<|begin_of_text|><|start_header_id|>system<|end_header_id|>

You are an expert at identifying data availability statements in scientific text. A data availability statement describes where research data can be found or how it can be accessed.<|eot_id|><|start_header_id|>user<|end_header_id|>

Determine if the following text contains a data availability statement. Answer with 'yes' or 'no'.

Text: Lastly, interrupted time series analysis was employed to examine COVID-19's impact on police reactive and proactive activities. In time series data, observations have a natural temporal ordering. Observations close in time may have stronger correlations than observations further apart. Because of this non-independence or autocorrelation, t-tests may not be able to detect the intervention effect adequately. Interrupted time series analysis using ARIMA modeling, which not only features a quasiexperimental design, but also takes into consideration of the autoregressive moving-average process of the data, would produce statistically more rigorous findings. Based on the results of the augmented Dickey-Fuller tests, as well as examinations of both an auto-correlation function (ACF) and partial auto-correlation function (PACF), ARIMA models for different types of policing activities were identified and analyzed. A binary variable (before-after-March 12, 2020) was set up to examine the interrupted effects of the COVID-19. In the case of examining the patrol and DRT self-initiated activities, to control for the step change between the emergence of COVID-19 and the death of George Floyd, the indicator of the George Floyd incident was also included in the models. Fig. 1 presents the time sequence trend graphs for each reactivity and proactivity measure. With respect to reactivity, violent crime calls appeared to increase slightly after COVID-19. For calls for property crime, there appeared to be a reduction coinciding with COVID-19, but then a return to pre-COVID levels. Disorder calls varied greatly pre-COVID, with observable increases and decreases, but appeared to increase after COVID-19. Suspicious incident CFS exhibited a decreased trend that continued after COVID-19, but with periodic fluctuations. Traffic-related CFS notably declined after COVID-19. The visual examination of the plotted time series **data** for serviced-related activity calls suggested a decrease with the emergence of COVID-19. For non-crime events, there appeared to be a decreased trend before and after COVID-19.<|eot_id|><|start_header_id|>assistant<|end_header_id|>

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