The need for methodological pluralism in epidemiological modelling.

During the Covid-19 pandemic, the best-performing modelling groups were not always the best-resourced. This paper seeks to understand and learn from notable predictions in two reports by the UK's Scientific Advisory Group for Emergencies (SAGE). In July 2021, SAGE reported that, after the upcoming lifting of restrictions ("Freedom Day") cases would "almost certainly remain extremely high for the rest of the summer" and that hospitalisations per day would peak between 100 and 10,000.

A systematic review of sample size estimation accuracy on power in malaria cluster randomised trials measuring epidemiological outcomes.

Introduction: Cluster randomised trials (CRTs) are the gold standard for measuring the community-wide impacts of malaria control tools. CRTs rely on well-defined sample size estimations to detect statistically significant effects of trialled interventions, however these are often predicted poorly by triallists. Here, we review the accuracy of predicted parameters used in sample size calculations for malaria CRTs with epidemiological outcomes.

Seamless, rapid, and accurate analyses of outbreak genomic data using split -mer analysis.

Sequence variation observed in populations of pathogens can be used for important public health and evolutionary genomic analyses, especially outbreak analysis and transmission reconstruction. Identifying this variation is typically achieved by aligning sequence reads to a reference genome, but this approach is susceptible to reference biases and requires careful filtering of called genotypes. There is a need for tools that can process this growing volume of bacterial genome data, providing rapid results, but that remain simple so they can be used without highly trained bioinformaticians, expensive data analysis, and long-term storage and processing of large files.

CELEBRIMBOR: core and accessory genes from metagenomes.

Motivation: Metagenome-Assembled Genomes (MAGs) or Single-cell Amplified Genomes (SAGs) are often incomplete, with sequences missing due to errors in assembly or low coverage. This presents a particular challenge for the identification of true gene frequencies within a microbial population, as core genes missing in only a few assemblies will be mischaracterized by current pangenome approaches.

Results: Here, we present CELEBRIMBOR, a Snakemake pangenome analysis pipeline which uses a measure of genome completeness to automatically adjust the frequency threshold at which core genes are identified, enabling accurate core gene identification in MAGs and SAGs.

Real-time estimation of immunological responses against emerging SARS-CoV-2 variants in the UK: a mathematical modelling study.

Background: The emergence of SARS-CoV-2 variants and COVID-19 vaccination have resulted in complex exposure histories. Rapid assessment of the effects of these exposures on neutralising antibodies against SARS-CoV-2 infection is crucial for informing vaccine strategy and epidemic management. We aimed to investigate heterogeneity in individual-level and population-level antibody kinetics to emerging variants by previous SARS-CoV-2 exposure history, to examine implications for real-time estimation, and to examine the effects of vaccine-campaign timing.

SARS-CoV-2 Dynamics in the Premier League Testing Program, United Kingdom.

During 2020-2022, players and staff in the English Premier League in the United Kingdom were tested regularly for SARS-CoV-2 with the aim of creating a biosecure bubble for each team. We found that prevalence and reinfection estimates were consistent with those from other studies and with community infection trends.

Recent approaches in computational modelling for controlling pathogen threats.

In this review, we assess the status of computational modelling of pathogens. We focus on three disparate but interlinked research areas that produce models with very different spatial and temporal scope. First, we examine antimicrobial resistance (AMR).

Choice Architecture in Opioid Safety Alerting.

The need for effective and efficient clinical decision support (CDS) embedded in electronic health record (EHR) processes is growing. Using choice architecture design strategies may increase effectiveness of CDS solutions. The authors describe implementation of an opioid risk alert and subsequent revisions of that alert to increase effectiveness and reduce alert volumes.

Within-host SARS-CoV-2 viral kinetics informed by complex life course exposures reveals different intrinsic properties of Omicron and Delta variants.

The emergence of successive SARS-CoV-2 variants of concern (VOC) during 2020-22, each exhibiting increased epidemic growth relative to earlier circulating variants, has created a need to understand the drivers of such growth. However, both pathogen biology and changing host characteristics - such as varying levels of immunity - can combine to influence replication and transmission of SARS-CoV-2 within and between hosts. Disentangling the role of variant and host in individual-level viral shedding of VOCs is essential to inform COVID-19 planning and response, and interpret past epidemic trends.

