Japanese
Albanian
Arabic
Armenian
Azerbaijani
Belarusian
Bengali
Bosnian
Catalan
Czech
Danish
Deutsch
Dutch
English
Estonian
Finnish
Français
Greek
Haitian Creole
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Irish
Italian
Japanese
Korean
Latvian
Lithuanian
Macedonian
Mongolian
Norwegian
Persian
Polish
Portuguese
Romanian
Russian
Serbian
Slovak
Slovenian
Spanish
Swahili
Swedish
Turkish
Ukrainian
Vietnamese
Български
中文(简体)
中文(繁體)
Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi 2011-May

[Comparison on the different thresholds on the 'moving percentile method' for outbreak detection].

登録ユーザーのみが記事を翻訳できます
ログインサインアップ
リンクがクリップボードに保存されます
Qiao Sun
Sheng-Jie Lai
Zhong-Jie Li
Ya-Jia Lan
Hong-Long Zhang
Dan Zhao
Lian-Mei Jin
Wei-Zhong Yang

キーワード

概要

OBJECTIVE

To compare the different thresholds of 'moving percentile method' for outbreak detection in the China Infectious Diseases Automated-alert and Response System (CIDARS).

METHODS

The thresholds of P(50), P(60), P(70), P(80) and P(90) were respectively adopted as the candidates of early warning thresholds on the moving percentile method. Aberration was detected through the reported cases of 19 notifiable infectious diseases nationwide from July 1, 2008 to June 30, 2010. Number of outbreaks and time to detection were recorded and the amount of signals acted as the indicators for determining the optimal threshold of moving percentile method in CIDARS.

RESULTS

The optimal threshold for bacillary and amebic dysentery was P(50). For non-cholera infectious diarrhea, dysentery, typhoid and paratyphoid, and epidemic mumps, it was P(60). As for hepatitis A, influenza and rubella, the threshold was P(70), but for epidemic encephalitis B it was P(80). For the following diseases as scarlet fever, typhoid and paratyphoid, hepatitis E, acute hemorrhagic conjunctivitis, malaria, epidemic hemorrhagic fever, meningococcal meningitis, leptospirosis, dengue fever, epidemic endemic typhus, hepatitis C and measles, it was P(90). When adopting the adjusted optimal threshold for 19 infectious diseases respectively, 64 840 (12.20%) signals had a decrease, comparing to the adoption of the former defaulted threshold (P(50)) during the 2 years. However, it did not reduce the number of outbreaks being detected as well as the time to detection, in the two year period.

CONCLUSIONS

The optimal thresholds of moving percentile method for different kinds of diseases were different. Adoption of the right optimal threshold for a specific disease could further optimize the performance of outbreak detection for CIDARS.

Facebookページに参加する

科学に裏打ちされた最も完全な薬草データベース

  • 55の言語で動作します
  • 科学に裏打ちされたハーブ療法
  • 画像によるハーブの認識
  • インタラクティブGPSマップ-場所にハーブをタグ付け(近日公開)
  • 検索に関連する科学出版物を読む
  • それらの効果によって薬草を検索する
  • あなたの興味を整理し、ニュース研究、臨床試験、特許について最新情報を入手してください

症状や病気を入力し、役立つ可能性のあるハーブについて読み、ハーブを入力して、それが使用されている病気や症状を確認します。
*すべての情報は公開された科学的研究に基づいています

Google Play badgeApp Store badge