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. 2024 Jun 25;19(6):e0295742.
doi: 10.1371/journal.pone.0295742. eCollection 2024.

Parallel multi-criteria decision analysis for sub-national prioritization of zoonoses and animal diseases in Africa: The case of Cameroon

Serge Eugene Mpouam  1 , Dalida Ikoum  1   2 , Limane Hadja  1 , Jean Pierre Kilekoung Mingoas  1 , Claude Saegerman  3
Affiliations

Parallel multi-criteria decision analysis for sub-national prioritization of zoonoses and animal diseases in Africa: The case of Cameroon

Serge Eugene Mpouam et al. PLoS One. .

Abstract

The use of multi-criteria decision analysis (MCDA) for disease prioritization at the sub-national level in sub-Sahara Africa (SSA) is rare. In this research, we contextualized MCDA for parallel prioritization of endemic zoonoses and animal diseases in The Adamawa and North regions of Cameroon. MCDA was associated to categorical principal component analysis (CATPCA), and two-step cluster analysis. Six and seven domains made of 17 and 19 criteria (out of 70) respectively were selected by CATPCA for the prioritization of zoonoses and animal diseases, respectively. The most influencing domains were "public health" for zoonoses and "control and prevention" for animal diseases. Twenty-seven zoonoses and 40 animal diseases were ranked and grouped in three clusters. Sensitivity analysis resulted in high correlation between complete models and reduced models showing the robustness of the simplification processes. The tool used in this study can be applied to prioritize endemic zoonoses and transboundary animal diseases in SSA at the sub-national level and upscaled at the national and regional levels. The relevance of MCDA is high because of its contextualization process and participatory nature enabling better operationalization of disease prioritization outcomes in the context of African countries or other low and middle-income countries.

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Conflict of interest statement

No.

Figures

Fig 1
Fig 1. Systematic process for selecting the zoonoses and animal diseases.
*farm animals: Cattle, sheep, goats, swine, and poultry; ** AEZ: Agro-ecological zone.
Fig 2
Fig 2. Mean score and standard deviation of zoonoses and animal diseases prioritized.
Mean scores and standard deviations are mentioned. For each prioritization process, three clusters marked by brackets were identified by two step cluster analysis for the prioritization of zoonoses (A) and animal diseases (B) respectively. For cluster, CZD: Cluster of zoonotic diseases; CAD: Cluster of animal diseases. 1: Very high importance, 2: High importance, 3: Moderate importance, 4: Low importance. ASF: African swine fever; BVD: Bovine viral disease; CBPP: Contagious bovine pleuropneumonia; CCPP: Contagious caprine pleuropneumonia; CSF: Classical swine fever; FMD: Foot and mouth disease; HPAI: High pathogenic avian influenza; IBD; infectious bursal disease, IBR: Infectious bovine rhinotracheitis, LPHAI: Low pathogenic avian influenza; PPR: Small ruminant plague.
Fig 3
Fig 3
Frequency of rank using spider webs: From 1 to 6 for zoonoses (A) and 1 to 7 for animal diseases (B). The line inside the spider web displays the relative performance (count) of each domain for the different ranks (represented by 1–7).
Fig 4
Fig 4. Sensitivity analysis for the five zoonoses (I) and five animal diseases (J) with highest mean scores.
The graph illustrates the trends upward or downward in the ranking. *Ranking changed by three positions or more. (A) Epidemiology and infectiology; (B) Control and prevention; (C) Economy and trade; (D) Public health; (E) Environment; (F) Livestock production system and (G) Society. FMD, foot-and- mouth disease; RVF, Rift Valley fever. Each reduced model derived from the complete model with the exclusion of one domain of criteria (i.e. A, B, C, D, E, F or G).
See this image and copyright information in PMC

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