Consultancy Service: Continental PPR Vaccination Analysis, Vaccine Demand Forecasting and ARIS Vaccination Data Standardization (INDIVIDUALS ONLY) | AU-IBAR

Commissioning institution	African Union Interafrican Bureau for Animal Resources (AU-IBAR), through the Pan-African PPR Secretariat (PAPS)
Position	One Individual Consultant: Senior PPR Epidemiologist / Senior Data Analyst
Modality	Predominantly desk-based and home-based; virtual or written consultation only; no country missions
Effort and duration	Up to 40 working days over three calendar months from the agreed commencement date
Supervision	Technical: Programme Expert, Disease Management and Control. Overall: Director of AU-IBAR

Background and rationale

AU-IBAR supports the sustainable development of animal resources in African Union Member States. Through PAPS, it coordinates the Pan-African PPR Eradication Programme. Activity 3.2.1 requires an analysis of PPR vaccination data and its relationship with disease occurrence over the last five years, together with an estimate of possible vaccine demand.

Vaccination records are dispersed across national Veterinary Services, the Animal Resources Information System (ARIS), Regional Economic Communities (RECs), AU-PANVAC, partner programmes and project reports. Definitions and population denominators are not harmonised, and post-vaccination evaluation (PVE) evidence is uneven. Without a consolidated evidence base, vaccine need, procurement and PPR2 investment cannot be planned reliably.

This assignment will consolidate and assess the evidence, develop transparent vaccine-demand forecasts and define the core vaccination data standards for routine capture through ARIS. It builds on two existing assets, ARIS and the draft Vaccination Strategic Framework, and will inform PPR2 formulation, Activity 3.2.4 and resource mobilisation. It creates neither a new information system nor a new strategy.

Objectives and expected results

The overall objective is to establish a validated and sustainable evidence base on PPR vaccination and its epidemiological effects, estimate current and future vaccine demand, and standardise routine vaccination reporting through ARIS.

Specific objective	Expected result and use
Consolidate, clean and classify country vaccination, population, PVE and disease-occurrence data for an agreed five-year core period.	A cleaned, evidence-classified continental vaccination dataset.
Assess vaccination performance, geographical and population gaps, and the relationship between vaccination and reported disease occurrence, distinguishing association from causal evidence.	An understanding of what vaccination has achieved and where coverage did not translate into immunity.
Develop a core ARIS vaccination data dictionary, reporting templates, validation rules and an annual updating mechanism with assigned responsibilities.	ARIS vaccination data standards and an annual update mechanism, handed over to the ARIS team.
Produce a reproducible four-scenario vaccine-demand forecast by country, REC and episystem, with uncertainty analysis.	Demand estimates with implications for vaccine production, AU-PANVAC certification, procurement, cold chain and financing.
Produce a reconciled reference table of small-ruminant population denominators and PPR Monitoring and Assessment Tool (PMAT) stages by country (and by priority episystem or targeted sub-national zone where relevant), with an explicit source hierarchy.	A common reference for this assignment, PPR2 costing and ARIS.
Translate findings into a prioritised Evidence-to-Strategy Matrix and transfer the data, analytical methods and forecasting tools to AU-IBAR.	Evidence feeding the vaccination framework, PPR2 formulation, Activity 3.2.4 and resource mobilisation, and tools AU-IBAR can maintain.

Scope and approach

Approach

1. Desk-based delivery: review of programme documents, ARIS extracts, partner datasets and literature, plus data submitted through PAPS-facilitated structured requests. Consultation and validation are virtual or written only. No country missions, primary field surveys or new laboratory testing are envisaged.
2. Proportionate methodology: epidemiological rigour combined with a data-management approach that can be completed within the approved effort.
3. Evidence discipline: reported, validated, partner, estimated and modelled data are kept distinct, and causal claims are made only where the design supports them.
4. Single point of accountability: one consultant combines epidemiology and data analysis, leads the technical work, facilitates remote validation, documents assumptions and limitations, and delivers an integrated evidence and handover package. The Technical Reference Team (section 6.1) supports data access, technical review and specialised questions; it does not replace the consultant’s accountability for complete and reproducible outputs.
5. Consultation: national veterinary authorities and PPR focal points are consulted through established PAPS and REC channels; AU-PANVAC, the ARIS team, M&E personnel, Regional Coordinators, FAO and WOAH through the Technical Reference Team. Points of agreement, unresolved differences and limitations in participation are recorded. Sensitive or unpublished data are accessed and shared only under agreed permissions.

