Developing policy options for SARS and SARS-like diseases - a Delphi study

Main Factors Affecting the Readiness and Responsiveness of Healthcare Systems during Epidemic Crises: A Scoping Review on Cases of SARS, MERS, and COVID-19

Background:

Given the significance of the preparedness and responsiveness of healthcare systems in relation to epidemics, this study aimed to determine their influencing factors during epidemic crises with a view to utilizing the findings in the battle against the coronavirus disease 2019 (COVID-19) outbreak.

Methods:

This scoping study was conducted in 2020 via the Arksey and O’Malley approach. A systematic search was conducted on five online databases from January 2000 to June 15, 2020. Initially, 1926 English articles were retrieved based on their abstracts. After the screening process, 60 articles were considered for the final analysis. Data were charted by applying Microsoft Office Excel 2013 and were synthesized via thematic analysis.

Results:

Five main factors have affected the responsiveness and preparedness of countries during the epidemics of severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and COVID-19: community-related interventions, managerial interventions, socioeconomic factors, the readiness of hospitals and health centers, and environmental factors. These themes are associated with 38 related sub-themes. The thematic framework shows that interactions between these five determinantes can affect the preparedness and responsiveness of healthcare systems during pandemics/epidemics.

Conclusion:

According to the results, healthcare systems need to pay attention to their internal capacities, managerial interventions, and health centers to overcome the current pandemic. They should also consider such external factors as socioeconomic and environmental determinants that can affect their potential preparedness against pandemic/epidemic crises. Community-related interventions such as improvement of the community health literacy, teamwork, and social responsibility can enhance the readiness of healthcare systems against the COVID-19 outbreak.

Effects of heterogeneous self-protection awareness on resource-epidemic coevolution dynamics

Recent studies have demonstrated that the allocation of individual resources has a significant influence on the dynamics of epidemic spreading. In the real scenario, individuals have a different level of awareness for self-protection when facing the outbreak of an epidemic. To investigate the effects of the heterogeneous self-awareness distribution on the epidemic dynamics, we propose a resource-epidemic coevolution model in this paper. We first study the effects of the heterogeneous distributions of node degree and self-awareness on the epidemic dynamics on artificial networks. Through extensive simulations, we find that the heterogeneity of self-awareness distribution suppresses the outbreak of an epidemic, and the heterogeneity of degree distribution enhances the epidemic spreading. Next, we study how the correlation between node degree and self-awareness affects the epidemic dynamics. The results reveal that when the correlation is positive, the heterogeneity of self-awareness restrains the epidemic spreading. While, when there is a significant negative correlation, strong heterogeneous or strong homogeneous distribution of the self-awareness is not conducive for disease suppression. We find an optimal heterogeneity of self-awareness, at which the disease can be suppressed to the most extent. Further research shows that the epidemic threshold increases monotonously when the correlation changes from most negative to most positive, and a critical value of the correlation coefficient is found. When the coefficient is below the critical value, an optimal heterogeneity of self-awareness exists; otherwise, the epidemic threshold decreases monotonously with the decline of the self-awareness heterogeneity. At last, we verify the results on four typical real-world networks and find that the results on the real-world networks are consistent with those on the artificial network.

The cognitive mediation model: factors influencing public knowledge of the H1N1 pandemic and intention to take precautionary behaviors

This study uses the cognitive mediation model as the theoretical framework to examine the influence of motivations, communication, and news elaboration on public knowledge of the H1N1 pandemic and the intention to take precautionary behaviors in Singapore. Using a nationally representative random digit dialing telephone survey of 1,055 adult Singaporeans, the authors' results show that the cognitive mediation model can be applied to health contexts, in which motivations (surveillance gratification, guidance, and need for cognition) were positively associated with news attention, elaboration, and interpersonal communication. News attention, elaboration, and interpersonal communication in turn positively influence public knowledge about the H1N1 influenza. In addition, results show that the motivations have significant indirect effects on behavioral intentions, as partially mediated by communication (media attention and interpersonal communication), elaboration, and knowledge. The authors conclude that the cognitive mediation model can be extended to behavioral outcomes, above and beyond knowledge. Implications for theory and practice for health communication were discussed.

Use of a structured panel process to define quality metrics for antimicrobial stewardship programs

INTRODUCTION

Antimicrobial stewardship programs are being implemented in health care to reduce inappropriate antimicrobial use, adverse events, Clostridium difficile infection, and antimicrobial resistance. There is no standardized approach to evaluate the impact of these programs.

OBJECTIVE

To use a structured panel process to define quality improvement metrics for evaluating antimicrobial stewardship programs in hospital settings that also have the potential to be used as part of public reporting efforts.

DESIGN

A multiphase modified Delphi technique.

SETTING

Paper-based survey supplemented with a 1-day consensus meeting.

PARTICIPANTS

A 10-member expert panel from Canada and the United States was assembled to evaluate indicators for relevance, effectiveness, and the potential to aid quality improvement efforts.

RESULTS

There were a total of 5 final metrics selected by the panel: (1) days of therapy per 1000 patient-days; (2) number of patients with specific organisms that are drug resistant; (3) mortality related to antimicrobial-resistant organisms; (4) conservable days of therapy among patients with community-acquired pneumonia (CAP), skin and soft-tissue infections (SSTI), or sepsis and bloodstream infections (BSI); and (5) unplanned hospital readmission within 30 days after discharge from the hospital in which the most responsible diagnosis was one of CAP, SSTI, sepsis or BSI. The first and second indicators were also identified as useful for accountability purposes, such as public reporting.

CONCLUSION

We have successfully identified 2 measures for public reporting purposes and 5 measures that can be used internally in healthcare settings as quality indicators. These indicators can be implemented across diverse healthcare systems to enable ongoing evaluation of antimicrobial stewardship programs and complement efforts for improved patient safety.

Where there is no evidence: use of expert consensus methods to fill the evidence gap in low-income countries and cultural minorities

BACKGROUND

In both developing countries and in relation to cultural minorities there have been calls to scale up mental health services and for evidence-informed policy and practice.

EVIDENCE BASED MEDICINE

The evidence based medicine movement has had a major influence in improving practice. However, implementation of this approach has some major difficulties. One that has been neglected is the situation where there is no relevant evidence. This situation is more likely to occur for healthcare decisions in developing countries or for cultural minorities within developed countries, because resources do not exist for expensive research studies.

CONSENSUS METHODS

Consensus methods, such as the Delphi process, can be useful in providing an evidence base in situations where there is insufficient evidence. They provide a way of systematically tapping the expertise of people working in the area and give evidence that is readily applicable for a particular country and culture. Although consensus methods are often thought of as low in the hierarchy of evidence, consensus is central to the scientific process. We present four examples where the Delphi method was used to assess expert consensus in situations where no other evidence existed: estimating the prevalence of dementia in developing countries, developing mental health first aid guidelines in Asian countries, mental health first aid guidelines for Australian Aboriginal people, and modification of the concept of 'recovery' for Australian immigrant communities.

CONCLUSION

Consensus methods can provide a basis for decision-making and considered action when there is no evidence or when there are doubts about the applicability of evidence that has been generated from other populations or health system settings.