R01AI161399

COVID-19 - Global Mix / Investigation of COVID-19 Disease Parameters for Transmission Models in Low-Resource Settings - Project Summary

We began to quantify household- and community-level interactions in 2019 with our project, "Comprehensive Profiling of Social Mixing Patterns in Resource Poor Countries" ("GlobalMix", Grant R01 HD097175-01), to investigate human-to-human interactions relevant for respiratory infection transmission. This proposal will build on existing GlobalMix study infrastructure to estimate LMIC-specific epidemiologic parameters for COVID-19.

In the proposed study, we will connect field epidemiology and mathematical modeling approaches by estimating the rate of, and heterogeneity in, household-based transmission of SARS-CoV-2 through longitudinal cohort approaches. We will use this information in conjunction with highly-granular data on social interactions from GlobalMix to identify key epidemiological parameters for COVID-19, including the community-level force of infection and attack rates within households. We will then use this information to build LMIC-specific dynamic models to evaluate the impact of key interventions to reduce transmission: vaccination and non-pharmaceutical interventions such as face masks, shelter-in-place policies, and school closure.

This work will be completed in three specific aims:

Aim 1: Quantify COVID-19 transmission across contact networks within the household environment. We will conduct longitudinal respiratory disease surveillance in households participating in the GlobalMix study. We will collect longitudinal samples of respiratory specimens from household members for identification of COVID-19 and other respiratory pathogens such as influenza. This information will be overlaid on contact network data from GlobalMix.

Aim 2: Estimate key epidemiological features of SARS-CoV-2 and other respiratory pathogens in LMIC settings. We will collect blood specimens from GlobalMix study participants and test for antibody levels (IgG) against SARS-CoV-2. We will calculate age-specific infection fatality rates (IFRs) and use antibody titers to infer time of infection and calculate community-level incidence over time. We will generate age-structured seroprevalence curves, which will provide a robust measure of exposure across the age range. Together with the contact data from GlobalMix, we will infer age-specific transmission probabilities that will be used as inputs into the network models in Aim 3. Samples will be stored for future testing, including antibody avidity and T/B cell activation.

Aim 3: Estimate the impact of control measures on COVID-19 in LMIC. We will use the epidemiological parameters estimated in Aim 1 and the setting- and age-specific force of infection estimates from Aim 2 to parameterize dynamic network-based mathematical models of disease transmission. Models will incorporate social mixing data from GlobalMix to project the impact of extended shelter-in-place policies, policies concerning the use of face masks, and the introduction of a SARS-CoV-2 vaccine.

The University Of Texas Southwestern Medical Center

TO ASSIST PUBLIC AND PRIVATE NONPROFIT INSTITUTIONS AND INDIVIDUALS TO ESTABLISH, EXPAND AND IMPROVE BIOMEDICAL RESEARCH AND RESEARCH TRAINING IN INFECTIOUS DISEASES AND RELATED AREAS, TO CONDUCT DEVELOPMENTAL RESEARCH, TO PRODUCE AND TEST RESEARCH MATERIALS. TO ASSIST PUBLIC, PRIVATE AND COMMERCIAL INSTITUTIONS TO CONDUCT DEVELOPMENTAL RESEARCH, TO PRODUCE AND TEST RESEARCH MATERIALS, TO PROVIDE RESEARCH SERVICES AS REQUIRED BY THE AGENCY FOR PROGRAMS IN INFECTIOUS DISEASES, AND CONTROLLING DISEASE CAUSED BY INFECTIOUS OR PARASITIC AGENTS, ALLERGIC AND IMMUNOLOGIC DISEASES AND RELATED AREAS. PROJECTS RANGE FROM STUDIES OF MICROBIAL PHYSIOLOGY AND ANTIGENIC STRUCTURE TO COLLABORATIVE TRIALS OF EXPERIMENTAL DRUGS AND VACCINES, MECHANISMS OF RESISTANCE TO ANTIBIOTICS AS WELL AS RESEARCH DEALING WITH EPIDEMIOLOGICAL OBSERVATIONS IN HOSPITALIZED PATIENTS OR COMMUNITY POPULATIONS AND PROGRESS IN ALLERGIC AND IMMUNOLOGIC DISEASES. BECAUSE OF THIS DUAL FOCUS, THE PROGRAM ENCOMPASSES BOTH BASIC RESEARCH AND CLINICAL RESEARCH. SMALL BUSINESS INNOVATION RESEARCH (SBIR) PROGRAM EXPANDS AND IMPROVES PRIVATE SECTOR PARTICIPATION IN BIOMEDICAL RESEARCH. THE SBIR PROGRAM INTENDS TO INCREASE AND FACILITATE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, TO INCREASE SMALL BUSINESS PARTICIPATION IN FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION. THE SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAM STIMULATES AND FOSTERS SCIENTIFIC AND TECHNOLOGICAL INNOVATION THROUGH COOPERATIVE RESEARCH AND DEVELOPMENT CARRIED OUT BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO FOSTER TECHNOLOGY TRANSFER BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION. RESEARCH CAREER DEVELOPMENT AWARDS SUPPORT THE DEVELOPMENT OF SCIENTISTS DURING THE FORMATIVE STAGES OF THEIR CAREERS. INDIVIDUAL NATIONAL RESEARCH SERVICE AWARDS (NRSAS) ARE MADE DIRECTLY TO APPROVE APPLICANTS FOR RESEARCH TRAINING IN SPECIFIED BIOMEDICAL SHORTAGE AREAS. IN ADDITION, INSTITUTIONAL NATIONAL RESEARCH SERVICE AWARDS ARE MADE TO ENABLE INSTITUTIONS TO SELECT AND MAKE AWARDS TO INDIVIDUALS TO RECEIVE TRAINING UNDER THE AEGIS OF THEIR INSTITUTIONAL PROGRAM.

93.855 - Allergy and Infectious Diseases Research

National Institute of Allergy and Infectious Diseases (NIAID) [HHS - NIH]

Dallas, Texas 753907208 United States

Single Zip Code

NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed) (PA-20-185)

Amendment Since initial award the total obligations have increased 334% from $785,776 to $3,407,949.