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Agricultural stress and crop hotspot warnings by country, monthly, sub-Saharan Africa

A monthly early-warning bulletin per country and region: warning levels for cropland and rangeland, a hotspot code, and the analyst's paragraph naming the places and the causes, for the whole continent.

Catalogue entry: Agricultural stress. Early-warning hotspot flags per region: warning levels for cropland and rangeland where the season is going badly.

Questions this data answers

  • Which counties will need relief food, seed or fertilizer support next quarter, before the appeal is published?
  • Is Kenya on the regional hotspot list this month, and is it cropland or pasture that is failing?
  • Where should an insurer expect claims this season, county by county, from the analyst's own words?
  • Which countries in East Africa carry a warning right now, for planning cross-border trade?
  • Does the bulletin expect the coming short rains to recover, or to compound the stress?
On this page
  1. Questions this data answers
  2. What the hotspot bulletin holds
  3. The July 2026 bulletin for Kenya
  4. How the 3 stress datasets fit together
  5. Sample data
  6. Fields
  7. Filters
  8. The same call, three ways
  9. Related datasets

What the hotspot bulletin holds

A monthly early-warning bulletin per country and region, built from 3 things together: a warning level for cropland, a separate one for rangeland, and a hotspot code, all backed by the analyst’s own narrative naming the places and the causes in plain text. The numbers say a season is going badly; the paragraph says where, and why. Every bulletin gets stamped on the first of the month it describes.

The July 2026 bulletin for Kenya

Hotspot, cropland warning 2, rangeland 0. The narrative reported vegetation across much of Kenya deteriorating from June after below-average rainfall since late May, moisture deficits building in the arid and semi-arid lands, crop development slowing across the unimodal zones, visible impacts in Kakamega, Bungoma, Uasin Gishu, Elgeyo Marakwet and Trans Nzoia, irreversible wilting in parts of the North Rift with some maize fields unlikely to recover at all, localised yield losses reported up to 60 %, and a strong El Niño forecast for the short rains carrying its own flood risk.

How the 3 stress datasets fit together

The bulletin runs monthly and regional. The rainfall anomaly runs weekly and by county, and on 26 August it read Bungoma at 26 % and Kakamega at 39 % of normal, the same 2 counties the bulletin had already named. The vegetation series, also weekly and by county, kept reading those same counties below their own normal well into September. One explains; the other 2 locate and measure. The county names inside the narrative are the exact same slugs the price, demand and news layers already use.

Sample data

Sample row, Kenya, bulletin of 2026-09

hs_nameHotspot (code 1)
g1_w_crop / g1_w_range / g1_w_any11 / 9 / 13
commentPoor crop production is expected across Kenya’s North Rift and parts of western Kenya following prolonged dry spells and severe rainfall deficits during critical crop-development stages. [https://urldefense.com/v3/__https:/fews.net/east-africa/kenya/food-security-outlook-update/august-2026?utm_source=chatgpt.com__;!!DOxrgLBm!GvWpxNNoS3o2bepAZH_wm1CK821qFcTUlevYiAwCBQeeT2zfJo6y8aXbCUtXWXbk7FEwl4O3dKctNya28rzaGf7GTIYHLqrggBGJ$" target="_blank] FEWSNET estimates long-rains maize production at 22–28% below the five-year average nationally, with production in key North Rift counties including Uasin Gishu, Elgeyo-Marakwet, Nandi and Trans Nzoia estimated at around 43% below the five-year average. Government assessments also report widespread crop failure in the North Rift, with significant losses reported in Uasin Gishu, Trans Nzoia, Bungoma and parts of Kakamega. The Government has subsequently announced plans to import 25 million bags of maize to address the anticipated national supply deficit. Looking ahead, forecasts of a strong El Niño for the upcoming short rains season point to above average rainfall. It is important however to bear in mind that high intensity rainfall will not be immediately beneficial to drought affected crop areas and that there is a high risk of adverse impacts including increased risk of flooding. These conditions could further affect agricultural production, disrupt livelihoods, and complicate recovery efforts in areas already impacted by the current dry spell.

The counties named in this paragraph are the same slugs the price and news layers use, so the bulletin joins to them.

Dataset idmarket.agri_stress
Cadencedekadal
EndpointGET /market/agri-stress
Key scopemarket:read
Declared fields6
History2026-06 to today
Coverageall of sub-Saharan Africa, country and region
StatusServed over the API

Global reference data — the same rows for every caller.

Source: Anomaly hotSpots of Agricultural Production (ASAP), European Commission Joint Research Centre.

Fields

FieldUnitNote
g1_w_any—warning level — any land cover
g1_w_crop—warning level — cropland
g1_w_range—warning level — rangeland
hs_code—hotspot code
hs_name—hotspot name
comment—

Filters

sourcecountryregionasap0_id

The same call, three ways

curl -G https://api.nuasense.com/api/nuasense/v1/market/agri-stress \
  -H "Authorization: Bearer nua_live_…" \
  -d start=-30d -d country=ken

Through the MCP connector the same read is the platform_dataset tool with dataset=market.agri_stress. Through a scheduled export it is one job with the same filters, delivered as a file. Every dataset takes the same arguments: start and end, every with agg, fields, limit up to 5,000, order, and the tags it declares.