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  1. Article ; Online: Correction: Analysis of zero inflated dichotomous variables from a Bayesian perspective: application to occupational health.

    Moriña, David / Puig, Pedro / Navarro, Albert

    BMC medical research methodology

    2022  Volume 22, Issue 1, Page(s) 210

    Language English
    Publishing date 2022-08-04
    Publishing country England
    Document type Published Erratum
    ZDB-ID 2041362-2
    ISSN 1471-2288 ; 1471-2288
    ISSN (online) 1471-2288
    ISSN 1471-2288
    DOI 10.1186/s12874-022-01697-4
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Left-censored recurrent event analysis in epidemiological studies: a proposal for when the number of previous episodes is unknown.

    Hernández-Herrera, Gilma / Moriña, David / Navarro, Albert

    BMC medical research methodology

    2022  Volume 22, Issue 1, Page(s) 20

    Abstract: Background: When dealing with recurrent events in observational studies it is common to include subjects who became at risk before follow-up. This phenomenon is known as left censoring, and simply ignoring these prior episodes can lead to biased and ... ...

    Abstract Background: When dealing with recurrent events in observational studies it is common to include subjects who became at risk before follow-up. This phenomenon is known as left censoring, and simply ignoring these prior episodes can lead to biased and inefficient estimates. We aimed to propose a statistical method that performs well in this setting.
    Methods: Our proposal was based on the use of models with specific baseline hazards. In this, the number of prior episodes were imputed when unknown and stratified according to whether the subject had been at risk of presenting the event before t = 0. A frailty term was also used. Two formulations were used for this "Specific Hazard Frailty Model Imputed" based on the "counting process" and "gap time." Performance was then examined in different scenarios through a comprehensive simulation study.
    Results: The proposed method performed well even when the percentage of subjects at risk before follow-up was very high. Biases were often below 10% and coverages were around 95%, being somewhat conservative. The gap time approach performed better with constant baseline hazards, whereas the counting process performed better with non-constant baseline hazards.
    Conclusions: The use of common baseline methods is not advised when knowledge of prior episodes experienced by a participant is lacking. The approach in this study performed acceptably in most scenarios in which it was evaluated and should be considered an alternative in this context. It has been made freely available to interested researchers as R package miRecSurv.
    MeSH term(s) Bias ; Computer Simulation ; Epidemiologic Studies ; Humans ; Models, Statistical ; Proportional Hazards Models ; Research Design
    Language English
    Publishing date 2022-01-16
    Publishing country England
    Document type Journal Article
    ZDB-ID 2041362-2
    ISSN 1471-2288 ; 1471-2288
    ISSN (online) 1471-2288
    ISSN 1471-2288
    DOI 10.1186/s12874-022-01503-1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Analysis of the impact of lockdown on the reproduction number of the SARS-Cov-2 in Spain.

    Hyafil, Alexandre / Moriña, David

    Gaceta sanitaria

    2020  Volume 35, Issue 5, Page(s) 453–458

    Abstract: Objective: The late 2019 COVID-19 outbreak has put the health systems of many countries to the limit of their capacity. The most affected European countries are, so far, Italy and Spain. In both countries (and others), the authorities decreed a lockdown, ...

    Abstract Objective: The late 2019 COVID-19 outbreak has put the health systems of many countries to the limit of their capacity. The most affected European countries are, so far, Italy and Spain. In both countries (and others), the authorities decreed a lockdown, with local specificities. The objective of this work is to evaluate the impact of the measures undertaken in Spain to deal with the pandemic.
    Method: We estimated the number of cases and the impact of lockdown on the reproducibility number based on the hospitalization reports up to April 15th 2020.
    Results: The estimated number of cases shows a sharp increase until the lockdown, followed by a slowing down and then a decrease after full quarantine was implemented. Differences in the basic reproduction ratio are also significant, dropping from 5.89 (95% confidence interval [95%CI]: 5.46-7.09) before the lockdown to 0.48 (95%CI: 0.15-1.17) afterwards.
    Conclusions: Handling a pandemic like COVID-19 is complex and requires quick decision making. The large differences found in the speed of propagation of the disease show us that being able to implement interventions at the earliest stage is crucial to minimise the impact of a potential infectious threat. Our work also stresses the importance of reliable up to date epidemiological data in order to accurately assess the impact of Public Health policies on viral outbreak.
    MeSH term(s) COVID-19 ; Communicable Disease Control ; Humans ; Reproducibility of Results ; Reproduction ; SARS-CoV-2 ; Spain/epidemiology
    Keywords covid19
    Language English
    Publishing date 2020-05-23
    Publishing country Spain
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1038713-4
    ISSN 1578-1283 ; 0213-9111
    ISSN (online) 1578-1283
    ISSN 0213-9111
    DOI 10.1016/j.gaceta.2020.05.003
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Analysis of the impact of lockdown on the reproduction number of the SARS-Cov-2 in Spain