Core and extended scope

The minimum acceptable scope comprises:

1. A desk inventory of available vaccination data sources for all countries of the programme area, as listed by PAPS at inception.
2. An in-depth analysis of the five-year core period for 12 to 15 priority countries agreed with PAPS in the Inception Report, selected to represent the priority episystems communicated by PAPS, the four RECs and the range of PMAT stages, and including countries with documented PVE.
3. A selective desk review of earlier programmes where documents or ARIS data are already available.
4. The core ARIS vaccination data standard.
5. The vaccine-demand forecast at country level for the priority countries, at REC level for the programme area using harmonised desk parameters, and at episystem level for the priority episystems.
6. The Evidence-to-Strategy Matrix.

Extended elements (additional countries, systematic historical reconstruction beyond five years, sub-national estimates, detailed dashboard design, and adaptation of the vaccination-event model to other priority diseases) are proposed in the Inception Report. They proceed only once the core outputs are secured and must not delay the core deliverables. Data gaps are recorded and handed to the annual update mechanism, not closed through new field data collection.

Exclusions

The following fall outside this consultancy: implementation, deployment or modification of ARIS software; field data collection; vaccination campaigns; laboratory investigations; and the creation of a new information system or a separate vaccination strategy.

Tasks and responsibilities

Inception and scope confirmation

Review the concept note, relevant Action documentation, the draft Vaccination Strategic Framework, and available ARIS extracts and programme datasets. Agree with PAPS:

•    the five consecutive years of the core period (the most recent five years with sufficiently comparable evidence; incomplete current-year observations are labelled separately and not compared directly with full-year totals) and the evidence cut-off date;
•    geographical coverage, the list of priority countries, the country-to-REC mapping and episystem definitions;
•    the forecast horizon and the priority review questions.

Prepare a feasible 40-day work plan covering all six deliverables, data access, remote consultations and review windows within three calendar months. Establish a source hierarchy, a country-data request and validation protocol, an issues register and a prioritised core scope. Identify dependencies on ARIS access, national focal points and partner inputs, and escalate unresolved constraints promptly. Confirm relevant technical standards and definitions with FAO, WOAH and the Technical Reference Team.
Submit the harmonised data-request template and country questionnaire (Annex 3), in English and French, within the first week as an early component of D1, so that PAPS can dispatch the formal data requests without waiting for the full Inception Report.

Data source registry and ARIS gap assessment

•    Source inventory. Inventory national Veterinary Services records, ARIS data, REC submissions, AU-PANVAC information, FAO and WOAH sources, partner datasets, programme reports and relevant literature. For each source record the custodian, period, geographical coverage, variables, format, access conditions, completeness, validation status and limitations. Earlier programmes include national mass-vaccination programmes, SHARE, PRAPS, Mano River initiatives, PRODEL and related World Bank, EU, FAO, WOAH, AfDB, IFAD and bilateral interventions; review them selectively, where data are readily available and directly useful, and avoid an open-ended historical review.
•    ARIS gap assessment. Map existing ARIS vaccination fields and workflows against minimum analytical and routine-reporting needs: identifiers, species and age categories, campaign records, denominators, geographical detail, vaccine batches, PVE linkage, reporting frequency and validation arrangements. Distinguish missing data from missing fields, and procedural problems from software requirements. Agree a practical gap-closure plan with the ARIS team.
•    Denominator and PMAT reference table. Compile the reconciled reference table of small-ruminant populations and PMAT stages (Annex 1, Template H) under an explicit source hierarchy, record differences with the AU-IBAR/PAPS costing and population datasets together with the arbitration rule applied, and update the table in D4.

