Nicholas C. Grassly

Enterovirus D68 (EV-D68) is a common cause of mild respiratory illness in children but is also linked to acute flaccid myelitis (AFM), a rare and severe neurological condition which can result in permanent paralysis. Tracking EV-D68 transmission is difficult because symptoms overlap with other common childhood illnesses, making case reporting unreliable. As a result, the burden of EV-D68 transmission remains poorly understood, particularly prior to the first widely recognised outbreak in 2014. Phylodynamic approaches offer a powerful alternative to case-based surveillance, inferring epidemiological parameters directly from pathogen genetic sequences. Here we show, using a birth-death-sampling phylodynamic model applied to publicly available EV-D68 sequences from the 1990s to 2023 collected in Europe and North America, that seasonal EV-D68 transmission was well established long before the 2014 outbreak brought the virus to widespread attention. Furthermore, we show that AFM case burden is strongly associated with the transmission dynamics of a specific EV-D68 clade, clade B, an association not seen for clades A and D. These findings suggest that clade-specific biological differences drive AFM risk, with important implications for surveillance prioritisation and the timing of future burden of neurological disease.

The control of infectious diseases depends on effective diagnostics and interventions. In Africa, resource limitations hinder clinical surveillance. Environmental surveillance (ES), particularly wastewater surveillance, offers a cost-effective alternative. While globally expanding, its application in Africa remains limited. This review aimed to describe published studies in Africa that have utilized ES for the detection of infectious pathogens of public health importance in Africa. The study employed a rapid review approach to synthesize evidence on ES of infectious pathogens in Africa, following guidance from the Cochrane Rapid Reviews Methods. Articles from major databases, including Scopus, PubMed, Science Direct, and Cochrane, were screened using Catchii.org. Duplicates were removed, and data were extracted into Excel, and study quality was appraised using the AXIS tool and a modified Newcastle-Ottawa Scale. The search strategy identified 2,189 articles, of which 90 were found to be eligible. We identified 47 microbial species that have been reported across studies. These consisted of 46.8% bacteria ( n = 22), 36.2% viruses ( n = 17), 4.3% fungi ( n = 2), and 12.7% parasites ( n = 6). Among viruses identified, SARS-CoV-2 was the most common, followed by rotaviruses and polioviruses. Vibrio cholerae was mostly reported among bacterial pathogens. The most common sampling method was grab sampling ( n = 85, 94.4%), while two-phase separation ( n = 22, 37.3%) and filtration ( n = 11, 39.3%) were the most frequently used concentration methods for viral and bacterial detection, respectively. ES of infectious pathogens in Africa remains limited. There is a need to expand this to enhance pathogen monitoring, transmission insights, and preparedness for emerging variants.

Vaccine-derived poliovirus serotype 2 (VDPV2) outbreaks are a major challenge to polio eradication, seeded by rare reversions of oral polio vaccine to a neurovirulent strain. The Democratic Republic of the Congo has experienced more VDPV2 outbreaks than any other country; however, little is known about the subnational dynamics of VDPV2 spread, and understanding of the quality of VDPV2 surveillance and outbreak response in the country is incomplete. We used phylodynamic and phylogeographic methods to analyse 116 VP1 sequences from cases of poliomyelitis associated with RDC-MAN-3, the largest VDPV2 outbreak to date in the DRC with cases reported between October 2021 and August 2023, alongside programmatic data from the RDC-MAN-3 outbreak. We identified a pair of vaccination campaigns in Tshopo in October 2020 as the most plausible seeding event, making the delay between seeding and first discovery by environmental sampling approximately 12 months. Phylogeographic reconstruction showed predominantly local spread, with a median of 74% (20/27) of inferred cross-province movements occurring between neighbouring provinces. and identified pairs of provinces with the most important contributions to spatial dispersal of the outbreak; in particular, transmission from Tanganyika to Haut Lomami was highly frequent (9/27 cross-province movements). We inferred from the effective population size trajectory that surveillance was likely less intensive in the first wave of the outbreak, and that in some provinces RDC-MAN-3 was introduced at least two months before detection, while in Équateur province RDC-MAN-3 was never detected by culture testing. Finally, our analysis found that outbreak response vaccination campaigns were conducted 2-13 months (modal average across provinces of 5 months) after the estimated importation of poliovirus into each province. These results show how campaign scope and timing were insufficient to stop the outbreak early and highlight how routine genomic data can retrospectively assess the adequacy of surveillance and response implementation.

