Fine-scale variation in the effect of national border on COVID-19 spread: A case study of the Saxon-Czech border region

Vyskočil, Jiří; Schüler, Lennart; Schlechte-Wełnicz, Weronika; Calabrese, Justin M.

doi:10.1016/j.sste.2022.100560

Cited by 3 publications

(1 citation statement)

References 25 publications

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“…The COVID-19 pandemic is unprecedented in modern world history and has triggered a flurry of research activity across the health-related sciences. This effort has produced an equally unprecedented flood of spatially referenced epidemiological data [ 1 ]. Since 2019, humanity has been threatened by the severe acute respiratory syndrome virus (SARS-CoV-2) pandemic, which causes COVID-19.…”

Section: Introductionmentioning

confidence: 99%

Spatial Autocorrelation of COVID-19 in Slovakia

Vilinová

Petrikovičová

2023

TropicalMed

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The pandemic situation of COVID-19, which affected almost the entire civilized world with its consequences, offered a unique opportunity for analysis of geographical space. In a relatively short period of time, the COVID-19 pandemic became a truly global event with consequences affecting all areas of life. Circumstances with COVID-19, which affected the territory of Slovakia and its regions, represent a sufficient premise for analysis three years after the registration of the first case in Slovakia. The study presents the results of a detailed spatiotemporal analysis of the course of registered cases of COVID-19 in six periods in Slovakia. The aim of the paper was to analyze the development of the number of people infected with the disease COVID-19 in Slovakia. At the level of the districts of Slovakia, using spatial autocorrelation, we identified spatial differences in the disease of COVID-19. Moran’s global autocorrelation index and Moran’s local index were used in the synthesis of knowledge. Spatial analysis of data on the number of infected in the form of spatial autocorrelation analysis was used as a practical sustainable approach to localizing statistically significant areas with high and low positivity. This manifested itself in the monitored area mainly in the form of positive spatial autocorrelation. The selection of data and methods used in this study together with the achieved and presented results can serve as a suitable tool to support decisions in further measures for the future.

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Section: Introductionmentioning

confidence: 99%

Spatial Autocorrelation of COVID-19 in Slovakia

Vilinová

Petrikovičová

2023

TropicalMed

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Modelling and Visualization of Spatial Data: A Case Study of COVID-19 Data in Maine, USA

Abdi

2024

2024 IEEE 3rd Conference on Information Technology and Data Science (CITDS)

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Estimating Cross-Border Mobility from the Difference in Peak Timing: A Case Study of Poland–Germany Border Regions

Senapati,

Mertel,

Schlechte-Welnicz

et al. 2024

Mathematics

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Human mobility contributes to the fast spatiotemporal propagation of infectious diseases. During an outbreak, monitoring the infection on either side of an international border is crucial as cross-border migration increases the risk of disease importation. Due to the unavailability of cross-border mobility data, mainly during pandemics, it becomes difficult to propose reliable, model-based strategies. In this study, we propose a method for estimating commuting-type cross-border mobility flux between any pair of regions that share an international border from the observed difference in their infection peak timings. Assuming the underlying disease dynamics are governed by a Susceptible–Infected–Recovered (SIR) model, we employ stochastic simulations to obtain the maximum likelihood cross-border mobility estimate for any pair of regions. We then investigate how the estimate of cross-border mobility flux varies depending on the transmission rate. We further show that the uncertainty in the estimates decreases for higher transmission rates and larger observed differences in peak timing. Finally, as a case study, we apply the method to some selected regions along the Poland–Germany border that are directly connected through multiple modes of transportation and quantify the cross-border fluxes from the COVID-19 cases data from 20 February to 20 June 2021.

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Fine-scale variation in the effect of national border on COVID-19 spread: A case study of the Saxon-Czech border region

Cited by 3 publications

References 25 publications

Spatial Autocorrelation of COVID-19 in Slovakia

Spatial Autocorrelation of COVID-19 in Slovakia

Modelling and Visualization of Spatial Data: A Case Study of COVID-19 Data in Maine, USA

Estimating Cross-Border Mobility from the Difference in Peak Timing: A Case Study of Poland–Germany Border Regions

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