LIVIVO - Search results -

Search results

Result 1 - 10 of total 876

Search options

Article ; Online: Inferring UK COVID-19 fatal infection trajectories from daily mortality data: Were infections already in decline before the UK lockdowns?

Wood, Simon N

2021 Volume 78, Issue 3, Page(s) 1127–1140

Abstract: The number of new infections per day is a key quantity for effective epidemic management. It can be estimated relatively directly by testing of random population samples. Without such direct epidemiological measurement, other approaches are required to ... ...

Abstract	The number of new infections per day is a key quantity for effective epidemic management. It can be estimated relatively directly by testing of random population samples. Without such direct epidemiological measurement, other approaches are required to infer whether the number of new cases is likely to be increasing or decreasing: for example, estimating the pathogen-effective reproduction number, R, using data gathered from the clinical response to the disease. For coronavirus disease 2019 (Covid-19/SARS-Cov-2), such R estimation is heavily dependent on modelling assumptions, because the available clinical case data are opportunistic observational data subject to severe temporal confounding. Given this difficulty, it is useful to retrospectively reconstruct the time course of infections from the least compromised available data, using minimal prior assumptions. A Bayesian inverse problem approach applied to UK data on first-wave Covid-19 deaths and the disease duration distribution suggests that fatal infections were in decline before full UK lockdown (24 March 2020), and that fatal infections in Sweden started to decline only a day or two later. An analysis of UK data using the model of Flaxman et al. gives the same result under relaxation of its prior assumptions on R, suggesting an enhanced role for non-pharmaceutical interventions short of full lockdown in the UK context. Similar patterns appear to have occurred in the subsequent two lockdowns.
MeSH term(s)	Bayes Theorem ; COVID-19 ; Communicable Disease Control ; Humans ; Retrospective Studies ; SARS-CoV-2 ; United Kingdom/epidemiology
Language	English
Publishing date	2021-04-07
Publishing country	United States
Document type	Journal Article
ZDB-ID	213543-7
ISSN	1541-0420 ; 0099-4987 ; 0006-341X
ISSN (online)	1541-0420
ISSN	0099-4987 ; 0006-341X
DOI	10.1111/biom.13462
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

In stock of ZB MED Cologne/Königswinter

Zs.B 72: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
ab Jg. 2022: Lesesaal (EG)

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Details ▾

Article ; Online: Inferring UK COVID‐19 fatal infection trajectories from daily mortality data: Were infections already in decline before the UK lockdowns?

Wood, Simon N.

Biometrics. 2022 Sept., v. 78, no. 3 p.1127-1140

2022

Abstract	The number of new infections per day is a key quantity for effective epidemic management. It can be estimated relatively directly by testing of random population samples. Without such direct epidemiological measurement, other approaches are required to infer whether the number of new cases is likely to be increasing or decreasing: for example, estimating the pathogen‐effective reproduction number, R, using data gathered from the clinical response to the disease. For coronavirus disease 2019 (Covid‐19/SARS‐Cov‐2), such R estimation is heavily dependent on modelling assumptions, because the available clinical case data are opportunistic observational data subject to severe temporal confounding. Given this difficulty, it is useful to retrospectively reconstruct the time course of infections from the least compromised available data, using minimal prior assumptions. A Bayesian inverse problem approach applied to UK data on first‐wave Covid‐19 deaths and the disease duration distribution suggests that fatal infections were in decline before full UK lockdown (24 March 2020), and that fatal infections in Sweden started to decline only a day or two later. An analysis of UK data using the model of Flaxman et al. gives the same result under relaxation of its prior assumptions on R, suggesting an enhanced role for non‐pharmaceutical interventions short of full lockdown in the UK context. Similar patterns appear to have occurred in the subsequent two lockdowns.
Keywords	Bayesian theory ; COVID-19 infection ; models ; mortality ; observational studies ; reproduction ; Sweden
Language	English
Dates of publication	2022-09
Size	p. 1127-1140.
Publishing place	John Wiley & Sons, Ltd
Document type	Article ; Online
Note	JOURNAL ARTICLE
ZDB-ID	213543-7
ISSN	0099-4987 ; 0006-341X
ISSN	0099-4987 ; 0006-341X
DOI	10.1111/biom.13462
Database	NAL-Catalogue (AGRICOLA)

In stock of ZB MED Bonn / Germany

Z 58/144: Show issues
I/354: Show issues

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: Rejoinder to the discussions of "Spatial+: A novel approach to spatial confounding".

