Patch dynamics modeling framework from pathogens' perspective: Unified and standardized approach for complicated epidemic systems.

Mathematical models are powerful tools to investigate, simulate, and evaluate potential interventions for infectious diseases dynamics. Much effort has focused on the Susceptible-Infected-Recovered (SIR)-type compartment models. These models consider host populations and measure change of each compartment. In this study, we propose an alternative patch dynamic modeling framework from pathogens' perspective. Each patch, the basic module of this modeling framework, has four standard mechanisms of pathogen population size change: birth (replication), death, inflow, and outflow. This framework naturally distinguishes between-host transmission process (inflow and outflow) and within-host infection process (replication) during the entire transmission-infection cycle. We demonstrate that the SIR-type model is actually a special cross-sectional and discretized case of our patch dynamics model in pathogens' viewpoint. In addition, this patch dynamics modeling framework is also an agent-based model from hosts' perspective by incorporating individual host's specific traits. We provide an operational standard to formulate this modular-designed patch dynamics model. Model parameterization is feasible with a wide range of sources, including genomics data, surveillance data, electronic health record, and from other emerging technologies such as multiomics. We then provide two proof-of-concept case studies to tackle some of the existing challenges of SIR-type models: sexually transmitted disease and healthcare acquired infections. This patch dynamics modeling framework not only provides theoretical explanations to known phenomena, but also generates novel insights of disease dynamics from a more holistic viewpoint. It is also able to simulate and handle more complicated scenarios across biological scales such as the current COVID-19 pandemic.

Four Challenges Associated With Current Mathematical Modeling Paradigm of Infectious Diseases and Call for a Shift.

Mathematical models are critical tools to characterize COVID-19 dynamics and take action accordingly. We identified 4 major challenges associated with the current modeling paradigm (SEIR) that hinder the efforts to accurately characterize the emerging COVID-19 and future epidemics. These challenges included (1) lack of consistent definition of "case"; (2) discrepancy between patient-level clinical insights and population-level modeling efforts; (3) lack of adequate inclusion of individual behavioral and social influence; and (4) allowing little flexibility of including new evidence and insights when our knowledge evolved rapidly during the pandemic. Therefore, these challenges made the current SEIR modeling paradigm less practical to handle the complex COVID-19 and future pandemics. Novel and more reliable data sources and alternative modeling paradigms are needed to address these issues.

Caloric intake and hypothalamic neurotransmitters in Zucker rats made acutely diabetic with streptozocin.

Zucker rats, lean and obese, treated with low dose intraperitoneal injections of streptozocin become hyperglycemic within 24h. Insulin levels fall, although the obese animal remains hyperinsulinemic. Associated with these changes in glucose and insulin there are transient decreases in caloric intake. Macronutrient selection studies show that protein consumption decreases. There is a trend for fat intake to decrease. The levels of hypothalamic neurotransmitters in the lean animals are not altered by streptozocin. The levels of 5-hydroxyindoleacetic acid increases in the streptozocin-treated obese animal in the paraventricular region, ventromedial region and the raphe. Serotonin is also significantly increased in the paraventricular region of the obese rat. These results suggest that acutely, treatment with streptozocin injures pancreatic islets, causing, in turn, decreases in insulin levels so that hyperglycemia ensues in both phenotypes. Associated with these perturbations are decreases in caloric intake. The magnitude of change in insulin levels is much greater in the obese rat. It is hypothesized that in the obese Zucker rat decrements in food intake are mediated by increase in serotonin turnover in the hypothalamus and these changes are related to changes of insulin levels. These data support the concept that circulating insulin affects hypothalamic neurotransmitters.