Methods to concentrate wastewater samples are essential for sensitive environmental surveillance of infectious diseases. We defined six main principles used to concentrate viral pathogens in wastewater and performed a systematic review and meta-analysis of their performance. PubMed and Web of Science were searched on 31 January 2025 using terms wastewater, sewage, concentration methods and wastewater surveillance. We included all studies comparing ≥2 concentration methods for virus detection. Our search identified 49 eligible studies published since 2013 across seven continents. We ranked the performance of evaluated methods in each study and generated an overall performance metric for each method principle by virus group (enveloped vs. non-enveloped) using Plackett-Luce analysis. Precipitation and filtration methods were the most studied, while magnetic bead-based and centrifugation were least studied. Magnetic bead-based methods were more effective for concentrating enveloped viruses (63% of pairwise comparisons), whereas flocculation performed better for non-enveloped viruses (60%). However, no single method strongly dominated and method rankings were variable between studies. This study provides evidence-based guidance for selecting wastewater concentration methods to support environmental surveillance of viral pathogens.

Outbreaks of vaccine-derived poliovirus type 2 (cVDPV2) have become a major threat to polio eradication. However, variations in spatiotemporal spread have not been quantified. Here we analysed cVDPV2 cases and wild poliovirus type 1 sequences to uncover spatiotemporal patterns and drivers of poliovirus spread. Between 1 May 2016 and 29 September 2023, 3,120 cVDPV2 poliomyelitis cases were reported across 75 outbreaks in 39 countries. Outbreaks had a median observed circulation of 202 (range 0–1,905) days and a median maximum distance of 231 (range 0–4,442) km. Wavefront velocity analysis of large outbreaks revealed a median velocity of spread of 2.3 (5th–95th percentile 0.7–9.2) km per day. International borders were associated with a slower velocity of spread ( P < 0.001), in periods with high estimated population immunity. Phylogeographic analysis of 1,572 global wild poliovirus 1 sequences revealed that historic spread resembles recent cVDPV2 patterns and that international spread is largely sustained by unidirectional movement between neighbouring countries. Our findings offer insights for enhancing the geographical scope of vaccination response in the final phases of poliovirus eradication.

Vaccines can provide protection against infection or limit disease severity. Vaccine efficacy (VE) is typically evaluated independently for different outcomes, but this does not provide insight into the mechanism of the protective effect and can cause biased estimates of VE. We propose a new conceptual framework and statistical implementation for VE estimation for infections with multiple possible outcomes of infection: joint analysis of multiple outcomes in vaccine efficacy trials (JAMOVET). JAMOVET is a Bayesian hierarchical regression model that controls for biases and can evaluate covariates for VE, the hazard of infection, and the probability of progression. We applied JAMOVET to simulated data, and data from COV002 (NCT04400838), a phase 2/3 trial of ChAdOx1 nCoV-19 (AZD1222) vaccine. Simulations showed that biases are corrected by explicitly modeling disease progression and imperfect test characteristics. JAMOVET estimated ChAdOx1 nCoV-19 VE against infection (${\mathrm{VE}}_{in}$) at 55% (95% credible interval [CrI] 35-70) and progression to symptoms (${\mathrm{VE}}_{pr}$) at 44% (95% CrI 26-59). This implies a VE against symptomatic infection of 75% (95% CrI 62-85), consistent with published trial estimates. JAMOVET is a powerful tool for evaluating diseases with multiple dependent outcomes and can be used to adjust for biases and identify predictors of key outcomes.

