INTRODUCTION:Superspreading events are known to disproportionally contribute to onwards transmission of epidemic and pandemic viruses. Preventing infections in a small number of high-transmission settings is therefore an attractive public health goal. METHODS:We use deterministic and stochastic mathematical modelling to quantify the impact of intranasal sprays in containing outbreaks at a confirmed superspreading event (the 2020 SARS-CoV-2 outbreak at the Diamond Princess cruise ship) and a conference event that led to extensive transmission. RESULTS:In the Diamond Princess cruise ship case study, there exists a 7-14-day window of opportunity for widespread prophylactic intranasal spray usage to significantly impact the number of infections averted. Given an immediate response to a known SARS-CoV-2 outbreak, alongside testing and social distancing measures, prophylactic efficacy and coverage greater than 65% could reduce the average number of infections by over 90%. In the conference case study, in the absence of additional public health interventions, analyses suggest much higher prophylactic efficacy and coverage is required to achieve a similar outcome on a population level. However, prophylactic use can halve an individual's probability of being infected, and significantly reduce the probability of developing a severe infection. CONCLUSIONS:At a known potential superspreading event, early use of intranasal sprays can complement quarantining measures and significantly suppress a SARS-CoV-2 outbreak, even at suboptimal coverage. At a potential superspreading event of short duration, intranasal sprays can reduce individuals' risk of infection, but in the absence of other interventions, they cannot prevent all infections or all onwards community transmission. PLAIN LANGUAGE SUMMARY:Where crowds are in close contact in closed spaces, respiratory viruses like coronavirus spread easily. At such events, superspreading may occur: one person transmitting the virus to many other event-goers, fuelling the epidemic or pandemic. We used mathematical modelling to predict whether antiviral nose sprays which act immediately can prevent such superspreading events. We found that early use of nose sprays can suppress a SARS-CoV-2 outbreak, even if not everybody is treated with the nose spray, as long as people are also tested and use social distancing if infected. At a conference where people do not quarantine, it is more difficult to prevent spreading of the virus altogether with nose sprays alone. However, at an individual level, people who take the nose spray have lower chance of getting infected with the virus.

Neither vaccination nor natural infection result in long-lasting protection against SARS-COV-2 infection and transmission, but both reduce the risk of severe COVID-19. To generate insights into optimal vaccination strategies for prevention of severe COVID-19 in the population, we extended a Susceptible-Exposed-Infectious-Removed (SEIR) mathematical model to compare the impact of vaccines that are highly protective against severe COVID-19 but not against infection and transmission, with those that block SARS-CoV-2 infection. Our analysis shows that vaccination strategies focusing on the prevention of severe COVID-19 are more effective than those focusing on creating of herd immunity. Key uncertainties that would affect the choice of vaccination strategies are: (1) the duration of protection against severe disease, (2) the protection against severe disease from variants that escape vaccine-induced immunity, (3) the incidence of long-COVID and level of protection provided by the vaccine, and (4) the rate of serious adverse events following vaccination, stratified by demographic variables.

The COVID-19 pandemic has demonstrated that there is an unmet need for the development of novel prophylactic antiviral treatments to control the outbreak of emerging respiratory virus infections. Passive antibody-based immunisation approaches such as intranasal antibody prophylaxis have the potential to provide immediately accessible universal protection as they act directly at the most common route of viral entry, the upper respiratory tract. The need for such products is very apparent for SARS-CoV-2 at present, given the relatively low effectiveness of vaccines to prevent infection and block virus onward transmission. We explore the benefits and challenges of the use of antibody-based nasal sprays prior and post exposure to the virus. The classic susceptible-exposed-infectious-removed (SEIR) mathematical model was extended to describe the potential population-level impact of intranasal antibody prophylaxis on controlling the spread of an emerging respiratory infection in the community. Intranasal administration of monoclonal antibodies provides only a short-term protection to the mucosal surface. Consequently, sustained intranasal antibody prophylaxis of a substantial proportion of the population would be needed to contain infections. Post-exposure prophylaxis against the development of severe disease would be essential for the overall reduction in hospital admissions. Antibody-based nasal sprays could provide protection against infection to individuals that are likely to be exposed to the virus. Large-scale administration for a long period of time would be challenging. Intranasal antibody prophylaxis alone cannot prevent community-wide transmission of the virus. It could be used along with other protective measures, such as non-pharmaceutical interventions, to bridge the time required to develop and produce effective vaccines, and complement active immunisation strategies.

