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

299 results found

Gaythorpe KA, Hamlet A, Cibrelus L, Garske T, Ferguson NMet al., 2020, The effect of climate change on yellow fever disease burden in Africa., Elife, Vol: 9

Yellow Fever (YF) is an arbovirus endemic in tropical regions of South America and Africa and it is estimated to cause 78,000 deaths a year in Africa alone. Climate change may have substantial effects on the transmission of YF and we present the first analysis of the potential impact on disease burden. We extend an existing model of YF transmission to account for rainfall and a temperature suitability index and project transmission intensity across the African endemic region in the context of four climate change scenarios. We use these transmission projections to assess the change in burden in 2050 and 2070. We find disease burden changes heterogeneously across the region. In the least severe scenario, we find a 93.0%[95%CI(92.7, 93.2%)] chance that annual deaths will increase in 2050. This change in epidemiology will complicate future control efforts. Thus, we may need to consider the effect of changing climatic variables on future intervention strategies.

Journal article

Perez Guzman PN, Daunt A, Mukherjee S, Crook P, Forlano R, Kont M, Lochen A, Vollmer M, Middleton P, Judge R, Harlow C, Soubieres A, Cooke G, White PJ, Hallett T, Aylin P, Ferguson N, Hauck K, Thursz M, Nayagam Set al., Clinical characteristics and predictors of outcomes of hospitalized patients with COVID-19 in a multi-ethnic London NHS Trust: a retrospective cohort study, Clinical Infectious Diseases, ISSN: 1058-4838

Background: Emerging evidence suggests ethnic minorities are disproportionatelyaffected by COVID-19. Detailed clinical analyses of multi-cultural hospitalized patientcohorts remain largely undescribed.Methods: We performed regression, survival andcumulative competing risk analyses to evaluate factors associated with mortality inpatients admitted for COVID-19 in three large London hospitals between February 25and April 5, censored as of May 1, 2020.Results: Of 614 patients (median age 69years, (IQR 25) and 62% male), 381 (62%) had been discharged alive, 178 (29%)died and 55 (9%) remained hospitalized at censoring. Severe hypoxemia (aOR 4.25,95%CI 2.36-7.64), leukocytosis (aOR 2.35, 95%CI 1.35-4.11), thrombocytopenia (aOR1.01, 95%CI 1.00-1.01, increase per 10x9decrease), severe renal impairment (aOR5.14, 95%CI 2.65-9.97), and low albumin (aOR 1.06, 95%CI 1.02-1.09, increase per gdecrease) were associated with death. Forty percent (244) were from black, Asian andother minority ethnic (BAME) groups, 38% (235) white and for 22% (135) ethnicity wasunknown. BAME patients were younger and had fewer comorbidities. Whilst theunadjusted odds of death did not differ by ethnicity, when adjusting for age, sex andcomorbidities, black patients were at higher odds of death compared to whites (aOR1.69, 95%CI 1.00-2.86). This association was stronger when further adjusting foradmission severity (aOR 1.85 95% CI 1.06-3.24). Conclusions: BAME patients were over-represented in our cohort and, whenaccounting for demographic and clinical profile of admission, black patients were atincreased odds of death. Further research is needed into biologic drivers of differencesin COVID-19 outcomes by ethnicity.

Journal article

Candido DS, Claro IM, de Jesus JG, Souza WM, Moreira FRR, Dellicour S, Mellan TA, du Plessis L, Pereira RHM, Sales FCS, Manuli ER, Thézé J, Almeida L, Menezes MT, Voloch CM, Fumagalli MJ, Coletti TM, da Silva CAM, Ramundo MS, Amorim MR, Hoeltgebaum HH, Mishra S, Gill MS, Carvalho LM, Buss LF, Prete CA, Ashworth J, Nakaya HI, Peixoto PS, Brady OJ, Nicholls SM, Tanuri A, Rossi ÁD, Braga CKV, Gerber AL, de C Guimarães AP, Gaburo N, Alencar CS, Ferreira ACS, Lima CX, Levi JE, Granato C, Ferreira GM, Francisco RS, Granja F, Garcia MT, Moretti ML, Perroud MW, Castiñeiras TMPP, Lazari CS, Hill SC, de Souza Santos AA, Simeoni CL, Forato J, Sposito AC, Schreiber AZ, Santos MNN, de Sá CZ, Souza RP, Resende-Moreira LC, Teixeira MM, Hubner J, Leme PAF, Moreira RG, Nogueira ML, Brazil-UK Centre for Arbovirus Discovery, Diagnosis, Genomics and Epidemiology CADDE Genomic Network, Ferguson NM, Costa SF, Proenca-Modena JL, Vasconcelos ATR, Bhatt S, Lemey P, Wu C-H, Rambaut A, Loman NJ, Aguiar RS, Pybus OG, Sabino EC, Faria NRet al., 2020, Evolution and epidemic spread of SARS-CoV-2 in Brazil., Science

Brazil currently has one of the fastest growing SARS-CoV-2 epidemics in the world. Owing to limited available data, assessments of the impact of non-pharmaceutical interventions (NPIs) on virus spread remain challenging. Using a mobility-driven transmission model, we show that NPIs reduced the reproduction number from >3 to 1-1.6 in São Paulo and Rio de Janeiro. Sequencing of 427 new genomes and analysis of a geographically representative genomic dataset identified >100 international virus introductions in Brazil. We estimate that most (76%) of the Brazilian strains fell in three clades that were introduced from Europe between 22 February11 March 2020. During the early epidemic phase, we found that SARS-CoV-2 spread mostly locally and within-state borders. After this period, despite sharp decreases in air travel, we estimated multiple exportations from large urban centers that coincided with a 25% increase in average travelled distances in national flights. This study sheds new light on the epidemic transmission and evolutionary trajectories of SARS-CoV-2 lineages in Brazil, and provide evidence that current interventions remain insufficient to keep virus transmission under control in the country.

Journal article

Grassly NC, Pons Salort M, Parker EPK, White PJ, Ferguson NM, Imperial College COVID-19 Response Teamet al., Role of molecular testing in COVID-19 control: a mathematical modelling study, Lancet Infectious Diseases, ISSN: 1473-3099

Background: The World Health Organization has called for increased testing in response to COVID-19, but countries have taken different approaches and the effectiveness of alternative strategies is unknown. 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 reproduction number (R) achieved by testing and isolating symptomatic individuals, regular screening of high-risk groups irrespective of symptoms,and quarantine of contacts identified through ‘test-and-trace’ protocols. We reviewed data on the performance of antibody tests reported by the Foundation for Innovative New Diagnostics and examined the potential of ‘immunity passports’. Results: Weekly screening of healthcare workers and other high-riskgroups irrespective of symptoms using PCR is estimated to reduce their contribution to transmissionby 23% (95% uncertainty interval: 16-40%), on top of reductions achieved by self-isolation following symptoms, assuming results are available at 24 hours. The effectiveness of test-and-trace depends strongly on coverage and the timeliness of contact tracing, potentially reducing R by26% (14-35%) if 80% of cases and contactsare identified and there is immediate testing on symptom onset and quarantine of contacts within 24 hours. Immunity passports based on tests for antibody or infection face significant technical, legal and ethical challenges. Interpretation: PCR and antibody testing can play a critical role in prevention of SARS-CoV-2 transmission, especially among healthcare workers and other high-risk groups,but no single strategy will reduce R below 1 at current levels of population immunity.