    Alexandre Hyafil / David Moriña

    Gaceta Sanitaria, Vol 35, Iss 5, Pp 453-

    2021  Volume 458

    Abstract: Objective: The late 2019 COVID-19 outbreak has put the health systems of many countries to the limit of their capacity. The most affected European countries are, so far, Italy and Spain. In both countries (and others), the authorities decreed a lockdown, ...

    Abstract Objective: The late 2019 COVID-19 outbreak has put the health systems of many countries to the limit of their capacity. The most affected European countries are, so far, Italy and Spain. In both countries (and others), the authorities decreed a lockdown, with local specificities. The objective of this work is to evaluate the impact of the measures undertaken in Spain to deal with the pandemic. Method: We estimated the number of cases and the impact of lockdown on the reproducibility number based on the hospitalization reports up to April 15th 2020. Results: The estimated number of cases shows a sharp increase until the lockdown, followed by a slowing down and then a decrease after full quarantine was implemented. Differences in the basic reproduction ratio are also significant, dropping from 5.89 (95% confidence interval [95%CI]: 5.46-7.09) before the lockdown to 0.48 (95%CI: 0.15-1.17) afterwards. Conclusions: Handling a pandemic like COVID-19 is complex and requires quick decision making. The large differences found in the speed of propagation of the disease show us that being able to implement interventions at the earliest stage is crucial to minimise the impact of a potential infectious threat. Our work also stresses the importance of reliable up to date epidemiological data in order to accurately assess the impact of Public Health policies on viral outbreak. Resumen: Objetivo: El brote de COVID-19 a finales de 2019 ha puesto los sistemas de salud de muchos países al límite de su capacidad. Los países europeos más afectados son, hasta ahora, Italia y España. En ambos (y en otros países), las autoridades decretaron un confinamiento, con especificidades locales. El objetivo de este trabajo es evaluar el impacto de las medidas adoptadas en España para hacer frente a la pandemia. Método: Estimamos el número de casos y el impacto del confinamiento en el número básico de reproducción según los informes de hospitalización hasta el 15 de abril de 2020. Resultados: El número estimado de casos muestra un fuerte ...
    Keywords COVID-19 ; Estudio de evaluación ; Salud pública ; Infecciones ; Virus ; Public aspects of medicine ; RA1-1270
    Language English
    Publishing date 2021-09-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Estimated Covid-19 burden in Spain: ARCH underreported non-stationary time series.

    Moriña, David / Fernández-Fontelo, Amanda / Cabaña, Alejandra / Arratia, Argimiro / Puig, Pedro

    BMC medical research methodology

    2023  Volume 23, Issue 1, Page(s) 75

    Abstract: Background: The problem of dealing with misreported data is very common in a wide range of contexts for different reasons. The current situation caused by the Covid-19 worldwide pandemic is a clear example, where the data provided by official sources ... ...

    Abstract Background: The problem of dealing with misreported data is very common in a wide range of contexts for different reasons. The current situation caused by the Covid-19 worldwide pandemic is a clear example, where the data provided by official sources were not always reliable due to data collection issues and to the high proportion of asymptomatic cases. In this work, a flexible framework is proposed, with the objective of quantifying the severity of misreporting in a time series and reconstructing the most likely evolution of the process.
    Methods: The performance of Bayesian Synthetic Likelihood to estimate the parameters of a model based on AutoRegressive Conditional Heteroskedastic time series capable of dealing with misreported information and to reconstruct the most likely evolution of the phenomenon is assessed through a comprehensive simulation study and illustrated by reconstructing the weekly Covid-19 incidence in each Spanish Autonomous Community.
    Results: Only around 51% of the Covid-19 cases in the period 2020/02/23-2022/02/27 were reported in Spain, showing relevant differences in the severity of underreporting across the regions.
    Conclusions: The proposed methodology provides public health decision-makers with a valuable tool in order to improve the assessment of a disease evolution under different scenarios.
    MeSH term(s) Humans ; COVID-19/epidemiology ; Spain/epidemiology ; Bayes Theorem ; Time Factors ; Public Health
    Language English
    Publishing date 2023-03-28
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2041362-2
    ISSN 1471-2288 ; 1471-2288
    ISSN (online) 1471-2288
    ISSN 1471-2288
    DOI 10.1186/s12874-023-01894-9
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Analysis of zero inflated dichotomous variables from a Bayesian perspective: application to occupational health.