INTRODUCTION: We assessed the association of plasma neurofilament light chain (pNfL) with cognitive decline and neuroimaging markers, and investigated its potential relationship with the clinical progression to dementia due to Alzheimer’s disease (AD).METHODS: Individuals had evidence of amyloid beta accumulation. Linear and beta-regression models were developed to consider: i) the association between pNfL and cognition, ii) the association between the rate of change (ROC) of pNfL and that of imaging markers, iii) the temporal dynamics of pNfL before and after cognitive impairment as assessed by the Clinical Dementia Rating.RESULTS: Higher levels of pNfL were associated with declining cognition. The ROC of pNfL was associated with the ROC of ventricular, hippocampal and whole brain volumes, but not with PET amyloid. pNfL levels did not reflect the clinical progression of AD.DISCUSSION: pNfL is associated with cognitive decline and brain imaging markers. However, it is not specific to AD clinical diagnosis.

CSF biomarkers, including total-tau, neurofilament light chain (NfL) and amyloid-beta, are increasingly being used to define and stage Alzheimer's disease. These biomarkers can be measured more quickly and less invasively in plasma and may provide important information for early diagnosis of Alzheimer's disease. We used stored plasma samples and clinical data obtained from 4444 nondemented participants in the Rotterdam study at baseline (between 2002 and 2005) and during follow-up until January 2016. Plasma concentrations of total-tau, NfL, amyloid-beta(40) and amyloid-beta(42) were measured using the Simoa NF-lightVR and N3PA assays. Associations between biomarker plasma levels and incident all-cause and Alzheimer's disease dementia during follow-up were assessed using Cox proportional-hazard regression models adjusted for age, sex, education, cardiovascular risk factors and APOE epsilon 4 status. Moreover, biomarker plasma levels and rates of change over time of participants who developed Alzheimer's disease dementia during follow-up were compared with age and sex-matched dementia-free control subjects. During up to 14 years follow-up, 549 participants developed dementia, including 374 cases with Alzheimer's disease dementia. A log(2) higher baseline amyloid-beta(42) plasma level was associated with a lower risk of developing all-cause or Alzheimer's disease dementia, adjusted hazard ratio (HR) 0.61 [95% confidence interval (CI), 0.47-0.78; P<0.0001] and 0.59 (95% CI, 0.43-0.79; P = 0.0006), respectively. Conversely, a log2 higher baseline plasma NfL level was associated with a higher risk of all-cause dementia [adjusted HR 1.59 (95% CI, 1.38-1.83); P<0.0001] or Alzheimer's disease [adjusted HR 1.50 (95% CI, 1.26-1.78); P50.0001]. Combining the lowest quartile group of amyloid-beta(42) with the highest of NfL resulted in a stronger association with all-cause dementia [adjusted HR 9.5 (95% CI, 2.3-40.4); P<0.002] and with Alzheimer's disease [adjusted HR 15.7 (95% CI, 2.1-117.4); P50.0001], compared to the highest quartile group of amyloid-beta(42) and lowest of NfL. Total-tau and amyloid-beta(40) levels were not associated with all-cause or Alzheimer's disease dementia risk. Trajectory analyses of biomarkers revealed that mean NfL plasma levels increased 3.4 times faster in participants who developed Alzheimer's disease compared to those who remained dementia-free (P<0.0001), plasma values for cases diverged from controls 9.6 years before Alzheimer's disease diagnosis. Amyloid-beta(42) levels began to decrease in Alzheimer's disease cases a few years before diagnosis, although the decline did not reach significance compared to dementiafree participants. In conclusion, our study shows that low amyloid-beta(42) and high NfL plasma levels are each independently and in combination strongly associated with risk of all-cause and Alzheimer's disease dementia. These data indicate that plasma NfL and amyloid-beta(42) levels can be used to assess the risk of developing dementia in a non-demented population. Plasma NfL levels, although not specific, may also be useful in monitoring progression of Alzheimer's disease dementia.

OBJECTIVE:To determine changes in the incidence of dementia between 1988 and 2015.METHODS:This analysis was performed in aggregated data from individuals >65 years of age in 7 population-based cohort studies in the United States and Europe from the Alzheimer Cohort Consortium. First, we calculated age- and sex-specific incidence rates for all-cause dementia, and then defined nonoverlapping 5-year epochs within each study to determine trends in incidence. Estimates of change per 10-year interval were pooled and results are presented combined and stratified by sex.RESULTS:Of 49,202 individuals, 4,253 (8.6%) developed dementia. The incidence rate of dementia increased with age, similarly for women and men, ranging from about 4 per 1,000 person-years in individuals aged 65-69 years to 65 per 1,000 person-years for those aged 85-89 years. The incidence rate of dementia declined by 13% per calendar decade (95% confidence interval [CI], 7%-19%), consistently across studies, and somewhat more pronouncedly in men than in women (24% [95% CI 14%-32%] vs 8% [0%-15%]).CONCLUSION:The incidence rate of dementia in Europe and North America has declined by 13% per decade over the past 25 years, consistently across studies. Incidence is similar for men and women, although declines were somewhat more profound in men. These observations call for sustained efforts to finding the causes for this decline, as well as determining their validity in geographically and ethnically diverse populations.

Background Quantifying changes in the levels of biological and cognitive markers prior to the clinical presentation of Alzheimer’s disease (AD) will provide a template for understanding the underlying aetiology of the clinical syndrome and, concomitantly, for improving early diagnosis, clinical trial recruitment and treatment assessment. This study aims to characterise continuous changes of such markers and determine their rate of change and temporal order throughout the AD continuum. Methods The methodology is founded on the development of stochastic models to estimate the expected time to reach different clinical disease states, for different risk groups, and synchronise short-term individual biomarker data onto a disease progression timeline. Twenty-seven markers are considered, including a range of cognitive scores, cerebrospinal (CSF) and plasma fluid proteins, and brain structural and molecular imaging measures. Data from 2014 participants in the Alzheimer’s Disease Neuroimaging Initiative database is utilised. Results The model suggests that detectable memory dysfunction could occur up to three decades prior to the onset of dementia due to AD (ADem). This is closely followed by changes in amyloid-β CSF levels and the first cognitive decline, as assessed by sensitive measures. Hippocampal atrophy could be observed as early as the initial amyloid-β accumulation. Brain hypometabolism starts later, about 14 years before onset, along with changes in the levels of total and phosphorylated tau proteins. Loss of functional abilities occurs rapidly around ADem onset. Neurofilament light is the only protein with notable early changes in plasma levels. The rate of change varies, with CSF, memory, amyloid PET and brain structural measures exhibiting the highest rate before the onset of ADem, followed by a decline. The probability of progressing to a more severe clinical state increases almost exponentially with age. In accordance with previous studies, the presence of apolipoprotein E4 alleles and amyloid-β accumulation can be associated with an increased risk of developing the disease, but their influence depends on age and clinical state. Conclusions Despite the limited longitudinal data at the individual level and the high variability observed in such data, the study elucidates the link between the long asynchronous pathophysiological processes and the preclinical and clinical stages of AD.

Samenvatting Vanaf 1 juni 2020 kan iedereen met klachten of symptomen die kunnen wijzen op COVID-19 worden getest op de aanwezigheid van SARS-CoV-2 in de neuskeelholte en komen tegelijk testen voor het vaststellen van antistoffen tegen dit virus beschikbaar. We bespreken hier de kennis van dit moment over het opsporen van SARS-CoV-2 in en op slijmvlies van de neuskeelholte dat is verzameld met een wattenstaafje en in speeksel, over het verschijnen van SARS-CoV-2 antistoffen in het bloed en over de beoordeling van de uitslag van verschillende testen. Op basis van het virologisch en serologisch beloop kan een acute, recente en een doorgemaakte infectie worden onderscheiden. We bespreken daarnaast hoe aangetoond kan worden of iemand besmettelijk is en wat het verband is tussen de aanwezigheid van SARS-CoV-2-antistoffen en immuniteit tegen herinfectie.