Data consolidation and quality assurance

•    Requests and traceability. Develop structured data requests for issue through PAPS and the Regional Coordinators. Retain immutable source copies and a traceable record of cleaning, reconciliation and revisions. Use stable country and administrative identifiers and explicit mappings to RECs and episystems, and allocate overlapping records consistently so that regional or episystem totals do not double count animals or doses.
•    Harmonisation. Harmonise reporting periods, species, units and population denominators. Distinguish doses procured, distributed, administered, wasted and remaining in stock, and distinguish unique animals vaccinated from repeated vaccinations where the evidence allows.
•    Quality checks. Check for duplicates, impossible dates, missing values, inconsistent totals and coverage above 100%. Investigate discrepancies rather than automatically capping coverage or replacing missing entries with zero, and record unresolved issues and their implications. Assign transparent quality ratings with reasons.
•    Evidence classification. Keep separate fields for source type, validation status and estimation method. Every value in the consolidated dataset and the demand model carries one of the classes below; modelled values are never presented as official national data.

Class	Definition
A	Official data validated by the competent Veterinary Authority.
B	Official data reported by the country (including through ARIS or the World Animal Health Information System, WAHIS) but not validated for this assignment.
C	Partner, project, programme or published scientific data.
D	Estimated or modelled values.

•    Validation. Submit country records for written or virtual validation and retain dates, reviewers and comments. Where no response is received, retain the evidence with its provisional status and document the follow-up attempts; silence does not constitute validation.

Vaccination performance and epidemiological analysis

•    Performance. Analyse trends in vaccination volumes, administrative coverage, geographical reach, campaign timing and continuity, eligible and missed populations, and available PVE or serological findings. Define each numerator and denominator, and report administrative coverage, geographical coverage and measured immunity separately. Assess the evidence on delivery arrangements, vaccine quality and certification, cold chain, accessibility, insecurity, animal movement, population turnover and community participation as explanations for performance gaps.
•    Association with disease occurrence. Relate vaccination timing and intensity to reported PPR outbreaks or other supported disease indicators at comparable spatial and temporal scales. Assess reporting completeness, surveillance effort, diagnostic confirmation, missing periods and changes in definitions, and adjust for surveillance and reporting intensity, since increased vaccination activity is often accompanied by increased reporting. Use descriptive and stratified analysis as the minimum; apply comparative or statistical methods only where data quality and design justify them. Document confounding, plausible time lags, selection bias and sensitivity to weak denominators.
•    Serology and PVE. Interpret serology in light of vaccination and infection histories, sampling methods and laboratory procedures. Because no DIVA test (differentiating infected from vaccinated animals) is available for PPR, keep PVE, including seromonitoring of vaccinated cohorts, distinct from general serosurveillance. Where possible, separate vaccine-induced from infection-induced immunity using age, marking or identification, vaccination records and sampling of young unvaccinated animals beyond the age of maternal-antibody decline, and state the residual bias. For each country with PVE, report whether the target immunity was reached in the target population, with the sampling design and confidence intervals.
•    Interpretation limits. Doses administered are not proof of protection, reduced reporting is not proof of reduced transmission, and immunity is not proof of disease freedom. Identify where causal impact cannot be estimated. Produce country, regional and episystem summaries and a prioritised evidence-gap assessment without implying uniform evidence coverage across the continent.

ARIS vaccination data standardisation

•    Minimum viable data package, co-designed with the ARIS team: data dictionary; harmonised reporting templates; core indicator list; mandatory and optional fields; controlled values; validation rules; example records; and a crosswalk to existing ARIS fields. Specify units, geographic and temporal granularity, unique keys, denominator provenance, missing-value codes, evidence classifications and links between campaign, vaccine batch and PVE records. Align the standard with the reporting requirements of WOAH-WAHIS and FAO’s Sustainable Livestock Transformation and One Health Intelligence and Knowledge Hub, ensuring interoperability among AU-ARIS, WAHIS and relevant FAO systems.
•    Testing and review. Test the templates and rules on representative available records, record errors and revisions, and obtain a documented ARIS-team technical review. Provide a prioritised implementation backlog for any changes requiring software development. Acceptance rests on the standards, tested templates and handover.
•    Annual update procedure. Identify national submitters, REC coordination roles, PAPS oversight, ARIS stewardship, quality checks, approval steps, version control and publication permissions (indicative sequence in Annex 2). Propose a reporting calendar and an escalation process for late or disputed records. Distinguish recommended arrangements from commitments formally accepted by participating institutions.

