ABSTRACT
BackgroundNon-pharmaceutical interventions (NPI) play a key role in managing epidemics, yet it is challenging to evaluate their impacts on disease spread and outcomes. MethodsTo estimate the effect of a mask-wearing intervention to mitigate the spread of SARS-CoV-2 on the island of Ireland, we focused on the potential for interindividual infectious contact over time as the outcome. This is difficult to measure directly; in a companion paper we estimated it using a multi-strain epidemiological model. We used data on mask-wearing and mobility in both Northern Ireland (NI) and the Republic of Ireland (ROI) to predict independently the estimated infectious contact over time. We made counterfactual predictions of infectious contact rates and hospitalisations under a hypothetical intervention where 90% of the population were wearing masks during early 2020, when in reality few people were wearing masks in public; this was mandated in both jurisdictions on 10th August 2020. ResultsThere were 1601 hospitalisations with COVID-19 in NI between 12th March and 10th August 2020, and 1521 in ROI between 3rd April and 10th August 2020. Under the counterfactual mask-wearing scenario, we estimated 512 (95% CI 400, 730) hospitalisations in NI, and 344 (95% CI 266, 526) in ROI, during the same periods. ConclusionsWe have estimated a large effect of population mask-wearing on COVID-19 hospitalisations. This could be partly due to other factors that were also changing over time.
ABSTRACT
Mathematical modelling plays a key role in understanding and predicting the epidemiological dynamics of infectious diseases. We construct a flexible discrete-time model that incorporates multiple viral strains with different transmissibilities to estimate the changing infectious contact that generates new infections. Using a Bayesian approach, we fit the model to longitudinal data on hospitalisation with COVID-19 from the Republic of Ireland and Northern Ireland during the first year of the pandemic. We describe the estimated change in infectious contact in the context of governmentmandated non-pharmaceutical interventions in the two jurisdictions on the island of Ireland. We take advantage of the fitted model to conduct counterfactual analyses exploring the impact of lockdown timing and introducing a novel, more transmissible variant. We found substantial differences in infectious contact between the two jurisdictions during periods of varied restriction easing and December holidays. Our counterfactual analyses reveal that implementing lockdowns earlier would have decreased subsequent hospitalisation substantially in most, but not all cases, and that an introduction of a more transmissible variant - without necessarily being more severe - can cause a large impact on the health care burden.
ABSTRACT
Background@#and Purpose The association of dyslipidemia with stroke has been inconsistent, which may be due to differing associations within etiological stroke subtypes. We sought to determine the association of lipoproteins and apolipoproteins within stroke subtypes. @*Methods@#Standardized incident case-control STROKE study in 32 countries. Cases were patients with acute hospitalized first stroke, and matched by age, sex and site to controls. Concentrations of total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (apoA1), and apoB were measured. Non-HDL-C was calculated. We estimated multivariable odds ratio (OR) and population attributable risk percentage (PAR%). Outcome measures were all stroke, ischemic stroke (and subtypes), and intracerebral hemorrhage (ICH). @*Results@#Our analysis included 11,898 matched case-control pairs; 77.3% with ischemic stroke and 22.7% with ICH. Increasing apoB (OR, 1.10; 95% confidence interval [CI], 1.06 to 1.14 per standard deviation [SD]) and LDL-C (OR, 1.06; 95% CI, 1.02 to 1.10 per SD) were associated with an increase in risk of ischemic stroke, but a reduced risk of ICH. Increased apoB was significantly associated with large vessel stroke (PAR 13.4%; 95% CI, 5.6 to 28.4) and stroke of undetermined cause. Higher HDL-C (OR, 0.75; 95% CI, 0.72 to 0.78 per SD) and apoA1 (OR, 0.63; 95% CI, 0.61 to 0.66 per SD) were associated with ischemic stroke (and subtypes). While increasing HDL-C was associated with an increased risk of ICH (OR, 1.20; 95% CI, 1.14 to 1.27 per SD), apoA1 was associated with a reduced risk (OR, 0.80; 95% CI, 0.75 to 0.85 per SD). ApoB/A1 (OR, 1.38; 95% CI, 1.32 to 1.44 per SD) had a stronger magnitude of association than the ratio of LDL-C/HDL-C (OR, 1.26; 95% CI, 1.21 to 1.31 per SD) with ischemic stroke (P<0.0001). @*Conclusions@#The pattern and magnitude of association of lipoproteins and apolipoproteins with stroke varies by etiological stroke subtype. While the directions of association for LDL, HDL, and apoB were opposing for ischemic stroke and ICH, apoA1 was associated with a reduction in both ischemic stroke and ICH. The ratio of apoB/A1 was the best lipid predictor of ischemic stroke risk.
