissions classified as resistant, susceptible, or missing). To analyse trends before the COVID-19 pandemic and during the COVID-19 pandemic, we used generalised estimating equation models and reported average annual percentage changes (AAPC). FINDINGS: We collected 991 527 30-day incident isolates from 507 760 patients in 138 VA Medical Centers and 50 states in the USA. Between Feb 1, 2007, and Dec 31, 2019, infection incidence and antimicrobial resistance declined for many pathogens and pathogen-drug combinations. The proportion of methicillin resistance in Staphylococcus aureus decreased from 57·7% (11 876 of 20 584 incident isolates) to 44·6% (5916 of 13 257) over these 13 years (AAPC -1·8%; 95% CI -2·4 to -1·2; p<0·0001), and vancomycin-resistant Enterococcus faecium infections decreased from 77·8% (2555 of 3285) to 65·1% (893 of 1371; AAPC -1·2%; 95% CI -2·5 to 0·0; p=0·052). Fluoroquinolone resistance declined in both proportion and incidence for most pathogens. These trends correlated with substantial reductions in fluoroquinolone use, from 125 DOT per 1000 patient-days to 20 DOT per 1000 patient-days. Third generation cephalosporin resistance increased steeply in Escherichia coli infections from 6·7% (942 of 14 042) in 2007 to 15·3% (2153 of 14 053) in 2019 (AAPC 8·5%; 95% CI 6·2 to 10·7; p<0·0001). Carbapenem resistance proportion increased in Enterobacter cloacae infections from 1·1% (30 of 2852) in 2007 to 7·3% (212 of 2919) in 2019 (AAPC 19·8%; 95% CI 13·7 to 26·2; p<0·0001), but remained low for Klebsiella pneumoniae and E coli. During the COVID-19 pandemic between Jan 1, 2020, and March 31, 2022, several pathogen-drug combinations increased in both incidence and resistance for hospital-associated infections. For some pathogen-drug combinations, trends in incidence of resistant and susceptible infections were divergent, whereas for other combinations, these trends were in the same direction. INTERPRETATION: Significant reductions in methicillin resistance in S aureus, vancomycin-resistant E faecium, and fluoroquinolone resistance across multiple pathogens suggest that control efforts have had an effect on resistance. The rise in extended-spectrum ß-lactamases-producing Enterobacterales and recent surge in hospital-associated infections emphasise the need for ongoing surveillance and interventions. Our study highlights how coupling the analysis of phenotypic incidence with resistance proportion can enhance interpretation of antimicrobial resistance data. FUNDING: US Centers for Disease Control and Prevention.
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Hand hygiene is among the most fundamental and widely used behavioural measures to reduce the person-to-person spread of human pathogens and its effectiveness as a community intervention is supported by evidence from randomized trials. However, a theoretical understanding of the relationship between hand hygiene frequency and change in risk of infection is lacking. Using a simple model-based framework for understanding the determinants of hand hygiene effectiveness in preventing viral respiratory tract infections, we show that a crucial, but overlooked, determinant of the relationship between hand hygiene frequency and risk of infection via indirect transmission is persistence of viable virus on hands. If persistence is short, as has been reported for influenza, hand-washing needs to be performed very frequently or immediately after hand contamination to substantially reduce the probability of infection. When viable virus survival is longer (e.g. in the presence of mucus or for some enveloped viruses) less frequent hand washing can substantially reduce the infection probability. Immediate hand washing after contamination is consistently more effective than at fixed-time intervals. Our study highlights that recommendations on hand hygiene should be tailored to persistence of viable virus on hands and that more detailed empirical investigations are needed to help optimize this key intervention.
