Classification of unsequenced Mycobacterium tuberculosis strains in a high-burden setting using a pairwise logistic regression approach.

Over the past three decades, molecular epidemiological studies have provided new opportunities to investigate the transmission dynamics of . In most studies, a sizable fraction of individuals with notified tuberculosis cannot be included, either because they do not have culture-positive disease (and thus do not have specimens available for molecular typing) or because resources for conducting sequencing are limited. A recent study introduced a regression-based approach for inferring the membership of unsequenced tuberculosis cases in transmission clusters based on host demographic and epidemiological data.

Inferring enterovirus D68 transmission dynamics from the genomic data of two 2022 North American outbreaks.

Enterovirus D68 (EV-D68) has emerged as a significant cause of acute respiratory illness in children globally, notably following its extensive outbreak in North America in 2014. A recent outbreak of EV-D68 was observed in Ontario, Canada, from August to October 2022. Our phylogenetic analysis revealed a notable genetic similarity between the Ontario outbreak and a concurrent outbreak in Maryland, USA.

Integrating genomic and spatial analyses to describe tuberculosis transmission: a scoping review.

Tuberculosis remains a leading cause of infection-related mortality, and efforts to reduce its incidence have been hindered by an incomplete understanding of local Mycobacterium tuberculosis transmission dynamics. Advances in pathogen sequencing and spatial analysis have created new opportunities to map M tuberculosis transmission patterns more precisely. In this scoping review, we searched for studies combining pathogen genetics and location data to analyse the spatial patterns of M tuberculosis transmission and identified 142 studies published between 1994 and 2024.

Using artificial intelligence tools to automate data extraction for living evidence syntheses.

Living evidence synthesis (LES) involves repeatedly updating a systematic review or meta-analysis at regular intervals to incorporate new evidence into the summary results. It requires a considerable amount of human time investment in the article search, collection, and data extraction phases. Tools exist to automate the retrieval of relevant journal articles, but pulling data out of those articles is currently still a manual process.

Distribution and transmission of M. tuberculosis in a high-HIV prevalence city in Malawi: A genomic and spatial analysis.

Delays in identifying and treating individuals with infectious tuberculosis (TB) contribute to poor health outcomes and allow ongoing community transmission of M. tuberculosis (Mtb). Current recommendations for screening for tuberculosis specify community characteristics (e.

A vector representation for phylogenetic trees.

Good representations for phylogenetic trees and networks are important for enhancing storage efficiency and scalability for the inference and analysis of evolutionary trees for genes, genomes and species. We propose a new representation for rooted phylogenetic trees that encodes a tree on [Formula: see text] ordered taxa as a vector of length [Formula: see text] in which each taxon appears exactly twice. Using this new tree representation, we introduce a novel tree rearrangement operator, termed an , that results in a tree space of linear diameter and quadratic neighbourhood size.

Measles in Canada: modelling outbreaks with variable vaccine coverage and interventions.

Background: The global incidence of measles has increased markedly since 2023. In Canada, where measles has had elimination status for more than two decades, most cases can typically be traced to travel. While the majority of Canadians are vaccinated against the measles virus, or considered immune due to previous infection, there are communities with low vaccination coverage.

A new method for detecting mixed Mycobacterium tuberculosis infection and reconstructing constituent strains provides insights into transmission.

Background: Mixed infection with multiple strains of the same pathogen in a single host can present clinical and analytical challenges. Whole genome sequence (WGS) data can identify signals of multiple strains in samples, though the precision of previous methods can be improved. Here, we present MixInfect2, a new tool to accurately detect mixed samples from Mycobacterium tuberculosis short-read WGS data.

Uncertainty in COVID-19 transmission could undermine our ability to predict long COVID.

As SARS-CoV-2 has transitioned from a novel pandemic-causing pathogen into an established seasonal respiratory virus, focus has shifted to post-acute sequelae of COVID-19 (PASC, colloquially 'long COVID'). We use compartmental mathematical models simulating emergence of new variants to help identify key sources of uncertainty in PASC trajectories. Some parameters (such as the duration and equilibrium prevalence of infection, as well as the fraction of infections that develop PASC) matter more than others (such as the duration of immunity and secondary vaccine efficacy against PASC).

Measuring genetic diversity across populations.

Diversity plays an important role in various domains, including conservation, whether it describes diversity within a population or diversity over a set of species. While various strategies for measuring among-species diversity have emerged (e.g.

Signatures of transmission in within-host Mycobacterium tuberculosis complex variation: a retrospective genomic epidemiology study.

Background: Mycobacterium tuberculosis complex (MTBC) species evolve slowly, so isolates from individuals linked in transmission often have identical or nearly identical genomes, making it difficult to reconstruct transmission chains. Finding additional sources of shared MTBC variation could help overcome this problem. Previous studies have reported MTBC diversity within infected individuals; however, whether within-host variation improves transmission inferences remains unclear.

Early prediction of Mycobacterium tuberculosis transmission clusters using supervised learning models.

