Risk assessment of vector-borne diseases for public health governance

• Published in: Public health (London) Vol. 128; no. 12; pp. 1049 - 1058
• Main Authors: Sedda, L, Morley, D.W, Braks, M.A.H, De Simone, L, Benz, D, Rogers, D.J
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Ltd 01-12-2014
• Subjects: Animals; Bayes Theorem; Communicable Diseases - transmission; Disease Vectors; Diseases; Government and politics; Health policy; Humans; Infectious Disease; Internal Medicine; Legislation; Models, Theoretical; Public health; Public Health Administration; Public Health governance; Risk; Risk assessment; Risk Assessment - methods; Risk governance; Statistical analysis; Threats; Vector-borne diseases; Vector-borne diseases; Public Health governance; Statistical analysis; Risk governance; Risk assessment
• ISSN: 0033-3506; 1476-5616
• DOI: 10.1016/j.puhe.2014.08.018

Abstract Objectives In the context of public health, risk governance (or risk analysis) is a framework for the assessment and subsequent management and/or control of the danger posed by an identified disease threat. Generic frameworks in which to carry out risk assessment have been developed by various agencies. These include monitoring, data collection, statistical analysis and dissemination. Due to the inherent complexity of disease systems, however, the generic approach must be modified for individual, disease-specific risk assessment frameworks. Study design The analysis was based on the review of the current risk assessments of vector-borne diseases adopted by the main Public Health organisations (OIE, WHO, ECDC, FAO, CDC etc…). Methods Literature, legislation and statistical assessment of the risk analysis frameworks. Results This review outlines the need for the development of a general public health risk assessment method for vector-borne diseases, in order to guarantee that sufficient information is gathered to apply robust models of risk assessment. Stochastic (especially spatial) methods, often in Bayesian frameworks are now gaining prominence in standard risk assessment procedures because of their ability to assess accurately model uncertainties. Conclusions Risk assessment needs to be addressed quantitatively wherever possible, and submitted with its quality assessment in order to enable successful public health measures to be adopted. In terms of current practice, often a series of different models and analyses are applied to the same problem, with results and outcomes that are difficult to compare because of the unknown model and data uncertainties. Therefore, the risk assessment areas in need of further research are identified in this article.