Imperial College London

Professor Neil Ferguson

Faculty of MedicineSchool of Public Health

Director of the School of Public Health
 
 
 
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Contact

 

+44 (0)20 7594 3296neil.ferguson Website

 
 
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Location

 

Medical SchoolSt Mary's Campus

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Summary

 

Publications

Publication Type
Year
to

435 results found

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

McCormack C, Goethals O, Goeyvaerts N, Woot de Trixhe XD, Geluykens P, Borrenberghs D, Ferguson NM, Ackaert O, Dorigatti Iet al., 2023, Modelling the impact of JNJ-1802, a first-in-class dengue inhibitor blocking the NS3-NS4B interaction, on in-vitro DENV-2 dynamics, PLoS Computational Biology, Vol: 19, ISSN: 1553-734X

Dengue virus (DENV) is a public health challenge across the tropics and subtropics. Currently, there is no licensed prophylactic or antiviral treatment for dengue. The novel DENV inhibitor JNJ-1802 can significantly reduce viral load in mice and non-human primates. Here, using a mechanistic viral kinetic model calibrated against viral RNA data from experimental in-vitro infection studies, we assess the in-vitro inhibitory effect of JNJ-1802 by characterising infection dynamics of two DENV-2 strains in the absence and presence of different JNJ-1802 concentrations. Viral RNA suppression to below the limit of detection was achieved at concentrations of >1.6 nM, with a median concentration exhibiting 50% of maximal inhibitory effect (IC50) of 1.23x10-02 nM and 1.28x10-02 nM for the DENV-2/RL and DENV-2/16681 strains, respectively. This work provides important insight into the in-vitro inhibitory effect of JNJ-1802 and presents a first step towards a modelling framework to support characterization of viral kinetics and drug effect across different host systems.

Journal article

Hogan AB, Wu SL, Toor J, Olivera Mesa D, Doohan P, Watson OJ, Winskill P, Charles G, Barnsley G, Riley EM, Khoury DS, Ferguson NM, Ghani ACet al., 2023, Long-term vaccination strategies to mitigate the impact of SARS-CoV-2 transmission: A modelling study., PLoS Med, Vol: 20

BACKGROUND: Vaccines have reduced severe disease and death from Coronavirus Disease 2019 (COVID-19). However, with evidence of waning efficacy coupled with continued evolution of the virus, health programmes need to evaluate the requirement for regular booster doses, considering their impact and cost-effectiveness in the face of ongoing transmission and substantial infection-induced immunity. METHODS AND FINDINGS: We developed a combined immunological-transmission model parameterised with data on transmissibility, severity, and vaccine effectiveness. We simulated Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) transmission and vaccine rollout in characteristic global settings with different population age-structures, contact patterns, health system capacities, prior transmission, and vaccine uptake. We quantified the impact of future vaccine booster dose strategies with both ancestral and variant-adapted vaccine products, while considering the potential future emergence of new variants with modified transmission, immune escape, and severity properties. We found that regular boosting of the oldest age group (75+) is an efficient strategy, although large numbers of hospitalisations and deaths could be averted by extending vaccination to younger age groups. In countries with low vaccine coverage and high infection-derived immunity, boosting older at-risk groups was more effective than continuing primary vaccination into younger ages in our model. Our study is limited by uncertainty in key parameters, including the long-term durability of vaccine and infection-induced immunity as well as uncertainty in the future evolution of the virus. CONCLUSIONS: Our modelling suggests that regular boosting of the high-risk population remains an important tool to reduce morbidity and mortality from current and future SARS-CoV-2 variants. Our results suggest that focusing vaccination in the highest-risk cohorts will be the most efficient (and hence cost-effective) strateg

Journal article

Bhatia S, Parag KV, Wardle J, Nash RK, Imai N, Elsland SLV, Lassmann B, Brownstein JS, Desai A, Herringer M, Sewalk K, Loeb SC, Ramatowski J, Cuomo-Dannenburg G, Jauneikaite E, Unwin HJT, Riley S, Ferguson N, Donnelly CA, Cori A, Nouvellet Pet al., 2023, Retrospective evaluation of real-time estimates of global COVID-19 transmission trends and mortality forecasts, PLOS ONE, Vol: 18, ISSN: 1932-6203

Journal article

Bhatt S, Ferguson N, Flaxman S, Gandy A, Mishra S, Scott JAet al., 2023, Bhatt, Ferguson, Flaxman, Gandy, Mishra, and Scott’s reply to the Discussion of ‘The Second Discussion Meeting on Statistical aspects of the Covid-19 Pandemic’, Journal of the Royal Statistical Society. Series A: Statistics in Society, Vol: 186, Pages: 651-653, ISSN: 0964-1998