Vaccine demand forecasting

•    Model and scenarios. Develop one editable, reproducible model with four scenarios, proposed for confirmation at inception: (i) continuation of documented current practice; (ii) needs-based implementation of the existing framework; (iii) accelerated and synchronised action in priority episystems; and (iv) resource-constrained delivery. Apply a common population baseline and forecast horizon, state what changes between scenarios, and do not treat any scenario as an approved campaign or procurement commitment.
•    Parameters. For each scenario specify eligible and susceptible populations, population growth and turnover, prior vaccination and immunity where supported, campaign coverage, timing and number of rounds, wastage, usable stock, confirmed pipeline and reserve requirements. Distinguish animals requiring vaccination, doses to be administered and doses to be procured, and document how repeat rounds, stock expiry, existing reserves and pipeline commitments are handled to prevent double counting. Where detailed population dynamics cannot be supported, use explicit simplifying assumptions and sensitivity ranges.
•    Targeting and coverage. Derive the targeting rule of each country or zone from its PMAT stage and strategy. Apply the principle retained by PAPS that disease mapping and surveillance precede vaccine deployment where the epidemiological situation is not sufficiently established, and provide for tapering and cessation of vaccination where PMAT progression allows. Derive target coverage from the herd-immunity target of the PPR Global Control and Eradication Strategy (GCES) and of the draft continental vaccination framework (to be confirmed at inception; indicative sensitivity range 67–83%, corresponding to R0 ≈ 3–6, to be justified from the literature), the expected seroconversion rate and the accessible share of the population, without counting accessibility or prior immunity twice. Include a scenario share of thermotolerant vaccine meeting the criteria established by AU-PANVAC and adopted by WOAH, with its cold-chain implications.
•    Reconciliation. Reconcile denominators and vaccination assumptions with the AU-IBAR/PAPS costing and population datasets and with the country vaccination targets and 2027–2030 projections submitted to PAPS, documenting every difference.
•    Requirements and supply. Calculate requirements by country and year, and aggregate to REC, episystem and continental levels using documented allocation rules. Show gross requirements and net procurement needs separately (Annex 2). Compare demand with the evidence on production, AU-PANVAC certification and supply lead times, distinguishing installed capacity, certified output and confirmed availability. Identify procurement, storage, cold-chain and financing constraints without representing unconfirmed supply as available stock.
•    Financing. Estimate indicative financing requirements using sourced or explicitly assumed unit costs, separating vaccine procurement from delivery and other cost components where evidence permits. Present low, central and high estimates or parameter sensitivities for the main uncertainties.
•    Documentation and tools. Provide a user guide, formula or code documentation, sample calculations, consistency checks and a statement of limitations. Use accessible tools that AU-IBAR can update without unapproved proprietary dependencies.

Evidence translation and handover

•    Evidence-to-Strategy Matrix. Link each material finding and its strength of evidence to implications for the draft Vaccination Strategic Framework, PPR2, Activity 3.2.4 and resource mobilisation. Prioritise actions, identify responsible institutions and dependencies, and indicate the decisions or additional evidence required. Recommendations remain proportionate to evidence quality and within the existing programme architecture.
•    Review. Present draft findings remotely to the Technical Reference Team and relevant focal points, maintain a consolidated comments-and-response matrix, and incorporate agreed revisions.
•    Handover. Deliver a remote handover session for PAPS and the ARIS team demonstrating dataset updates, quality controls and scenario calculations. Provide all editable outputs, data, code, model files, metadata and instructions in an organised handover folder.