In 2018, the National Institute of Aging-Alzheimer's Association (NIA-AA) updated its research framework outlining a biological definition of the Alzheimer's disease (AD) continuum, through the use of biomarkers relating to β-amyloid deposition, pathologic tau and neurodegeneration. While providing a construct that has been used to improve the reporting of observational and interventional clinical research, the NIA-AA reiterates that while a single cut point approach is useful in many ways, alternatives do exist. We seek to reignite the discussion around the need to improve the current binary classification, by focusing on individuals near the cut point. We fit linear mixed effects models to longitudinal data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), to estimate the trajectories of cognitive decline in cognitively healthy individuals classified as either amyloid positive or negative at baseline. We focused on β-amyloid due primarily to its relevance in recent clinical trials in at-risk pre-symptomatic individuals. Amyloid positivity was defined as having a Florbetapir amyloid PET SUVR value above 1.11. These models formed part of a sensitivity analysis, which considered progressively smaller subsets of individuals around the cut point. We demonstrate the similarities/dissimilarities in cognitive trajectories between amyloid groups over time, by considering overlapping/non-overlapping PACC credible intervals [CIs]. For example, the PACC CIs at five years since baseline for average individuals within 0.20 of the cut point (SUVR 0.91 – 1.31) do not overlap (positive: −1.63 [−2.61, -0.63]; negative: 0.18 [−0.54, 0.88]), whereas the CIs for individuals within 0.10 (SUVR 1.01 – 1.21) overlap substantially (positive: −0.55 [−1.93, 0.90]; negative: 0.04 [−1.01, 1.03]). Of note, approximately 40% of our sample that had PET measured at baseline lies within plus or minus 0.10 of the cut point. We interpret the implications this may have, most notably in the context of clinical trial recruitment. More emphasis should be placed on developing alternatives to the single cut point approach as suggested in the NIA-AA framework and associated literature. Our findings highlight the potential significance of the large number of individuals near (or, in fact, not so near) the current cut point.

Clinical trials of potential therapies for Alzheimer's Disease (AD) have shifted focus towards patients in the early stages of the disease. And the need for scores sensitive to AD specific clinical changes to be used as endpoints in trials led to the development of AD Composite Score (ADCOMS), specifically for prodromal AD. Recently, the Phase II clinical study by Eisai and Biogen's for BAN2401 which showed positive topline results used ADCOMS as their key clinical endpoint. We developed a statistical model for describing the progression of ADCOMS over time using data from Alzheimer's Disease Neuroimaging Initiative (ADNI). Longitudinal ADCOMS was modelled within a Bayesian framework using a hierarchical Bayesian beta regression model with random intercepts and slopes. Beta distribution was appropriate for our bounded continuous outcome, which could also take different shapes depending on its two parameters for skewed and heteroskedastic data. Time invariant and varying covariates were modelled for the initial status (intercept) and the growth trajectory of ADCOMS over time (slope). Posterior predictive checks were done for model validation by reproducing the scores using posterior distributions of the parameters. The statistical model described above was used to generate individual-level continuous trajectories of ADCOMS over time as a function of a number of covariates in ADNI. In particular, baseline cognitive severity measured by Mini Mental State Examination Score (MMSE) and Alzheimer's Disease Assessment Scale – Cognitive Subscale (ADAS-Cog 13) were used as covariates to explain variation in the initial score, whereas age, years of education, gender, APOE E4 allele status, ventricular volume and pathological levels of AD related plasma biomarkers were incorporated as predictors for the growth rate/ disease progression. We demonstrated that routinely collected data on demographics, biomarkers and cognitive test scores are highly predictive of the longitudinal progression of the disease as assessed by ADCOMS. With treatment efficacy having some quantifiable effect on an individual's trajectory, the model presented here will be used to simulate clinical trials for potential therapies targeting prodromal AD patients with ADCOMS as the primary endpoint.