Journal article

Bhatt S, Ferguson N, Flaxman S, Gandy A, Mishra S, Scott JAet al., 2023, Semi-mechanistic Bayesian modelling of COVID-19 with renewal processes, Journal of the Royal Statistical Society. Series A: Statistics in Society, Vol: 186, Pages: 633-636, ISSN: 0964-1998

We propose a general Bayesian approach to modelling epidemics such as COVID-19. The approach grew out of specific analyses conducted during the pandemic, in particular, an analysis concerning the effects of non-pharmaceutical interventions (NPIs) in reducing COVID-19 transmission in 11 European countries. The model parameterises the time-varying reproduction number Rt through a multilevel regression framework in which covariates can be governmental interventions, changes in mobility patterns, or other behavioural measures. Bayesian multilevel modelling allows a joint fit across regions, with partial pooling to share strength. This innovation was critical to our timely estimates of the impact of lockdown and other NPIs in the European epidemics: estimates from countries at later stages in their epidemics informed those of countries at earlier stages. Originally released as Imperial College Reports, the validity of this approach was borne out by the subsequent course of the epidemic. Our framework provides a fully generative model for latent infections and derived observations, including deaths, cases, hospitalizations, ICU admissions, and seroprevalence surveys. In this article, we additionally explore the confounded nature of NPIs and mobility. Versions of our model were used by New York State, Tennessee, and Scotland to estimate the current epidemic situation and make policy decisions.

Journal article

Zhou J, Singanayagam A, Goonawardane N, Moshe M, Sweeney F, Sukhova K, Killingley B, Kalinova M, Mann A, Catchpole A, Barer MR, Ferguson NM, Chiu C, Barclay WSet al., 2023, Viral emissions into the air and environment after SARS-CoV-2 human challenge: a phase 1, open label, first-in-human study, The Lancet Microbe, Vol: 4, Pages: e579-e590, ISSN: 2666-5247

BackgroundEffectively implementing strategies to curb SARS-CoV-2 transmission requires understanding who is contagious and when. Although viral load on upper respiratory swabs has commonly been used to infer contagiousness, measuring viral emissions might be more accurate to indicate the chance of onward transmission and identify likely routes. We aimed to correlate viral emissions, viral load in the upper respiratory tract, and symptoms, longitudinally, in participants who were experimentally infected with SARS-CoV-2.MethodsIn this phase 1, open label, first-in-human SARS-CoV-2 experimental infection study at quarantine unit at the Royal Free London NHS Foundation Trust, London, UK, healthy adults aged 18–30 years who were unvaccinated for SARS-CoV-2, not previously known to have been infected with SARS-CoV-2, and seronegative at screening were recruited. Participants were inoculated with 10 50% tissue culture infectious dose of pre-alpha wild-type SARS-CoV-2 (Asp614Gly) by intranasal drops and remained in individual negative pressure rooms for a minimum of 14 days. Nose and throat swabs were collected daily. Emissions were collected daily from the air (using a Coriolis μ air sampler and directly into facemasks) and the surrounding environment (via surface and hand swabs). All samples were collected by researchers, and tested by using PCR, plaque assay, or lateral flow antigen test. Symptom scores were collected using self-reported symptom diaries three times daily. The study is registered with ClinicalTrials.gov, NCT04865237.FindingsBetween March 6 and July 8, 2021, 36 participants (ten female and 26 male) were recruited and 18 (53%) of 34 participants became infected, resulting in protracted high viral loads in the nose and throat following a short incubation period, with mild-to-moderate symptoms. Two participants were excluded from the per-protocol analysis owing to seroconversion between screening and inoculation, identified post hoc. Viral RNA was de

Journal article

Hogan A, Doohan P, Wu S, Olivera Mesa D, Turner J, Watson O, Winskill P, Charles G, Barnsley G, Riley E, Khoury D, Ferguson N, Ghani Aet al., 2023, Estimating long-term vaccine effectiveness against SARS-CoV-2 variants: a model-based approach, Nature Communications, Vol: 14, Pages: 1-10, ISSN: 2041-1723

With the ongoing evolution of the SARS-CoV-2 virus updated vaccines may be needed. We fitted a model linking immunity levels and protection to vaccine effectiveness data from England for three vaccines (Oxford/AstraZeneca AZD1222, Pfizer-BioNTech BNT162b2, Moderna mRNA-1273) and two variants (Delta, Omicron). Our model reproduces the observed sustained protection against hospitalisation and death from the Omicron variant over the first six months following dose 3 with the monovalent vaccines but projects a gradual waning to moderate protection after 1 year. Switching the fourth dose to a variant-matched vaccine against Omicron BA.1/2 is projected to prevent nearly twice as many hospitalisations and deaths over a 1-year period compared to administering the ancestral vaccine. This result is sensitive to the degree to which immunogenicity data can be used to predict vaccine effectiveness and uncertainty regarding the impact that infection-induced immunity (not captured here) may play in modifying future vaccine effectiveness.

