Imperial College London

Professor Neil Ferguson

Faculty of MedicineSchool of Public Health

Vice-Dean (Academic Development)
 
 
 
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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

331 results found

Ciavarella C, Ferguson NM, 2021, Deriving fine-scale models of human mobility from aggregated origin-destination flow data, PLOS Computational Biology, Vol: 17, Pages: e1008588-e1008588

<jats:p>The spatial dynamics of epidemics are fundamentally affected by patterns of human mobility. Mobile phone call detail records (CDRs) are a rich source of mobility data, and allow semi-mechanistic models of movement to be parameterised even for resource poor settings. While the gravity model typically reproduces human movement reasonably well at the administrative level spatial scale, past studies suggest that parameter estimates vary with the level of spatial discretisation at which models are fitted. Given that privacy concerns usually preclude public release of very fine-scale movement data, such variation would be problematic for individual-based simulations of epidemic spread parametrised at a fine spatial scale. We therefore present new methods to fit fine-scale mathematical mobility models (here we implement variants of the gravity and radiation models) to spatially aggregated movement data and investigate how model parameter estimates vary with spatial resolution. We use gridded population data at 1km resolution to derive population counts at different spatial scales (down to ∼ 5km grids) and implement mobility models at each scale. Parameters are estimated from administrative-level flow data between overnight locations in Kenya and Namibia derived from CDRs: where the model spatial resolution exceeds that of the mobility data, we compare the flow data between a particular origin and destination with the sum of all model flows between cells that lie within those particular origin and destination administrative units. Clear evidence of over-dispersion supports the use of negative binomial instead of Poisson likelihood for count data with high values. Radiation models use fewer parameters than the gravity model and better predict trips between overnight locations for both considered countries. Results show that estimates for some parameters change between countries and with spatial resolution and highlight how imperfect flow data and spatial po

Journal article

McCabe R, Kont M, Schmit N, Whittaker C, Lochen A, Baguelin M, Knock E, Whittles L, Lees J, Brazeau N, Walker P, Ghani A, Ferguson N, White P, Donnelly C, Hauck K, Watson Oet al., 2021, Modelling ICU capacity under different epidemiological scenarios of the COVID-19 pandemic in three western European countries, International Journal of Epidemiology, ISSN: 0300-5771

Background: The coronavirus disease 2019 (COVID-19) pandemic has placed enormous strain on intensive care units (ICUs) in Europe. Ensuring access to care, irrespective of COVID-19 status, in winter 2020/21 is essential.Methods: An integrated model of hospital capacity planning and epidemiological projections of COVID-19 patients is used to estimate the demand for and resultant spare capacity of ICU beds, staff, and ventilators under different epidemic scenarios in France, Germany, and Italy across the 2020/21 winter period. The effect of implementing lockdowns triggered by different numbers of COVID-19 patients in ICU under varying levels of effectiveness is examined, using a ‘dual-demand’ (COVID-19 and non-COVID-19) patient model.Results: Without sufficient mitigation, we estimate that COVID-19 ICU patient numbers will exceed those seen in the first peak, resulting in substantial capacity deficits, with beds being consistently found to be the most constrained resource. Reactive lockdowns could lead to large improvements in ICU capacity during the winter season, with pressure being most effectively alleviated when lockdown is triggered early and sustained under a higher level of suppression. The success of such interventions also depends on baseline bed numbers and average non-COVID-19 patient occupancy.Conclusions: Reductions in capacity deficits under different scenarios must be weighed against the feasibility and drawbacks of further lockdowns. Careful, continuous decision-making by national policymakers will be required across the winter period 2020/21.

Journal article

Thompson H, Mousa A, Dighe A, Fu H, Arnedo-Pena A, Barrett P, Bellido-Blasco J, Bi Q, Caputi A, Chaw L, De Maria L, Hoffmann M, Mahapure K, Hg K, Raghuram J, Singh G, Soman B, Soriano V, Valent F, Vimercati L, En Wee L, Wong J, Ghani A, Ferguson Net al., 2021, SARS-CoV-2 setting-specific transmission rates: a systematic review and meta-analysis, Clinical Infectious Diseases, ISSN: 1058-4838

Background Understanding the drivers of SARS-CoV-2 transmission is crucial for control policies but evidence of transmission rates in different settings remains limited. MethodsWe conducted a systematic review to estimate secondary attack rates (SAR) and observed reproduction numbers (Robs) in different settings exploring differences by age, symptom status, and duration of exposure. To account for additional study heterogeneity, we employed a Beta-Binomial model to pool SARs across studies and a Negative-binomial model to estimate Robs. ResultsHouseholds showed the highest transmission rates, with a pooled SAR of 21.1% (95%CI:17.4%-24.8%). SARs were significantly higher where the duration of household exposure exceeded 5 days compared with exposure of ≤5 days. SARs related to contacts at social events with family and friends were higher than those for low-risk casual contacts (5.9% vs. 1.2%). Estimates of SAR and Robs for asymptomatic index cases were approximately a seventh, and for pre-symptomatic two thirds of those for symptomatic index cases. We found some evidence for reduced transmission potential both from and to individuals under 20 years of age in the household context, which is more limited when examining all settings.ConclusionsOur results suggest that exposure in settings with familiar contacts increases SARS-CoV-2 transmission potential. Additionally, the differences observed in transmissibility by index case symptom status and duration of exposure have important implications for control strategies such as contact tracing, testing and rapid isolation of cases. There was limited data to explore transmission patterns in workplaces, schools, and care-homes, highlighting the need for further research in such settings.