Journal article

Fu H, Xi X, Wang H, Boonyasiri A, Wang Y, Hinsley W, Fraser K, McCabe R, Olivera Mesa D, Skarp J, Ledda A, Dewe T, Dighe A, Winskill P, van Elsland S, Ainslie K, Baguelin M, Bhatt S, Boyd O, Brazeau N, Cattarino L, Charles G, Coupland H, Cucunuba Perez Z, Cuomo-Dannenburg G, Donnelly C, Dorigatti I, Green W, Hamlet A, Hauck K, Haw D, Jeffrey B, Laydon D, Lees J, Mellan T, Mishra S, Nedjati Gilani G, Nouvellet P, Okell L, Parag K, Ragonnet-Cronin M, Riley S, Schmit N, Thompson H, Unwin H, Verity R, Vollmer M, Volz E, Walker P, Walters C, Watson O, Whittaker C, Whittles L, Imai N, Bhatia S, Ferguson Net al., 2020, Report 30: The COVID-19 epidemic trends and control measures in mainland China

Report

Vollmer M, Radhakrishnan S, Kont M, Flaxman S, Bhatt S, Costelloe C, Honeyford C, Aylin P, Cooke G, Redhead J, White P, Ferguson N, Hauck K, Nayagam AS, Perez Guzman PNet al., 2020, Report 29: The impact of the COVID-19 epidemic on all-cause attendances to emergency departments in two large London hospitals: an observational study

The health care system in England has been highly affected by the surge in demand due to patients afflicted by COVID-19. Yet the impact of the pandemic on the care seeking behaviour of patients and thus on Emergency department (ED) services is unknown, especially for non-COVID-19 related emergencies. In this report, we aimed to assess how the reorganisation of hospital care and admission policies to respond to the COVID-19 epidemic affected ED attendances and emergency hospital admissions. We performed time-series analyses of present year vs historic (2015-2019) trends of ED attendances between March 12 and May 31 at two large central London hospitals part of Imperial College Healthcare NHS Trust (ICHNT) and compared these to regional and national trends. Historic attendances data to ICHNT and publicly available NHS situation reports were used to calibrate time series auto-regressive integrated moving average (ARIMA) forecasting models. We thus predicted the (conterfactual) expected number of ED attendances between March 12 (when the first public health measure leading to lock-down started in England) to May 31, 2020 (when the analysis was censored) at ICHNT, at all acute London Trusts and nationally. The forecasted trends were compared to observed data for the same periods of time. Lastly, we analysed the trends at ICHNT disaggregating by mode of arrival, distance from postcode of patient residence to hospital and primary diagnosis amongst those that were subsequently admitted to hospital and compared these data to an average for the same period of time in the years 2015 to 2019.During the study period (January 1 to May 31, 2020) there was an overall decrease in ED attendances of 35% at ICHNT, of 50% across all London NHS Trusts and 53% nationally. For ICHNT, the decrease in attendances was mainly amongst those aged younger than 65 and those arriving by their own means (e.g. personal or public transport). Increasing distance (km) from postcode of residence to hospi

Report

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 S, 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, Imperial College COVID-19 Response Team, Brazzale AR, Toppo S, Trevisan M, Baldo V, Donnelly CA, Ferguson NM, Dorigatti I, Crisanti Aet al., 2020, Suppression of a SARS-CoV-2 outbreak in the Italian municipality of Vo'., Nature, ISSN: 0028-0836

On the 21st of February 2020 a resident of the municipality of Vo', a small town near Padua, died of pneumonia due to SARS-CoV-2 infection1. This was the first COVID-19 death detected in Italy since the emergence of SARS-CoV-2 in the Chinese city of Wuhan, Hubei province2. In response, the regional authorities imposed the lockdown of the whole municipality for 14 days3. We collected information on the demography, clinical presentation, hospitalization, contact network and presence of SARS-CoV-2 infection in nasopharyngeal swabs for 85.9% and 71.5% of the population of Vo' at two consecutive time points. On the first survey, which was conducted around the time the town lockdown started, we found a prevalence of infection of 2.6% (95% confidence interval (CI) 2.1-3.3%). On the second survey, which was conducted at the end of the lockdown, we found a prevalence of 1.2% (95% Confidence Interval (CI) 0.8-1.8%). Notably, 42.5% (95% CI 31.5-54.6%) of the confirmed SARS-CoV-2 infections detected across the two surveys were asymptomatic (i.e. did not have symptoms at the time of swab testing and did not develop symptoms afterwards). The mean serial interval was 7.2 days (95% CI 5.9-9.6). We found no statistically significant difference in the viral load of symptomatic versus asymptomatic infections (p-values 0.62 and 0.74 for E and RdRp genes, respectively, Exact Wilcoxon-Mann-Whitney test). This study sheds new light on the frequency of asymptomatic SARS-CoV-2 infection, their infectivity (as measured by the viral load) and provides new insights into its transmission dynamics and the efficacy of the implemented control measures.

Journal article

Okell LC, Verity R, Watson OJ, Mishra S, Walker P, Whittaker C, Katzourakis A, Donnelly CA, Riley S, Ghani AC, Gandy A, Flaxman S, Ferguson NM, Bhatt Set al., 2020, Have deaths from COVID-19 in Europe plateaued due to herd immunity?, Lancet, Vol: 395, Pages: e110-e111

Journal article

Forchini G, Lochen A, Hallett T, Aylin P, White P, Donnelly C, Ghani A, Ferguson N, Hauck Ket al., 2020, Report 28: Excess non-COVID-19 deaths in England and Wales between 29th February and 5th June 2020

There were 189,403 deaths from any cause reported in England from 29th February to 5th June 2020 inclusive, and 11,278 all-cause deaths in Wales over the same period. Of those deaths, 44,736 (23.6%) registered COVID-19 on the death certificate in England, and 2,294 (20.3%) in Wales, while 144,667 (76.4%) were not recorded as having been due to COVID-19 in England, and 8,984 (79.7%) in Wales. However, it could be that some of the ‘non-COVID-19’ deaths have in fact also been caused by COVID-19, either as the direct cause of death, or indirectly through provisions for the pandemic impeding access to care for other conditions. There is uncertainty in how many of the non-COVID-19 deaths were directly or indirectly caused by the pandemic. We estimated the excess deaths that were not recorded as associated with COVID-19 in the death certificate (excess non-COVID-19 deaths) as the deaths for which COVID-19 was not reported as the cause, compared to those we would have expected to occur had the pandemic not happened. Expected deaths were forecast with an analysis of historic trends in deaths between 2010 and April 2020 using data by the Office of National Statistics and a statistical time series model. According to the model, we expected 136,294 (95% CI 133,882 - 138,696) deaths in England, and 8,983 (CI 8,051 - 9,904) in Wales over this period, significantly fewer than the number of deaths reported. This means that there were 8,983 (95% CI 5,971 - 10,785) total excess non-COVID-19 deaths in England. For every 100 COVID-19 deaths during the period from 29th February to 5th June 2020 there were between 13 and 24 cumulative excess non-COVID-19 deaths. The proportion of cumulative excess non-COVID-19 deaths of all reported deaths during this period was 4.4% (95% CI 3.2% - 5.7%) in England, with small regional variations. Excess deaths were highest in the South East at 2,213 (95% CI 327 - 4,047) and in London at 1,937 (95% CI 896 - 3,010), respectively. There is no e

