Estimating critical level of $$\hbox {PM}_{{10}}$$ to affect hospital infant admissions in Vitória, Brazil

Sarnaglia, Alessandro José Queiroz; Rodrigues, Mariana C.

doi:10.1007/s00477-021-01979-1

Cited by 4 publications

(1 citation statement)

References 36 publications

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“…The basis behind change point analysis can be extended to account for the effect of a temporallyvarying covariate potentially associated with a variation in the values of a time series of interest. This leads to models with change points in the covariates, which can be adapted to multiple contexts, including survival analyses (Lee et al, 2020) and exposure-outcome epidemiological studies (Sarnaglia et al, 2021). In general, segmented regression models (Muggeo, 2003) are the natural framework for dealing with this type of covariate effects.…”

Section: Model Descriptionmentioning

confidence: 99%

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

Briz‐Redón¹,

Serrano‐Aroca²

2021

Preprint

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The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the coronavirus disease 2019 , 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%.

show abstract

Section: Model Descriptionmentioning

confidence: 99%

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

Briz‐Redón¹,

Serrano‐Aroca²

2021

Preprint

View full text Add to dashboard Cite

show abstract

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

Briz‐Redón

Serrano‐Aroca

2022

Stoch Environ Res Risk Assess

View full text Add to dashboard Cite

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%.

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Robust segmented regression: application to oxygen uptake plateau identification

Sarnaglia,

Fajardo Molinares,

Azevedo

2023

Environ Ecol Stat

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Recently, segmented regression has been utilized as a "working" model for a bootstrap test to detect true oxygen uptake plateau. This approach employs an iterative procedure based on least squares to fit the model. However, it is widely acknowledged that least squares is highly sensitive to outliers, often yielding inefficient estimates. This paper proposes an alternative iterative method by substituting the least squares step with a M-estimator step. Leveraging the robust features of M-estimators, the proposed method is expected to exhibit resilience against outliers. To empirically investigate the performance of the proposed method, a Monte Carlo simulation study is conducted. For comparison purposes, the classical iterative method is also considered. The results indicate that, in uncontaminated scenarios, both methods exhibit similar behavior, with the classical method presenting a slightly superior performance. However, in contaminated cases, the classical method is highly deteriorated, with significant bias and root mean squared error, while the proposed method demonstrates much better performance. Both methods are employed to fit the "working" 3-segment regression model and perform a plateau test on apparently contaminated oxygen uptake data. The results reveal that, due to the presence of outliers, the classical method produces inflated estimates for the error variance and larger standard errors for all parameters, in comparison to the proposed method. Moreover, the plateau test conducted using the classical (robust) method leads to the rejection (confirmation) of a plateau of oxygen uptake for the same data. Overall, these findings highlight the superiority of the proposed method in handling outliers.

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Estimating critical level of $$\hbox {PM}_{{10}}$$ to affect hospital infant admissions in Vitória, Brazil

Cited by 4 publications

References 36 publications

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

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

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

Robust segmented regression: application to oxygen uptake plateau identification

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