Journal article

Monod M, Blenkinsop A, Xi X, Hebert D, Bershan S, Tietze S, Baguelin M, Bradley VC, Chen Y, Coupland H, Filippi S, Ish-Horowicz J, McManus M, Mellan T, Gandy A, Hutchinson M, Unwin HJT, van Elsland SL, Vollmer MAC, Weber S, Zhu H, Bezancon A, Ferguson NM, Mishra S, Flaxman S, Bhatt S, Ratmann O, Imperial College COVID-19 Response Teamet al., 2021, Age groups that sustain resurging COVID-19 epidemics in the United States., Science

Following initial declines, in mid 2020 a resurgence in transmission of novel coronavirus disease (COVID-19) occurred in the US and Europe. As COVID19 disease control efforts are re-intensified, understanding the age demographics driving transmission and how these affect the loosening of interventions is crucial. We analyze aggregated, age-specific mobility trends from more than 10 million individuals in the US and link these mechanistically to age-specific COVID-19 mortality data. We estimate that as of October 2020, individuals aged 20-49 are the only age groups sustaining resurgent SARS-CoV-2 transmission with reproduction numbers well above one, and that at least 65 of 100 COVID-19 infections originate from individuals aged 20-49 in the US. Targeting interventions - including transmission-blocking vaccines - to adults aged 20-49 is an important consideration in halting resurgent epidemics and preventing COVID-19-attributable deaths.

Journal article

Li X, Mukandavire C, Cucunubá ZM, Echeverria Londono S, Abbas K, Clapham HE, Jit M, Johnson HL, Papadopoulos T, Vynnycky E, Brisson M, Carter ED, Clark A, de Villiers MJ, Eilertson K, Ferrari MJ, Gamkrelidze I, Gaythorpe KAM, Grassly NC, Hallett TB, Hinsley W, Jackson ML, Jean K, Karachaliou A, Klepac P, Lessler J, Li X, Moore SM, Nayagam S, Nguyen DM, Razavi H, Razavi-Shearer D, Resch S, Sanderson C, Sweet S, Sy S, Tam Y, Tanvir H, Tran QM, Trotter CL, Truelove S, van Zandvoort K, Verguet S, Walker N, Winter A, Woodruff K, Ferguson NM, Garske T, Vaccine Impact Modelling Consortiumet al., 2021, Estimating the health impact of vaccination against ten pathogens in 98 low-income and middle-income countries from 2000 to 2030: a modelling study., Lancet, Vol: 397, Pages: 398-408

BACKGROUND: The past two decades have seen expansion of childhood vaccination programmes in low-income and middle-income countries (LMICs). We quantify the health impact of these programmes by estimating the deaths and disability-adjusted life-years (DALYs) averted by vaccination against ten pathogens in 98 LMICs between 2000 and 2030. METHODS: 16 independent research groups provided model-based disease burden estimates under a range of vaccination coverage scenarios for ten pathogens: hepatitis B virus, Haemophilus influenzae type B, human papillomavirus, Japanese encephalitis, measles, Neisseria meningitidis serogroup A, Streptococcus pneumoniae, rotavirus, rubella, and yellow fever. Using standardised demographic data and vaccine coverage, the impact of vaccination programmes was determined by comparing model estimates from a no-vaccination counterfactual scenario with those from a reported and projected vaccination scenario. We present deaths and DALYs averted between 2000 and 2030 by calendar year and by annual birth cohort. FINDINGS: We estimate that vaccination of the ten selected pathogens will have averted 69 million (95% credible interval 52-88) deaths between 2000 and 2030, of which 37 million (30-48) were averted between 2000 and 2019. From 2000 to 2019, this represents a 45% (36-58) reduction in deaths compared with the counterfactual scenario of no vaccination. Most of this impact is concentrated in a reduction in mortality among children younger than 5 years (57% reduction [52-66]), most notably from measles. Over the lifetime of birth cohorts born between 2000 and 2030, we predict that 120 million (93-150) deaths will be averted by vaccination, of which 58 million (39-76) are due to measles vaccination and 38 million (25-52) are due to hepatitis B vaccination. We estimate that increases in vaccine coverage and introductions of additional vaccines will result in a 72% (59-81) reduction in lifetime mortality in the 2019 birth cohort. INTERPRETATION: In

Journal article

Sabino EC, Buss LF, Carvalho MPS, Prete CA, Crispim MAE, Fraiji NA, Pereira RHM, Parag KV, da Silva Peixoto P, Kraemer MUG, Oikawa MK, Salomon T, Cucunuba ZM, Castro MC, de Souza Santos AA, Nascimento VH, Pereira HS, Ferguson NM, Pybus OG, Kucharski A, Busch MP, Dye C, Faria NRet al., 2021, Resurgence of COVID-19 in Manaus, Brazil, despite high seroprevalence., Lancet

Journal article

Christen P, D'Aeth J, Lochen A, McCabe R, Rizmie D, Schmit N, Nayagam S, Miraldo M, Aylin P, Bottle A, Perez Guzman P, Donnelly C, Ghani A, Ferguson N, White P, Hauck Ket al., 2021, The J-IDEA pandemic planner: a framework for implementing hospital provision interventions during the COVID-19 pandemic, Medical Care, Pages: 1-8, ISSN: 0025-7079

