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When Hurricane Harvey landed along the Texas coast on August 25, 2017, it caused massive flooding and damage and displaced tens of thousands of residents of Harris County, Texas. Between August 29 and September 23, Harris County, along with community partners, operated a megashelter at NRG Center, which housed 3365 residents at its peak. Harris County Public Health conducted comprehensive public health surveillance and response at NRG, which comprised disease identification through daily medical record reviews, nightly “cot-to-cot” resident health surveys, and epidemiological consultations; messaging and communications; and implementation of control measures including stringent isolation and hygiene practices, vaccinations, and treatment. Despite the lengthy operation at the densely populated shelter, an early seasonal influenza A (H3) outbreak of 20 cases was quickly identified and confined. Influenza outbreaks in large evacuation shelters after a disaster pose a significant threat to populations already experiencing severe stressors. A holistic surveillance and response model, which consists of coordinated partnerships with onsite agencies, in-time epidemiological consultations, predesigned survey tools, trained staff, enhanced isolation and hygiene practices, and sufficient vaccines, is essential for effective disease identification and control. The lessons learned and successes achieved from this outbreak may serve for future disaster response settings. (Disaster Med Public Health Preparedness. 2019;13:97-101)
The purpose of this study was to determine the economic risk efficiency of implementing a boll weevil (Anthonomus grandis [Boheman]) eradication (BWE) program in cotton (Gossypium hirsutum L.) producing regions of the Mississippi Delta. Alternative producer pest management practices and program cost sharing were incorporated into a biophysical cotton simulation model. Participation in a BWE program along with strict adherence to Cooperative Extension Service pest management guidelines proved to be the risk efficient practice.
The importance of timeliness is investigated in the selection of machinery complements for double-crop wheat and soybean production in the southeastern coastal plain. An intertemporal stochastic simulation model was developed to generate probability distributions that were evaluated with stochastic dominance analysis. This research investigated the importance of intertemporal production linkages and inadequate soil moisture on machinery selection. Failure to include these dimensions can result in erroneous machinery choices.
A conceptual link among mean-variance (EV), stochastic dominance (SD), mean-risk (ET), and Gini mean difference (EG) is established for determining risk efficient decision sets. The theoretical relations among the various efficiency criteria are then empirically demonstrated with a soybean and wheat double-crop simulation model. Empirical results associated with extended Gini mean difference (EEG) and extended mean-absolute Gini (EEΓ) for risk analysis are encouraging.
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