Quantifying the risk of workplace COVID-19 clusters in terms of commuter, workplace, and population characteristics (preprint)

Objectives: To identify and quantify risk factors that contribute to clusters of COVID-19 in the workplace. Methods: We identified clusters of COVID-19 cases in the workplace and investigated the characteristics of the individuals, the workplaces, the areas they work, and the methods of commute to work, through data linkages based on Middle Layer Super Output Areas (MSOAs) in England between 20/06/2021 and 20/02/2022. We estimated associations between potential risk factors and workplace clusters, adjusting for plausible confounders identified using a Directed Acyclic Graph (DAG). Results: For most industries, increased physical proximity in the workplace was associated with increased risk of COVID-19 clusters, while increased vaccination was associated with reduced risk. Commuter demographic risk factors varied across industry, but for the majority of industries, a higher proportion of black/african/caribbean ethnicities, and living in deprived areas, was associated with increased cluster risk. A higher proportion of commuters in the 60-64 age group was associated with reduced cluster risk. There were significant associations between gender, work commute methods, and staff contract type with cluster risk, but these were highly variable across industries. Conclusions: This study has used novel national data linkages to identify potential risk factors of workplace COVID-19 clusters, including possible protective effects of vaccination and increased physical distance at work. The same methodological approach can be applied to wider occupational and environmental health research.

Potential impact of individual exposure histories to endemic human coronaviruses on age-dependence in severity of COVID-19 (preprint)

Cross-reactivity to SARS-CoV-2 from previous exposure to endemic coronaviruses (eHCoV) is gaining increasing attention as a possible driver of both protection against infection and severity of COVID-19 disease. Here, we use a stochastic individual-based model to show that heterogeneities in individual exposure histories to endemic coronaviruses are able to explain observed age patterns of hospitalisation due to COVID-19 in EU/EEA countries and the UK, provided there is (i) a decrease in cross-protection to SARS-CoV-2 with the number of eHCoV exposures and (ii) an increase in potential disease severity with number of eHCoV exposures or as a result of immune senescence. We also show that variation in health care capacity and testing efforts is compatible with country-specific differences in hospitalisation rates. Our findings call for further research on the role of cross-reactivity to endemic coronaviruses and highlight potential challenges arising from heterogeneous health care capacity and testing.

Neutralising antibodies to SARS coronavirus 2 in Scottish blood donors - a pilot study of the value of serology to determine population exposure (preprint)

BackgroundThe progression and geographical distribution of SARS coronavirus 2 (SARS-CoV-2) infection in the UK and elsewhere is unknown because typically only symptomatic individuals are diagnosed. We performed a serological study of blood donors in Scotland between the 17th of March and the 18th of May to detect neutralising antibodies to SARS-CoV-2 as a marker of past infection and epidemic progression. AimTo determine if sera from blood bank donors can be used to track the emergence and progression of the SARS-CoV-2 epidemic. MethodsA pseudotyped SARS-CoV-2 virus microneutralisation assay was used to detect neutralising antibodies to SARS-CoV-2. The study group comprised samples from 3,500 blood donors collected in Scotland between the 17th of March and 19th of May, 2020. Controls were collected from 100 donors in Scotland during 2019. ResultsAll samples collected on the 17th March, 2020 (n=500) were negative in the pseudotyped SARS-CoV-2 virus microneutralisation assay. Neutralising antibodies were detected in 6/500 donors from the 23th-26th of March. The number of samples containing neutralising antibodies did not significantly rise after the 5th-6th April until the end of the study on the 18th of May. We find that infections are concentrated in certain postcodes indicating that outbreaks of infection are extremely localised. In contrast, other areas remain comparatively untouched by the epidemic. ConclusionThese data indicate that sero-surveys of blood banks can serve as a useful tool for tracking the emergence and progression of an epidemic like the current SARS-CoV-2 outbreak.