Background : Planning for extreme surges in demand for hospital care of patientsrequiring urgent life-saving treatment for COVID-19, whilst retaining capacity for otheremergency conditions, is one of the most challenging tasks faced by healthcareproviders and policymakers during the pandemic. Health systems must be wellpreparedto cope with large and sudden changes in demand by implementinginterventions to ensure adequate access to care. We developed the first planning toolfor the COVID-19 pandemic to account for how hospital provision interventions (suchas cancelling elective surgery, setting up field hospitals, or hiring retired staff) will affectthe capacity of hospitals to provide life-saving care.Methods : We conducted a review of interventions implemented or considered in 12 European countries in March-April 2020, an evaluation of their impact on capacity, anda review of key parameters in the care of COVID-19 patients. This information wasused to develop a planner capable of estimating the impact of specific interventions ondoctors, nurses, beds and respiratory support equipment. We applied this to ascenario-based case study of one intervention, the set-up of field hospitals in England,under varying levels of COVID-19 patients.Results : The J-IDEA pandemic planner is a hospital planning tool that allows hospitaladministrators, policymakers and other decision-makers to calculate the amount ofcapacity in terms of beds, staff and crucial medical equipment obtained byimplementing the interventions. Flexible assumptions on baseline capacity, the numberof hospitalisations, staff-to-beds ratios, and staff absences due to COVID-19 make theplanner adaptable to multiple settings. The results of the case study show that whilefield hospitals alleviate the burden on the number of beds available, this intervention isfutile unless the deficit of critical care nurses is addressed first.Discussion : The tool supports decision-makers in delivering a fast and effectiveresponse to

Journal article

Lavezzo E, Franchin E, Ciavarella C, Cuomo-Dannenburg G, Barzon L, Del Vecchio C, Rossi L, Manganelli R, Loregian A, Navarin N, Abate D, Sciro M, Merigliano S, De Canale E, Vanuzzo MC, Besutti V, Saluzzo F, Onelia F, Pacenti M, Parisi SG, Carretta G, Donato D, Flor L, Cocchio S, Masi G, Sperduti A, Cattarino L, Salvador R, Nicoletti M, Caldart F, Castelli G, Nieddu E, Labella B, Fava L, Drigo M, Gaythorpe KAM, Brazzale AR, Toppo S, Trevisan M, Baldo V, Donnelly CA, Ferguson NM, Dorigatti I, Crisanti A, Crisanti Aet al., 2021, Suppression of a SARS-CoV-2 outbreak in the Italian municipality of Vo' (vol 584, pg 425, 2020), NATURE, ISSN: 0028-0836

Journal article

Nouvellet P, Bhatia S, Cori A, Ainslie K, Baguelin M, Bhatt S, Boonyasiri A, Brazeau N, Cattarino L, Cooper L, Coupland H, Cucunuba Perez Z, Cuomo-Dannenburg G, Dighe A, Djaafara A, Dorigatti I, Eales O, van Elsland S, NASCIMENTO F, Fitzjohn R, Gaythorpe K, Geidelberg L, green W, Hamlet A, Hauck K, Hinsley W, Imai N, Jeffrey, Jeffrey B, Knock E, Laydon D, Lees J, Mangal T, Mellan T, Nedjati Gilani G, Parag K, Pons Salort M, Ragonnet-Cronin M, Riley S, Unwin H, Verity R, Vollmer M, Volz E, Walker P, Walters C, Wang H, Watson O, Whittaker C, Whittles L, Xi X, Ferguson N, Donnelly Cet al., 2021, Reduction in mobility and COVID-19 transmission, Nature Communications, ISSN: 2041-1723

In response to the COVID-19 pandemic, countries have sought to control SARS-CoV-2 transmission by restricting population movement through social distancing interventions, thus reducing the number of contacts.Mobility data represent an important proxy measure of social distancing, and here, we characterise the relationship between transmission and mobility for 52 countries around the world.Transmission significantly decreased with the initial reduction in mobility in 73% of the countries analysed, but we found evidence of decoupling of transmission and mobility following the relaxation of strict control measures for 80% of countries. For the majority of countries, mobility explained a substantial proportion of the variation in transmissibility (median adjusted R-squared: 48%, interquartile range - IQR - across countries [27-77%]). Where a change in the relationship occurred, predictive ability decreased after the relaxation; from a median adjusted R-squared of 74% (IQR across countries [49-91%]) pre-relaxation, to a median adjusted R-squared of 30% (IQR across countries [12-48%]) post-relaxation.In countries with a clear relationship between mobility and transmission both before and after strict control measures were relaxed, mobility was associated with lower transmission rates after control measures were relaxed indicating that the beneficial effects of ongoing social distancing behaviours were substantial.

Journal article

Londono SE, Li X, Toor J, Villiers MJD, Nayagam S, Hallett TB, Abbas K, Jit M, Klepac P, Jean K, Garske T, Ferguson NM, Gaythorpe KAMet al., 2021, How can the public health impact of vaccination be estimated?

<jats:title>ABSTRACT</jats:title><jats:p>Deaths due to vaccine preventable diseases cause a notable proportion of mortality worldwide. To quantify the importance of vaccination, it is necessary to estimate the burden averted through vaccination. The Vaccine Impact Modelling Consortium (VIMC) was established to estimate the health impact of vaccination. We describe the methods implemented by the VIMC to estimate impact by calendar year, birth year and year of vaccination (YoV). The calendar and birth year methods estimate impact in a particular year and over the lifetime of a particular birth cohort, respectively. The YoV method estimates the impact of a particular year’s vaccination activities through the use of impact ratios which have no stratification and stratification by activity type and/or birth cohort. Furthermore, we detail an impact extrapolation (IE) method for use between coverage scenarios. We compare the methods, focusing on YoV for hepatitis B, measles and yellow fever. We find that the YoV methods estimate similar impact with routine vaccinations but have greater yearly variation when campaigns occur with the birth cohort stratification. The IE performs well for the YoV methods, providing a time-efficient mechanism for updates to impact estimates. These methods provide a robust set of approaches to quantify vaccination impact.</jats:p>

