Imperial College London

DrThomasMellan

Faculty of MedicineSchool of Public Health

Research Associate
 
 
 
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t.mellan

 
 
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St Mary's Research BuildingSt Mary's Campus

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Summary

 

Publications

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44 results found

Mishra S, Mindermann S, Sharma M, Whittaker C, Mellan TA, Wilton T, Klapsa D, Mate R, Fritzsche M, Zambon M, Ahuja J, Howes A, Miscouridou X, Nason GP, Ratmann O, Semenova E, Leech G, Sandkühler JF, Rogers-Smith C, Vollmer M, Unwin HJT, Gal Y, Chand M, Gandy A, Martin J, Volz E, Ferguson NM, Bhatt S, Brauner JM, Flaxman S, COVID-19 Genomics UK COG-UK Consortiumet al., 2021, Changing composition of SARS-CoV-2 lineages and rise of Delta variant in England., EClinicalMedicine, Vol: 39

Background: Since its emergence in Autumn 2020, the SARS-CoV-2 Variant of Concern (VOC) B.1.1.7 (WHO label Alpha) rapidly became the dominant lineage across much of Europe. Simultaneously, several other VOCs were identified globally. Unlike B.1.1.7, some of these VOCs possess mutations thought to confer partial immune escape. Understanding when and how these additional VOCs pose a threat in settings where B.1.1.7 is currently dominant is vital. Methods: We examine trends in the prevalence of non-B.1.1.7 lineages in London and other English regions using passive-case detection PCR data, cross-sectional community infection surveys, genomic surveillance, and wastewater monitoring. The study period spans from 31st January 2021 to 15th May 2021. Findings: Across data sources, the percentage of non-B.1.1.7 variants has been increasing since late March 2021. This increase was initially driven by a variety of lineages with immune escape. From mid-April, B.1.617.2 (WHO label Delta) spread rapidly, becoming the dominant variant in England by late May. Interpretation: The outcome of competition between variants depends on a wide range of factors such as intrinsic transmissibility, evasion of prior immunity, demographic specificities and interactions with non-pharmaceutical interventions. The presence and rise of non-B.1.1.7 variants in March likely was driven by importations and some community transmission. There was competition between non-B.1.17 variants which resulted in B.1.617.2 becoming dominant in April and May with considerable community transmission. Our results underscore that early detection of new variants requires a diverse array of data sources in community surveillance. Continued real-time information on the highly dynamic composition and trajectory of different SARS-CoV-2 lineages is essential to future control efforts. Funding: National Institute for Health Research, Medicines and Healthcare products Regulatory Agency, DeepMind, EPSRC, EA Funds programme, Open

Journal article

Mishra S, Scott JA, Laydon DJ, Flaxman S, Gandy A, Mellan TA, Unwin HJT, Vollmer M, Coupland H, Ratmann O, Monod M, Zhu HH, Cori A, Gaythorpe KAM, Whittles LK, Whittaker C, Donnelly CA, Ferguson NM, Bhatt Set al., 2021, Comparing the responses of the UK, Sweden and Denmark to COVID-19 using counterfactual modelling, SCIENTIFIC REPORTS, Vol: 11, Pages: 1-9, ISSN: 2045-2322

The UK and Sweden have among the worst per-capita COVID-19 mortality in Europe. Sweden stands out for its greater reliance on voluntary, rather than mandatory, control measures. We explore how the timing and effectiveness of control measures in the UK, Sweden and Denmark shaped COVID-19 mortality in each country, using a counterfactual assessment: what would the impact have been, had each country adopted the others’ policies? Using a Bayesian semi-mechanistic model without prior assumptions on the mechanism or effectiveness of interventions, we estimate the time-varying reproduction number for the UK, Sweden and Denmark from daily mortality data. We use two approaches to evaluate counterfactuals which transpose the transmission profile from one country onto another, in each country’s first wave from 13th March (when stringent interventions began) until 1st July 2020. UK mortality would have approximately doubled had Swedish policy been adopted, while Swedish mortality would have more than halved had Sweden adopted UK or Danish strategies. Danish policies were most effective, although differences between the UK and Denmark were significant for one counterfactual approach only. Our analysis shows that small changes in the timing or effectiveness of interventions have disproportionately large effects on total mortality within a rapidly growing epidemic.