Controlling Intramolecular Interactions in the Design of Selective, High-Affinity, Ligands for the CREBBP Bromodomain (preprint)

CREBBP (CBP or KAT3A) and its paralogue P300 (also KAT3B) are lysine acetyltransferases (KATs) that are essential for human development. They each comprise ten domains through which they interact with over 400 proteins, making them important transcriptional co-activators, and key nodes in the human protein-protein interactome. The bromodomain of CREBBP and P300 enables binding of acetylated lysine residues from histones, and a number of other important proteins, including p53, p73, E2F and GATA1. Here we report work to develop a high affinity, small molecule, ligand for the CREBBP and P300 bromodomains [(−)-OXFBD05] that shows >100-fold selectivity over the BET bromodomains. Key to the development of (−)-OXFBD05 were fundamental studies on molecular conformation in solution and when bound to the CREBBP bromodomain. In particular, the effect of an intramolecular hydrogen bond on solution state conformation, and use of an amide bioisostere, enabled the development of (−)-OXFBD05. Initial cellular studies using this ligand demonstrate that inhibition of the CREBBP/P300 bromodomain in HCT116 colon cancer cells results in lowered levels of c-Myc, and a modest but repeatable reduction in H3K18 acetylation. In hypoxia (<0.1% O 2 ), inhibition of the CREBBP/P300 bromodomain results in enhanced stabilization of HIF-1α. This presents an opportunity for modulating proteins that are affected by HIF-1α levels, including ACE2, which mediates SARS-CoV-2 infection of human cells.

Fundamental principles of epidemic spread highlight the immediate need forlarge-scale serological surveys to assess the stage of the SARS-CoV-2 epidemic (preprint)

The spread of a novel pathogenic infectious agent eliciting protective immunity is typically characterised by three distinct phases: (I) an initial phase of slow accumulation of new infections (often undetectable), (II) a second phase of rapid growth in cases of infection, disease and death, and (III) an eventual slow down of transmission due to the depletion of susceptible individuals, typically leading to the termination of the (first) epidemic wave. Before the implementation of control measures (e.g. social distancing, travel bans, etc) and under the assumption that infection elicits protective immunity, epidemiological theory indicates that the ongoing epidemic of SARS-CoV-2 will conform to this pattern. Here, we calibrate a susceptible-infected-recovered (SIR) model to data on cumulative reported SARS-CoV-2 associated deaths from the United Kingdom (UK) and Italy under the assumption that such deaths are well reported events that occur only in a vulnerable fraction of the population. We focus on model solutions which take into consideration previous estimates of critical epidemiological parameters such as the basic reproduction number (R0), probability of death in the vulnerable fraction of the population, infectious period and time from infection to death, with the intention of exploring the sensitivity of the system to the actual fraction of the population vulnerable to severe disease and death. Our simulations are in agreement with other studies that the current epidemic wave in the UK and Italy in the absence of interventions should have an approximate duration of 2-3 months, with numbers of deaths lagging behind in time relative to overall infections. Importantly, the results we present here suggest the ongoing epidemics in the UK and Italy started at least a month before the first reported death and have already led to the accumulation of significant levels of herd immunity in both countries. There is an inverse relationship between the proportion currently immune and the fraction of the population vulnerable to severe disease. This relationship can be used to determine how many people will require hospitalisation (and possibly die) in the coming weeks if we are able to accurately determine current levels of herd immunity. There is thus an urgent need for investment in technologies such as virus (or viral pseudotype) neutralization assays and other robust assays which provide reliable read-outs of protective immunity, and for the provision of open access to valuable data sources such as blood banks and paired samples of acute and convalescent sera from confirmed cases of SARS-CoV-2 to validate these. Urgent development and assessment of such tests should be followed by rapid implementation at scale to provide real-time data. These data will be critical to the proper assessment of the effects of social distancing and other measures currently being adopted to slow down the case incidence and for informing future policy direction.