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
Year
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128 results found

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., 2022, Context-specific emergence and growth of the SARS-CoV-2 Delta variant., Nature

The SARS-CoV-2 Delta variant of concern spread globally, causing resurgences of COVID-19 worldwide1,2. Delta's emergence in the UK occurred on the background of a heterogeneous landscape of immunity and relaxation of non-pharmaceutical interventions. Here we analyse 52,992 virus genomes from England together 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 geographic focus of Delta's expansion 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 reduced onward transmission from importations; however transmission chains that later dominated England's Delta wave were seeded before travel restrictions were introduced. Increasing inter-regional travel within England drove Delta's nationwide dissemination, with some cities receiving >2,000 observable lineage introductions from elsewhere. Subsequently, increased levels of local population mixing, not the number of importations, were associated with faster relative growth of Delta. Delta's invasion dynamics depended on spatial heterogeneity in contact patterns, and our findings will inform optimal spatial interventions to reduce transmission of current and future variant of concern, such as Omicron.

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

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, Pages: 174-174

<ns3:p><ns3:bold>Background:</ns3:bold> 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.</ns3:p><ns3:p> <ns3:bold>Methods:</ns3:bold> We separately analysed HIV-1 for <ns3:italic>gag</ns3:italic>, <ns3:italic>pol</ns3:italic>, and <ns3:italic>env </ns3:italic>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.</ns3:p><ns3:p> <ns3:bold>Results:</ns3:bold> 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 <ns3:italic>gag</ns3:italic> were generally smaller than those estimated with <ns3:italic>pol</ns3:italic> and <ns3:italic>env</ns3:italic>. 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 <ns3:italic>gag</ns3:italic>, 62% (CI = 40%–78%) for <ns3:italic>pol</

Journal article

Vöhringer HS, Sanderson T, Sinnott M, De Maio N, Nguyen T, Goater R, Schwach F, Harrison I, Hellewell J, Ariani CV, Gonçalves S, Jackson DK, Johnston I, Jung AW, Saint C, Sillitoe J, Suciu M, Goldman N, Panovska-Griffiths J, Wellcome Sanger Institute COVID-19 Surveillance Team, COVID-19 Genomics UK COG-UK Consortium, Birney E, Volz E, Funk S, Kwiatkowski D, Chand M, Martincorena I, Barrett JC, Gerstung Met al., 2022, Publisher Correction: Genomic reconstruction of the SARS CoV-2 epidemic in England., Nature, Vol: 606

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, LANCET, Vol: 399, Pages: 1303-1312, ISSN: 0140-6736

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

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

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., 2021, 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

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

Report

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

Sonabend R, Whittles LK, Imai N, Perez Guzman PN, Knock E, Rawson T, Gaythorpe KA, Djaafara A, Hinsley W, Fitzjohn R, Lees JA, Thekke Kanapram D, Volz E, Ghani A, Ferguson NM, Baguelin M, Cori Aet al., 2021, Non-pharmaceutical interventions, vaccination, and the SARS-CoV-2 delta variant in England: a mathematical modelling study, The Lancet, Vol: 398, Pages: 1825-1835, ISSN: 0140-6736

Background:England's COVID-19 roadmap out of lockdown policy set out the timeline and conditions for the stepwise lifting of non-pharmaceutical interventions (NPIs) as vaccination roll-out continued, with step one starting on March 8, 2021. In this study, we assess the roadmap, the impact of the delta (B.1.617.2) variant of SARS-CoV-2, and potential future epidemic trajectories.Methods:This mathematical modelling study was done to assess the UK Government's four-step process to easing lockdown restrictions in England, UK. We extended a previously described model of SARS-CoV-2 transmission to incorporate vaccination and multi-strain dynamics to explicitly capture the emergence of the delta variant. We calibrated the model to English surveillance data, including hospital admissions, hospital occupancy, seroprevalence data, and population-level PCR testing data using a Bayesian evidence synthesis framework, then modelled the potential trajectory of the epidemic for a range of different schedules for relaxing NPIs. We estimated the resulting number of daily infections and hospital admissions, and daily and cumulative deaths. Three scenarios spanning a range of optimistic to pessimistic vaccine effectiveness, waning natural immunity, and cross-protection from previous infections were investigated. We also considered three levels of mixing after the lifting of restrictions.Findings:The roadmap policy was successful in offsetting the increased transmission resulting from lifting NPIs starting on March 8, 2021, with increasing population immunity through vaccination. However, because of the emergence of the delta variant, with an estimated transmission advantage of 76% (95% credible interval [95% CrI] 69–83) over alpha, fully lifting NPIs on June 21, 2021, as originally planned might have led to 3900 (95% CrI 1500–5700) peak daily hospital admissions under our central parameter scenario. Delaying until July 19, 2021, reduced peak hospital admissions by three fol

