Predicting optimal impact interventions in the post‐ <scp>HPV</scp> vaccination world

International Journal of Cancer · 2026-01-19

Prophylactic vaccination is a powerful tool that changes exposure to infections and associated morbidity of preventable diseases. We discuss the impact of pneumococci and human papillomavirus (HPV) vaccination on the population biology of the two micro-organisms and related public health effects. Data on HPV type-replacement in communities where vaccine-covered HPVs are almost eliminated, and interactions of the remaining HPV types on the risk of cervical cancer are reviewed. Results of comprehensive models for European country-specific conduction of cervical screening among HPV-vaccinated and unvaccinated women, assuming different HPV-vaccination coverage and strategies, are discussed in our policy-oriented review. An acceptable balance of benefits and harms of cervical cancer screening in HPV vaccinated populations requires an understanding of cancer risks in differently vaccinated birth cohorts. Finally, the challenges are complex but can be met if strategies are applied that (i) as fast as possible achieve herd effect and (ii) use a risk-based design of HPV screening.

Linkage-based ortholog refinement in bacterial pangenomes with CLARC

Nucleic Acids Research · 2025-06-18 · 1 citations

Bacterial genomes exhibit significant variation in gene content and sequence identity. Pangenome analyses explore this diversity by classifying genes into core and accessory clusters of orthologous groups (COGs). However, strict sequence identity cutoffs can misclassify divergent alleles as different genes, inflating accessory gene counts. CLARC (Connected Linkage and Alignment Redefinition of COGs) (https://github.com/IndraGonz/CLARC) improves pangenome analyses by condensing accessory COGs using functional annotation and linkage information. Through this approach, orthologous groups are consolidated into more practical units of selection. Analyzing 8000+ Streptococcus pneumoniae genomes, CLARC reduced accessory gene estimates by >30% and improved evolutionary predictions based on accessory gene frequencies. CLARC is effective across different bacterial species, making it a broadly applicable tool for comparative genomics. By refining COG definitions, CLARC offers critical insights into bacterial evolution, aiding genetic studies across diverse populations.

Antimicrobial selection for resistance in four major pathogens in the US Veterans Affairs Healthcare System, 2007-2021

medRxiv · 2025-03-13 · 2 citations

Abstract Background Systematic evidence on antimicrobial selection for antimicrobial resistance (AMR) is scarce. We estimated the effect of prescribing key antibiotic classes on AMR across U.S. Veterans Affairs Medical Centres (VAMC). Methods We analysed clinical isolates of Staphylococcus aureus, Escherichia coli, Klebsiella pneumoniae , and Pseudomonas aeruginosa from 138 VAMC from Feb 1, 2007 to Dec 31, 2021. Antimicrobial prescribing was measured as inpatient days of therapy per 1000 patient-days; multidrug resistance as number of resistant phenotypes per 1,000 admissions. Temporal trends were modelled using generalized estimating equations and average annual percentage changes (AAPC). Multilevel multinomial logistic regression related facility-level antibiotic prescribing (days of therapy per 100 patient-days in the last 14d) to the relative odds of resistant phenotypes. Findings Hospital-onset infection incidence declined for all pathogens, except third-generation cephalosporin (3GC)-resistant E coli . Antimicrobial prescribing remained stable or decreased, except 3GC prescribing, which increased from 2007 until 2019 (AAPC=2·4%, 95% CI 1·3%–3·5%, p-value&lt;0.0001). Fluoroquinolone (FQL) use was associated with resistance across all pathogens. In S aureus , each day of FQL treatment was linked to a 4·6% (95CI: 1·5, 7·7, p-value=0.0127) increase in the relative odds of isolating FQL-resistant, macrolide-susceptible, methicillin-resistant S aureus . Anti-staphylococcal beta-lactams were not linked to MRSA. Each day of 3GC treatment increased the odds of isolating 3GC- and beta-lactam/beta-lactamase-resistant E coli by 5·2% (95%CI: 1·3%, 9·4%, p-value=0.0079) and K pneumoniae by 3·0% (95% CI: −0·1%-6·2%, p-value=0.0600). Each day of carbapenem treatment increased the odds of carbapenem-resistant, FQL- and BL/BLI-susceptible P aeruginosa by 15·7% (95%CI: 9·4%, 22·4%, p-value&lt;0.0001). Interpretation Higher facility-level antimicrobial use increased the odds of corresponding resistant phenotypes, with important exceptions. FQLs selected for resistance across multiple pathogens. Increased 3GC prescribing likely offset reductions in FQLs and was associated with co-resistance in E coli . These findings underscore the need for comprehensive stewardship that coordinates strategies across antimicrobials.