Report

Hogan A, Jewell B, Sherrard-Smith E, Watson O, Whittaker C, Hamlet A, Smith J, Winskill P, Verity R, Baguelin M, Lees J, Whittles L, Ainslie K, Bhatt S, Boonyasiri A, Brazeau N, Cattarino L, Cooper L, Coupland H, Cuomo-Dannenburg G, Dighe A, Djaafara A, Donnelly C, Eaton J, van Elsland S, Fitzjohn R, Fu H, Gaythorpe K, Green W, Haw D, Hayes S, Hinsley W, Imai N, Laydon D, Mangal T, Mellan T, Mishra S, Parag K, Thompson H, Unwin H, Vollmer M, Walters C, Wang H, Ferguson N, Okell L, Churcher T, Arinaminpathy N, Ghani A, Walker P, Hallett Tet al., 2020, Potential impact of the COVID-19 pandemic on HIV, TB and malaria in low- and middle-income countries: A Modelling Study, The Lancet Global Health, ISSN: 2214-109X

Background: COVID-19 has the potential to cause substantial disruptions to health services, including by cases overburdening the health system or response measures limiting usual programmatic activities. We aimed to quantify the extent to which disruptions in services for human immunodeficiency virus (HIV), tuberculosis (TB) and malaria in low- and middle-income countries with high burdens of those disease could lead to additional loss of life. Methods: We constructed plausible scenarios for the disruptions that could be incurred during the COVID-19 pandemic and used established transmission models for each disease to estimate the additional impact on health that could be caused in selected settings.Findings: In high burden settings, HIV-, TB- and malaria-related deaths over five years may increase by up to 10%, 20% and 36%, respectively, compared to if there were no COVID-19 pandemic. We estimate the greatest impact on HIV to be from interruption to antiretroviral therapy, which may occur during a period of high health system demand. For TB, we estimate the greatest impact is from reductions in timely diagnosis and treatment of new cases, which may result from any prolonged period of COVID-19 suppression interventions. We estimate that the greatest impact on malaria burden could come from interruption of planned net campaigns. These disruptions could lead to loss of life-years over five years that is of the same order of magnitude as the direct impact from COVID-19 in places with a high burden of malaria and large HIV/TB epidemics.Interpretation: Maintaining the most critical prevention activities and healthcare services for HIV, TB and malaria could significantly reduce the overall impact of the COVID-19 pandemic.Funding: Bill & Melinda Gates Foundation, The Wellcome Trust, DFID, MRC

Journal article

Bhatia S, Imai N, Cuomo-Dannenburg G, Baguelin M, Boonyasiri A, Cori A, Cucunuba Perez Z, Dorigatti I, Fitzjohn R, Fu H, Gaythorpe K, Ghani A, Hamlet A, Hinsley W, Laydon D, Nedjati Gilani G, Okell L, Riley S, Thompson H, van Elsland S, Volz E, Wang H, Wang Y, Whittaker C, Xi X, Donnelly CA, Ferguson NMet al., 2020, Estimating the number of undetected COVID-19 cases among travellers from mainland China, Publisher: F1000 Research Ltd

Background: Since the start of the COVID-19 epidemic in late 2019, there have been more than 152 affected regions and countries with over 110,000 confirmed cases outside mainland China.Methods: We analysed COVID-19 cases among travellers from mainland China to different regions and countries, comparing the region- and country-specific rates of detected and confirmed cases per flight volume to estimate the relative sensitivity of surveillance in different regions and countries.Results: Although travel restrictions from Wuhan City and other cities across China may have reduced the absolute number of travellers to and from China, we estimated that more than two thirds (70%, 95% CI: 54% - 80%, compared to Singapore; 75%, 95% CI: 66% - 82%, compared to multiple countries) of cases exported from mainland China have remained undetected.Conclusions: These undetected cases potentially resulted in multiple chains of human-to-human transmission outside mainland China.

Working paper

McCabe R, Schmit N, Christen P, D'Aeth J, Lochen A, Rizmie D, Nayagam AS, Miraldo M, Aylin P, Bottle R, Perez Guzman PN, Ghani A, Ferguson N, White PJ, Hauck Ket al., 2020, Report 27 Adapting hospital capacity to meet changing demands during the COVID-19 pandemic

To meet the growing demand for hospital care due to the COVID-19 pandemic, England implemented a range of hospital provision interventions including the procurement of equipment, the establishment of additional hospital facilities and the redeployment of staff and other resources. Additionally, to further release capacity across England’s National Health Service (NHS), elective surgery was cancelled in March 2020, leading to a backlog of patients requiring care. This created a pressure on the NHS to reintroduce elective procedures, which urgently needs to be addressed. Population-level measures implemented in March and April 2020 reduced transmission of SARS-CoV-2, prompting a gradual decline in the demand for hospital care by COVID-19 patients after the peak in mid-April. Planning capacity to bring back routine procedures for non-COVID-19 patients whilst maintaining the ability to respond to any potential future increases in demand for COVID-19 care is the challenge currently faced by healthcare planners.In this report, we aim to calculate hospital capacity for emergency treatment of COVID-19 and other patients during the pandemic surge in April and May 2020; to evaluate the increase in capacity achieved via five interventions (cancellation of elective surgery, field hospitals, use of private hospitals, and deployment of former and newly qualified medical staff); and to determine how to re-introduce elective surgery considering continued demand from COVID-19 patients. We do this by modelling the supply of acute NHS hospital care, considering different capacity scenarios, namely capacity before the pandemic (baseline scenario) and after the implementation of capacity expansion interventions that impact available general and acute (G&A) and critical care (CC) beds, staff and ventilators. Demand for hospital care is accounted for in terms of non-COVID-19 and COVID-19 patients. Our results suggest that NHS England would not have had sufficient daily capacity