Dupont, Emiko / Wood, Simon N / Augustin, Nicole H

Biometrics

2022 Volume 78, Issue 4, Page(s) 1309–1312

Abstract: In this rejoinder, we set out some of the main points that we took from the discussions of our paper "Spatial+: A novel approach to spatial confounding." The comments provided by the discussants include excellent questions and suggestions for extensions ... ...

Abstract	In this rejoinder, we set out some of the main points that we took from the discussions of our paper "Spatial+: A novel approach to spatial confounding." The comments provided by the discussants include excellent questions and suggestions for extensions and improvements to spatial+. The discussions also highlight the growing interest in understanding spatial confounding, underpinned by the many recent contributions to the literature on this topic.
Language	English
Publishing date	2022-04-01
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	213543-7
ISSN	1541-0420 ; 0099-4987 ; 0006-341X
ISSN (online)	1541-0420
ISSN	0099-4987 ; 0006-341X
DOI	10.1111/biom.13653
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

In stock of ZB MED Cologne/Königswinter

Zs.B 72: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾

Article ; Online: Was R < 1 before the English lockdowns? On modelling mechanistic detail, causality and inference about Covid-19.

Wood, Simon N / Wit, Ernst C

PloS one

2021 Volume 16, Issue 9, Page(s) e0257455

Abstract: Detail is a double edged sword in epidemiological modelling. The inclusion of mechanistic detail in models of highly complex systems has the potential to increase realism, but it also increases the number of modelling assumptions, which become harder to ... ...

Abstract	Detail is a double edged sword in epidemiological modelling. The inclusion of mechanistic detail in models of highly complex systems has the potential to increase realism, but it also increases the number of modelling assumptions, which become harder to check as their possible interactions multiply. In a major study of the Covid-19 epidemic in England, Knock et al. (2020) fit an age structured SEIR model with added health service compartments to data on deaths, hospitalization and test results from Covid-19 in seven English regions for the period March to December 2020. The simplest version of the model has 684 states per region. One main conclusion is that only full lockdowns brought the pathogen reproduction number, R, below one, with R ≫ 1 in all regions on the eve of March 2020 lockdown. We critically evaluate the Knock et al. epidemiological model, and the semi-causal conclusions made using it, based on an independent reimplementation of the model designed to allow relaxation of some of its strong assumptions. In particular, Knock et al. model the effect on transmission of both non-pharmaceutical interventions and other effects, such as weather, using a piecewise linear function, b(t), with 12 breakpoints at selected government announcement or intervention dates. We replace this representation by a smoothing spline with time varying smoothness, thereby allowing the form of b(t) to be substantially more data driven, and we check that the corresponding smoothness assumption is not driving our results. We also reset the mean incubation time and time from first symptoms to hospitalisation, used in the model, to values implied by the papers cited by Knock et al. as the source of these quantities. We conclude that there is no sound basis for using the Knock et al. model and their analysis to make counterfactual statements about the number of deaths that would have occurred with different lockdown timings. However, if fits of this epidemiological model structure are viewed as a reasonable basis for inference about the time course of incidence and R, then without very strong modelling assumptions, the pathogen reproduction number was probably below one, and incidence in substantial decline, some days before either of the first two English national lockdowns. This result coincides with that obtained by more direct attempts to reconstruct incidence. Of course it does not imply that lockdowns had no effect, but it does suggest that other non-pharmaceutical interventions (NPIs) may have been much more effective than Knock et al. imply, and that full lockdowns were probably not the cause of R dropping below one.
MeSH term(s)	COVID-19/epidemiology ; COVID-19/prevention & control ; COVID-19/transmission ; Epidemics ; Hospitalization ; Humans ; Models, Statistical
Language	English
Publishing date	2021-09-22
Publishing country	United States
Document type	Journal Article
ISSN	1932-6203
ISSN (online)	1932-6203
DOI	10.1371/journal.pone.0257455
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article: Did COVID-19 infections decline before UK lockdown?

Wood, Simon N.

