The Use of Expert Opinion to Assess the Risk of Emergence or Re-Emergence of Infectious Diseases in Canada Associated with Climate Change

Abstract

Global climate change is predicted to lead to an increase in infectious disease outbreaks. Reliable surveillance for diseases that are most likely to emerge is required, and given limited resources, policy decision makers need rational methods with which to prioritise pathogen threats. Here expert opinion was collected to determine what criteria could be used to prioritise diseases according to the likelihood of emergence in response to climate change and according to their impact. We identified a total of 40 criteria that might be used for this purpose in the Canadian context. The opinion of 64 experts from academic, government and independent backgrounds was collected to determine the importance of the criteria. A weight was calculated for each criterion based on the expert opinion. The five that were considered most influential on disease emergence or impact were: potential economic impact, severity of disease in the general human population, human case fatality rate, the type of climate that the pathogen can tolerate and the current climatic conditions in Canada. There was effective consensus about the influence of some criteria among participants, while for others there was considerable variation. The specific climate criteria that were most likely to influence disease emergence were: an annual increase in temperature, an increase in summer temperature, an increase in summer precipitation and to a lesser extent an increase in winter temperature. These climate variables were considered to be most influential on vector-borne diseases and on food and water-borne diseases. Opinion about the influence of climate on air-borne diseases and diseases spread by direct/indirect contact were more variable. The impact of emerging diseases on the human population was deemed more important than the impact on animal populations.

Best practices in ranking communicable disease threats: a literature review, 2015

“…The studies used one of five methodologies to rank communicable disease risks: bibliometric index [33,34], the Delphi technique [35][36][37][38], Multi-Criteria Decision Analysis (MCDA) [31,32,[39][40][41], qualitative algorithms [42,43], and questionnaires [29][30][31]45 In general, risk-ranking exercises begin with identifying diseases to consider for prioritisation, formulating a list of criteria to assess diseases against, then weighting the criteria according to importance, and scoring diseases against the criteria to create a ranking based on the scores.…”

“…The qualitative Likert assessments, which are based upon scales that typically range from 'strongly disagree' to 'strongly agree', are represented using a red-amber-green 'traffic light rating system' (with red indicating a high risk of bias likely). Where multiple articles described the same risk-ranking exercise, articles were appraised and extracted as one study, but counted individually within the flowchart (Figure 1) [28][29][30][31][32]. …”

“…Framework of best practice for risk ranking exercises, for use across methodologies, literature review on best practices in ranking communicable disease threats, 2015 Cardoen et al [39] Multi-criteria decision analysis 51 diseases ranked 5 criteria used Criteria weighted using Las Vegas method 7 participants weighted criteria 35 participants scored diseases Scores of 0-4 points allocated to each disease (based on occurrence and severity) Cox et al [31,32] Multi-criteria decision analysis 9 diseases ranked 40 criteria used Criteria weighted using a qualitative Likert scale (based on likelihood or importance) 64 participants weighted criteria 47 participants scored diseases Likert scale used to score diseases Havelaar et al [40] Multi-criteria decision analysis 86 diseases ranked 7 criteria used Criteria weighted using relative ranking 29 participants Quantitative, scaled values used to score diseases Humblet et al [41] Multi-criteria decision analysis 100 diseases ranked 57 criteria (in 5 categories) 40 participants Criteria weighted using the Las Vegas method Co-efficients of 0-7 points assigned to each option Morgan et al [42] Qualitative algorithm 1 disease ranked (a worked example) 1 participant…”

“…The included studies often provided explanations for their choice of methodology in terms of overcoming or balancing the potential limitations of alternative methodologies, but rarely explained their choice of methods with regards to the specific objectives of their risk-ranking exercise. Five of the reviewed studies used a quantitative methodology [33][34][35]37,40,41], three used qualitative approaches [36,42,43], and six studies used semiquantitative, mixed methods [28][29][30][31][32]35,38,39,44]. Only four studies used either entirely qualitative or quantitative methods [33,34,42,43], however, these studies were considered by their authors to be most useful as part of a wider risk-ranking exercise rather than as a stand-alone methodology.…”

“…There are advantages and disadvantages to using quantitative or qualitative methods in different scenarios. For example, in areas where there is little evidence (and what does exist is of poor quality) it may be preferable to use semiquantitative methods (to make best use of the evidence available [39]) or qualitative methods (in recognition that the evidence is not of much help and uncertainty remains [31]). Qualitative data generally takes longer to collect and analyse than quantitative data, although it provides a richness and context to responses that quantitative data cannot.…”