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

Derqui N, Koycheva A, Zhou J, Pillay TD, Crone MA, Hakki S, Fenn J, Kundu R, Varro R, Conibear E, Madon KJ, Barnett JL, Houston H, Singanayagam A, Narean JS, Tolosa-Wright MR, Mosscrop L, Rosadas C, Watber P, Anderson C, Parker E, Freemont PS, Ferguson NM, Zambon M, McClure MO, Tedder R, Barclay WS, Dunning J, Taylor GP, Lalvani A, INSTINCT and ATACCC study groupet al., 2023, Risk factors and vectors for SARS-CoV-2 household transmission: a prospective, longitudinal cohort study, The Lancet Microbe, Vol: 4, Pages: e397-e408, ISSN: 2666-5247

BACKGROUND: Despite circumstantial evidence for aerosol and fomite spread of SARS-CoV-2, empirical data linking either pathway with transmission are scarce. Here we aimed to assess whether the presence of SARS-CoV-2 on frequently-touched surfaces and residents' hands was a predictor of SARS-CoV-2 household transmission. METHODS: In this longitudinal cohort study, during the pre-alpha (September to December, 2020) and alpha (B.1.1.7; December, 2020, to April, 2021) SARS-CoV-2 variant waves, we prospectively recruited contacts from households exposed to newly diagnosed COVID-19 primary cases, in London, UK. To maximally capture transmission events, contacts were recruited regardless of symptom status and serially tested for SARS-CoV-2 infection by RT-PCR on upper respiratory tract (URT) samples and, in a subcohort, by serial serology. Contacts' hands, primary cases' hands, and frequently-touched surface-samples from communal areas were tested for SARS-CoV-2 RNA. SARS-CoV-2 URT isolates from 25 primary case-contact pairs underwent whole-genome sequencing (WGS). FINDINGS: From Aug 1, 2020, until March 31, 2021, 620 contacts of PCR-confirmed SARS-CoV-2-infected primary cases were recruited. 414 household contacts (from 279 households) with available serial URT PCR results were analysed in the full household contacts' cohort, and of those, 134 contacts with available longitudinal serology data and not vaccinated pre-enrolment were analysed in the serology subcohort. Household infection rate was 28·4% (95% CI 20·8-37·5) for pre-alpha-exposed contacts and 51·8% (42·5-61·0) for alpha-exposed contacts (p=0·0047). Primary cases' URT RNA viral load did not correlate with transmission, but was associated with detection of SARS-CoV-2 RNA on their hands (p=0·031). SARS-CoV-2 detected on primary cases' hands, in turn, predicted contacts' risk of infection (adjusted relative risk [aRR]=1·70 [95% CI 1·24-2·3

Journal article

Gaythorpe K, Fitzjohn R, Hinsley W, Imai N, Knock E, Perez Guzman P, Djaafara B, Fraser K, Baguelin M, Ferguson Net al., 2023, Data pipelines in a public health emergency: the human in the machine, Epidemics: the journal of infectious disease dynamics, Vol: 43, ISSN: 1755-4365

In an emergency epidemic response, data providers supply data on a best-faith effort to modellers and analysts who are typically the end user of data collected for other primary purposes such as to inform patient care. Thus, modellers who analyse secondary data have limited ability to influence what is captured. During an emergency response, models themselves are often under constant development and require both stability in their data inputs and flexibility to incorporate new inputs as novel data sources become available. This dynamic landscape is challenging to work with. Here we outline a data pipeline used in the ongoing COVID-19 response in the UK that aims to address these issues.A data pipeline is a sequence of steps to carry the raw data through to a processed and useable model input, along with the appropriate metadata and context. In ours, each data type had an individual processing report, designed to produce outputs that could be easily combined and used downstream. Automated checks were in-built and added as new pathologies emerged. These cleaned outputs were collated at different geographic levels to provide standardised datasets. Finally, a human validation step was an essential component of the analysis pathway and permitted more nuanced issues to be captured. This framework allowed the pipeline to grow in complexity and volume and facilitated the diverse range of modelling approaches employed by researchers. Additionally, every report or modelling output could be traced back to the specific data version that informed it ensuring reproducibility of results.Our approach has been used to facilitate fast-paced analysis and has evolved over time. Our framework and its aspirations are applicable to many settings beyond COVID-19 data, for example for other outbreaks such as Ebola, or where routine and regular analyses are required.

