Can scarlet fever trends be used to predict cases of invasive Group A Streptococcal Infections in South East England and London for public health action?
PHE ePoster Library. Hams R. Apr 10, 2019; 257508; 15412
Ms. Rebecca Hams
Ms. Rebecca Hams
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Abstract
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Abstract Scarlet Fever (SF) and invasive Group A Streptococcal (iGAS) infections are both caused by streptococcus pyogenes. While SF is easily treated with antibiotics, iGAS has a 20% mortality rate. Following a threefold increase of SF cases in England from 8.2 per 100,000 (2013) to 27.2 per 100,000 (2014), we aimed to assess if increases in SF cases precede those in iGAS in order to enable actions such as proactive alerting of forecast iGAS incidence.SF and iGAS cases were extracted from case management system records from 01/12/09 to 01/11/18. Date of onset was aggregated by ISO week for each infection. Time series regression models (TSRM) were used to assess associations with different time lags between iGAS and SF, for all years and from 1st January 2014 onwards.Between 01/12/09 to 31/12/13 there was an increasing trend of 3.12 cases per annum (95% CI 2.08, 5.2) in SF cases and 0.52 iGAS cases per annum (95% CI 0.26, 0.78). From 01/01/14 to 01/11/18 the upward trend was 15.6 SF cases per annum (95% CI 5.72, 25.48) and 10.4 iGAS cases per annum (95% CI 6.2, 13.5). Time lag TSRM were not important (p<0.05) after allowing for seasonal pattern and trend.These results suggest that the numbers of preceding cases of SF does not assist in our ability to predict iGAS cases. The strongest association occurs with no time lag between SF and iGAS cases. Increasing trends in the number of cases observed from 2014 onwards is observed with periodicity peaking of both infections in February and March.The lack of associations for lagged SF prevented the use of increases in SF cases to trigger public health messaging to alert potential increases in iGAS. Thus, we recommend that only the regular seasonal pattern can be used to reinforce awareness of iGAS.
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