Journal article

Krawczyk K, Chelkowski T, Laydon DJ, Mishra S, Xifara D, Gibert B, Flaxman S, Mellan T, Schwämmle V, Röttger R, Hadsund JT, Bhatt Set al., 2021, Correction: Quantifying Online News Media Coverage of the COVID-19 Pandemic: Text Mining Study and Resource., J Med Internet Res, Vol: 23

[This corrects the article DOI: 10.2196/28253.].

Journal article

Krawczyk K, Chelkowski T, Laydon DJ, Mishra S, Xifara D, Flaxman S, Mellan T, Schwammle V, Rottger R, Hadsund JT, Bhatt Set al., 2021, Quantifying Online News Media Coverage of the COVID-19 Pandemic: Text Mining Study and Resource, JOURNAL OF MEDICAL INTERNET RESEARCH, Vol: 23, ISSN: 1438-8871

Journal article

Faria NR, Mellan TA, Whittaker C, Claro IM, Candido DDS, Mishra S, Crispim MAE, Sales FC, Hawryluk I, McCrone JT, Hulswit RJG, Franco LAM, Ramundo MS, de Jesus JG, Andrade PS, Coletti TM, Ferreira GM, Silva CAM, Manuli ER, Pereira RHM, Peixoto PS, Kraemer MU, Gaburo N, Camilo CDC, Hoeltgebaum H, Souza WM, Rocha EC, de Souza LM, de Pinho MC, Araujo LJT, Malta FS, de Lima AB, Silva JDP, Zauli DAG, Ferreira ACDS, Schnekenberg RP, Laydon DJ, Walker PGT, Schlueter HM, dos Santos ALP, Vidal MS, Del Caro VS, Filho RMF, dos Santos HM, Aguiar RS, Proenca-Modena JLP, Nelson B, Hay JA, Monod M, Miscouridou X, Coupland H, Sonabend R, Vollmer M, Gandy A, Prete CA, Nascimento VH, Suchard MA, Bowden TA, Pond SLK, Wu C-H, Ratmann O, Ferguson NM, Dye C, Loman NJ, Lemey P, Rambaut A, Fraiji NA, Carvalho MDPSS, Pybus OG, Flaxman S, Bhatt S, Sabino ECet al., 2021, Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil, SCIENCE, Vol: 372, Pages: 815-+, ISSN: 0036-8075

Journal article

Poulou A, Mellan TA, Finnis MW, 2021, Stability of Zr-Al-C and Ti-Al-C MAX phases: A theoretical study, PHYSICAL REVIEW MATERIALS, Vol: 5, ISSN: 2475-9953

Journal article

Vollmer MAC, Glampson B, Mellan TA, Mishra S, Mercuri L, Costello C, Klaber R, Cooke G, Flaxman S, Bhatt Set al., 2021, A unified machine learning approach to time series forecasting applied to demand at emergency departments, BMC Emergency Medicine, Vol: 21, Pages: 1-14, ISSN: 1471-227X

There were 25.6 million attendances at Emergency Departments (EDs) in Englandin 2019 corresponding to an increase of 12 million attendances over the pastten years. The steadily rising demand at EDs creates a constant challenge toprovide adequate quality of care while maintaining standards and productivity.Managing hospital demand effectively requires an adequate knowledge of thefuture rate of admission. Using 8 years of electronic admissions data from twomajor acute care hospitals in London, we develop a novel ensemble methodologythat combines the outcomes of the best performing time series and machinelearning approaches in order to make highly accurate forecasts of demand, 1, 3and 7 days in the future. Both hospitals face an average daily demand of 208and 106 attendances respectively and experience considerable volatility aroundthis mean. However, our approach is able to predict attendances at theseemergency departments one day in advance up to a mean absolute error of +/- 14and +/- 10 patients corresponding to a mean absolute percentage error of 6.8%and 8.6% respectively. Our analysis compares machine learning algorithms tomore traditional linear models. We find that linear models often outperformmachine learning methods and that the quality of our predictions for any of theforecasting horizons of 1, 3 or 7 days are comparable as measured in MAE. Inaddition to comparing and combining state-of-the-art forecasting methods topredict hospital demand, we consider two different hyperparameter tuningmethods, enabling a faster deployment of our models without compromisingperformance. We believe our framework can readily be used to forecast a widerange of policy relevant indicators.

