When 11/11 Cases Isn't Enough: Building an Outbreak Investigator with FalkorDB
Eleven people got sick. Two ingredients appeared in all eleven cases. Two suppliers tied. The case counts narrowed the search, but they couldn’t tell us which lot was responsible. To break the tie, we needed evidence that was independent of exposure counts—and a way to show exactly how the investigation reached its conclusion. That was the challenge behind BatchZero , our Graph Hacks 2026 project…
The article discusses the BatchZero project, a Graph Hacks 2026 project for the FalkorDB track, aimed at building an outbreak investigator. The challenge was to break a tie between two ingredients responsible for eleven cases, where both ingredients and their respective suppliers appeared in all cases. To do this, the project leverages synthetic data to represent the investigation workflow, demonstrating how relationships between entities like people, cases, exposures, menu items, ingredients, lots, and suppliers can be followed directly using a graph.
The article highlights the importance of not only identifying common factors among cases but also determining which facilities served the ingredient, which lots were received, and the evidence supporting the final source. BatchZero incorporates additional elements such as isolates and genomic matches, represented as graph nodes and relationships, to further refine the investigation.
The project also addresses the possibility of misleading evidence by incorporating temporal checks to ensure that retrieved records align with the case onset and pathogen incubation window. The article emphasizes the significance of understanding the path from evidence to the final conclusion, rather than merely presenting the answer.
Brief written by urgent.news from Dev.to's own syndicated text. Machine-written — may contain errors; check the original before relying on it.