Journal article

Volz E, Mishra S, Chand M, Barrett JC, Johnson R, Geidelberg L, Hinsley WR, Laydon DJ, Dabrera G, OToole Á, Amato R, Ragonnet-Cronin M, Harrison I, Jackson B, Ariani CV, Boyd O, Loman N, McCrone JT, Gonc calves S, Jorgensen D, Myers R, Hill V, Jackson DK, Gaythorpe K, Groves N, Sillitoe J, Kwiatkowski DP, Flaxman S, Ratman O, Bhatt S, Hopkins S, Gandy A, Rambaut A, Ferguson NMet al., 2021, Transmission of SARS-CoV-2 Lineage B.1.1.7 in England: Insights from linking epidemiological and genetic data, Publisher: Cold Spring Harbor Laboratory Press

The SARS-CoV-2 lineage B.1.1.7, now designated Variant of Concern 202012/01 (VOC) by Public Health England, originated in the UK in late Summer to early Autumn 2020. We examine epidemiological evidence for this VOC having a transmission advantage from several perspectives. First, whole genome sequence data collected from community-based diagnostic testing provides an indication of changing prevalence of different genetic variants through time. Phylodynamic modelling additionally indicates that genetic diversity of this lineage has changed in a manner consistent with exponential growth. Second, 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. Third, we examine growth trends in SGTF and non-SGTF case numbers at local area level across England, and show that the VOC has higher transmissibility than non-VOC lineages, even if the VOC has a different latent period or generation time. Available SGTF data indicate a shift in the age composition of reported cases, with a larger share of under 20 year olds among reported VOC than non-VOC cases. Fourth, we assess the association of VOC frequency with independent estimates of the overall SARS-CoV-2 reproduction number through time. Finally, we fit a semi-mechanistic model directly to local VOC and non-VOC case incidence to estimate the reproduction numbers over time for each. There is a consensus among all analyses that the VOC has a substantial transmission advantage, with the estimated difference in reproduction numbers between VOC and non-VOC ranging between 0.4 and 0.7, and the ratio of reproduction numbers varying between 1.4 and 1.8. We note that these estimates of transmission advantage apply to a period where high levels of social distancing were in place in England; extrapolation to other transmission contexts therefore requires caution.Competing Interest StatementThe authors have declared

Working paper

Hamlet A, Gaythorpe KAM, Garske T, Ferguson NMet al., 2021, Seasonal and inter-annual drivers of yellow fever transmission in South America, PLOS NEGLECTED TROPICAL DISEASES, Vol: 15, ISSN: 1935-2735

Journal article

Verity R, Okell L, Dorigatti I, Winskill P, Whittaker C, Walker P, Donnelly C, Ferguson N, Ghani Aet al., 2021, COVID-19 and the difficulty of inferring epidemiological parameters from clinical data Reply, LANCET INFECTIOUS DISEASES, Vol: 21, Pages: 28-28, ISSN: 1473-3099

Journal article

Flaxman S, Mishra S, Scott J, Ferguson N, Gandy A, Bhatt Set al., 2020, The effect of interventions on COVID-19, NATURE, Vol: 588, Pages: E29-E32, ISSN: 0028-0836

Journal article

Knock E, Whittles L, Lees J, Perez Guzman P, Verity R, Fitzjohn R, Gaythorpe K, Imai N, Hinsley W, Okell L, Rosello A, Kantas N, Walters C, Bhatia S, Watson O, Whittaker C, Cattarino L, Boonyasiri A, Djaafara A, Fraser K, Fu H, Wang H, Xi X, Donnelly C, Jauneikaite E, Laydon D, White P, Ghani A, Ferguson N, Cori A, Baguelin Met al., 2020, Report 41: The 2020 SARS-CoV-2 epidemic in England: key epidemiological drivers and impact of interventions

England has been severely affected by COVID-19. We fitted a model of SARS-CoV-2 transmission in care homes and the community to regional 2020 surveillance data. Only national lockdown brought the reproduction number below 1 consistently; introduced one week earlier in the first wave it could have reduced mortality by 23,300 deaths on average. The mean infection fatality ratio was initially ~1.3% across all regions except London and halved following clinical care improvements. The infection fatality ratio was two-fold lower throughout in London, even when adjusting for demographics. The infection fatality ratio in care homes was 2.5-times that in the elderly in the community. Population-level infection-induced immunity in England is still far from herd immunity, with regional mean cumulative attack rates ranging between 4.4% and 15.8%.

Report

D'Aeth J, Ghosal S, Grimm F, Haw D, Koca E, Lau K, Moret S, Rizmie D, Deeny S, Perez Guzman P, Ferguson N, Hauck K, Smith P, Wiesemann W, Forchini G, Miraldo Met al., 2020, Report 40: Optimal scheduling rules for elective care to minimize years of life lost during the SARS-CoV-2 pandemic: an application to England

SummaryCountries have deployed a wide range of policies to prioritize patients to hospital care to address unprecedent surges in demand during the course of the pandemic. Those policies included postponing planned hospital care for non-emergency cases and rationing critical care.We develop a model to optimally schedule elective hospitalizations and allocate hospital general and critical care beds to planned and emergency patients in England during the pandemic. We apply the model to NHS England data and show that optimized scheduling leads to lower years of life lost and costs than policies that reflect those implemented in England during the pandemic. Overall across all disease areas the model enables an extra 50,750 - 5,891,608 years of life gained when compared to standard policies, depending on the scenarios. Especially large gains in years of life are seen for neoplasms, diseases of the digestive system, and injuries & poisoning.

