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COVID-19 trends by CCG level

Using the new algorithm ASMODEE (Automatic Selection of Models and Outlier Detection for Epidemics) we monitor changes in potential COVID-19 cases reported through the NHS pathways, including calls to 111, 999, and 111-online. These analyses are broken down by Clinical Commissioning Groups (CCG). Only the last 6 weeks of data are used. The last week of data is not used to define the temporal trend so that recent outliers can be detected.

Note: this research has not been peer-reviewed yet. This website is still experimental. Please contact the authors before using its content.

Models considered here for trend fitting include:

  • linear regression of counts over time

  • Poisson GLM with a constant rate

  • Negative Binomial GLM with a log-linear effect of time

  • Negative Binomial GLM with a log-linear effect of time and a ‘weekday’ effect distinguishing weekends, Mondays, and the rest of the week

Analyses are run separately for each CCG.

Results: 111/999 calls

Recent observations suggest that 111/999 calls may be more reflective of actual dynamics than 111-online. Therefore, this section only shows analyses based on these data. See next section for results using the whole dataset, i.e. including 111/999 calls and 111-online.

Top 25 CCG

These plots show the 25 CGGs with the most increases in the last 7 days. Future versions will provide plots for all CCGs.

Table summary for all CCGs

Results: 111/999 calls and 111-online

These results reproduce the analyses above using all data, i.e. also including 111-online calls.

Top 25 CCG

These plots show the 25 CGGs with the most increases in the last 7 days. Future versions will provide plots for all CCGs.

Table summary for all CCGs