Imperial College London

DrErikVolz

Faculty of MedicineSchool of Public Health

Reader in Population Biology of Infectious Diseases
 
 
 
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+44 (0)20 7594 1933e.volz Website

 
 
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Location

 

UG10Norfolk PlaceSt Mary's Campus

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Summary

 

Publications

Publication Type
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142 results found

Drake K, Boyd O, Franceschi V, Volz E, Colquhoun R, Ellaby Net al., 2024, Phylogenomic early warning signals for SARS-CoV-2 epidemic waves, EBioMedicine, Vol: 100, ISSN: 2352-3964

Background:Epidemic waves of coronavirus disease 2019 (COVID-19) infections have often been associated with the emergence of novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. Rapid detection of growing genomic variants can therefore serve as a predictor of future waves, enabling timely implementation of countermeasures such as non-pharmaceutical interventions (social distancing), additional vaccination (booster campaigns), or healthcare capacity adjustments. The large amount of SARS-CoV-2 genomic sequence data produced during the pandemic has provided a unique opportunity to explore the utility of these data for generating early warning signals (EWS).Methods:We developed an analytical pipeline (Transmission Fitness Polymorphism Scanner – designated in an R package mrc-ide/tfpscanner) for systematically exploring all clades within a SARS-CoV-2 virus phylogeny to detect variants showing unusually high growth rates. We investigated the use of these cluster growth rates as the basis for a variety of statistical time series to use as leading indicators for the epidemic waves in the UK during the pandemic between August 2020 and March 2022. We also compared the performance of these phylogeny-derived leading indicators with a range of non-phylogeny-derived leading indicators. Our experiments simulated data generation and real-time analysis.Findings:Using phylogenomic analysis, we identified leading indicators that would have generated EWS ahead of significant increases in COVID-19 hospitalisations in the UK between August 2020 and March 2022. Our results also show that EWS lead time is sensitive to the threshold set for the number of false positive (FP) EWS. It is often possible to generate longer EWS lead times if more FP EWS are tolerated. On the basis of maximising lead time and minimising the number of FP EWS, the best performing leading indicators that we identified, amongst a set of 1.4 million, were the maximum logistic growth rate (

Journal article

Nascimento FF, Mehta SR, Little SJ, Volz EMet al., 2023, Assessing transmission attribution risk from simulated sequencing data in HIV molecular epidemiology, AIDS, ISSN: 0269-9370

BACKGROUND: HIV molecular epidemiology (ME) is the analysis of sequence data together with individual-level clinical, demographic, and behavioral data to understand HIV epidemiology. The use of ME has raised concerns regarding identification of the putative source in direct transmission events. This could result in harm ranging from stigma to criminal prosecution in some jurisdictions. Here we assessed the risks of ME using simulated HIV genetic sequencing data. METHODS: We simulated social networks of men-who-have-sex-with-men, calibrating the simulations to data from San Diego. We used these networks to simulate consensus and next-generation sequence (NGS) data to evaluate the risks of identifying direct transmissions using different HIV sequence lengths, and population sampling depths. To identify the source of transmissions, we calculated infector probability and used phyloscanner software for the analysis of consensus and NGS data, respectively. RESULTS: Consensus sequence analyses showed that the risk of correctly inferring the source (direct transmission) within identified transmission pairs was very small and independent of sampling depth. Alternatively, NGS analyses showed that identification of the source of a transmission was very accurate, but only for 6.5% of inferred pairs. False positive transmissions were also observed, where one or more unobserved intermediaries were present when compared to the true network. CONCLUSION: Source attribution using consensus sequences rarely infers direct transmission pairs with high confidence but is still useful for population studies. In contrast, source attribution using NGS data was much more accurate in identifying direct transmission pairs, but for only a small percentage of transmission pairs analyzed.

Journal article

Perez-Guzman PN, Knock E, Imai N, Rawson T, Elmaci Y, Alcada J, Whittles LK, Thekke Kanapram D, Sonabend R, Gaythorpe KAM, Hinsley W, FitzJohn RG, Volz E, Verity R, Ferguson NM, Cori A, Baguelin Met al., 2023, Author Correction: Epidemiological drivers of transmissibility and severity of SARS-CoV-2 in England., Nat Commun, Vol: 14

Journal article

Volz E, 2023, Fitness, growth and transmissibility of SARS-CoV-2 genetic variants, NATURE REVIEWS GENETICS, Vol: 24, Pages: 724-734, ISSN: 1471-0056

