AbstractsBiology & Animal Science

Modeling Environmental Exposure and Disease at the Scale of Microbes, Hospital Patients, and Geographic Regions

by Ben K Greenfield

Institution: University of California – Berkeley
Year: 2016
Keywords: Environmental health; Public health; Microbiology; antibiotic; exposure science; hospital-associated infection; model; multivariate; spatial
Posted: 02/05/2017
Record ID: 2131102
Full text PDF: http://www.escholarship.org/uc/item/5wz4t5pj


This thesis presents the application of three mathematical models to problems linking environmental exposures to human health. The models differ in spatial and temporal analysis scale. The premise underlying this work is that reliable models follow from careful matching of model scale to the specific research question. Chapter 1 models bacterial competition at a cellular scale, to study the factors that may result in environmental antimicrobial resistance. A simple analytical solution for the antibiotic minimum selection concentration (MSC) is developed. The MSC is the lowest environmental antibiotic concentration at which a resistant bacterial strain will outcompete a sensitive strain. The solution is formulated as the ratio between the MSC and the minimum inhibitory concentration (MIC), which is a widely available laboratory measurement of the antibiotic concentration at which the growth of a sensitive strain is inhibited. Model equations were fitted to published experimental growth rate competition results. The model fit varied among nine compound-taxa combinations examined, but predicted the experimentally observed MSC/MIC ratio well (R2 ≥ 0.95). Sensitivity analysis indicated that the MSC was sensitive to the shape of the antibiotic versus growth dose–response for the sensitive strain and to the fitness difference between strains. Model findings suggest a benefit of future experimental studies characterizing bacterial competition at low antibiotic concentrations. Employing the model in combination with empirical antibiotic growth curve data, it may be possible to predict environmental antibiotic concentrations at which resistant strains will be selected for. This could be incorporated into risk assessment models, to identify high risk environments for dissemination of antibiotic resistance.Chapter 2 describes a quantitative model of the relative importance of direct skin-to-skin contact versus indirect transfer via environmental textiles and surfaces for hospital pathogens. The model describes the rate of environmental transfer of pathogenic microbes between patients in a hospital setting. However, the model does not consider the likelihood of infection. The model was applied to transmission of pathogens between patients residing in separate hospital rooms, via a health-care worker. Simulations were performed to examine the separate contribution of skin, textiles, and nonporous surfaces to the total pathogen number transmitted. The role of elimination (organism death) was considered by comparing literature elimination rates for six pathogens: Acinetobacter baumannii, Staphylococcus aureus, Streptococcus pneumoniae, Bordetella pertussis, sudden acute respiratory syndrome coronavirus (SARS-CoV), and influenza A. Based on model results, all pathogens except influenza A exhibit a high rate of transmission in the model scenario, suggesting that transmission via health-care workers is a valid concern. With the exception of influenza A, there was overlap in literature elimination rates among the pathogens, resulting in…