The Naval Research Laboratory Marine Meteorology Division, over a period of more than 15 years, has developed a series of satellite imagery training documents called the Navy Tactical Applications Guides (NT AGs). The NT AG materials are unique because of their innovative focus on operationally relevant meteorological and oceanographic phenomena of concern to naval forces throughout the world and the exceedingly high quality of printed images. Advances in hypermedia and CD-ROM technology are enabling the enhancement and continued distribution of the NT AGs through the development of an electronic application called LaserTAG. CD-ROM technology provides large reproduction and storage capacity at a relatively low cost ($25 for LaserTAG discs versus $1000 for the 11-volume NTAG set). Hypermedia and electronic conversion supply the ability to 1) rapidly locate material through keyword searches and navigate to those locations through hypermedia links, 2) read text and view graphics simultaneously using multiple windows, and 3) create electronic annotation and bookmark files. A second technology, expert systems, is further expanding potential uses of the information documented in the NTAG series. The Satellite Image Analysis Meteorological Expert System (SIAMES) encapsulates important conclusions and rules of analysis. The SIAMES prototype described here leads the user through a hierarchy of image interpretation expertise derived from the NTAG series by querying the user about details appearing in the satellite imagery. The ultimate goal, particularly important when resident expertise is minimal or nonexistent, is to develop an automated method to deduce sensible weather parameters that affect navy operations. Applications of these technologies to environmental satellite image analysis provide new opportunities for their use, not only in the operational community, but in training and research as well.
The widespread and in many countries unprecedented use of non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic has highlighted the need for mathematical models which can estimate the impact of these measures while accounting for the highly heterogeneous risk profile of COVID-19. Models accounting either for age/risk structure or the household structure necessary to explicitly model many NPIs are commonly used in infectious disease modelling, but models incorporating both levels of structure present substantial computational and mathematical challenges due to their high dimensionality. Here we present a modelling framework for the spread of an epidemic including explicit representation of age/risk structure and household structure. Our model is formulated in terms of tractable systems of ordinary differential equations for which we provide an open-source Python implementation. Such tractability leads to significant benefits for model calibration, exhaustive evaluation of possible parameter values, and interpretability of results. We demonstrate the flexibility of our model through four policy case studies, where we quantify the likely benefits of the following measures which were either considered or implemented in the UK during the current COVID-19 pandemic: control of within-and between-household mixing through NPIs; formation of support bubbles during lockdown periods; out-of-household isolation (OOHI); and temporary relaxation of NPIs during holiday periods. Our ordinary differential equation formulation and associated analysis demonstrate that multiple dimensions of risk stratification and social structure can be incorporated into infectious disease models without sacrificing mathematical tractability. This model and its software implementation expand the range of tools available to infectious disease policy analysts.
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