Extending lead times in prospective cholera emergence
Early warning for waterborne epidemics like cholera is critical for prepositioning oral cholera vaccines and clean water supplies. Fortunately, outbreaks are rare: in any given week, fewer than 1 in 100 of the country’s 403 health zones sees one begin. Unfortunately, this very same rarity makes them hard to anticipate.
To address a use case defined by the World Health Organization Regional Office for Africa using national surveillance data from the Democratic Republic of the Congo’s Integrated Disease Surveillance and Response (IDSR) reporting, we tested whether a lightweight, low-resource version of PDFM (adapted for regions with sparse internet connectivity) could help forecast cholera hotspots.
The benefit depended on how far ahead we looked. One or two weeks out, recent case counts told most of the story and PDFM did not significantly enhance the accuracy. Four to eight weeks out, when there is still time to move supplies, it helped produce:
- Sharper shortlists: Response teams work from a short list of high-risk zones, so each week we checked how many of the model’s top five picks went on to have an outbreak. Eight weeks ahead, PDFM raised this from 1.78 to 2.10 correct picks per week, an 18% improvement.
- Bigger gains where cholera is endemic: In the 15 zones that had reported cholera in at least half of all weeks, Precision@5 of eight-week shortlists improved from 0.3333 to 0.3975, a relative gain of 19%.
These findings demonstrate that while short-term tracking can rely on recent clinical data, foundation model embeddings capture underlying environmental, connectivity, and population determinants that supplement historical data, allowing for proactive planning one to two months in advance.
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