<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT04405934</url>
  </required_header>
  <id_info>
    <org_study_id>CTU/2020/353</org_study_id>
    <secondary_id>283014</secondary_id>
    <secondary_id>20/EE/0118</secondary_id>
    <nct_id>NCT04405934</nct_id>
  </id_info>
  <brief_title>COG-UK Project Hospital-Onset COVID-19 Infections Study</brief_title>
  <acronym>COG-UK HOCI</acronym>
  <official_title>A Phase III Prospective, Interventional, Cohort, Superiority Study to Evaluate the Benefit of Rapid COVID-19 Genomic Sequencing (the COVID-19 GENOMICS UK Project) on Infection Control in Preventing the Spread of the Virus in United Kingdom NHS Hospitals</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University College, London</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Public Health England</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>University College, London</source>
  <oversight_info>
    <has_dmc>Yes</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      Hospitals are recognised to be a major risk for the spread of infections despite the&#xD;
      availability of protective measures. Under normal circumstances, staff may acquire and&#xD;
      transmit infections, but the health impact of within hospital infection is greatest in&#xD;
      vulnerable patients. For the novel coronavirus that causes COVID-19, like recent outbreaks&#xD;
      such as the SARS and Ebola virus, the risk of within hospital spread of infection presents an&#xD;
      additional, significant health risk to healthcare workers.&#xD;
&#xD;
      Infection Prevention and Control (IPC) teams within hospitals engage in practices that&#xD;
      minimise the number of infections acquired within hospital. This includes surveillance of&#xD;
      infection spread, and proactively leading on training to clinical and other hospital teams.&#xD;
&#xD;
      There is now good evidence that genome sequencing of epidemic viruses such as that which&#xD;
      causes COVID-19, together with standard IPC, more effectively reduces within hospital&#xD;
      infection rates and may help identify the routes of transmission, than just existing IPC&#xD;
      practice. It is proposed to evaluate the benefit of genome sequencing in this context, and&#xD;
      whether rapid (24-48h) turnaround on the data to IPC teams has an impact on that level of&#xD;
      benefit.&#xD;
&#xD;
      The study team will ask participating NHS hospitals to collect IPC information as per usual&#xD;
      practice for a short time to establish data for comparison. Where patients are confirmed to&#xD;
      have a COVID-19 infection thought to have been transmitted within hospital, their samples&#xD;
      will be sequenced with data fed back to hospital teams during the intervention phase. A final&#xD;
      phase without the intervention may take place for additional information on standard IPC&#xD;
      practice when the COVID-19 outbreak is at a low level nationwide.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Hospitals are recognised to be a major risk for the spread of infections despite the&#xD;
      availability of protective measures. Under normal circumstances, staff may acquire and&#xD;
      transmit infections, but the health impact of nosocomial infection is greatest in vulnerable&#xD;
      patients. For COVID-19, like SARS-CoV, MERS-CoV and Ebola virus, the risk of nosocomial&#xD;
      spread of infection presents an additional and significant health risk to healthcare workers&#xD;
      (HCW). During epidemics, normal infection prevention and control (IPC) practice is further&#xD;
      complicated by the difficulties of distinguishing community- and hospital-acquired&#xD;
      infections. This can lead to erroneous identification of nosocomial transmission, involving&#xD;
      unnecessary IPC efforts, while true nosocomial transmissions are missed thereby putting&#xD;
      patients and HCW at increased risk.&#xD;
&#xD;
      There is now good evidence that genome sequencing of epidemic viruses, together with standard&#xD;
      IPC, better excludes nosocomial transmissions and, depending on the virus, better identifies&#xD;
      routes of transmission, than IPC alone1-3. To date, all studies have been retrospective.&#xD;
      However, the development of rapid nanopore sequencing methods enables identification of&#xD;
      potentially linked or unlinked viruses within 24-48 hours: this timescale is short enough to&#xD;
      inform clinical IPC decisions in near-real-time. Although COVID-19 has a low mutation rate&#xD;
      estimated at around 2.5 changes per genome per month, it is generally agreed that sufficient&#xD;
      viral diversity now exists to identify where patient and staff infections that are apparently&#xD;
      clustered in time and space, are in fact due to different COVID-19 genotypes4. Such&#xD;
      information would rapidly exclude nosocomial transmission as the cause of the cluster, reduce&#xD;
      the need for IPC intervention and provide reassurance to healthcare workers that IPC measures&#xD;
      including personal protective equipment (PPE), had not been breached. However, confirmation&#xD;
      of COVID-19 transmission to patients and healthcare workers may be more difficult with a&#xD;
      single observed mutation between two genomes feasibly representing anything between one and&#xD;
      ten transmissions. Identical genomes will not necessarily provide evidence of a link between&#xD;
      two cases. Nonetheless by placing genotypes detected within the framework of all the&#xD;
      genotypes detected within the hospital setting, the surrounding community and COG-UK as a&#xD;
      whole, it may be possible to postulate nosocomial transmission where comparatively uncommon&#xD;
      genotypes are apparently linked or cluster in time and space.&#xD;
&#xD;
      The COG-UK initiative, which aims to sequence as many COVID-19 viruses as possible across the&#xD;
      UK thus provides an important and unique opportunity to test whether viral sequence data&#xD;
      produced in near-real-time, in addition to providing valuable information for public health&#xD;
      planning, could also reduce uncertainties around nosocomial transmission events, better&#xD;
      target IPC effort, improve hospital functioning and reduce the role of hospitals as a source&#xD;
      of infection to the community.&#xD;
&#xD;
      To address this,the investigators propose an adjunctive study, COG-UK HOCI. COG-UK HOCI will&#xD;
      take advantage of the COG-UK design, with its mixed model of smaller sequencing hubs located&#xD;
      close to hospitals and a large centralised hub sequencing most viruses, to identify not only&#xD;
