The novel coronavirus that emerged late in 2019 (COVID-19) has highlighted the importance of incorporating human behavior and socio-economic factors that affect disease risk on the transmission dynamics and control of respiratory pathogens. Several classical epidemiological models that did not explicitly account for these factors generally failed to accurately capture the observed trajectory (thereby failing to make realistic forecasts) of the pandemic. Specifically, classical epidemiological models need to be extended to explicitly account for the impacts of, and the bi-direction feedbacks between, human behavior and socio-economic factors that influence the disease risk choices humans make during outbreaks of respiratory pathogens. This conference brings together a diverse interdisciplinary team of researchers, from mathematics, epidemiology, economics, social science, computer science, statistics, data science and public health, to discuss the state-of-the-art methodologies and theories for realistically incorporating the pertinent human behavior and socio-economic heterogeneities that affect disease risk and transmission dynamics into classical epidemiological models, aimed at enhancing their predictive power. In addition to using behavior theories and observed data to develop behavior-driven mathematical models for the spread of emerging (novel), re-emerging and re-surging respiratory pathogens, the conference will also address the problem of designing realistic models for the spread of new ideas, technologies, information, and misinformation pertaining to (and during) the spread and control of respiratory pathogens. The conference will also celebrate the distinguished career of James Yorke.