Journal article

Laydon D, Cauchemez S, Hinsley W, Bhatt S, Ferguson Net al., 2023, Impact of proactive and reactive vaccination strategies for health-care workers against MERS-CoV: a mathematical modelling study, The Lancet Global Health, Vol: 11, Pages: e759-e769, ISSN: 2214-109X

BackgroundSeveral vaccine candidates are in development against MERS-CoV, which remains a major public health concern. In anticipation of available MERS-CoV vaccines, we examine strategies for their optimal deployment among health-care workers.MethodsUsing data from the 2013–14 Saudi Arabia epidemic, we use a counterfactual analysis on inferred transmission trees (who-infected-whom analysis) to assess the potential impact of vaccination campaigns targeting health-care workers, as quantified by the proportion of cases or deaths averted. We investigate the conditions under which proactive campaigns (ie vaccinating in anticipation of the next outbreak) would outperform reactive campaigns (ie vaccinating in response to an unfolding outbreak), considering vaccine efficacy, duration of vaccine protection, effectiveness of animal reservoir control measures, wait (time between vaccination and next outbreak, for proactive campaigns), reaction time (for reactive campaigns), and spatial level (hospital, regional, or national, for reactive campaigns). We also examine the relative efficiency (cases averted per thousand doses) of different strategies.FindingsThe spatial scale of reactive campaigns is crucial. Proactive campaigns outperform campaigns that vaccinate health-care workers in response to outbreaks at their hospital, unless vaccine efficacy has waned significantly. However, reactive campaigns at the regional or national levels consistently outperform proactive campaigns, regardless of vaccine efficacy. When considering the number of cases averted per vaccine dose administered, the rank order is reversed: hospital-level reactive campaigns are most efficient, followed by regional-level reactive campaigns, with national-level and proactive campaigns being least efficient. If the number of cases required to trigger reactive vaccination increases, the performance of hospital-level campaigns is greatly reduced; the impact of regional-level campaigns is variable, but tha

Journal article

Lison A, Banholzer N, Sharma M, Mindermann S, Unwin HJT, Mishra S, Stadler T, Bhatt S, Ferguson NM, Brauner J, Werner Vet al., 2023, Effectiveness assessment of non-pharmaceutical interventions: lessons learned from the COVID-19 pandemic, The Lancet Public Health, Vol: 8, Pages: e311-e317, ISSN: 2468-2667

Numerous studies have assessed the effectiveness of non-pharmaceutical interventions (NPIs), such as school closures and stay-at-home orders, during the COVID-19 pandemic. Such assessments can inform public health policy and contribute to evidence-based choices of NPIs during subsequentwaves or future epidemics. However, methodological issues and a lack of common standards have limited the practical value of the existing evidence. Based on our work and literature review, we discuss lessons learned from the COVID-19 pandemic and make recommendations for standardizing and improving assessment, data collection, and modeling. These recommendations can contribute to more reliable and policy-relevant assessments of NPI effectiveness during future epidemics.

Journal article

Johnson R, Djaafara B, Haw D, Doohan P, Forchini G, Pianella M, Ferguson N, Smith PC, Hauck KDet al., 2023, The societal value of SARS-CoV-2 booster vaccination in Indonesia, VACCINE, Vol: 41, Pages: 1885-1891, ISSN: 0264-410X

Journal article

Rawson T, Doohan P, Hauck K, Murray K, Ferguson Net al., 2023, Climate change and communicable diseases in the Gulf Cooperation Council (GCC) countries, Epidemics: the journal of infectious disease dynamics, Vol: 42, Pages: 1-6, ISSN: 1755-4365

A review of the extant literature reveals the extent to which the spread of communicable diseases will be significantly impacted by climate change. Specific research into how this will likely be observed in the countries of the Gulf Cooperation Council (GCC) is, however, greatly lacking. This report summarises the unique public health challenges faced by the GCC countries in the coming century, and outlines the need for greater investment in public health research and disease surveillance to better forecast the imminent epidemiological landscape. Significant data gaps currently exist regarding vector occurrence, spatial climate measures, and communicable disease case counts in the GCC — presenting an immediate research priority for the region. We outline policy work necessary to strengthen public health interventions, and to facilitate evidence-driven mitigation strategies. Such research will require a transdisciplinary approach, utilising existing cross-border public health initiatives, to ensure that such investigations are well-targeted and effectively communicated.

