Imperial College London

DrJohnLees

Faculty of MedicineSchool of Public Health

MRC Centre GIDA Research Fellow
 
 
 
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Contact

 

+44 (0)20 7594 2939j.lees Website

 
 
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Location

 

UG4Sir Alexander Fleming BuildingSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

50 results found

Croucher N, Harrow G, Lees J, Hanage W, Lipsitch M, Corander J, Colijn Cet al., 2021, Negative frequency-dependent selection and asymmetrical transformation stabilise multi-strain bacterial population structures, The ISME Journal: multidisciplinary journal of microbial ecology, ISSN: 1751-7362

Journal article

Knock ES, Whittles LK, Perez-Guzman PN, Bhatia S, Guntoro F, Watson OJ, Whittaker C, Ferguson NM, Cori A, Baguelin M, FitzJohn RG, Lees JAet al., 2020, Reproducible parallel inference and simulation of stochastic state space models using odin, dust, and mcstate, Wellcome Open Research, Vol: 5, Pages: 288-288

<ns3:p>State space models, including compartmental models, are used to model physical, biological and social phenomena in a broad range of scientific fields. A common way of representing the underlying processes in these models is as a system of stochastic processes which can be simulated forwards in time. Inference of model parameters based on observed time-series data can then be performed using sequential Monte Carlo techniques. However, using these methods for routine inference problems can be made difficult due to various engineering considerations: allowing model design to change in response to new data and ideas, writing model code which is highly performant, and incorporating all of this with up-to-date statistical techniques. Here, we describe a suite of packages in the R programming language designed to streamline the design and deployment of state space models, targeted at infectious disease modellers but suitable for other domains. Users describe their model in a familiar domain-specific language, which is converted into parallelised C++ code. A fast, parallel, reproducible random number generator is then used to run large numbers of model simulations in an efficient manner. We also provide standard inference and prediction routines, though the model simulator can be used directly if these do not meet the user’s needs. These packages provide guarantees on reproducibility and performance, allowing the user to focus on the model itself, rather than the underlying computation. The ability to automatically generate high-performance code that would be tedious and time-consuming to write and verify manually, particularly when adding further structure to compartments, is crucial for infectious disease modellers. Our packages have been critical to the development cycle of our ongoing real-time modelling efforts in the COVID-19 pandemic, and have the potential to do the same for models used in a number of different domains.</ns3:p>

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, 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

Kremer PHC, Lees JA, Ferwerda B, Bijlsma MW, MacAlasdair N, van der Ende A, Brouwer MC, Bentley SD, van de Beek Det al., 2020, Diversification in immunogenicity genes caused by selective pressures in invasive meningococci, MICROBIAL GENOMICS, Vol: 6, ISSN: 2057-5858

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

Sherrard-Smith E, Hogan AB, Hamlet A, Watson OJ, Whittaker C, Winskill P, Ali F, Mohammad AB, Uhomoibhi P, Maikore I, Ogbulafor N, Nikau J, Kont MD, Challenger JD, Verity R, Lambert B, Cairns M, Rao B, Baguelin M, Whittles LK, Lees JA, Bhatia S, Knock ES, Okell L, Slater HC, Ghani AC, Walker PGT, Okoko OO, Churcher TSet al., 2020, The potential public health consequences of COVID-19 on malaria in Africa., Nature Medicine, Vol: 26, Pages: 1411-1416, ISSN: 1078-8956

The burden of malaria is heavily concentrated in sub-Saharan Africa (SSA) where cases and deaths associated with COVID-19 are rising1. In response, countries are implementing societal measures aimed at curtailing transmission of SARS-CoV-22,3. Despite these measures, the COVID-19 epidemic could still result in millions of deaths as local health facilities become overwhelmed4. Advances in malaria control this century have been largely due to distribution of long-lasting insecticidal nets (LLINs)5, with many SSA countries having planned campaigns for 2020. In the present study, we use COVID-19 and malaria transmission models to estimate the impact of disruption of malaria prevention activities and other core health services under four different COVID-19 epidemic scenarios. If activities are halted, the malaria burden in 2020 could be more than double that of 2019. In Nigeria alone, reducing case management for 6 months and delaying LLIN campaigns could result in 81,000 (44,000-119,000) additional deaths. Mitigating these negative impacts is achievable, and LLIN distributions in particular should be prioritized alongside access to antimalarial treatments to prevent substantial malaria epidemics.

