Influence and transmission of commensal and infectious pathogens
Date of Award
Fall 2023
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Engineering and Applied Science
First Advisor
Christakis, Nicholas
Abstract
It is possible to exploit rapidly developing insights and data availability about social network structure and function so as to improve the accuracy of forecasting epidemics – which in the context of newer epidemics still remains a multi-layered problem. Here, we utilize new real-world network data we mapped among 24,703 villagers in Honduras over the span of 4 years to build a complete epidemiological model, using villager’s personal attributes (like age, gender), the quality of their social interaction (number of social neighbors, frequency and amount of contact in each interaction), and the characteristics of the pathogen. we show that individual biology, social interaction patterns and the type of the pathogen all play a vital role in determining a person’s vulnerability and super-spreading ability.Just like pathogens, gut commensals are also an integral part of our lives. In order to comprehensively characterize the relationship of the microbiome with multiple aspects of people’s physical and social lives, we used a population-based approach and sequenced the gut metagenome from 1,871 villagers from 19 villages in the isolated Mesoamerican highlands of Western Honduras. After analysis, we report 2,148 statistically robust associations spanning 639 microbial species (including both known (73.2%) and unknown (26.8%) taxa) and 123 phenotypes. Our phenotypes combined account for 19.2% of the species variation and 33.4% of the pathway variation. By expanding our knowledge of the human microbiome to a novel non-Westernized cohort, it is possible to further our understanding of the role of the gut microbiome in illness and other phenotypes, and, at the same time, open up opportunities to use such findings to develop inexpensive biomarkers to aid diagnostics in rural settings. Since social relationships are also an integral part of our lives, we also observe that socially central individuals are more microbially similar to the overall village than those on the social periphery. Furthermore, using strain-sharing data alone, we can confidently predict a wide variety of relationships within the villages, and the rate of strain sharing between two individuals more strongly predicts the presence of a social relationship than any other sociodemographic covariate.
Recommended Citation
Vishnempet Shridhar, Shivkumar, "Influence and transmission of commensal and infectious pathogens" (2023). Yale Graduate School of Arts and Sciences Dissertations. 1243.
https://elischolar.library.yale.edu/gsas_dissertations/1243
