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PubMed2026

Stenotrophomonas maltophilia in the Antimicrobial Resistance Era: Species-Complex Taxonomy, Pathogenesis, Evolving Therapeutic Priorities, and Genomic Surveillance.

Stenotrophomonas maltophilia is a globally distributed, aerobic, non-fermenting Gram-negative bacillus increasingly recognized as an opportunistic pathogen in hospitalized and immunocompromised patients. Clinical interpretation is challenging because respiratory and device-associated isolates may represent colonization, polymicrobial infection, or true invasive disease. Recent genomic studies further suggest that organisms historically identified as S. maltophilia comprise a genetically diverse species complex, with implications for epidemiology, virulence, resistance surveillance, and susceptibility testing. Treatment is difficult because of biofilm formation, persistence in water-associated healthcare reservoirs, and intrinsic or acquired resistance mediated by L1 and L2 β-lactamases, multidrug efflux pumps, reduced permeability, mobile resistance determinants, and biofilm-associated tolerance. Current IDSA guidance identifies cefiderocol monotherapy as the preferred treatment for invasive S. maltophilia infection, whereas aztreonam-avibactam and agents such as trimethoprim-sulfamethoxazole, levofloxacin, and minocycline occupy alternative or combination-based roles. Nevertheless, the therapeutic evidence base remains uneven, and clinical decisions should integrate infection severity, source control, susceptibility findings, pharmacokinetic/pharmacodynamic (PK/PD) exposure, toxicity, infection site, and host-related factors. This review summarizes advances in taxonomy, epidemiology, pathogenesis, diagnostics, resistance, treatment, infection prevention, and genomic surveillance, and highlights the need for standardized identification, validated breakpoints, prospective comparative-effectiveness studies, and pragmatic or adaptive trial designs.

L1 β-lactamase↗
PubMed2025

Developing and Benchmarking One Health Genomic Surveillance Tools for Influenza A Virus in Wastewater.

Influenza A viruses (IAV) remain a persistent One Health threat, and whole-genome sequencing from wastewater offers a promising surveillance tool. However, IAV is at low abundance in wastewater, making it difficult to sequence. We benchmarked four targeted enrichment methods suited for whole-genome sequencing including custom and off-the-shelf amplicon and probe-based methods. Our custom HA tiled-amplicon panel was sensitive, fast, and cost-effective, making it suitable for monitoring low-abundance seasonal variants of known subtypes. However, its reliance on conserved and intact primer-binding sites limited primer design to fewer subtypes. A previously published universal amplicon method targeted all IAV subtypes, but it performed poorly in wastewater due to its reliance on intact genome segments. Probe-capture methods were resilient to RNA degradation and mismatches, potentially enabling broader surveillance and detection of emerging strains. However, probes were costly, labor-intensive, and less sensitive than tiled-amplicon. When testing compatibility of sequencing methods with upstream virus concentration and extraction methods, ultrafiltration-based virus concentration outperformed large-volume direct extraction with all four sequencing methods. This set of benchmarking comparisons and custom panels provides needed information for the translation of IAV genomic sequencing into a routine component of wastewater surveillance.

Journal Article↗
PubMed2026

Whole-genome surveillance supports hazard profiling of Escherichia coli lineages in recycled water treatment systems.

UNLABELLED: The use of treated wastewater is increasingly important for sustainable water management under a changing climate, yet conventional monitoring based on Escherichia coli enumeration provides limited insight into strain diversity and associated public health hazards. Here, we applied longitudinal whole-genome sequencing (WGS) to 180 E. coli isolates collected across the treatment continuum of a recycled water facility, from influent to final effluent. Genomic analysis revealed extensive strain-level heterogeneity, comprising 88 sequence types across eight phylogroups, with greater diversity in influent than in treated effluent. Phylogenetic comparisons with contextual Australian genomes indicated clustering with strains associated with companion animals, wild birds, humans, and livestock, suggesting multiple potential source reservoirs rather than a single dominant origin, although source contributions were not definitive. Despite a >90% reduction in total E. coli loads, isolates recovered from upstream and downstream stages exhibited broadly comparable virulence factor and antimicrobial resistance gene (ARG) profiles, suggesting that, within the cultured isolate collection, reductions in abundance exceeded shifts in genomic composition. To assess operational relevance, we prototyped a genomics-informed hazard framework integrating virulence determinants, ARGs, plasmid-associated mobility, and reuse-specific exposure context. Using this framework, 92.8% of isolates were classified as low hazard, and 7.2% as moderate hazard, with no isolates meeting criteria for high or critical hazard classifications. These findings demonstrate that genomic profiling of indicator organisms can reveal population structure and hazard heterogeneity not captured by conventional enumeration alone, and can provide a practical basis for incorporating genomic information into hazard-informed monitoring of recycled water systems. IMPORTANCE: Routine recycled water monitoring relies largely on culture-based E. coli counts, which indicate regulatory compliance but provide limited insight into strain diversity, persistence, and genomic characteristics relevant to public health. Using longitudinal whole-genome sequencing, we show that genetically distinct E. coli lineages, including isolates carrying combinations of virulence and antimicrobial resistance determinants, can persist through advanced treatment despite substantial reductions in overall E. coli loads. While most isolates were classified as low genomic hazard and no high- or critical-hazard isolates were detected, these findings demonstrate that conventional enumeration alone cannot distinguish between genetically diverse lineages with differing hazard potential in highly treated systems. By integrating genomic data into a hazard classification framework, this study demonstrates an applied approach to contextualize E. coli detections and distinguish low-risk background populations from isolates with elevated genomic hazard profiles. This work supports the use of genomic profiling of indicator organisms to improve surveillance, inform treatment performance assessment, and enable more risk-based management of recycled water systems.

Escherichia coli↗
PubMed2026

Genomic surveillance reveals escalating antimicrobial resistance and plasmid diversity in clinical Salmonella 1,4,[5],12:i:- ST34 isolates from Guizhou Province, China.

INTRODUCTION: Salmonella 1,4,[5],12:i:- ST34 has emerged as a significant public health issue due to its association with various antimicrobial resistance genes (ARGs) and transferable plasmids. However, its genomic characteristics and potential influence on public health in Guizhou have not been comprehensively assessed. METHODS: From 2019 to 2023, a 5-year surveillance was conducted in nine cities (prefectures) of Guizhou Province. We integrated phenotypic and genomic analyses of 281 clinical Salmonella 1,4,[5],12:i:- ST34 isolates to investigate the prevalence of ARGs and plasmids and to analyze the molecular epidemiology and evolution. RESULTS: The isolates exhibited resistance to first-line antibiotics, with 22.4% for ciprofloxacin, 11.4% for azithromycin, 18.5% for ceftazidime, and 39.1% for cefotaxime. ARGs showed substantial agreement with phenotypes for tetracycline, macrolides, third-generation cephalosporins (3GCs), carbapenems, and colistin (80.8-100.0% consistency; Kappa: 0.50-1.00). Plasmid analysis identified IncQ1 (84.3%) and IncHI2/IncHI2A (26.3%) as the main replicons, with the variety of plasmid replicons increasing from 7 to 21 over the 5 years. ARGs associated with resistance to critically important antibiotics (CIAs) were frequently predicted to be located on plasmid-associated contigs, with significant associations observed between IncHI2/IncHI2A plasmids and ARGs conferring resistance to fluoroquinolones, macrolides, and cephalosporins (P < 0.05). Molecular typing divided 281 isolates into 37 cgSTs, with cgST52428 being the most common. Molecular epidemiological analysis revealed that Guizhou isolates primarily clustered together, sharing close genetic ties with those from Sichuan and Guangdong, and exhibited the highest genetic similarity to pork-derived isolates. Phylogenetic analysis revealed clustering of CIA-resistant ARGs and plasmids in Clades 4 and 5, with a significant association between IncHI2/IncHI2A plasmids and CIA-resistant ARGs (&#x3c7;2 = 112.12, P < 0.001). Additionally, class 1 integron was associated with higher ARG burdens, while virulence-associated genes were conserved and predominantly chromosome-associated. Gene-content analysis revealed that isolates in Clades 4 and 5 harbored the largest mean gene complements, and cgST52428 isolates also harbored the largest among dominant cgSTs. DISCUSSION: This study presents a comprehensive genomic profile of Salmonella 1,4,[5],12:i:- ST34 in Guizhou, providing essential data for exploring the resistance characteristics and investigating the molecular epidemiology of Salmonella 1,4,[5],12:i:-.