Background: An increasing number of HIV-positive individuals now start antiretroviral therapy (ART) with high CD4 cell counts. We investigated whether this makes restoration of CD4 and CD8 cell counts and the CD4:CD8 ratio during virologically suppressive ART to median levels seen in HIV-uninfected individuals more likely and whether restoration depends on gender, age, and other individual characteristics. Methods: We determined median and quartile reference values for CD4 and CD8 cell counts and their ratio using cross-sectional data from 2309 HIV-negative individuals. We used longitudinal measurements of 60,997 HIV-positive individuals from the Antiretroviral Therapy Cohort Collaboration in linear mixed-effects models. Results: When baseline CD4 cell counts were higher, higher long-term CD4 cell counts and CD4:CD8 ratios were reached. Highest long-term CD4 cell counts were observed in middle-aged individuals. During the first 2 years, median CD8 cell counts converged toward median reference values. However, changes were small thereafter and long-term CD8 cell count levels were higher than median reference values. Median 8-year CD8 cell counts were higher when ART was started with <250 CD4 cells/mm3. Median CD4:CD8 trajectories did not reach median reference values, even when ART was started at 500 cells/mm3. Discussion: Starting ART with a CD4 cell count of ≥500 cells/mm3 makes reaching median reference CD4 cell counts more likely. However, median CD4:CD8 ratio trajectories remained below the median levels of HIV-negative individuals because of persisting high CD8 cell counts. To what extent these subnormal immunological responses affect specific clinical endpoints requires further investigation.

The 2018 National Institute on Aging and the Alzheimer's Association (NIA-AA) research framework recently redefined Alzheimer's disease (AD) as a biological construct, based on in vivo biomarkers reflecting key neuropathologic features. Combinations of normal/abnormal levels of three biomarker categories, based on single thresholds, form the AD signature profile that defines the biological disease state as a continuum, independent of clinical symptomatology. While single thresholds may be useful in defining the biological signature profile, we provide evidence that their use in studies with cognitive outcomes merits further consideration. Using data from the Alzheimer's Disease Neuroimaging Initiative with a focus on cortical amyloid binding, we discuss the limitations of applying the biological definition of disease status as a tool to define the increased likelihood of the onset of the Alzheimer's clinical syndrome and the effects that this may have on trial study design. We also suggest potential research objectives going forward and what the related data requirements would be.

To date nearly all clinical trials of Alzheimer’s disease (AD) therapies have failed. These failures are, at least in part, attributable to poor endpoint choice and to inadequate recruitment criteria. Recently, focus has shifted to targeting at-risk populations in the preclinical stages of AD thus improved predictive markers for identifying individuals likely to progress to AD are crucial to help inform the sample of individuals to be recruited into clinical trials. We focus on hippocampal volume (HV) and assess the added benefit of combining HV and rate of hippocampal atrophy over time in relation to disease progression. Following the cross-validation of previously published estimates of the predictive value of HV, we consider a series of combinations of HV metrics and show that a combination of HV and rate of hippocampal atrophy characterises disease progression better than either measure individually. Furthermore, we demonstrate that the risk of disease progression associated with HV metrics does not differ significantly between clinical states. HV and rate of hippocampal atrophy should therefore be used in tandem when describing AD progression in at-risk individuals. Analyses also suggest that the effects of HV metrics are constant across the continuum of the early stages of the disease.

There exist a large number of cohort studies that have been used to identify genetic and biological risk factors for developing Alzheimer's disease (AD). However, there is a disagreement between studies as to how strongly these risk factors affect the rate of progression through diagnostic groups toward AD. We have calculated the probability of transitioning through diagnostic groups in six studies and considered how uncertainty around the strength of the effect of these risk factors affects estimates of the distribution of individuals in each diagnostic group in an AD clinical trial simulator. In this work, we identify the optimal choice of widely collected variables for comparing data sets and calculating probabilities of progression toward AD. We use the estimated transition probabilities to inform stochastic simulations of AD progression that are based on a Markov model and compare predicted incidence rates to those in a community-based study, the Cardiovascular Health Study.

