The effect of data aggregation on dispersion estimates in count data models

Errington, Adam; Einbeck, Jochen; Cumming, Jonathan A.; Rößler, Ute; Endesfelder, David

doi:10.1515/ijb-2020-0079

Cited by 5 publications

(4 citation statements)

References 33 publications

(40 reference statements)

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“…For the scenario in the current paper, where we have weekly counts, an equivalent analysis suggested using

and

, hence indicating a slightly larger heterogeneity across countries in terms of their death rates. This result is somewhat plausible given other indications in the literature that data aggregation (in this case, from daily to weekly counts), can increase dispersion [ 26 ]. It is important to emphasise that the entire methodology described so far is fully cross-sectional.…”

Section: Methododoloysupporting

confidence: 66%

A Sequential Cross-Sectional Analysis Producing Robust Weekly COVID-19 Rates for South East Asian Countries

Almohaimeed

Einbeck

2023

Viruses

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The COVID-19 pandemic has expanded fast over the world, affecting millions of people and generating serious health, social, and economic consequences. All South East Asian countries have experienced the pandemic, with various degrees of intensity and response. As the pandemic progresses, it is important to track and analyse disease trends and patterns to guide public health policy and treatments. In this paper, we carry out a sequential cross-sectional study to produce reliable weekly COVID-19 death (out of cases) rates for South East Asian countries for the calendar years 2020, 2021, and 2022. The main objectives of this study are to characterise the trends and patterns of COVID-19 death rates in South East Asian countries through time, as well as compare COVID-19 rates among countries and regions in South East Asia. Our raw data are (daily) case and death counts acquired from “Our World in Data”, which, however, for some countries and time periods, suffer from sparsity (zero or small counts), and therefore require a modelling approach where information is adaptively borrowed from the overall dataset where required. Therefore, a sequential cross-sectional design will be utilised, that will involve examining the data week by week, across all countries. Methodologically, this is achieved through a two-stage random effect shrinkage approach, with estimation facilitated by nonparametric maximum likelihood.

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“…For the scenario in the current paper, where we have weekly counts, an equivalent analysis suggested using

and

Section: Methododoloysupporting

confidence: 66%

A Sequential Cross-Sectional Analysis Producing Robust Weekly COVID-19 Rates for South East Asian Countries

Almohaimeed

Einbeck

2023

Viruses

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“…Poisson (Kato et al 2006;Rübe et al 2008;Martin et al 2013) or quasi-Poisson models (Errington et al 2021). In our case, none of the tested distributions gave us satisfactory results, for this reason we did not assume any distribution.…”

Section: Discussionmentioning

confidence: 61%

Establishment and validation of surface model for biodosimetry based on γ-H2AX foci detection

López

Pujol-Canadell

Puig

et al. 2021

International Journal of Radiation Biology

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Introduction:In the event of a radiation accident detecting γ-H2AX foci is being accepted as fast method for triage and dose assessment. However, due to their disappearance kinetics, published calibrations have been constructed at specific postirradiation times.Objectives: To develop a surface, or tridimensional, model to estimate doses at times not included in the calibration analysis, and to validate it.Materials and methods: Calibration data was obtained irradiating peripheral mononucleated cells from one donor with radiation doses ranging from 0 to 3 Gy, and γ -H2AX foci were detected microscopically using a semi-automatic method, at different post-irradiation times from 0.5 to 24 h. For validation, in addition to the abovementioned donor, blood samples from another donor were also used. Validation was done within the range of doses and post-irradiation times used in the calibration. Results:The calibration data clearly shows that at each analyzed time, the γ-H2AX foci frequency increases as dose increases, and for each dose this frequency decreases with post-irradiation time. The γ-H2AX foci nucleus distribution was clearly overdispersed, for this reason to obtain bidimensional and tridimensional dose-effect relationships no probability distribution was assumed, and linear and non-linear least squares weighted regression was used. In the two validation exercises for most evaluated samples, the 95% confidence limits of the estimated dose were between ±0.5Gy of the real dose. No major differences were observed between donors. Conclusion:In case of a suspected overexposure to radiation, the surface model here presented allows a correct dose estimation using γ-H2AX foci as biomarker. The 3 advantage of this surface model is that it can be used at any post-irradiation time, in our model between 0.5 and 24 h.

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“…We conducted an ecological time series study. Time series analysis was conducted using generalised linear models with negative binomial (type II) regression, to take account of overdispersion of the data, 21 while allowing model comparison using Akaike Information Criterion (AIC). The method was adapted from that described by Tadano et al 22 Mean daily relative humidity, wind speed, temperature and season (calendar day) were controlled for using a smooth function in the analyses.…”

Section: Discussionmentioning

confidence: 99%

Relationship between air quality and asthma-related emergency hospital admissions in Mexico City 2017–2019

Hayes,

Mejia-Arangure,

Errington

et al. 2023

Thorax

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BackgroundPrevious studies found exposure to air pollution leads to exacerbations of asthma in paediatric and adult patients and increases asthma-related emergency hospital admissions (AREHA).MethodsAREHAs and levels of air pollutants (PM10, PM2.5and NO2) were obtained from Mexico City for the period 2017–2019. A time-series approach was used to explore the relationship between air pollutants and AREHA. Relative risks of AREHA were estimated using a negative binomial regression in young children (less than 5 years) and adults (greater than 18 years).ResultsThere was a positive association between AREHA and PM10, PM2.5and NO2in adults, which remained after mutual adjustment for these pollutants. The relative risk (RR) of admission in adults increased by 3% (95% CI 1% to 4%) for a 10 µg/m3increase in PM10, 1% (0.03% to 3%) for a 5 µg/m3increase in PM2.5and by 1% (0.06% to 2%) for a 5 µg/m3increase in NO2. In contrast, in young children, AREHAs were negatively associated with PM10after adjustment for NO2(RR 0.97 (0.95 to 0.99) for a 10 µg/m3and with NO2after adjustment for PM10and PM2.5(RR 0.98 (0.96 to 0.99) and 0.97 (0.96 to 0.99), respectively, for a 5 µg/m3increase in NO2). AREHAs in children were not associated with PM2.5after adjustment for NO2.ConclusionsAmbient air pollution, within the previous week, was associated with emergency hospital admissions for asthma to public hospitals in adults in Mexico City. The relationship in children was less consistent. Further work is needed to explore why differences between adults and children exist to inform appropriate interventions to benefit public health.

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The effect of data aggregation on dispersion estimates in count data models

Cited by 5 publications

References 33 publications

A Sequential Cross-Sectional Analysis Producing Robust Weekly COVID-19 Rates for South East Asian Countries

A Sequential Cross-Sectional Analysis Producing Robust Weekly COVID-19 Rates for South East Asian Countries

Establishment and validation of surface model for biodosimetry based on γ-H2AX foci detection

Relationship between air quality and asthma-related emergency hospital admissions in Mexico City 2017–2019

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