ST34↗
PubMed2025

Identifying genomic surveillance gaps in Africa for the global public health response to West Nile virus: a systematic review.

West Nile virus (WNV) is a priority pathogen that poses a high risk for public health emergencies of global concern. Although WNV is endemic to Africa, only few (n=63) whole genomic sequences are available from the continent. In this Review, we examined the status of the molecular testing and genomic sequencing of WNV across Africa and mapped its global spatiotemporal spread. WNV has been detected in 39 African countries, the Canary Islands, and R&#xe9;union Island. Although publications, including those with molecular data, originated from 24 of these countries, genomic sequences were available from only 16 countries. Our analysis identified regions with detected viral circulation but without molecular surveillance. The current literature has substantial knowledge gaps in terms of the disease burden, molecular epidemiology, and distribution of WNV in Africa. Addressing these gaps requires an integrated One Health surveillance approach, which is challenging to establish. We propose three key surveillance needs that could improve the current understanding of the WNV disease burden in Africa, to strengthen the global public health response to this vector-borne disease.

West Nile Fever↗
PubMed2026

Long-term clinical and genomic surveillance of rare respiratory enterovirus C types in France, 2013-2025.

INTRODUCTION: Rare enterovirus types assigned to species C (EV-C) display respiratory tropism and may be associated with neurological involvement, which display similarities to EV-D68 disease. PATIENTS AND METHODS: We conducted continuous enterovirus/rhinovirus (EV/RV) surveillance between 2013 and 2025, including systematic EV/RV screening of all respiratory samples and reflex VP4/VP2 sequencing (a total of 5855 samples). When an EV-C strain was detected, the VP1-coding and complete genome sequence was sequenced to investigate phylogenetic relationships and to identify any recombinant forms. RESULTS: Over the 13-year period, 30 EV-C infections were identified from respiratory samples, with 23 cases (77%) detected between 2013 and 2018. EV-C105 was the most frequent type (n&#x202f;=&#x202f;11), followed by EV-C104 (n&#x202f;=&#x202f;8), EV-C109 (n&#x202f;=&#x202f;6), and EV-C117 (n&#x202f;=&#x202f;5). We also document the first detection of EV-C117 in France and only the second case reported in Europe since its initial description in 2011 in Lithuania. Clinical data were available for 25 patients, of whom 19 (76%) were children. Respiratory symptoms predominated (17/25, 68%), and 7 patients presented with lower respiratory tract infections. Hospitalization was required in 18 cases (72%), including three with ICU admissions (12%). Nearly half of the patients (12/25, 48%) had at least one risk factor for severe respiratory disease. Across all respiratory EV-C types, recovered sequences clustered with contemporary global strains. CONCLUSIONS: This long-term surveillance highlights the sustained circulation of multiple respiratory EV-C types in France and underscores the need for continued clinical and genomic monitoring to assess the evolution and pathogenic potential of these enteroviruses.

Complete genome characterization↗
PubMed2026

Multimodal genomic surveillance for respiratory pathogens at four U.S. international airports: A comparison of air, wastewater, clinical, and national surveillance data.

Early detection of outbreaks and emerging pathogens is critical for public health and global biosecurity. Airports, as major international travel hubs with dense, enclosed populations, are high-risk settings for disease transmission and potential pathogen introduction. The U.S. Centers for Disease Control and Prevention, in collaboration with Ginkgo Biosecurity and the University of Wisconsin-Madison, implemented air monitoring for pathogen surveillance in congregate areas at four U.S. international airports. From October 2023 to August 2024, SARS-CoV-2 was detected by PCR in 98.3% of air samples and influenza A in 17.2%. Influenza A positivity in air samples correlated with aviation wastewater (r&#x2009;=&#x2009;0.48), traveler nasal swab positivity (r&#x2009;=&#x2009;0.73), and national clinical surveillance (r&#x2009;=&#x2009;0.86), whereas SARS-CoV-2 measurements did not correlate significantly across these modalities. Targeted amplicon sequencing of SARS-CoV-2 from air samples identified contemporaneous lineages also detected in wastewater collected from the same airports. Targeted enrichment sequencing detected 30 viral species and recovered high-quality genomes for SARS-CoV-2, influenza, bocavirus, and seasonal coronaviruses. Together, these findings demonstrate that air sampling can complement aviation wastewater surveillance at ports of entry, although performance and concordance vary by pathogen and sample type.