Kinetics of <scp>SARS</scp> ‐ <scp>CoV</scp> ‐2 Shedding in Nursing Home Residents and Staff

Journal of the American Geriatrics Society · 2025-05-02 · 3 citations

BACKGROUND: Nursing homes (NHs) were disproportionately affected by the COVID-19 pandemic. However, little is known regarding the kinetics of SARS-CoV-2 shedding in NH residents and staff, which could inform treatment and infection prevention. METHODS: We enrolled NH residents and staff in eight US states from April to November 2023 and analyzed the kinetics of SARS-CoV-2 using serial antigen and molecular (RT-PCR) tests, whole genome sequencing, and viral culture (VC). Symptoms, vaccination, and treatment were collected via interviews and chart review. Viral load trajectories were modeled with gamma distribution functional forms. Antigen and VC test positivity over time were assessed using a Chi-squared test. RESULTS: Of the 587 enrolled participants, 86 tested positive and 73 underwent testing for ≥ 10 days; most residents (78%) and staff (87%) had ≥ 3 COVID-19 vaccine doses. The modeled SARS-CoV-2 proliferation period (period prior to reaching peak viral load) had ended for 48% (14/29) of residents and 56% (9/16) of staff when they took the initial RT-PCR test. Both antigen and VC showed higher positivity rates early in the course of disease (Days 0-5 vs. Days ≥ 6) (antigen: p < 0·001, VC: p < 0·001). VC positivity was 15% after Day 5 (14/96); two participants were VC positive after Day 10. CONCLUSIONS: Peak viral load occurs early in the disease, suggesting asymptomatic and presymptomatic transmission may be a significant driver of transmission. Only two participants had a positive VC after Day 10, supporting current isolation and return to work recommendations.

Causal Estimands for Analyses of Averted and Avertible Outcomes due to Infectious Disease Interventions

Epidemiology · 2025-01-24 · 2 citations

During the coronavirus disease (COVID-19) pandemic, researchers attempted to estimate the number of averted and avertible outcomes due to vaccination campaigns to quantify public health impact. However, the estimands used in these analyses have not been previously formalized. It is also unclear how these analyses relate to the broader framework of direct, indirect, total, and overall causal effects under interference. Here, using potential outcome notation, we adjust the direct and overall effects to accommodate analyses of averted and avertible outcomes. We use this framework to interrogate the commonly held assumption that vaccine-averted outcomes via direct impact among vaccinated individuals (or vaccine-avertible outcomes via direct impact among unvaccinated individuals) is a lower bound on vaccine-averted (or -avertible) outcomes overall. To do so, we describe a susceptible-infected-recovered-death model stratified by vaccination status. When vaccine efficacies wane, the lower bound fails for vaccine-avertible outcomes. When transmission or fatality parameters increase over time, the lower bound fails for both vaccine-averted and -avertible outcomes. Only in the simplest scenario where vaccine efficacies, transmission, and fatality parameters are constant over time, outcomes averted via direct impact among vaccinated individuals (or outcomes avertible via direct impact among unvaccinated individuals) is a lower bound on overall impact. In conclusion, the lower bound can fail under common violations to assumptions on time-invariant vaccine efficacy, pathogen properties, or behavioral parameters. In real data analyses, estimating what seems like a lower bound on overall impact through estimating direct impact may be inadvisable without examining the directions of indirect effects.

Focusing a viral risk ranking tool on prediction

Proceedings of the National Academy of Sciences · 2025-04-17 · 2 citations

Preparing to rapidly respond to emerging infectious diseases is critical. SpillOver: Viral Risk Ranking is an open-source tool developed to assess the risk of novel wildlife-origin viruses spilling over from animals to humans and spreading in human populations. Several risk factors used by the tool depend on evidence of previous zoonotic spillover itself or sustained transmission in humans. Therefore, we reanalyzed the Ranking Comparison after removing eight of the 31 risk factors that require postspillover knowledge and compared the adjusted risk rankings to the originals. The area under the receiver operating characteristic curve deteriorated from 0.94 for the original risk scores to 0.73 for the adjusted ones for predicting the classification as a human virus. We also compared the mean and SD of the risk scores for the human and non-human viruses at the risk factor level. Most excluded spillover-dependent risk factors had dissimilar means between the human and non-human virus classifications, but nonspillover-dependent risk factors frequently showed similar means between the two classifications. The original formulation of the tool depended on the inclusion of spillover-dependent risk factors to quantitatively assess the risk of zoonotic spillover for a novel virus. Future iterations of the tool should omit such risk factors and consider other nonspillover-dependent risk factors to ensure that the tool is fit for risk prediction of novel viruses.

