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This paper presents a statistical analysis of structural changes in the Central England temperature series, one of the longest surface temperature records available. A changepoint analysis is performed to detect abrupt changes, which can be regarded as a preliminary step before further analysis is conducted to identify the causes of the changes (e.g., artificial, human-induced, or natural variability). Regression models with structural breaks, including mean and trend shifts, are fitted to the series and compared via two commonly used multiple changepoint penalized likelihood criteria that balance model fit quality (as measured by likelihood) against parsimony considerations. Our changepoint model fits, with independent and short-memory errors, are also compared with a different class of models termed long-memory models that have been previously used by other authors to describe persistence features in temperature series. In the end, the optimal model is judged to be one containing a changepoint in the late 1980s, with a transition to an intensified warming regime. This timing and warming conclusion is consistent across changepoint models compared in this analysis. The variability of the series is not found to be significantly changing, and shift features are judged to be more plausible than either short- or long-memory autocorrelations. The final proposed model is one including trend shifts (both intercept and slope parameters) with independent errors. The analysis serves as a walk-through tutorial of different changepoint techniques, illustrating what can be statistically inferred. [ABSTRACT FROM AUTHOR]

Gallstone related pathology (GRP) accounts for a significant proportion of general surgery admissions. The aim of this study is to investigate if seasonal variation for GRP admissions exist in England allowing improved resource allocation and planning. This multicentre retrospective cohort study included only emergency adult (≥18 years old) admissions to acute secondary care with ICD-10 codes associated with gallstones between 01/01/2010 to 31/12/2019 in England using Hospital Episode Statistics data. Seasons were defined according to United Kingdom Met Office. A total of 396 879 GRP related admissions were recorded during the specified period, accounting for 1.44% of all emergency admissions. Our study suggests a significant seasonal peak in Summer (n = 102 620) based cumulative admissions per season and a linear regression model (p < 0.001), followed by Autumn (n = 102 267), then Spring (n = 97 807) and finally Winter (n = 94 185). Spectral analysis confirmed there is seasonality in the emergency GRP admissions every 12 months. A forecasting model was shown to be reliable; all observed admissions for 2019 were within the 95% prediction intervals for each month for the proportion of emergency GRP admissions. Resource allocation towards the Summer months to target seasonal peaks in GRP should be considered. [ABSTRACT FROM AUTHOR]