Abstract: The number of new infections per day is a key quantity for effective epidemic management. It can be estimated by testing of random population samples. Without such direct epidemiological measurement, other approaches are required to infer whether the ... ...

Abstract	The number of new infections per day is a key quantity for effective epidemic management. It can be estimated by testing of random population samples. Without such direct epidemiological measurement, other approaches are required to infer whether the number of new cases is likely to be increasing or decreasing: for example, estimating the pathogen reproductive rate, R, using data gathered from the clinical response to the disease. For COVID-19 (SARS-CoV-2) such R estimation is heavily dependent on modelling assumptions, because the available clinical case data are opportunistic observational data subject to severe temporal confounding. Given this difficulty it is useful to reconstruct the time course of infections from the least compromised available data, using minimal prior assumptions. A Bayesian inverse problem approach applied to UK data on COVID-19 deaths and the disease duration distribution suggests that infections were in decline before full UK lockdown (24 March 2020), and that infections in Sweden started to decline only a day or two later. An analysis of UK data using the model of Flaxman et al. (2020, Nature 584) gives the same result under relaxation of its prior assumptions on R.
Keywords	covid19
Publisher	ArXiv
Document type	Article
Database	COVID19

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Details ▾

Article: Simple models for COVID-19 death and fatal infection profiles

Wood, Simon N.

Abstract: Simple smooth additive models for the observed death-with-COVID-19 series adequately capture the underlying death rate and strong weekly pattern in the data. Clear inference about peak timing is then possible. Further, inference about the earlier ... ...

Abstract	Simple smooth additive models for the observed death-with-COVID-19 series adequately capture the underlying death rate and strong weekly pattern in the data. Clear inference about peak timing is then possible. Further, inference about the earlier infection rate dynamics driving the death rate dynamics can be treated as a simple Bayesian inverse problem, which can be readily solved by imposing a smoothness assumption on the infection rate. This straightforward semi-parametric approach is substantially better founded than the running mean smoothers which generally form the basis for public debate. In the absence of direct statistically based measurement of infection rates, it also offers a usefully assumption-light approach to data analysis, for comparison with the results of the more assumption-rich process simulation models used to inform policy. An interesting result of the analysis is that it suggests that the number of new daily infections in the UK peaked some days before lock down was implemented, although it does not completely rule out a slightly later peak.
Keywords	covid19
Publisher	ArXiv
Document type	Article
Database	COVID19

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Details ▾

Article ; Online: Why is early-onset atrial fibrillation uncommon in patients with Duchenne muscular dystrophy? Insights from the mdx mouse.

Nguyen, My-Nhan / Hooper, Charlotte / Stefanini, Matilde / Vrellaku, Besarte / Carnicer, Ricardo / Wood, Matthew J / Simon, Jillian N / Casadei, Barbara

Cardiovascular research

2024 Volume 120, Issue 5, Page(s) 519–530

Abstract: Aims: A reduction in both dystrophin and neuronal nitric oxide synthase (NOS1) secondary to microRNA-31 (miR-31) up-regulation contributes to the atrial electrical remodelling that underpins human and experimental atrial fibrillation (AF). In contrast, ... ...

