Tracking the emergence of disparities in the subnational spread of COVID-19 in Brazil using an online application for real-time data visualisation: a longitudinal analysis

Mee, Paul; Alexander, Neal; Mayaud, Philippe; Colón‐González, Felipe J.; Abbott, Sam; Santos, Andreza Aruska de Souza; Acosta, André Luís; Parag, Kris V; Pereira, Rafael H. M.; Prete, Carlos A.; Sabino, Ester C.; Faria, Nuno Rodrigues; Brady, Oliver J.

doi:10.1101/2021.04.30.21256386

Cited by 4 publications

(3 citation statements)

References 49 publications

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“…Time series analysis provides useful information to detect trends and unusual data (anomaly detection), which is used to select and develop appropriate interventions. Anomaly detection and other visualisation methods have been successfully used during the COVID-19 pandemic [6][7][8]. However, there is little research on the use of anomaly detection methods to measure indirect impacts and their suitability to identify targets for care coordination interventions.…”

Section: Methodsmentioning

confidence: 99%

Data-Driven Interventions for an Emergency Preparedness System: A National Experience in Australia

Andrade,

Kerr,

Roughead

2024

Studies in Health Technology and Informatics

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Natural disasters and health emergencies disproportionally affect vulnerable populations causing disruptions to usual care and increasing chronic disease burden. Data and digital technologies are important tools to identify and mitigate indirect effects of emergencies. In this paper, we describe the methods used in the development of a series of digital emergency preparedness interventions to mitigate the direct and indirect consequences of the COVID-19 pandemic in the veteran community in Australia. The case studies demonstrate the use of data for surveillance, patient phenotyping, data-driven decision support and stakeholder communication in primary care. The intervention successfully increased appropriate healthcare use by vulnerable individuals and could be expanded to other populations.

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Section: Methodsmentioning

confidence: 99%

Data-Driven Interventions for an Emergency Preparedness System: A National Experience in Australia

Andrade,

Kerr,

Roughead

2024

Studies in Health Technology and Informatics

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“…This has little impact on retrospective R t estimates and substantially reduces the computational overhead. We used a generation time modelled as a gamma distribution with mean: 3.6 (standard deviation of mean: 0.7), standard deviation 3.1 (standard deviation of standard deviation: 0.76) and maximum: 15 [5,32]. We assumed a negative binomial observation model for reported cases with a day of the week effect modelled as a simplex allowing us to model weekly reported cases without manual specification.…”

Section: R T Estimationmentioning

confidence: 99%

Association between mobility, non-pharmaceutical interventions, and COVID-19 transmission in Ghana: A modelling study using mobile phone data

Gibbs

Liu²,

Abbott³

et al. 2022

PLOS Glob Public Health

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Governments around the world have implemented non-pharmaceutical interventions to limit the transmission of COVID-19. Here we assess if increasing NPI stringency was associated with a reduction in COVID-19 cases in Ghana. While lockdowns and physical distancing have proven effective for reducing COVID-19 transmission, there is still limited understanding of how NPI measures are reflected in indicators of human mobility. Further, there is a lack of understanding about how findings from high-income settings correspond to low and middle-income contexts. In this study, we assess the relationship between indicators of human mobility, NPIs, and estimates of Rt, a real-time measure of the intensity of COVID-19 transmission. We construct a multilevel generalised linear mixed model, combining local disease surveillance data from subnational districts of Ghana with the timing of NPIs and indicators of human mobility from Google and Vodafone Ghana. We observe a relationship between reductions in human mobility and decreases in Rt during the early stages of the COVID-19 epidemic in Ghana. We find that the strength of this relationship varies through time, decreasing after the most stringent period of interventions in the early epidemic. Our findings demonstrate how the association of NPI and mobility indicators with COVID-19 transmission may vary through time. Further, we demonstrate the utility of combining local disease surveillance data with large scale human mobility data to augment existing surveillance capacity to monitor the impact of NPI policies.

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“…In [38] the method Epifilter is introduced as an extension of EpiEstim and of the Wallinga-Teunis formulation. Epifilter has been applied in practical studies like [39]. The core of Epifilter is again the causal renewal equation in Poisson form (13).…”

Section: Stochastic Observation Models For I T and R Tmentioning

confidence: 99%

Modeling Covid-19 incidence by the renewal equation after removal of administrative bias and noise

Álvarez

Morel

2022

Preprint

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The sanitary crisis of the past two years has focused the public's attention on quantitative indicators of the spread of the COVID-19 pandemic. The daily reproduction number Rt, defined by the average number of new infections caused by a single infected individual at time t, is one of the best metrics for estimating the epidemic trend. In this paper, we give a complete observation model for sampled epidemiological incidence signals obtained through periodic administrative measurements. The model is governed by the classic renewal equation using an empirical reproduction kernel, and subject to two perturbations: a time-varying gain with a weekly period and a white observation noise. We estimate this noise model and its parameters by extending a variational inversion of the model recovering its main driving variable Rt. Using Rt, a restored incidence curve, corrected of the weekly and festive day bias, can be deduced through the renewal equation. We verify experimentally on many countries that, once the weekly and festive days bias have been corrected, the difference between the incidence curve and its expected value is well approximated by an exponential distributed white noise multiplied by a power of the magnitude of the restored incidence curve.

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Tracking the emergence of disparities in the subnational spread of COVID-19 in Brazil using an online application for real-time data visualisation: a longitudinal analysis

Cited by 4 publications

References 49 publications

Data-Driven Interventions for an Emergency Preparedness System: A National Experience in Australia

Data-Driven Interventions for an Emergency Preparedness System: A National Experience in Australia

Association between mobility, non-pharmaceutical interventions, and COVID-19 transmission in Ghana: A modelling study using mobile phone data

Modeling Covid-19 incidence by the renewal equation after removal of administrative bias and noise

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