Report

Unwin H, Mishra S, Bradley V, Gandy A, Mellan T, Coupland H, Ish-Horowicz J, Vollmer M, Whittaker C, Filippi S, Xi X, Monod M, Ratmann O, Hutchinson M, Valka F, Zhu H, Hawryluk I, Milton P, Ainslie K, Baguelin M, Boonyasiri A, Brazeau N, Cattarino L, Cucunuba Z, Cuomo-Dannenburg G, Dorigatti I, Eales O, Eaton J, van Elsland S, Fitzjohn R, Gaythorpe K, Green W, Hinsley W, Jeffrey B, Knock E, Laydon D, Lees J, Nedjati-Gilani G, Nouvellet P, Okell L, Parag K, Siveroni I, Thompson H, Walker P, Walters C, Watson O, Whittles L, Ghani A, Ferguson N, Riley S, Donnelly C, Bhatt S, Flaxman Set al., 2020, State-level tracking of COVID-19 in the United States, Nature Communications, ISSN: 2041-1723

As of 1st June 2020, the US Centers for Disease Control and Prevention reported 104,232 confirmed or probable COVID-19-related deaths in the US. This was more than twice the number of deaths reported in the next most severely impacted country. We jointly model the US epidemic at the state-level, using publicly available deathdata within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate the number of individuals that have been infected, the number of individuals that are currently infectious and the time-varying reproduction number (the average number of secondary infections caused by an infected person). We use changes in mobility to capture the impact that non-pharmaceutical interventions and other behaviour changes have on therate of transmission of SARS-CoV-2. We estimate thatRtwas only below one in 23 states on 1st June. We also estimate that 3.7% [3.4%-4.0%] of the total population of the US had been infected, with wide variation between states, and approximately 0.01% of the population was infectious. We demonstrate good 3 week model forecasts of deaths with low error and good coverage of our credible intervals.

Journal article

Grassly NC, Pons-Salort M, Parker EPK, White PJ, Ferguson NM, Imperial College COVID-19 Response Teamet al., 2020, Comparison of molecular testing strategies for COVID-19 control: a mathematical modelling study, Lancet Infectious Diseases, Vol: 20, Pages: 1381-1389, ISSN: 1473-3099

BACKGROUND: WHO has called for increased testing in response to the COVID-19 pandemic, but countries have taken different approaches and the effectiveness of alternative strategies is unknown. We aimed to investigate the potential impact of different testing and isolation strategies on transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: We developed a mathematical model of SARS-CoV-2 transmission based on infectiousness and PCR test sensitivity over time since infection. We estimated the reduction in the effective reproduction number (R) achieved by testing and isolating symptomatic individuals, regular screening of high-risk groups irrespective of symptoms, and quarantine of contacts of laboratory-confirmed cases identified through test-and-trace protocols. The expected effectiveness of different testing strategies was defined as the percentage reduction in R. We reviewed data on the performance of antibody tests reported by the Foundation for Innovative New Diagnostics and examined their implications for the use of so-called immunity passports. FINDINGS: If all individuals with symptoms compatible with COVID-19 self-isolated and self-isolation was 100% effective in reducing onwards transmission, self-isolation of symptomatic individuals would result in a reduction in R of 47% (95% uncertainty interval [UI] 32-55). PCR testing to identify SARS-CoV-2 infection soon after symptom onset could reduce the number of individuals needing to self-isolate, but would also reduce the effectiveness of self-isolation (around 10% would be false negatives). Weekly screening of health-care workers and other high-risk groups irrespective of symptoms by use of PCR testing is estimated to reduce their contribution to SARS-CoV-2 transmission by 23% (95% UI 16-40), on top of reductions achieved by self-isolation following symptoms, assuming results are available at 24 h. The effectiveness of test and trace depends strongly on coverage and the timelines

Journal article

Thompson H, Imai N, Dighe A, Ainslie K, Baguelin M, Bhatia S, Bhatt S, Boonyasiri A, Boyd O, Brazeau N, Cattarino L, Cooper L, Coupland H, Cucunuba Z, Cuomo-Dannenburg G, Djaafara B, Dorigatti I, van Elsland S, Fitzjohn R, Fu H, Gaythorpe K, Green W, Hallett T, Hamlet A, Haw D, Hayes S, Hinsley W, Jeffrey B, Knock E, Laydon D, Lees J, Mangal T, Mellan T, Mishra S, Mousa A, Nedjati-Gilani G, Nouvellet P, Okell L, Parag K, Ragonnet-Cronin M, Riley S, Unwin H, Verity R, Vollmer M, Volz E, Walker P, Walters C, Wang H, Wang Y, Watson O, Whittaker C, Whittles L, Winskill P, Xi X, Donnelly C, Ferguson Net al., 2020, SARS-CoV-2 infection prevalence on repatriation flights from Wuhan City, China, Journal of Travel Medicine, Vol: 27, Pages: 1-3, ISSN: 1195-1982

We estimated SARS-CoV-2 infection prevalence in cohorts of repatriated citizens from Wuhan to be 0.44% (95% CI: 0.19%–1.03%). Although not representative of the wider population we believe these estimates are helpful in providing a conservative estimate of infection prevalence in Wuhan City, China, in the absence of large-scale population testing early in the epidemic.

Journal article

Thompson H, Mousa A, Dighe A, Fu H, Arnedo-Pena A, Barrett P, Bellido-Blasco J, Bi Q, Caputi A, Chaw L, De Maria L, Hoffmann M, Mahapure K, Ng K, Raghuram J, Singh G, Soman B, Soriano V, Valent F, Vimercati L, En Wee L, Wong J, Ghani A, Ferguson Net al., 2020, Report 38: SARS-CoV-2 setting-specific transmission rates: a systematic review and meta-analysis