Report

Walker PGT, Whittaker C, Watson OJ, Baguelin M, Winskill P, Hamlet A, Djafaara BA, Cucunubá Z, Olivera Mesa D, Green W, Thompson H, Nayagam S, Ainslie KEC, Bhatia S, Bhatt S, Boonyasiri A, Boyd O, Brazeau NF, Cattarino L, Cuomo-Dannenburg G, Dighe A, Donnelly CA, Dorigatti I, van Elsland SL, FitzJohn R, Fu H, Gaythorpe KAM, Geidelberg L, Grassly N, Haw D, Hayes S, Hinsley W, Imai N, Jorgensen D, Knock E, Laydon D, Mishra S, Nedjati-Gilani G, Okell LC, Unwin HJ, Verity R, Vollmer M, Walters CE, Wang H, Wang Y, Xi X, Lalloo DG, Ferguson NM, Ghani ACet al., 2020, The impact of COVID-19 and strategies for mitigation and suppression in low- and middle-income countries, Science, Vol: 369, Pages: 413-422, ISSN: 0036-8075

The ongoing COVID-19 pandemic poses a severe threat to public health worldwide. We combine data on demography, contact patterns, disease severity, and health care capacity and quality to understand its impact and inform strategies for its control. Younger populations in lower income countries may reduce overall risk but limited health system capacity coupled with closer inter-generational contact largely negates this benefit. Mitigation strategies that slow but do not interrupt transmission will still lead to COVID-19 epidemics rapidly overwhelming health systems, with substantial excess deaths in lower income countries due to the poorer health care available. Of countries that have undertaken suppression to date, lower income countries have acted earlier. However, this will need to be maintained or triggered more frequently in these settings to keep below available health capacity, with associated detrimental consequences for the wider health, well-being and economies of these countries.

Journal article

Flaxman S, Mishra S, Gandy A, Unwin HJT, Mellan TA, Coupland H, Whittaker C, Zhu H, Berah T, Eaton JW, Monod M, Perez Guzman PN, Schmit N, Cilloni L, Ainslie K, Baguelin M, Boonyasiri A, Boyd O, Cattarino L, Cucunuba Perez Z, Cuomo-Dannenburg G, Dighe A, Djaafara A, Dorigatti I, van Elsland S, Fitzjohn R, Gaythorpe K, Geidelberg L, Grassly N, Green W, Hallett T, Hamlet A, Hinsley W, Jeffrey B, Knock E, Laydon D, Nedjati Gilani G, Nouvellet P, Parag K, Siveroni I, Thompson H, Verity R, Volz E, Walters C, Wang H, Watson O, Winskill P, Xi X, Walker P, Ghani AC, Donnelly CA, Riley SM, Vollmer MAC, Ferguson NM, Okell LC, Bhatt Set al., 2020, Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe, Nature, ISSN: 0028-0836

Following the emergence of a novel coronavirus1 (SARS-CoV-2) and its spread outside of China, Europe has experienced large epidemics. In response, many European countries have implemented unprecedented non-pharmaceutical interventions such as closure of schools and national lockdowns. We study the impact of major interventions across 11 European countries for the period from the start of COVID-19 until the 4th of May 2020 when lockdowns started to be lifted. Our model calculates backwards from observed deaths to estimate transmission that occurred several weeks prior, allowing for the time lag between infection and death. We use partial pooling of information between countries with both individual and shared effects on the reproduction number. Pooling allows more information to be used, helps overcome data idiosyncrasies, and enables more timely estimates. Our model relies on fixed estimates of some epidemiological parameters such as the infection fatality rate, does not include importation or subnational variation and assumes that changes in the reproduction number are an immediate response to interventions rather than gradual changes in behavior. Amidst the ongoing pandemic, we rely on death data that is incomplete, with systematic biases in reporting, and subject to future consolidation. We estimate that, for all the countries we consider, current interventions have been sufficient to drive the reproduction number Rt below 1 (probability Rt< 1.0 is 99.9%) and achieve epidemic control. We estimate that, across all 11 countries, between 12 and 15 million individuals have been infected with SARS-CoV-2 up to 4th May, representing between 3.2% and 4.0% of the population. Our results show that major non-pharmaceutical interventions and lockdown in particular have had a large effect on reducing transmission. Continued intervention should be considered to keep transmission of SARS-CoV-2 under control.

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, Nscimento F, Fitzjohn R, Gaythorpe K, Geidelberg L, Grassly N, Green W, Hamlet A, Hauck K, Hinsley W, Imai N, 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., 2020, Report 26: Reduction in mobility and COVID-19 transmission

In response to the COVID-19 pandemic, countries have sought to control transmission of SARS-CoV-2by restricting population movement through social distancing interventions, reducing the number ofcontacts.Mobility data represent an important proxy measure of social distancing. Here, we develop aframework to infer the relationship between mobility and the key measure of population-level diseasetransmission, the reproduction number (R). The framework is applied to 53 countries with sustainedSARS-CoV-2 transmission based on two distinct country-specific automated measures of humanmobility, Apple and Google mobility data.For both datasets, the relationship between mobility and transmission was consistent within andacross countries and explained more than 85% of the variance in the observed variation intransmissibility. We quantified country-specific mobility thresholds defined as the reduction inmobility necessary to expect a decline in new infections (R<1).While social contacts were sufficiently reduced in France, Spain and the United Kingdom to controlCOVID-19 as of the 10th of May, we find that enhanced control measures are still warranted for themajority of countries. We found encouraging early evidence of some decoupling of transmission andmobility in 10 countries, a key indicator of successful easing of social-distancing restrictions.Easing social-distancing restrictions should be considered very carefully, as small increases in contactrates are likely to risk resurgence even where COVID-19 is apparently under control. Overall, strongpopulation-wide social-distancing measures are effective to control COVID-19; however gradualeasing of restrictions must be accompanied by alternative interventions, such as efficient contacttracing, to ensure control.

Report

Ferguson N, Nedjati Gilani G, Laydon D, 2020, CovidSim Report 9 - Main UK runs for Imperial Report 9 Tables 3,4,5 and A1

The directory report9 contains files to allow the results tables in the Imperial College Report 9 - Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand to be reproduced. The report can be downloaded from here https://www.imperial.ac.uk/mrc-global-infectious-disease-analysis/covid-19/report-9-impact-of-npis-on-covid-19/ or from Spiral https://spiral.imperial.ac.uk/handle/10044/1/77482 This directory has received a CODECHECK certificate 2020-010 https://doi.org/10.5281/zenodo.3865491) The COVID-19 CovidSim Model can be accessed at https://github.com/mrc-ide/covid-sim

Software

Verity R, Okell LC, Dorigatti I, Winskill P, Whittaker C, Imai N, Cuomo-Dannenburg G, Thompson H, Walker PGT, Fu H, Dighe A, Griffin JT, Baguelin M, Bhatia S, Boonyasiri A, Cori A, Cucunubá Z, FitzJohn R, Gaythorpe K, Green W, Hamlet A, Hinsley W, Laydon D, Nedjati-Gilani G, Riley S, van Elsland S, Volz E, Wang H, Wang Y, Xi X, Donnelly CA, Ghani AC, Ferguson NMet al., 2020, Estimates of the severity of coronavirus disease 2019: a model-based analysis., Lancet Infectious Diseases, Vol: 20, Pages: 669-677, ISSN: 1473-3099