Journal article

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, Vol: 11, Pages: 1-9, 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

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

Fossati PCM, Mellan TA, Kuganathan N, Lee WEet al., 2020, Atomistic modeling approach to the thermodynamics of sodium silicate glasses, JOURNAL OF THE AMERICAN CERAMIC SOCIETY, Vol: 104, Pages: 1331-1344, ISSN: 0002-7820

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

Report

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

Hogan A, Winskill P, Watson O, Walker P, Whittaker C, Baguelin M, Haw D, Lochen A, Gaythorpe K, Ainslie K, Bhatt S, Boonyasiri A, Boyd O, Brazeau N, Cattarino L, Charles G, Cooper L, Coupland H, Cucunuba Perez Z, Cuomo-Dannenburg G, Donnelly C, Dorigatti I, Eales O, van Elsland S, Ferreira Do Nascimento F, Fitzjohn R, Flaxman S, Green W, Hallett T, Hamlet A, Hinsley W, Imai N, Jauneikaite E, Jeffrey B, Knock E, Laydon D, Lees J, Mellan T, Mishra S, Nedjati Gilani G, Nouvellet P, Ower A, Parag K, Ragonnet-Cronin M, Siveroni I, Skarp J, Thompson H, Unwin H, Verity R, Vollmer M, Volz E, Walters C, Wang H, Wang Y, Whittles L, Xi X, Muhib F, Smith P, Hauck K, Ferguson N, Ghani Aet al., 2020, Report 33: Modelling the allocation and impact of a COVID-19 vaccine

Several SARS-CoV-2 vaccine candidates are now in late-stage trials, with efficacy and safety results expected by the end of 2020. Even under optimistic scenarios for manufacture and delivery, the doses available in 2021 are likely to be limited. Here we identify optimal vaccine allocation strategies within and between countries to maximise health (avert deaths) under constraints on dose supply. We extended an existing mathematical model of SARS-CoV-2 transmission across different country settings to model the public health impact of potential vaccines, using a range of target product profiles developed by the World Health Organization. We show that as supply increases, vaccines that reduce or block infection – and thus transmission – in addition to preventing disease have a greater impact than those that prevent disease alone, due to the indirect protection provided to high-risk groups. We further demonstrate that the health impact of vaccination will depend on the cumulative infection incidence in the population when vaccination begins, the duration of any naturally acquired immunity, the likely trajectory of the epidemic in 2021 and the level of healthcare available to effectively treat those with disease. Within a country, we find that for a limited supply (doses for <20% of the population) the optimal strategy is to target the elderly and other high-risk groups. However, if a larger supply is available, the optimal strategy switches to targeting key transmitters (i.e. the working age population and potentially children) to indirectly protect the elderly and vulnerable. Given the likely global dose supply in 2021 (2 billion doses with a two-dose vaccine), we find that a strategy in which doses are allocated to countries in proportion to their population size is close to optimal in averting deaths. Such a strategy also aligns with the ethical principles agreed in pandemic preparedness planning.

Report

Monod M, Blenkinsop A, Xi X, Herbert D, Bershan S, Tietze S, Bradley V, Chen Y, Coupland H, Filippi S, Ish-Horowicz J, McManus M, Mellan T, Gandy A, Hutchinson M, Unwin H, Vollmer M, Weber S, Zhu H, Bezancon A, Ferguson N, Mishra S, Flaxman S, Bhatt S, Ratmann O, Ainslie K, Baguelin M, Boonyasiri A, Boyd O, Cattarino L, Cooper L, Cucunuba Perez Z, Cuomo-Dannenburg G, Djaafara A, Dorigatti I, van Elsland S, Fitzjohn R, Gaythorpe K, Geidelberg L, Green W, Hamlet A, Jeffrey B, Knock E, Laydon D, Nedjati Gilani G, Nouvellet P, Parag K, Siveroni I, Thompson H, Verity R, Walters C, Donnelly C, Okell L, Bhatia S, Brazeau N, Eales O, Haw D, Imai N, Jauneikaite E, Lees J, Mousa A, Olivera Mesa D, Skarp J, Whittles Let al., 2020, Report 32: Targeting interventions to age groups that sustain COVID-19 transmission in the United States, Pages: 1-32

Following ini􀀂al declines, in mid 2020, a resurgence in transmission of novel coronavirus disease (COVID-19) has occurred in the United States and parts of Europe. Despite the wide implementa􀀂on of non-pharmaceu􀀂cal inter-ven􀀂ons, it is s􀀂ll not known how they are impacted by changing contact pa􀀁erns, age and other demographics. As COVID-19 disease control becomes more localised, understanding the age demographics driving transmission and how these impact the loosening of interven􀀂ons such as school reopening is crucial. Considering dynamics for the United States, we analyse aggregated, age-specific mobility trends from more than 10 million individuals and link these mechanis􀀂cally to age-specific COVID-19 mortality data. In contrast to previous approaches, we link mobility to mortality via age specific contact pa􀀁erns and use this rich rela􀀂onship to reconstruct accurate trans-mission dynamics. Contrary to anecdotal evidence, we find li􀀁le support for age-shi􀀃s in contact and transmission dynamics over 􀀂me. We es􀀂mate that, un􀀂l August, 63.4% [60.9%-65.5%] of SARS-CoV-2 infec􀀂ons in the United States originated from adults aged 20-49, while 1.2% [0.8%-1.8%] originated from children aged 0-9. In areas with con􀀂nued, community-wide transmission, our transmission model predicts that re-opening kindergartens and el-ementary schools could facilitate spread and lead to considerable excess COVID-19 a􀀁ributable deaths over a 90-day period. These findings indicate that targe􀀂ng interven􀀂ons to adults aged 20-49 are an important con-sidera􀀂on in hal􀀂ng resurgent epidemics, and preven􀀂ng COVID-19-a􀀁ributable deaths when kindergartens and elementary schools reopen.

Journal article

van Elsland S, Watson O, Alhaffar M, Mehchy Z, Whittaker C, Akil Z, Ainslie K, Baguelin M, Bhatt S, Boonyasiri A, Boyd O, Brazeau N, Cattarino L, Charles G, Ciavarella C, Cooper L, Coupland H, Cucunuba Perez Z, Cuomo-Dannenburg G, Djaafara A, Donnelly C, Dorigatti I, Eales O, van Elsland S, Nascimento F, Fitzjohn R, Flaxman S, Forna A, Fu H, Gaythorpe K, Green W, Hamlet A, Hauck K, Haw D, Hayes S, Hinsley W, Imai N, Jeffrey B, Johnson R, Jorgensen D, Knock E, Laydon D, Lees J, Mellan T, Mishra S, Nedjati Gilani G, Nouvellet P, Okell L, Olivera Mesa D, Pons Salort M, Ragonnet-Cronin M, Siveroni I, Stopard I, Thompson H, Unwin H, Verity R, Vollmer M, Volz E, Walters C, Wang H, Wang Y, Whittles L, Winskill P, Xi X, Ferguson N, Beals E, Walker P, Anonymous Authorset al., 2020, Report 31: Estimating the burden of COVID-19 in Damascus, Syria: an analysis of novel data sources to infer mortality under-ascertainment

The COVID-19 pandemic has resulted in substantial mortality worldwide. However, to date, countries in the Middle East and Africa have reported substantially lower mortality rates than in Europe and the Americas. One hypothesis is that these countries have been ‘spared’, but another is that deaths have been under-ascertained (deaths that have been unreported due to any number of reasons, for instance due to limited testing capacity). However, the scale of under-ascertainment is difficult to assess with currently available data. In this analysis, we estimate the potential under-ascertainment of COVID-19 mortality in Damascus, Syria, where all-cause mortality data has been reported between 25th July and 1st August. We fit a mathematical model of COVID-19 transmission to reported COVID-19 deaths in Damascus since the beginning of the pandemic and compare the model-predicted deaths to reported excess deaths. Exploring a range of different assumptions about under-ascertainment, we estimate that only 1.25% of deaths (sensitivity range 1% - 3%) due to COVID-19 are reported in Damascus. Accounting for under-ascertainment also corroborates local reports of exceeded hospital bed capacity. To validate the epidemic dynamics inferred, we leverage community-uploaded obituary certificates as an alternative data source, which confirms extensive mortality under-ascertainment in Damascus between July and August. This level of under-ascertainment suggests that Damascus is at a much later stage in its epidemic than suggested by surveillance reports, which have repo. We estimate that 4,340 (95% CI: 3,250 - 5,540) deaths due to COVID-19 in Damascus may have been missed as of 2nd September 2020. Given that Damascus is likely to have the most robust surveillance in Syria, these findings suggest that other regions of the country could have experienced similar or worse mortality rates due to COVID-19.