Deliverables and work schedule

The six milestones below are expressed in cumulative consultant working days, not calendar deadlines, and total up to 40 working days over three calendar months. The Inception Report assigns actual dates and counterpart review periods. The effort allocation may be refined at inception without increasing the approved ceiling or changing the six milestones.

Deliverable	Due	Effort	Required product and acceptance evidence
D1 Inception Report	Day 5	5 days	Agreed scope, five-year period, cut-off, forecast horizon, methods, four scenarios, work plan, data requests, consultation plan, risk register and responsibilities.
D2 Data Source Registry and ARIS Gap Assessment	Day 12	7 days	Traceable source inventory, coverage and quality assessment, ARIS field crosswalk, reconciled denominator and PMAT-stage reference table, gap priorities and country-data request and validation status.
D3 ARIS Vaccination Data Standardisation Package	Day 20	8 days	Dictionary, templates, indicators, validation rules, tested examples, ARIS technical review record, annual update procedure and implementation backlog.
D4 Consolidated Dataset and Vaccination Performance and Epidemiological Impact Report	Day 30	10 days	Cleaned, evidence-classified dataset, metadata and cleaning log; updated denominator and PMAT-stage reference table; country, REC and episystem findings; coverage and immunity analysis; supported disease associations, limitations and validation record.
D5 Continental PPR Vaccine Demand Forecast	Day 36	6 days	Reproducible four-scenario model; country/year, REC and episystem outputs; gross and net requirements; uncertainty, supply and financing implications; assumptions and user guide.
D6 Final Evidence-to-Strategy and Handover Package	Day 40	4 Days	Final revised D1–D5 products as applicable; prioritised matrix, executive brief, briefing slides, comment dispositions and complete editable handover with demonstration record.

Acceptance and format

•    Acceptance. AU-IBAR accepts deliverables in writing following technical review. Each submission must satisfy the required content above, preserve traceability to source evidence, distinguish validated from provisional findings, document limitations, and resolve material review comments or give reasoned dispositions. Numerical totals must reconcile across datasets, narrative, model and briefing materials, and formulas or scripts must reproduce the supplied outputs.
•    Review. The Programme Expert, Disease Management and Control, coordinates consolidated technical feedback with PAPS and the Technical Reference Team. The ARIS team reviews the standards and updating procedure, and relevant national authorities are invited to validate their records. AU-IBAR designates the contract manager and final acceptance authority at inception. Country non-response does not prevent completion where follow-up is documented, provisional classification is transparent and limitations are adequately stated. Review and revision windows must fit within the three-month schedule.
•    Format. Reports and briefs are submitted in editable English Word format; datasets and models in Excel and open tabular formats where appropriate; scripts with execution instructions; and briefing slides in PowerPoint, all using agreed AU-IBAR/PAPS branding. Apart from the English–French country questionnaire (Annex 3), translation or interpretation, if required, is arranged by AU-IBAR unless expressly included in the contract.

Institutional arrangements, reporting and data governance

Supervision and coordination

The consultant works under the technical supervision of the Programme Expert, Disease Management and Control, in coordination with PAPS, and under the overall supervision of the Director of AU-IBAR. The consultant engages the ARIS team directly on data standards and maintenance requirements. PAPS technical experts from implementing technical partners contribute to technical review.

The Technical Reference Team comprises PAPS, AU-PANVAC, the ARIS team, M&E personnel, Regional Coordinators, FAO and WOAH. Participation does not imply a separately funded appointment. Roles are as follows:

Institution	Role
PAPS	Coordinates institutional requests and consolidated feedback.
Regional Coordinators	Facilitate country engagement.
National veterinary authorities	Review and validate national records.
ARIS team	Co-designs the data standards and reviews the standards and updating procedure.
AU-PANVAC	Advises on vaccine quality and certification evidence.
FAO and WOAH	Support methodological and technical coherence.

Reporting and counterpart support

•    Consultant: brief fortnightly progress updates covering work completed, days used, data received, emerging findings, risks, decisions required and the next period’s tasks; a live issues-and-decisions log; a record of days worked and progress against milestones; and prompt notification to PAPS of material delays.
•    AU-IBAR: provides available programme documents and ARIS data in the first week, nominates focal points, facilitates structured data requests and convenes remote technical reviews. Where inputs are delayed, prioritisation or a revised schedule is agreed in writing, without silently reducing output quality.

