Protecting Vulnerable Populations From Pandemic Influenza in the United States: A Strategic Imperative

Hutchins, Sonja S.; Truman, Benedict I.; Merlin, Toby L.; Redd, Stephen C.

doi:10.2105/ajph.2009.164814

Cited by 59 publications

(57 citation statements)

References 22 publications

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“…Family members in need of special care (FNSC) are children, the elderly, those with disabilities, and those with chronic diseases. Respondents who live with people with these conditions have a higher risk perception concerning health [46][47][48]. Therefore, we assume that respondents with family members in need of special care have higher perceived risks.…”

Section: Conceptual Model and Hypothesesmentioning

confidence: 99%

Willingness to Self-Isolate When Facing a Pandemic Risk: Model, Empirical Test, and Policy Recommendations

Zhang

Wang

Zhu

et al. 2019

IJERPH

101

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Infected people are isolated to minimize the spread of pandemic diseases. Therefore, the factors related to self-isolation (SI) should not be neglected, and it is important to investigate the factors leading the infected (or possibly infected) people to choose to self-isolate. In this paper, we tried to show that the theory of planned behavior provides a useful conceptual framework for SI when facing a pandemic risk, and a regression method with Chinese provincial (Guangdong Province) data was applied to investigate how attitude (ATT), subjective norms (SN), and perceived behavioral control (PBC) influence SI when facing a pandemic emergency. The results and the robustness tests confirm that ATT, SN, and PBC have a significant positive influence on SI when facing a pandemic emergency. ATT plays the most important role, followed by SN and then PBC. Based on the factors of SI, we found, through theoretical and empirical analyses, at least three important aspects that local governments need to consider to encourage citizens to self-isolate when facing a pandemic.

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Section: Conceptual Model and Hypothesesmentioning

confidence: 99%

Willingness to Self-Isolate When Facing a Pandemic Risk: Model, Empirical Test, and Policy Recommendations

Zhang

Wang

Zhu

et al. 2019

IJERPH

101

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“…Interpretation and assimilation of information is determined by audience assessment of the ability of the messenger to listen and empathsize, as well as other indicators of trustworthiness (Garvin, 2001;Lupton, 1993). These models emphasize risk communication must address the specific needs of multiple populations, including the more vulnerable (Hutchins, Truman, Merlin, & Redd, 2009). …”

Section: Underpinning Theories In Risk Communicationmentioning

confidence: 99%

Reputation, Relationships, Risk Communication, and the Role of Trust in the Prevention and Control of Communicable Disease: A Review

Cairns

Andrade

MacDonald

2013

Journal of Health Communication

105

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Population-level compliance with health protective behavioral advice to prevent and control communicable disease is essential to optimal effectiveness. Multiple factors affect perceptions of trustworthiness, and trust in advice providers is a significant predeterminant of compliance. While competency in assessment and management of communicable disease risks is critical, communications competency may be equally important. Organizational reputation, quality of stakeholder relationships and risk information provision strategies are trust moderating factors, whose impact is strongly influenced by the content, timing and coordination of communications. This article synthesizes the findings of 2 literature reviews on trust moderating communications and communicable disease prevention and control. We find a substantial evidence base on risk communication, but limited research on other trust building communications. We note that awareness of good practice historically has been limited although interest and the availability of supporting resources is growing. Good practice and policy elements are identified: recognition that crisis and risk communications require different strategies; preemptive dialogue and planning; evidence-based approaches to media relations and messaging; and building credibility for information sources. Priority areas for future research include process and cost-effectiveness evaluation and the development of frameworks that integrate communication and biomedical disease control and prevention functions, conceptually and at scale.

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“…Furthermore, setting priority for vaccination by targeting the most susceptible (infants and elderly) [16,17] is key in the prevention of high morbidity and mortality due to influenza. Although there is no good evidence that influenza vaccine reduces mortality due to influenza in the elderly [18], the very young and the very old might be better protected by also vaccinating those who are more likely to be in contact with them thereby reducing the risk of exposure, infection and presentation of severe complications due to influenza [19,20] …”

Section: Discussionmentioning

confidence: 99%

Timely Prediction of Peak Seasonal Influenza Activity Estimation Using Sentinel Surveillance Data

Torner¹,

Soldevila²,

Martínez³

et al. 2012

PHR

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Influenza sentinel surveillance provides valuable information to help plan resources and preparedness. Study aim was to determine which age group could give timely prediction on onset of seasonal epidemic activity. Methods: Study period comprised influenza epidemic seasons 2006-2009. Incidence rates (IR) of influenza like illness (ILI), for 2 and 3 weeks prior to onset of epidemic activity by age group and peak epidemic activity weeks for general population were calculated. Rate Ratios (RR) between influenza virus positive samples (IV+) and ILI, between 2 and 3 weeks prior to epidemic ILI activity by age group and for peak activity period (PA) were obtained. Differences in rate proportions and their 95% confidence intervals were assessed by statistic z. Results: The highest RR between IV+ and ILI rates corresponded to 0-4y (0.34; 95% CI: 0.28-0.41), and lowest (0.26; 95%CI: 0.23-0.30) to 15-64y. Considering two and three weeks prior to epidemic activity onset related to overall population IRs during PA period, the only RR above 1 corresponded to 0-4y (1.38; 95%CI: 1.08,1.75)for two weeks and (1.29; 95%CI:1.04,1.6) for three weeks. Conclusion: High correspondence between ILI and IV+ was observed in 0-4y prior to other age groups; in this age group rates of ILI during two and three consecutive weeks prior to increase above threshold activity can be used to predict the onset of peak epidemic activity in a timely manner.

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Protecting Vulnerable Populations From Pandemic Influenza in the United States: A Strategic Imperative

Cited by 59 publications

References 22 publications

Willingness to Self-Isolate When Facing a Pandemic Risk: Model, Empirical Test, and Policy Recommendations

Willingness to Self-Isolate When Facing a Pandemic Risk: Model, Empirical Test, and Policy Recommendations

Reputation, Relationships, Risk Communication, and the Role of Trust in the Prevention and Control of Communicable Disease: A Review

Timely Prediction of Peak Seasonal Influenza Activity Estimation Using Sentinel Surveillance Data

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