Zika knowledge and prevention practices among U.S. travelers: a large cross-sectional survey study.

Zika knowledge and prevention practices among U.S. travelers: a large cross-sectional survey study.

Luetke, Maya;Omodior, Oghenekaro;Nelson, Erik J;
BMC public health 2019 Vol. 19 pp. 1217
237
luetke2019zikabmc

Abstract

The aim of this study was to investigate what factors predict knowledge about Zika transmission, symptomology, and treatment among U.S. travelers and, additionally, to evaluate how Zika knowledge influences the adoption of personal protective behaviors.Data were collected as part of a cross-sectional survey study using a probability-based internet panel of U.S. travelers in June 2017. We ran logistic regression models of factors predicting Zika knowledge (high vs. low) and of knowledge predicting adoption of personal protective measures.We found that traveling to a Zika endemic country and travelers' gender were both significantly predictive of higher Zika knowledge (odds ratio (OR): 1.48, 95% confidence interval (CI): 1.14-1.93 and OR: 1.44, 95% CI: 1.08-1.92), adjusting for age, race, education, income, and trip purpose. Additionally, among travelers to Zika endemic countries, individuals with higher Zika knowledge had significantly higher odds of engaging in preventive behaviors compared to those with lower knowledge. However, few travelers knew about the sexual transmission of Zika and adopted sexual prevention measures.Our findings suggest that there are gaps in knowledge about the risks and transmission of Zika and travelers with low knowledge are less likely to engage in the appropriate prevention methods. Significantly, few U.S. travelers have knowledge of the sexual transmission of Zika and, accordingly, there is less overall engagement with prevention measures for this transmission mechanism than for vector-borne transmission.

Citation

ID: 38106
Ref Key: luetke2019zikabmc
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
38106
Unique Identifier:
10.1186/s12889-019-7533-3
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