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As COVID-19 continues to pose significant public health threats, quantifying the effectiveness of different public health interventions is crucial to inform intervention strategies. Using detailed epidemiological and mobility data available for New York City and comprehensive modelling accounting for under-detection, we reconstruct the COVID-19 transmission dynamics therein during the 2020 spring pandemic wave and estimate the effectiveness of two major non-pharmaceutical interventions—lockdown-like measures that reduce contact rates and universal masking. Lockdown-like measures were associated with greater than 50% transmission reduction for all age groups. Universal masking was associated with an approximately 7% transmission reduction overall and up to 20% reduction for 65+ year olds during the first month of implementation. This result suggests that face covering can substantially reduce transmission when lockdown-like measures are lifted but by itself may be insufficient to control SARS-CoV-2 transmission. Overall, findings support the need to implement multiple interventions simultaneously to effectively mitigate COVID-19 spread before the majority of population can be protected through mass-vaccination.

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.

This paper describes a dynamic process of workforce development, implementation, and evaluation of evidence-based practices (EBPs) within an early childhood mental health (ECMH) network serving children birth to five and their families. The key feature of an effective structure and multi-year process to train clinical service providers in evidence-based practices is the capacity building cycle: Assess, Select, Train, Evaluate. The New York City (NYC) ECMH network assessed the capacity and competencies of early childhood clinical practitioners and selected evidence-based practices and models that are: 1) appropriate for the birth to five population, 2) dyadic or family based, and 3) trauma-informed and/or strengths-based. We describe the evaluation, needs assessments, and best practices that support the effective use of evidence-based practices. It is important to flexibly respond to the needs of the community when selecting evidence-based practices, paying particular attention to equity issues. Considerations to note are that the few EBPs available for this birth to five population are costly, have a limited number of trainers, may not have a train-thetrainer model, and rarely have these EBPs been evaluated in multilingual or diverse U.S. communities. The success of implementing a multi-year cycle in NYC lies in having a funded training center closely linked to the workforce.