Journal article

Kraemer MUG, Hill V, Ruis C, Dellicour S, Bajaj S, McCrone JT, Baele G, Parag KV, Battle AL, Gutierrez B, Jackson B, Colquhoun R, O'Toole Á, Klein B, Vespignani A, COVID-19 Genomics UK CoG-UK consortium, Volz E, Faria NR, Aanensen D, Loman NJ, du Plessis L, Cauchemez S, Rambaut A, Scarpino SV, Pybus OGet al., 2021, Spatiotemporal invasion dynamics of SARS-CoV-2 lineage B.1.1.7 emergence, Science, Vol: 373, Pages: 889-895, ISSN: 0036-8075

Understanding the causes and consequences of the emergence of SARS-CoV-2 variants of concern is crucial to pandemic control yet difficult to achieve, as they arise in the context of variable human behavior and immunity. We investigate the spatial invasion dynamics of lineage B.1.1.7 by jointly analyzing UK human mobility, virus genomes, and community-based PCR data. We identify a multi-stage spatial invasion process in which early B.1.1.7 growth rates were associated with mobility and asymmetric lineage export from a dominant source location, enhancing the effects of B.1.1.7's increased intrinsic transmissibility. We further explore how B.1.1.7 spread was shaped by non-pharmaceutical interventions and spatial variation in previous attack rates. Our findings show that careful accounting of the behavioral and epidemiological context within which variants of concern emerge is necessary to interpret correctly their observed relative growth rates.

Journal article

Didelot X, Geidelberg L, COVID-19 Genomics UK COG-UK consortium, Volz EMet al., 2021, Model design for non-parametric phylodynamic inference and applications to pathogen surveillance., bioRxiv

Inference of effective population size from genomic data can provide unique information about demographic history, and when applied to pathogen genetic data can also provide insights into epidemiological dynamics. The combination of non-parametric models for population dynamics with molecular clock models which relate genetic data to time has enabled phylodynamic inference based on large sets of time-stamped genetic sequence data. The methodology for non-parametric inference of effective population size is well-developed in the Bayesian setting, but here we develop a frequentist approach based on non-parametric latent process models of population size dynamics. We appeal to statistical principles based on out-of-sample prediction accuracy in order to optimize parameters that control shape and smoothness of the population size over time. We demonstrate the flexibility and speed of this approach in a series of simulation experiments, and apply the methodology to reconstruct the previously described waves in the seventh pandemic of cholera. We also estimate the impact of non-pharmaceutical interventions for COVID-19 in England using thousands of SARS-CoV-2 sequences. By incorporating a measure of the strength of these interventions over time within the phylodynamic model, we estimate the impact of the first national lockdown in the UK on the epidemic reproduction number.

Journal article

Mishra S, Mindermann S, Sharma M, Whittaker C, Mellan TA, Wilton T, Klapsa D, Mate R, Fritzsche M, Zambon M, Ahuja J, Howes A, Miscouridou X, Nason GP, Ratmann O, Semenova E, Leech G, Sandkuehler JF, Rogers-Smith C, Vollmer M, Unwin HJT, Gal Y, Chand M, Gandy A, Martin J, Volz E, Ferguson NM, Bhatt S, Brauner JM, Flaxman Set al., 2021, Changing composition of SARS-CoV-2 lineages and rise of Delta variant in England, ECLINICALMEDICINE, Vol: 39

Journal article

Helekal D, Ledda A, Volz E, Wyllie D, Didelot Xet al., 2021, Bayesian inference of clonal expansions in a dated phylogeny

<jats:title>ABSTRACT</jats:title><jats:p>Microbial population genetics models often assume that all lineages are constrained by the same population size dynamics over time. However, many neutral and selective events can invalidate this assumption, and can contribute to the clonal expansion of a specific lineage relative to the rest of the population. Such differential phylodynamic properties between lineages result in asymmetries and imbalances in phylogenetic trees that are sometimes described informally but which are difficult to analyse formally. To this end, we developed a model of how clonal expansions occur and affect the branching patterns of a phylogeny. We show how the parameters of this model can be inferred from a given dated phylogeny using Bayesian statistics, which allows us to assess the probability that one or more clonal expansion events occurred. For each putative clonal expansion event we estimate their date of emergence and subsequent phylodynamic trajectories, including their long-term evolutionary potential which is important to determine how much effort should be placed on specific control measures. We demonstrate the applicability of our methodology on simulated and real datasets.</jats:p>

