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1.
J Med Screen ; : 9691413241268819, 2024 Aug 01.
Artículo en Inglés | MEDLINE | ID: mdl-39091000

RESUMEN

BACKGROUND: Cervical cancer incidence in Estonia ranks among the highest in Europe, but screening attendance has remained low. This randomized study aimed to evaluate the impact of opt-in and opt-out human papillomavirus (HPV) self-sampling options on participation in organized screening. METHODS: A random sample of 25,591 women were drawn from the cervical cancer screening target population who were due to receive a reminder in autumn 2021 and thereafter randomly allocated to two equally sized intervention arms (opt-out and opt-in) receiving a choice between HPV self-sampling or clinician sampling. In the opt-out arm, a self-sampler was sent to home address by regular mail; the opt-in arm received an e-mail containing a link to order a self-sampler online. The remaining 30,102 women in the control group received a standard reminder for conventional screening. Participation by intervention arm, age and region of residence was calculated; a questionnaire was used to assess self-sampling user experience. RESULTS: A significant difference in participation was seen between opt-out (41.7%) (19.8% chose self-sampling and 21.9% clinician sampling), opt-in (34.1%) (7.9% self-sampling, 26.2% clinician sampling) and control group (29.0%, clinician sampling only). All age groups and regions in the intervention arms showed higher participation compared to the control group, but the size of the effect varied. Among self-sampling users, 99% agreed that the device was easy to use and only 3.5% preferred future testing at the clinic. CONCLUSION: Providing women with a choice between self-sampling and clinician sampling significantly increased participation in cervical cancer screening. Opt-in and opt-out options had a different effect across age groups, suggesting the need to adapt strategies.

2.
PLoS One ; 19(5): e0303176, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-38728305

RESUMEN

BACKGROUND: The COVID-19 pandemic was characterised by rapid waves of disease, carried by the emergence of new and more infectious SARS-CoV-2 virus variants. How the pandemic unfolded in various locations during its first two years has yet to be sufficiently covered. To this end, here we are looking at the circulating SARS-CoV-2 variants, their diversity, and hospitalisation rates in Estonia in the period from March 2000 to March 2022. METHODS: We sequenced a total of 27,550 SARS-CoV-2 samples in Estonia between March 2020 and March 2022. High-quality sequences were genotyped and assigned to Nextstrain clades and Pango lineages. We used regression analysis to determine the dynamics of lineage diversity and the probability of clade-specific hospitalisation stratified by age and sex. RESULTS: We successfully sequenced a total of 25,375 SARS-CoV-2 genomes (or 92%), identifying 19 Nextstrain clades and 199 Pango lineages. In 2020 the most prevalent clades were 20B and 20A. The various subsequent waves of infection were driven by 20I (Alpha), 21J (Delta) and Omicron clades 21K and 21L. Lineage diversity via the Shannon index was at its highest during the Delta wave. About 3% of sequenced SARS-CoV-2 samples came from hospitalised individuals. Hospitalisation increased markedly with age in the over-forties, and was negligible in the under-forties. Vaccination decreased the odds of hospitalisation in over-forties. The effect of vaccination on hospitalisation rates was strongly dependent upon age but was clade-independent. People who were infected with Omicron clades had a lower hospitalisation likelihood in age groups of forty and over than was the case with pre-Omicron clades regardless of vaccination status. CONCLUSIONS: COVID-19 disease waves in Estonia were driven by the Alpha, Delta, and Omicron clades. Omicron clades were associated with a substantially lower hospitalisation probability than pre-Omicron clades. The protective effect of vaccination in reducing hospitalisation likelihood was independent of the involved clade.


Asunto(s)
COVID-19 , Hospitalización , SARS-CoV-2 , Humanos , COVID-19/epidemiología , COVID-19/virología , Hospitalización/estadística & datos numéricos , SARS-CoV-2/genética , SARS-CoV-2/aislamiento & purificación , SARS-CoV-2/clasificación , Masculino , Femenino , Persona de Mediana Edad , Adulto , Anciano , Estonia/epidemiología , Genoma Viral , Adulto Joven , Filogenia , Pandemias , Adolescente , Niño , Lactante , Preescolar , Anciano de 80 o más Años
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