Data ownership, confidentiality and reproducibility

•    All assignment outputs, datasets, scripts and models remain AU-IBAR property; Member States retain ownership of their national data. The contract and data-sharing arrangements govern custody, permitted use and disclosure.
•    The consultant retains source attribution and access restrictions, protects confidential information, does not publish or share unpublished data or results without authorisation, and declares any conflict of interest, including relationships with vaccine suppliers or organisations whose programmes are assessed.
•    The analytical files, metadata, source registry, processing history and model documentation are transferred to AU-IBAR in usable formats. Third-party data licences and restrictions are identified separately; ownership of assignment products does not override third-party rights. Secure transfer, retention and deletion arrangements are agreed at inception, and appropriate consent is obtained for consultation records.

Key risks and mitigation

Risk	Mitigation
Limited or late country data	Issue PAPS data requests at inception; use ARIS and partner sources; classify data quality and state gaps explicitly; retain non-responses as provisional evidence.
Weak denominators and PVE evidence	Flag coverage above 100%, reconcile sources through the reference table, and apply sensitivity and uncertainty analysis.
Heavy workload for one consultant in 40 days	Core-scope priorities, staged deliverables with PAPS review, support from the Technical Reference Team, and extended elements only after the core outputs are secured.
Delayed ARIS access or counterpart inputs	ARIS data and documents provided in the first week; focal points nominated; early escalation; written re-prioritisation or revised schedule.
Narrow candidate pool for the combined profile	Minimum thresholds in both disciplines; each proposal must show how both are covered.

Duration, location and remuneration

Duration and location

The consultancy comprises up to 40 working days over three calendar months from the agreed commencement date. It is home-based and coordinated through AU-IBAR/PAPS in Nairobi, Kenya. Changes to scope, duration or effort require prior written contractual approval.

Remuneration

The approved professional fee budget is USD 12,000, calculated at USD 300 per working day for 40 days. No staff salary grade is implied.

The payment milestones below are proposed, subject to AU-IBAR approval before solicitation and inclusion in the contract. Payments depend on accepted outputs and the agreed contractual requirements; the schedule does not constitute an approved financial commitment.

Milestone	Deliverables accepted	Share of fee	Amount (USD)
1	D1 & D2	30%	3,600
2	D3 & D4	45%	5,400
3	D5 & D6	25%	3,000
Total		100%	12,000

No mission travel or subsistence is budgeted. Any additional expenditure, specialist support, translation or material change in scope must be separately authorised and funded. The consultant maintains appropriate personal insurance in accordance with the contract.

Qualifications and selection criteria

Qualifications

A degree in veterinary medicine or a closely related animal-health discipline, with a relevant Master’s degree in veterinary epidemiology, veterinary public health, biostatistics, epidemiology, data science or a closely related field. Candidates must demonstrate competence in both animal-disease epidemiology and quantitative data analysis. Doctoral training or specialised certification in vaccination evaluation, modelling or data management is an advantage.

Experience

Minimum:

• at least ten years of relevant professional experience, including at least five years in animal-disease epidemiology, surveillance, vaccination analysis or PPR programme work, and at least five years of applied quantitative data management and analysis (the periods may overlap).

Comparable assignments:

• evidence of at least two, including one directly related to PPR or small-ruminant vaccination and one involving reproducible analysis or forecasting of multi-country or multi-source data. A single assignment may demonstrate both.
  

 Essential:

• cleaning and reconciling heterogeneous datasets; interpreting vaccination coverage and PVE; assessing disease trends and epidemiological limitations; building transparent forecasting or demand models with uncertainty analysis; and producing data dictionaries, reporting standards or validation rules.

Desirable:

• experience with African veterinary systems, REC coordination, ARIS or comparable animal-health information systems (strongly desirable); familiarity with AU-PANVAC, FAO/WOAH approaches and donor-funded programmes.