Since the end of 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly across the world. Understanding the drivers of SARS-CoV-2 transmission is crucial for disease control policies but evidence of transmission rates in different settings remains limited. We conducted a systematic review to estimate the secondary attack rate (SAR) and observed reproduction number (Robs) in different settings and to explore differences by age, symptom status, duration of exposure and household size. A total of 97 studies were identified, 45 of which met inclusion criteria for meta-analysis. Households showed the highest transmission rates, with pooled SAR and Robs estimates of 21.1% (95% CI: 17.4%-24.8%) and 0.96 (95% CI: 0.67-1.32), respectively. Household SAR estimates were significantly higher where the duration of household exposure exceeded 5 days compared with exposure of 5 days or less. Attack rates related to familiar and prolonged close contacts, such as social events with family and friends were higher than those related to low-risk casual contacts, such as strangers (SAR of 5.9%, 95% CI: 3.8%-8.1% vs. 1.2%, 95% CI: 0.3%-2.1%). Estimates of SAR for asymptomatic index cases were approximately two thirds of those for symptomatic index (3.5% vs. 12.8%, p<0.001). We find moderate evidence for less transmission both from and to individuals under 20 years of age in the household context, but this difference is less evident when examining all settings. Prolonged contact in households and in settings with familiar close contacts increases the potential for transmission of SARS-CoV-2. Additionally, the differences observed in transmissibility by symptom status of index cases and the potential for age-dependent effects has important implications for outbreak control strategies such as contact tracing, testing and rapid isolation of cases. There was limited data to allow exploration of transmission patterns in workplaces, schools, and care-homes, hig

Report

Mishra S, Scott J, Zhu H, Ferguson NM, Bhatt S, Flaxman S, Gandy Aet al., 2020, A COVID-19 Model for Local Authorities of the United Kingdom

<jats:title>Abstract</jats:title><jats:p>We propose a new framework to model the COVID-19 epidemic of the United Kingdom at the level of local authorities. The model fits within a general framework for semi-mechanistic Bayesian models of the epidemic, with some important innovations: we model the proportion of infections that result in reported deaths and cases as random variables. This is in contrast to standard frameworks that model the latent infection as a deterministic function of time varying reproduction number, <jats:italic>R</jats:italic><jats:sub><jats:italic>t</jats:italic></jats:sub>. The model is tailored and designed to be updated daily based on publicly available data. We envisage the model to be useful for now-casting and short-term projections of the epidemic as well as estimating historical trends. The model fits are available on a public website, <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://imperialcollegelondon.github.io/covid19local">https://imperialcollegelondon.github.io/covid19local</jats:ext-link>. The model is currently being used by the Scottish government in their decisions on interventions within Scotland [1, issue 24 to now].</jats:p>

Journal article

Gaythorpe K, Bhatia S, Mangal T, Unwin H, Imai N, Cuomo-Dannenburg G, Walters C, Jauneikaite E, Bayley H, Kont M, Mousa A, Whittles L, Riley S, Ferguson Net al., 2020, Report 37: Children’s role in the COVID-19 pandemic: a systematic review of early surveillance data on susceptibility, severity, and transmissibility

SARS-CoV-2 infections have been reported in all age groups including infants, children, and adolescents. However, the role of children in the COVID-19 pandemic is still uncertain. This systematic review of early studies synthesises evidence on the susceptibility of children to SARS-CoV-2 infection, the severity and clinical outcomes in children with SARS-CoV-2 infection, and the transmissibility of SARS-CoV-2 by children. A systematic literature review was conducted in PubMed. Reviewers extracted data from relevant, peer-reviewed studies published during the first wave of the SARS-CoV-2 outbreak using a standardised form and assessed quality using the NIH Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. For studies included in the meta-analysis, we used a random effects model to calculate pooled estimates of the proportion of children considered asymptomatic or in a severe or critical state. We identified 2,775 potential studies of which 128 studies met our inclusion criteria; data were extracted from 99, which were then quality assessed. Finally, 29 studies were considered for the meta-analysis that included information of symptoms and/or severity, these were further assessed based on patient recruitment. Our pooled estimate of the proportion of test positive children who were asymptomatic was 21.1% (95% CI: 14.0 - 28.1%), based on 13 included studies, and the proportion of children with severe or critical symptoms was 3.8% (95% CI: 1.5 - 6.0%), based on 14 included studies. We did not identify any studies designed to assess transmissibility in children and found that susceptibility to infection in children was highly variable across studies.Children’s susceptibility to infection and onward transmissibility relative to adults is still unclear and varied widely between studies. However, it is evident that most children experience clinically mild disease or remain asymptomatically infected. More comprehensive contact-tracing studie

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McCabe R, Kont M, Schmit N, Whittaker C, Lochen A, Baguelin M, Knock E, Whittles L, Lees J, Walker P, Ghani A, Ferguson N, White P, Donnelly C, Hauck K, Watson Oet al., 2020, Report 36: Modelling ICU capacity under different epidemiological scenarios of the COVID-19 pandemic in three western European countries

The coronavirus disease 2019 (COVID-19) pandemic has placed enormous strain on healthcare systems, particularly intensive care units (ICUs), with COVID-19 patient care being a key concern of healthcare system planning for winter 2020/21. Ensuring that all patients who require intensive care, irrespective of COVID-19 status, can access it during this time is essential. This study uses an integrated model of hospital capacity planning and epidemiological projections of COVID-19 patients to estimate the spare capacity of key ICU resources under different epidemic scenarios in France, Germany and Italy across the winter period of 2020/21. In particular, we examine the effect of implementing suppression strategies of varying effectiveness, triggered by different numbers of COVID-19 patients in ICU. The use of a ‘dual-demand’ (COVID-19 and non-COVID-19) patient model and the consideration of multiple ICU resources that determine capacity (beds, doctors, nurses and ventilators) and the interdependencies between them, provides a detailed insight into potential capacity constraints this winter. Without sufficient mitigation, we estimate that COVID-19 ICU patient numbers will exceed those seen in the first peak, resulting in substantial capacity deficits, with beds being consistently found to be the most constrained resource across countries. Lockdowns triggered based on ICU capacity could lead to large improvements in spare capacity during the winter season, with pressure being most effectively alleviated when lockdown is triggered early and implemented at a higher level of suppression. In many cases, maximum deficits are reduced to lower levels which can then be managed by expanding supply-side hospital capacity, to ensure that all patients can receive treatment. The success of such interventions also depends on baseline ICU bed numbers and average non-COVID-19 patient occupancy. We find that lockdowns of longer duration reduce the total number of days in defic

