LGDec 28, 2025

Discovering Transmission Dynamics of COVID-19 in China

arXiv:2512.22787v1h-index: 8
Originality Synthesis-oriented
AI Analysis

This provides insights into public health interventions for COVID-19 in China, but it is incremental as it applies existing methods to new data.

The study analyzed COVID-19 transmission dynamics in China using public tracking data and mobility information, finding that larger cities had more infections linked to social activities, and 79% of symptomatic individuals were hospitalized within 5 days of symptom onset.

A comprehensive retrospective analysis of public health interventions, such as large scale testing, quarantining, and contact tracing, can help identify mechanisms most effective in mitigating COVID-19. We investigate China based SARS-CoV-2 transmission patterns (e.g., infection type and likely transmission source) using publicly released tracking data. We collect case reports from local health commissions, the Chinese CDC, and official local government social media, then apply NLP and manual curation to construct transmission/tracking chains. We further analyze tracking data together with Wuhan population mobility data to quantify and visualize temporal and spatial spread dynamics. Results indicate substantial regional differences, with larger cities showing more infections, likely driven by social activities. Most symptomatic individuals (79\%) were hospitalized within 5 days of symptom onset, and those with confirmed-case contact sought admission in under 5 days. Infection sources also shifted over time: early cases were largely linked to travel to (or contact with travelers from) Hubei Province, while later transmission was increasingly associated with social activities.

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