Journal Article↗
PubMed2026

Genomic surveillance of a deeply sampled local population reveals age-specific drivers of RSV transmission.

Respiratory syncytial virus (RSV) disproportionately causes severe infections among infants and older adults, yet the key age group responsible for viral spread to other age groups remains poorly defined. While current immunization approaches effectively reduce disease severity among the most vulnerable, identifying the core drivers of infection is essential to effectively disrupt population-level transmission. By generating 910 whole-genome viral sequences of RSV from all age groups (<1 to 65+ years) in Connecticut, we identified that children aged 12-35 months are the primary drivers of viral transmission to other age groups. This group significantly shapes the genetic diversity of circulating strains. Furthermore, we found that RSV is introduced into the community through frequent and independent entries from other US regions throughout the year, rather than through a single explosive seasonal introduction or long-term local persistence. Ultimately, our findings justify prevention strategies that expand beyond reducing disease burden to actively prioritizing the reduction of transmission and infection.

Journal Article↗
PubMed2026

Genomic wastewater surveillance of human and animal influenza A viruses in California during the 2024-2025 flu season.

BACKGROUND: Wastewater genomic surveillance provides an opportunity to detect human and animal influenza A virus (IAV). We aimed to implement an IAV genomic surveillance framework agnostic to subtype, which enables recovery of IAV from multiple hosts and estimation of proportions across subtypes. METHODS: We conducted IAV genomic surveillance in wastewater during the 2024-2025 flu season at multiple sites in California and compared these data with available human clinical IAV sequences and test positivity. We applied a custom whole-genome, multi-host IAV probe enrichment panel and adapted our custom expectation-maximization (EM) algorithm to deconvolute IAV mixtures in wastewater and infer subtype relative abundances. Absolute IAV concentrations were quantified using RT-PCR-based assays. H5N1 wastewater and clinical sequences were further characterized by constructing a whole-genome maximum-likelihood phylogenetic tree. Finally, we performed variant analysis to examine amino acid substitutions detected in wastewater. FINDINGS: Our IAV probe enrichment method and EM algorithm successfully enriched all eight segments of three circulating IAV subtypes and accurately estimated subclade relative abundances for mixed IAV samples. Seasonal human H1N1pdm09 and H3N2 were detected throughout the study period from both wastewater and clinical sequencing data, with H1N1 subclades 6B.1A.5a.2a.1 and 6B.1A.5a.2a co-circulating, and H3N2 dominated by subclade 3C.2a1b.2a.2a.3a.1. Wastewater surveillance consistently detected H5N1 clade 2.3.4.4b across three monitored wastewater sites, while clinical H5N1 detections, from anywhere in CA, were sporadic and rare. Whole-genome phylogenetic analysis revealed that wastewater H5N1 sequences clustered with reference sequences associated with dairy cow and avian infections, while all human clinical H5N1 sequences clustered exclusively with reference sequences associated with dairy cow infections. Amino acid substitutions were identified across viral segments, and no mutations associated with mammalian adaptation were observed from wastewater samples. INTERPRETATION: When IAV concentrations were dominated by seasonal human subtypes rather than H5N1, subtype patterns aligned between wastewater and clinical data. While sequencing IAV in wastewater was unable to distinguish if H5N1 detections were due to human or animal infections, it was able to provide clade-level information about H5N1 found in wastewater that could be useful in the future. Wastewater genomic surveillance can complement clinical surveillance, increasing ability to detect all circulating IAV subtypes and enhancing public health preparedness from a One Health perspective.

Journal Article↗
PubMed2024

A series of patients infected with the emerging tick-borne Yezo virus in China: an active surveillance and genomic analysis.

