Introduction
============

Humanitarians are increasingly recognizing the importance of estimating the
risk and predicting the occurrence of shocks and disasters,
whether it is through reducing the vulnerability and exposure of affected
populations to likely hazards, or acting in anticipation of predictable shocks.
This requires a wide array of data, from historical observations, to existing model forecasts
and related covariates.

This is where OCHA AnticiPy comes in, providing a simple interface for downloading and
processing a range of data relevant for anticipatory action and
disaster risk reduction in humanitarian response.

Datasets currently supported are:

 - CHIRPS rainfall
 - COD ABs (Common Operational Datasets administrative boundaries)
 - FEWS NET food insecurity
 - GloFAS river discharge
 - IRI seasonal rainfall forecast
 - USGS NDVI (normalized difference vegetation index)

At the `Centre for Humanitarian Data <https://centre.humdata.org/>`_,
we've now used OCHA Anticipy to develop
some of our own
`anticipatory action
<https://www.unocha.org/our-work/humanitarian-financing/anticipatory-action>`_
frameworks, such as for
`drought in Burkina Faso
<https://github.com/OCHA-DAP/pa-aa-bfa-drought>`_.