Chronological age alone is not a sufficient measure of the true physiological state of the body. The aims of the present study were to: (1) quantify biological age based on a physiological biomarker composite model; (2) and evaluate its association with death and age-related disease onset in the setting of an elderly population. Using structural equation modeling we computed biological age for 1699 individuals recruited from the first and second waves of the Rotterdam study. The algorithm included nine physiological parameters (c-reactive protein, creatinine, albumin, total cholesterol, cytomegalovirus optical density, urea nitrogen, alkaline phosphatase, forced expiratory volume and systolic blood pressure). We assessed the association between biological age, all-cause mortality, all-cause morbidity and specific age-related diseases over a median follow-up of 11 years. Biological age, compared to chronological age or the traditional biomarkers of age-related diseases, showed a stronger association with all-cause mortality (HR 1.15 vs. 1.13 and 1.10), all-cause morbidity (HR 1.06 vs. 1.05 and 1.03), stroke (HR 1.17 vs. 1.08 and 1.04), cancer (HR 1.07 vs. 1.04 and 1.02) and diabetes mellitus (HR 1.12 vs. 1.01 and 0.98). Individuals who were biologically younger exhibited a healthier life-style as reflected in their lower BMI (P < 0.001) and lower incidence of stroke (P < 0.001), cancer (P < 0.01) and diabetes mellitus (P = 0.02). Collectively, our findings suggest that biological age based on the biomarker composite model of nine physiological parameters is a useful construct to assess individuals 65 years and older at increased risk for specific age-related diseases.

INTRODUCTION:Cerebral small vessel disease is increasingly linked to dementia.METHODS:We systematically searched Medline, Embase, and Cochrane databases for prospective population-based studies addressing associations of white matter hyperintensities, covert brain infarcts (i.e., clinically silent infarcts), and cerebral microbleeds with risk of all-dementia or Alzheimer's disease and performed meta-analyses.RESULTS:We identified 11 studies on white matter hyperintensities, covert brain infarcts, or cerebral microbleeds with risk of all-dementia or Alzheimer's disease. Pooled analyses showed an association of white matter hyperintensity volume and a borderline association of covert brain infarcts with risk of all-dementia (hazard ratio: 1.39 [95% confidence interval: 1.00; 1.94], N = 3913, and 1.47 [95% confidence interval: 0.97; 2.22], N = 8296). Microbleeds were not statistically significantly associated with an increased risk of all-dementia (hazard ratio: 1.25 [95% confidence interval: 0.66; 2.38], N = 8739).DISCUSSION:White matter hyperintensities are associated with an increased risk of all-dementia and Alzheimer's disease in the general population. However, studies are warranted to further determine the role of markers of cerebral small vessel disease in dementia.

To date, Alzheimer's disease (AD) clinical trials have been largely unsuccessful. Failures have been attributed to a number of factors including ineffective drugs, inadequate targets, and poor trial design, of which the choice of endpoint is crucial. Using data from the Alzheimer's Disease Neuroimaging Initiative, we have calculated the minimum detectable effect size (MDES) in change from baseline of a range of measures over time, and in different diagnostic groups along the AD development trajectory. The Functional Activities Questionnaire score had the smallest MDES for a single endpoint where an effect of 27% could be detected within 3 years in participants with Late Mild Cognitive Impairment (LMCI) at baseline, closely followed by the Clinical Dementia Rating Sum of Boxes (CDRSB) score at 28% after 2 years in the same group. Composite measures were even more successful than single endpoints with an MDES of 21% in 3 years. Using alternative cognitive, imaging, functional, or composite endpoints, and recruiting patients that have LMCI could improve the success rate of AD clinical trials.

Despite the progressive nature of Alzheimer’s disease and other dementias, it is observed that many individuals that are diagnosed with mild cognitive impairment (MCI) in one clinical assessment, may return back to normal cognition (CN) in a subsequent assessment. Less frequently, such ‘back-transitions’ are also observed in people that had already been diagnosed with later stages of dementia. In this study, an analysis was performed on two longitudinal cohort datasets provided by 1) the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and 2) the National Alzheimer’s Coordinating Centre (NACC). The focus is on the observed improvement of individuals’ clinical condition recorded in these datasets to explore potential associations with different factors. It is shown that, in both datasets, transitions from MCI to CN are significantly associated with younger age, better cognitive function, and the absence of ApoE ɛ4 alleles. Better cognitive function and in some cases the absence of ApoE ɛ4 alleles are also significantly associated with transitions from types of dementia to less severe clinical states. The effect of gender and education is not clear-cut in these datasets, although highly educated people who reach MCI tend to be more likely to show an improvement in their clinical state. The potential effect of other factors such as changes in symptoms of depression is also discussed. Although improved clinical outcomes can be associated with many factors, better diagnostic tools are required to provide insight into whether such improvements are a result of misdiagnosis, and if they are not, whether they are linked to improvements in the underlying neuropathological condition.