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Article: The impact of modelling choices on modelling outcomes: a spatio-temporal study of the association between COVID-19 spread and environmental conditions in Catalonia (Spain).

Briz-Redón, Álvaro

Stochastic environmental research and risk assessment : research journal

2021 Volume 35, Issue 8, Page(s) 1701–1713

Abstract: The choices that researchers make while conducting a statistical analysis usually have a notable impact on the results. This fact has become evident in the ongoing research of the association between the environment and the evolution of the coronavirus ... ...

Abstract	The choices that researchers make while conducting a statistical analysis usually have a notable impact on the results. This fact has become evident in the ongoing research of the association between the environment and the evolution of the coronavirus disease 2019 (COVID-19) pandemic, in light of the hundreds of contradictory studies that have already been published on this issue in just a few months. In this paper, a COVID-19 dataset containing the number of daily cases registered in the regions of Catalonia (Spain) since the start of the pandemic to the end of August 2020 is analysed using statistical models of diverse levels of complexity. Specifically, the possible effect of several environmental variables (solar exposure, mean temperature, and wind speed) on the number of cases is assessed. Thus, the first objective of the paper is to show how the choice of a certain type of statistical model to conduct the analysis can have a severe impact on the associations that are inferred between the covariates and the response variable. Secondly, it is shown how the use of spatio-temporal models accounting for the nature of the data allows understanding the evolution of the pandemic in space and time. The results suggest that even though the models fitted to the data correctly capture the evolution of COVID-19 in space and time, determining whether there is an association between the spread of the pandemic and certain environmental conditions is complex, as it is severely affected by the choice of the model.
Language	English
Publishing date	2021-01-03
Publishing country	Germany
Document type	Journal Article
ZDB-ID	1481263-0
ISSN	1436-3259 ; 1435-151X ; 1436-3240 ; 0931-1955
ISSN (online)	1436-3259 ; 1435-151X
ISSN	1436-3240 ; 0931-1955
DOI	10.1007/s00477-020-01965-z
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: The impact of modelling choices on modelling outcomes: a spatio-temporal study of the association between COVID-19 spread and environmental conditions in Catalonia (Spain)

Briz-Redón, Álvaro

Stochastic environmental research and risk assessment. 2021 Aug., v. 35, no. 8

2021

Abstract	The choices that researchers make while conducting a statistical analysis usually have a notable impact on the results. This fact has become evident in the ongoing research of the association between the environment and the evolution of the coronavirus disease 2019 (COVID-19) pandemic, in light of the hundreds of contradictory studies that have already been published on this issue in just a few months. In this paper, a COVID-19 dataset containing the number of daily cases registered in the regions of Catalonia (Spain) since the start of the pandemic to the end of August 2020 is analysed using statistical models of diverse levels of complexity. Specifically, the possible effect of several environmental variables (solar exposure, mean temperature, and wind speed) on the number of cases is assessed. Thus, the first objective of the paper is to show how the choice of a certain type of statistical model to conduct the analysis can have a severe impact on the associations that are inferred between the covariates and the response variable. Secondly, it is shown how the use of spatio-temporal models accounting for the nature of the data allows understanding the evolution of the pandemic in space and time. The results suggest that even though the models fitted to the data correctly capture the evolution of COVID-19 in space and time, determining whether there is an association between the spread of the pandemic and certain environmental conditions is complex, as it is severely affected by the choice of the model.
Keywords	COVID-19 infection ; data collection ; evolution ; pandemic ; research ; risk assessment ; space and time ; statistical analysis ; statistical models ; temperature ; wind speed ; Spain
Language	English
Dates of publication	2021-08
Size	p. 1701-1713.
Publishing place	Springer Berlin Heidelberg
Document type	Article
ZDB-ID	1481263-0
ISSN	1436-3259 ; 1435-151X ; 1436-3240 ; 0931-1955
ISSN (online)	1436-3259 ; 1435-151X
ISSN	1436-3240 ; 0931-1955
DOI	10.1007/s00477-020-01965-z
Database	NAL-Catalogue (AGRICOLA)

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Article: On the association between COVID-19 vaccination levels and incidence and lethality rates at a regional scale in Spain.

