Prevalence and Severity of Symptoms 3 Months After Infection With SARS-CoV-2 Compared to Test-Negative and Population Controls in the Netherlands.

BACKGROUND: This prospective study assesses symptoms 3 months after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection compared to test-negative and population controls, and the effect of vaccination prior to infection. METHODS: Participants enrolled after a positive (cases) or negative (test-negative controls) SARS-CoV-2 test, or after invitation from the general population (population controls). After 3 months, participants indicated presence of 41 symptoms and severity of 4 symptoms. Permutation tests were used to select symptoms significantly elevated in cases compared to controls and to compare symptoms between cases that were vaccinated or unvaccinated prior to infection. RESULTS: In total, 9166 cases, 1698 symptomatic but test-negative controls, and 3708 population controls enrolled. At 3 months, 13 symptoms, and severity of fatigue, cognitive impairment, and dyspnea were significantly elevated incases compared to controls. Of cases, 48.5% reported ≥1 significantly elevated symptom compared to 29.8% of test-negative controls and 26.0% of population controls. Effect of vaccination could be determined for cases aged <65 years, and was significantly protective for loss of smell and taste but not for other symptoms. DISCUSSION: Three months after SARS-CoV-2 infection, almost half of cases report symptoms, which was higher than background prevalence and test-negative prevalence. Vaccination prior to infection was protective against loss of smell and taste in cases aged <65 years.

A scenario modelling analysis to anticipate the impact of COVID-19 vaccination in adolescents and children on disease outcomes in the Netherlands, summer 2021.

BackgroundSince the roll-out of COVID-19 vaccines in late 2020 and throughout 2021, European governments have relied on mathematical modelling to inform policy decisions about COVID-19 vaccination.AimWe present a scenario-based modelling analysis in the Netherlands during summer 2021, to inform whether to extend vaccination to adolescents (12-17-year-olds) and children (5-11-year-olds).MethodsWe developed a deterministic, age-structured susceptible-exposed-infectious-recovered (SEIR) model and compared modelled incidences of infections, hospital and intensive care admissions, and deaths per 100,000 people across vaccination scenarios, before the emergence of the Omicron variant.ResultsOur model projections showed that, on average, upon the release of all non-pharmaceutical control measures on 1 November 2021, a large COVID-19 wave may occur in winter 2021/22, followed by a smaller, second wave in spring 2022, regardless of the vaccination scenario. The model projected reductions in infections/severe disease outcomes when vaccination was extended to adolescents and further reductions when vaccination was extended to all people over 5 years-old. When examining projected disease outcomes by age group, individuals benefitting most from extending vaccination were adolescents and children themselves. We also observed reductions in disease outcomes in older age groups, particularly of parent age (30-49 years), when children and adolescents were vaccinated, suggesting some prevention of onward transmission from younger to older age groups.ConclusionsWhile our scenarios could not anticipate the emergence/consequences of SARS-CoV-2 Omicron variant, we illustrate how our approach can assist decision making. This could be useful when considering to provide booster doses or intervening against future infection waves.

Prevalence and determinants of persistent symptoms after infection with SARS-CoV-2: protocol for an observational cohort study (LongCOVID-study).

INTRODUCTION: A substantial proportion of individuals infected with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), report persisting symptoms weeks and months following acute infection. Estimates on prevalence vary due to differences in study designs, populations, heterogeneity of symptoms and the way symptoms are measured. Common symptoms include fatigue, cognitive impairment and dyspnoea. However, knowledge regarding the nature and risk factors for developing persisting symptoms is still limited. Hence, in this study, we aim to determine the prevalence, severity, risk factors and impact on quality of life of persisting symptoms in the first year following acute SARS-CoV-2 infection. METHODS AND ANALYSIS: The LongCOVID-study is both a prospective and retrospective cohort study being conducted in the Netherlands, with a one year follow-up. Participants aged 5 years and above, with self-reported positive or negative tests for SARS-CoV-2 will be included in the study. The primary outcome is the prevalence and severity of persistent symptoms in participants that tested positive for SARS-CoV-2 compared with controls. Symptom severity will be assessed for fatigue (Checklist Individual Strength (CIS subscale fatigue severity)), pain (Rand-36/SF-36 subscale bodily pain), dyspnoea (Medical Research Council (mMRC)) and cognitive impairment (Cognitive Failure Questionnaire (CFQ)). Secondary outcomes include effect of vaccination prior to infection on persistent symptoms, loss of health-related quality of life (HRQoL) and risk factors for persisting symptoms following infection with SARS-CoV-2. ETHICS AND DISSEMINATION: The Utrecht Medical Ethics Committee (METC) declared in February 2021 that the Medical Research Involving Human Subjects Act (WMO) does not apply to this study (METC protocol number 21-124/C). Informed consent is required prior to participation in the study. Results of this study will be submitted for publication in a peer-reviewed journal.

COVID-19 Vaccination Intent and Belief that Vaccination Will End the Pandemic.

High vaccination coverage is considered to be key in dealing with the coronavirus disease (COVID-19) pandemic. However, vaccine hesitancy can limit uptake. We examined the specific coronavirus beliefs that persons have regarding COVID-19 and COVID-19 vaccines and to what extent these beliefs explain COVID-19 vaccination intentions. We conducted a survey among 4,033 residents of the Netherlands that examined COVID-19 vaccination intentions and various beliefs. Random forest regression analysis explained 76% of the variance in vaccination intentions. The strongest determinant in the model was the belief the COVID-19 crisis will only end if many persons get vaccinated. Other strong determinants were beliefs about safety of vaccines, specifically in relation to vaccine development and approval process; (social) benefits of vaccination; social norms regarding vaccination behavior; and effectiveness of vaccines. We propose to address these specific beliefs in communications about COVID-19 vaccinations to stimulate vaccine uptake.

Optimal vaccine allocation for COVID-19 in the Netherlands: A data-driven prioritization.

For the control of COVID-19, vaccination programmes provide a long-term solution. The amount of available vaccines is often limited, and thus it is crucial to determine the allocation strategy. While mathematical modelling approaches have been used to find an optimal distribution of vaccines, there is an excessively large number of possible allocation schemes to be simulated. Here, we propose an algorithm to find a near-optimal allocation scheme given an intervention objective such as minimization of new infections, hospitalizations, or deaths, where multiple vaccines are available. The proposed principle for allocating vaccines is to target subgroups with the largest reduction in the outcome of interest. We use an approximation method to reconstruct the age-specific transmission intensity (the next generation matrix), and express the expected impact of vaccinating each subgroup in terms of the observed incidence of infection and force of infection. The proposed approach is firstly evaluated with a simulated epidemic and then applied to the epidemiological data on COVID-19 in the Netherlands. Our results reveal how the optimal allocation depends on the objective of infection control. In the case of COVID-19, if we wish to minimize deaths, the optimal allocation strategy is not efficient for minimizing other outcomes, such as infections. In simulated epidemics, an allocation strategy optimized for an outcome outperforms other strategies such as the allocation from young to old, from old to young, and at random. Our simulations clarify that the current policy in the Netherlands (i.e., allocation from old to young) was concordant with the allocation scheme that minimizes deaths. The proposed method provides an optimal allocation scheme, given routine surveillance data that reflect ongoing transmissions. This approach to allocation is useful for providing plausible simulation scenarios for complex models, which give a more robust basis to determine intervention strategies.