A Binary Prototype for Time-Series Surveillance and Intervention

medRxiv · 2025-02-05

Abstract Despite much research on early detection of anomalies from surveillance data, a systematic framework for appropriately acting on these signals is lacking. We addressed this gap by formulating a hidden Markov-style model for time-series surveillance, where the system state, the observed data, and the decision rule are all binary. We incur a delayed cost, c , whenever the system is abnormal and no action is taken, or an immediate cost, k , with action, where k &lt; c . If action costs are too high, then surveillance is detrimental, and intervention should never occur. If action costs are sufficiently low, then surveillance is detrimental, and intervention should always occur. Only when action costs are intermediate and surveillance costs are sufficiently low is surveillance beneficial. Our equations provide a framework for assessing which approach may apply under a range of scenarios and, if surveillance is warranted, facilitate methodical classification of intervention strategies. Our model thus offers a conceptual basis for designing real-world public health surveillance systems.

Predicting antibody kinetics and duration of protection against SARS-CoV-2 following vaccination from sparse serological data

PLoS Computational Biology · 2025-06-18 · 4 citations

Vaccination against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) generates an antibody response that shows large inter-individual variability. This variability complicates the use of antibody levels as a correlate of protection and the evaluation of population- and individual-level infection risk without access to broad serological testing. Here, we applied a mathematical model of antibody kinetics to capture individual anti-SARS-CoV-2 IgG antibody trajectories and to identify factors driving the humoral immune response. Subsequently, we evaluated model predictions and inferred the corresponding duration of protection for new individuals based on a single antibody measurement, assuming sparse access to serological testing. We observe a reduced antibody response in older and in male individuals, and in individuals with autoimmune diseases, diabetes and immunosuppression, using data from a longitudinal cohort study conducted in healthcare workers at Sheba Medical Center, Israel, following primary vaccination with the BNT162b2 COVID-19 vaccine. Our results further suggest that model predictions of an individual's antibody response to vaccination can be used to predict the duration of protection when serological data is limited, highlighting the potential of our approach to estimate infection risk over time on both the population and individual level to support public health decision-making in future pandemics.

How Should We Study the Indirect Effects of Antimicrobial Treatment Strategies?: A Causal Perspective

Epidemiology · 2025-11-02

Effective antimicrobial stewardship requires unbiased assessment of the benefits and harms of different treatment strategies, considering both immediate patient outcomes and patterns of antimicrobial resistance. In principle, these benefits and harms can be expressed as causal contrasts between treatment strategies and, therefore, should be ideally suited for study under the potential outcomes framework. However, causal inference in this setting is complicated by interference between individuals (or units) due to the indirect effects of antibiotic treatment, including the spread of resistant bacteria to others. These indirect effects complicate the assessment of trade-offs as benefits are mostly due to the direct effects among those treated, while harms are more diffuse and, therefore, harder to measure. While causal frameworks and study designs that accommodate interference have previously been proposed, they have been applied predominantly to the study of vaccines, which differ from antimicrobial interventions in fundamental ways. In this article, we review these existing approaches and propose alternative adaptations tailored to the study of antimicrobial treatment strategies.

Clade I mpox vaccination: strategies for deployment and evaluation

EBioMedicine · 2025-08-20

Clade I mpox continues to spread in Central Africa with no sign of abating,1 however very few doses of vaccine have been deployed. Mpox vaccination strategies using either of the licenced vaccines, MVA-BN and LC16m8, are being drawn up across 17 African countries and vaccination has begun in the Democratic Republic of Congo (DRC), Rwanda and Nigeria.2 Clinical studies during the rollout could deliver much-needed data about the effectiveness of the vaccine against clade I mpox. Choosing the right study design is fundamental.