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Title: A meta-analysis of the association between gender and protective behaviors in response to respiratory epidemics

Respiratory infectious disease epidemics and pandemics are recurring events that levy a high cost on individuals and society. The health-protective behavioral response of the public plays an important role in limiting respiratory infectious disease spread. Health-protective behaviors take several forms. Behaviors can be categorized as pharmaceutical (e.g., vaccination uptake, antiviral use) or non-pharmaceutical (e.g., hand washing, face mask use, avoidance of public transport). Due to the limitations of pharmaceutical interventions during respiratory epidemics and pandemics, public health campaigns aimed at limiting disease spread often emphasize both non-pharmaceutical and pharmaceutical behavioral interventions. Understanding the determinants of the public’s behavioral response is crucial for devising public health campaigns, providing information to parametrize mathematical models, and ultimately limiting disease spread. While other reviews have qualitatively analyzed the body of work on demographic determinants of health-protective behavior, this meta-analysis quantitatively combines the results from 85 publications to determine the global relationship between gender and health-protective behavioral response. The results show that women in the general population are about 50% more likely than men to adopt/practice non-pharmaceutical behaviors. Conversely, men in the general population are marginally (about 12%) more likely than women to adopt/practice pharmaceutical behaviors. It is possible that factors other than pharmaceutical/non-pharmaceutical statusmore » not included in this analysis act as moderators of this relationship. We find these results suggest an inherent difference in how men and women respond to epidemic and pandemic respiratory infectious diseases. In conclusion, this information can be used to target specific groups when developing non-pharmaceutical public health campaigns and to parameterize epidemic models incorporating demographic information.« less
Authors:
ORCiD logo [1] ;  [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Analytics, Intelligence and Technology Division
Publication Date:
Report Number(s):
LA-UR-16-20307; LA-UR-16-25594
Journal ID: ISSN 1932-6203
Grant/Contract Number:
AC52-06NA25396; U01-GM097658-01
Type:
Accepted Manuscript
Journal Name:
PLoS ONE
Additional Journal Information:
Journal Volume: 11; Journal Issue: 10; Journal ID: ISSN 1932-6203
Publisher:
Public Library of Science
Research Org:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org:
USDOE; National Institutes of Health (NIH)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 97 MATHEMATICS AND COMPUTING; Information Science; Mathematics; mathematics; behavior; behavioral and social aspects of health; demography; SARS; meta-analysis; database searching; infectious disease epidemiology; vaccination and immunization
OSTI Identifier:
1338744
Alternate Identifier(s):
OSTI ID: 1338780