Journal article

Meng B, Kemp SA, Papa G, Datir R, Ferreira IATM, Marelli S, Harvey WT, Lytras S, Mohamed A, Gallo G, Thakur N, Collier DA, Mlcochova P, Duncan LM, Carabelli AM, Kenyon JC, Lever AM, De Marco A, Saliba C, Culap K, Cameroni E, Matheson NJ, Piccoli L, Corti D, James LC, Robertson DL, Bailey D, Gupta RKet al., 2021, Recurrent emergence of SARS-CoV-2 spike deletion H69/V70 and its role in the Alpha variant B.1.1.7, CELL REPORTS, Vol: 35, ISSN: 2211-1247

Journal article

Dennis AM, Frost SDW, Enders K, Cressman AE, Volz E, Adams N, Miller WC, Cohen MS, Mobley V, Samoff E, Eron JJet al., 2021, HIV-1 Transmission linkages among persons with incident infection to inform public health surveillance, ECLINICALMEDICINE, Vol: 37

Journal article

Mishra S, Mindermann S, Sharma M, Whittaker C, Mellan T, Wilton T, Klapsa D, Mate R, Fritzsche M, Zambon M, Ahuja J, Howes A, Miscouridou X, Nason G, Ratmann O, Leech G, Fabienne Sandkühler J, Rogers-Smith C, Vollmer M, Unwin H, Gal Y, Chand M, Gandy A, Martin J, Volz E, Ferguson N, Bhatt S, Brauner J, Flaxman Set al., 2021, Report 44: Recent trends in SARS-CoV-2 variants of concern in England, Report 44: Recent trends in SARS-CoV-2 variants of concern in England, Publisher: Imperial College London, 44

Since its emergence in Autumn 2020, the SARS-CoV-2 Variant of Concern (VOC) B.1.1.7 rapidly became the dominant lineage across much of Europe. Simultaneously, several other VOCs were identified globally. Unlike B.1.1.7, some of these VOCs possess mutations thought to confer partial immune escape. Understanding when, whether, and how these additional VOCs pose a threat in settings where B.1.1.7 is currently dominant is vital. This is particularly true for England, which has high coverage from vaccines that are likely more protective against B.1.1.7 than some other VOCs. We examine trends in B.1.1.7’s prevalence in London and other English regions using passive-case detection PCR data, cross-sectional community infection surveys, genomic surveillance, and wastewater monitoring. Our results suggest shifts in the composition of SARS-CoV-2 lineages driving transmission in England between March and April 2021. Local transmission of non-B.1.1.7 VOCs may be increasing; this warrants urgent further investigation.

Report

Volz E, Mishra S, Chand M, Barrett JC, Johnson R, Geidelberg L, Hinsley WR, Laydon DJ, Dabrera G, O'Toole Á, Amato R, Ragonnet-Cronin M, Harrison I, Jackson B, Ariani CV, Boyd O, Loman NJ, McCrone JT, Gonçalves S, Jorgensen D, Myers R, Hill V, Jackson DK, Gaythorpe K, Groves N, Sillitoe J, Kwiatkowski DP, COVID-19 Genomics UK COG-UK consortium, Flaxman S, Ratmann O, Bhatt S, Hopkins S, Gandy A, Rambaut A, Ferguson NMet al., 2021, Assessing transmissibility of SARS-CoV-2 lineage B.1.1.7 in England, Nature, Vol: 593, Pages: 266-269, ISSN: 0028-0836

The SARS-CoV-2 lineage B.1.1.7, designated a Variant of Concern 202012/01 (VOC) by Public Health England1, originated in the UK in late Summer to early Autumn 20202. Whole genome SARS-CoV-2 sequence data collected from community-based diagnostic testing shows an unprecedentedly rapid expansion of the B.1.1.7 lineage during Autumn 2020, suggesting a selective advantage. We find that changes in VOC frequency inferred from genetic data correspond closely to changes inferred by S-gene target failures (SGTF) in community-based diagnostic PCR testing. Analysis of trends in SGTF and non-SGTF case numbers in local areas across England shows that the VOC has higher transmissibility than non-VOC lineages, even if the VOC has a different latent period or generation time. The SGTF data indicate a transient shift in the age composition of reported cases, with a larger share of under 20 year olds among reported VOC than non-VOC cases. Time-varying reproduction numbers for the VOC and cocirculating lineages were estimated using SGTF and genomic data. The best supported models did not indicate a substantial difference in VOC transmissibility among different age groups. There is a consensus among all analyses that the VOC has a substantial transmission advantage with a 50% to 100% higher reproduction number.

