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Centre for Agriculture and Biosciences International
Country: BurundiOrganization: Centre for Agriculture and Biosciences InternationalClosing date: 11 Nov 2026BackgroundEffective pest surveillance, diagnosis, risk assessment, phytosanitary decision-making and pest management depend on the availability of reliable, timely and accessible pest-related data. Such data may include information on pest occurrence and distribution, pest identification and diagnosis, crop and host associations, disease incidence, pest outbreaks, surveillance activities, pest risk assessments, phytosanitary measures and pest management interventions.In Burundi, pest-related information is generated and managed by several institutions, including the Institut des Sciences Agronomiques du Burundi (ISABU), the Direction de la Protection des Végétaux (DPV) and the Ministère de l'Environnement, de l'Agriculture et de l'Élevage (MINEAGRIE). These institutions have complementary mandates and may maintain data in different formats, systems and locations.The absence of a consolidated understanding of existing pest-related datasets, data flows, management practices and institutional responsibilities can result in data gaps, duplication, parallel data collection, inconsistent terminology and difficulties in accessing or integrating information. These challenges can limit the effective use of existing evidence for pest surveillance, early warning, diagnostics, phytosanitary decision-making, research and agricultural policy.This activity will therefore undertake a streamlined data audit across ISABU, DPV and MINEAGRIE. The audit will focus on identifying what pest-related data and information exist, where they are held, how they are generated and managed, who is responsible for them, how they are shared and used, and where important gaps, overlaps or interoperability challenges occur.The exercise is intended to provide a practical evidence base to strengthen coordination and develop a more coherent approach to pest-related data management and sharing in Burundi.PurposeThe purpose of the activity is to establish a concise institutional overview of pest-related data assets, management practices and data flows across ISABU, DPV and MINEAGRIE, and to identify priority data gaps, overlaps, duplication and opportunities for improved coordination and interoperability.Specific ObjectivesThe audit will aim to:Identify and catalogue key pest-related information generated, maintained or used by ISABU, DPV and MINEAGRIE.Assess the scope and characteristics of existing datasets, including data types, coverage, spatial and temporal dimensions, formats, frequency of updating and intended uses.Map institutional data flows and responsibilities from data generation and collection through validation, storage, analysis, sharing and use.Identify priority information gaps and overlaps, including duplication of data collection, parallel databases or records, missing data elements and areas where institutional mandates or data responsibilities intersect.Assess key data-management and interoperability constraints, including differences in terminology, coding systems, data formats, identifiers, metadata and mechanisms for data exchange.Identify opportunities for harmonisation and improved data sharing among the three institutions.Develop practical recommendations and priority actions to strengthen pest-related data management and support evidence-based pest surveillance and phytosanitary decision-making.Scope of the AuditThe audit will focus specifically on a variety of information sources relevant to plant health and agricultural production. It will not constitute a comprehensive audit of the information-management systems of the three institutions. You can refer to Requests for Proposals - CABI.org for the detailed ToR.How to applyInterested and qualified consultant should submit their technical and financial proposal (In USD) to the email tendersafrica@cabi.org; on or before 9th November 2026. Questions related to this request for proposal should be addressed to the same email.
Provenance
| Field | How we know | State | Confidence |
|---|---|---|---|
| Publication date | Official API or feed | Data quality: Source-backed | 100 |
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