aberration detection of pertussis from the mazandaran province, iran, from 2012 to 2018: application of discrete wavelet transform

aberration detection of pertussis from the mazandaran province, iran, from 2012 to 2018: application of discrete wavelet transform

;Yousef Alimohamadi;Seyed Mohsen Zahraei;Manoochehr Karami;Mehdi Yaseri;Mojtaba Lotfizad;Kourosh Holakouie-Naieni
journal of acute disease 2020 Vol. 9 pp. 114-120
312
alimohamadi2020journalaberration

Abstract

Objective: To define the level of alarm threshold for pertussis aberrations and to detect the aberrations of the reported suspected cases of pertussis from the Mazandaran province in the north of Iran. Methods: The included cases were composed of the suspected pertussis patients who came from Mazandaran province and registered in the Center for Disease Control and Prevention from 20 March 2012 to 20 March 2018. A discrete wavelet transform- based method was used to detect the aberrations. All analyses were performed using MATLAB Software version 2018a and Excel 2010. Results: A total of 1 162 cases were recruited in the study, including 545 (46.90%) males and 617 (53.10%) females, with median age of 1.47 (0.22-9.56) years. The median age of males was 1.18 (0.21-8.24) years, while that of females was 1.82 (0.21-10.75) years. Concerning the level of the alarm threshold, it was 1.28 case/d when k=2, while it was 1.34 case/d when k=3. The total detected aberration days were 123 d and 57 d by considering k=2 and 3, respectively. The most defined alarm threshold was related to spring (>2 cases/d) and summer (>1 case/d), respectively. Conclusions: The sensitivity of the surveillance system is subjected to a different time. Thus, determining the level of alarm threshold periodically using different methods is recommended.

Citation

ID: 130926
Ref Key: alimohamadi2020journalaberration
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
130926
Unique Identifier:
10.4103/2221-6189.283889
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet