Imperial College London

DrSethFlaxman

Faculty of Natural SciencesDepartment of Mathematics

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522Huxley BuildingSouth Kensington Campus

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Publications

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139 results found

Monod M, Blenkinsop A, Brizzi A, Chen Y, Cardoso Correia Perello C, Jogarah V, Wang Y, Flaxman S, Bhatt S, Ratmann Oet al., 2023, Regularised B-splines projected Gaussian Process priors to estimate time-trends in age-specific COVID-19 deaths, Bayesian Analysis, Vol: 18, Pages: 957-987, ISSN: 1931-6690

The COVID-19 pandemic has caused severe public health consequences in the United States. In this study, we use a hierarchical Bayesian model to estimate the age-specific COVID-19 attributable deaths over time in the United States. The model is specified by a novel non-parametric spatial approach over time and age, a low-rank Gaussian Process (GP) projected by regularised B-splines. We show that this projection defines a new GP with attractive smoothness and computational efficiency properties, derive its kernel function, and discuss the penalty terms induced by the projected GP. Simulation analyses and benchmark results show that the B-splines projected GP may perform better than standard B-splines and Bayesian P-splines, and equivalently well as a standard GP at considerably lowerruntimes. We apply the model to weekly, age-stratified COVID-19 attributabledeaths reported by the US Centers for Disease Control, which are subject to censoring and reporting biases. Using the B-splines projected GP, we can estimate longitudinal trends in COVID-19 associated deaths across the US by 1-year age bands. These estimates are instrumental to calculate age-specific mortality rates, describe variation in age-specific deaths across the US, and for fitting epidemic models. Here, we couple the model with age-specific vaccination rates to show that vaccination rates were significantly associated with the magnitude of resurgences in COVID-19 deaths during the summer 2021. With counterfactual analyses, we quantify the avoided COVID-19 deaths under lower vaccination rates and avoidable COVID-19 deaths under higher vaccination rates. The B-splines projected GP priors that we develop are likely an appealing addition to the arsenal of Bayesianregularising priors.

Journal article

Flaxman S, Kasonka L, Cluver L, Souza AS, Nelson Iii CA, Blenkinsop A, Unwin HJT, Hillis Set al., 2023, List child dependents on death certificates, SCIENCE, Vol: 380, ISSN: 0036-8075

Journal article

Howes A, Risher K, Nguyen VK, Stevens O, Jia K, Wolock T, Esra R, Zembe L, Wanyeki I, Mahy M, Benedikt C, Flaxman S, Eaton Jet al., 2023, Spatio-temporal estimates of HIV risk group proportions for adolescent girls and young women across 13 priority countries in sub-Saharan Africa, PLOS Global Public Health, Vol: 3, Pages: 1-14, ISSN: 2767-3375

The Global AIDS Strategy 2021-2026 identifies adolescent girls and young women (AGYW) as a priority population for HIV prevention, and recommends differentiating intervention portfolios geographically based on local HIV incidence and individual risk behaviours. We estimated prevalence of HIV risk behaviours and associated HIV incidence at health district level among AGYW living in 13 countries in sub-Saharan Africa. We analysed 46 geospatially-referenced national household surveys conducted between 1999-2018 across 13 high HIV burden countries in sub-Saharan Africa. Female survey respondents aged 15-29 years were classified into four risk groups (not sexually active, cohabiting, non-regular or multiple partner[s] and female sex workers [FSW]) based on reported sexual behaviour. We used a Bayesian spatio-temporal multinomial regression model to estimate the proportion of AGYW in each risk group stratified by district, year, and five-year age group. Using subnational estimates of HIV prevalence and incidence produced by countries with support from UNAIDS, we estimated new HIV infections in each risk group by district and age group. We then assessed the efficiency of prioritising interventions according to risk group. Data consisted of 274,970 female survey respondents aged 15-29. Among women aged 20-29, cohabiting (63.1%) was more common in eastern Africa than non-regular or multiple partner(s) (21.3%), while in southern countries non-regular or multiple partner(s) (58.9%) were more common than cohabiting (23.4%). Risk group proportions varied substantially across age groups (65.9% of total variation explained), countries (20.9%), and between districts within each country (11.3%), but changed little over time (0.9%). Prioritisation based on behavioural risk, in combination with location- and age-based prioritisation, reduced the proportion of population required to be reached in order to find half of all expected new infections from 19.4% to 10.6%. FSW were 1.3% of th

Journal article

Lamprinakou S, Barahona M, Flaxman S, Filippi S, Gandy A, McCoy EJet al., 2023, BART-based inference for Poisson processes, Computational Statistics and Data Analysis, Vol: 180, Pages: 1-25, ISSN: 0167-9473

The effectiveness of Bayesian Additive Regression Trees (BART) has been demonstrated in a variety of contexts including non-parametric regression and classification. A BART scheme for estimating the intensity of inhomogeneous Poisson processes is introduced. Poisson intensity estimation is a vital task in various applications including medical imaging, astrophysics and network traffic analysis. The new approach enables full posterior inference of the intensity in a non-parametric regression setting. The performance of the novel scheme is demonstrated through simulation studies on synthetic and real datasets up to five dimensions, and the new scheme is compared with alternative approaches.

Journal article

Bennett J, Rashid T, Zolfaghari A, Doyle Y, Suel E, Pearson-Stuttard J, Davies B, Fecht D, Muller ES, Nathvani RS, Sportiche N, Daby H, Johnson E, Li G, Flaxman S, Toledano M, Asaria M, Ezzati Met al., 2023, Changes in life expectancy and house prices in London from 2002 to 2019: Hyper-resolution spatiotemporal analysis of death registration and real estate data, The Lancet Regional Health Europe, Vol: 27, Pages: 1-13, ISSN: 2666-7762

Background:London has outperformed smaller towns and rural areas in terms of life expectancy increase. Our aim was to investigate life expectancy change at very-small-area level, and its relationship with house prices and their change.Methods:We performed a hyper-resolution spatiotemporal analysis from 2002 to 2019 for 4835 London Lower-layer Super Output Areas (LSOAs). We used population and death counts in a Bayesian hierarchical model to estimate age- and sex-specific death rates for each LSOA, converted to life expectancy at birth using life table methods. We used data from the Land Registry via the real estate website Rightmove (www.rightmove.co.uk), with information on property size, type and land tenure in a hierarchical model to estimate house prices at LSOA level. We used linear regressions to summarise how much life expectancy changed in relation to the combination of house prices in 2002 and their change from 2002 to 2019. We calculated the correlation between change in price and change in sociodemographic characteristics of the resident population of LSOAs and population turnover.Findings:In 134 (2.8%) of London's LSOAs for women and 32 (0.7%) for men, life expectancy may have declined from 2002 to 2019, with a posterior probability of a decline >80% in 41 (0.8%, women) and 14 (0.3%, men) LSOAs. The life expectancy increase in other LSOAs ranged from <2 years in 537 (11.1%) LSOAs for women and 214 (4.4%) for men to >10 years in 220 (4.6%) for women and 211 (4.4%) for men. The 2.5th-97.5th-percentile life expectancy difference across LSOAs increased from 11.1 (10.7–11.5) years in 2002 to 19.1 (18.4–19.7) years for women in 2019, and from 11.6 (11.3–12.0) years to 17.2 (16.7–17.8) years for men. In the 20% (men) and 30% (women) of LSOAs where house prices had been lowest in 2002, mainly in east and outer west London, life expectancy increased only in proportion to the rise in house prices. In contrast, in the 30% (men) and

Journal article

Wolock TM, Flaxman S, Chimpandule T, Mbiriyawanda S, Jahn A, Nyirenda R, Eaton JWet al., 2023, Subnational HIV incidence trends in Malawi: large, heterogeneous declines across space., medRxiv

The rate of new HIV infections globally has decreased substantially from its peak in the late 1990s, but the epidemic persists and remains highest in many countries in eastern and southern Africa. Previous research hypothesised that, as the epidemic recedes, it will become increasingly concentrated among sub-populations and geographic areas where transmission is the highest and that are least effectively reached by treatment and prevention services. However, empirical data on subnational HIV incidence trends is sparse, and the local transmission rates in the context of effective treatment scale-up are unknown. In this work, we developed a novel Bayesian spatio-temporal epidemic model to estimate adult HIV prevalence, incidence and treatment coverage at the district level in Malawi from 2010 through the end of 2021. We found that HIV incidence decreased in every district of Malawi between 2010 and 2021 but the rate of decline varied by area. National-level treatment coverage more than tripled between 2010 and 2021 and more than doubled in every district. Large increases in treatment coverage were associated with declines in HIV transmission, with 12 districts having incidence-prevalence ratios of 0.03 or less (a previously suggested threshold for epidemic control). Across districts, incidence varied more than HIV prevalence and ART coverage, suggesting that the epidemic is becoming increasingly spatially concentrated. Our results highlight the success of the Malawi HIV treatment programme over the past decade, with large improvements in treatment coverage leading to commensurate declines in incidence. More broadly, we demonstrate the utility of spatially resolved HIV modelling in generalized epidemic settings. By estimating temporal changes in key epidemic indicators at a relatively fine spatial resolution, we were able to directly assess, for the first time, whether the ART scaleup in Malawi resulted in spatial gaps or hotspots. Regular use of this type of analysis

Journal article

Flaxman S, Whittaker C, Semenova E, Rashid T, Parks RM, Blenkinsop A, Unwin HJT, Mishra S, Bhatt S, Gurdasani D, Ratmann Oet al., 2023, Assessment of COVID-19 as the underlying cause of death among children and young people aged 0 to 19 years in the US., Jama Network Open, Vol: 6, Pages: 1-9, ISSN: 2574-3805

IMPORTANCE: COVID-19 was the underlying cause of death for more than 940 000 individuals in the US, including at least 1289 children and young people (CYP) aged 0 to 19 years, with at least 821 CYP deaths occurring in the 1-year period from August 1, 2021, to July 31, 2022. Because deaths among US CYP are rare, the mortality burden of COVID-19 in CYP is best understood in the context of all other causes of CYP death. OBJECTIVE: To determine whether COVID-19 is a leading (top 10) cause of death in CYP in the US. DESIGN, SETTING, AND PARTICIPANTS: This national population-level cross-sectional epidemiological analysis for the years 2019 to 2022 used data from the US Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (WONDER) database on underlying cause of death in the US to identify the ranking of COVID-19 relative to other causes of death among individuals aged 0 to 19 years. COVID-19 deaths were considered in 12-month periods between April 1, 2020, and August 31, 2022, compared with deaths from leading non-COVID-19 causes in 2019, 2020, and 2021. MAIN OUTCOMES AND MEASURES: Cause of death rankings by total number of deaths, crude rates per 100 000 population, and percentage of all causes of death, using the National Center for Health Statistics 113 Selected Causes of Death, for ages 0 to 19 and by age groupings (<1 year, 1-4 years, 5-9 years, 10-14 years, 15-19 years). RESULTS: There were 821 COVID-19 deaths among individuals aged 0 to 19 years during the study period, resulting in a crude death rate of 1.0 per 100 000 population overall; 4.3 per 100 000 for those younger than 1 year; 0.6 per 100 000 for those aged 1 to 4 years; 0.4 per 100 000 for those aged 5 to 9 years; 0.5 per 100 000 for those aged 10 to 14 years; and 1.8 per 100 000 for those aged 15 to 19 years. COVID-19 mortality in the time period of August 1, 2021, to July 31, 2022, was among the 10 leading causes of death in CYP aged 0 to 19 years in the US

Journal article

Mishra S, Flaxman S, Berah T, Zhu H, Pakkanen M, Bhatt Set al., 2022, πVAE: a stochastic process prior for Bayesian deep learning with MCMC, STATISTICS AND COMPUTING, Vol: 32, ISSN: 0960-3174

Journal article

Brito AF, Semonva E, Dudas G, Hassler GW, Kalinich CC, Kraemer MUG, Ho J, Houriyah T, Githinji G, Agoti CN, Matkin LE, Whittaker C, Bulgarian SARS-CoV-2 sequencing group, Communicable Diseases Genomics Network Australia and New Zealand, COVID-19 Impact Project, Danish Covid-19 Genome Consortium; Fiocruz COVID-19 Genomic Surveillance Network, GISAID core curation team, Network for Genomic Surveillance in South Africa NGS-SA, Swiss SARS-CoV-2 Sequencing Consortium, Howden BP, Sintchenko V, Zuckerman NS, Mor O, Blankenship HM, de Oliveira T, Lin RTP, Siqueira MM, Resende PC, Vasconcelos TR, Spilki FR, Aguiar RS, Alexiev I, Ivanov IN, Philipova I, Carrington CVF, Sahadeo NSD, Branda B, Gurry C, Maurer-Stroh S, Naidoo D, von Eije KJ, Perkins MD, von Kerkhove M, Hill SC, Sabino EC, Pybus OG, Dye C, Bhatt S, Flaxman S, Suchard MA, Grubaugh ND, Baele G, Faria NMet al., 2022, Global disparities in SARS-CoV-2 genomic surveillance, Nature Communications, Vol: 13, Pages: 1-13, ISSN: 2041-1723

Genomic sequencing is essential to track the evolution and spread of SARS-CoV-2, optimize molecular tests, treatments, vaccines, and guide public health responses. To investigate the global SARS-CoV-2 genomic surveillance, we used sequences shared via GISAID to estimate the impact of sequencing intensity and turnaround times (TAT) on variant detection in 189 countries. In two years of pandemic, 78% of high income countries (HICs) sequenced >0.5% of their COVID-19 cases, while 42% of low (LICs) and middle income countries (MICs) reached that mark. Around 25% of the genomes from HICs were submitted within 21 days, a pattern observed in 5% of the genomes from LICs and MICs. We found that sequencing around 0.5% of the cases, with a TAT <21 days, could provide a benchmark for SARS-CoV-2 genomic surveillance. Socioeconomic inequalities undermine the global pandemic preparedness, and efforts must be made to support LICs and MICs improve their local sequencing capacity.

Journal article

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

Journal article

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

Journal article

Ball JGC, Petrova K, Coomes DA, Flaxman Set al., 2022, Using deep convolutional neural networks to forecast spatial patterns of Amazonian deforestation, METHODS IN ECOLOGY AND EVOLUTION, Vol: 13, Pages: 2622-2634, ISSN: 2041-210X

Journal article

Hillis S, N'konzi J-P, Msemburi W, Cluver L, Villaveces A, Flaxman S, Unwin Het al., 2022, Orphanhood and caregiver loss among children based on new global excess COVID-19 death estimates, JAMA Pediatrics, Vol: 176, Pages: 1145-1148, ISSN: 1072-4710

The availability of new excess mortality data enables us to update global minimum estimates of COVID-19 orphanhood and caregiver death among children.1-4 Consequences for children can be devastating, including institutionalization, abuse, traumatic grief, mental health problems, adolescent pregnancy, poor educational outcomes, and chronic and infectious diseases.4,5 Global totals and country comparisons were previously hampered by inconsistencies in COVID-19 testing and incomplete death reporting. The new orphanhood estimates derived here based on excess deaths provide a comprehensive measure of COVID-19’s long-term impact on orphanhood and caregiver loss.

Journal article

Brizzi A, Whittaker C, Servo LMS, Hawryluk I, Prete CA, de Souza WM, Aguiar RS, Araujo LJT, Bastos LS, Blenkinsop A, Buss LF, Candido D, Castro MC, Costa SF, Croda J, de Souza Santos AA, Dye C, Flaxman S, Fonseca PLC, Geddes VEV, Gutierrez B, Lemey P, Levin AS, Mellan T, Bonfim DM, Miscouridou X, Mishra S, Monod M, Moreira FRR, Nelson B, Pereira RHM, Ranzani O, Schnekenberg RP, Semenova E, Sonabend R, Souza RP, Xi X, Sabino EC, Faria NR, Bhatt S, Ratmann Oet al., 2022, Author correction: spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals, Nature Medicine, Vol: 28, Pages: 1509-1509, ISSN: 1078-8956

Correction to: Nature Medicine https://doi.org/10.1038/s41591-022-01807-1, published online 10 May 2022.

Journal article

Zhang Q, Wild V, Filippi S, Flaxman S, Sejdinovic Det al., 2022, Bayesian kernel two-sample testing, Journal of Computational and Graphical Statistics, Vol: 31, Pages: 1164-1176, ISSN: 1061-8600

In modern data analysis, nonparametric measures of discrepancies between random variables are particularly important. The subject is well-studied in the frequentist literature, while the development in the Bayesian setting is limited where applications are often restricted to univariate cases. Here, we propose a Bayesian kernel two-sample testing procedure based on modeling the difference between kernel mean embeddings in the reproducing kernel Hilbert space using the framework established by Flaxman et al. The use of kernel methods enables its application to random variables in generic domains beyond the multivariate Euclidean spaces. The proposed procedure results in a posterior inference scheme that allows an automatic selection of the kernel parameters relevant to the problem at hand. In a series of synthetic experiments and two real data experiments (i.e., testing network heterogeneity from high-dimensional data and six-membered monocyclic ring conformation comparison), we illustrate the advantages of our approach. Supplementary materials for this article are available online.

Journal article

Semenova E, Xu Y, Howes A, Rashid T, Bhatt S, Mishra S, Flaxman Set al., 2022, PriorVAE: encoding spatial priors with variational autoencoders for small-area estimation., Journal of the Royal Society Interface, Vol: 19, Pages: 1-11, ISSN: 1742-5662

Gaussian processes (GPs), implemented through multivariate Gaussian distributions for a finite collection of data, are the most popular approach in small-area spatial statistical modelling. In this context, they are used to encode correlation structures over space and can generalize well in interpolation tasks. Despite their flexibility, off-the-shelf GPs present serious computational challenges which limit their scalability and practical usefulness in applied settings. Here, we propose a novel, deep generative modelling approach to tackle this challenge, termed PriorVAE: for a particular spatial setting, we approximate a class of GP priors through prior sampling and subsequent fitting of a variational autoencoder (VAE). Given a trained VAE, the resultant decoder allows spatial inference to become incredibly efficient due to the low dimensional, independently distributed latent Gaussian space representation of the VAE. Once trained, inference using the VAE decoder replaces the GP within a Bayesian sampling framework. This approach provides tractable and easy-to-implement means of approximately encoding spatial priors and facilitates efficient statistical inference. We demonstrate the utility of our VAE two-stage approach on Bayesian, small-area estimation tasks.

Journal article

Brizzi A, Whittaker C, Servo LMS, Hawryluk I, Prete Jr CA, de Souza WM, Aguiar RS, Araujo LJT, Bastos LS, Blenkinsop A, Buss LF, Candido D, Castro M, Costa S, Croda J, de Souza Santos AA, Dye C, Flaxman S, Fonseca PLC, Geddes VEV, Gutierrez B, Lemey P, Levin AS, Mellan T, Bonfim D, Miscoridou X, Mishra S, Monod M, Moreira FRR, Ranzani O, Schnekenberg R, Semenova E, Sonnabend R, Souza RP, Xi X, Sabino E, Faria NR, Bhatt S, Ratmann Oet al., 2022, Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals, Nature Medicine, Vol: 28, ISSN: 1078-8956

The SARS-CoV-2 Gamma variant of concern spread rapidly across Brazil since late 2020, causing substantial infection and death waves. We use individual-level patient records following hospitalisation with suspected or confirmed COVID-19 between 20 January 2020 and 26 July 2021 to document temporary, sweeping shocks in hospital fatality rates that followed Gamma’s spread across 14 state capitals, during which typically more than half of hospitalised patients aged 70 and over died. We show that such extensive shocks in COVID-19 in-hospital fatality rates also existed prior to detection of Gamma. Using a Bayesian fatality rate model, we find that the geographic and temporal fluctuations in Brazil’s COVID-19 in-hospital fatality rates were primarily associated with geographic inequities and shortages in healthcare capacity. We estimate that approximately half of the COVID-19 deaths in hospitals in the 14 cities could have been avoided without pre-pandemic geographic inequities and without pandemic healthcare pressure. Our results suggest that investments in healthcare resources, healthcare optimization, and pandemic preparedness are critical to minimize population wide mortality and morbidity caused by highly transmissible and deadly pathogens such as SARS-CoV-2, especially in low- and middle-income countries.

Journal article

Nyberg T, Ferguson NM, Nash SG, Webster HH, Flaxman S, Andrews N, Hinsley W, Bernal JL, Kall M, Bhatt S, Blomquist P, Zaidi A, Volz E, Aziz NA, Harman K, Funk S, Abbott S, Hope R, Charlett A, Chand M, Ghani AC, Seaman SR, Dabrera G, De Angelis D, Presanis AM, Thelwall Set al., 2022, Comparative analysis of the risks of hospitalisation and death associated with SARS-CoV-2 omicron (B.1.1.529) and delta (B.1.617.2) variants in England: a cohort study, The Lancet, Vol: 399, Pages: 1303-1312, ISSN: 0140-6736

BackgroundThe omicron variant (B.1.1.529) of SARS-CoV-2 has demonstrated partial vaccine escape and high transmissibility, with early studies indicating lower severity of infection than that of the delta variant (B.1.617.2). We aimed to better characterise omicron severity relative to delta by assessing the relative risk of hospital attendance, hospital admission, or death in a large national cohort.MethodsIndividual-level data on laboratory-confirmed COVID-19 cases resident in England between Nov 29, 2021, and Jan 9, 2022, were linked to routine datasets on vaccination status, hospital attendance and admission, and mortality. The relative risk of hospital attendance or admission within 14 days, or death within 28 days after confirmed infection, was estimated using proportional hazards regression. Analyses were stratified by test date, 10-year age band, ethnicity, residential region, and vaccination status, and were further adjusted for sex, index of multiple deprivation decile, evidence of a previous infection, and year of age within each age band. A secondary analysis estimated variant-specific and vaccine-specific vaccine effectiveness and the intrinsic relative severity of omicron infection compared with delta (ie, the relative risk in unvaccinated cases).FindingsThe adjusted hazard ratio (HR) of hospital attendance (not necessarily resulting in admission) with omicron compared with delta was 0·56 (95% CI 0·54–0·58); for hospital admission and death, HR estimates were 0·41 (0·39–0·43) and 0·31 (0·26–0·37), respectively. Omicron versus delta HR estimates varied with age for all endpoints examined. The adjusted HR for hospital admission was 1·10 (0·85–1·42) in those younger than 10 years, decreasing to 0·25 (0·21–0·30) in 60–69-year-olds, and then increasing to 0·47 (0·40–0·56) in those aged at leas

Journal article

Altman G, Ahuja J, Monrad JT, Dhaliwal G, Rogers-Smith C, Leech G, Snodin B, Sandbrink JB, Finnveden L, Norman AJ, Oehm SB, Sandkuehler JF, Kulveit J, Flaxman S, Gal Y, Mishra S, Bhatt S, Sharma M, Mindermann S, Brauner JMet al., 2022, A dataset of non-pharmaceutical interventions on SARS-CoV-2 in Europe, SCIENTIFIC DATA, Vol: 9

Journal article

Unwin HJT, Hillis S, Cluver L, Flaxman S, Goldman PS, Butchart A, Bachman G, Rawlings L, Donnelly CA, Ratmann O, Green P, Nelson CA, Blenkinsop A, Bhatt S, Desmond C, Villaveces A, Sherr Let al., 2022, Global, regional, and national minimum estimates of children affected by COVID-19-associated orphanhood and caregiver death, by age and family circumstance up to Oct 31, 2021: an updated modelling study, The Lancet Child & Adolescent Health, Vol: 6, Pages: 249-259, ISSN: 2352-4642

BACKGROUND: In the 6 months following our estimates from March 1, 2020, to April 30, 2021, the proliferation of new coronavirus variants, updated mortality data, and disparities in vaccine access increased the amount of children experiencing COVID-19-associated orphanhood. To inform responses, we aimed to model the increases in numbers of children affected by COVID-19-associated orphanhood and caregiver death, as well as the cumulative orphanhood age-group distribution and circumstance (maternal or paternal orphanhood). METHODS: We used updated excess mortality and fertility data to model increases in minimum estimates of COVID-19-associated orphanhood and caregiver deaths from our original study period of March 1, 2020-April 30, 2021, to include the new period of May 1-Oct 31, 2021, for 21 countries. Orphanhood was defined as the death of one or both parents; primary caregiver loss included parental death or the death of one or both custodial grandparents; and secondary caregiver loss included co-residing grandparents or kin. We used logistic regression and further incorporated a fixed effect for western European countries into our previous model to avoid over-predicting caregiver loss in that region. For the entire 20-month period, we grouped children by age (0-4 years, 5-9 years, and 10-17 years) and maternal or paternal orphanhood, using fertility contributions, and we modelled global and regional extrapolations of numbers of orphans. 95% credible intervals (CrIs) are given for all estimates. FINDINGS: The number of children affected by COVID-19-associated orphanhood and caregiver death is estimated to have increased by 90·0% (95% CrI 89·7-90·4) from April 30 to Oct 31, 2021, from 2 737 300 (95% CrI 1 976 100-2 987 000) to 5 200 300 (3 619 400-5 731 400). Between March 1, 2020, and Oct 31, 2021, 491 300 (95% CrI 485 100-497 900) children

Journal article

Bradley VC, Kuriwaki S, Isakov M, Sejdinovic D, Meng X-L, Flaxman Set al., 2021, Unrepresentative big surveys significantly overestimated US vaccine uptake, NATURE, Vol: 600, Pages: 695-+, ISSN: 0028-0836

Journal article

Scott L, Hsiao N-Y, Moyo S, Singh L, Tegally H, Dor G, Maes P, Pybus OG, Kraemer MUG, Semenova E, Bhatt S, Flaxman S, Faria NR, de Oliveira Tet al., 2021, Track Omicron's spread with molecular data, Science, Vol: 374, Pages: 1454-1455, ISSN: 0036-8075

Journal article

Ball J, Petrova K, Coomes DA, Flaxman Set al., 2021, Using deep convolutional neural networks to forecast spatial patterns of Amazonian deforestation

<jats:title>A<jats:sc>bstract</jats:sc></jats:title><jats:p><jats:list list-type="order"><jats:list-item><jats:p>Tropical forests are subject to diverse deforestation pressures but their conservation is essential to achieve global climate goals. Predicting the location of deforestation is challenging due to the complexity of the natural and human systems involved but accurate and timely forecasts could enable effective planning and on-the-ground enforcement practices to curb deforestation rates. New computer vision technologies based on deep learning can be applied to the increasing volume of Earth observation data to generate novel insights and make predictions with unprecedented accuracy.</jats:p></jats:list-item><jats:list-item><jats:p>Here, we demonstrate the ability of deep convolutional neural networks to learn spatiotemporal patterns of deforestation from a limited set of freely available global data layers, including multispectral satellite imagery, the Hansen maps of historic deforestation (2001-2020) and the ALOS JAXA digital surface model, to forecast future deforestation (2021). We designed four original deep learning model architectures, based on 2D Convolutional Neural Networks (2DCNN), 3D Convolutional Neural Networks (3DCNN), and Long Short-Term Memory (LSTM) Recurrent Neural Networks (RNN) to produce spatial maps that indicate the risk to each forested pixel (~30 m) in the landscape of becoming deforested within the next year. They were trained and tested on data from two ~80,000 km<jats:sup>2</jats:sup> tropical forest regions in the Southern Peruvian Amazon.</jats:p></jats:list-item><jats:list-item><jats:p>We found that the networks could predict the likely location of future deforestation to a high degree of accuracy. Our best performing model – a 3DCNN – had the highest pixel-wise accuracy (80-90%) when validated on 2

Journal article

Brito AF, Semenova E, Dudas G, Hassler GW, Kalinich CC, Kraemer MUG, Ho J, Tegally H, Githinji G, Agoti CN, Matkin LE, Whittaker C, Danish Covid-19 Genome Consortium, COVID-19 Impact Project, Network for Genomic Surveillance in South Africa NGS-SA, GISAID core curation team, Howden BP, Sintchenko V, Zuckerman NS, Mor O, Blankenship HM, de Oliveira T, Lin RTP, Siqueira MM, Resende PC, Vasconcelos ATR, Spilki FR, Aguiar RS, Alexiev I, Ivanov IN, Philipova I, Carrington CVF, Sahadeo NSD, Gurry C, Maurer-Stroh S, Naidoo D, von Eije KJ, Perkins MD, van Kerkhove M, Hill SC, Sabino EC, Pybus OG, Dye C, Bhatt S, Flaxman S, Suchard MA, Grubaugh ND, Baele G, Faria NRet al., 2021, Global disparities in SARS-CoV-2 genomic surveillance.

Genomic sequencing provides critical information to track the evolution and spread of SARS-CoV-2, optimize molecular tests, treatments and vaccines, and guide public health responses. To investigate the spatiotemporal heterogeneity in the global SARS-CoV-2 genomic surveillance, we estimated the impact of sequencing intensity and turnaround times (TAT) on variant detection in 167 countries. Most countries submit genomes >21 days after sample collection, and 77% of low and middle income countries sequenced <0.5% of their cases. We found that sequencing at least 0.5% of the cases, with a TAT <21 days, could be a benchmark for SARS-CoV-2 genomic surveillance efforts. Socioeconomic inequalities substantially impact our ability to quickly detect SARS-CoV-2 variants, and undermine the global pandemic preparedness.

Working paper

Hillis S, Blenkinsop A, Villaveces A, Annor F, Liburd L, Massetti G, Demissie Z, Mercy J, Nelson C, Cluver L, Flaxman S, Sherr L, Donnelly C, Ratmann O, Unwin Jet al., 2021, COVID-19-associated orphanhood and caregiver death in the United States, Pediatrics, Vol: 148, Pages: 1-13, ISSN: 0031-4005

Background: Most COVID-19 deaths occur among adults, not children, and attention has focused on mitigating COVID-19 burden among adults. However, a tragic consequence of adult deaths is that high numbers of children might lose their parents and caregivers to COVID-19-associated deaths.Methods: We quantified COVID-19-associated caregiver loss and orphanhood in the US and for each state using fertility and excess and COVID-19 mortality data. We assessed burden and rates of COVID-19-associated orphanhood and deaths of custodial and co-residing grandparents, overall and by race/ethnicity. We further examined variations in COVID-19-associated orphanhood by race/ethnicity for each state. Results: We found that from April 1, 2020 through June 30, 2021, over 140,000 children in the US experienced the death of a parent or grandparent caregiver. The risk of such loss was 1.1 to 4.5 times higher among children of racial and ethnic minorities, compared to Non-Hispanic White children. The highest burden of COVID-19-associated death of parents and caregivers occurred in Southern border states for Hispanic children, Southeastern states for Black children, and in states with tribal areas for American Indian/Alaska Native populations.Conclusions: We found substantial disparities in distributions of COVID-19-associated death of parents and caregivers across racial and ethnic groups. Children losing caregivers to COVID-19 need care and safe, stable, and nurturing families with economic support, quality childcare and evidence-based parenting support programs. There is an urgent need to mount an evidence-based comprehensive response focused on those children at greatest risk, in the states most affected.