Journal article

Eales O, Page AJ, Tang S, Walters C, Wang H, Haw D, Trotter AJ, Viet TL, Foster-Nyarko E, Prosolek S, Atchison C, Ashby D, Cooke G, Barclay W, Donnelly C, O'Grady J, Volz E, The COVID-19 Genomics UK Consortium, Darzi A, Ward H, Elliott P, Riley Set al., 2021, SARS-CoV-2 lineage dynamics in England from January to March 2021 inferred from representative community samples

Genomic surveillance for SARS-CoV-2 lineages informs our understanding of possible future changes in transmissibility and vaccine efficacy. However, small changes in the frequency of one lineage over another are often difficult to interpret because surveillance samples are obtained from a variety of sources. Here, we describe lineage dynamics and phylogenetic relationships using sequences obtained from a random community sample who provided a throat and nose swab for rt-PCR during the first three months of 2021 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 B.1.1.7 lineage (first identified in Kent) predominant, driven by a 0.3 unit higher reproduction number over the prior wild type. During January, positive samples were more likely B.1.1.7 in younger and middle-aged adults (aged 18 to 54) than in other age groups. Although individuals infected with the B.1.1.7 lineage 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. Viral load was higher in B.1.1.7 infection as measured by cycle threshold (Ct) values, but did not account for the increased rate of testing positive for antibodies. The presence of infections with non-imported B.1.351 lineage (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 and targeted public health interventions and does not immediately imply similar lineages could not become established in the future. Sequence data from representative community surveys such as REACT-1 can augment routine genomic surveillance.

Working paper

Graham MS, Sudre CH, May A, Antonelli M, Murray B, Varsavsky T, Kläser K, Canas LS, Molteni E, Modat M, Drew DA, Nguyen LH, Polidori L, Selvachandran S, Hu C, Capdevila J, COVID-19 Genomics UK COG-UK Consortium, Hammers A, Chan AT, Wolf J, Spector TD, Steves CJ, Ourselin Set al., 2021, Changes in symptomatology, reinfection, and transmissibility associated with the SARS-CoV-2 variant B.1.1.7: an ecological study, The Lancet Public Health, Vol: 6, Pages: e335-e345, ISSN: 2468-2667

BACKGROUND: The SARS-CoV-2 variant B.1.1.7 was first identified in December, 2020, in England. We aimed to investigate whether increases in the proportion of infections with this variant are associated with differences in symptoms or disease course, reinfection rates, or transmissibility. METHODS: We did an ecological study to examine the association between the regional proportion of infections with the SARS-CoV-2 B.1.1.7 variant and reported symptoms, disease course, rates of reinfection, and transmissibility. Data on types and duration of symptoms were obtained from longitudinal reports from users of the COVID Symptom Study app who reported a positive test for COVID-19 between Sept 28 and Dec 27, 2020 (during which the prevalence of B.1.1.7 increased most notably in parts of the UK). From this dataset, we also estimated the frequency of possible reinfection, defined as the presence of two reported positive tests separated by more than 90 days with a period of reporting no symptoms for more than 7 days before the second positive test. The proportion of SARS-CoV-2 infections with the B.1.1.7 variant across the UK was estimated with use of genomic data from the COVID-19 Genomics UK Consortium and data from Public Health England on spike-gene target failure (a non-specific indicator of the B.1.1.7 variant) in community cases in England. We used linear regression to examine the association between reported symptoms and proportion of B.1.1.7. We assessed the Spearman correlation between the proportion of B.1.1.7 cases and number of reinfections over time, and between the number of positive tests and reinfections. We estimated incidence for B.1.1.7 and previous variants, and compared the effective reproduction number, Rt, for the two incidence estimates. FINDINGS: From Sept 28 to Dec 27, 2020, positive COVID-19 tests were reported by 36 920 COVID Symptom Study app users whose region was known and who reported as healthy on app sign-up. We found no changes in repo

Journal article

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