      whether rapid viral sequencing is useful for patient management but how time-critical this&#xD;
      might be ; turnaround times for sequence data from the central hub are likely to be longer&#xD;
      (5-7 days) than those from local sequencing hubs (&lt;48 hours).&#xD;
&#xD;
      COG-UK HOCI, by defining and reporting COVID-19 genotype frequencies within its participating&#xD;
      hospitals, as compared to those in the wider community, will also have the potential to&#xD;
      overcome some of the inherent barriers to identifying the likely sources of HOCI. The data&#xD;
      generated will provide as accurate as possible a picture, given the constraints of viral&#xD;
      genetic diversity, of numbers of COVID-19 infections being acquired by nosocomial&#xD;
      transmission and where these transmissions are occurring. While COG-UK will provide data on&#xD;
      the utility of viral genomics for national public health planning, COG-UK HOCI will quantify&#xD;
      the utility of the same data for local management of nosocomial infection, whether observed&#xD;
      benefits are time dependent and deliver the best estimates of how viral sequence data can be&#xD;
      used to quantify HOCI.&#xD;
&#xD;
      The outputs from COG-UK HOCI will further inform decisions about the likely future use of&#xD;
      viral genome sequencing for the management of epidemics and pandemics and how it might best&#xD;
      be organised, centralised or diversified, to deliver maximal impact.&#xD;
&#xD;
      The overarching aim of this study is to determine the utility of whole-genome sequencing to&#xD;
      provide additional insight into hospital-onset COVID-19 infections (HOCI) which, in turn, can&#xD;
      optimise IPC measures. In addition, the project aims to provide early data to help quantify&#xD;
      HOCI events and where these are occurring. These will contribute to local trust level&#xD;
      planning and to understanding of the role of HOCIs in contributing to COVID-19 outcomes and&#xD;
      spread.&#xD;
&#xD;
      Specifically, the study will determine the role of real-time availability of COVID-19&#xD;
      sequence data:&#xD;
&#xD;
        -  In conjunction with routine IPC data, to identify and characterise HOCI&#xD;
&#xD;
        -  To identify and characterise HOCI not previously identified by routine IPC data&#xD;
&#xD;
        -  To generate estimated numbers of HOCI and where these are occurring&#xD;
&#xD;
        -  To identify linked HOCI and hospital outbreaks&#xD;
&#xD;
        -  To identify ways to reduce the incidence of HOCI&#xD;
&#xD;
        -  In optimising IPC actions, e.g. by reducing the need for extra cleaning, ward closures&#xD;
           etc where a hospital outbreaks are excluded&#xD;
&#xD;
        -  In changing workload, e.g. by reducing the need for extra cleaning, ward closures etc&#xD;
           where a hospital outbreaks are excluded Augmenting these approaches, the investigators&#xD;
           will measure whether the above are influenced by the time to sequence data result.&#xD;
&#xD;
      COG-UK HOCI is a phase III prospective, interventional, cohort, superiority study.&#xD;
&#xD;
      Allocation to either rapid local sequencing (c.24-48h) or lack of rapid local sequencing&#xD;
      (i.e. via Wellcome Sanger Institute at &gt;96h) will be dependent on the time of the study (see&#xD;
      timelines).&#xD;
&#xD;
      Proposed study duration: 12 months; comprising 6 months of set-up, baseline data collection,&#xD;
      interventional data collection) and up to 6 months of data cleaning, data analysis and&#xD;
      reporting.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">October 15, 2020</start_date>
  <completion_date type="Actual">October 8, 2021</completion_date>
  <primary_completion_date type="Actual">April 26, 2021</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>N/A</allocation>
    <intervention_model>Sequential Assignment</intervention_model>
    <intervention_model_description>Superiority model:&#xD;
Baseline/control phase 1 Sample collection and genomic sequencing from Covid-19 positive participants suspected of acquiring infection in hospital (suspected nosocomial Covid-19 infection where tested positive &gt;48 hours after hospital admission) where sequencing reports not interpreted/actioned by Infection Prevention Control (IPC) site teams&#xD;
Site intervention phase Sample collection and genomic sequencing from Covid-19 positive participants suspected of acquiring infection in hospital where sequencing reports generated both rapid or standard and received by site IPC teams for interpretation and action&#xD;
Control phase 2 (prospective) Sample collection and genomic sequencing from Covid-19 positive participants suspected of acquiring infection in hospital where sequencing reports not interpreted/actioned by IPC site teams - where deemed ethical and approved by oversight committees i.e. DMEC.</intervention_model_description>
    <primary_purpose>Health Services Research</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Incidence rates of IPC-defined hospital-onset COVID-19 infection (HOCIs)</measure>
    <time_frame>6 months</time_frame>
    <description>Incidence rate of IPC-defined HOCIs, measured as incidence rate of recorded cases per week per 100 inpatients, during each phase of the study based on case report forms.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Change in incidence rates of IPC-defined HOCIs with rapid vs standard sequencing</measure>
    <time_frame>6 months</time_frame>
    <description>Identification of nosocomial transmission using sequencing data in potential HOCIs in whom this was not identified by pre-sequencing IPC evaluation, measured using pre- and post-sequencing case report forms for each enrolled patient during study phases in which the sequence reporting tool is in use.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Incidence rates of IPC-defined hospital outbreaks</measure>
    <time_frame>6 months</time_frame>
    <description>Incidence rate of IPC-defined hospital outbreaks, defined as cases of hospital transmission linked by location and with intervals between diagnoses of no greater than 2 weeks (relevant data extracted from case report forms), measured as incidence rate of outbreak events per week per 100 inpatients during each phase of the study.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Incidence rates of IPC+sequencing-defined hospital outbreaks</measure>
    <time_frame>6 months</time_frame>
    <description>Incidence rate of IPC+sequencing-defined hospital outbreaks, defined by retrospective review of all available sequencing and epidemiological data for identification of transmission clusters and measured as outbreak events per week per 100 inpatients during each phase of the study.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Changes to IPC actions following viral sequence reports</measure>
    <time_frame>6 months</time_frame>
    <description>Changes to IPC actions implemented following receipt of viral sequence report, measured using pre- and post-sequencing case report forms for each enrolled patient during study phases in which the sequence reporting tool is in use.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Recommended changes to IPC actions following viral sequence report - not implemented</measure>
    <time_frame>6 months</time_frame>
    <description>Changes to IPC actions that would ideally have been implemented (given unlimited resources) following receipt of viral sequence report, measured using pre- and post-sequencing case report forms for each enrolled patient during study phases in which the sequence reporting tool is in use.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Health economic benefit to IPC of standard vs rapid sequencing reports</measure>
    <time_frame>6 months</time_frame>
    <description>Health economic benefit of standard and rapid sequencing reports to IPC measured using bespoke health economic case report data comparison between baseline, standard and rapid sequencing phases.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Impact of both standard and rapid sequencing reports on number of HCW days off work</measure>
    <time_frame>6 months</time_frame>
    <description>Number of HCW days off work measured from sampling these data points on case report forms at all study phases.</description>
  </secondary_outcome>
  <number_of_arms>1</number_of_arms>
  <enrollment type="Actual">2170</enrollment>
  <condition>Covid-19</condition>
  <condition>Nosocomial Infection</condition>
  <condition>Coronavirus</condition>
  <condition>Coronavirus Infection</condition>
  <condition>SARS-CoV 2</condition>
  <arm_group>
    <arm_group_label>Genomic-sequence informed IPC measures</arm_group_label>
    <arm_group_type>Other</arm_group_type>
    <description>Cohort follow baseline (no report receipt), then rapid vs standard sequencing report receipt phase, then return to baseline phase (no report receipt)</description>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>Use of virus (Covid-19) genome sequence report to inform infection prevention control procedures</intervention_name>
    <description>Rapid or standard (time to return to sites) receipt of virus (Covid-19) genomic sequencing reports</description>
    <arm_group_label>Genomic-sequence informed IPC measures</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Participants must have confirmed COVID-19 infection and either:&#xD;
&#xD;
               1. be a potential hospital-onset COVID-19 infection (HOCI); or&#xD;
&#xD;
               2. potential workplace infection from COV-SARS-2 for site-based healthcare workers.&#xD;
&#xD;
          -  Participants must have provided nasal swab/pharyngeal swab / combined nasal and&#xD;
             pharyngeal swab / nasopharyngeal aspirate or broncho alveolar lavage sample for&#xD;
             evaluation in the COG-UK project.&#xD;
&#xD;
          -  Participants may be of any age to be included in study For clarity, in the above&#xD;
             criterion a potential HOCI is an admitted patient at site with first confirmed test&#xD;
             for COVID-19 &gt;48 hours after admission, where they were not suspected to have COVID-19&#xD;
             at time of admission.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
        - There are no exclusion criteria for COG-UK HOCI&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>N/A</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Judith Breuer, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University College, London</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>University College London Hospitals NHS Foundation Trust</name>
      <address>
        <city>London</city>
        <country>United Kingdom</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United Kingdom</country>
  </location_countries>
  <verification_date>February 2022</verification_date>
  <study_first_submitted>May 7, 2020</study_first_submitted>
  <study_first_submitted_qc>May 26, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">May 28, 2020</study_first_posted>
  <last_update_submitted>February 16, 2022</last_update_submitted>
  <last_update_submitted_qc>February 16, 2022</last_update_submitted_qc>
  <last_update_posted type="Actual">March 2, 2022</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <keyword>Nosocomial Covid-19</keyword>
  <keyword>Covid-19</keyword>
  <keyword>Coronavirus</keyword>
  <keyword>Infection Prevention and Control</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Infections</mesh_term>
    <mesh_term>Communicable Diseases</mesh_term>
    <mesh_term>COVID-19</mesh_term>
    <mesh_term>Coronavirus Infections</mesh_term>
    <mesh_term>Cross Infection</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>Yes</sharing_ipd>
    <ipd_description>The fully anonymised datasets analysed during the study will be stored on a publicly available repository. The COG-UK HOCI study to be shared on the UCL Data Repository data-sharing platform so that the data may be reused by other researchers. The protocol will also be shared.</ipd_description>
    <ipd_info_type>Study Protocol</ipd_info_type>
    <ipd_time_frame>This will be done with 6 months of public reporting of results, with data available for 5 years.</ipd_time_frame>
    <ipd_access_criteria>Fully open access</ipd_access_criteria>
  </patient_data>
  <pending_results>
    <submitted>September 5, 2022</submitted>
    <returned>August 7, 2023</returned>
  </pending_results>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT04405934
org study id: CTU/2020/353
secondary id: 283014
secondary id: 20/EE/0118
nct id: NCT04405934
lead sponsor: 
collaborator: 
has dmc: Yes
is fda regulated drug: No
is fda regulated device: No
Hospitals are recognised to be a major risk for the spread of infections despite the
      availability of protective measures. Under normal circumstances, staff may acquire and
      transmit infections, but the health impact of within hospital infection is greatest in
      vulnerable patients. For the novel coronavirus that causes COVID-19, like recent outbreaks
      such as the SARS and Ebola virus, the risk of within hospital spread of infection presents an
      additional, significant health risk to healthcare workers.

      Infection Prevention and Control (IPC) teams within hospitals engage in practices that
      minimise the number of infections acquired within hospital. This includes surveillance of
      infection spread, and proactively leading on training to clinical and other hospital teams.

      There is now good evidence that genome sequencing of epidemic viruses such as that which
      causes COVID-19, together with standard IPC, more effectively reduces within hospital
      infection rates and may help identify the routes of transmission, than just existing IPC
      practice. It is proposed to evaluate the benefit of genome sequencing in this context, and
      whether rapid (24-48h) turnaround on the data to IPC teams has an impact on that level of
      benefit.

      The study team will ask participating NHS hospitals to collect IPC information as per usual
      practice for a short time to establish data for comparison. Where patients are confirmed to
      have a COVID-19 infection thought to have been transmitted within hospital, their samples
      will be sequenced with data fed back to hospital teams during the intervention phase. A final
      phase without the intervention may take place for additional information on standard IPC
      practice when the COVID-19 outbreak is at a low level nationwide.
Hospitals are recognised to be a major risk for the spread of infections despite the
      availability of protective measures. Under normal circumstances, staff may acquire and
      transmit infections, but the health impact of nosocomial infection is greatest in vulnerable
      patients. For COVID-19, like SARS-CoV, MERS-CoV and Ebola virus, the risk of nosocomial
      spread of infection presents an additional and significant health risk to healthcare workers
      (HCW). During epidemics, normal infection prevention and control (IPC) practice is further
      complicated by the difficulties of distinguishing community- and hospital-acquired
      infections. This can lead to erroneous identification of nosocomial transmission, involving
      unnecessary IPC efforts, while true nosocomial transmissions are missed thereby putting
      patients and HCW at increased risk.