BACKGROUND: In the face of rapidly changing data, a range of case fatality ratio estimates for coronavirus disease 2019 (COVID-19) have been produced that differ substantially in magnitude. We aimed to provide robust estimates, accounting for censoring and ascertainment biases. METHODS: We collected individual-case data for patients who died from COVID-19 in Hubei, mainland China (reported by national and provincial health commissions to Feb 8, 2020), and for cases outside of mainland China (from government or ministry of health websites and media reports for 37 countries, as well as Hong Kong and Macau, until Feb 25, 2020). These individual-case data were used to estimate the time between onset of symptoms and outcome (death or discharge from hospital). We next obtained age-stratified estimates of the case fatality ratio by relating the aggregate distribution of cases to the observed cumulative deaths in China, assuming a constant attack rate by age and adjusting for demography and age-based and location-based under-ascertainment. We also estimated the case fatality ratio from individual line-list data on 1334 cases identified outside of mainland China. Using data on the prevalence of PCR-confirmed cases in international residents repatriated from China, we obtained age-stratified estimates of the infection fatality ratio. Furthermore, data on age-stratified severity in a subset of 3665 cases from China were used to estimate the proportion of infected individuals who are likely to require hospitalisation. FINDINGS: Using data on 24 deaths that occurred in mainland China and 165 recoveries outside of China, we estimated the mean duration from onset of symptoms to death to be 17·8 days (95% credible interval [CrI] 16·9-19·2) and to hospital discharge to be 24·7 days (22·9-28·1). In all laboratory confirmed and clinically diagnosed cases from mainland China (n=70 117), we estimated a crude case fatality ratio (adjusted for cen

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, Boyd O, Brazeau N, Charles G, Cooper L, Coupland H, Cucunuba Perez Z, Djaafara A, Dorigatti I, Eales O, Eaton J, van Elsland S, Ferreira Do Nascimento F, Fitzjohn R, Flaxman S, Fraser K, Geidelberg L, Green W, Hallett T, Hamlet A, Hauck K, Haw D, Hinsley W, Jeffrey B, Knock E, Laydon D, Lees J, Mellan T, Mishra S, Nedjati Gilani G, Nouvellet P, Okell L, Parag K, Pons Salort M, Ragonnet-Cronin M, Thompson H, Unwin H, Verity R, Whittaker C, Whittles L, Xi X, Ghani A, Donnelly C, Ferguson N, Riley Set al., 2020, Report 25: Response to COVID-19 in South Korea and implications for lifting stringent interventions, 25

While South Korea experienced a sharp growth in COVID-19 cases early in the global pandemic, it has since rapidly reduced rates of infection and now maintains low numbers of daily new cases. Despite using less stringent “lockdown” measures than other affected countries, strong social distancing measures have been advised in high incidence areas and a 38% national decrease in movement occurred voluntarily between February 24th - March 1st. Suspected and confirmed cases were isolated quickly even during the rapid expansion of the epidemic and identification of the Shincheonji cluster. South Korea swiftly scaled up testing capacity and was able to maintain case-based interventions throughout. However, individual case-based contact tracing, not associated with a specific cluster, was a relatively minor aspect of their control program, with cluster investigations accounting for a far higher proportion of cases: the underlying epidemic was driven by a series of linked clusters, with 48% of all cases in the Shincheonji cluster and 20% in other clusters. Case-based contacts currently account for only 11% of total cases. The high volume of testing and low number of deaths suggests that South Korea experienced a small epidemic of infections relative to other countries. Therefore, caution is needed in attempting to duplicate the South Korean response in settings with larger more generalized epidemics. Finding, testing and isolating cases that are linked to clusters may be more difficult in such settings.

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Jeffrey B, Walters C, Ainslie K, Eales O, Ciavarella C, Bhatia S, Hayes S, Baguelin M, Boonyasiri A, Brazeau N, Cuomo-Dannenburg G, Fitzjohn R, Gaythorpe K, Green W, Imai N, Mellan T, Mishra S, Nouvellet P, Unwin H, Verity R, Vollmer M, Whittaker C, Ferguson N, Donnelly C, Riley Set al., 2020, Report 24: Mobility data from mobile phones suggests that initial compliance with COVID-19 social distancing interventions was high and geographically consistent across the UK, 24

Since early March 2020, the COVID-19 epidemic across the United Kingdom has led to a range of socialdistancing policies, which have resulted in reduced mobility across different regions. Crowd level dataon mobile phone usage can be used as a proxy for actual population mobility patterns and provide away of quantifying the impact of social distancing measures on changes in mobility. Here, we use twomobile phone-based datasets (anonymised and aggregated crowd level data from O2 and from theFacebook app on mobile phones) to assess changes in average mobility, both overall and broken downinto high and low population density areas, and changes in the distribution of journey lengths. Weshow that there was a substantial overall reduction in mobility with the most rapid decline on the 24thMarch 2020, the day after the Prime Minister’s announcement of an enforced lockdown. Thereduction in mobility was highly synchronized across the UK. Although mobility has remained low since26th March 2020, we detect a gradual increase since that time. We also show that the two differentdatasets produce similar trends, albeit with some location-specific differences. We see slightly largerreductions in average mobility in high-density areas than in low-density areas, with greater variationin mobility in the high-density areas: some high-density areas eliminated almost all mobility. We areonly able to observe populations living in locations where sufficient number of people use Facebookor a device connected to the relevant provider’s network such that no individual is identifiable. Theseanalyses form a baseline with which to monitor changes in behaviour in the UK as social distancing iseased.

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Verity R, Okell L, Dorigatti I, Winskill P, Whittaker C, Walker P, Donnelly C, Ferguson N, Ghani Aet al., 2020, COVID-19 and the difficulty of inferring epidemiological parameters from clinical data - Authors' reply., Lancet Infect Dis

Journal article

Unwin H, Mishra S, Bradley VC, Gandy A, Vollmer M, Mellan T, Coupland H, Ainslie K, Whittaker C, Ish-Horowicz J, Filippi S, Xi X, Monod M, Ratmann O, Hutchinson M, Valka F, Zhu H, Hawryluk I, Milton P, Baguelin M, Boonyasiri A, Brazeau N, Cattarino L, Charles G, Cooper L, Cucunuba Perez Z, Cuomo-Dannenburg G, Djaafara A, Dorigatti I, Eales O, Eaton J, van Elsland S, Fitzjohn R, Gaythorpe K, Green W, Hallett T, Hinsley W, Imai N, Jeffrey B, Knock E, Laydon D, Lees J, Nedjati Gilani G, Nouvellet P, Okell L, Ower A, Parag K, Siveroni I, Thompson H, Verity R, Walker P, Walters C, Wang Y, Watson O, Whittles L, Ghani A, Ferguson N, Riley S, Donnelly C, Bhatt S, Flaxman Set al., 2020, Report 23: State-level tracking of COVID-19 in the United States