Other essential skills

Strong analytical writing, remote facilitation, independent judgement and timely delivery; advanced spreadsheet skills and proficiency in a suitable reproducible analytical environment, such as R, Python, Stata or an equivalent tool, with outputs that AU-IBAR can maintain; excellent written and spoken English. Working French and other AU languages are advantages.

Selection criteria

Candidates must meet the minimum requirements in both epidemiology and data analysis; strength in one discipline does not substitute for absence of the other. The weighting below follows the AU-IBAR template (30–50–20) and, together with the technical pass mark, any interview and the treatment of financial proposals, will be confirmed by AU-IBAR before advertisement.

Criterion	Components (maximum points)	Score
Qualifications and training	Relevant academic qualifications (20); specialist training in epidemiology, vaccination evaluation or data analysis (10)	30
Experience	PPR and vaccination epidemiology (20); data integration and quantitative analysis (15); reproducible forecasting or demand modelling (10); African institutional or information-system experience (5)	50
Approach and communication	Quality and feasibility of the technical approach and work plan (12); writing and virtual facilitation (5); relevant language capability (3)	20
Total		100

Comparable outputs, references and analytical examples may be verified. Any demonstration or interview will assess epidemiological interpretation and practical data-analysis competence in accordance with the published procedure.

Gender mainstreaming

The African Union Commission is an equal opportunity employer, and qualified women are strongly encouraged to apply. The consultant shall examine available evidence on differential access to vaccination among women, youth, mobile livestock keepers and underserved communities, and propose feasible reporting improvements. Findings are disaggregated only where the data support it, gaps are identified explicitly, and household characteristics are not inferred from aggregate animal records.

HOW TO APPLY

Submission of applications

Applicants submit, through the official procurement process:

•    a detailed CV, and academic and relevant professional certificates;
•    a concise technical proposal and 40-day work plan demonstrating both epidemiological and analytical competencies;
•    evidence of two comparable assignments, with referees, and a sample or description of a reproducible analytical product;
•    a separate financial proposal stating the daily rate, total professional fee and tax treatment; and
•    the required declarations and identification documents, with the applicable privacy notice.

Application subject	Consultancy: Continental PPR Vaccination Analysis, Vaccine Demand Forecasting and ARIS Data Standardisation, Activity 3.2.1
Submission channel	procurement@au-ibar.org, copied to: millicent.ngayo@au-ibar.org (channel retained from the AU-IBAR template; to be confirmed before publication)
Deadline	25/11/2026 at 23:59:00 hours Nairobi Local Time

AU-IBAR will include its applicable Personal Data Protection and Privacy Statement in the published solicitation.

Annex 1. Minimum data and analytical templates

The consultant operationalises the following linked templates at inception. They set minimum content requirements, to be refined with the ARIS team; optional fields shall not prevent submission of core data.

Template	Minimum fields
A. Source registry	Source ID; custodian; document or dataset; country; period; geography; variables; access date; permissions; completeness; limitations; validation contact.
B. Campaign and population record	Record and source IDs; country and area codes; episystem mapping; year and campaign dates; species; eligible age group; target population and source/year; doses administered; unique animals if known; rounds; coverage formula; delivery method; vaccine batch and certification reference where available; quality and validation status.
C. PVE and disease evidence	Campaign linkage; sampling dates and design; sample size; laboratory/test; serology result and interpretation; vaccination history; disease-event period/location; suspected or confirmed status; surveillance/reporting limitations; source and validation status.
D. ARIS data dictionary	Field name; definition; data type; unit; permitted values; mandatory/optional status; reporting level and frequency; key/link; missing code; validation rule; ARIS field mapping; owner.
E. Demand model inputs and outputs	Scenario; country/area; PMAT stage and strategy rule; herd-immunity target and seroconversion rate; thermotolerant share; year; population baseline; eligibility; turnover; immunity assumptions; coverage; rounds; wastage; usable stock and pipeline; reserve; gross doses; net procurement; unit costs; uncertainty; sources and assumptions.
F. Evidence-to-Strategy Matrix	Finding; evidence reference and quality; limitation; implication for framework/PPR2/Activity 3.2.4; recommended action; priority; responsible institution; timing; dependency; decision or financing need.
G. Validation and update log	Record/output ID; reviewer and institution; request/response dates; validation status; discrepancy; disposition; change/version; unresolved issue; owner; completion date.
H. Denominator and PMAT reference table	Country; zone or priority episystem; species; population; denominator source and hierarchy rank; reference year; PMAT stage; PMAT source and date; differences with PPR2 costing and population datasets; arbitration rule; evidence class.

