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COVID-19 Transmission Dynamics and Effectiveness of Public Health Interventions in New York City during the 2020 Spring Pandemic Wave
Wan Yang; Jaimie Shaff; Jeffrey Shaman.
Affiliation
  • Wan Yang; Columbia University
  • Jaimie Shaff; New York City Department of Health and Mental Hygiene
  • Jeffrey Shaman; Columbia University
Preprint in English | medRxiv | ID: ppmedrxiv-20190710
ABSTRACT
New York City experienced a large COVID-19 pandemic wave during March - May 2020. We model the transmission dynamics of COVID-19 in the city during the pandemic and estimate the effectiveness of public health interventions (overall and for each major intervention separately) for the entire population and by age group. We estimate that the overall effective reproductive number was 2.99 at the beginning of the pandemic wave and reduced to 0.93 one week after the stay-at-home mandate. Most age groups experienced similar reductions in transmission. Interventions reducing contact rates were associated with a 70.7% (95% CI 65.0 - 76.4%) reduction of transmission overall and > 50% for all age groups during the pandemic. Face covering was associated with a 6.6% (95% CI 0.8 - 12.4%) reduction of transmission overall and up to 20% for 65+ year-olds during the first month of implementation. Accounting for the amount of time masks are in use (i.e. mainly outside homes), these findings indicate universal masking could reduce transmission by up to 28-32% when lockdown-like measures are lifted, if the high effectiveness estimated for older adults were achieved for all ages. These estimates are verified by out-of-fit projections and support the need for implementing multiple interventions simultaneously in order to effectively mitigate the spread of COVID-19.
License
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Full text: Available Collection: Preprints Database: medRxiv Type of study: Experimental_studies / Rct Language: English Year: 2020 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Type of study: Experimental_studies / Rct Language: English Year: 2020 Document type: Preprint
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