our estimates show that the percentage of individuals that have been infected is 4.1% [3.7%-4.5%], with widevariation between states. For all states, even for the worst affected states, we estimate that less than a quarter of thepopulation has been infected; in New York, for example, we estimate that 16.6% [12.8%-21.6%] of individuals have beeninfected to date. Our attack rates for New York are in line with those from recent serological studies [1] broadly supportingour choice of infection fatality rate.There is variation in the initial reproduction number, which is likely due to a range of factors; we find a strong associationbetween the initial reproduction number with both population density (measured at the state level) and the chronologicaldate when 10 cumulative deaths occurred (a crude estimate of the date of locally sustained transmission).Our estimates suggest that the epidemic is not under control in much of the US: as of 17 May 2020 the reproductionnumber is above the critical threshold (1.0) in 24 [95% CI: 20-30] states. Higher reproduction numbers are geographicallyclustered in the South and Midwest, where epidemics are still developing, while we estimate lower reproduction numbersin states that have already suffered high COVID-19 mortality (such as the Northeast). These estimates suggest that cautionmust be taken in loosening current restrictions if effective additional measures are not put in place.We predict that increased mobility following relaxation of social distancing will lead to resurgence of transmission, keepingall else constant. We predict that deaths over the next two-month period could exceed current cumulative deathsby greater than two-fold, if the relationship between mobility and transmission remains unchanged. Our results suggestthat factors modulating transmission such as rapid testing, contact tracing and behavioural precautions are crucial to offsetthe rise of transmission associated with loosening of social distancing. Overall, we

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Winskill P, Whittaker C, Walker P, Watson O, Laydon D, Imai N, Cuomo-Dannenburg G, Ainslie K, Baguelin M, Bhatt S, Boonyasiri A, Cattarino L, Ciavarella C, Cooper L, Coupland H, Cucunuba Perez Z, van Elsland S, Fitzjohn R, Flaxman S, Gaythorpe K, Green W, Hallett T, Hamlet A, Hinsley W, Knock E, Lees J, Mellan T, Mishra S, Nedjati Gilani G, Nouvellet P, Okell L, Parag K, Thompson H, Unwin H, Wang Y, Whittles L, Xi X, Ferguson N, Donnelly C, Ghani Aet al., 2020, Report 22: Equity in response to the COVID-19 pandemic: an assessment of the direct and indirect impacts on disadvantaged and vulnerable populations in low- and lower middle-income countries, 22

The impact of the COVID-19 pandemic in low-income settings is likely to be more severe due to limited healthcare capacity. Within these settings, however, there exists unfair or avoidable differences in health among different groups in society – health inequities – that mean that some groups are particularly at risk from the negative direct and indirect consequences of COVID-19. The structural determinants of these are often reflected in differences by income strata, with the poorest populations having limited access to preventative measures such as handwashing. Their more fragile income status will also mean that they are likely to be employed in occupations that are not amenable to social-distancing measures, thereby further reducing their ability to protect themselves from infection. Furthermore, these populations may also lack access to timely healthcare on becoming ill. We explore these relationships by using large-scale household surveys to quantify the differences in handwashing access, occupation and hospital access with respect to wealth status in low-income settings. We use a COVID-19 transmission model to demonstrate the impact of these differences. Our results demonstrate clear trends that the probability of death from COVID-19 increases with increasing poverty. On average, we estimate a 32.0% (2.5th-97.5th centile 8.0%-72.5%) increase in the probability of death in the poorest quintile compared to the wealthiest quintile from these three factors alone. We further explore how risk mediators and the indirect impacts of COVID-19 may also hit these same disadvantaged and vulnerable the hardest. We find that larger, inter-generational households that may hamper efforts to protect the elderly if social distancing are associated with lower-income countries and, within LMICs, lower wealth status. Poorer populations are also more susceptible to food security issues - with these populations having the highest levels under-nourishment whilst also being

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Mellan T, Hoeltgebaum H, Mishra S, Whittaker C, Schnekenberg R, Gandy A, Unwin H, Vollmer M, Coupland H, Hawryluk I, Rodrigues Faria N, Vesga J, Zhu H, Hutchinson M, Ratmann O, Monod M, Ainslie K, Baguelin M, Bhatia S, Boonyasiri A, Brazeau N, Charles G, Cooper L, Cucunuba Perez Z, Cuomo-Dannenburg G, Dighe A, Djaafara A, Eaton J, van Elsland S, Fitzjohn R, Fraser K, Gaythorpe K, Green W, Hayes S, Imai N, Jeffrey B, Knock E, Laydon D, Lees J, Mangal T, Mousa A, Nedjati Gilani G, Nouvellet P, Olivera Mesa D, Parag K, Pickles M, Thompson H, Verity R, Walters C, Wang H, Wang Y, Watson O, Whittles L, Xi X, Okell L, Dorigatti I, Walker P, Ghani A, Riley S, Ferguson N, Donnelly C, Flaxman S, Bhatt Set al., 2020, Report 21: Estimating COVID-19 cases and reproduction number in Brazil

Brazil is an epicentre for COVID-19 in Latin America. In this report we describe the Brazilian epidemicusing three epidemiological measures: the number of infections, the number of deaths and the reproduction number. Our modelling framework requires sufficient death data to estimate trends, and wetherefore limit our analysis to 16 states that have experienced a total of more than fifty deaths. Thedistribution of deaths among states is highly heterogeneous, with 5 states—São Paulo, Rio de Janeiro,Ceará, Pernambuco and Amazonas—accounting for 81% of deaths reported to date. In these states, weestimate that the percentage of people that have been infected with SARS-CoV-2 ranges from 3.3% (95%CI: 2.8%-3.7%) in São Paulo to 10.6% (95% CI: 8.8%-12.1%) in Amazonas. The reproduction number (ameasure of transmission intensity) at the start of the epidemic meant that an infected individual wouldinfect three or four others on average. Following non-pharmaceutical interventions such as school closures and decreases in population mobility, we show that the reproduction number has dropped substantially in each state. However, for all 16 states we study, we estimate with high confidence that thereproduction number remains above 1. A reproduction number above 1 means that the epidemic isnot yet controlled and will continue to grow. These trends are in stark contrast to other major COVID19 epidemics in Europe and Asia where enforced lockdowns have successfully driven the reproductionnumber below 1. While the Brazilian epidemic is still relatively nascent on a national scale, our resultssuggest that further action is needed to limit spread and prevent health system overload.

