Forecasting the 2017/2018 seasonal influenza epidemic in England using multiple dynamic transmission models: a case study.

BACKGROUND:Since the 2009 A/H1N1 pandemic, Public Health England have developed a suite of real-time statistical models utilising enhanced pandemic surveillance data to nowcast and forecast a future pandemic. Their ability to track seasonal influenza and predict heightened winter healthcare burden in the light of high activity in Australia in 2017 was untested. METHODS:Four transmission models were used in forecasting the 2017/2018 seasonal influenza epidemic in England: a stratified primary care model using daily, region-specific, counts and virological swab positivity of influenza-like illness consultations in general practice (GP); a strain-specific (SS) model using weekly, national GP ILI and virological data; an intensive care model (ICU) using reports of ICU influenza admissions; and a synthesis model that included all data sources. For the first 12 weeks of 2018, each model was applied to the latest data to provide estimates of epidemic parameters and short-term influenza forecasts. The added value of pre-season population susceptibility data was explored. RESULTS:The combined results provided valuable nowcasts of the state of the epidemic. Short-term predictions of burden on primary and secondary health services were initially highly variable before reaching consensus beyond the observed peaks in activity between weeks 3-4 of 2018. Estimates for R0 were consistent over time for three of the four models until week 12 of 2018, and there was consistency in the estimation of R0 across the SPC and SS models, and in the ICU attack rates estimated by the ICU and the synthesis model. Estimation and predictions varied according to the assumed levels of pre-season immunity. CONCLUSIONS:This exercise successfully applied a range of pandemic models to seasonal influenza. Forecasting early in the season remains challenging but represents a crucially important activity to inform planning. Improved knowledge of pre-existing levels of immunity would be valuable

ICAR: endoscopic skull‐base surgery

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Forecasting the 2017/2018 seasonal influenza epidemic in England using multiple dynamic transmission models: a case study

BACKGROUND: Since the 2009 A/H1N1 pandemic, Public Health England have developed a suite of real-time statistical models utilising enhanced pandemic surveillance data to nowcast and forecast a future pandemic. Their ability to track seasonal influenza and predict heightened winter healthcare burden in the light of high activity in Australia in 2017 was untested. METHODS: Four transmission models were used in forecasting the 2017/2018 seasonal influenza epidemic in England: a stratified primary care model using daily, region-specific, counts and virological swab positivity of influenza-like illness consultations in general practice (GP); a strain-specific (SS) model using weekly, national GP ILI and virological data; an intensive care model (ICU) using reports of ICU influenza admissions; and a synthesis model that included all data sources. For the first 12 weeks of 2018, each model was applied to the latest data to provide estimates of epidemic parameters and short-term influenza forecasts. The added value of pre-season population susceptibility data was explored. RESULTS: The combined results provided valuable nowcasts of the state of the epidemic. Short-term predictions of burden on primary and secondary health services were initially highly variable before reaching consensus beyond the observed peaks in activity between weeks 3-4 of 2018. Estimates for R0 were consistent over time for three of the four models until week 12 of 2018, and there was consistency in the estimation of R0 across the SPC and SS models, and in the ICU attack rates estimated by the ICU and the synthesis model. Estimation and predictions varied according to the assumed levels of pre-season immunity. CONCLUSIONS: This exercise successfully applied a range of pandemic models to seasonal influenza. Forecasting early in the season remains challenging but represents a crucially important activity to inform planning. Improved knowledge of pre-existing levels of immunity would be valuable

Interplay of constipation, intestinal barrier dysfunction and fungal exposome in aetiopathogensis of Parkinson’s disease; hypothesis with supportive data

Constipation is a forerunner to Parkinson’s disease (PD) diagnosis, worsening thereafter. We explore the relationship of intestinal barrier dysfunction to constipation, and whether intestinal fungal load is an aggravating factor. Fungal load was quantified by real-time PCR, using ITS1F-ITS2 primer-set, on microbial DNA-extract from stool in 68 participants with PD, 102 without. Fungal load was 60% higher per decade after age 60 years, with no PD-status interaction with age. After age adjustment, it was associated inversely with dietary renal acid load. It was unrelated to presence of constipation or barrier dysfunction. Neither consumption of antimicrobials nor of other targeted exogenous substances was associated. Enzyme-linked-immunosorbent assays measured barrier dysfunction markers, faecal alpha-1 antitrypsin and zonulin and serum intestinal-fatty-acid-binding-protein. Barrier dysfunction was associated with constipation and slower colonic transit. Functional constipation was 28% more frequent with a doubling of alpha-1 antitrypsin concentration. More colonic-transit-test markers were retained in transverse colon, the higher alpha-1 antitrypsin and zonulin concentrations, anatomically spotlighting abnormality for entire colon. In contrast, the concentration of the small intestinal barrier marker, fatty-acid-binding-protein, was associated with looser stool consistency, that is consistent with secondary microbial overgrowth. By showing the relationship of intestinal barrier dysfunction to constipation, this study supports the hypothesis that dysfunction may be consequential. Dysfunction may be a necessary, but not sufficient, precursor to PD, in allowing inflammaging. Since ageing is the clearest risk for PD, a gut pathogen escalating in abundance from the sixth decade, integral to fungal load, whose reproduction and virulence is favoured by alkalinity, tallies