BACKGROUND: Yezo virus (YEZV) is an emerging tick-borne pathogen, which was initially reported in Japan in 2021. Only one patient had been reported in China so far. We aimed to describe the epidemiological, clinical, and laboratory findings of a series of patients, and to characterise the viral genomes of YEZV. METHODS: In this active surveillance and genomic analysis, we conducted active surveillance at Mudanjiang Forestry Central Hospital, Heilongjiang Province of northeast China. Participants were eligible for inclusion if they sought medical care for a recent tick bite between May 1 and July 31, in 2022 and 2023, and between May 1 and July 10, in 2024. We collected sera from participants to detect YEZV infection by meta-transcriptomic sequencing, real-time RT-PCR, and indirect immunofluorescence assay. We isolated YEZV by cell culture and characterised the pathogen by morphological and phylogenetic analyses. FINDINGS: A series of 18 patients with YEZV infection (12 male and six female; median age 53 years, IQR 45-60) were identified among 988 participants. The patients presented with fever (18 patients, 100%), headache (ten patients, 56%), dizziness (nine patients, 50%), malaise (three patients, 17%), lumbago (three patients, 17%), and cough (three patients, 17%). Nine (50%) patients had rash around the tick bite site and four (22%) had lymphadenopathy. Nine (50%) patients had gastrointestinal symptoms, and five (28%) had neurological symptoms. We observed leukopenia in ten (63%) and thrombocytopenia in five (31%) of 16 assessed patients. Elevated hepatic transaminase concentrations were identified in 13 (72%) of all 18 patients, lactate dehydrogenase or &#x3b1;-hydroxybutyric dehydrogenase in nine (50%), serum amyloid protein A in 13 (72%), and hypersensitive C-reactive protein in ten (56%). Eight (7%) of 119 Ixodes persulcatus ticks removed from participants were positive for YEZV. Three YEZV strains were isolated from the sera of patients. Ten viral genomes were obtained from five patients, a blood-sucking I persulcatus removed from a participant, and four host-questing tick samples collected in the areas where patients were identified or in the adjacent region. Phylogenetic analyses revealed that YEZVs in either patients or ticks were divided into two clades, each with distinct mutations. INTERPRETATION: Awareness of YEZV infection is important and clinicians should consider the virus when diagnosing patients with suitable symptoms. FUNDING: National Key Research and Development Program of China. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Humans↗
PubMed2026

Hospital transmission of methicillin-resistant Staphylococcus aureus driven by addictive mupA plasmids.

BACKGROUND: Resistance to mupirocin, a cornerstone of Staphylococcus aureus decolonization, is a recognized cause of decolonization failure. Its role in hospital transmission is unknown. METHODS: We conducted genomic surveillance of >10,000 S. aureus isolates from adult patients at two urban hospitals where mupirocin decolonization is routine. Bacterial phenotypes and fitness were evaluated in vitro and in murine colonization models to interpret surveillance results. RESULTS: Genome sequencing identified 475 hospital transmission events; conventional surveillance detected none. The plasmid-mediated resistance determinant mupA ( ileS2 ) was enriched eightfold in methicillin-resistant S. aureus (MRSA) relative to methicillin-susceptible strains. mupA was associated with nearly threefold greater hospital transmission, especially within healthcare-associated MRSA lineages. Surprisingly, multiple independently evolved inactivating mutations in the essential chromosomal gene ileS1 co-occurred with mupA , creating plasmid addiction in which mupA became indispensable for bacterial survival. Plasmid carriage activated the stringent response and reduced colonization fitness, but also conferred collateral tolerance to disinfectants such as ethanol and peroxide. Although addiction further reduced S. aureus fitness, it increased plasmid transfer, promoting spread despite these costs. Unexpectedly, we found a mupirocin-dependent vulnerability to isoleucine limitation, revealing a potential strategy to target mupA -mediated resistance. CONCLUSIONS: Hospital transmission of mupirocin-resistant MRSA is promoted by plasmids that create an evolutionary trap in which mupirocin use selects for bacterial dependence on costly resistance elements. These findings suggest that reducing mupirocin use alone is unlikely to eliminate resistance, underscore the need for genomic surveillance and resistance testing, and provide a framework for strategies to preserve mupirocin effectiveness. MAJOR POINT: This work shows that mupirocin resistance promotes hospital transmission of MRSA, identifies a previously unappreciated mechanism of plasmid addiction, and exposes a collateral vulnerability. These findings underscore the need for genomic surveillance and provide a framework to preserve mupirocin effectiveness.