Report

Candido DS, Claro IM, de Jesus JG, Souza WM, Moreira FRR, Dellicour S, Mellan TA, du Plessis L, Pereira RHM, Sales FCS, Manuli ER, Theze J, Almeida L, Menezes MT, Voloch CM, Fumagalli MJ, Coletti TM, Silva CAM, Ramundo MS, Amorim MR, Hoeltgebaum HH, Mishra S, Gill MS, Carvalho LM, Buss LF, Prete Jr CA, Ashworth J, Nakaya H, Peixoto PS, Brady OJ, Nicholls SM, Tanuri A, Rossi AD, Braga CK, Gerber AL, Guimaraes APDC, Gaburo Jr N, Alencar CS, Ferreira ACS, Lima CX, Levi JE, Granato C, Ferreira GM, Francisco Jr RS, Granja F, Garcia MT, Moretti ML, Perroud Jr MW, Castineiras TMPP, Lazari CS, Hill SC, de Souza Santos AA, Simeoni CL, Forato J, Sposito AC, Schreiber AZ, Santos MNN, de Sa CZ, Souza RP, Resende-Moreira LC, Teixeira MM, Hubner J, Leme PAF, Moreira RG, Nogueira ML, 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, Vol: 369, Pages: 1255-1260, ISSN: 0036-8075

Brazil currently has one of the fastest-growing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemics in the world. Because of limited available data, assessments of the impact of nonpharmaceutical interventions (NPIs) on this virus spread remain challenging. Using a mobility-driven transmission model, we show that NPIs reduced the reproduction number from >3 to 1 to 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 February and 11 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 traveled distances in national flights. This study sheds new light on the epidemic transmission and evolutionary trajectories of SARS-CoV-2 lineages in Brazil and provides evidence that current interventions remain insufficient to keep virus transmission under control in this country.

Journal article

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, Vol: 8, Pages: e1132-e1141, 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

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, Vol: 584, Pages: 425-429, 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

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, Vol: 584, Pages: 257-261, 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

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

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

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.

Report

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.

Report

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

Report

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.

Report

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.

Report

Jeffrey B, Walters CE, Ainslie KEC, Eales O, Ciavarella C, Bhatia S, Hayes S, Baguelin M, Boonyasiri A, Brazeau NF, Cuomo-Dannenburg G, FitzJohn RG, Gaythorpe K, Green W, Imai N, Mellan TA, Mishra S, Nouvellet P, Unwin HJT, Verity R, Vollmer M, Whittaker C, Ferguson NM, Donnelly CA, Riley Set al., 2020, Anonymised and aggregated crowd level mobility data from mobile phones suggests that initial compliance with COVID-19 social distancing interventions was high and geographically consistent across the UK., Wellcome open research, Vol: 5, ISSN: 2398-502X

<b>Background:</b> Since early March 2020, the COVID-19 epidemic across the United Kingdom has led to a range of social distancing policies, which have resulted in reduced mobility across different regions. Crowd level data on mobile phone usage can be used as a proxy for actual population mobility patterns and provide a way of quantifying the impact of social distancing measures on changes in mobility. <b>Methods:</b> Here, we use two mobile phone-based datasets (anonymised and aggregated crowd level data from O2 and from the Facebook app on mobile phones) to assess changes in average mobility, both overall and broken down into high and low population density areas, and changes in the distribution of journey lengths. <b>Results:</b> We show that there was a substantial overall reduction in mobility, with the most rapid decline on the 24th March 2020, the day after the Prime Minister's announcement of an enforced lockdown. The reduction in mobility was highly synchronized across the UK. Although mobility has remained low since 26th March 2020, we detect a gradual increase since that time. We also show that the two different datasets produce similar trends, albeit with some location-specific differences. We see slightly larger reductions in average mobility in high-density areas than in low-density areas, with greater variation in mobility in the high-density areas: some high-density areas eliminated almost all mobility. <b>Conclusions:</b> These analyses form a baseline from which to observe changes in behaviour in the UK as social distancing is eased and inform policy towards the future control of SARS-CoV-2 in the UK.