      There is now good evidence that genome sequencing of epidemic viruses, together with standard
      IPC, better excludes nosocomial transmissions and, depending on the virus, better identifies
      routes of transmission, than IPC alone1-3. To date, all studies have been retrospective.
      However, the development of rapid nanopore sequencing methods enables identification of
      potentially linked or unlinked viruses within 24-48 hours: this timescale is short enough to
      inform clinical IPC decisions in near-real-time. Although COVID-19 has a low mutation rate
      estimated at around 2.5 changes per genome per month, it is generally agreed that sufficient
      viral diversity now exists to identify where patient and staff infections that are apparently
      clustered in time and space, are in fact due to different COVID-19 genotypes4. Such
      information would rapidly exclude nosocomial transmission as the cause of the cluster, reduce
      the need for IPC intervention and provide reassurance to healthcare workers that IPC measures
      including personal protective equipment (PPE), had not been breached. However, confirmation
      of COVID-19 transmission to patients and healthcare workers may be more difficult with a
      single observed mutation between two genomes feasibly representing anything between one and
      ten transmissions. Identical genomes will not necessarily provide evidence of a link between
      two cases. Nonetheless by placing genotypes detected within the framework of all the
      genotypes detected within the hospital setting, the surrounding community and COG-UK as a
      whole, it may be possible to postulate nosocomial transmission where comparatively uncommon
      genotypes are apparently linked or cluster in time and space.

