| Disease transmission between host individuals is the defining characteristic of infectious disease dynamics, and the transmission process is the core element of epidemic models. This dissertation describes advances in the modeling of disease transmission in populations with structural and dynamical heterogeneities, including behavioral changes due to illness, distinctions in contact patterns and control measures between hospitals and general communities, and individual-level variation in infectiousness arising from host, pathogen and environmental factors. Theoretical and empirical approaches are presented, motivated sometimes by fundamental questions about disease spread, and sometimes by applied problems related to specific outbreaks.; In Chapter 2, I present a mechanistic derivation of the frequency-dependent transmission model from a pair-based contact process, then extends this classical model to incorporate effects of illness on pairing behavior. Frequency-dependent transmission is the standard model for sexually-transmitted diseases (STDs), but a timescale approximation required for the derivation means that pair-based STD transmission is portrayed accurately only for promiscuous populations and chronic, less-transmissible infections. Simulations define the limits of the classical model for two broad classes of STD.; In Chapter 3, I investigate the stochastic invasion dynamics of an emerging disease in a community and its associated hospital, exploring for the first time the potential amplifying role of hospitals in an outbreak characterized by nosocomial spread. Severe acute respiratory syndrome (SARS) was transmitted extensively within hospitals, and healthcare workers comprised a large proportion of SARS cases worldwide. I evaluate contact precautions and case management (quarantine and isolation) as control measures for SARS, revealing that hospital infection control is the most potent measure and should be practiced by all individuals in affected hospitals, rather than only those interacting with known SARS cases.; In Chapter 4, I address the impact of individual-level variation in infectiousness, and resulting superspreading events (SSEs), on disease emergence. I introduce the "individual reproductive number", a natural extension of the basic reproductive number R0 from a population average to a distribution incorporating individual variation. The degree of individual variation is quantified from outbreak data for ten diseases of casual contact (including SARS, smallpox, plague and H5N1 avian influenza), showing conclusively that conventional models are inadequate to represent real transmission patterns. I provide the first in-depth discussion and analysis of SSEs, including an extensive review of their causes and a general, probabilistic definition that allows prediction of the proportion of cases causing SSEs for a given disease outbreak. (Abstract shortened by UMI.)... |