Journal article

Tsui JL-H, McCrone JT, Lambert B, Bajaj S, Inward RPD, Bosetti P, Pena RE, Tegally H, Hill V, Zarebski AE, Peacock TP, Liu L, Wu N, Davis M, Bogoch II, Khan K, Kall M, Aziz NIBA, Colquhoun R, O'Toole A, Jackson B, Dasgupta A, Wilkinson E, de Oliveira T, Connor TR, Loman NJ, Colizza V, Fraser C, Volz E, Ji X, Gutierrez B, Chand M, Dellicour S, Cauchemez S, Raghwani J, Suchard MA, Lemey P, Rambaut A, Pybus OG, Kraemer MUGet al., 2023, Genomic assessment of invasion dynamics of SARS-CoV-2 Omicron BA.1, SCIENCE, Vol: 381, Pages: 336-343, ISSN: 0036-8075

Journal article

Perez Guzman PN, Knock ES, Imai N, Rawson T, Elmaci Y, Alcada J, Whittles LK, Thekke Kanapram D, Sonabend R, Gaythorpe KAM, Hinsley W, Fitzjohn RG, Volz E, Verity R, Ferguson NM, Cori A, Baguelin Met al., 2023, Epidemiological drivers of transmissibility and severity of SARS-CoV-2 in England, Nature Communications, Vol: 14, Pages: 1-9, ISSN: 2041-1723

As the SARS-CoV-2 pandemic progressed, distinct variants emerged and dominated in England. These variants, Wildtype, Alpha, Delta, and Omicron were characterized by variations in transmissibility and severity. We used a robust mathematical model and Bayesian inference framework to analyse epidemiological surveillance data from England. We quantified the impact of non-pharmaceutical interventions (NPIs), therapeutics, and vaccination on virus transmission and severity. Each successive variant had a higher intrinsic transmissibility. Omicron (BA.1) had the highest basic reproduction number at 8.3 (95% credible interval (CrI) 7.7-8.8). Varying levels of NPIs were crucial in controlling virus transmission until population immunity accumulated. Immune escape properties of Omicron decreased effective levels of immunity in the population by a third. Furthermore, in contrast to previous studies, we found Alpha had the highest basic infection fatality ratio (2.9%, 95% CrI 2.7-3.2), followed by Delta (2.2%, 95% CrI 2.0–2.4), Wildtype (1.2%, 95% CrI 1.1–1.2), and Omicron (0.7%, 95% CrI 0.6-0.8). Our findings highlight the importance of continued surveillance. Long-term strategies for monitoring and maintaining effective immunity against SARS-CoV-2 are critical to inform the role of NPIs to effectively manage future variants with potentially higher intrinsic transmissibility and severe outcomes.

Journal article

Didelot X, Franceschi V, Frost SDW, Dennis A, Volz EMet al., 2023, Model design for nonparametric phylodynamic inference and applications to pathogen surveillance, VIRUS EVOLUTION, Vol: 9

Journal article

Eales O, Page AJ, Tang SN, Walters CE, Wang H, Haw D, Trotter AJ, Le Viet T, Foster-Nyarko E, Prosolek S, Atchison C, Ashby D, Cooke G, Barclay W, Donnelly CA, O'Grady J, Volz E, The Covid-Genomics Uk Cog-Uk Consortium, Darzi A, Ward H, Elliott P, Riley Set al., 2023, The use of representative community samples to assess SARS-CoV-2 lineage competition: Alpha outcompetes Beta and wild-type in England from January to March 2021., Microbial Genomics, Vol: 9, Pages: 1-14, ISSN: 2057-5858

Genomic surveillance for SARS-CoV-2 lineages informs our understanding of possible future changes in transmissibility and vaccine efficacy and will be a high priority for public health for the foreseeable future. However, small changes in the frequency of one lineage over another are often difficult to interpret because surveillance samples are obtained using a variety of methods all of which are known to contain biases. As a case study, using an approach which is largely free of biases, we here describe lineage dynamics and phylogenetic relationships of the Alpha and Beta variant in England during the first 3 months of 2021 using sequences obtained from a random community sample who provided a throat and nose swab for rt-PCR as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. Overall, diversity decreased during the first quarter of 2021, with the Alpha variant (first identified in Kent) becoming predominant, driven by a reproduction number 0.3 higher than for the prior wild-type. During January, positive samples were more likely to be Alpha in those aged 18 to 54 years old. Although individuals infected with the Alpha variant were no more likely to report one or more classic COVID-19 symptoms compared to those infected with wild-type, they were more likely to be antibody-positive 6 weeks after infection. Further, viral load was higher in those infected with the Alpha variant as measured by cycle threshold (Ct) values. The presence of infections with non-imported Beta variant (first identified in South Africa) during January, but not during February or March, suggests initial establishment in the community followed by fade-out. However, this occurred during a period of stringent social distancing. These results highlight how sequence data from representative community surveys such as REACT-1 can augment routine genomic surveillance during periods of lineage diversity.

Journal article

Hill V, Plessis LD, Peacock TP, Aggarwal D, Colquhoun R, Carabelli AM, Ellaby N, Gallagher E, Groves N, Jackson B, McCrone JT, O'Toole A, Price A, Sanderson T, Scher E, Southgate J, Volz E, Barclay WS, Barrett JC, Chand M, Connor T, Goodfellow I, Gupta RK, Harrison EM, Loman N, Myers R, Robertson DL, Pybus OG, Rambaut Aet al., 2022, The origins and molecular evolution of SARS-CoV-2 lineage B.1.1.7 in the UK (vol 8, veac080, 2022), Virus Evolution, Vol: 8, Pages: 1-1, ISSN: 2057-1577

Journal article

McCrone JT, Hill V, Bajaj S, Pena RE, Lambert BC, Inward R, Bhatt S, Volz E, Ruis C, Dellicour S, Baele G, Zarebski AE, Sadilek A, Wu N, Schneider A, Ji X, Raghwani J, Ben J, Colquhoun R, Peacock TP, Twohig K, Thelwall S, Dabrera G, Myers R, Faria NR, Huber C, Bogoch II, Khan K, du Plessis L, Barrett JC, Aanensen DM, Barclay WS, Chand M, Connor T, Loman NJ, Suchard MA, Pybus OG, Rambaut A, Kraemer MUGet al., 2022, Context-specific emergence and growth of the SARS-CoV-2 Delta variant, NATURE, Vol: 610, Pages: 154-+, ISSN: 0028-0836

Journal article

Hill V, Du Plessis L, Peacock TP, Aggarwal D, Colquhoun R, Carabelli AM, Ellaby N, Gallagher E, Groves N, Jackson B, McCrone JT, O'Toole A, Price A, Sanderson T, Scher E, Southgate J, Volz E, Barclay WS, Barrett JC, Chand M, Connor T, Goodfellow I, Gupta RK, Harrison EM, Loman N, Myers R, Robertson DL, Pybus OG, Rambaut Aet al., 2022, The origins and molecular evolution of SARS-CoV-2 lineage B.1.1.7 in the UK, VIRUS EVOLUTION, Vol: 8

Journal article

Eales O, Wang H, Bodinier B, Haw D, Jonnerby J, Atchison C, Ashby D, Barclay W, Taylor G, Cooke G, Ward H, Darzi A, Riley S, Chadeau M, Donnelly C, Elliott Pet al., 2022, SARS-CoV-2 lineage dynamics in England from September to November 2021: high diversity of Delta sub-lineages and increased transmissibility of AY.4.2, BMC Infectious Diseases, Vol: 22, ISSN: 1471-2334

Background: Since the emergence of SARS-CoV-2, evolutionary pressure has driven large increases in the transmissibility of the virus. However, with increasing levels of immunity through vaccination and natural infection the evolutionary pressure will switch towards immune escape. Genomic surveillance in regions of high immunity is crucial in detecting emerging variants that can more successfully navigate the immune landscape. Methods: We present phylogenetic relationships and lineage dynamics within England (a country with high levels of immunity), as inferred from a random community sample of individuals who provided a self-administered throat and nose swab for rt-PCR testing as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. During round 14 (9 September - 27 September 2021) and 15 (19 October - 5 November 2021) lineages were determined for 1322 positive individuals, with 27.1% of those which reported their symptom status reporting no symptoms in the previous month.Results: We identified 44 unique lineages, all of which were Delta or Delta sub-lineages, and found a reduction in their mutation rate over the study period. The proportion of the Delta sub-lineage AY.4.2 was increasing, with a reproduction number 15% (95% CI, 8%-23%) greater than the most prevalent lineage, AY.4. Further, AY.4.2 was less associated with the most predictive COVID-19 symptoms (p = 0.029) and had a reduced mutation rate (p = 0.050). Both AY.4.2 and AY.4 were found to be geographically clustered in September but this was no longer the case by late October/early November, with only the lineage AY.6 exhibiting clustering towards the South of England.Conclusions: As SARS-CoV-2 moves towards endemicity and new variants emerge, genomic data obtained from random community samples can augment routine surveillance data without the potential biases introduced due to higher sampling rates of symptomatic individuals.

Journal article

Vohringer HS, Sanderson T, Sinnott M, De Maio N, Nguyen T, Goater R, Schwach F, Harrison I, Hellewell J, Ariani CV, Goncalves S, Jackson DK, Johnston I, Jung AW, Saint C, Sillitoe J, Suciu M, Goldman Net al., 2022, Genomic reconstruction of the SARS CoV-2 epidemic in England (vol 600, pg 506, 2021), NATURE, Vol: 606, Pages: E18-E18, ISSN: 0028-0836

Journal article

Subissi L, von Gottberg A, Thukral L, Worp N, Munnink BBO, Rathore S, Abu-Raddad LJ, Aguilera X, Alm E, Archer BN, Cohen HA, Barakat A, Barclay WS, Bhiman JN, Caly L, Chand M, Chen M, Cullinane A, de Oliveira T, Drosten C, Druce J, Effler P, El Masry I, Faye A, Gaseitsiwe S, Ghedin E, Grant R, Haagmans BL, Herring BL, Iyer SS, Kassamali Z, Kakkar M, Kondor RJ, Leite JA, Leo Y-S, Leung GM, Marklewitz M, Moyo S, Mendez-Rico J, Melhem NM, Munster V, Nahapetyan K, Oh D-Y, Pavlin B, Peacock TP, Peiris M, Peng Z, Poon LLM, Rambaut A, Sacks J, Shen Y, Siqueira MM, Tessema SK, Volz EM, Thiel V, van der Werf S, Briand S, Perkins MD, Van Kerkhove MD, Koopmans MPG, Agrawal Aet al., 2022, An early warning system for emerging SARS-CoV-2 variants, NATURE MEDICINE, Vol: 28, Pages: 1110-1115, ISSN: 1078-8956

Journal article

Ragonnet-Cronin M, Golubchik T, Moyo S, Fraser C, Essex M, Novitsky V, Volz Eet al., 2022, HIV genetic diversity informs stage of HIV-1 infection among patients receiving antiretroviral therapy in Botswana, The Journal of Infectious Diseases, Vol: 225, Pages: 1330-1338, ISSN: 0022-1899

BackgroundHIV-1 genetic diversity increases during infection and can help infer the time elapsed since infection. However the effect of antiretroviral treatment (ART) on the inference remains unknown.MethodsParticipants with estimated duration of HIV-1 infection based on repeated testing were sourced from cohorts in Botswana (n=1944). Full-length HIV genome sequencing was performed from proviral DNA. We optimized a machine learning model to classify infections as < or >1 year based on viral genetic diversity, demographic and clinical data.ResultsThe best predictive model included variables for genetic diversity of HIV-1 gag, pol and env, viral load, age, sex and ART status. Most participants were on ART. Balanced accuracy was 90.6% (95%CI:86.7%-94.1%). We tested the algorithm among newly diagnosed participants with or without documented negative HIV tests. Among those without records, those who self-reported a negative HIV test within <1 year were more frequently classified as recent than those who reported a test >1 year previously. There was no difference in classification between those self-reporting a negative HIV test <1 year, whether or not they had a record.ConclusionsThese results indicate that recency of HIV-1 infection can be inferred from viral sequence diversity even among patients on suppressive ART.

Journal article

Nyberg T, Ferguson NM, Nash SG, Webster HH, Flaxman S, Andrews N, Hinsley W, Bernal JL, Kall M, Bhatt S, Blomquist P, Zaidi A, Volz E, Aziz NA, Harman K, Funk S, Abbott S, Hope R, Charlett A, Chand M, Ghani AC, Seaman SR, Dabrera G, De Angelis D, Presanis AM, Thelwall Set al., 2022, Comparative analysis of the risks of hospitalisation and death associated with SARS-CoV-2 omicron (B.1.1.529) and delta (B.1.617.2) variants in England: a cohort study, The Lancet, Vol: 399, Pages: 1303-1312, ISSN: 0140-6736

BackgroundThe omicron variant (B.1.1.529) of SARS-CoV-2 has demonstrated partial vaccine escape and high transmissibility, with early studies indicating lower severity of infection than that of the delta variant (B.1.617.2). We aimed to better characterise omicron severity relative to delta by assessing the relative risk of hospital attendance, hospital admission, or death in a large national cohort.MethodsIndividual-level data on laboratory-confirmed COVID-19 cases resident in England between Nov 29, 2021, and Jan 9, 2022, were linked to routine datasets on vaccination status, hospital attendance and admission, and mortality. The relative risk of hospital attendance or admission within 14 days, or death within 28 days after confirmed infection, was estimated using proportional hazards regression. Analyses were stratified by test date, 10-year age band, ethnicity, residential region, and vaccination status, and were further adjusted for sex, index of multiple deprivation decile, evidence of a previous infection, and year of age within each age band. A secondary analysis estimated variant-specific and vaccine-specific vaccine effectiveness and the intrinsic relative severity of omicron infection compared with delta (ie, the relative risk in unvaccinated cases).FindingsThe adjusted hazard ratio (HR) of hospital attendance (not necessarily resulting in admission) with omicron compared with delta was 0·56 (95% CI 0·54–0·58); for hospital admission and death, HR estimates were 0·41 (0·39–0·43) and 0·31 (0·26–0·37), respectively. Omicron versus delta HR estimates varied with age for all endpoints examined. The adjusted HR for hospital admission was 1·10 (0·85–1·42) in those younger than 10 years, decreasing to 0·25 (0·21–0·30) in 60–69-year-olds, and then increasing to 0·47 (0·40–0·56) in those aged at leas

