A business venue being explored by Amazon and smaller companies as well is delivery via drones. Interesting to see that the technology for skyjacking drones is already being pursued. If you consider drone piracy to be a business model (and I guess it should be...
Learn with BioMedware Posts
The quantified self and crowd sourcing of the genome+, exposome and behavome: Perspective and call for action
by Geoffrey Jacquez, Ph.D. | Jan 28, 2014 | Learn with BioMedware
by Geoffrey M. Jacquez1,2 and Robert Rommel2 1. Department of Geography, State University of New York at Buffalo, Buffalo, NY 2. BioMedware, Ann Arbor MI Introduction: Perhaps one of the greatest challenges and limitations in environmental health and epidemiology is...
A commentary on the Behavome and Genetic GIS
by Geoffrey Jacquez, Ph.D. | Sep 5, 2013 | Learn with BioMedware
Recently, I coined the term “Behavome” as the totality of an individual’s behaviors that mediate exposures (the exposome) and gene expression (the genome). This construct matters because it largely defines the determinants of human health. Figure 1 This schematic...
Researchers suggest geographic boundary analysis to detect shift in species distributions in response to climate change
by Geoffrey Jacquez, Ph.D. | Oct 25, 2012 | Learn with BioMedware
Quantifying the spatial relationship between bird species’ distributions and landscape feature boundaries in southern Ontario, Canada
Drugs recalled by New England Compounding Center: The tip of the iceberg?
by Geoffrey Jacquez, Ph.D. | Oct 17, 2012 | Learn with BioMedware
As hypotheses are tested and rejected, the remaining hypotheses are those that plausibly might explain the observed pattern. But how often do we include medications contaminated with foreign agents — fungus, bacteria, or otherwise — in our set of explanatory hypotheses? Until now, rarely, if ever. What we are learning from the New England Compounding Center is that contaminated medications largely explain the observed outbreak of fungal meningitis.
Genetic GIS: A call and a research agenda.
by Geoffrey Jacquez, Ph.D. | Oct 5, 2012 | Learn with BioMedware
Genetic GIS provides a comprehensive model of human health and its determinants including genetic, environmental and behavioral dimensions.
Part 3: Spatial Autocorrelation and Clusters of Health Events
by Geoffrey Jacquez, Ph.D. | Jan 31, 2012 | Learn with BioMedware
Part 3 Neutral models This is the third in a series on spatial autocorrelation and clusters of health events. The first part presented a framework for analyzing disease clusters that builds on the principles of strong inference. Strong inference involves enumeration...
Part 2: Spatial Autocorrelation and Clusters of Health Events
by Geoffrey Jacquez, Ph.D. | Jan 24, 2012 | Learn with BioMedware
Part 2 Sources of Spatial Autocorrelation Summary: This blog presents several of the sources of spatial autocorrelation in health event data. Many of these could plausibly lead to clusters of health events, others (such as interpolation autocorrelation) may act...
Part 1: Spatial Autocorrelation and Clusters of Health Events
by Geoffrey Jacquez, Ph.D. | Jan 15, 2012 | Learn with BioMedware
Part 1 Strong Inference The Centers for Disease Control as well as state and local health agencies use information on clusters of health events to respond to cluster allegations brought forward by a concerned public; identify impacted local populations (where are...
The small numbers problem Part 3: Diagnostics for the small numbers problem
by Geoffrey Jacquez, Ph.D. | Nov 14, 2011 | Learn with BioMedware
To follow along with the analyses in this blog, download and install a trial version of SpaceStat here. An earlier blog defined the small numbers problem and illustrated that rates calculated with small denominators (e.g. small at-risk populations) have high variance...