Abstract	Aims: A reduction in both dystrophin and neuronal nitric oxide synthase (NOS1) secondary to microRNA-31 (miR-31) up-regulation contributes to the atrial electrical remodelling that underpins human and experimental atrial fibrillation (AF). In contrast, patients with Duchenne muscular dystrophy (DMD), who lack dystrophin and NOS1 and, at least in the skeletal muscle, have raised miR-31 expression, do not have increase susceptibility to AF in the absence of left ventricular (LV) dysfunction. Here, we investigated whether dystrophin deficiency is also associated with atrial up-regulation of miR-31, loss of NOS1 protein, and increased AF susceptibility in young mdx mice. Methods and results: Echocardiography showed normal cardiac structure and function in 12-13 weeks mdx mice, with no indication by assay of hydroxyproline that atrial fibrosis had developed. The absence of dystrophin in mdx mice was accompanied by an overall reduction in syntrophin and a lower NOS1 protein content in the skeletal muscle and in the left atrial and ventricular myocardium, with the latter occurring alongside reduced Nos1 transcript levels (exons 1-2 by quantitative polymerase chain reaction) and an increase in NOS1 polyubiquitination [assessed using tandem polyubiquitination pulldowns; P < 0.05 vs. wild type (WT)]. Neither the up-regulation of miR-31 nor the substantial reduction in NOS activity observed in the skeletal muscle was present in the atrial tissue of mdx mice. At difference with the skeletal muscle, the mdx atrial myocardium showed a reduction in the constitutive NOS inhibitor, caveolin-1, coupled with an increase in NOS3 serine1177 phosphorylation, in the absence of differences in the protein content of other NOS isoforms or in the relative expression NOS1 splice variants. In line with these findings, transoesophageal atrial burst pacing revealed no difference in AF susceptibility between mdx mice and their WT littermates. Conclusion: Dystrophin depletion is not associated with atrial miR-31 up-regulation, reduced NOS activity, or increased AF susceptibility in the mdx mouse. Compared with the skeletal muscle, the milder atrial biochemical phenotype may explain why patients with DMD do not exhibit a higher prevalence of atrial arrhythmias despite a reduction in NOS1 content.
MeSH term(s)	Animals ; Muscular Dystrophy, Duchenne/metabolism ; Muscular Dystrophy, Duchenne/genetics ; Muscular Dystrophy, Duchenne/complications ; Atrial Fibrillation/metabolism ; Atrial Fibrillation/genetics ; Atrial Fibrillation/physiopathology ; Atrial Fibrillation/etiology ; Atrial Fibrillation/pathology ; Mice, Inbred mdx ; Nitric Oxide Synthase Type I/metabolism ; Nitric Oxide Synthase Type I/genetics ; MicroRNAs/metabolism ; MicroRNAs/genetics ; Disease Models, Animal ; Dystrophin/genetics ; Dystrophin/metabolism ; Humans ; Male ; Mice, Inbred C57BL ; Muscle, Skeletal/metabolism ; Heart Atria/metabolism ; Heart Atria/physiopathology ; Heart Atria/pathology ; Atrial Remodeling ; Mice
Chemical Substances	Nitric Oxide Synthase Type I (EC 1.14.13.39) ; MicroRNAs ; Dystrophin ; Nos1 protein, mouse (EC 1.14.13.39) ; Dmd protein, mouse
Language	English
Publishing date	2024-01-25
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	80340-6
ISSN	1755-3245 ; 0008-6363
ISSN (online)	1755-3245
ISSN	0008-6363
DOI	10.1093/cvr/cvae022
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 565: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Book ; Online: Inferring UK COVID-19 fatal infection trajectories from daily mortality data

Wood, Simon N.

were infections already in decline before the UK lockdowns?

2020

Abstract	The number of new infections per day is a key quantity for effective epidemic management. It can be estimated relatively directly by testing of random population samples. Without such direct epidemiological measurement, other approaches are required to infer whether the number of new cases is likely to be increasing or decreasing: for example, estimating the pathogen effective reproduction number, R, using data gathered from the clinical response to the disease. For Covid-19 (SARS-CoV-2) such R estimation is heavily dependent on modelling assumptions, because the available clinical case data are opportunistic observational data subject to severe temporal confounding. Given this difficulty it is useful to retrospectively reconstruct the time course of infections from the least compromised available data, using minimal prior assumptions. A Bayesian inverse problem approach applied to UK data on first wave Covid-19 deaths and the disease duration distribution suggests that fatal infections were in decline before full UK lockdown (24 March 2020), and that fatal infections in Sweden started to decline only a day or two later. An analysis of UK data using the model of Flaxman et al. (2020, Nature 584) gives the same result under relaxation of its prior assumptions on R, suggesting an enhanced role for non pharmaceutical interventions (NPIs) short of full lock down in the UK context. Similar patterns appear to have occurred in the subsequent two lockdowns. Estimates from the main UK Covid statistical surveillance surveys, available since original publication, support these results. Replication code for the paper is available in the supporting information of doi/10.1111/biom.13462. Comment: Gives the location of the replication code and corrects an accidental deletion in the first line of the conclusions
Keywords	Statistics - Applications ; Quantitative Biology - Populations and Evolution ; covid19
Subject code	310
Publishing date	2020-05-05
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Spatial+: A novel approach to spatial confounding.