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Jean K, Hamlet A, Benzler J, Cibrelus L, Gaythorpe KAM, Sall A, Ferguson NM, Garske Tet al., 2020, Eliminating yellow fever epidemics in Africa: Vaccine demand forecast and impact modelling, PLoS Neglected Tropical Diseases, Vol: 14, Pages: 1-16, ISSN: 1935-2727

BackgroundTo counter the increasing global risk of Yellow fever (YF), the World Health Organisation initiated the Eliminate Yellow fever Epidemics (EYE) strategy. Estimating YF burden, as well as vaccine impact, while accounting for the features of urban YF transmission such as indirect benefits of vaccination, is key to informing this strategy.Methods and findingsWe developed two model variants to estimate YF burden in sub-Saharan Africa, assuming all infections stem from either the sylvatic or the urban cycle of the disease. Both relied on an ecological niche model fitted to the local presence of any YF reported event in 34 African countries. We calibrated under-reporting using independent estimates of transmission intensity provided by 12 serological surveys performed in 11 countries. We calculated local numbers of YF infections, deaths and disability-adjusted life years (DALYs) lost based on estimated transmission intensity while accounting for time-varying vaccination coverage. We estimated vaccine demand and impact of future preventive mass vaccination campaigns (PMVCs) according to various vaccination scenarios.Vaccination activities conducted in Africa between 2005 and 2017 were estimated to prevent from 3.3 (95% CI 1.2–7.7) to 6.1 (95% CI 2.4–13.2) millions of deaths over the lifetime of vaccinees, representing extreme scenarios of none or maximal herd effects, respectively. By prioritizing provinces based on the risk of urban YF transmission in future PMVCs, an average of 37.7 million annual doses for PMVCs over eight years would avert an estimated 9,900,000 (95% CI 7,000,000–13,400,000) infections and 480,000 (180,000–1,140,000) deaths over the lifetime of vaccinees, corresponding to 1.7 (0.7–4.1) deaths averted per 1,000 vaccine doses.ConclusionsBy estimating YF burden and vaccine impact over a range of spatial and temporal scales, while accounting for the specificity of urban transmission, our model can be used to inform th

Journal article

Vollmer M, Mishra S, Unwin H, Gandy A, Melan T, Bradley V, Zhu H, Coupland H, Hawryluk I, Hutchinson M, Ratmann O, Monod M, Walker P, Whittaker C, Cattarino L, Ciavarella C, Cilloni L, Ainslie K, Baguelin M, Bhatia S, Boonyasiri A, Brazeau N, Charles G, Cooper L, Cucunuba Perez Z, Cuomo-Dannenburg G, Dighe A, Djaafara A, Eaton J, van Elsland S, Fitzjohn R, Gaythorpe K, Green W, Hayes S, Imai N, Jeffrey B, Knock E, Laydon D, Lees J, Mangal T, Mousa A, Nedjati Gilani G, Nouvellet P, Olivera Mesa D, Parag K, Pickles M, Thompson H, Verity R, Walters C, Wang H, Wang Y, Watson O, Whittles L, Xi X, Ghani A, Riley S, Okell L, Donnelly C, Ferguson N, Dorigatti I, Flaxman S, Bhatt Set al., 2020, Report 20: A sub-national analysis of the rate of transmission of Covid-19 in Italy

Italy was the first European country to experience sustained local transmission of COVID-19. As of 1st May 2020, the Italian health authorities reported 28; 238 deaths nationally. To control the epidemic, the Italian government implemented a suite of non-pharmaceutical interventions (NPIs), including school and university closures, social distancing and full lockdown involving banning of public gatherings and non essential movement. In this report, we model the effect of NPIs on transmission using data on average mobility. We estimate that the average reproduction number (a measure of transmission intensity) is currently below one for all Italian regions, and significantly so for the majority of the regions. Despite the large number of deaths, the proportion of population that has been infected by SARS-CoV-2 (the attack rate) is far from the herd immunity threshold in all Italian regions, with the highest attack rate observed in Lombardy (13.18% [10.66%-16.70%]). Italy is set to relax the currently implemented NPIs from 4th May 2020. Given the control achieved by NPIs, we consider three scenarios for the next 8 weeks: a scenario in which mobility remains the same as during the lockdown, a scenario in which mobility returns to pre-lockdown levels by 20%, and a scenario in which mobility returns to pre-lockdown levels by 40%. The scenarios explored assume that mobility is scaled evenly across all dimensions, that behaviour stays the same as before NPIs were implemented, that no pharmaceutical interventions are introduced, and it does not include transmission reduction from contact tracing, testing and the isolation of confirmed or suspected cases. We find that, in the absence of additional interventions, even a 20% return to pre-lockdown mobility could lead to a resurgence in the number of deaths far greater than experienced in the current wave in several regions. Future increases in the number of deaths will lag behind the increase in transmission intensity and so a

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Hogan A, Jewell B, Sherrard-Smith E, Vesga J, Watson O, Whittaker C, Hamlet A, Smith J, Ainslie K, Baguelin M, Bhatt S, Boonyasiri A, Brazeau N, Cattarino L, Charles G, Cooper L, Coupland H, Cuomo-Dannenburg G, Dighe A, Djaafara A, Donnelly C, Dorigatti I, Eaton J, van Elsland S, Fitzjohn R, Fu H, Gaythorpe K, Green W, Haw D, Hayes S, Hinsley W, Imai N, Knock E, Laydon D, Lees J, Mangal T, Mellan T, Mishra S, Nedjati Gilani G, Nouvellet P, Okell L, Ower A, Parag K, Pickles M, Stopard I, Thompson H, Unwin H, Verity R, Vollmer M, Walters C, Wang H, Wang Y, Whittles L, Winskill P, Xi X, Ferguson N, Churcher T, Arinaminpathy N, Ghani A, Walker P, Hallett Tet al., 2020, Report 19: The potential impact of the COVID-19 epidemic on HIV, TB and malaria in low- and middle-income countries

COVID-19 has the potential to cause disruptions to health services in different ways; through the health system becoming overwhelmed with COVID-19 patients, through the intervention used to slow transmission of COVID-19 inhibiting access to preventative interventions and services, and through supplies of medicine being interrupted. We aim to quantify the extent to which such disruptions in services for HIV, TB and malaria in high burden low- and middle-income countries could lead to additional loss of life. In high burden settings, HIV, TB and malaria related deaths over 5 years may be increased by up to 10%, 20% and 36%, respectively, compared to if there were no COVID-19 epidemic. We estimate the greatest impact on HIV to be from interruption to ART, which may occur during a period of high or extremely high health system demand; for TB, we estimate the greatest impact is from reductions in timely diagnosis and treatment of new cases, which may result from a long period of COVID-19 suppression interventions; for malaria, we estimate that the greatest impact could come from reduced prevention activities including interruption of planned net campaigns, through all phases of the COVID-19 epidemic. In high burden settings, the impact of each type of disruption could be significant and lead to a loss of life-years over five years that is of the same order of magnitude as the direct impact from COVID-19 in places with a high burden of malaria and large HIV/TB epidemics. Maintaining the most critical prevention activities and healthcare services for HIV, TB and malaria could significantly reduce the overall impact of the COVID-19 epidemic.

