# Google COVID-19 Vaccination Search Insights: Anonymization Process Description

arXiv: https://arxiv.org/abs/2107.01179 · HTML: https://mlsanity.com/paper/2107.01179/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Jul 2021.

## Built on by (most cited first, 5 of 5)

- [General Geospatial Inference with a Population Dynamics Foundation Model](https://mlsanity.com/paper/2411.07207/) (2024)
- [Data-Centric Epidemic Forecasting: A Survey](https://mlsanity.com/paper/2207.09370/) (2022)
- [Samplable Anonymous Aggregation for Private Federated Data Analysis](https://mlsanity.com/paper/2307.15017/) (2023)
- [Accurate Measures of Vaccination and Concerns of Vaccine Holdouts from Web Search Logs](https://mlsanity.com/paper/2306.07457/) (2023)
- [Differential Privacy via Distributionally Robust Optimization](https://mlsanity.com/paper/2304.12681/) (2023)

## Abstract (arXiv)

This report describes the aggregation and anonymization process applied to the COVID-19 Vaccination Search Insights (published at http://goo.gle/covid19vaccinationinsights), a publicly available dataset showing aggregated and anonymized trends in Google searches related to COVID-19 vaccination. The applied anonymization techniques protect every user's daily search activity related to COVID-19 vaccinations with (varepsilon, δ)-differential privacy for varepsilon = 2.19 and δ = 10-5.