Journal article

Dhar MS, Marwal R, Radhakrishnan VS, Ponnusamy K, Jolly B, Bhoyar RC, Sardana V, Naushin S, Rophina M, Mellan TA, Mishra S, Whittaker C, Fatihi S, Datta M, Singh P, Sharma U, Ujjainiya R, Bhatheja N, Divakar MK, Singh MK, Imran M, Senthivel V, Maurya R, Jha N, Mehta P, Vivekanand A, Sharma P, Arvinden VR, Chaudhary U, Soni N, Thukral L, Flaxman S, Bhatt S, Pandey R, Dash D, Faruq M, Lall H, Gogia H, Madan P, Kulkarni S, Chauhan H, Sengupta S, Kabra S, Gupta RK, Singh SK, Agrawal A, Rakshit Pet al., 2021, Genomic characterization and epidemiology of an emerging SARS-CoV-2 variant in Delhi, India, SCIENCE, Vol: 374, Pages: 995-+, ISSN: 0036-8075

Journal article

Mlcochova P, Kemp SA, Dhar MS, Papa G, Meng B, Ferreira IATM, Datir R, Collier DA, Albecka A, Singh S, Pandey R, Brown J, Zhou J, Goonawardane N, Mishra S, Whittaker C, Mellan T, Marwal R, Datta M, Sengupta S, Ponnusamy K, Radhakrishnan VS, Abdullahi A, Charles O, Chattopadhyay P, Devi P, Caputo D, Peacock T, Wattal C, Goel N, Satwik A, Vaishya R, Agarwal M, Chauhan H, Chauhan H, Dikid T, Gogia H, Lall H, Verma K, Dhar MS, Singh MK, Soni N, Meena N, Madan P, Singh P, Sharma R, Sharma R, Kabra S, Kumar S, Kumari S, Sharma U, Chaudhary U, Sivasubbu S, Scaria V, Oberoi JK, Raveendran R, Datta S, Das S, Maitra A, Chinnaswamy S, Biswas NK, Parida A, Raghav SK, Prasad P, Sarin A, Mayor S, Ramakrishnan U, Palakodeti D, Seshasayee ASN, Thangaraj K, Bashyam MD, Dalal A, Bhat M, Shouche Y, Pillai A, Abraham P, Potdar VA, Cherian SS, Desai AS, Pattabiraman C, Manjunatha MV, Mani RS, Udupi GA, Nandicoori V, Tallapaka KB, Sowpati DT, Kawabata R, Kawabata R, Morizako N, Sadamasu K, Asakura H, Nagashima M, Yoshimura K, Ito J, Kimura I, Uriu K, Kosugi Y, Suganami M, Oide A, Yokoyama M, Chiba M, Saito A, Butlertanaka EP, Tanaka YL, Ikeda T, Motozono C, Nasser H, Shimizu R, Yuan Y, Kitazato K, Hasebe H, Nakagawa S, Wu J, Takahashi M, Fukuhara T, Shimizu K, Tsushima K, Kubo H, Shirakawa K, Kazuma Y, Nomura R, Horisawa Y, Takaori-Kondo A, Tokunaga K, Ozono S, Baker S, Baker S, Dougan G, Hess C, Kingston N, Lehner PJ, Lyons PA, Matheson NJ, Owehand WH, Saunders C, Summers C, Thaventhiran JED, Toshner M, Weekes MP, Maxwell P, Shaw A, Bucke A, Calder J, Canna L, Domingo J, Elmer A, Fuller S, Harris J, Hewitt S, Kennet J, Jose S, Kourampa J, Meadows A, O'Brien C, Price J, Publico C, Rastall R, Ribeiro C, Rowlands J, Ruffolo V, Tordesillas H, Bullman B, Dunmore BJ, Fawke S, Graf S, Hodgson J, Huang C, Hunter K, Jones E, Legchenko E, Matara C, Martin J, Mescia F, O'Donnell C, Pointon L, Pond N, Shih J, Sutcliffe R, Tilly T, Treacy C, Tong Z, Wood J, Wylot M, Bergamaschi L, Betancourt A, Boweet al., 2021, SARS-CoV-2 B.1.617.2 Delta variant replication and immune evasion, NATURE, Vol: 599, Pages: 114-+, ISSN: 0028-0836

Journal article

Gurdasani D, Bhatt S, Costello A, Denaxas S, Flaxman S, Greenhalgh T, Griffin S, Hyde Z, Katzourakis A, McKee M, Michie S, Ratmann O, Reicher S, Scally G, Tomlinson C, Yates C, Ziauddeen H, Pagel Cet al., 2021, Vaccinating adolescents against SARS-CoV-2 in England: a risk-benefit analysis., Journal of the Royal Society of Medicine, Vol: 114, Pages: 513-524, ISSN: 0141-0768