Journal article

Tonkin-Hill G, MacAlasdair N, Ruis C, Weimann A, Horesh G, Lees JA, Gladstone RA, Lo S, Beaudoin C, Floto RA, Frost SDW, Corander J, Bentley SD, Parkhill Jet al., 2020, Producing polished prokaryotic pangenomes with the Panaroo pipeline, GENOME BIOLOGY, Vol: 21, ISSN: 1474-760X

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

Lees JA, Mai TT, Galardini M, Wheeler NE, Horsfield ST, Parkhill J, Corander Jet al., 2020, Improved Prediction of Bacterial Genotype-Phenotype Associations Using Interpretable Pangenome-Spanning Regressions, MBIO, Vol: 11, ISSN: 2150-7511

Journal article

Nouvellet P, Bhatia S, Cori A, Ainslie K, Baguelin M, Bhatt S, Boonyasiri A, Brazeau N, Cattarino L, Cooper L, Coupland H, Cucunuba Perez Z, Cuomo-Dannenburg G, Dighe A, Djaafara A, Dorigatti I, Eales O, van Elsland S, Nscimento F, Fitzjohn R, Gaythorpe K, Geidelberg L, Grassly N, Green W, Hamlet A, Hauck K, Hinsley W, Imai N, Jeffrey B, Knock E, Laydon D, Lees J, Mangal T, Mellan T, Nedjati Gilani G, Parag K, Pons Salort M, Ragonnet-Cronin M, Riley S, Unwin H, Verity R, Vollmer M, Volz E, Walker P, Walters C, Wang H, Watson O, Whittaker C, Whittles L, Xi X, Ferguson N, Donnelly Cet al., 2020, Report 26: Reduction in mobility and COVID-19 transmission

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

Report

Harrow GL, Lees JA, Hanage WP, Lipsitch M, Corander J, Colijn C, Croucher NJet al., 2020, Negative frequency-dependent selection and asymmetrical transformation stabilise multi-strain bacterial population structures

<jats:title>Abstract</jats:title><jats:p><jats:italic>Streptococcus pneumoniae</jats:italic> can be split into multiple strains, each with a characteristic combination of core and accessory genome variation, able to co-circulate and compete within the same hosts. Previous analyses of epidemiological datasets suggested the short-term vaccine-associated dynamics of <jats:italic>S. pneumoniae</jats:italic> strains may be mediated through multi-locus negative frequency-dependent selection (NFDS), acting to maintain accessory loci at equilibrium frequencies. To test whether this model could explain how such multi-strain populations were generated, it was modified to incorporate recombination. The outputs of simulations featuring symmetrical recombination were compared with genomic data on locus frequencies and distributions between genotypes, pairwise genetic distances and tree shape. These demonstrated NFDS prevented the loss of variation through neutral drift, but generated unstructured populations of diverse isolates. Making recombination asymmetrical, favouring deletion of accessory loci over insertion, alongside multi-locus NFDS significantly improved the fit to genomic data. In a population at equilibrium, structuring into multiple strains was stable due to outbreeding depression, resulting from recombinants with reduced accessory genomes having lower fitness than their parental genotypes. As many bacteria inhibit the integration of insertions into their chromosomes, this combination of asymmetrical recombination and multi-locus NFDS may underlie the co-existence of strains within a single ecological niche.</jats:p>

Journal article

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

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

Report

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

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

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

Vollmer MAC, Mishra S, Unwin HJT, Gandy A, Mellan TA, Bradley V, Zhu H, Coupland H, Hawryluk I, Hutchinson M, Ratmann O, Monod M, Walker P, Whittaker C, Cattarino L, Ciavarella C, Cilloni L, Ainslie K, Baguelin M, Bhatia S, Boonyasiri A, Brazeau N, Charles G, Cooper LV, Cucunuba Z, Cuomo-Dannenburg G, Dighe A, Djaafara B, Eaton J, van Elsland SL, 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 D, Parag KV, Pickles M, Thompson HA, Verity R, Walters C, Wang H, Wang Y, Watson OJ, Whittles L, Xi X, Ghani AAM, Riley S, Okell LC, Donnelly CA, Ferguson NM, Dorigatti I, Flaxman S, Bhatt Set al., 2020, A sub-national analysis of the rate of transmission of COVID-19 in Italy

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

Journal article

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

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

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

Report

Gladstone RA, Lo SW, Goater R, Yeats C, Taylor B, Hadfield J, Lees JA, Croucher NJ, van Tonder AJ, Bentley LJ, Quah FX, Blaschke AJ, Pershing NL, Byington CL, Balaji V, Hryniewicz W, Sigauque B, Ravikumar KL, Almeida SCG, Ochoa TJ, Ho PL, du Plessis M, Ndlangisa KM, Cornick JE, Kwambana-Adams B, Benisty R, Nzenze SA, Madhi SA, Hawkins PA, Pollard AJ, Everett DB, Antonio M, Dagan R, Klugman KP, von Gottberg A, Metcalf BJ, Li Y, Beall BW, McGee L, Breiman RF, Aanensen DM, Bentley SDet al., 2020, Visualizing variation within Global Pneumococcal Sequence Clusters (GPSCs) and country population snapshots to contextualize pneumococcal isolates, MICROBIAL GENOMICS, Vol: 6, ISSN: 2057-5858

