David Jorgensen

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.

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.

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.

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.

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 post-2020, with the die-out of one of two major genetic clusters and recent detections are now close genetic relatives. We find that high-risk and hard-to-access regions have been key to persistent polio transmission over the past decade, supporting transmission when it had stopped elsewhere. Karachi, one of the most densely populated cities globally, has acted as a major 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. This information has been used to guide polio vaccination and surveillance.

Background: Lassa fever, caused by Lassa virus (LASV), poses a significant public health threat in West Africa. Understanding the epidemiological parameters and transmission dynamics of LASV is crucial for informing evidence-based interventions and outbreak response strategies. Methods: We conducted a systematic review (PROSPERO CRD42023393345) to compile and analyse key epidemiological parameters, mathematical models, and past outbreaks of LASV. Data were double extracted from published literature, focusing on past outbreaks, seroprevalence, transmissibility, epidemiological delays, and disease severity. Findings: We found 157 publications meeting our inclusion criteria and extracted 374 relevant parameter estimates. Although LASV is endemic in West Africa, spatiotemporal coverage of recent seroprevalence estimates, ranging from 0.06% to 35%, was poor. Highlighting the uncertainty in LASV risk spatially. Similarly, only two basic reproduction number estimates at 1.13 and 1.19 were available. We estimated a pooled total random effect case fatality ratio of 33.1% (95% CI: 25.7 – 41.5, I ² = 94%) and found potential variation in severity by geographic regions typically associated with specific LASV lineages. We estimated a pooled total random effect mean symptom-onset-to-hospital-admission delay of 8.3 days (95% CI: 7.4 – 9.3, I2 = 92%), but other epidemiological delays were poorly characterised. Interpretation: Our findings highlight the relative lack of empirical LASV parameter estimates despite its high severity. Improved surveillance to capture mild cases and approaches that integrate rodent populations are needed to better understand LASV transmission dynamics. Addressing these gaps is essential for developing accurate mathematical models and informing evidence-based interventions to mitigate the impact of Lassa fever on public health in endemic regions. Funding: UK Medical Research Council, National Institute for Health and Care Research, Academy of Medical Sciences, Wellcome, UK Department for Business, Energy, and Industrial Strategy, British Heart Foundation, Diabetes UK, Schmidt Foundation, Community Jameel, Royal Society, and Imperial College London. Research in Context: Evidence before this study: We searched PubMed up to August 2, 2023 for ((lassa fever) or (lassa virus)) and (epidemiology or outbreak or (models not image) or transmissibility or severity or delays or (risk factors) or (mutation rate) or seroprevalence). We found ten systematic reviews. Three on ribavirin as a Lassa fever treatment, two on Lassa virus (LASV) vaccine candidates, and one each on historical importations of Lassa fever cases from West Africa to non-endemic countries, clinical characteristics for protocol development, and Lassa fever in pregnancy. Two systematically reviewed epidemiological parameters. One on basic reproduction number estimates which ranged from 1.1 to 1.8 for human-to-human and 1.5 to 1.7 for rodent-to-rodent transmission. However, no meta-analyses were conducted. The other focused on LASV infection case fatality ratios (CFRs): 29.7% (22.3–37.5) in humans and prevalence: 8.7% (95% confidence interval: 6.8– 10.8) in humans, 3.2% (1.9–4.6) in rodents, and 0.7% (0.0–2.3) in other mammals. There were no systematic reviews on LASV transmission models. Added value of this study: We provide a comprehensive overview of published outbreaks, transmission models and epidemiological parameters for LASV. We highlight the sparsity of key epidemiological parameter estimates such as the serial interval or generation time. The discrepancy between the high overall severity and the high seroprevalence in the general population suggests a high proportion of infections are asymptomatic or only result in mild disease. Therefore, current surveillance systems may need refining to better characterise LASV transmission dynamics. Implications of all the available evidence: Epidemiological models are useful tools for real-time analysis of outbreaks, assessing epidemic trajectories and the impact of interventions. Our study is a useful basis to inform future LASV models, but highlights uncertainties and knowledge gaps that need to be filled in LASV transmission and natural history. Future LASV studies will benefit from integrating human and rodent reservoir surveillance.

Discrete trait analysis (DTA) methods are widely used to infer patterns of movement between discrete geographic locations from genetic sequence data as they are simple and fast to implement. With the increasing interest in phylogeography for pathogen genomic epidemiology, accounting for and understanding the limitations of the methods used is becoming increasingly important. Applying DTA to location makes several strong simplifying assumptions, including the assumption of equal sampling probability across locations. This may lead to biased estimates of migration rates and ancestral locations where sampling rates vary. Here we investigate these biases using simulated migration and transmission data. We propose a simple correction to DTA for unequal sampling probability across locations when sampling rates are known or can be estimated. This correction to the migration rate matrix can be applied only to phylogenetic branches leading to sampled tips or to the whole phylogeny. We assess the performance of this correction using simulated data for a range of endemic transmission scenarios with varied sampling and migration rates. In a simple, two-location, case the correction performs significantly better than a standard DTA method in three of the four sampling rate distributions investigated. Applying the correction across only the tips of the phylogeny and over the full depth of the tree gives similar results, with the correction only at the tips performing marginally better in this simple two-location simulation. As migration is a key driver of infectious disease spread, improving estimates of migration with simple phylogenetic methods is a valuable development in infectious disease phylogeography.

Background Unprecedented public health interventions including travel restrictions and national lockdowns have been implemented to stem the COVID-19 epidemic, but the effectiveness of non-pharmaceutical interventions is still debated. International comparisons are hampered by highly variable conditions under which epidemics spread and differences in the timing and scale of interventions. Cumulative COVID-19 morbidity and mortality are functions of both the rate of epidemic growth and the duration of uninhibited growth before interventions were implemented. Incomplete and sporadic testing during the early COVID-19 epidemic makes it difficult to identify how long SARS-CoV-2 was circulating in different places. SARS-CoV-2 genetic sequences can be analyzed to provide an estimate of both the time of epidemic origin and the rate of early epidemic growth in different settings. Methods We carried out a phylogenetic analysis of more than 29,000 publicly available whole genome SARS-CoV-2 sequences from 57 locations to estimate the time that the epidemic originated in different places. These estimates were cross-referenced with dates of the most stringent interventions in each location as well as the number of cumulative COVID-19 deaths following maximum intervention. Phylodynamic methods were used to estimate the rate of early epidemic growth and proxy estimates of epidemic size. Findings The time elapsed between epidemic origin and maximum intervention is strongly associated with different measures of epidemic severity and explains 46% of variance in numbers infected at time of maximum intervention. The reproduction number is independently associated with epidemic severity. In multivariable regression models, epidemic severity was not associated with census population size. The time elapsed between detection of initial COVID-19 cases to interventions was not associated with epidemic severity, indicating that many locations experienced long periods of cryptic transmission. Interpretation Locations where strong non-pharmaceutical interventions were implemented earlier experienced much less severe COVID-19 morbidity and mortality during the period of study. Funding MRC is jointly funded by the UK Medical Research Council (MRC) and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement and this award is part of the EDCTP2 programme supported by the European Union (MR/R015600/1). RJ and EV acknowledge funding from the European Commission (CoroNAb 101003653). EV additionally acknowledges funding from the Wellcome Trust (220885/Z/20/Z).

Summary: Global dispersal and increasing frequency of the SARS-CoV-2 Spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of Spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large data set, well represented by both Spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the Spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant.