FMD Industry Coordination Council

Foot and mouth disease in South Africa.

A weekly view of vaccine rollout, disease status and provincial coverage. Compiled by AgriCulture South Africa from provincial Joint Operations Committee submissions.

As at 2026-05-21 Built 2026-05-22
National headline indicators

What we know this week.

Provincial snapshot

Active cases and vaccine coverage by province.

Provincial list.

Sorted by confirmed case load. The accent bar at the left shows severity; the bar to the right of the percentage shows vaccine coverage of the provincial cattle herd.

0 to 10 cases 11 to 100 cases 101 to 250 cases 251 to 400 cases More than 400 cases

Outbreak hotspots.

Confirmed positive cases by province.

Trends over time

Disease and vaccine progression.

Weekly disease cases.

Vaccines received and administered. Cumulative.

Vaccine flow

Doses by province and by manufacturer.

Doses received and animals vaccinated by province.

Vaccine source mix.

Provincial detail

Per province as at the latest available submission.

Province Positive Suspect Pending Cattle herd Doses received Animals vaccinated Balance Coverage
Coverage gap

Herd coverage against the two dose protocol.

First round coverage: share of provincial cattle herd that has received at least one dose.

Dairy industry view

MPO: Dairy herd vaccination and FMD case burden.

Submitted by the Milk Producers’ Organisation (MPO). Covers dairy cattle only.

Dairy cows vaccinated by province.

Active dairy FMD cases by province.

Ministerial update — 5 May 2026

Updated figures from the Minister of Agriculture.

Policy milestones.

    Upcoming vaccine supply pipeline.

    Data validation

    Ministerial briefing vs JOC provincial returns.

    Comparing DAFF ministerial figures (23 April 2026) against AgriSA JOC provincial returns (latest available). A positive difference means JOC reports more vaccinations than the ministerial figure — expected given the later date. A negative difference flags a data quality issue for investigation.

    Animals vaccinated: ministerial vs JOC per province.

    Discrepancy summary.

    Province Ministerial
    23 Apr
    JOC / AgriSA
    Latest
    Difference Status

    Ministerial figures cover all cloven-hoofed animals. JOC returns may be cattle-only in some provinces — explaining part of the gap.

    Data quality

    Where the data still needs work.

    Reconciliation issues.

    • Spoilage is not tracked nationally.The national total is reported as zero or blank in every weekly submission. Only KZN reports percentages. True wastage remains unknown.
    • About 988 000 doses without a manufacturer breakdown.KZN's bulk allocation is reported only as a Total figure, with no Bioaftogen, DolVet, OBP or BVI split.
    • State and Private Vet figures do not reconcile to Total.Suggests Total is the planned allocation while State and Private Vet are recorded receipts.
    • Animals Vaccinated by type does not reconcile to TOTAL Animals Vaccinated.Free State and Limpopo subtotals do not match the stated totals.

    Reporting gaps and ambiguities.

    • Mpumalanga reporting is sparse.Limited spoilage and channel split data despite being a top five outbreak province.
    • KZN allocation rationale is undocumented.Largest provincial allocation but minimal cases. The pattern suggests pre-emptive ring vaccination, but the policy is not stated in any source file.
    • No batch, expiry or cold chain data.Cumulative receipts only. The current balance could be ageing toward spoilage with no visibility.
    • The reporting schema changed mid-period.Reports before 1 April 2026 use a simpler schema. Later weeks add State and Private Vet and Commercial and Communal columns.
    • The national herd denominator changed silently.From 12 470 648 on 1 April 2026 to 12 496 199 from 17 April 2026 onwards, with no annotation.
    • Commodity submissions partial.MPO and RPO have submitted to date. NWGA (wool growers) and SAPPO (pork producers) returns are not yet in the dataset.

    Action items — data quality to-do list.

    Issues detected automatically from the current dataset. Each item identifies the responsible party and the corrective action required.

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