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Principal Investigator: Lee H Harrison
Organization: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
Fiscal Year: 2024
Award: $777,266
Funding agency: National Institute of Allergy and Infectious Diseases
Project Summary
Despite recent progress in reducing the incidence of healthcare-associated infections (HAIs), the Centers for
Disease Control and Prevention estimated that 687,000 HAIs occurred in U.S. acute care hospitals in 2015
and that the HAI prevalence on a given day was one in 30 patients. An estimated 72,000 patients died with
HAIs during their hospitalization. In addition, outbreaks in hospitals remain a serious problem but the vast
majority of hospitals use antiquated and ineffective methods to detect them. We established the Enhanced
Detection System for Healthcare Acquired Transmission (EDS-HAT) (R01AI127472), which combines bacterial
whole genome sequencing (WGS) surveillance (as opposed to reactive WGS) to detect outbreaks with data
mining (DM) of the electronic health record (EHR) and machine learning (ML) to identify the responsible
transmission routes. We have demonstrated that EDS-HAT detects both serious outbreaks that were otherwise
unrecognized and novel transmission routes. Despite this success, additional research is needed to improve
upon EDS-HAT and further increase capacity to detect and interrupt hospital outbreaks. For example, hospital
outbreaks of respiratory viruses such as influenza and SARS-CoV-2 are well documented, but this area of
infection prevention is understudied. The addition of respiratory virus surveillance to EDS-HAT would improve
detection and prevention of these costly HAIs. In addition, readily-available clinical microbiology data can be
incorporated into EDS-HAT algorithms to reduce reliance on WGS surveillance. Finally, WGS surveillance
analysis based entirely on core single nucleotide polymorphisms (SNPs) can falsely cluster patients.
Therefore, research to investigate the contribution(s) of the accessory genome is necessary to improve
discriminatory power of EDS-HAT. In this R01 renewal application, we propose to leverage the success of
EDS-HAT by developing additional innovative methods for identification and interruption of hospital-associated
transmission. In aim 1, we plan to use WGS surveillance and EHR DM/ML to study hospital transmission of
respiratory viruses from retrospective (aim 1a) and prospective collections (aim 1b) of respiratory virus positive
specimens at two large academic hospitals (EDS-HAT RV), one for adults and the other pediatric. In aim 2, we
will develop advanced analytic methods to create a version of EDS-HAT that relies primarily on DM/ML of the
EHR (EDS-HAT Lite) (aim 2a) and improve the discriminatory power of WGS to correctly classify patients who
are part of an outbreak (aim 2b). EDS-HAT RV and EDS-HAT Lite will undergo clinical and budget impact
analyses to determine the number of cases prevented and healthcare costs averted. These aims will be
accomplished by a team with expertise in infectious diseases epidemiology, outbreak investigation, infection
prevention, microbial genomics and genomic epidemiology, machine learning and data mining, and economic
analysis and modeling. Our proposed research will lead to improved patient safety and can serve as a model
for how outbreaks are detected and interrupted in hospitals.
Terms: <2019 novel corona virus><2019 novel coronavirus><2019-nCoV><21+ years old><Adult><Adult Human><Algorithms><Area><COVID-19 virus><COVID19 virus><Centers for Disease Control><Centers for Disease Control and Prevention><Centers for Disease Control and Prevention (U.S.)><Childhood><Classification><Clinical><Clinical Data><Clinical Microbiology><CoV-2><CoV2><Collection><Complex><Computing Methodologies><Data><Data Bases><Databases><Detection><Development><Disease Outbreaks><Economic Models><Economics><Electronic Health Record><Epidemiology><Evaluation><Genes><Genetic><Genome><Genomics><Goals><Grippe><Health Care Costs><Health Care Systems><Health Costs><Healthcare><Healthcare Costs><Healthcare Systems><Hospital Admission><Hospital Costs><Hospitalization><Hospitalization cost><Hospitals><Incidence><Infection><Infection prevention><Infectious Disease Epidemiology><Infectious Epidemiology><Influenza><Interruption><Investigation><Laboratories><Link><Machine Learning><Methods><Minisatellite Repeats><Minisatellites><Mobile Genetic Elements><Modeling><Morbidity><Morbidity - disease rate><Outbreaks><Patients><Policies><Prevalence><Prevent infection><Prevention><Prevention program><Research><Research Resources><Research Specimen><Residual><Residual state><Resources><Respiratory syncytial virus><Route><SARS corona virus 2><SARS-CO-V2><SARS-COVID-2><SARS-CoV-2><SARS-CoV2><SARS-associated corona virus 2><SARS-associated coronavirus 2><SARS-coronavirus-2><SARS-related corona virus 2><SARS-related coronavirus 2><SARSCoV2><Sampling><Seasons><Severe Acute Respiratory Coronavirus 2><Severe Acute Respiratory Distress Syndrome CoV 2><Severe Acute Respiratory Distress Syndrome Corona Virus 2><Severe Acute Respiratory Distress Syndrome Coronavirus 2><Severe Acute Respiratory Syndrome CoV 2><Severe Acute Respiratory Syndrome-associated coronavirus 2><Severe Acute Respiratory Syndrome-related coronavirus 2><Severe acute respiratory syndrome associated corona virus 2><Severe acute respiratory syndrome coronavirus 2><Severe acute respiratory syndrome related corona virus 2><Simple Repetitive Sequence><Single Base Polymorphism><Single Nucleotide Polymorphism><Specimen><Syntenic Homology><Synteny><Systematics><Testing><Time><Transmission><United States Centers for Disease Control><United States Centers for Disease Control and Prevention><VNTR><VNTR Loci><VNTR Region><VNTR Sequences><Validation><Variable Number of Tandem Repeats><Variable Tandem Repeats><Viral Respiratory Tract Infection><Virus><Wuhan coronavirus><acute care><adjudication><adjudicative process and procedure><adulthood><advanced analytics><analytical method><analytical tool><bacterial genome sequencing><bacterial whole genome sequencing><budget impact><computational methodology><computational methods><computer based method><computer methods><computing method><coronavirus disease 2019 virus><coronavirus disease-19 virus><data base><data mining><datamining><detection platform><detection system><developmental><economic><economic analysis><economic assessment><economic evaluation><electronic health care record><electronic health medical record><electronic health plan record><electronic health registry><electronic medical health record><entire genome><epidemiologic><epidemiological><evidence base><full genome><genome sequencing><genomic epidemiology><hCoV19><health care><health care settings><health care-associated infections><healthcare settings><healthcare-associated infections><hospital care><improved><innovate><innovation><innovative><machine based learning><microbial genomics><mortality><nCoV2><neglect><new approaches><novel><novel approaches><novel strategies><novel strategy><outbreak concern><outbreak potential><outbreak risk><outbreak threat><pathogen><patient safety><pediatric><prevent><preventing><prospective><respiratory><respiratory infection virus><respiratory virus><single nucleotide variant><sound><success><transmission process><validations><viral disease outbreak><viral outbreak><viral respiratory infection><viral transmission><virus disease outbreak><virus transmission><wasting><whole genome>