OBJECTIVE: To offer a quantitative risk-benefit analysis of two doses of SARS-CoV-2 vaccination among adolescents in England. SETTING: England. DESIGN: Following the risk-benefit analysis methodology carried out by the US Centers for Disease Control, we calculated historical rates of hospital admission, Intensive Care Unit admission and death for ascertained SARS-CoV-2 cases in children aged 12-17 in England. We then used these rates alongside a range of estimates for incidence of long COVID, vaccine efficacy and vaccine-induced myocarditis, to estimate hospital and Intensive Care Unit admissions, deaths and cases of long COVID over a period of 16 weeks under assumptions of high and low case incidence. PARTICIPANTS: All 12-17 year olds with a record of confirmed SARS-CoV-2 infection in England between 1 July 2020 and 31 March 2021 using national linked electronic health records, accessed through the British Heart Foundation Data Science Centre. MAIN OUTCOME MEASURES: Hospitalisations, Intensive Care Unit admissions, deaths and cases of long COVID averted by vaccinating all 12-17 year olds in England over a 16-week period under different estimates of future case incidence. RESULTS: At high future case incidence of 1000/100,000 population/week over 16 weeks, vaccination could avert 4430 hospital admissions and 36 deaths over 16 weeks. At the low incidence of 50/100,000/week, vaccination could avert 70 hospital admissions and two deaths over 16 weeks. The benefit of vaccination in terms of hospitalisations in adolescents outweighs risks unless case rates are sustainably very low (below 30/100,000 teenagers/week). Benefit of vaccination exists at any case rate for the outcomes of death and long COVID, since neither have been associated with vaccination to date. CONCLUSIONS: Given the current (as at 15 September 2021) high case rates (680/100,000 population/week in 10-19 year olds) in England, our findings support vaccination of adolescents against SARS-CoV2.

Journal article

Rashid T, Bennett J, Paciorek C, Doyle Y, Pearson-Stuttard J, Flaxman S, Fecht D, Toledano M, Li G, Daby H, Johnson E, Davies B, Ezzati Met al., 2021, Life expectancy and risk of death in 6,791 English communities from 2002 to 2019: high-resolution spatiotemporal analysis of civil registration data, The Lancet Public Health, Vol: 6, Pages: e805-e816, ISSN: 2468-2667

Background: There is limited data with high spatial granularity on how mortality and longevity have changed in English communities. We estimated trends from 2002 to 2019 in life expectancy and probabilities of death at different ages for all 6,791 English middle-layer super output areas (MSOAs).Methods: We used de-identified data for all deaths in England from 2002 to 2019 with information on age, sex and MSOA of residence, and population counts by age, sex and MSOA. We used a Bayesian hierarchical model to obtain estimates of age-specific death rates by sharing information across age groups, MSOAs and years. We used life table methods to calculate life expectancy at birth and probabilities of death in different ages by sex and MSOA.Results: In 2002-2006 and 2006-2010, the vast majority of MSOAs experienced a life expectancy increase for both sexes. In 2010-2014, female life expectancy decreased in 351 (5%) of MSOAs. By 2014-2019, the number of MSOAs with declining life expectancy was 1,270 (19%) for women and 784 (12%) for men. The life expectancy increase from 2002 to 2019 was smaller where life expectancy had been lower in 2002, mostly northern urban MSOAs, and larger where life expectancy had been higher in 2002, mostly MSOAs in and around London. As a result of these trends, the gap between the 1st and 99th percentiles of MSOA life expectancy for women increased from 10.7 (95% credible interval 10.4-10.9) in 2002 to reach 14.2 (13.9-14.5) years in 2019, and from 11.5 (11.3-11.7) years to 13.6 (13.4-13.9) years for men. Interpretation: In many English communities, life expectancy declined in the years prior to the Covid-19 pandemic. To ensure that this trend does not continue there is a need for pro-equity economic and social policies, and greater investment on public health and healthcare.

Journal article

Bhatt S, 2021, Understanding the effectiveness of government interventions against the resurgence of COVID-19 in Europe, Nature Communications, Vol: 12, Pages: 1-12, ISSN: 2041-1723

As European governments face resurging waves of COVID-19, non-pharmaceutical interventions (NPIs) continue to be the primary tool for infection control. However, updated estimates of their relative effectiveness have been absent for Europe’s second wave, largely due to a lack of collated data that considers the increased subnational variation and diversity of NPIs. We collect the largest dataset of NPI implementation dates in Europe, spanning 114 subnational areas in 7 countries, with a systematic categorisation of interventions tailored to the second wave. Using a hierarchical Bayesian transmission model, we estimate the effectiveness of 17 NPIs from local case and death data. We manually validate the data, address limitations in modelling from previous studies, and extensively test the robustness of our estimates. The combined effect of all NPIs was smaller relative to estimates from the first half of 2020, indicating the strong influence of safety measures and individual protective behaviours--such as distancing--that persisted after the first wave. Closing specific businesses was highly effective. Gathering restrictions were highly effective but only for the strictest limits. We find smaller effects for closing educational institutions compared to the first wave, suggesting that safer operation of schools was possible with a set of stringent safety measures including testing and tracing, preventing mixing, and smaller classes. These results underscore that effectiveness estimates from the early stage of an epidemic are measured relative to pre-pandemic behaviour. Updated estimates are required to inform policy in an ongoing pandemic.

Journal article

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