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Perez Guzman PN, Daunt A, Mukherjee S, Crook P, Forlano R, Kont M, Lochen A, Vollmer M, Middleton P, Judge R, Harlow C, Soubieres A, Cooke G, White P, Hallett T, Aylin P, Ferguson N, Hauck K, Thursz M, Nayagam ASet al., 2020, Report 17: Clinical characteristics and predictors of outcomes of hospitalised patients with COVID-19 in a London NHS Trust: a retrospective cohort study

Clinical characteristics and determinants of outcomes for hospitalised COVID-19 patients in the UK remain largely undescribed and emerging evidence suggests ethnic minorities might be disproportionately affected. We describe the characteristics and outcomes of patients hospitalised for COVID-19 in three large London hospitals with a multi-ethnic catchment population.We performed a retrospective cohort study on all patients hospitalised with laboratory-confirmed SARS-CoV-2 infection at Imperial College Healthcare NHS Trust between February 25 and April 5, 2020. Outcomes were recorded as of April 19, 2020. Logistic regression models, survival analyses and cumulative competing risk analyses were performed to evaluate factors associated with COVID-19 hospital mortality.Of 520 patients in this cohort (median age 67 years, (IQR 26) and 62% male), 302 (68%) had been discharged alive, 144 (32%) died and 74 (14%) were still hospitalised at the time of censoring. Increasing age (adjusted odds ratio [aOR] 2·16, 95%CI 1·50-3·12), severe hypoxia (aOR 3·75, 95%CI 1·80-7·80), low platelets (aOR 0·65, 95%CI 0.49·0·85), reduced estimated glomerular filtration rate (aOR 4·11, 95%CI 1·58-10·69), bilirubin >21mmol/L (aOR 2·32, 95%CI 1·05-5·14) and low albumin (aOR 0·77, 9%%CI 0·59-1·01) were associated with increased risk of in-hospital mortality. Individual comorbidities were not independently associated with risk of death. Regarding ethnicity, 209 (40%) were from a black and Asian minority, for 115 (22%) ethnicity was unknown and 196 (38%) patients were white. Compared to the latter, black patients were significantly younger and had less comorbidities. Whilst the crude OR of death of black compared to white patients was not significant (1·14, 95%CI 0·69-1·88, p=0.62), adjusting for age and comorbidity showed a trend towards significance

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Ainslie KEC, Walters CE, Fu H, Bhatia S, Wang H, Xi X, Baguelin M, Bhatt S, Boonyasiri A, Boyd O, Cattarino L, Ciavarella C, Cucunuba Z, Cuomo-Dannenburg G, Dighe A, Dorigatti I, van Elsland SL, FitzJohn R, Gaythorpe K, Ghani AC, Green W, Hamlet A, Hinsley W, Imai N, Jorgensen D, Knock E, Laydon D, Nedjati-Gilani G, Okell LC, Siveroni I, Thompson HA, Unwin HJT, Verity R, Vollmer M, Walker PGT, Wang Y, Watson OJ, Whittaker C, Winskill P, Donnelly CA, Ferguson NM, Riley Set al., 2020, Evidence of initial success for China exiting COVID-19 social distancing policy after achieving containment [version 1; peer review: 2 approved], Wellcome Open Res, Vol: 5, ISSN: 2398-502X

Background: The COVID-19 epidemic was declared a Global Pandemic by WHO on 11 March 2020. By 24 March 2020, over 440,000 cases and almost 20,000 deaths had been reported worldwide. In response to the fast-growing epidemic, which began in the Chinese city of Wuhan, Hubei, China imposed strict social distancing in Wuhan on 23 January 2020 followed closely by similar measures in other provinces. These interventions have impacted economic productivity in China, and the ability of the Chinese economy to resume without restarting the epidemic was not clear. Methods: Using daily reported cases from mainland China and Hong Kong SAR, we estimated transmissibility over time and compared it to daily within-city movement, as a proxy for economic activity. Results: Initially, within-city movement and transmission were very strongly correlated in the five mainland provinces most affected by the epidemic and Beijing. However, that correlation decreased rapidly after the initial sharp fall in transmissibility. In general, towards the end of the study period, the correlation was no longer apparent, despite substantial increases in within-city movement. A similar analysis for Hong Kong shows that intermediate levels of local activity were maintained while avoiding a large outbreak. At the very end of the study period, when China began to experience the re-introduction of a small number of cases from Europe and the United States, there is an apparent up-tick in transmission. Conclusions: Although these results do not preclude future substantial increases in incidence, they suggest that after very intense social distancing (which resulted in containment), China successfully exited its lockdown to some degree. Elsewhere, movement data are being used as proxies for economic activity to assess the impact of interventions. The results presented here illustrate how the eventual decorrelation between transmission and movement is likely a key feature of successful COVID-19 exit strategies.

Journal article

Grassly N, Pons Salort M, Parker E, White P, Ainslie K, Baguelin M, Bhatt S, Boonyasiri A, Boyd O, Brazeau N, Cattarino L, Ciavarella C, Cooper L, Coupland H, Cucunuba Perez Z, Cuomo-Dannenburg G, Dighe A, Djaafara A, Donnelly C, Dorigatti I, van Elsland S, Ferreira Do Nascimento F, Fitzjohn R, Fu H, Gaythorpe K, Geidelberg L, Green W, Hallett T, Hamlet A, Hayes S, Hinsley W, Imai N, Jorgensen D, Knock E, Laydon D, Lees J, Mangal T, Mellan T, Mishra S, Nedjati Gilani G, Nouvellet P, Okell L, Ower A, Parag K, Pickles M, Ragonnet-Cronin M, Stopard I, Thompson H, 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, Ferguson Net al., 2020, Report 16: Role of testing in COVID-19 control

The World Health Organization has called for increased molecular testing in response to the COVID-19 pandemic, but different countries have taken very different approaches. We used a simple mathematical model to investigate the potential effectiveness of alternative testing strategies for COVID-19 control. Weekly screening of healthcare workers (HCWs) and other at-risk groups using PCR or point-of-care tests for infection irrespective of symptoms is estimated to reduce their contribution to transmission by 25-33%, on top of reductions achieved by self-isolation following symptoms. Widespread PCR testing in the general population is unlikely to limit transmission more than contact-tracing and quarantine based on symptoms alone, but could allow earlier release of contacts from quarantine. Immunity passports based on tests for antibody or infection could support return to work but face significant technical, legal and ethical challenges. Testing is essential for pandemic surveillance but its direct contribution to the prevention of transmission is likely to be limited to patients, HCWs and other high-risk groups.

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Ferguson N, Nedjati Gilani G, Laydon D, 2020, COVID-19 CovidSim microsimulation model

This is the COVID-19 CovidSim microsimulation model developed by the MRC Centre for Global Infectious Disease Analysis hosted at Imperial College, London.The following papers are relevant to the model. Please note that some of them may require a subscription.https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-NPI-modelling-16-03-2020.pdfhttps://www.nature.com/articles/nature04795https://www.nature.com/articles/nature04017https://www.pnas.org/content/105/12/4639.shortA copy of Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand can also be downloaded from Spiral: https://spiral.imperial.ac.uk/handle/10044/1/77482

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