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Haw D, Forchini G, Christen P, Bajaj S, Hogan A, Winskill P, Miraldo M, White P, Ghani A, Ferguson N, Smith P, Hauck Ket al., 2020, Report 35: How can we keep schools and universities open? Differentiating closures by economic sector to optimize social and economic activity while containing SARS-CoV-2 transmission

There is a trade-off between the education sector and other economic sectors in the control of SARS-Cov-2 transmission. Here we integrate a dynamic model of SARS-CoV-2 transmission with a 63-sector economic model reflecting sectoral heterogeneity in transmission and economic interdependence between sectors. We identify COVID-19 control strategies which optimize economic production while keeping schools and universities operational and constraining infections such that emergency hospital capacity is not exceeded. The model estimates an economic gain of between £163bn and £205bn for the United Kingdom compared to a blanket lockdown of non-essential activity over six months, depending on hospital capacity. Sectors identified as potential priorities for closure are contact-intensive and/or less economically productive.

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Biggerstaff M, Cowling BJ, Cucunubá ZM, Dinh L, Ferguson NM, Gao H, Hill V, Imai N, Johansson MA, Kada S, Morgan O, Pastore y Piontti A, Polonsky JA, Prasad PV, Quandelacy TM, Rambaut A, Tappero JW, Vandemaele KA, Vespignani A, Warmbrod KL, Wong JYet al., 2020, Early insights from statistical and mathematical modeling of key epidemiologic parameters of COVID-19, Emerging Infectious Diseases, Vol: 26, ISSN: 1080-6040

We report key epidemiologic parameter estimates for coronavirus disease identified in peer-reviewed publications, preprint articles, and online reports. Range estimates for incubation period were 1.8–6.9 days, serial interval 4.0–7.5 days, and doubling time 2.3–7.4 days. The effective reproductive number varied widely, with reductions attributable to interventions. Case burden and infection fatality ratios increased with patient age. Implementation of combined interventions could reduce cases and delay epidemic peak up to 1 month. These parameters for transmission, disease severity, and intervention effectiveness are critical for guiding policy decisions. Estimates will likely change as new information becomes available.

Journal article

Okell LC, Verity R, Katzourakis A, Volz EM, Watson OJ, Mishra S, Walker P, Whittaker C, Donnelly CA, Riley S, Ghani AC, Gandy A, Flaxman S, Ferguson NM, Bhatt Set al., 2020, Host or pathogen-related factors in COVID-19 severity? Reply, LANCET, Vol: 396, Pages: 1397-1397, ISSN: 0140-6736

Journal article

Brazeau N, Verity R, Jenks S, Fu H, Whittaker C, Winskill P, Dorigatti I, Walker P, Riley S, Schnekenberg RP, Heltgebaum H, Mellan T, Mishra S, Unwin H, Watson O, Cucunuba Perez Z, Baguelin M, Whittles L, Bhatt S, Ghani A, Ferguson N, Okell Let al., 2020, Report 34: COVID-19 infection fatality ratio: estimates from seroprevalence

The infection fatality ratio (IFR) is a key statistic for estimating the burden of coronavirus disease 2019 (COVID-19) and has been continuously debated throughout the current pandemic. Previous estimates have relied on data early in the epidemic, or have not fully accounted for uncertainty in serological test characteristics and delays from onset of infection to seroconversion, death, and antibody waning. After screening 175 studies, we identified 10 representative antibody surveys to obtain updated estimates of the IFR using a modelling framework that addresses the limitations listed above. We inferred serological test specificity from regional variation within serosurveys, which is critical for correctly estimating the cumulative proportion infected when seroprevalence is still low. We find that age-specific IFRs follow an approximately log-linear pattern, with the risk of death doubling approximately every eight years of age. Using these age-specific estimates, we estimate the overall IFR in a typical low-income country, with a population structure skewed towards younger individuals, to be 0.23% (0.14-0.42 95% prediction interval range). In contrast, in a typical high income country, with a greater concentration of elderly individuals, we estimate the overall IFR to be 1.15% (0.78-1.79 95% prediction interval range). We show that accounting for seroreversion, the waning of antibodies leading to a negative serological result, can slightly reduce the IFR among serosurveys conducted several months after the first wave of the outbreak, such as Italy. In contrast, uncertainty in test false positive rates combined with low seroprevalence in some surveys can reconcile apparently low crude fatality ratios with the IFR in other countries. Unbiased estimates of the IFR continue to be critical to policymakers to inform key response decisions. It will be important to continue to monitor the IFR as new treatments are introduced. The code for reproducing these results are av

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Fu H, Wang H, Xi X, Boonyasiri A, Wang Y, Hinsley W, Fraser KJ, McCabe R, Olivera Mesa D, Skarp J, Ledda A, Dewé T, Dighe A, Winskill P, van Elsland SL, Ainslie KEC, Baguelin M, Bhatt S, Boyd O, Brazeau NF, Cattarino L, Charles G, Coupland H, Cucunubá ZM, Cuomo-Dannenburg G, Donnelly CA, Dorigatti I, Eales OD, Fitzjohn RG, Flaxman S, Gaythorpe KAM, Ghani AC, Green WD, Hamlet A, Hauck K, Haw DJ, Jeffrey B, Laydon DJ, Lees JA, Mellan T, Mishra S, Nedjati Gilani G, Nouvellet P, Okell L, Parag KV, Ragonnet-Cronin M, Riley S, Schmit N, Thompson HA, Unwin HJT, Verity R, Vollmer MAC, Volz E, Walker PGT, Walters CE, Waston OJ, Whittaker C, Whittles LK, Imai N, Bhatia S, Ferguson NMet al., 2020, A database for the epidemic trends and control measures during the first wave of COVID-19 in mainland China, International Journal of Infectious Diseases, ISSN: 1201-9712

