# Mapping county-level mobility pattern changes in the United States in response to COVID-19

arXiv: https://arxiv.org/abs/2004.04544 · HTML: https://mlsanity.com/paper/2004.04544/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Apr 2020.

## Built on by (most cited first, 8 of 8)

- [Revisiting Synthetic Human Trajectories: Imitative Generation and Benchmarks Beyond Datasaurus](https://mlsanity.com/paper/2409.13790/) (2024)
- [The role of alcohol outlet visits derived from mobile phone location data in enhancing domestic violence prediction at the neighborhood level](https://mlsanity.com/paper/2203.04088/) (2022)
- [Change of human mobility during COVID-19: A United States case study](https://mlsanity.com/paper/2109.09022/) (2021)
- [STORM-GAN: Spatio-Temporal Meta-GAN for Cross-City Estimation of Human Mobility Responses to COVID-19](https://mlsanity.com/paper/2301.08648/) (2023)
- [Infected Smallville: How Disease Threat Shapes Sociality in LLM Agents](https://mlsanity.com/paper/2506.13783/) (2025)
- [Enhancing Ride-Hailing Forecasting at DiDi with Multi-View Geospatial Representation Learning from the Web](https://mlsanity.com/paper/2602.10502/) (2026)
- [Evaluating shifts in mobility and COVID-19 case rates in U.S. counties: A demonstration of modified treatment policies for causal inference with continuous exposures](https://mlsanity.com/paper/2110.12529/) (2021)
- [Causal Analysis and Prediction of Human Mobility in the U.S. during the COVID-19 Pandemic](https://mlsanity.com/paper/2111.12272/) (2021)

## Abstract (arXiv)

To contain the Coronavirus disease (COVID-19) pandemic, one of the non-pharmacological epidemic control measures in response to the COVID-19 outbreak is reducing the transmission rate of SARS-COV-2 in the population through (physical) social distancing. An interactive web-based mapping platform that provides timely quantitative information on how people in different counties and states reacted to the social distancing guidelines was developed with the support of the National Science Foundation (NSF). It integrates geographic information systems (GIS) and daily updated human mobility statistical patterns derived from large-scale anonymized and aggregated smartphone location big data at the county-level in the United States, and aims to increase risk awareness of the public, support governmental decision-making, and help enhance community responses to the COVID-19 outbreak.