ESTIMATING COVID-19 TRANSMISSION TIME USING HAWKES POINT PROCESSES

• 成果类型: Article
• 署名作者: Schoenberg, Frederic
• 署名单位: University of California System; University of California Los Angeles
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/23-AOAS1765
• 发表日期: 2023
• 页码: 3349-3362
• 关键词: residual analysis; PROCESS MODELS; clinical characteristics

摘要

The question addressed here is whether, using Hawkes models. the distribution of SARS-CoV-2 (Covid-19) transmission times can be estimated accurately with only case-count data. We fit Hawkes models with varying productivities to each of the 50 United States individually, estimating for each state a transmission time density, both nonparametrically and using a normal approximation. We find that, for nearly all states, the estimated transmission times are centered near seven days with a standard deviation of approximately one day. Compared to previous reports, the results here suggest that trans-mission times for SARS-CoV-2 are somewhat shorter, on average, and the distribution is less diffuse, though the results also suggest the possibility of transmission occurring on the first day of exposure.