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      Unambiguous Linkage Between the Vaccination Coverage and the Spread of COVID-19: Geostatistical Evidence from the Slovak LAU 1 Regions

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          Abstract

          This case study refutes some controversial findings about a minor connection between the vaccination coverage and the spread of COVID-19. We try to eliminate some methodological shortcomings and risks, which are included in such previously published studies. Firstly, our selection comprises all regional units in one country. Secondly, the quality of data is basically identical in all examined regions within the country. Thirdly, all Slovak regions had an equal starting position. They were at the same stages of the COVID-19 wave, and the measures taken were analogous in all regions. Slovakia with a significantly different vaccination rates among regions is a very suitable study case. We used the empirical data at the level of its LAU 1 regions for the two latest COVID-19 waves at that time (Delta, Omicron). The methods of regression analysis and geostatistical methods were applied in the study. Indubitably, there is an obvious link between the vaccination coverage and the spread of COVID-19. We have shown that the incidence-trajectories among regions vary based on the vaccination rates. The positivity and incidence in the most vaccinated regional populations were significantly lower than in the least vaccinated regions in a whole analyzed period. Their values in the best vaccinated regions were lower by roughly 20–25 % during the delta and omicron wave-peaks. Using the spatial autocorrelation, we also managed to clearly identify a close relationship between vaccination on the one hand and standardized incidence and positivity on the other hand, although some regions deviated from this general finding.

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          The Analysis of Spatial Association by Use of Distance Statistics

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            Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity

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              Community transmission and viral load kinetics of the SARS-CoV-2 delta (B.1.617.2) variant in vaccinated and unvaccinated individuals in the UK: a prospective, longitudinal, cohort study

              Background The SARS-CoV-2 delta (B.1.617.2) variant is highly transmissible and spreading globally, including in populations with high vaccination rates. We aimed to investigate transmission and viral load kinetics in vaccinated and unvaccinated individuals with mild delta variant infection in the community. Methods Between Sept 13, 2020, and Sept 15, 2021, 602 community contacts (identified via the UK contract-tracing system) of 471 UK COVID-19 index cases were recruited to the Assessment of Transmission and Contagiousness of COVID-19 in Contacts cohort study and contributed 8145 upper respiratory tract samples from daily sampling for up to 20 days. Household and non-household exposed contacts aged 5 years or older were eligible for recruitment if they could provide informed consent and agree to self-swabbing of the upper respiratory tract. We analysed transmission risk by vaccination status for 231 contacts exposed to 162 epidemiologically linked delta variant-infected index cases. We compared viral load trajectories from fully vaccinated individuals with delta infection (n=29) with unvaccinated individuals with delta (n=16), alpha (B.1.1.7; n=39), and pre-alpha (n=49) infections. Primary outcomes for the epidemiological analysis were to assess the secondary attack rate (SAR) in household contacts stratified by contact vaccination status and the index cases’ vaccination status. Primary outcomes for the viral load kinetics analysis were to detect differences in the peak viral load, viral growth rate, and viral decline rate between participants according to SARS-CoV-2 variant and vaccination status. Findings The SAR in household contacts exposed to the delta variant was 25% (95% CI 18–33) for fully vaccinated individuals compared with 38% (24–53) in unvaccinated individuals. The median time between second vaccine dose and study recruitment in fully vaccinated contacts was longer for infected individuals (median 101 days [IQR 74–120]) than for uninfected individuals (64 days [32–97], p=0·001). SAR among household contacts exposed to fully vaccinated index cases was similar to household contacts exposed to unvaccinated index cases (25% [95% CI 15–35] for vaccinated vs 23% [15–31] for unvaccinated). 12 (39%) of 31 infections in fully vaccinated household contacts arose from fully vaccinated epidemiologically linked index cases, further confirmed by genomic and virological analysis in three index case–contact pairs. Although peak viral load did not differ by vaccination status or variant type, it increased modestly with age (difference of 0·39 [95% credible interval –0·03 to 0·79] in peak log 10 viral load per mL between those aged 10 years and 50 years). Fully vaccinated individuals with delta variant infection had a faster (posterior probability >0·84) mean rate of viral load decline (0·95 log 10 copies per mL per day) than did unvaccinated individuals with pre-alpha (0·69), alpha (0·82), or delta (0·79) variant infections. Within individuals, faster viral load growth was correlated with higher peak viral load (correlation 0·42 [95% credible interval 0·13 to 0·65]) and slower decline (–0·44 [–0·67 to –0·18]). Interpretation Vaccination reduces the risk of delta variant infection and accelerates viral clearance. Nonetheless, fully vaccinated individuals with breakthrough infections have peak viral load similar to unvaccinated cases and can efficiently transmit infection in household settings, including to fully vaccinated contacts. Host–virus interactions early in infection may shape the entire viral trajectory. Funding National Institute for Health Research.
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                Author and article information

                Contributors
                branislav.bleha@uniba.sk
                pavol.durcek@uniba.sk
                Journal
                J geovis spat anal
                Journal of Geovisualization and Spatial Analysis
                Springer International Publishing (Cham )
                2509-8810
                2509-8829
                24 May 2023
                24 May 2023
                2023
                : 7
                : 1
                : 14
                Affiliations
                GRID grid.7634.6, ISNI 0000000109409708, Department of Economic and Social Geography, Demography and Territorial Development, Faculty of Natural Sciences, , Comenius University in Bratislava, ; Bratislava, Slovakia
                Author information
                http://orcid.org/0000-0001-9302-8114
                Article
                144
                10.1007/s41651-023-00144-2
                10208556
                328e999a-d998-4e39-90e7-614e815ecc39
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 15 May 2023
                Funding
                Funded by: Comenius University in Bratislava
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                © Springer Nature Switzerland AG 2023

                covid-19,spatial analysis,spatial spread,vaccination coverage,slovakia

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