Determining arterial mechanical properties is important for understanding the work done by the heart and how it changes with cardiovascular disease. Ex vivo tests are necessary to apply various loads to the artery and obtain data to model and predict the behavior under any load. Most ex vivo tests are performed within 24 hours of dissection, so the tissue is still “alive”. For large elastic arteries, however, the passive mechanical behavior is attributed mostly to the very stable proteins, elastin and collagen. If the testing equipment fails, is in use, or is located at another facility, it would be useful to store the vessels and postpone the tests until the equipment is available. The goal of this study is to determine the effects of storage time on the mechanical behavior of the common carotid artery from adult mice. Each artery was tested after storage for 1–28 days in physiologic saline at 4°C. There were no significant effects of storage time on the arterial diameter or force at each pressure, but there were significant effects on the stretch ratio and stress at each pressure. The significant effects on the stretch ratio and stress were due to decreases in the unloaded dimensions with storage time, when measured from cut arterial rings. When the unloaded dimensions were measured instead from histology sections, there were no significant changes with storage time. We conclude that histology sections yield a more consistent measurement of the unloaded dimensions and that there are no significant changes in the mechanical behavior of mouse carotid artery with storage up to 28 days.
Despite recent progress, Malawi continues to perform poorly on key health indicators such as child mortality and life expectancy. These problems are exacerbated by a severe lack of access to health care. Health Surveillance Assistants (HSAs) help bridge this gap by providing community-level access to basic health care services. However, the success of these HSAs is limited by a lack of supplies and long distances between HSAs and patients. To address this issue, we used large-scale weighted p-median and capacitated facility location problems to create a scalable, three-tiered plan for optimal allocation of HSAs, HSA designated medical backpacks, and backpack resupply centers. Our analysis uses real data on the location and characteristics of hospitals, health centers, and the general population. In addition to offering specific recommendations for HSA, backpack, and resupply center locations, it provides general insights into the scope of the proposed HSA backpack program scale-up. In particular, it demonstrates the importance of local health centers to the resupply network. The proposed assignments are robust to changes in the underlying population structure, and could significantly improve access to medical supplies for both HSAs and patients.
Emergency medical services (EMS) provide life-saving care and hospital transport to patients with severe trauma or medical conditions. Severe weather events, such as snow events, may lead to adverse patient outcomes by increasing call volumes and service times. Adequate staffing levels during such weather events are critical for ensuring that patients receive timely care. To determine staffing levels that depend on weather, we propose a model that uses a discrete event simulation of a reliability model to identify minimum staffing levels that provide timely patient care, with regression used to provide the input parameters. The system is said to be reliable if there is a high degree of confidence that ambulances can immediately respond to a given proportion of patients (e.g., 99 %). Four weather scenarios capture varying levels of snow falling and snow on the ground. An innovative feature of our approach is that we evaluate the mitigating effects of different extrinsic response policies and intrinsic system adaptation. The models use data from Hanover County, Virginia to quantify how snow reduces EMS system reliability and necessitates increasing staffing levels. The model and its analysis can assist in EMS preparedness by providing a methodology to adjust staffing levels during weather events. A key observation is that when it is snowing, intrinsic system adaptation has similar effects on system reliability as one additional ambulance.
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