Journal article

Hawryluk I, Mellan TA, Hoeltgebaum H, Mishra S, Schnekenberg RP, Whittaker C, Zhu H, Gandy A, Donnelly CA, Flaxman S, Bhatt Set al., 2020, Inference of COVID-19 epidemiological distributions from Brazilian hospital data, Journal of The Royal Society Interface, Vol: 17, Pages: 20200596-20200596, ISSN: 1742-5662

Knowing COVID-19 epidemiological distributions, such as the time from patient admission to death, is directly relevant to effective primary and secondary care planning, and moreover, the mathematical modelling of the pandemic generally. We determine epidemiological distributions for patients hospitalized with COVID-19 using a large dataset (N = 21 000 − 157 000) from the Brazilian Sistema de Informação de Vigilância Epidemiológica da Gripe database. A joint Bayesian subnational model with partial pooling is used to simultaneously describe the 26 states and one federal district of Brazil, and shows significant variation in the mean of the symptom-onset-to-death time, with ranges between 11.2 and 17.8 days across the different states, and a mean of 15.2 days for Brazil. We find strong evidence in favour of specific probability density function choices: for example, the gamma distribution gives the best fit for onset-to-death and the generalized lognormal for onset-to-hospital-admission. Our results show that epidemiological distributions have considerable geographical variation, and provide the first estimates of these distributions in a low and middle-income setting. At the subnational level, variation in COVID-19 outcome timings are found to be correlated with poverty, deprivation and segregation levels, and weaker correlation is observed for mean age, wealth and urbanicity.

Journal article

Jeffrey B, Walters CE, Ainslie KEC, Eales O, Ciavarella C, Bhatia S, Hayes S, Baguelin M, Boonyasiri A, Brazeau NF, Cuomo-Dannenburg G, FitzJohn RG, Gaythorpe K, Green W, Imai N, Mellan TA, Mishra S, Nouvellet P, Unwin HJT, Verity R, Vollmer M, Whittaker C, Ferguson NM, Donnelly CA, Riley Set al., 2020, Anonymised and aggregated crowd level mobility data from mobile phones suggests that initial compliance with COVID-19 social distancing interventions was high and geographically consistent across the UK., Wellcome Open Res, Vol: 5, ISSN: 2398-502X

Background: Since early March 2020, the COVID-19 epidemic across the United Kingdom has led to a range of social distancing policies, which have resulted in reduced mobility across different regions. Crowd level data on mobile phone usage can be used as a proxy for actual population mobility patterns and provide a way of quantifying the impact of social distancing measures on changes in mobility. Methods: Here, we use two mobile phone-based datasets (anonymised and aggregated crowd level data from O2 and from the Facebook app on mobile phones) to assess changes in average mobility, both overall and broken down into high and low population density areas, and changes in the distribution of journey lengths. Results: We show that there was a substantial overall reduction in mobility, with the most rapid decline on the 24th March 2020, the day after the Prime Minister's announcement of an enforced lockdown. The reduction in mobility was highly synchronized across the UK. Although mobility has remained low since 26th March 2020, we detect a gradual increase since that time. We also show that the two different datasets produce similar trends, albeit with some location-specific differences. We see slightly larger reductions in average mobility in high-density areas than in low-density areas, with greater variation in mobility in the high-density areas: some high-density areas eliminated almost all mobility. Conclusions: These analyses form a baseline from which to observe changes in behaviour in the UK as social distancing is eased and inform policy towards the future control of SARS-CoV-2 in the UK.

Journal article

Srinivasan P, Duff AI, Mellan TA, Sluiter MHF, Nicola L, Simone Aet al., 2019, The effectiveness of reference-free modified embedded atom method potentials demonstrated for NiTi and NbMoTaW, MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING, Vol: 27, ISSN: 0965-0393

Journal article

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