BACKGROUND AND OBJECTIVE: The reported impacts of the COVID-19 pandemic on child maltreatment in the United States have been mixed. Encounter trends for child physical abuse within pediatric emergency departments may provide insights. Thus, this study sought to determine the change in the rate of emergency department encounters related to child physical abuse. METHODS: A retrospective study within the Pediatric Emergency Care Applied Research Network Registry. Encounters related to child physical abuse were identified by 3 methods: child physical abuse diagnoses among all ages, age-restricted high-risk injury, or age-restricted skeletal survey completion. The primary outcomes were encounter rates per day and clinical severity before (January 2018–March 2020) and during the COVID-19 pandemic (April 2020–March 2021). Multivariable Poisson regression models were fit to estimate rate ratios with marginal estimation methods. RESULTS: Encounter rates decreased significantly during the pandemic for 2 of 3 identification methods. In fully adjusted models, encounter rates were reduced by 19% in the diagnosis-code cohort (adjusted rate ratio: 0.81 [99% confidence interval: 0.75–0.88], P <.001), with the greatest reduction among preschool and school-aged children. Encounter rates decreased 10% in the injury cohort (adjusted rate ratio: 0.90 [confidence interval: 0.82–0.98], P = .002). For all 3 methods, rates for lower-severity encounters were significantly reduced whereas higher-severity encounters were not. CONCLUSIONS: Encounter rates for child physical abuse were reduced or unchanged. Reductions were greatest for lower-severity encounters and preschool and school-aged children. This pattern calls for critical assessment to clarify whether pandemic changes led to true reductions versus decreased recognition of child physical abuse.

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In many natural and technological systems the rule that governs the system’s dynamics changes over time. In such switched systems the system’s switching can be a significant source of instability. Here we give a simple sufficient criterium to determine if an i.i.d. stochastically switched system is stable in expectation. This method extends recent results for linear switched systems to nonlinear switched systems. It also extends results known for general switched systems giving improved results for systems with i.i.d. stochastic switching. The paper also considers the effects of time-delays on the stability of switched systems. Such time delays, which are intrinsic to any real-world system, can also have a destabilising effect on the system’s dynamics. Previously, it has been shown that if a dynamical system is intrinsically stable, which is a stronger form of global stability, then it maintains its stability even when time-delays are introduced into the system. Here we extend this notion to stochastically switched systems. We refer to this type of stability as patient stability and give a simple sufficient criterium under which such systems are patiently stable, i.e. cannot be destabilised by time delays. Both criteria introduced in this paper side step the need to use Lyapunov, linear matrix inequalities, and semi-definite programming-type methods. Our examples in this paper demonstrate the simplicity of these criteria.