Identifying individuals with tuberculosis (TB) with a high risk of onward transmission can guide disease prevention and public health strategies. Here, we train classification models to predict the first sampled isolates in Mycobacterium tuberculosis transmission clusters from demographic and disease data. We find that supervised learning, in particular balanced random forests, can be used to develop predictive models to identify people with TB that are more likely associated with TB cluster growth, with good model performance and AUCs of ≥ 0.

Mathematical modelling for pandemic preparedness in Canada: Learning from COVID-19.

Background: The COVID-19 pandemic underlined the need for pandemic planning but also brought into focus the use of mathematical modelling to support public health decisions. The types of models needed (compartment, agent-based, importation) are described. Best practices regarding biological realism (including the need for multidisciplinary expert advisors to modellers), model complexity, consideration of uncertainty and communications to decision-makers and the public are outlined.

Canada's provincial COVID-19 pandemic modelling efforts: A review of mathematical models and their impacts on the responses.

Setting: Mathematical modelling played an important role in the public health response to COVID-19 in Canada. Variability in epidemic trajectories, modelling approaches, and data infrastructure across provinces provides a unique opportunity to understand the factors that shaped modelling strategies.

Intervention: Provinces implemented stringent pandemic interventions to mitigate SARS-CoV-2 transmission, considering evidence from epidemic models.

e3SIM: epidemiological-ecological-evolutionary simulation framework for genomic epidemiology.

Infectious disease dynamics are driven by the complex interplay of epidemiological, ecological, and evolutionary processes. Accurately modeling these interactions is crucial for understanding pathogen spread and informing public health strategies. However, existing simulators often fail to capture the dynamic interplay between these processes, resulting in oversimplified models that do not fully reflect real-world complexities in which the pathogen's genetic evolution dynamically influences disease transmission.

The Canadian VirusSeq Data Portal & Duotang: open resources for SARS-CoV-2 viral sequences and genomic epidemiology.

The COVID-19 pandemic led to a large global effort to sequence SARS-CoV-2 genomes from patient samples to track viral evolution and inform public health response. Millions of SARS-CoV-2 genome sequences have been deposited in global public repositories. The Canadian COVID-19 Genomics Network (CanCOGeN - VirusSeq), a consortium tasked with coordinating expanded sequencing of SARS-CoV-2 genomes across Canada early in the pandemic, created the Canadian VirusSeq Data Portal, with associated data pipelines and procedures, to support these efforts.

The recent rapid expansion of multidrug resistant Ural lineage Mycobacterium tuberculosis in Moldova.

The projected trajectory of multidrug resistant tuberculosis (MDR-TB) epidemics depends on the reproductive fitness of circulating strains of MDR M. tuberculosis (Mtb). Previous efforts to characterize the fitness of MDR Mtb have found that Mtb strains of the Beijing sublineage (Lineage 2.

Endemic does not mean constant as SARS-CoV-2 continues to evolve.

COVID-19 has become endemic, with dynamics that reflect the waning of immunity and re-exposure, by contrast to the epidemic phase driven by exposure in immunologically naïve populations. Endemic does not, however, mean constant. Further evolution of SARS-CoV-2, as well as changes in behavior and public health policy, continue to play a major role in the endemic load of disease and mortality.

The role of vaccine status homophily in the COVID-19 pandemic: a cross-sectional survey with modelling.

Background: Vaccine homophily describes non-heterogeneous vaccine uptake within contact networks. This study was performed to determine observable patterns of vaccine homophily, as well as the impact of vaccine homophily on disease transmission within and between vaccination groups under conditions of high and low vaccine efficacy.

Methods: Residents of British Columbia, Canada, aged ≥ 16 years, were recruited via online advertisements between February and March 2022, and provided information about vaccination status, perceived vaccination status of household and non-household contacts, compliance with COVID-19 prevention guidelines, and history of COVID-19.

Signatures of transmission in within-host variation.

Background: Because evolves slowly, transmission clusters often contain multiple individuals with identical consensus genomes, making it difficult to reconstruct transmission chains. Finding additional sources of shared variation could help overcome this problem. Previous studies have reported diversity within infected individuals; however, whether within-host variation improves transmission inferences remains unclear.

Pneumococcal population dynamics: Investigating vaccine-induced changes through multiscale modelling.

The mechanisms behind vaccine-induced strain replacement in the pneumococcus remain poorly understood. There is emerging evidence that distinct pneumococcal lineages can co-colonise for significant time periods, and that novel recombinants can readily emerge during natural colonisation. Despite this, patterns of post-vaccine replacement are indicative of competition between specific lineages.

Capturing diversity: Split systems and circular approximations for conservation.

We investigated the implications of employing a circular approximation of split systems in the calculation of maximum diversity subsets of a set of taxa in a conservation biology context where diversity is measured using Split System Diversity (SSD). We conducted a comparative analysis between the maximum SSD score and the maximum SSD set(s) of size k, efficiently determined using a circular approximation, and the true results obtained through brute-force search based on the original data. Through experimentation on simulated datasets and SNP data across 50 Atlantic Salmon populations, our findings demonstrate that employing a circular approximation can lead to the generation of an incorrect max-SSD set(s).