Journal article

Imai N, Rawson T, Knock E, Sonabend R, Elmaci Y, Perez-Guzman P, Whittles L, Thekke Kanapram D, Gaythorpe K, Hinsley W, Djaafara B, Wang H, Fraser K, Fitzjohn R, Hogan A, Doohan P, Ghani A, Ferguson N, Baguelin M, Cori Aet al., 2023, Quantifying the impact of delaying the second COVID-19 vaccine dose in England: a mathematical modelling study, The Lancet Public Health, Vol: 8, Pages: e174-e183, ISSN: 2468-2667

Background: The UK was the first country to start national COVID-19 vaccination programmes, initially administering doses 3-weeks apart. However, early evidence of high vaccine effectiveness after the first dose and the emergence of the Alpha variant prompted the UK to extend the interval between doses to 12-weeks. In this study, we aim to quantify the impact of delaying the second vaccine dose on the epidemic in England.Methods: We used a previously described model of SARS-CoV-2 transmission, calibrated to English COVID-19 surveillance data including hospital admissions, hospital occupancy, seroprevalence data, and population-level PCR testing data using a Bayesian evidence synthesis framework. We modelled and compared the epidemic trajectory assuming that vaccine doses were administered 3-weeks apart against the real reported vaccine roll-out schedule. We estimated and compared the resulting number of daily infections, hospital admissions, and deaths. Scenarios spanning a range of vaccine effectiveness and waning assumptions were investigated.Findings: We estimate that delaying the interval between the first and second COVID-19 vaccine doses from 3- to 12-weeks prevented an average 58,000 COVID-19 hospital admissions and 10,100 deaths between 8th December 2020 and 13th September 2021. Similarly, we estimate that the 3-week strategy would have resulted in more infections and deaths compared to the 12-week strategy. Across all sensitivity analyses the 3-week strategy resulted in a greater number of hospital admissions. Interpretation: England’s delayed second dose vaccination strategy was informed by early real-world vaccine effectiveness data and a careful assessment of the trade-offs in the context of limited vaccine supplies in a growing epidemic. Our study shows that rapidly providing partial (single dose) vaccine-induced protection to a larger proportion of the population was successful in reducing the burden of COVID-19 hospitalisations and deaths. Ther

Journal article

Unwin H, Cori A, Imai N, Gaythorpe K, Bhatia S, Cattarino L, Donnelly C, Ferguson N, Baguelin Met al., 2022, Using next generation matrices to estimate the proportion of infections that are not detected in an outbreak, Epidemics: the journal of infectious disease dynamics, Vol: 41, ISSN: 1755-4365

Contact tracing, where exposed individuals are followed up to break ongoing transmission chains, is a key pillar of outbreak response for infectious disease outbreaks. Unfortunately, these systems are not fully effective, and infections can still go undetected as people may not remember all their contacts or contacts may not be traced successfully. A large proportion of undetected infections suggests poor contact tracing and surveillance systems, which could be a potential area of improvement for a disease response. In this paper, we present a method for estimating the proportion of infections that are not detected during an outbreak. Our method uses next generation matrices that are parameterized by linked contact tracing data and case line-lists. We validate the method using simulated data from an individual-based model and then investigate two case studies: the proportion of undetected infections in the SARS-CoV-2 outbreak in New Zealand during 2020 and the Ebola epidemic in Guinea during 2014. We estimate that only 5.26% of SARS-CoV-2 infections were not detected in New Zealand during 2020 (95% credible interval: 0.243 – 16.0%) if 80% of contacts were under active surveillance but depending on assumptions about the ratio of contacts not under active surveillance versus contacts under active surveillance 39.0% or 37.7% of Ebola infections were not detected in Guinea (95% credible intervals: 1.69 – 87.0% or 1.70 – 80.9%).

Journal article

Echeverria-Londono S, Hartner A-M, Li X, Roth J, Portnoy A, Sbarra AN, Abbas K, Ferrari M, Fu H, Jit M, Ferguson NM, Gaythorpe KAMet al., 2022, Exploring the subnational inequality and heterogeneity of the impact of routine measles immunisation in Africa., Vaccine, Vol: 40, Pages: 6806-6817