Journal article

Hill V, Du Plessis L, Peacock TP, Aggarwal D, Colquhoun R, Carabelli AM, Ellaby N, Gallagher E, Groves N, Jackson B, McCrone JT, OToole Á, Price A, Sanderson T, Scher E, Southgate J, Volz E, Barclay WS, Barrett JC, Chand M, Connor T, Goodfellow I, Gupta RK, Harrison EM, Loman N, Myers R, Robertson DL, Pybus OG, Rambaut Aet al., 2022, The origins and molecular evolution of SARS-CoV-2 lineage B.1.1.7 in the UK

<jats:title>Abstract</jats:title><jats:p>The first SARS-CoV-2 variant of concern (VOC) to be designated was lineage B.1.1.7, later labelled by the World Health Organisation (WHO) as Alpha. Originating in early Autumn but discovered in December 2020, it spread rapidly and caused large waves of infections worldwide. The Alpha variant is notable for being defined by a long ancestral phylogenetic branch with an increased evolutionary rate, along which only two sequences have been sampled. Alpha genomes comprise a well-supported monophyletic clade within which the evolutionary rate is more typical of SARS-CoV-2. The Alpha epidemic continued to grow despite the continued restrictions on social mixing across the UK, and the imposition of new restrictions, in particular the English national lockdown in November 2020. While these interventions succeeded in reducing the absolute number of cases, the impact of these non-pharmaceutical interventions was predominantly to drive the decline of the SARS-CoV-2 lineages which preceded Alpha. We investigate the only two sampled sequences that fall on the branch ancestral to Alpha. We find that one is likely to be a true intermediate sequence, providing information about the order of mutational events that led to Alpha. We explore alternate hypotheses that can explain how Alpha acquired a large number of mutations yet remained largely unobserved in a region of high genomic surveillance: an under-sampled geographical location, a non-human animal population, or a chronically-infected individual. We conclude that the last hypothesis provides the best explanation of the observed behaviour and dynamics of the variant, although we find that the individual need not be immunocompromised, as persistently-infected immunocompetent hosts also display a higher within-host rate of evolution. Finally, we compare the ancestral branches and mutation profiles of other VOCs to each other, and identify that Delta appears to be an outlier

Journal article

Stirrup O, Tostevin A, Ragonnet-Cronin M, Volz E, Burns F, Delpech V, Dunn Det al., 2022, Diagnosis delays in the UK according to pre or postmigration acquisition of HIV, AIDS, Vol: 36, Pages: 415-422, ISSN: 0269-9370

Journal article

Aggarwal D, Page AJ, Schaefer U, Savva GM, Myers R, Volz E, Ellaby N, Platt S, Groves N, Gallagher E, Tumelty NM, Thanh LV, Hughes GJ, Chen C, Turner C, Logan S, Harrison A, Peacock SJ, Chand M, Harrison EMet al., 2022, Genomic assessment of quarantine measures to prevent SARS-CoV-2 importation and transmission, Nature Communications, Vol: 13, ISSN: 2041-1723

Mitigation of SARS-CoV-2 transmission from international travel is a priority. We evaluated the effectiveness of travellers being required to quarantine for 14-days on return to England in Summer 2020. We identified 4,207 travel-related SARS-CoV-2 cases and their contacts, and identified 827 associated SARS-CoV-2 genomes. Overall, quarantine was associated with a lower rate of contacts, and the impact of quarantine was greatest in the 16–20 age-group. 186 SARS-CoV-2 genomes were sufficiently unique to identify travel-related clusters. Fewer genomically-linked cases were observed for index cases who returned from countries with quarantine requirement compared to countries with no quarantine requirement. This difference was explained by fewer importation events per identified genome for these cases, as opposed to fewer onward contacts per case. Overall, our study demonstrates that a 14-day quarantine period reduces, but does not completely eliminate, the onward transmission of imported cases, mainly by dissuading travel to countries with a quarantine requirement.

Journal article

Mourier T, Shuaib M, Hala S, Mfarrej S, Alofi F, Naeem R, Alsomali A, Jorgensen D, Subudhi AK, Ben Rached F, Guan Q, Salunke RP, Ooi A, Esau L, Douvropoulou O, Nugmanova R, Perumal S, Zhang H, Rajan I, Al-Omari A, Salih S, Shamsan A, Al Mutair A, Taha J, Alahmadi A, Khotani N, Alhamss A, Mahmoud A, Alquthami K, Dageeg A, Khogeer A, Hashem AM, Moraga P, Volz E, Almontashiri N, Pain Aet al., 2022, SARS-CoV-2 genomes from Saudi Arabia implicate nucleocapsid mutations in host response and increased viral load, Nature Communications, Vol: 13, ISSN: 2041-1723

Monitoring SARS-CoV-2 spread and evolution through genome sequencing is essential in handling the COVID-19 pandemic. Here, we sequenced 892 SARS-CoV-2 genomes collected from patients in Saudi Arabia from March to August 2020. We show that two consecutive mutations (R203K/G204R) in the nucleocapsid (N) protein are associated with higher viral loads in COVID-19 patients. Our comparative biochemical analysis reveals that the mutant N protein displays enhanced viral RNA binding and differential interaction with key host proteins. We found increased interaction of GSK3A kinase simultaneously with hyper-phosphorylation of the adjacent serine site (S206) in the mutant N protein. Furthermore, the host cell transcriptome analysis suggests that the mutant N protein produces dysregulated interferon response genes. Here, we provide crucial information in linking the R203K/G204R mutations in the N protein to modulations of host-virus interactions and underline the potential of the nucleocapsid protein as a drug target during infection.

Journal article

Nascimento FF, Ragonnet-Cronin M, Golubchik T, Danaviah S, Derache A, Fraser C, Volz Eet al., 2022, Evaluating whole HIV-1 genome sequence for estimation of incidence and migration in a rural South African community, Wellcome Open Research, Vol: 7

Background: South Africa has the largest number of people living with HIV (PLWHIV) in the world, with HIV prevalence and transmission patterns varying greatly between provinces. Transmission between regions is still poorly understood, but phylodynamics of HIV-1 evolution can reveal how many infections are attributable to contacts outside a given community. We analysed whole genome HIV-1 genetic sequences to estimate incidence and the proportion of transmissions between communities in Hlabisa, a rural South African community. Methods: We separately analysed HIV-1 for gag, pol, and env genes sampled from 2,503 PLWHIV. We estimated time-scaled phylogenies by maximum likelihood under a molecular clock model. Phylodynamic models were fitted to time-scaled trees to estimate transmission rates, effective number of infections, incidence through time, and the proportion of infections imported to Hlabisa. We also partitioned time-scaled phylogenies with significantly different distributions of coalescent times. Results: Phylodynamic analyses showed similar trends in epidemic growth rates between 1980 and 1990. Model-based estimates of incidence and effective number of infections were consistent across genes. Parameter estimates with gag were generally smaller than those estimated with pol and env. When estimating the proportions of new infections in Hlabisa from immigration or transmission from external sources, our posterior median estimates were 85% (95% credible interval (CI) = 78%–92%) for gag, 62% (CI = 40%–78%) for pol, and 77% (CI = 58%–90%) for env in 2015. Analysis of phylogenetic partitions by gene showed that most close global reference sequences clustered within a single partition. This suggests local evolving epidemics or potential unmeasured heterogeneity in the population. Conclusions: We estimated consistent epidemic dynamic trends for gag, pol and env genes using phylodynamic models. There was a high probability that new infections were not

Journal article

Twohig KA, Nyberg T, Zaidi A, Thelwall S, Sinnathamby MA, Aliabadi S, Seaman SR, Harris RJ, Hope R, Lopez-Bernal J, Gallagher E, Charlett A, De Angelis D, Presanis AM, Dabrera Get al., 2022, Hospital admission and emergency care attendance risk for SARS-CoV-2 delta (B.1.617.2) compared with alpha (B.1.1.7) variants of concern: a cohort study, LANCET INFECTIOUS DISEASES, Vol: 22, Pages: 35-42, ISSN: 1473-3099

Journal article

Nascimento FF, Ragonnet-Cronin M, Golubchik T, Danaviah S, Derache A, Fraser C, Volz Eet al., 2022, Evaluating whole HIV-1 genome sequence for estimation of incidence and migration in a rural South African community., Wellcome Open Res, Vol: 7, ISSN: 2398-502X

Background: South Africa has the largest number of people living with HIV (PLWHIV) in the world, with HIV prevalence and transmission patterns varying greatly between provinces. Transmission between regions is still poorly understood, but phylodynamics of HIV-1 evolution can reveal how many infections are attributable to contacts outside a given community. We analysed whole genome HIV-1 genetic sequences to estimate incidence and the proportion of transmissions between communities in Hlabisa, a rural South African community. Methods: We separately analysed HIV-1 for gag, pol, and env genes sampled from 2,503 PLWHIV. We estimated time-scaled phylogenies by maximum likelihood under a molecular clock model. Phylodynamic models were fitted to time-scaled trees to estimate transmission rates, effective number of infections, incidence through time, and the proportion of infections imported to Hlabisa. We also partitioned time-scaled phylogenies with significantly different distributions of coalescent times. Results: Phylodynamic analyses showed similar trends in epidemic growth rates between 1980 and 1990. Model-based estimates of incidence and effective number of infections were consistent across genes. Parameter estimates with gag were generally smaller than those estimated with pol and env. When estimating the proportions of new infections in Hlabisa from immigration or transmission from external sources, our posterior median estimates were 85% (95% credible interval (CI) = 78%-92%) for gag, 62% (CI = 40%-78%) for pol, and 77% (CI = 58%-90%) for env in 2015. Analysis of phylogenetic partitions by gene showed that most close global reference sequences clustered within a single partition. This suggests local evolving epidemics or potential unmeasured heterogeneity in the population. Conclusions: We estimated consistent epidemic dynamic trends for gag, pol and env genes using phylodynamic models. There was a high probability that new infections were not attributable to en

Journal article

Ferguson N, Ghani A, Hinsley W, Volz E, on behalf of the Imperial College COVID-19 Response Teamet al., 2021, Report 50: Hospitalisation risk for Omicron cases in England

To assess differences in the risk of hospitalisation between the Omicron variant of concern (1) and the Delta variant, we analysed data from all PCR-confirmed SARS-CoV-2 cases in England with last test specimen dates between 1st and 14th December inclusive. Variant was defined using a combination of S-gene Target Failure (SGTF) and genetic data. Case data were linked by National Health service (NHS) number to the National Immunisation Management System (NIMS) database, the NHS Emergency Care (ECDS) and Secondary Use Services (SUS) hospital episode datasets. Hospital attendance was defined as any record of attendance at a hospital by a case in the 14 days following their last positive PCR test, up to and including the day of attendance. A secondary analysis examined the subset of attendances with a length of stay of one or more days. We used stratified conditional Poisson regression to predict hospitalisation status, with demographic strata defined by age, sex, ethnicity, region, specimen date, index of multiple deprivation and in some analyses, vaccination status. Predictor variables were variant (Omicron or Delta), reinfection status and vaccination status. Overall, we find evidence of a reduction in the risk of hospitalisation for Omicron relative to Delta infections, averaging over all cases in the study period. The extent of reduction is sensitive to the inclusion criteria used for cases and hospitalisation, being in the range 20-25% when using any attendance at hospital as the endpoint, and 40-45% when using hospitalisation lasting 1 day or longer or hospitalisations with the ECDS discharge field recorded as “admitted” as the endpoint (Table 1). These reductions must be balanced against the larger risk of infection with Omicron, due to the reduction in protection provided by both vaccination and natural infection. A previous infection reduces the

Report

McCrone JT, Hill V, Bajaj S, Pena RE, Lambert BC, Inward R, Bhatt S, Volz E, Ruis C, Dellicour S, Baele G, Zarebski AE, Sadilek A, Wu N, Schneider A, Ji X, Raghwani J, Jackson B, Colquhoun R, O'Toole Á, Peacock TP, Twohig K, Thelwall S, Dabrera G, Myers R, COVID-19 genomics UK COG-UK consortium, Faria NR, Huber C, Bogoch II, Khan K, du Plessis L, Barrett JC, Aanensen DM, Barclay WS, Chand M, Connor T, Loman NJ, Suchard MA, Pybus OG, Rambaut A, Kraemer MUGet al., 2021, Context-specific emergence and growth of the SARS-CoV-2 Delta variant., medRxiv

The Delta variant of concern of SARS-CoV-2 has spread globally causing large outbreaks and resurgences of COVID-19 cases 1-3 . The emergence of Delta in the UK occurred on the background of a heterogeneous landscape of immunity and relaxation of non-pharmaceutical interventions 4,5 . Here we analyse 52,992 Delta genomes from England in combination with 93,649 global genomes to reconstruct the emergence of Delta, and quantify its introduction to and regional dissemination across England, in the context of changing travel and social restrictions. Through analysis of human movement, contact tracing, and virus genomic data, we find that the focus of geographic expansion of Delta shifted from India to a more global pattern in early May 2021. In England, Delta lineages were introduced >1,000 times and spread nationally as non-pharmaceutical interventions were relaxed. We find that hotel quarantine for travellers from India reduced onward transmission from importations; however the transmission chains that later dominated the Delta wave in England had been already seeded before restrictions were introduced. In England, increasing inter-regional travel drove Delta's nationwide dissemination, with some cities receiving >2,000 observable lineage introductions from other regions. Subsequently, increased levels of local population mixing, not the number of importations, was associated with faster relative growth of Delta. Among US states, we find that regions that previously experienced large waves also had faster Delta growth rates, and a model including interactions between immunity and human behaviour could accurately predict the rise of Delta there. Delta's invasion dynamics depended on fine scale spatial heterogeneity in immunity and contact patterns and our findings will inform optimal spatial interventions to reduce transmission of current and future VOCs such as Omicron.

Journal article

McCrone JT, Hill V, Bajaj S, Pena RE, Lambert BC, Inward R, Bhatt S, Volz E, Ruis C, Dellicour S, Baele G, Zarebski AE, Sadilek A, Wu N, Schneider A, Ji X, Raghwani J, Jackson B, Colquhoun R, O'Toole Á, Peacock TP, Twohig K, Thelwall S, Dabrera G, Myers R, COVID-19 genomics UK COG-UK consortium, Faria NR, Huber C, Bogoch II, Khan K, du Plessis L, Barrett JC, Aanensen DM, Barclay WS, Chand M, Connor T, Loman NJ, Suchard MA, Pybus OG, Rambaut A, Kraemer MUGet al., 2021, Context-specific emergence and growth of the SARS-CoV-2 Delta variant., Res Sq

The Delta variant of concern of SARS-CoV-2 has spread globally causing large outbreaks and resurgences of COVID-19 cases. The emergence of Delta in the UK occurred on the background of a heterogeneous landscape of immunity and relaxation of non-pharmaceutical interventions. Here we analyse 52,992 Delta genomes from England in combination with 93,649 global genomes to reconstruct the emergence of Delta, and quantify its introduction to and regional dissemination across England, in the context of changing travel and social restrictions. Through analysis of human movement, contact tracing, and virus genomic data, we find that the focus of geographic expansion of Delta shifted from India to a more global pattern in early May 2021. In England, Delta lineages were introduced >1,000 times and spread nationally as non-pharmaceutical interventions were relaxed. We find that hotel quarantine for travellers from India reduced onward transmission from importations; however the transmission chains that later dominated the Delta wave in England had been already seeded before restrictions were introduced. In England, increasing inter-regional travel drove Delta's nationwide dissemination, with some cities receiving >2,000 observable lineage introductions from other regions. Subsequently, increased levels of local population mixing, not the number of importations, was associated with faster relative growth of Delta. Among US states, we find that regions that previously experienced large waves also had faster Delta growth rates, and a model including interactions between immunity and human behaviour could accurately predict the rise of Delta there. Delta’s invasion dynamics depended on fine scale spatial heterogeneity in immunity and contact patterns and our findings will inform optimal spatial interventions to reduce transmission of current and future VOCs such as Omicron.

Journal article

Vohringer HS, Sanderson T, Sinnott M, De Maio N, Thuy N, Goater R, Schwach F, Harrison I, HeHowells J, Ariani C, Goncalves S, Jackson DK, Johnstone I, Jung AW, Saint C, Sillitoe J, Suciu M, Goldman N, Panovska-Griffiths J, Birney E, Volz E, Funk S, Kwiatkowski D, Chand M, Martincorena I, Barrett JC, Gerstung Met al., 2021, Genomic reconstruction of the SARS-CoV-2 epidemic in England, NATURE, Vol: 600, Pages: 506-+, ISSN: 0028-0836

Journal article

Ferguson N, Ghani A, Cori A, Hogan A, Hinsley W, Volz Eet al., 2021, Report 49: Growth, population distribution and immune escape of Omicron in England

To estimate the growth of the Omicron variant of concern (1) and its immune escape (2–9) characteristics, we analysed data from all PCR-confirmed SARS-CoV-2 cases in England excluding those with a history of recent international travel. We undertook separate analyses according to two case definitions. For the first definition, we included all cases with a definitive negative S-gene Target Failure (SGTF) result and specimen dates between 29/11/2021 and 11/12/2021 inclusive. For the second definition, we included cases with a positive genotype result and specimen date between 23/11/2021 and 11/12/2021 inclusive. We chose a later start date for the SGTF definition to ensure greater specificity of SGTF for Omicron.We used logistic and Poisson regression to identify factors associated with testing positive for Omicron compared to non-Omicron (mostly Delta) cases. We explored the following predictors: day, region, symptomatic status, sex, ethnicity, age band and vaccination status. Our results suggest rapid growth of the frequency of the Omicron variant relative to Delta, with the exponential growth rate of its frequency estimated to be 0.34/day (95% CI: 0.33-0.35) [2.0 day doubling time] over the study period from both SGTF and genotype data. The distribution of Omicron by age, region and ethnicity currently differs markedly from Delta, with 18–29-year-olds, residents in the London region, and those of African ethnicity having significantly higher rates of infection with Omicron relative to Delta.Hospitalisation and asymptomatic infection indicators were not significantly associated with Omicron infection, suggesting at most limited changes in severity compared with Delta.To estimate the impact of Omicron on vaccine effectiveness (VE) for symptomatic infection we used conditional Poisson regression to estimate the hazard ratio of being an Omicron case (using SGTF definition) compared with Delta, restricting our analysis to symptomatic cases and matching by da

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Helekal D, Ledda A, Volz E, Wyllie D, Didelot Xet al., 2021, Bayesian Inference of Clonal Expansions in a Dated Phylogeny, SYSTEMATIC BIOLOGY, ISSN: 1063-5157

Journal article

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