A Quantitative and Novel Approach to the Prioritization of Zoonotic Diseases in North America: A Public Perspective

Abstract

BackgroundZoonoses account for over half of all communicable diseases causing illness in humans. As there are limited resources available for the control and prevention of zoonotic diseases, a framework for their prioritization is necessary to ensure resources are directed into those of highest importance. Although zoonotic outbreaks are a significant burden of disease in North America, the systematic prioritization of zoonoses in this region has not been previously evaluated.Methodology/Principal FindingsThis study describes the novel use of a well-established quantitative method, conjoint analysis (CA), to identify the relative importance of 21 key characteristics of zoonotic diseases that can be used for their prioritization in Canada and the US. Relative importance weights from the CA were used to develop a point-scoring system to derive a recommended list of zoonoses for prioritization in Canada and the US. Over 1,500 participants from the general public were recruited to complete the online survey (761 from Canada and 778 from the US). Hierarchical Bayes models were fitted to the survey data to derive CA-weighted scores. Scores were applied to 62 zoonotic diseases of public health importance in Canada and the US to rank diseases in order of priority.Conclusions/SignificanceThis was the first study to describe a systematic and quantitative approach to the prioritization of zoonoses in North America involving public participants. We found individuals with no prior knowledge or experience in prioritizing zoonoses were capable of producing meaningful results using CA as a novel quantitative approach to prioritization. More similarities than differences were observed between countries suggesting general agreement in disease prioritization between Canadians and Americans. We demonstrate CA as a potential tool for the prioritization of zoonoses; other prioritization exercises may also consider this approach.

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]. …”

“…Ng et al [28][29][30] Questionnaire studies 62 diseases ranked 21 criteria used Criteria weighted using conjoint analysis 4,161 participants Used two criteria of likelihood and impact. Assessment against content validity domain was based on the facets listed as included in the 'supportive information'; did not include many of those criteria.…”

“…Ng et al [28][29][30] Questionnaire Green Green Green Green Implementation issues were not specifically discussed, but practical considerations were discussed which would assist implementation. Most of the key communicable disease facets were met.…”

“…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.…”