Annex 2. Core analytical and reporting rules

Administrative coverage

Administrative coverage = (eligible animals vaccinated ÷ eligible target population for the same area and period) × 100. Where only doses are available, identify the result as a dose-based proxy and disclose the repeat-dose limitation. Geographical reach and measured immunity require separate definitions and denominators.

Procurement identity

Gross doses required = planned administrations ÷ (1 − wastage proportion) + any justified reserve addition. Net procurement = the non-negative balance after deducting usable, appropriately timed stock and confirmed pipeline allocated to the same requirement. More detailed population and campaign calculations may be used, provided every parameter, timing assumption and stock adjustment remains explicit and reproducible.

Quality checks

•    Data: uniqueness, mandatory-field completeness, valid codes and dates, non-negative quantities, denominator consistency, coverage anomalies, inventory reconciliation, and agreement between detailed records and aggregates.
•    Model: scenario reproducibility, sensitivity to key assumptions, and prevention of duplicate allocation across rounds, regions and episystems.

Annual update sequence

Annual updating follows an agreed sequence: national submission, country verification, REC reconciliation, ARIS quality checks, PAPS review and controlled release. The handover identifies the proposed annual timetable, version custodian, permissions, sign-off points and actions for late or disputed data. Final institutional responsibilities are confirmed by AU-IBAR and participating authorities.

Annex 3. Harmonised country PPR vaccination data request (minimum modules)

The questionnaire (section 4.1) is issued through PAPS in English and French within the first week of the assignment. Its procurement module is guided by the WOAH practical guidelines for national procurement of veterinary vaccines. It collects the minimum information below for each country; modules are completed to the extent that data exist, and non-availability is recorded as such rather than left blank.

Module	Minimum information to be collected
A. Respondent and authority	Country; competent Veterinary Authority; PPR, epidemiology and ARIS focal points; reporting period; validation authority.
B. Historical programme inventory	Programme/project; years; objectives; funding; geographic scope; strategy; partners; rounds; main results and lessons.
C. Population denominator	Sheep and goat population by year and geography; denominator source (census, projection, registry, estimate); age structure; eligible population; turnover and birth assumptions.
D. Vaccine procurement	Product; strain; manufacturer; lot; AU-PANVAC certification; quantities ordered and received; dates; supplier; price; funding; lead time; stock-outs; expiry.
E. Distribution and cold chain	National and sub-national stocks; quantities dispatched and received; storage; transport; temperature monitoring; losses and causes.
F. Campaign implementation	Dates; rounds; teams; provider type; villages, herds and households reached; animals presented and vaccinated; marking; doses used, returned and wasted.
G. Coverage and denominator issues	Administrative, species, geographic and herd coverage; denominator used and its limitations; target herd-immunity rate.
H. PVE and herd immunity	Protocol; sampling frame and design; date; sample size; assay and laboratory; seroprevalence; herd immunity rate (HIR) and confidence interval; corrective actions.
I. Disease occurrence	Outbreaks before and after campaigns; dates; location; cases and deaths; laboratory confirmation; vaccination status of affected animals; surveillance intensity; suspected introduction.
J. Mobility and episystem	Transhumance routes; markets; corridors; border crossings; synchronisation with neighbours; protection or buffer zones; episystem.
K. Costs and financing	Vaccine, freight, cold chain, transport, personnel, communication, marking, PVE, surveillance; total cost; government and partner contributions.
L. Future demand	Planned strategy; target population; rounds; target herd-immunity rate; annual vaccine need; emergency reserve; operational constraints.