Journal article

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

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

Report

Lehtinen S, Chewapreecha C, Lees J, Hanage WP, Lipsitch M, Croucher NJ, Bentley SD, Turner P, Fraser C, Mostowy RJet al., 2020, Horizontal gene transfer rate is not the primary determinant of observed antibiotic resistance frequencies in Streptococcus pneumoniae, SCIENCE ADVANCES, Vol: 6, ISSN: 2375-2548

Journal article

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

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

Report

Binsker U, Lees JA, Hammond AJ, Weiser JNet al., 2020, Immune exclusion by naturally acquired secretory IgA against pneumococcal pilus-1, JOURNAL OF CLINICAL INVESTIGATION, Vol: 130, Pages: 927-941, ISSN: 0021-9738

Journal article

Tonkin-Hill G, MacAlasdair N, Ruis C, Weimann A, Horesh G, Lees JA, Gladstone RA, Lo S, Beaudoin C, Floto RA, Frost SDW, Corander J, Bentley SD, Parkhill Jet al., 2020, Producing Polished Prokaryotic Pangenomes with the Panaroo Pipeline

<jats:p>Population-level comparisons of prokaryotic genomes must take into account the substantial differences in gene content, resulting from frequent horizontal gene transfer, gene duplication and gene loss. However, the automated annotation of prokaryotic genomes is imperfect, and errors due to fragmented assemblies, contamination, diverse gene families and mis-assemblies accumulate over the population, leading to profound consequences when analysing the set of all genes found in a species. Here we introduce Panaroo, a graph based pangenome clustering tool that is able to account for many of the sources of error introduced during the annotation of prokaryotic genome assemblies. We verified our approach through extensive simulations of de novo assemblies using the infinitely many genes model and by analysing a number of publicly available large bacterial genome datasets. Using a highly clonal <jats:italic>Mycobacterium tuberculosis</jats:italic> dataset as a negative control case, we show that failing to account for annotation errors can lead to pangenome estimates that are dominated by error. We additionally demonstrate the utility of the improved graphical output provided by Panaroo by performing a pan-genome wide association study in <jats:italic>Neisseria gonorrhoeae</jats:italic> and by analysing gene gain and loss rates across 51 of the major global pneumococcal sequence clusters. Panaroo is freely available under an open source MIT licence at <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://github.com/gtonkinhill/panaroo">https://github.com/gtonkinhill/panaroo</jats:ext-link>.</jats:p>

Journal article

Lees JA, Tien Mai T, Galardini M, Wheeler NE, Corander Jet al., 2019, Improved inference and prediction of bacterial genotype-phenotype associations using pangenome-spanning regressions

<jats:title>ABSTRACT</jats:title><jats:p>Discovery of influential genetic variants and prediction of phenotypes such as antibiotic resistance are becoming routine tasks in bacterial genomics. Genome-wide association study (GWAS) methods can be applied to study bacterial populations, with a particular emphasis on alignment-free approaches, which are necessitated by the more plastic nature of bacterial genomes. Here we advance bacterial GWAS by introducing a computationally scalable joint modeling framework, where genetic variants covering the entire pangenome are compactly represented by unitigs, and the model fitting is achieved using elastic net penalization. In contrast to current leading GWAS approaches, which test each genotype-phenotype association separately for each variant, our joint modelling approach is shown to lead to increased statistical power while maintaining control of the false positive rate. Our inference procedure also delivers an estimate of the narrow-sense heritability, which is gaining considerable interest in studies of bacteria. Using an extensive set of state-of-the-art bacterial population genomic datasets we demonstrate that our approach performs accurate phenotype prediction, comparable to popular machine learning methods, while retaining both interpretability and computational efficiency. We expect that these advances will pave the way for the next generation of high-powered association and prediction studies for an increasing number of bacterial species.</jats:p>

Journal article

Pensar J, Puranen S, Arnold B, MacAlasdair N, Kuronen J, Tonkin-Hill G, Pesonen M, Xu Y, Sipola A, Sanchez-Buso L, Lees JA, Chewapreechi C, Bentley SD, Harris SR, Parkhill J, Croucher NJ, Corander Jet al., 2019, Genome-wide epistasis and co-selection study using mutual information, NUCLEIC ACIDS RESEARCH, Vol: 47, ISSN: 0305-1048

Journal article

Corander J, Croucher N, Harris S, Lees J, Tonkin-Hill Get al., 2019, Bacterial Population Genomics, Handbook of Statistical Genomics, Editors: Balding, Moltke, Marioni, Publisher: John Wiley & Sons, ISBN: 9781119429142

The Handbook of Statistical Genomics is an excellent introductory text for advanced graduate students and early-career researchers involved in statistical genetics.

Book chapter

Lo SW, Gladstone RA, van Tonder AJ, Lees JA, du Plessis M, Benisty R, Givon-Lavi N, Hawkins PA, Cornick JE, Kwambana-Adams B, Law PY, Ho PL, Antonio M, Everett DB, Dagan R, von Gottberg A, Klugman KP, McGee L, Breiman RF, Bentley SD, Brooks AW, Corso A, Davydov A, Maguire A, Pollard A, Kiran A, Skoczynska A, Moiane B, Beall B, Sigauque B, Aanensen D, Lehmann D, Faccone D, Faster-Nyarko E, Bojang E, Egorova E, Voropaeva E, Sampane-Donkor E, Sadowy E, Bigogo G, Mucavele H, Belabbes H, Diawara I, Moisi J, Verani J, Keenan J, Nair JN, Bhai T, Ndlangisa KM, Zerouali K, Ravikumar KL, Titov L, De Gouveia L, Alaerts M, Ip M, Brandileone MCDC, Hasanuzzaman M, Paragi M, Nurse-Lucas M, Ali M, Elmdaghri N, Croucher N, Wolter N, Porat N, Eser OK, Akpaka PE, Turner P, Gagetti P, Tientcheu P-E, Carter PE, Mostowy R, Kandasamy R, Ford R, Henderson R, Malaker R, Shakoor S, Almeida SCG, Saha SK, Doiphode S, Madhi SA, Sekaran SD, Srifuengfung S, Obaro S, Clarke SC, Nzenze SA, Kastrin T, Ochoa TJ, Balaji V, Hryniewicz W, Urban Yet al., 2019, Pneumococcal lineages associated with serotype replacement and antibiotic resistance in childhood invasive pneumococcal disease in the post-PCV13 era: an international whole-genome sequencing study, LANCET INFECTIOUS DISEASES, Vol: 19, Pages: 759-769, ISSN: 1473-3099

Journal article

Tonkin-Hill G, Lees JA, Bentley SD, Frost SDW, Corander Jet al., 2019, y Fast hierarchical Bayesian analysis of population structure, NUCLEIC ACIDS RESEARCH, Vol: 47, Pages: 5539-5549, ISSN: 0305-1048

Journal article

Davies MR, McIntyre L, Mutreja A, Lacey JA, Lees JA, Towers RJ, DuchĂȘne S, Smeesters PR, Frost HR, Price DJ, Holden MTG, David S, Giffard PM, Worthing KA, Seale AC, Berkley JA, Harris SR, Rivera-Hernandez T, Berking O, Cork AJ, Torres RSLA, Lithgow T, Strugnell RA, Bergmann R, Nitsche-Schmitz P, Chhatwal GS, Bentley SD, Fraser JD, Moreland NJ, Carapetis JR, Steer AC, Parkhill J, Saul A, Williamson DA, Currie BJ, Tong SYC, Dougan G, Walker MJet al., 2019, Atlas of group A streptococcal vaccine candidates compiled using large-scale comparative genomics, Nature Genetics, Vol: 51, Pages: 1035-1043, ISSN: 1061-4036

Journal article

Lees JA, Ferwerda B, Kremer PHC, Wheeler NE, Seron MV, Croucher NJ, Gladstone RA, Bootsma HJ, Rots NY, Wijmega-Monsuur AJ, Sanders EAM, Trzcinski K, Wyllie AL, Zwinderman AH, van den Berg LH, van Rheenen W, Veldink JH, Harboe ZB, Lundbo LF, de Groot LCPGM, van Schoor NM, van der Velde N, Angquist LH, Sorensen TIA, Nohr EA, Mentzer AJ, Mills TC, Knight JC, du Plessis M, Nzenze S, Weiser JN, Parkhill J, Madhi S, Benfield T, von Gottberg A, van der Ende A, Brouwer MC, Barrett JC, Bentley SD, van de Beek Det al., 2019, Joint sequencing of human and pathogen genomes reveals the genetics of pneumococcal meningitis, NATURE COMMUNICATIONS, Vol: 10, ISSN: 2041-1723

Journal article

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