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BACKGROUND: Increasing vaccination coverage against SARS-CoV-2 enabled relaxation of lockdowns in many countries in Europe. As the vaccination rollouts progressed, the public health authorities were seeking recommendations on the continuation of physical distancing measures during ongoing vaccination rollouts. Compliance with these measures was declining while more transmissible virus variants have emerged. METHODS: We used a SARS-CoV-2 transmission model to investigate the feedback between compliance, infection incidence, and vaccination coverage. We quantified our findings in terms of cumulative number of new hospitalisations three and six months after the start of vaccination. RESULTS: Our results suggest that the combination of fast waning compliance in non-vaccinated individuals, low compliance in vaccinated individuals, low vaccine efficacy against infection and more transmissible virus variants may result in a higher cumulative number of new hospitalisations than in a situation without vaccination. These adverse effects can be alleviated by deploying behavioural interventions that should preferably target both vaccinated and non-vaccinated individuals. The choice of the most appropriate intervention depends on vaccination rate and vaccine efficacy against infection. CONCLUSIONS: Supplementary behavioural interventions aiming to boost compliance to physical distancing measures can improve the outcome of vaccination programmes, until vaccination coverage is sufficiently high. For optimal results, these interventions should be selected based on the vaccine efficacy against infection and expected vaccination rate. While we considered the dynamics of SARS-CoV-2, the qualitative effects of the interplay between infectious disease spread and behavior on the outcomes of a vaccination programme can be used as guidance in a future similar pandemic.
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Many infection prevention and control (IPC) interventions have been adopted by hospitals to limit nosocomial transmission of SARS-CoV-2. The aim of this systematic review is to identify evidence on the effectiveness of these interventions. We conducted a literature search of five databases (OVID MEDLINE, Embase, CENTRAL, COVID-19 Portfolio (pre-print), Web of Science). SWIFT ActiveScreener software was used to screen English titles and abstracts published between 1st January 2020 and 6th April 2021. Intervention studies, defined by Cochrane Effective Practice and Organisation of Care, that evaluated IPC interventions with an outcome of SARS-CoV-2 infection in either patients or healthcare workers were included. Personal protective equipment (PPE) was excluded as this intervention had been previously reviewed. Risks of bias were assessed using the Cochrane tool for randomised trials (RoB2) and non-randomized studies of interventions (ROBINS-I). From 23,156 screened articles, we identified seven articles that met the inclusion criteria, all of which evaluated interventions to prevent infections in healthcare workers and the majority of which were focused on effectiveness of prophylaxes. Due to heterogeneity in interventions, we did not conduct a meta-analysis. All agents used for prophylaxes have little to no evidence of effectiveness against SARS-CoV-2 infections. We did not find any studies evaluating the effectiveness of interventions including but not limited to screening, isolation and improved ventilation. There is limited evidence from interventional studies, excluding PPE, evaluating IPC measures for SARS-CoV-2. This review calls for urgent action to implement such studies to inform policies to protect our most vulnerable populations and healthcare workers.
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BACKGROUND: Hospital outbreaks of multidrug resistant Pseudomonas aeruginosa are often caused by Pseudomonas aeruginosa clones which produce metallo-ß-lactamases, such as Verona Integron-encoded Metallo-ß-lactamase (VIM). Although different sources have been identified, the exact transmission routes often remain unknown. However, quantifying the role of different transmission routes of VIM-PA is important for tailoring infection prevention and control measures. The aim of this study is to quantify the relative importance of different transmission routes by applying a mathematical transmission model using admission and discharge dates as well as surveillance culture data of patients. METHODS: We analyzed VIM-PA surveillance data collected between 2010 and 2018 of two intensive-care unit (ICU) wards for adult patients of the Erasmus University Medical Center Rotterdam using a mathematical transmission model. We distinguished two transmission routes: direct cross-transmission and a persistent environmental route. Based on admission, discharge dates, and surveillance cultures, we estimated the proportion of transmissions assigned to each of the routes. RESULTS: Our study shows that only 13.7% (95% CI 1.4%, 29%) of the transmissions that occurred in these two ICU wards were likely caused by cross-transmission, leaving the vast majority of transmissions (86.3%, 95% CI 71%, 98.6%) due to persistent environmental contamination. CONCLUSIONS: Our results emphasize that persistent contamination of the environment may be an important driver of nosocomial transmissions of VIM-PA in ICUs. To minimize the transmission risk from the environment, potential reservoirs should be regularly and thoroughly cleaned and disinfected, or redesigned.