Despite vaccination being one of the most effective public health interventions, there are persisting inequalities and inequities in immunisation. Understanding the differences in subnational vaccine impact can help improve delivery mechanisms and policy. We analyse subnational vaccination coverage of measles first-dose (MCV1) and estimate patterns of inequalities in impact, represented as deaths averted, across 45 countries in Africa. We also evaluate how much this impact would improve under more equitable vaccination coverage scenarios. Using coverage data for MCV1 from 2000-2019, we estimate the number of deaths averted at the first administrative level. We use the ratio of deaths averted per vaccination from two mathematical models to extrapolate the impact at a subnational level. Next, we calculate inequality for each country, measuring the spread of deaths averted across its regions, accounting for differences in population. Finally, using three more equitable vaccination coverage scenarios, we evaluate how much impact of MCV1 immunisation could improve by (1) assuming all regions in a country have at least national coverage, (2) assuming all regions have the observed maximum coverage; and (3) assuming all regions have at least 80% coverage. Our results show that progress in coverage and reducing inequality has slowed in the last decade in many African countries. Under the three scenarios, a significant number of additional deaths in children could be prevented each year; for example, under the observed maximum coverage scenario, global MCV1 coverage would improve from 76% to 90%, resulting in a further 363(95%CrI:299-482) deaths averted per 100,000 live births. This paper illustrates that estimates of the impact of MCV1 immunisation at a national level can mask subnational heterogeneity. We further show that a considerable number of deaths could be prevented by maximising equitable access in countries with high inequality when increasing the global coverage o

Journal article

Morgenstern C, Laydon D, Whittaker C, Mishra S, Haw D, Bhatt S, Ferguson Net al., 2022, The interaction of transmission intensity, mortality, and the economy: a retrospective analysis of the COVID-19 pandemic

<jats:title>Abstract</jats:title> <jats:p>The COVID-19 pandemic has caused over 6.4 million registered deaths to date, and has had a profound impact on economic activity. Here, we study the interaction of transmission, mortality, and the economy during the SARS-CoV-2 pandemic from January 2020 to December 2022 across 25 European countries. We adopt a Bayesian vector autoregressive model with both fixed and random effects. We find that increases in disease transmission intensity decreases Gross domestic product (GDP) and increases daily excess deaths, with a longer lasting impact on excess deaths in comparison to GDP, which recovers more rapidly. Broadly, our results reinforce the intuitive phenomenon that significant economic activity arises from diverse person-to-person interactions. We report on the effectiveness of non-pharmaceutical interventions (NPIs) on transmission intensity, excess deaths and changes in GDP, and resulting implications for policy makers. Our results highlight a complex cost-benefit trade off from individual NPIs. For example, banning international travel increases GDP however reduces excess deaths. We consider country random effects and their associations with excess changes in GDP and excess deaths. For example, more developed countries in Europe typically had more cautious approaches to the COVID-19 pandemic, prioritising healthcare and excess deaths over economic performance. Long term economic impairments are not fully captured by our model, as well as long term disease effects (Long Covid). Our results highlight that the impact of disease on a country is complex and multifaceted, and simple heuristic conclusions to extract the best outcome from the economy and disease burden are challenging.</jats:p>

Journal article

Hakki S, Zhou J, Jonnerby J, Singanayagam A, Barnett JL, Madon KJ, Koycheva A, Kelly C, Houston H, Nevin S, Fenn J, Kundu R, Crone MA, Pillay TD, Ahmad S, Derqui-Fernandez N, Conibear E, Freemont PS, Taylor GP, Ferguson N, Zambon M, Barclay WS, Dunning J, Lalvani A, ATACCC study investigatorset al., 2022, Onset and window of SARS-CoV-2 infectiousness and temporal correlation with symptom onset: a prospective, longitudinal, community cohort study, The Lancet Respiratory Medicine, Vol: 10, Pages: 1061-1073, ISSN: 2213-2600

BACKGROUND: Knowledge of the window of SARS-CoV-2 infectiousness is crucial in developing policies to curb transmission. Mathematical modelling based on scarce empirical evidence and key assumptions has driven isolation and testing policy, but real-world data are needed. We aimed to characterise infectiousness across the full course of infection in a real-world community setting. METHODS: The Assessment of Transmission and Contagiousness of COVID-19 in Contacts (ATACCC) study was a UK prospective, longitudinal, community cohort of contacts of newly diagnosed, PCR-confirmed SARS-CoV-2 index cases. Household and non-household exposed contacts aged 5 years or older were eligible for recruitment if they could provide informed consent and agree to self-swabbing of the upper respiratory tract. The primary objective was to define the window of SARS-CoV-2 infectiousness and its temporal correlation with symptom onset. We quantified viral RNA load by RT-PCR and infectious viral shedding by enumerating cultivable virus daily across the course of infection. Participants completed a daily diary to track the emergence of symptoms. Outcomes were assessed with empirical data and a phenomenological Bayesian hierarchical model. FINDINGS: Between Sept 13, 2020, and March 31, 2021, we enrolled 393 contacts from 327 households (the SARS-CoV-2 pre-alpha and alpha variant waves); and between May 24, 2021, and Oct 28, 2021, we enrolled 345 contacts from 215 households (the delta variant wave). 173 of these 738 contacts were PCR positive for more than one timepoint, 57 of which were at the start of infection and comprised the final study population. The onset and end of infectious viral shedding were captured in 42 cases and the median duration of infectiousness was 5 (IQR 3-7) days. Although 24 (63%) of 38 cases had PCR-detectable virus before symptom onset, only seven (20%) of 35 shed infectious virus presymptomatically. Symptom onset was a median of 3 days before both peak viral RNA and

Journal article

Mishra S, Scott JA, Laydon DJ, Zhu H, Ferguson NM, Bhatt S, Flaxman S, Gandy Aet al., 2022, Authors' reply to the discussion of 'A COVID-19 Model for Local Authorities of the United Kingdom' by Mishra et al. in Session 2 of the Royal Statistical Society's Special Topic Meeting on COVID-19 transmission: 11 June 2021, JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY, Vol: 185, Pages: S110-S111, ISSN: 0964-1998

Journal article

Mishra S, Scott JA, Laydon DJ, Zhu H, Ferguson NM, Bhatt S, Flaxman S, Gandy Aet al., 2022, A COVID-19 model for local authorities of the United Kingdom, JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY, Vol: 185, Pages: S86-S95, ISSN: 0964-1998

Journal article

Webster HH, Nyberg T, Sinnathamby MA, Aziz NA, Ferguson N, Seghezzo G, Blomquist PB, Bridgen J, Chand M, Groves N, Myers R, Hope R, Ashano E, Lopez-Bernal J, De Angelis D, Dabrera G, Presanis AM, Thelwall Set al., 2022, Hospitalisation and mortality risk of SARS-COV-2 variant omicron sub-lineage BA.2 compared to BA.1 in England, NATURE COMMUNICATIONS, Vol: 13

Journal article

Nyberg T, Ferguson NM, Blake J, Hinsley W, Bhatt S, De Angelis D, Thelwall S, Presanis AMet al., 2022, Misclassification bias in estimating clinical severity of SARS-CoV-2 variants - Authors' reply., Lancet, Vol: 400, Pages: 809-810

Journal article

Toor J, Li X, Jit M, Trotter CL, Echeverria-Londono S, Hartner A-M, Roth J, Portnoy A, Abbas K, Ferguson NM, Gaythorpe KAMet al., 2022, COVID-19 impact on routine immunisations for vaccine-preventable diseases: Projecting the effect of different routes to recovery, VACCINE, Vol: 40, Pages: 4142-4149, ISSN: 0264-410X

Journal article

Ahmed Ali H, Hartner A-M, Echeverria-Londono S, Roth J, Li X, Abbas K, Portnoy A, Vynnycky E, Woodruff K, Ferguson NM, Toor J, Gaythorpe KAMet al., 2022, Vaccine equity in low and middle income countries: a systematic review and meta-analysis (vol 21, 82, 2022), INTERNATIONAL JOURNAL FOR EQUITY IN HEALTH, Vol: 21

Journal article

Houston H, Hakki S, Pillay TD, Madon K, Derqui-Fernandez N, Koycheva A, Singanayagam A, Fenn J, Kundu R, Conibear E, Varro R, Cutajar J, Quinn V, Wang L, Narean JS, Tolosa-Wright MR, Barnett J, Kon OM, Tedder R, Taylor G, Zambon M, Ferguson N, Dunning J, Deeks JJ, Lalvani Aet al., 2022, Broadening symptom criteria improves early case identification in SARS-CoV-2 contacts, European Respiratory Journal, Vol: 60, Pages: 1-13, ISSN: 0903-1936

Background The success of case isolation and contact tracing for the control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission depends on the accuracy and speed of case identification. We assessed whether inclusion of additional symptoms alongside three canonical symptoms (CS), i.e. fever, cough and loss or change in smell or taste, could improve case definitions and accelerate case identification in SARS-CoV-2 contacts.Methods Two prospective longitudinal London (UK)-based cohorts of community SARS-CoV-2 contacts, recruited within 5 days of exposure, provided independent training and test datasets. Infected and uninfected contacts completed daily symptom diaries from the earliest possible time-points. Diagnostic information gained by adding symptoms to the CS was quantified using likelihood ratios and area under the receiver operating characteristic curve. Improvements in sensitivity and time to detection were compared with penalties in terms of specificity and number needed to test.Results Of 529 contacts within two cohorts, 164 (31%) developed PCR-confirmed infection and 365 (69%) remained uninfected. In the training dataset (n=168), 29% of infected contacts did not report the CS. Four symptoms (sore throat, muscle aches, headache and appetite loss) were identified as early-predictors (EP) which added diagnostic value to the CS. The broadened symptom criterion “≥1 of the CS, or ≥2 of the EP” identified PCR-positive contacts in the test dataset on average 2 days earlier after exposure (p=0.07) than “≥1 of the CS”, with only modest reduction in specificity (5.7%).Conclusions Broadening symptom criteria to include individuals with at least two of muscle aches, headache, appetite loss and sore throat identifies more infections and reduces time to detection, providing greater opportunities to prevent SARS-CoV-2 transmission.Tweetable abstract @ERSpublications