Objectives: This data collation effort aims to provide a comprehensive database to describe the epidemic trends and responses during the first wave of coronavirus disease 2019 (COVID-19)across main provinces in China. Methods: From mid-January to March 2020, we extracted publicly available data on the spread and control of COVID-19 from 31 provincial health authorities and major media outlets in mainland China. Based on these data, we conducted a descriptive analysis of the epidemics in the six most-affected provinces. Results: School closures, travel restrictions, community-level lockdown, and contact tracing were introduced concurrently around late January but subsequent epidemic trends were different across provinces. Compared to Hubei, the other five most-affected provinces reported a lower crude case fatality ratio and proportion of critical and severe hospitalised cases. From March 2020, as local transmission of COVID-19 declined, switching the focus of measures to testing and quarantine of inbound travellers could help to sustain the control of the epidemic. Conclusions: Aggregated indicators of case notifications and severity distributions are essential for monitoring an epidemic. A publicly available database with these indicators and information on control measures provides useful source for exploring further research and policy planning for response to the COVID-19 epidemic.

Journal article

McCabe R, Schmit N, Christen P, D'Aeth J, Løchen A, Rizmie D, Nayagam AS, Miraldo M, Aylin P, Bottle R, Perez-Guzman PN, Ghani A, Ferguson N, White P, Hauck Ket al., 2020, Adapting hospital capacity to meet changing demands during the COVID-19 pandemic, BMC Medicine, Vol: 18, Pages: 1-12, ISSN: 1741-7015

BackgroundTo calculate hospital surge capacity, achieved via hospital provision interventions implemented for the emergency treatment of coronavirus disease 2019 (COVID-19) and other patients through March to May 2020; to evaluate the conditions for admitting patients for elective surgery under varying admission levels of COVID-19 patients.MethodsWe analysed National Health Service (NHS) datasets and literature reviews to estimate hospital care capacity before the pandemic (pre-pandemic baseline) and to quantify the impact of interventions (cancellation of elective surgery, field hospitals, use of private hospitals, deployment of former medical staff and deployment of newly qualified medical staff) for treatment of adult COVID-19 patients, focusing on general and acute (G&A) and critical care (CC) beds, staff and ventilators.ResultsNHS England would not have had sufficient capacity to treat all COVID-19 and other patients in March and April 2020 without the hospital provision interventions, which alleviated significant shortfalls in CC nurses, CC and G&A beds and CC junior doctors. All elective surgery can be conducted at normal pre-pandemic levels provided the other interventions are sustained, but only if the daily number of COVID-19 patients occupying CC beds is not greater than 1550 in the whole of England. If the other interventions are not maintained, then elective surgery can only be conducted if the number of COVID-19 patients occupying CC beds is not greater than 320. However, there is greater national capacity to treat G&A patients: without interventions, it takes almost 10,000 G&A COVID-19 patients before any G&A elective patients would be unable to be accommodated.ConclusionsUnless COVID-19 hospitalisations drop to low levels, there is a continued need to enhance critical care capacity in England with field hospitals, use of private hospitals or deployment of former and newly qualified medical staff to allow some or all elective surge

Journal article

Dighe A, Cattarino L, Cuomo-Dannenburg G, Skarp J, Imai N, Bhatia S, Gaythorpe K, Ainslie K, Baguelin M, Bhatt S, Boonyasiri A, Brazeau N, Cooper L, Coupland H, Cucunuba Perez Z, Dorigatti I, Eales O, van Elsland S, Fitzjohn R, Green W, Haw D, Hinsley W, Knock E, Laydon D, Mellan T, Mishra S, Nedjati Gilani G, Nouvellet P, Pons Salort M, Thompson H, Unwin H, Verity R, Vollmer M, Walters C, Watson O, Whittaker C, Whittles L, Ghani A, Donnelly C, Ferguson N, Riley Set al., 2020, Response to COVID-19 in South Korea and implications for lifting stringent interventions, BMC Medicine, Vol: 18, Pages: 1-12, ISSN: 1741-7015

Background After experiencing a sharp growth in COVID-19 cases early in the pandemic, South Korea rapidly controlled transmission while implementing less stringent national social distancing measures than countries in Europe and the US. This has led to substantial interest in their “test, trace, isolate” strategy. However, it is important to understand the epidemiological peculiarities of South Korea’s outbreak and characterise their response before attempting to emulate these measures elsewhere.MethodsWe systematically extracted numbers of suspected cases tested, PCR-confirmed cases, deaths, isolated confirmed cases, and numbers of confirmed cases with an identified epidemiological link from publicly available data. We estimated the time-varying reproduction number, Rt, using an established Bayesian framework, and reviewed the package of interventions implemented by South Korea using our extracted data, plus published literature and government sources. Results We estimated that after the initial rapid growth in cases, Rt dropped below one in early April before increasing to a maximum of 1.94 (95%CrI; 1.64-2.27) in May following outbreaks in Seoul Metropolitan Region. By mid-June Rt was back below one where it remained until the end of our study (July 13th). Despite less stringent “lockdown” measures, strong social distancing measures were implemented in high incidence areas and studies measured a considerable national decrease in movement in late-February. Testing capacity was swiftly increased, and protocols were in place to isolate suspected and confirmed cases quickly however we could not estimate the delay to isolation using our data. Accounting for just 10% of cases, individual case-based contact-tracing picked up a relatively minor proportion of total cases, with cluster investigations accounting for 66%. ConclusionsWhilst early adoption of testing and contact-tracing are likely to be important for South Korea’s successf

Journal article

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