Journal Article↗
PubMed2026

Spatiotemporal dynamics and phylogeography of HCoV-NL63 and HCoV-OC43 in Thailand, 2024-2025.

Endemic human coronaviruses (HCoVs) HCoV-NL63 and HCoV-OC43 are common causes of acute respiratory infections (ARI), yet integrated surveillance and genomic data from Southeast Asia remain limited. We characterized HCoV-NL63 and HCoV-OC43 circulation in Thailand, during 2024-2025 using routine real-time RT-PCR testing, partial spike sequencing, and time-scaled phylogenetic analyses with global references. Among 11,709 ARI specimens, 329/8,122 were HCoV-positive in 2024 (4.05%) and 131/3,587 in 2025 (3.65%). Positivity was strongly seasonal, peaking in winter, and SARS-CoV-2 surges in the same testing stream generally coincided with lower endemic HCoV positivity. Genotype composition differed by virus: HCoV-OC43 was dominated by genotypes K and J at near-equal frequencies (48.3% and 47.2%), whereas HCoV-NL63 was mainly genotype C4 (43.6%), followed by B2 (32.7%) and C3 (20.9%). Time-scaled phylogenies placed Thai sequences across multiple regions of global diversity, consistent with repeated introductions and onward transmission within several co-circulating lineages. Estimated substitution rates were 3.86&#x2009;&#xd7;&#x2009;10-4 substitutions/site/year for HCoV-NL63 and 9.27&#x2009;&#xd7;&#x2009;10-4 for HCoV-OC43. Discrete-trait phylogeography supported bidirectional connectivity involving Thailand, with virus-specific differences in the most supported routes. Skygrid reconstructions suggested declines in genetic diversity after 2020, overlapping the COVID-19 era, with a more pronounced decrease for HCoV-OC43. Evidence for selection was limited and inconsistent for HCoV-NL63, whereas several HCoV-OC43 sites overlapped codon-based signals of diversifying selection. Overall, these findings provide a baseline for endemic HCoV seasonality, genotype composition, and connectivity in Thailand, and support continued genomic surveillance in Southeast Asia.

Thailand↗
PubMed2024

Reflective Evaluation of Next-Generation Sequencing Data during Early Phase Detection of the Delta Variant.

During the SARS-CoV-2 pandemic, next-generation sequencing (NGS) technologies like the Ion Torrent S5 and Illumina MiSeq, alongside advanced software, improved genomic surveillance in South Africa. This study analysed anonymized samples from the Eastern Cape using Genome Detective and NextClade, showing Ion Torrent S5 and Illumina MiSeq success rates of 96% and 94%, respectively. The study focused on genomic coverage (above 80%) and mutation detection (below 100), with the Ion Torrent S5 achieving 99% coverage compared to Illumina MiSeq's 80%, likely due to different primers used in amplification. The Ion Torrent S5 was more effective in sequencing varied viral loads, whereas Illumina MiSeq had difficulties with lower loads. Both platforms were adept at identifying clades, successfully differentiating between Beta (<45%) and Delta variants (<30%), despite minor discrepancies in assignments due to Illumina MiSeq's lower coverage, leading to a failure rate of up to 6%. Manual library preparation showed similar sample processing and clade identification capabilities for both platforms. However, differences in sequencing duration (3.5 vs. 36 hours), automation level, genomic coverage (80% vs. 99%), and viral load compatibility were noted, highlighting each platform's unique advantages and challenges in SARS-CoV-2 genomic surveillance. In conclusion, the Illumina MiSeq and Ion Torrent S5 platforms are both efficacious in executing whole-genome sequencing (WGS) via amplicons, facilitating precise, accurate, and high-throughput examinations of SARS-CoV-2 viral genomes. However, it is important to note the existence of disparities in the quality of data produced by each platform. Each system offers unique benefits and limitations, rendering them viable choices for the genomic surveillance of SARS-CoV-2.

Illumina MiSeq↗
PubMed2026

Mapping Sub-National Respiratory Virus Circulation in Cambodia Using Metatranscriptomic Sequencing: A Multi-Center Hospital-Based Surveillance Study.

