State context

GEThttps://api.ai4mproject.com/v1/context/statesScope: risk_scores

Returns what surrounds a risk score: how many people live in each state, and how well it is covered by bed nets, treatment and health facilities. Use it with the risk score to decide where need is greatest.

Note

These figures are modelled estimates from the Malaria Atlas Project and population counts from WorldPop. They are context, not inputs to the AI4M risk score, and they do not change from month to month.

Parameters

None.

Request

curl

curl "https://api.ai4mproject.com/v1/context/states" \
  -H "Authorization: Bearer $AI4M_API_KEY"

Python

for state in client.get_state_context():
    print(state.state, state.population, state.itn_use, state.travel_minutes_to_care)

TypeScript

const report = await client.getStateContext();
for (const state of report.states) {
  console.log(state.state, state.population, state.itn_use, state.travel_minutes_to_care);
}

Go

states, err := client.StateContext(ctx)
if err != nil {
  log.Fatal(err)
}
for _, state := range states {
  fmt.Println(state.State, state.Population)
}

Response

Shares run from 0 to 1. A figure is null where the source has no estimate for the area.

Field	Type	Description
source.name	string	Where the coverage figures come from
source.coverage_year	integer	The year the net and treatment figures describe
states[].state_code	string	Two-letter state code
states[].state	string	State name
states[].zone	string	Geopolitical zone
states[].lgas	integer	Number of LGAs in the state
states[].population	integer	People living in the area
states[].area_km2	number	Land area in square kilometres
states[].itn_use	number	Share of people who slept under a treated net
states[].itn_access	number	Share of people with access to a treated net
states[].irs_coverage	number	Share of people protected by indoor spraying
states[].effective_treatment	number	Share of malaria cases that get an effective treatment
states[].travel_minutes_to_care	number	Average travel time to the nearest health facility, in minutes
states[].response_index	number	Average of net use and effective treatment

200 OK

{
  "source": {
    "name": "Malaria Atlas Project",
    "coverage_year": 2024,
    "note": "Modelled estimates shown as context. They are not inputs to the risk score. Shares run from 0 to 1."
  },
  "states": [
    {
      "state_code": "KN",
      "state": "Kano",
      "zone": "North West",
      "lgas": 44,
      "population": 14310694,
      "area_km2": 20072,
      "itn_use": 0.497,
      "itn_access": 0.542,
      "irs_coverage": 0,
      "effective_treatment": 0.574,
      "travel_minutes_to_care": 5.145,
      "response_index": 0.535
    },
    {
      "state_code": "LA",
      "state": "Lagos",
      "zone": "South West",
      "lgas": 20,
      "population": 12782537,
      "area_km2": 3783.6,
      "itn_use": 0.162,
      "itn_access": 0.285,
      "irs_coverage": 0,
      "effective_treatment": 0.574,
      "travel_minutes_to_care": 3.395,
      "response_index": 0.368
    }
  ]
}

The example shows two of the 37 states. A state’s figures are averages across its LGAs, weighted by population.

Errors

Code	Status	When
SCOPE_REQUIRED	403	The key does not include the scope this endpoint needs

Any request can also return 401 for a bad key and 429 when a limit is reached. See Errors.

See also

• LGA context
• Data sources