Amplicon sequencing is a popular method for understanding the diversity of bacterial communities in samples containing multiple organisms as exemplified by 16S rRNA sequencing. Another application of amplicon sequencing includes multiplexing both primer sets and samples, allowing sequencing of multiple targets in multiple samples in the same sequencing run. Multiple tools exist to process the amplicon sequencing data produced via the short-read Illumina platform, but there are fewer options for long-read Oxford Nanopore Technologies (ONT) sequencing, or for processing data from environmental surveillance or other sources with many different organisms. We have developed AmpliconTyper (v0.1.28, DOI: 10.5281/zenodo.15045111) for analysing multiplex amplicon sequencing data from environmental (e.g. wastewater) or similarly complex samples, generated using ONT devices. The tool uses machine learning to classify sequencing reads into target and non-target organisms with very high specificity and sensitivity. The user can train models using public and/or user-generated data, which can subsequently be applied to analyse new data. The tool can also generate amplicon consensus sequences, as well as identify SNPs and report their genotype implications, such as association with lineages or antimicrobial resistance (AMR). The tool is freely available via Bioconda and GitHub (https://github.com/AntonS-bio/AmpliconTyper). AmpliconTyper allows robust identification of target organism reads in ONT-sequenced environmental samples and can identify user-specified lineage or AMR markers.

Despite concerted global vaccination efforts, wild poliovirus remains endemic in two countries in 2024, Pakistan and Afghanistan. This study uses phylogeographic analysis of poliovirus genetic and epidemiological data from clinical and wastewater surveillance to identify the causes of poliovirus persistence and routes of spread over the last decade (2012 to 2023). Poliovirus genetic diversity declined after 2020, with one of two major genetic clusters dying out, and recent detections are now closely related genetically. High-risk and hard-to-access regions have sustained polio transmission over the past decade, even when interrupted elsewhere. Karachi, one of the most densely populated cities globally, has acted as a hub for the amplification and spread of poliovirus to other regions, many of which we show to be dead-end for onwards transmission despite frequent virus detection. Phylogenetic analysis has long been central to the polio surveillance network, and advancing the approaches used can provide critical epidemiological insights to accelerate eradication efforts.

Background: Between 2016 and 2023, 3248 cases of circulating vaccine-derived type 2 poliomyelitis (cVDPV2) were reported globally and supplementary immunization activities (SIAs) with monovalent type 2 oral poliovirus vaccine (mOPV2) and novel type 2 oral poliovirus vaccine (nOPV2) targeted an estimated 356 and 525 million children, respectively. This analysis estimates the community-level impact of nOPV2 relative to mOPV2 SIAs. Methods: We fitted interrupted time-series regressions to surveillance data between January 2016 and November 2023 to estimate the impact of nOPV2 and mOPV2 SIAs on cVDPV2 poliomyelitis incidence and prevalence in environmental surveillance across 37 countries, directly comparing the impact of SIAs in 13 countries where both vaccines were used. Results: We did not find any statistically significant differences between nOPV2 and mOPV2 SIA impact except for in the Democratic Republic of Congo (DRC), where nOPV2 SIAs had lower impact (adjusted relative risk [aRR] for cVDPV2 poliomyelitis incidence per nOPV2 SIA, 0.505; 95% confidence interval [CI], .409–.623) compared to mOPV2 (aRR, 0.193; 95% CI, .137–.272); P value for difference in RRs = 3e-6. Conclusions: We find variation in OPV2 SIA impacts globally, with greater certainty about Nigeria and DRC, where large outbreaks provided an opportunity to assess impact at scale. In most countries, we find no significant difference between nOPV2 and mOPV2 SIA impact. We are unable to identify the reason for the significant difference in DRC, which could include differential SIA coverage, timing, vaccine effectiveness, or outbreak dynamics.