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Principal Investigator: Laura Forsberg White
Organization: BOSTON UNIVERSITY MEDICAL CAMPUS
Fiscal Year: 2024
Award: $412,500
Funding agency: National Institute of General Medical Sciences
PROJECT SUMMARY
The “Tools for Transmission of Agents and Conditions (TRAC)” program will synergize statistical and
mathematical modeling work in three areas of application: 1) Tuberculosis (TB) incidence and transmission; 2)
monitoring substance use disorder (SUD) patterns; and 3) SARS CoV-2 transmission modeling. These three
conditions are major public health problems, with TB being the leading cause of infectious disease death globally,
SUD causing more deaths in the United States than HIV/AIDS in its peak, and SARS CoV-2 causing a pandemic
with societal disruption and mortality exceeding anything we have experienced in the last century. We need
improved analytical tools that leverage existing data to monitor these diseases, infer transmission hot spots,
determine the efficacy of interventions, and understand the burden of these conditions.
This program will bring together an expert group of quantitative researchers with skills that are readily applied to
these problems. We also leverage our strong collaborations with clinician researchers and public health officials
to ensure that the methods we develop are addressing important questions and consistent with our current
understanding of these diseases. By creating a program to facilitate communication between these experts, we
will enable greater innovation in modeling key aspects of these diseases and create exciting methodological
synergies across diseases. Our team is well positioned to incorporate data from emerging technologies, including
high throughput sequencing data to determine TB risk signatures and inform transmission links for TB and SARS
CoV-2. Our expertise in machine learning, a broad range of statistical methodologies, and mathematical
modeling will enable us to leverage the rich information in large databases that are emerging to better understand
SUD patterns and identify risk signatures. We will also build infrastructure with our partners to make the analytical
tools that we develop more accessible to public health practitioners and other researchers.
The impact of this work is to develop a suite of analytical tools that leverage rapidly emerging rich data sets to
improve our understanding of disease transmission patterns, monitor changing dynamics of these conditions,
and understand intervention strategies that are most effective. This work will inform public health practice for
these diseases and create reproducible tools that can be used in an ongoing way.
Terms: <2019 novel corona virus><2019 novel coronavirus><2019-nCoV><AIDS/HIV><Address><Area><Award><COVID-19 transmission><COVID-19 virus><COVID-19 virus transmission><COVID19 virus><Cessation of life><CoV-2><CoV2><Collaborations><Communicable Diseases><Communication><Data><Data Bases><Data Set><Databases><Death><Disease><Disorder><Emergent Technologies><Emerging Technologies><HIV/AIDS><High-Throughput Nucleotide Sequencing><High-Throughput Sequencing><Hot Spot><Incidence><Infectious Disease Pathway><Infectious Diseases><Infectious Disorder><Infrastructure><Intervention><Intervention Strategies><Investigators><Link><M tuberculosis infection><M. tb infection><M. tuberculosis infection><M.tb infection><M.tuberculosis infection><MTB infection><Machine Learning><Math Models><Methodology><Methods><Modeling><Monitor><Mycobacterium tuberculosis (MTB) infection><Mycobacterium tuberculosis infection><Pattern><Position><Positioning Attribute><Probabilistic Models><Probability Models><Public Health><Public Health Practice><Reproducibility><Research><Research Personnel><Researchers><Risk><SARS corona virus 2><SARS-CO-V2><SARS-COVID-2><SARS-CoV-2><SARS-CoV-2 transmission><SARS-CoV2><SARS-associated corona virus 2><SARS-associated coronavirus 2><SARS-coronavirus-2><SARS-related corona virus 2><SARS-related coronavirus 2><SARSCoV2><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><Statistical Models><Substance Use Disorder><TB infection><Transmission><Treatment Efficacy><Tuberculosis><United States><Work><Wuhan coronavirus><analytical tool><communicable disease transmission><coronavirus disease 2019 transmission><coronavirus disease 2019 virus><coronavirus disease 2019 virus transmission><coronavirus disease-19 virus><data base><determine efficacy><disease transmission><disseminated TB><disseminated tuberculosis><efficacy analysis><efficacy assessment><efficacy determination><efficacy evaluation><efficacy examination><evaluate efficacy><examine efficacy><experience><hCoV19><improved><infection due to Mycobacterium tuberculosis><infectious disease transmission><innovate><innovation><innovative><intervention efficacy><interventional strategy><machine based learning><mathematic model><mathematical model><mathematical modeling><mortality><nCoV2><pandemic><pandemic disease><programs><severe acute respiratory syndrome coronavirus 2 transmission><skills><statistical linear mixed models><statistical linear models><substance use and disorder><synergism><therapeutic efficacy><therapy efficacy><tool><transmission process><transmitted COVID-19><transmitted SARS-CoV-2><transmitted coronavirus disease 2019><transmitted severe acute respiratory syndrome coronavirus 2><tuberculosis infection><tuberculous spondyloarthropathy>