BACKGROUND: Genomic surveillance can guide early detection of and response to emerging epidemics. Metatranscriptomic sequencing was used to investigate sub-national respiratory virus circulation in Cambodia from 2020 to 2023. METHODS: Nasopharyngeal swabs were collected from individuals aged 2&#x2009;months to 65&#x2009;years with influenza-like illness in four Cambodian hospitals. Metatranscriptomic data were generated by short-read RNA sequencing. Bernoulli space-time scan statistics were used to identify temporal virus clusters. Bayesian inference of phylogenetic trees was used to compute divergence times for temporally clustered, highly represented viruses (influenza A/H3N2 and B, Betacoronavirus 1, respiratory syncytial virus [RSV] A and B), and publicly available global influenza virus genomes. RESULTS: Of 1093 individuals, 499 (45.7%) had detectable respiratory viruses belonging to 68 distinct species. Moderate (N&#x2009;>&#x2009;20) discrete time-clusters were noted of RSV-A (37 cases), Betacoronavirus 1 (21 cases), RSV-B (22 cases), and A/H3N2 (30 cases). The posterior median of time to most recent common ancestor ranged from 0.71&#x2009;years (95% HPD 0.38-1.10) for Betacoronavirus 1 and 1.31&#x2009;years (95% HPD 0.60-3.20) for A/H3N2, to 2.75&#x2009;years (1.82-4.26) for RSV-A and 4.79&#x2009;years (2.39-7.74) for RSV-B. A/H3N2 and influenza B virus genomes mapped to clades 3C.2a1b.2a.2a and Victoria 1A.3a.2, respectively, and inter-mixed with concurrent global strains. CONCLUSIONS: Multiple respiratory viruses circulated at a sub-national level in Cambodia from 2020 to 2023 despite pandemic disruptions. Influenza virus population diversity decreased during the height of lockdown but recovered in mid-2022. Re-emerging influenza strains were distinct from historically circulating strains and clustered with contemporaneous global variants, suggesting multiple external introductions.

Humans↗
PubMed2026

A reusable model of pangenome selection informs optimal surveillance strategies over vaccine introductions.

BACKGROUND: The human pathogen Streptococcus&#xa0;pneumoniae is a major cause of disease, including pneumonia and meningitis. The introduction of Pneumococcal Conjugate Vaccines (PCVs) initially reduced the burden of disease through a reduction of colonisation by vaccine-targeted serotypes. However, since PCVs only target a proportion of pneumococcal serotypes, they shift intraspecific competition, eventually allowing non-targeted types to 'replace' vaccine types. Understanding the host and pathogen factors causing replacement is important for future vaccine development. Mechanistic understanding of vaccine replacement dynamics is crucial for forecasting and optimisation of genomic surveillance strategies to evaluate realised vaccine effectiveness. METHODS: We developed a mathematical model of the genomic and demographic factors which explain vaccine replacement, used this model to replicate serotype-frequency changes, and investigated cost-effective genomic surveillance strategies. We extended a forward-time model based on the Wright-Fisher model, developing a user-friendly model framework that describes the post-vaccine dynamics of S.&#xa0;pneumoniae populations. Our model describes vaccine replacement as a function of vaccine impact, immigration of new strains, and negative frequency-dependent selection (NFDS) on the accessory genome content. RESULTS: We used our model to study vaccine replacement in newly sequenced genomic surveillance data from Kathmandu (Nepal), and existing data from Massachusetts (US) and Southampton (UK), with distinct surveillance strategies. We showed that the model with NFDS better replicates replacement dynamics than a null model without NFDS, and that NFDS likely only acts on part of the S.&#xa0;pneumoniae accessory genome. We found consistent estimates for vaccination effectiveness across the different study locations and region-specific genes under NFDS, highlighting the importance of conducting genomic surveillance in each country of interest. By simulating data from the model, we showed that an optimal surveillance strategy prioritises per-sampling sample size over sampling frequency for small sampling budgets. CONCLUSIONS: Our model can be used to predict vaccine replacement dynamics after PCV introduction, and can be easily reapplied to analyse new data from vaccine introductions or new regions. Our model is available in the R package Stubentiger (Studying Balancing Evolution (NFDS) To Investigate Genome Replacement) on GitHub https://github.com/bacpop/Stubentiger .

Streptococcus pneumoniae↗