    Moriña, David / Puig, Pedro / Navarro, Albert

    BMC medical research methodology

    2021  Volume 21, Issue 1, Page(s) 277

    Abstract: Background: Zero-inflated models are generally aimed to addressing the problem that arises from having two different sources that generate the zero values observed in a distribution. In practice, this is due to the fact that the population studied ... ...

    Abstract Background: Zero-inflated models are generally aimed to addressing the problem that arises from having two different sources that generate the zero values observed in a distribution. In practice, this is due to the fact that the population studied actually consists of two subpopulations: one in which the value zero is by default (structural zero) and the other is circumstantial (sample zero).
    Methods: This work proposes a new methodology to fit zero inflated Bernoulli data from a Bayesian approach, able to distinguish between two potential sources of zeros (structural and non-structural).
    Results: The proposed methodology performance has been evaluated through a comprehensive simulation study, and it has been compiled as an R package freely available to the community. Its usage is illustrated by means of a real example from the field of occupational health as the phenomenon of sickness presenteeism, in which it is reasonable to think that some individuals will never be at risk of suffering it because they have not been sick in the period of study (structural zeros). Without separating structural and non-structural zeros one would be studying jointly the general health status and the presenteeism itself, and therefore obtaining potentially biased estimates as the phenomenon is being implicitly underestimated by diluting it into the general health status.
    Conclusions: The proposed methodology is able to distinguish two different sources of zeros (structural and non-structural) from dichotomous data with or without covariates in a Bayesian framework, and has been made available to any interested researcher in the form of the bayesZIB R package ( https://cran.r-project.org/package=bayesZIB ).
    MeSH term(s) Bayes Theorem ; Computer Simulation ; Humans ; Models, Statistical ; Occupational Health ; Poisson Distribution
    Language English
    Publishing date 2021-12-12
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2041362-2
    ISSN 1471-2288 ; 1471-2288
    ISSN (online) 1471-2288
    ISSN 1471-2288
    DOI 10.1186/s12874-021-01427-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Correction

    David Moriña / Pedro Puig / Albert Navarro

    BMC Medical Research Methodology, Vol 22, Iss 1, Pp 1-

    Analysis of zero inflated dichotomous variables from a Bayesian perspective: application to occupational health

    2022  Volume 1

    Keywords Medicine (General) ; R5-920
    Language English
    Publishing date 2022-08-01T00:00:00Z
    Publisher BMC
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: Left-censored recurrent event analysis in epidemiological studies

    Gilma Hernández-Herrera / David Moriña / Albert Navarro

    BMC Medical Research Methodology, Vol 22, Iss 1, Pp 1-

    a proposal for when the number of previous episodes is unknown

    2022  Volume 9

    Abstract: Abstract Background When dealing with recurrent events in observational studies it is common to include subjects who became at risk before follow-up. This phenomenon is known as left censoring, and simply ignoring these prior episodes can lead to biased ... ...

    Abstract Abstract Background When dealing with recurrent events in observational studies it is common to include subjects who became at risk before follow-up. This phenomenon is known as left censoring, and simply ignoring these prior episodes can lead to biased and inefficient estimates. We aimed to propose a statistical method that performs well in this setting. Methods Our proposal was based on the use of models with specific baseline hazards. In this, the number of prior episodes were imputed when unknown and stratified according to whether the subject had been at risk of presenting the event before t = 0. A frailty term was also used. Two formulations were used for this “Specific Hazard Frailty Model Imputed” based on the “counting process” and “gap time.” Performance was then examined in different scenarios through a comprehensive simulation study. Results The proposed method performed well even when the percentage of subjects at risk before follow-up was very high. Biases were often below 10% and coverages were around 95%, being somewhat conservative. The gap time approach performed better with constant baseline hazards, whereas the counting process performed better with non-constant baseline hazards. Conclusions The use of common baseline methods is not advised when knowledge of prior episodes experienced by a participant is lacking. The approach in this study performed acceptably in most scenarios in which it was evaluated and should be considered an alternative in this context. It has been made freely available to interested researchers as R package miRecSurv.
    Keywords Medicine (General) ; R5-920
    Subject code 310
    Language English
    Publishing date 2022-01-01T00:00:00Z
    Publisher BMC
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: Persistent inequality: evolution of psychosocial exposures at work among the salaried population in Spain between 2005 and 2016.

