A stochastic multi-scale model of HIV-1 transmission for decision-making: application to a MSM population.

BackgroundIn the absence of an effective vaccine against HIV-1, the scientific community is presented with the challenge of developing alternative methods to curb its spread. Due to the complexity of the disease, however, our ability to predict the impact of various prevention and treatment strategies is limited. While ART has been widely accepted as the gold standard of modern care, its timing is debated.ObjectivesTo evaluate the impact of medical interventions at the level of individuals on the spread of infection across the whole population. Specifically, we investigate the impact of ART initiation timing on HIV-1 spread in an MSM (Men who have Sex with Men) population.Design and methodsA stochastic multi-scale model of HIV-1 transmission that integrates within a single framework the in-host cellular dynamics and their outcomes, patient health states, and sexual contact networks. The model captures disease state and progression within individuals, and allows for simulation of therapeutic strategies.ResultsEarly ART initiation may substantially affect disease spread through a population.ConclusionsOur model provides a multi-scale, systems-based approach to evaluate the broader implications of therapeutic strategies

Immune Activation, Cd4+ T Cell Counts, and Viremia Exhibit Oscillatory Patterns over Time in Patients with Highly Resistant HIV Infection

The rates of immunologic and clinical progression are lower in patients with drug-resistant HIV compared to wild-type HIV. This difference is not fully explained by viral load. It has been argued that reductions in T cell activation and/or viral fitness might result in preserved target cells and an altered relationship between the level of viremia and the rate of CD4+ T cell loss. We tested this hypothesis over time in a cohort of patients with highly resistant HIV. Fifty-four antiretroviral-treated patients with multi-drug resistant HIV and detectable plasma HIV RNA were followed longitudinally. CD4+ T cell counts and HIV RNA levels were measured every 4 weeks and T cell activation (CD38/HLA-DR) was measured every 16 weeks. We found that the levels of CD4+ T cell activation over time were a strong independent predictor of CD4+ T cell counts while CD8+ T cell activation was more strongly associated with viremia. Using spectral analysis, we found strong evidence for oscillatory (or cyclic) behavior in CD4+ T cell counts, HIV RNA levels, and T cell activation. Each of the cell populations exhibited an oscillatory behavior with similar frequencies. Collectively, these data suggest that there may be a mechanistic link between T cell activation, CD4+ T cell counts, and viremia and lends support for the hypothesis of altered predator-prey dynamics as a possible explanation of the stability of CD4+ T cell counts in the presence of sustained multi-drug resistant viremia

A stochastic multi-scale model of HIV-1 transmission for decision-making: application to a MSM population.

BackgroundIn the absence of an effective vaccine against HIV-1, the scientific community is presented with the challenge of developing alternative methods to curb its spread. Due to the complexity of the disease, however, our ability to predict the impact of various prevention and treatment strategies is limited. While ART has been widely accepted as the gold standard of modern care, its timing is debated.ObjectivesTo evaluate the impact of medical interventions at the level of individuals on the spread of infection across the whole population. Specifically, we investigate the impact of ART initiation timing on HIV-1 spread in an MSM (Men who have Sex with Men) population.Design and methodsA stochastic multi-scale model of HIV-1 transmission that integrates within a single framework the in-host cellular dynamics and their outcomes, patient health states, and sexual contact networks. The model captures disease state and progression within individuals, and allows for simulation of therapeutic strategies.ResultsEarly ART initiation may substantially affect disease spread through a population.ConclusionsOur model provides a multi-scale, systems-based approach to evaluate the broader implications of therapeutic strategies

A cluster containing 10% of the population is infected at time zero, all infected individuals receive ART.

<p>ART initiation scenarios are as in Figure 2. The simulation is performed to test the response of the model to an increase of the number of patients infected at time zero. </p

The two individuals with the highest number of sexual partners (20) are infected at time zero.

<p>No one receives ART. The simulation is performed to test the response of the model to the impact of highly connected individuals.</p

A multi-scale model of HIV-1 transmission.

