Mapping the likelihood of introduction and spread of HPAI in Africa and Indonesia using Multicriteria Decision Modelling

• Main Authors: Stevens, Kim, de Glanville, Will, Costard, Solenne, Métras, Raphaëlle, Theuri, Wachira, Kruska, Russ, Randolph, Thomas F., Grace, Delia, Hendrickx, Saskia, Pfeiffer, Dirk
• Format: Manuscript
• Language: English
• Published: International Food Policy Research Institute (IFPRI); International Livestock Research Institute (ILRI); Royal Veterinary College (RVC) 2008
• Subjects: AFRICA SOUTH OF SAHARA; ETHIOPIA; GHANA; INDONESIA; KENYA; NIGERIA; avian flu; avian influenza; developing countries; disease; health risks; vulnerability analysis mapping; Avian flu
• Online Access: http://www.ifpri.org/publication/mapping-likelihood-introduction-and-spread-hpai-africa-and-indonesia-using-multicriteria; http://ebrary.ifpri.org/cdm/ref/collection/p15738coll2/id/25826

Spatial analysis of the distribution of disease risk and its visual presentation through risk maps can be used to inform the design of animal disease surveillance resulting in more cost-effective strategies. It is suitable for application in the context of HPAI H5N1 in Africa and Indonesia where the disease has already been introduced and is endemic in some areas.; Two main approaches can be used to produce risk maps:; A data-driven approach, which uses actual disease data to identify risk factors that allow the absolute risk of disease occurrence in an area to be determined;; A knowledge-driven approach, which uses knowledge about the epidemiology of the disease to identify areas at higher or lower risk of disease occurrence relative to the surrounding areas.; Both approaches are based on available evidence. However, when empirical data about the distribution of the disease are not readily available or when data are only available on some aspects of the epidemiology of a multi-factorial disease, knowledge-driven approaches can be used to determine those areas in which a specific disease is most likely to occur using models such as multicriteria decision modelling (MCDM) (Clements et al. 2006, Pfeiffer et al. 2008).; In contrast to data-driven modelling, MCDM does not generate estimates of absolute risk. Instead, MCDM generates maps that identify areas with a higher or lower likelihood of an event of interest occurring relative to surrounding areas on the same map. A study described in more detail in EDRS-AIA risk mapping documents (2009) was conducted using an MCDM approach to describe the spatial variation in the likelihood of: introduction and spread of highly pathogenic avian influenza virus HPAI H5N1 in Africa, and spread of HPAI H5N1 in Indonesia.; This brief summarizes the methodology used to produce the maps for continental Africa and Indonesia, and the findings. In addition to the three maps in this brief, maps for other African countries were produced and are presented in the report, Mapping the ...