BackgroundSevere fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease that was recently identified in China, South Korea and Japan. The objective of the study was to evaluate the epidemiologic and clinical characteristics of SFTS in South Korea.Methods/Principal FindingsSFTS is a reportable disease in South Korea. We included all SFTS cases reported to the Korea Centers for Disease Control and Prevention (KCDC) from January 2013 to December 2015. Clinical information was gathered by reviewing medical records, and epidemiologic characteristics were analyzed using both KCDC surveillance data and patient medical records. Risk factors for mortality in patients with SFTS were assessed. A total of 172 SFTS cases were reported during the study period. SFTS occurred throughout the country, except in urban areas. Hilly areas in the eastern and southeastern regions and Jeju island (incidence, 1.26 cases /105 person-years) were the main endemic areas. The yearly incidence increased from 36 cases in 2013 to 81 cases in 2015. Most cases occurred from May to October. The overall case fatality ratio was 32.6%. The clinical progression was similar to the 3 phases reported in China: fever, multi-organ dysfunction, and convalescence. Confusion, elevated C-reactive protein, and prolonged activated partial thromboplastin times were associated with mortality in patients with SFTS. Two outbreaks of nosocomial SFTS transmission were observed.ConclusionsSFTS is an endemic disease in South Korea, with a nationwide distribution and a high case-fatality ratio. Confusion, elevated levels of C-reactive protein, and prolonged activated partial thromboplastin times were associated with mortality in patients with SFTS.
BackgroundThis study was designed to investigate the clinical significance of hypoalbuminemia as a marker of severity and mortality in patients with Scrub typhus.MethodsThe patients with scrub typhus were divided into two groups based on the serum albumin levels; Group I (serum albumin <3.0 g/dL) and Group II (serum albumin ≥3.0 g/dL). The outcome of patients with hypoalbuminemia was compared with that of normoalbuminemia.ResultsOf the total 246 patients who underwent the study, 84 patients (34.1%) were categorized as Group I and 162 patients were (65.9%) as Group II. Group I showed significantly higher incidence of confusion (24.6% vs. 5.3%, p < 0.001), pulmonary edema (15.8% vs. 3.2%, p = 0.002), pleural effusion (22.8% vs. 11.1%, p = 0.03), arrhythmia (12.3% vs. 2.6%, p = 0.008) and non-oliguric acute renal failure (40.4% vs. 11.1%, p < 0.001) compared to group II. Hypoalbuminemic group had a higher APACHE II score (11.37 ± 5.0 vs. 6.94 ± 4.2, p < 0.001), longer hospital stay (19.9 ± 42.1 days vs 7.5 ± 13.8 days, p = 0.012), and higher hospital cost compared to Group II.ConclusionsThis study showed hypoalbuminemia in scrub typhus was closely related to the frequency of various complication, longer hospital stay, consequently the higher medical cost, necessitating more efficient management of patients, including medical resources.
This paper proposes an agricultural environment monitoring server system for monitoring information concerning an outdoors agricultural production environment utilizing Wireless Sensor Network (WSN) technology. The proposed agricultural environment monitoring server system collects environmental and soil information on the outdoors through WSN-based environmental and soil sensors, collects image information through CCTVs, and collects location information using GPS modules. This collected information is converted into a database through the agricultural environment monitoring server consisting of a sensor manager, which manages information collected from the WSN sensors, an image information manager, which manages image information collected from CCTVs, and a GPS manager, which processes location information of the agricultural environment monitoring server system, and provides it to producers. In addition, a solar cell-based power supply is implemented for the server system so that it could be used in agricultural environments with insufficient power infrastructure. This agricultural environment monitoring server system could even monitor the environmental information on the outdoors remotely, and it could be expected that the use of such a system could contribute to increasing crop yields and improving quality in the agricultural field by supporting the decision making of crop producers through analysis of the collected information.
There has been much research and various attempts to apply new IoT technology to agricultural areas. However, IoT for the agriculture should be considered differently against the same areas such as industrial, logistics. This paper presents the IoT-based agricultural production system for stabilizing supply and demand of agricultural products while developing the environment sensors and prediction system for the growth and production amount of crops by gathering its environmental information. Currently, the demand by consumption of agricultural products could be predicted quantitatively, however, the variation of harvest and production by the change of farm's cultivated area, weather change, disease and insect damage etc. could not be predicted, so that the supply and demand of agricultural products has not been controlled properly.To overcome it, this paper designed the IoT-based monitoring system to analyze crop environment, and the method to improve the efficiency of decision making by analyzing harvest statistics. Therefore, this paper developed the decision support system to forecast agricultural production using IoT sensors. This system was also a unified system that supports the processes sowing seeds through selling agricultural products to consumers.The IoT-based agricultural production system through correlation analysis between the crop statistical information and agricultural environment information has enhanced the ability of farmers, researchers, and government officials to analyze current conditions and predict future harvest. Additionally, agricultural products quality can be improved because farmers observe whole cycle from seeding to selling using this IoT-based decision support system.
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