R01AI160780

Human Mobility Models to Forecast Disease Dynamics and the Effectiveness of Public Health Interventions - Project Summary/Abstract

Human mobility underlies infectious disease transmission and determines the spatial-temporal dynamics of outbreaks and endemic disease dynamics. Yet, we do not understand how best to incorporate individual or population mobility patterns into models of infectious diseases.

Human travel has been successfully incorporated into models used for planning, surveillance, and reactive responses to influenza pandemics, the COVID-19 pandemic, malaria, and others. However, little validation or comparison of approaches used in these models has been performed. Further, there has been no systematic investigation of the extent to which the many different existing sources of human travel data quantify travel patterns, or which descriptions of human mobility are most relevant to disease processes.

The small amount of human mobility data available globally requires generalization or extrapolation of features of one dataset to another setting, time, or circumstance. This generalization may work for some features of pathogens for a subset of pathogens or transmission routes but may fail miserably in others. It is unlikely that all travel patterns are relevant for all types of diseases. The life history of each pathogen, transmission routes, age structure of incidence, and outbreak context will all dictate the importance of specific types of movement.

For mobility data to be useful in planning for outbreaks and monitoring interventions, transmission models utilizing mobility data and models must be confronted with epidemiological data (including contact tracing, traditional surveillance, and genetic data) from a variety of sources.

Here, we propose to perform the first systematic analysis of existing mobility data and models to identify which models perform best under multiple assumptions using a range of simulations and data from historic outbreaks. We will also identify circumstances when generalized models or non-local data are misleading.

To do this, we will collate and standardize a large number of mobility datasets collected by various methods. We will statistically characterize these datasets to identify sources of variation in human mobility at individual, household, community, and larger scales. We will develop multiple candidate models describing mobility and incorporate these candidate models into a range of commonly used models of infectious disease transmission.

Proceeding with the principle that human mobility is only useful to models of infectious diseases if it improves our ability to recapitulate the dynamics of observed outbreaks, we will test the ability of each of these candidate mobility models to explain observed patterns of contacts and sequenced pathogens observed in outbreaks of dengue, Zika, Ebola, and COVID-19.

In doing this, we will identify conditions under which human mobility can improve our understanding of the transmission and pathogens, inform response strategies, and create a resource that can inform responses to multiple current and future outbreaks.

The Johns Hopkins University

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]

Baltimore, Maryland 212052103 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 361% from $706,315 to $3,257,651.