    Utzet, Mireia / Llorens, Clara / Moriña, David / Moncada, Salvador

    International archives of occupational and environmental health

    2020  Volume 94, Issue 4, Page(s) 621–629

    Abstract: Purpose: To assess the prevalence of poor mental health and of exposure to psychosocial risks among the working population in Spain in 2005, 2010 and 2016; to analyse the associations between workplace psychosocial exposures and mental health problems ... ...

    Abstract Purpose: To assess the prevalence of poor mental health and of exposure to psychosocial risks among the working population in Spain in 2005, 2010 and 2016; to analyse the associations between workplace psychosocial exposures and mental health problems according to gender and occupation.
    Methods: Three representative samples of the Spanish working population were analysed, in 2005 (n = 7,023), 2010 (n = 4,979), and 2016 (n = 1,807). Prevalence ratios between mental health and the five dimensions - job demands, job control, social support, employment insecurity and insecurity over working conditions-were estimated using multilevel mixed-effects Poisson regressions. All the analyses were separated by gender and occupation.
    Results: In 2016, there were improvements in job control, job demands and social support, and deteriorations in employment insecurity and insecurity over working conditions. The risk of poor mental health among manual workers rose if they were exposed to high demands, low social support and high employment insecurity; among non-manual workers, the risk increased if they were exposed to high demands, low control, low social support and high insecurity over working conditions. There were no differences according to gender.
    Conclusion: The new findings shed light on the evolution of the working conditions and health of the wage-earning population in Spain over the last 11 years. The stratification by gender and occupational group is relevant, since it allows a detailed analysis of the social disparities in the associations between psychosocial risks and mental health. The most vulnerable groups can be identified and preventive measures developed at source.
    MeSH term(s) Adolescent ; Adult ; Aged ; Employment ; Female ; Humans ; Interviews as Topic ; Male ; Mental Disorders/epidemiology ; Mental Disorders/psychology ; Mental Health ; Middle Aged ; Occupational Exposure/adverse effects ; Occupational Stress/epidemiology ; Occupational Stress/psychology ; Risk Factors ; Salaries and Fringe Benefits ; Sex Distribution ; Social Support ; Spain/epidemiology ; Workload/psychology ; Workplace/psychology ; Young Adult
    Language English
    Publishing date 2020-11-25
    Publishing country Germany
    Document type Comparative Study ; Journal Article
    ZDB-ID 129038-1
    ISSN 1432-1246 ; 0340-0131 ; 0367-9977
    ISSN (online) 1432-1246
    ISSN 0340-0131 ; 0367-9977
    DOI 10.1007/s00420-020-01609-3
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Un I Zs.366: Show issues Location:
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  10. Article ; Online: New statistical model for misreported data with application to current public health challenges.

    Moriña, David / Fernández-Fontelo, Amanda / Cabaña, Alejandra / Puig, Pedro

    Scientific reports

    2021  Volume 11, Issue 1, Page(s) 23321

    Abstract: The main goal of this work is to present a new model able to deal with potentially misreported continuous time series. The proposed model is able to handle the autocorrelation structure in continuous time series data, which might be partially or totally ... ...

    Abstract The main goal of this work is to present a new model able to deal with potentially misreported continuous time series. The proposed model is able to handle the autocorrelation structure in continuous time series data, which might be partially or totally underreported or overreported. Its performance is illustrated through a comprehensive simulation study considering several autocorrelation structures and three real data applications on human papillomavirus incidence in Girona (Catalonia, Spain) and Covid-19 incidence in two regions with very different circumstances: the early days of the epidemic in the Chinese region of Heilongjiang and the most current data from Catalonia.
    MeSH term(s) COVID-19/epidemiology ; China/epidemiology ; Computer Simulation ; Humans ; Models, Statistical ; Papillomavirus Infections/epidemiology ; Public Health/methods ; Spain/epidemiology ; Time Factors
    Language English
    Publishing date 2021-12-02
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-021-02620-5
    Database MEDical Literature Analysis and Retrieval System OnLINE

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