Dupont, Emiko / Wood, Simon N / Augustin, Nicole H

Biometrics

2022 Volume 78, Issue 4, Page(s) 1279–1290

Abstract: In spatial regression models, collinearity between covariates and spatial effects can lead to significant bias in effect estimates. This problem, known as spatial confounding, is encountered modeling forestry data to assess the effect of temperature on ... ...

Abstract	In spatial regression models, collinearity between covariates and spatial effects can lead to significant bias in effect estimates. This problem, known as spatial confounding, is encountered modeling forestry data to assess the effect of temperature on tree health. Reliable inference is difficult as results depend on whether or not spatial effects are included in the model. We propose a novel approach, spatial+, for dealing with spatial confounding when the covariate of interest is spatially dependent but not fully determined by spatial location. Using a thin plate spline model formulation we see that, in this case, the bias in covariate effect estimates is a direct result of spatial smoothing. Spatial+ reduces the sensitivity of the estimates to smoothing by replacing the covariates by their residuals after spatial dependence has been regressed away. Through asymptotic analysis we show that spatial+ avoids the bias problems of the spatial model. This is also demonstrated in a simulation study. Spatial+ is straightforward to implement using existing software and, as the response variable is the same as that of the spatial model, standard model selection criteria can be used for comparisons. A major advantage of the method is also that it extends to models with non-Gaussian response distributions. Finally, while our results are derived in a thin plate spline setting, the spatial+ methodology transfers easily to other spatial model formulations.
MeSH term(s)	Models, Statistical ; Computer Simulation ; Spatial Regression ; Bias ; Software
Language	English
Publishing date	2022-03-30
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	213543-7
ISSN	1541-0420 ; 0099-4987 ; 0006-341X
ISSN (online)	1541-0420
ISSN	0099-4987 ; 0006-341X
DOI	10.1111/biom.13656
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

In stock of ZB MED Cologne/Königswinter

Zs.B 72: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾

Article ; Online: Spatial+: A novel approach to spatial confounding

Dupont, Emiko / Wood, Simon N. / Augustin, Nicole H.

Biometrics. 2022 Dec., v. 78, no. 4 p.1279-1290

2022

Abstract	In spatial regression models, collinearity between covariates and spatial effects can lead to significant bias in effect estimates. This problem, known as spatial confounding, is encountered modeling forestry data to assess the effect of temperature on tree health. Reliable inference is difficult as results depend on whether or not spatial effects are included in the model. We propose a novel approach, spatial+, for dealing with spatial confounding when the covariate of interest is spatially dependent but not fully determined by spatial location. Using a thin plate spline model formulation we see that, in this case, the bias in covariate effect estimates is a direct result of spatial smoothing. Spatial+ reduces the sensitivity of the estimates to smoothing by replacing the covariates by their residuals after spatial dependence has been regressed away. Through asymptotic analysis we show that spatial+ avoids the bias problems of the spatial model. This is also demonstrated in a simulation study. Spatial+ is straightforward to implement using existing software and, as the response variable is the same as that of the spatial model, standard model selection criteria can be used for comparisons. A major advantage of the method is also that it extends to models with non‐Gaussian response distributions. Finally, while our results are derived in a thin plate spline setting, the spatial+ methodology transfers easily to other spatial model formulations.
Keywords	computer software ; forestry ; models ; temperature ; tree health
Language	English
Dates of publication	2022-12
Size	p. 1279-1290.
Publishing place	John Wiley & Sons, Ltd
Document type	Article ; Online
Note	JOURNAL ARTICLE
ZDB-ID	213543-7
ISSN	0099-4987 ; 0006-341X
ISSN	0099-4987 ; 0006-341X
DOI	10.1111/biom.13656
Database	NAL-Catalogue (AGRICOLA)

In stock of ZB MED Bonn / Germany

Z 58/144: Show issues
I/354: Show issues

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Details ▾
- See ZB MED holdings
- Order with fees

To top

Full text online

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

In stock of ZB MED Bonn / Germany

Order via subito

Inter-library loan at ZB MED

Full text online

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

Kategorien

Inter-library loan at ZB MED

Kategorien

Inter-library loan at ZB MED

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

In stock of ZB MED Bonn / Germany

Order via subito

Inter-library loan at ZB MED