Abstract:The COVID-19 pandemic was in 2020 and 2021 for a large part mitigated by reducing contacts in the general population. To monitor how these contacts changed over the course of the pandemic in the Netherlands, a longitudinal survey was conducted where participants reported on their at-risk contacts every two weeks, as part of the European CoMix survey. The survey included 1659 participants from April to August 2020 and 2514 participants from December 2020 to September 2021.We categorized the number of unique con… Show more
“…Moreover, in-depth questionnaire data allowed investigation into (sub)groups. Response rates in children were rather low and drop-out rates high, however since children were less restricted by control measures and schools were mostly open, we do not expect large differences between children in terms of exposure, and this was also confirmed by contact data [34, 35]. Despite random selection and weighting our sample, some groups are underrepresented, such as those living in nursing homes – that were hit hard pre-Alpha – and non-Western, who might have refrained from participation due to digital- and/or language barriers.…”
BackgroundRepeated population-based SARS-CoV-2 serosurveillance is key in complementing other surveillance tools.AimAssessing trends in infection- and/or vaccine-induced immunity, including breakthrough infections, among (sub)groups and regions in the Dutch population during the Variant of Concern (VOC)-era whilst varying levels of stringency, to evaluate population immunity dynamics and inform future pandemic response planning.MethodsIn this prospective population-based cohort, randomly-selected participants (n=9,985) aged 1-92 years (recruited since early-2020) donated home-collected fingerstick blood samples at six timepoints in 2021-2022, covering waves dominated by Alpha, Delta, and Omicron (BA.1, BA.2, BA.5). IgG antibody assessments against Spike-S1 and Nucleoprotein were combined with vaccination- and testing data to estimate infection-induced (inf) and total (infection- and vaccination-induced) seroprevalence.ResultsIn 2021, nationwide inf-seroprevalence rose modestly from 12% since Alpha to 26% amidst Delta, while total seroprevalence increased rapidly to nearly 90%, particularly fast in vulnerable groups (i.e., elderly and those with comorbidities). Highest infection rates were noticeable in adolescents and young adults, low/middle educated elderly, non-Western, contact professions (other than healthcare), and low-vaccination coverage regions. In 2022, following Omicron emergence, inf-seroprevalence elevated sharply to 62% and further to 86%, with frequent breakthrough infections and reduction of seroprevalence dissimilarities between most groups. Whereas >90% of <60-year-olds had been infected, 30% of vaccinated vulnerable individuals had not acquired hybrid immunity.ConclusionAlthough total SARS-CoV-2 seroprevalence had increased rapidly, infection rates were unequally distributed within the Dutch population. Ongoing tailored vaccination efforts and (sero-)monitoring of vulnerable groups remain important given their lowest rate of hybrid immunity and highest susceptibility to severe disease.
“…Moreover, in-depth questionnaire data allowed investigation into (sub)groups. Response rates in children were rather low and drop-out rates high, however since children were less restricted by control measures and schools were mostly open, we do not expect large differences between children in terms of exposure, and this was also confirmed by contact data [34, 35]. Despite random selection and weighting our sample, some groups are underrepresented, such as those living in nursing homes – that were hit hard pre-Alpha – and non-Western, who might have refrained from participation due to digital- and/or language barriers.…”
BackgroundRepeated population-based SARS-CoV-2 serosurveillance is key in complementing other surveillance tools.AimAssessing trends in infection- and/or vaccine-induced immunity, including breakthrough infections, among (sub)groups and regions in the Dutch population during the Variant of Concern (VOC)-era whilst varying levels of stringency, to evaluate population immunity dynamics and inform future pandemic response planning.MethodsIn this prospective population-based cohort, randomly-selected participants (n=9,985) aged 1-92 years (recruited since early-2020) donated home-collected fingerstick blood samples at six timepoints in 2021-2022, covering waves dominated by Alpha, Delta, and Omicron (BA.1, BA.2, BA.5). IgG antibody assessments against Spike-S1 and Nucleoprotein were combined with vaccination- and testing data to estimate infection-induced (inf) and total (infection- and vaccination-induced) seroprevalence.ResultsIn 2021, nationwide inf-seroprevalence rose modestly from 12% since Alpha to 26% amidst Delta, while total seroprevalence increased rapidly to nearly 90%, particularly fast in vulnerable groups (i.e., elderly and those with comorbidities). Highest infection rates were noticeable in adolescents and young adults, low/middle educated elderly, non-Western, contact professions (other than healthcare), and low-vaccination coverage regions. In 2022, following Omicron emergence, inf-seroprevalence elevated sharply to 62% and further to 86%, with frequent breakthrough infections and reduction of seroprevalence dissimilarities between most groups. Whereas >90% of <60-year-olds had been infected, 30% of vaccinated vulnerable individuals had not acquired hybrid immunity.ConclusionAlthough total SARS-CoV-2 seroprevalence had increased rapidly, infection rates were unequally distributed within the Dutch population. Ongoing tailored vaccination efforts and (sero-)monitoring of vulnerable groups remain important given their lowest rate of hybrid immunity and highest susceptibility to severe disease.
“…By uniformly sampling from the uncertainty ranges of the Fermi estimates, 200 contact matrices were obtained to describe the effect of a given set of COVID-19 control measures. On 28 May 2020, new estimates were made for all sets of control measures, to match the observations of the first CoMix contact study (19, 20), and new matrices were created.…”
Section: Methodsmentioning
confidence: 99%
“…In 2020 an international collaboration started collecting contact survey data in several European countries (19). We used the data of the first survey conducted in the Netherlands in early April 2020 (20).…”
Introduction: Model projections of COVID-19 incidence into the future help policy makers about decisions to implement or lift control measures. During 2020, policy makers in the Netherlands were informed on a weekly basis with short-term projections of COVID-19 intensive care unit (ICU) admissions. Here we present the model and the procedure by which it was updated. Methods: the projections were produced using an age-structured transmission model. A consistent, incremental update procedure that integrated all new surveillance and hospital data was conducted weekly. First, up-to-date estimates for most parameter values were obtained through re-analysis of all data sources. Then, estimates were made for changes in the age-specific contact rates in response to policy changes. Finally, a piecewise constant transmission rate was estimated by fitting the model to reported daily ICU admissions, with a change point analysis guided by Akaike's Information Criterion. Results: The model and update procedure allowed us to make mostly accurate weekly projections, accounting for recent and future policy changes, and to adapt the estimated effectiveness of the policy changes based only on the natural accumulation of incoming data. Discussion: The model incorporates basic epidemiological principles and most model parameters were estimated per data source. Therefore, it had potential to be adapted to a more complex epidemiological situation, as it would develop after 2020.
“…The respiratory disease SARS affected Canada, Spain, Russia, Brazil, India and Australia, while the respiratory disease MERS affected North African countries, Turkey, Iran and Saudi Arabia a few years after SARS. Both SARS and MERS had effects on countries in Western Europe, the USA and China [ [1] , [2] , [3] , [4] , [5] , [6] ]. There are several reasons for the greater spread of these diseases compared to the Spanish flu, one of which can be considered the phenomenon of mass air travel, which has fully manifested in the most recent pandemic.…”
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