      The COG-UK initiative, which aims to sequence as many COVID-19 viruses as possible across the
      UK thus provides an important and unique opportunity to test whether viral sequence data
      produced in near-real-time, in addition to providing valuable information for public health
      planning, could also reduce uncertainties around nosocomial transmission events, better
      target IPC effort, improve hospital functioning and reduce the role of hospitals as a source
      of infection to the community.

      To address this,the investigators propose an adjunctive study, COG-UK HOCI. COG-UK HOCI will
      take advantage of the COG-UK design, with its mixed model of smaller sequencing hubs located
      close to hospitals and a large centralised hub sequencing most viruses, to identify not only
      whether rapid viral sequencing is useful for patient management but how time-critical this
      might be ; turnaround times for sequence data from the central hub are likely to be longer
      (5-7 days) than those from local sequencing hubs (<48 hours).

      COG-UK HOCI, by defining and reporting COVID-19 genotype frequencies within its participating
      hospitals, as compared to those in the wider community, will also have the potential to
      overcome some of the inherent barriers to identifying the likely sources of HOCI. The data
      generated will provide as accurate as possible a picture, given the constraints of viral
      genetic diversity, of numbers of COVID-19 infections being acquired by nosocomial
      transmission and where these transmissions are occurring. While COG-UK will provide data on
      the utility of viral genomics for national public health planning, COG-UK HOCI will quantify
      the utility of the same data for local management of nosocomial infection, whether observed
      benefits are time dependent and deliver the best estimates of how viral sequence data can be
      used to quantify HOCI.

      The outputs from COG-UK HOCI will further inform decisions about the likely future use of
      viral genome sequencing for the management of epidemics and pandemics and how it might best
      be organised, centralised or diversified, to deliver maximal impact.

      The overarching aim of this study is to determine the utility of whole-genome sequencing to
      provide additional insight into hospital-onset COVID-19 infections (HOCI) which, in turn, can
      optimise IPC measures. In addition, the project aims to provide early data to help quantify
      HOCI events and where these are occurring. These will contribute to local trust level
      planning and to understanding of the role of HOCIs in contributing to COVID-19 outcomes and
      spread.

      Specifically, the study will determine the role of real-time availability of COVID-19
      sequence data:

        -  In conjunction with routine IPC data, to identify and characterise HOCI

        -  To identify and characterise HOCI not previously identified by routine IPC data

        -  To generate estimated numbers of HOCI and where these are occurring

        -  To identify linked HOCI and hospital outbreaks

        -  To identify ways to reduce the incidence of HOCI

        -  In optimising IPC actions, e.g. by reducing the need for extra cleaning, ward closures
           etc where a hospital outbreaks are excluded

        -  In changing workload, e.g. by reducing the need for extra cleaning, ward closures etc
           where a hospital outbreaks are excluded Augmenting these approaches, the investigators
           will measure whether the above are influenced by the time to sequence data result.

      COG-UK HOCI is a phase III prospective, interventional, cohort, superiority study.

      Allocation to either rapid local sequencing (c.24-48h) or lack of rapid local sequencing
      (i.e. via Wellcome Sanger Institute at >96h) will be dependent on the time of the study (see
      timelines).