Briz-Redón, Álvaro / Serrano-Aroca, Ángel

Stochastic environmental research and risk assessment : research journal

2022 Volume 36, Issue 9, Page(s) 2941–2948

Abstract: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the coronavirus disease 2019 (COVID-19), has led to the deepest global health and economic crisis of the current century. This dramatic situation has forced the public health ... ...

Abstract	The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the coronavirus disease 2019 (COVID-19), has led to the deepest global health and economic crisis of the current century. This dramatic situation has forced the public health authorities and pharmaceutical companies to develop anti-COVID-19 vaccines in record time. Currently, almost 80% of the population are vaccinated with the required number of doses in Spain. Thus, in this paper, COVID-19 incidence and lethality rates are analyzed through a segmented spatio-temporal regression model that allows studying if there is an association between a certain vaccination level and a change (in mean) in either the incidence or the lethality rates. Spatial dependency is included by considering the Besag-York-Mollié model, whereas natural cubic splines are used for capturing the temporal structure of the data. Lagged effects between the exposure and the outcome are also taken into account. The results suggest that COVID-19 vaccination has not allowed yet (as of September 2021) to observe a consistent reduction in incidence levels at a regional scale in Spain. In contrast, the lethality rates have displayed a declining tendency which has associated with vaccination levels above 50%.
Language	English
Publishing date	2022-01-05
Publishing country	Germany
Document type	Journal Article
ZDB-ID	1481263-0
ISSN	1436-3259 ; 1435-151X ; 1436-3240 ; 0931-1955
ISSN (online)	1436-3259 ; 1435-151X
ISSN	1436-3240 ; 0931-1955
DOI	10.1007/s00477-021-02166-y
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: On the association between COVID-19 vaccination levels and incidence and lethality rates at a regional scale in Spain

Briz-Redón, Álvaro / Serrano-Aroca, Ángel

Stochastic environmental research and risk assessment. 2022 Sept., v. 36, no. 9

2022

Abstract	The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the coronavirus disease 2019 (COVID-19), has led to the deepest global health and economic crisis of the current century. This dramatic situation has forced the public health authorities and pharmaceutical companies to develop anti-COVID-19 vaccines in record time. Currently, almost 80% of the population are vaccinated with the required number of doses in Spain. Thus, in this paper, COVID-19 incidence and lethality rates are analyzed through a segmented spatio-temporal regression model that allows studying if there is an association between a certain vaccination level and a change (in mean) in either the incidence or the lethality rates. Spatial dependency is included by considering the Besag–York–Mollié model, whereas natural cubic splines are used for capturing the temporal structure of the data. Lagged effects between the exposure and the outcome are also taken into account. The results suggest that COVID-19 vaccination has not allowed yet (as of September 2021) to observe a consistent reduction in incidence levels at a regional scale in Spain. In contrast, the lethality rates have displayed a declining tendency which has associated with vaccination levels above 50%.
Keywords	COVID-19 infection ; Severe acute respiratory syndrome coronavirus 2 ; death ; economic crises ; models ; public health ; regression analysis ; research ; risk assessment ; vaccination ; Spain
Language	English
Dates of publication	2022-09
Size	p. 2941-2948.
Publishing place	Springer Berlin Heidelberg
Document type	Article
ZDB-ID	1481263-0
ISSN	1436-3259 ; 1435-151X ; 1436-3240 ; 0931-1955
ISSN (online)	1436-3259 ; 1435-151X
ISSN	1436-3240 ; 0931-1955
DOI	10.1007/s00477-021-02166-y
Database	NAL-Catalogue (AGRICOLA)

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Book ; Online: The impact of modelling choices on modelling outcomes

Briz-Redón, Álvaro

a spatio-temporal study of the association between COVID-19 spread and environmental conditions in Catalonia (Spain)