<p>Within-host models (A) specific to each stage of disease (B) produce estimates of viral load and CD4+ cell count in every individual. These are key parameters that determine the course of disease, and dictate when regimens need to be changed. Graphs in (A) are a sample simulation of viral load within one patient, they demonstrate the differences in viral load in response to changing the timing of ART initiation . Viremia is tempered with ART initiated during the acute infection phase. Each individual is placed on a sexual network (C) with a distinct structure. The transmissibility is a function of the CD4+ count that determines the overall health of an individual and therefore the level of sexual activity; and of viral load which determines the probability of infection in each sexual encounter.</p

A7. Decision Making and Analysis Tools for Bio-surveillance and Sustainable Watershed Management

The biggest challenges in mitigating water contamination with chemical and biological agents are (1) identification of their sources, and (2) lack of real- or near-real time assessment of environmental processes. This problem is exacerbated by the heterogeneous distribution of contaminants in time and space. Any watershed management decisions must therefore be made under conditions of uncertainty. This is the focus of the ongoing work at UC’s Multi-Scale Environmental Modeling Lab, which brings into a common, systems-based framework several aspects of watershed management. In this framework, strategic and optimized biosurveillance yields multi-scale data that include environmental information coupled with microbial concentrations, genetic sequences and host-specific information from environmental samples. These data are used in stochastic models of microbial dynamics and nutrient transport that capture their interactions with sediment transport in watersheds. Results embedded into GIS are employed to develop risk and vulnerability maps, which in turn are used to inform decisions on surveillance strategies and watershed management. We show two applications in Little Miami River’s East Fork Watershed in Southeast Ohio. The first application couples a stochastic microbial transport model with an erosion model (the Water Erosion Prediction Project – WEPP) to better understand transport and partitioning of fecal contaminants in overland and stream flow. The second develops spatial probability maps that indicate probabilities of exceeding the nitrogen standard in various hydrologic regimes. This effort is based on load-resistance models borrowed from structural engineering, which provide methodology to estimate failure in complex structures. Both models are implemented in ArcGIS’s Schematic Processor, a suite of geoprocessing tools expanded to accommodate for complexities of microbial and nutrient transport in watersheds

Immune activation, CD4+ T cell counts, and viremia exhibit oscillatory patterns over time in patients with highly resistant HIV infection.

The rates of immunologic and clinical progression are lower in patients with drug-resistant HIV compared to wild-type HIV. This difference is not fully explained by viral load. It has been argued that reductions in T cell activation and/or viral fitness might result in preserved target cells and an altered relationship between the level of viremia and the rate of CD4+ T cell loss. We tested this hypothesis over time in a cohort of patients with highly resistant HIV. Fifty-four antiretroviral-treated patients with multi-drug resistant HIV and detectable plasma HIV RNA were followed longitudinally. CD4+ T cell counts and HIV RNA levels were measured every 4 weeks and T cell activation (CD38/HLA-DR) was measured every 16 weeks. We found that the levels of CD4+ T cell activation over time were a strong independent predictor of CD4+ T cell counts while CD8+ T cell activation was more strongly associated with viremia. Using spectral analysis, we found strong evidence for oscillatory (or cyclic) behavior in CD4+ T cell counts, HIV RNA levels, and T cell activation. Each of the cell populations exhibited an oscillatory behavior with similar frequencies. Collectively, these data suggest that there may be a mechanistic link between T cell activation, CD4+ T cell counts, and viremia and lends support for the hypothesis of altered predator-prey dynamics as a possible explanation of the stability of CD4+ T cell counts in the presence of sustained multi-drug resistant viremia

Determining Hot Spots of Fecal Contamination in a Tropical Watershed by Combining Land-Use Information and Meteorological Data with Source-Specific Assays

The objective of this study was to combine knowledge of environmental, topographical, meteorological, and anthropologic factors in the Río Grande de Arecibo (RGA) watershed in Puerto Rico with information provided by microbial source tracking (MST) to map hot spots (i.e., likely sources) of fecal contamination. Water samples were tested for the presence of human and bovine fecal contamination in addition to fecal indicator bacteria and correlated against several land uses and the density of septic tanks, sewers, and latrines. Specifically, human sources were positively correlated with developed (<i>r</i> = 0.68), barren land uses (<i>r</i> = 0.84), density of septic tanks (<i>r</i> = 0.78), slope (<i>r</i> = 0.63), and the proximity to wastewater treatment plants (WWTPs) (<i>r</i> = 0.82). Agricultural land, the number of upstream National Pollution Discharge Elimination System (NPDES) facilities, and density of latrines were positively associated with the bovine marker (<i>r</i> = 0.71; <i>r</i> = 0.74; and <i>r</i> = 0.68, respectively). Using this information, we provided a hot spot map, which shows areas that should be closely monitored for fecal contamination in the RGA watershed. The results indicated that additional bovine assays are needed in tropical regions. We concluded that meteorological, topographical, anthropogenic, and land cover data are needed to evaluate and verify the performance of MST assays and, therefore, to identify important sources of fecal contamination in environmental waters