Journal article

Williams LR, Ferguson NM, Donnelly CA, Grassly NCet al., 2022, Measuring vaccine efficacy against infection and disease in clinical trials: sources and magnitude of bias in COVID-19 vaccine efficacy estimates, Clinical Infectious Diseases, Vol: 75, Pages: e764-e773, ISSN: 1058-4838

BACKGROUND: Phase III trials have estimated COVID-19 vaccine efficacy (VE) against symptomatic and asymptomatic infection. We explore the direction and magnitude of potential biases in these estimates and their implications for vaccine protection against infection and against disease in breakthrough infections. METHODS: We developed a mathematical model that accounts for natural and vaccine-induced immunity, changes in serostatus and imperfect sensitivity and specificity of tests for infection and antibodies. We estimated expected biases in VE against symptomatic, asymptomatic and any SARS͏CoV2 infections and against disease following infection for a range of vaccine characteristics and measurement approaches, and the likely overall biases for published trial results that included asymptomatic infections. RESULTS: VE against asymptomatic infection measured by PCR or serology is expected to be low or negative for vaccines that prevent disease but not infection. VE against any infection is overestimated when asymptomatic infections are less likely to be detected than symptomatic infections and the vaccine protects against symptom development. A competing bias towards underestimation arises for estimates based on tests with imperfect specificity, especially when testing is performed frequently. Our model indicates considerable uncertainty in Oxford-AstraZeneca ChAdOx1 and Janssen Ad26.COV2.S VE against any infection, with slightly higher than published, bias-adjusted values of 59.0% (95% uncertainty interval [UI] 38.4 to 77.1) and 70.9% (95% UI 49.8 to 80.7) respectively. CONCLUSIONS: Multiple biases are likely to influence COVID-19 VE estimates, potentially explaining the observed difference between ChAdOx1 and Ad26.COV2.S vaccines. These biases should be considered when interpreting both efficacy and effectiveness study results.

Journal article

Ali HA, Hartner A-M, Echeverria-Londono S, Roth J, Li X, Abbas K, Portnoy A, Vynnycky E, Woodruff K, Ferguson NM, Toor J, Gaythorpe KAMet al., 2022, Vaccine equity in low and middle income countries: a systematic review and meta-analysis, INTERNATIONAL JOURNAL FOR EQUITY IN HEALTH, Vol: 21

Journal article

Imai N, Gaythorpe K, Bhatia S, Mangal T, Cuomo-Dannenburg G, Unwin H, Jauneikaite E, Ferguson NMet al., 2022, COVID-19 in Japan, January – March 2020: insights from the first three months of the epidemic, BMC Infectious Diseases, Vol: 22, ISSN: 1471-2334

Background:Understanding the characteristics and natural history of novel pathogens is crucial to inform successful control measures. Japan was one of the first affected countries in the COVID-19 pandemic reporting their first case on 14 January 2020. Interventions including airport screening, contact tracing, and cluster investigations were quickly implemented. Here we present insights from the first 3 months of the epidemic in Japan based on detailed case data. Methods:We conducted descriptive analyses based on information systematically extracted from individual case reports from 13 January to 31 March 2020 including patient demographics, date of report and symptom onset, symptom progression, travel history, and contact type. We analysed symptom progression and estimated the time-varying reproduction number, Rt, correcting for epidemic growth using an established Bayesian framework. Key delays and the age-specific probability of transmission were estimated using data on exposures and transmission pairs. Results:The corrected fitted mean onset-to-reporting delay after the peak was 4 days (standard deviation: ±2 days). Early transmission was driven primarily by returning travellers with Rt peaking at 2.4 (95%CrI:1.6, 3.3) nationally. In the final week of the trusted period (16 – 23 March 2020), Rt accounting for importations diverged from overall Rt at 1.1 (95% CrI: 1.0, 1.2) compared to 1.5 (95% CrI: 1.3, 1.6) respectively. Household (39.0%) and workplace (11.6%) exposures were the most frequently reported potential source of infection. The estimated probability of transmission was assortative by age with individuals more likely to infect, and be infected by, contacts in a similar age group to them. Across all age groups, cases most frequently onset with cough, fever, and fatigue. There were no reported cases of patients <20 years old developing pneumonia or severe respiratory symptoms.Conclusions:Information collected in the early phases of an out

Journal article

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