      Proposed study duration: 12 months; comprising 6 months of set-up, baseline data collection,
      interventional data collection) and up to 6 months of data cleaning, data analysis and
      reporting.
allocation: N/A
intervention model: Sequential Assignment
intervention model description: Superiority model:
Baseline/control phase 1 Sample collection and genomic sequencing from Covid-19 positive participants suspected of acquiring infection in hospital (suspected nosocomial Covid-19 infection where tested positive >48 hours after hospital admission) where sequencing reports not interpreted/actioned by Infection Prevention Control (IPC) site teams
Site intervention phase Sample collection and genomic sequencing from Covid-19 positive participants suspected of acquiring infection in hospital where sequencing reports generated both rapid or standard and received by site IPC teams for interpretation and action
Control phase 2 (prospective) Sample collection and genomic sequencing from Covid-19 positive participants suspected of acquiring infection in hospital where sequencing reports not interpreted/actioned by IPC site teams - where deemed ethical and approved by oversight committees i.e. DMEC.
primary purpose: Health Services Research
masking: None (Open Label)
measure: Incidence rates of IPC-defined hospital-onset COVID-19 infection (HOCIs)
time frame: 6 months
description: Incidence rate of IPC-defined HOCIs, measured as incidence rate of recorded cases per week per 100 inpatients, during each phase of the study based on case report forms.
measure: Change in incidence rates of IPC-defined HOCIs with rapid vs standard sequencing
time frame: 6 months
description: Identification of nosocomial transmission using sequencing data in potential HOCIs in whom this was not identified by pre-sequencing IPC evaluation, measured using pre- and post-sequencing case report forms for each enrolled patient during study phases in which the sequence reporting tool is in use.
measure: Incidence rates of IPC-defined hospital outbreaks
time frame: 6 months
description: Incidence rate of IPC-defined hospital outbreaks, defined as cases of hospital transmission linked by location and with intervals between diagnoses of no greater than 2 weeks (relevant data extracted from case report forms), measured as incidence rate of outbreak events per week per 100 inpatients during each phase of the study.
measure: Incidence rates of IPC+sequencing-defined hospital outbreaks
time frame: 6 months
description: Incidence rate of IPC+sequencing-defined hospital outbreaks, defined by retrospective review of all available sequencing and epidemiological data for identification of transmission clusters and measured as outbreak events per week per 100 inpatients during each phase of the study.
measure: Changes to IPC actions following viral sequence reports
time frame: 6 months
description: Changes to IPC actions implemented following receipt of viral sequence report, measured using pre- and post-sequencing case report forms for each enrolled patient during study phases in which the sequence reporting tool is in use.
measure: Recommended changes to IPC actions following viral sequence report - not implemented
time frame: 6 months
description: Changes to IPC actions that would ideally have been implemented (given unlimited resources) following receipt of viral sequence report, measured using pre- and post-sequencing case report forms for each enrolled patient during study phases in which the sequence reporting tool is in use.
measure: Health economic benefit to IPC of standard vs rapid sequencing reports
time frame: 6 months
description: Health economic benefit of standard and rapid sequencing reports to IPC measured using bespoke health economic case report data comparison between baseline, standard and rapid sequencing phases.
measure: Impact of both standard and rapid sequencing reports on number of HCW days off work
time frame: 6 months
description: Number of HCW days off work measured from sampling these data points on case report forms at all study phases.
arm group label: Genomic-sequence informed IPC measures
arm group type: Other
description: Cohort follow baseline (no report receipt), then rapid vs standard sequencing report receipt phase, then return to baseline phase (no report receipt)
intervention type: Other
intervention name: Use of virus (Covid-19) genome sequence report to inform infection prevention control procedures
description: Rapid or standard (time to return to sites) receipt of virus (Covid-19) genomic sequencing reports
arm group label: Genomic-sequence informed IPC measures
criteria: 
gender: All
minimum age: N/A
maximum age: N/A
healthy volunteers: No
last name: Judith Breuer, MD
role: Principal Investigator
affiliation: University College, London
facility: 
country: United Kingdom
responsible party type: Sponsor
mesh term: Infections
mesh term: Communicable Diseases
mesh term: COVID-19
mesh term: Coronavirus Infections
mesh term: Cross Infection
sharing ipd: Yes
ipd description: The fully anonymised datasets analysed during the study will be stored on a publicly available repository. The COG-UK HOCI study to be shared on the UCL Data Repository data-sharing platform so that the data may be reused by other researchers. The protocol will also be shared.
ipd info type: Study Protocol
ipd time frame: This will be done with 6 months of public reporting of results, with data available for 5 years.
ipd access criteria: Fully open access
submitted: September 5, 2022
returned: August 7, 2023