2020

Abstract	The choices that researchers make while conducting a statistical analysis usually have a notable impact on the results. This fact has become evident in the ongoing research of the association between the environment and the evolution of the COVID-19 pandemic, in light of the hundreds of contradictory studies that have already been published on this issue in just a few months. In this paper, a COVID-19 dataset containing the number of daily cases registered in the regions of Catalonia (Spain) since the start of the pandemic is analysed. Specifically, the possible effect of several environmental variables (solar exposure, mean temperature, and wind speed) on the number of cases is assessed. Thus, the first objective of the paper is to show how the choice of a certain type of statistical model to conduct the analysis can have a severe impact on the associations that are inferred between the covariates and the response variable. Secondly, it is shown how the use of spatio-temporal models accounting for the nature of the data allows understanding the evolution of the pandemic in space and time.
Keywords	Statistics - Applications ; covid19
Subject code	306
Publishing date	2020-09-26
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: A city-level analysis of PM

Briz-Redón, Álvaro / Belenguer-Sapiña, Carolina / Serrano-Aroca, Ángel

Journal of environmental health science & engineering

2022 Volume 20, Issue 1, Page(s) 395–403

Language	English
Publishing date	2022-01-06
Publishing country	England
Document type	Journal Article
ZDB-ID	2756287-6
ISSN	2052-336X
ISSN	2052-336X
DOI	10.1007/s40201-022-00786-2
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: SpNetPrep

Álvaro Briz-Redón

Research Ideas and Outcomes, Vol 5, Iss , Pp 1-

An R package using Shiny to facilitate spatial statistics on road networks

2019 Volume 17

Abstract: Spatial statistics is an important field of data science with many applications in very different areas of study such as epidemiology, criminology, seismology, astronomy and econometrics, among others. In particular, spatial statistics has frequently ... ...

Abstract	Spatial statistics is an important field of data science with many applications in very different areas of study such as epidemiology, criminology, seismology, astronomy and econometrics, among others. In particular, spatial statistics has frequently been used to analyze traffic accidents datasets with explanatory and preventive objectives. Traditionally, these studies have employed spatial statistics techniques at some level of areal aggregation, usually related to administrative units. However, last decade has brought an increasing number of works on the spatial incidence and distribution of traffic accidents at the road level by means of the spatial structure known as a linear network. This change seems positive because it could provide deeper and more accurate investigations than previous studies that were based on areal spatial units. The interest in working at the road level renders some technical difficulties due to the high complexity of these structures, specially in terms of manipulation and rectification. The R Shiny app SpNetPrep, which is available online and via an R package named the same way, has the goal of providing certain functionalities that could be useful for a user which is interested in performing an spatial analysis over a road network structure.
Keywords	R package ; spatial statistics ; linear networks ; Science ; Q
Language	English
Publishing date	2019-02-01T00:00:00Z
Publisher	Pensoft Publishers
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A mechanistic spatio-temporal modeling of COVID-19 data.

Briz-Redón, Álvaro / Iftimi, Adina / Mateu, Jorge / Romero-García, Carolina

Biometrical journal. Biometrische Zeitschrift

2022 Volume 65, Issue 1, Page(s) e2100318

Abstract: Understanding the evolution of an epidemic is essential to implement timely and efficient preventive measures. The availability of epidemiological data at a fine spatio-temporal scale is both novel and highly useful in this regard. Indeed, having ... ...

Abstract	Understanding the evolution of an epidemic is essential to implement timely and efficient preventive measures. The availability of epidemiological data at a fine spatio-temporal scale is both novel and highly useful in this regard. Indeed, having geocoded data at the case level opens the door to analyze the spread of the disease on an individual basis, allowing the detection of specific outbreaks or, in general, of some interactions between cases that are not observable if aggregated data are used. Point processes are the natural tool to perform such analyses. We analyze a spatio-temporal point pattern of Coronavirus disease 2019 (COVID-19) cases detected in Valencia (Spain) during the first 11 months (February 2020 to January 2021) of the pandemic. In particular, we propose a mechanistic spatio-temporal model for the first-order intensity function of the point process. This model includes separate estimates of the overall temporal and spatial intensities of the model and a spatio-temporal interaction term. For the latter, while similar studies have considered different forms of this term solely based on the physical distances between the events, we have also incorporated mobility data to better capture the characteristics of human populations. The results suggest that there has only been a mild level of spatio-temporal interaction between cases in the study area, which to a large extent corresponds to people living in the same residential location. Extending our proposed model to larger areas could help us gain knowledge on the propagation of COVID-19 across cities with high mobility levels.
MeSH term(s)	Humans ; COVID-19/epidemiology ; Spatio-Temporal Analysis ; Disease Outbreaks ; Pandemics ; Cities
Language	English
Publishing date	2022-08-07
Publishing country	Germany
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	131640-0
ISSN	1521-4036 ; 0323-3847 ; 0006-3452
ISSN (online)	1521-4036
ISSN	0323-3847 ; 0006-3452
DOI	10.1002/bimj.202100318
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Article: SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks

Briz-Redón, Álvaro

Research Ideas and Outcomes. 2019 Feb. 01, v. 5

2019

Abstract	Spatial statistics is an important field of data science with many applications in very different areas of study such as epidemiology, criminology, seismology, astronomy and econometrics, among others. In particular, spatial statistics has frequently been used to analyze traffic accidents datasets with explanatory and preventive objectives. Traditionally, these studies have employed spatial statistics techniques at some level of areal aggregation, usually related to administrative units. However, last decade has brought an increasing number of works on the spatial incidence and distribution of traffic accidents at the road level by means of the spatial structure known as a linear network. This change seems positive because it could provide deeper and more accurate investigations than previous studies that were based on areal spatial units. The interest in working at the road level renders some technical difficulties due to the high complexity of these structures, specially in terms of manipulation and rectification. The R Shiny app SpNetPrep, which is available online and via an R package named the same way, has the goal of providing certain functionalities that could be useful for a user which is interested in performing an spatial analysis over a road network structure.
Keywords	criminology ; data collection ; econometrics ; epidemiology ; geophysics ; research ; roads ; statistics ; traffic
Language	English
Dates of publication	2019-0201
Publishing place	Pensoft Publishers
Document type	Article
ZDB-ID	2833254-4
ISSN	2367-7163
ISSN	2367-7163
DOI	10.3897/rio.5.e33521
Database	NAL-Catalogue (AGRICOLA)

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Article: Changing delta hepatitis patient profile: A single center experience in Valencia region, Spain.

Hernàndez-Èvole, Helena / Briz-Redón, Álvaro / Berenguer, Marina

World journal of hepatology

2020 Volume 12, Issue 6, Page(s) 277–287

Abstract: Background: Delta hepatitis is a rare infection with an aggressive disease course. For almost three decades, however, there have been no epidemiological studies in our traditionally endemic area.: Aim: To investigate the prevalence of delta hepatitis ...

Abstract	Background: Delta hepatitis is a rare infection with an aggressive disease course. For almost three decades, however, there have been no epidemiological studies in our traditionally endemic area. Aim: To investigate the prevalence of delta hepatitis in a sample of patients with chronic hepatitis B virus (HBV) infection followed at a Hepatology Unit in Valencia, Spain. Methods: Retrospective evaluation of anti-hepatitis D virus-immunoglobulin G seroprevalence among patients with chronic HBV infection ( Results: The prevalence of anti-hepatitis D virus-immunoglobulin G among HBV-infected patients was 11.5%: Male (63%) and median age of 52 years. The majority were born in Spain (67%) and primarily infected through intravenous drug use. However, a significant percent (24.5%), particularly those diagnosed in more recent years, were migrants presumably nosocomially infected. Comorbidities such as diabetes (8.5%), obesity/overweight (55%), and alcohol consumption (34%) were frequent. A high proportion of patients developed liver complications such as cirrhosis (77%), liver decompensation (81%), hepatocellular carcinoma (HCC) (16.5%), or required liver transplantation (LT) (59.5%). Diabetes was associated with progression to cirrhosis, LT, and death. Male sex, increasing age, and alcohol were associated with LT and HCC. Compared to HBV mono-infected patients, delta individuals developed cirrhosis and liver decompensation more frequently, with no differences in HCC rates. Conclusion: Patients infected in the 1980's were mostly locals infected through intravenous drug use, whereas those diagnosed recently are frequently non-Spanish natives from endemic areas. Regardless of their origin, patients are predominantly male with significant comorbidities, which potentially play a major role in disease progression. We confirm a high rate of subsequent liver complications.
Language	English
Publishing date	2020-07-08
Publishing country	United States
Document type	Journal Article
ZDB-ID	2573703-X
ISSN	1948-5182
ISSN	1948-5182
DOI	10.4254/wjh.v12.i6.277
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