Embedding a State-Wide Prescription Drug Monitoring Program into the Electronic Health Record.

A new FHIR-based (fast healthcare interoperability resource), EHR-integrated (electronic health record) application was created that embeds directly into prescribers' workflows. The intervention automatically performs MME (morphine milligram equivalent) calculations, highlights unsafe thresholds, while also presenting controlled-substance medications each patient is using. Using this intervention, the number of clinicians who have checked a patient's controlled substance prescription data has increased 57.

Improving Head CT Scan Decisions for Pediatric Minor Head Trauma in General Emergency Departments: A Pragmatic Implementation Study.

Study Objective: To measure the effectiveness of a multimodal strategy, including simultaneous implementation of a clinical decision support system, to sustain adherence to a clinical pathway for care of children with minor head trauma treated in general emergency departments (EDs).

Methods: Prospective, type III hybrid effectiveness-implementation cohort study with a nonrandomized stepped-wedge design and monthly repeated site measures. The study population included pediatric minor head trauma encounters from July 2018 to December 2020 at 21 urban and rural general ED sites in an integrated health care system.

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.

Comparative assessment of methods for short-term forecasts of COVID-19 hospital admissions in England at the local level.

Background: Forecasting healthcare demand is essential in epidemic settings, both to inform situational awareness and facilitate resource planning. Ideally, forecasts should be robust across time and locations. During the COVID-19 pandemic in England, it is an ongoing concern that demand for hospital care for COVID-19 patients in England will exceed available resources.

Inference of the SARS-CoV-2 generation time using UK household data.

The distribution of the generation time (the interval between individuals becoming infected and transmitting the virus) characterises changes in the transmission risk during SARS-CoV-2 infections. Inferring the generation time distribution is essential to plan and assess public health measures. We previously developed a mechanistic approach for estimating the generation time, which provided an improved fit to data from the early months of the COVID-19 pandemic (December 2019-March 2020) compared to existing models (Hart et al.

Correction: Practical considerations for measuring the effective reproductive number, Rt.

[This corrects the article DOI: 10.1371/journal.pcbi.

Comparative assessment of methods for short-term forecasts of COVID-19 hospital admissions in England at the local level.

Background: Forecasting healthcare demand is essential in epidemic settings, both to inform situational awareness and facilitate resource planning. Ideally, forecasts should be robust across time and locations. During the COVID-19 pandemic in England, it is an ongoing concern that demand for hospital care for COVID-19 patients in England will exceed available resources.

Genomic reconstruction of the SARS-CoV-2 epidemic in England.

The evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus leads to new variants that warrant timely epidemiological characterization. Here we use the dense genomic surveillance data generated by the COVID-19 Genomics UK Consortium to reconstruct the dynamics of 71 different lineages in each of 315 English local authorities between September 2020 and June 2021. This analysis reveals a series of subepidemics that peaked in early autumn 2020, followed by a jump in transmissibility of the B.

Contact tracing is an imperfect tool for controlling COVID-19 transmission and relies on population adherence.

Emerging evidence suggests that contact tracing has had limited success in the UK in reducing the R number across the COVID-19 pandemic. We investigate potential pitfalls and areas for improvement by extending an existing branching process contact tracing model, adding diagnostic testing and refining parameter estimates. Our results demonstrate that reporting and adherence are the most important predictors of programme impact but tracing coverage and speed plus diagnostic sensitivity also play an important role.

When intuition falters: repeated testing accuracy during an epidemic.

Widespread, repeated testing using rapid antigen tests to proactively detect asymptomatic SARS-CoV-2 infections has been a promising yet controversial topic during the COVID-19 pandemic. Concerns have been raised over whether currently authorized lateral flow tests are sufficiently sensitive and specific to detect enough infections to impact transmission whilst minimizing unnecessary isolation of false positives. These concerns have often been illustrated using simple, textbook calculations of positivity rates and positive predictive value assuming fixed values for sensitivity, specificity and prevalence.

Exploring surveillance data biases when estimating the reproduction number: with insights into subpopulation transmission of COVID-19 in England.

The time-varying reproduction number (: the average number of secondary infections caused by each infected person) may be used to assess changes in transmission potential during an epidemic. While new infections are not usually observed directly, they can be estimated from data. However, data may be delayed and potentially biased.