Publications
434 results found
Thompson H, Mousa A, Dighe A, et al., 2021, SARS-CoV-2 setting-specific transmission rates: a systematic review and meta-analysis, Clinical Infectious Diseases, Vol: 73, Pages: e754-e764, ISSN: 1058-4838
Background Understanding the drivers of SARS-CoV-2 transmission is crucial for control policies but evidence of transmission rates in different settings remains limited. MethodsWe conducted a systematic review to estimate secondary attack rates (SAR) and observed reproduction numbers (Robs) in different settings exploring differences by age, symptom status, and duration of exposure. To account for additional study heterogeneity, we employed a Beta-Binomial model to pool SARs across studies and a Negative-binomial model to estimate Robs. ResultsHouseholds showed the highest transmission rates, with a pooled SAR of 21.1% (95%CI:17.4%-24.8%). SARs were significantly higher where the duration of household exposure exceeded 5 days compared with exposure of ≤5 days. SARs related to contacts at social events with family and friends were higher than those for low-risk casual contacts (5.9% vs. 1.2%). Estimates of SAR and Robs for asymptomatic index cases were approximately a seventh, and for pre-symptomatic two thirds of those for symptomatic index cases. We found some evidence for reduced transmission potential both from and to individuals under 20 years of age in the household context, which is more limited when examining all settings.ConclusionsOur results suggest that exposure in settings with familiar contacts increases SARS-CoV-2 transmission potential. Additionally, the differences observed in transmissibility by index case symptom status and duration of exposure have important implications for control strategies such as contact tracing, testing and rapid isolation of cases. There was limited data to explore transmission patterns in workplaces, schools, and care-homes, highlighting the need for further research in such settings.
Mishra S, Mindermann S, Sharma M, et al., 2021, Changing composition of SARS-CoV-2 lineages and rise of Delta variant in England, EClinicalMedicine, Vol: 39, Pages: 1-8, ISSN: 2589-5370
BackgroundSince 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.MethodsWe 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.FindingsAcross 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.InterpretationThe 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 effortsFundingNational Institute for Health Research, Medicines and Healthcare products Regulatory Agency, DeepMind, EPSRC, EA Funds programme, Open Philanthropy
Dorigatti I, Lavezzo E, Manuto L, et al., 2021, SARS-CoV-2 antibody dynamics and transmission from community-wide serological testing in the Italian municipality of Vo’, Nature Communications, Vol: 12, Pages: 1-11, ISSN: 2041-1723
In February and March 2020, two mass swab testing campaigns were conducted in Vo’, Italy. In May 2020, we tested 86% of the Vo’ population with three immuno-assays detecting antibodies against the spike and nucleocapsid antigens, a neutralisation assay and Polymerase Chain Reaction (PCR). Subjects testing positive to PCR in February/March or a serological assay in May were tested again in November. Here we report on the results of the analysis of the May and November surveys. We estimate a seroprevalence of 3.5% (95% Credible Interval (CrI): 2.8%-4.3%) in May. In November, 98.8% (95% Confidence Interval (CI): 93.7%-100.0%) of sera which tested positive in May still reacted against at least one antigen; 18.6% (95%CI:11.0%-28.5%) showed an increase of antibody or neutralisation reactivity from May. Analysis of the serostatus of the members of 1,118 households indicates a 26.0% (95%CrI:17.2%-36.9%) Susceptible-Infectious Transmission Probability. Contact tracing had limited impact on epidemic suppression.
Knock ES, Whittles LK, Lees JA, et al., 2021, Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England, Science Translational Medicine, Vol: 13, Pages: 1-12, ISSN: 1946-6234
We fitted a model of SARS-CoV-2 transmission in care homes and the community to regional surveillance data for England. Compared with other approaches, our model provides a synthesis of multiple surveillance data streams into a single coherent modelling framework allowing transmission and severity to be disentangled from features of the surveillance system. Of the control measures implemented, only national lockdown brought the reproduction number (Rteff ) below 1 consistently; if introduced one week earlier it could have reduced deaths in the first wave from an estimated 48,600 to 25,600 (95% credible interval [95%CrI]: 15,900-38,400). The infection fatality ratio decreased from 1.00% (95%CrI: 0.85%-1.21%) to 0.79% (95%CrI: 0.63%-0.99%), suggesting improved clinical care. The infection fatality ratio was higher in the elderly residing in care homes (23.3%, 95%CrI: 14.7%-35.2%) than those residing in the community (7.9%, 95%CrI: 5.9%-10.3%). On 2nd December 2020 England was still far from herd immunity, with regional cumulative infection incidence between 7.6% (95%CrI: 5.4%-10.2%) and 22.3% (95%CrI: 19.4%-25.4%) of the population. Therefore, any vaccination campaign will need to achieve high coverage and a high degree of protection in vaccinated individuals to allow non-pharmaceutical interventions to be lifted without a resurgence of transmission.
Toor J, Echeverria-Londono S, Li X, et al., 2021, Lives saved with vaccination for 10 pathogens across 112 countries in a pre-COVID-19 world, eLife, Vol: 10, ISSN: 2050-084X
Background: Vaccination is one of the most effective public health interventions. We investigate the impact of vaccination activities for Haemophilus influenzae type b, hepatitis B, human papillomavirus, Japanese encephalitis, measles, Neisseria meningitidis serogroup A, rotavirus, rubella, Streptococcus pneumoniae, and yellow fever over the years 2000-2030 across 112 countries. Methods: Twenty-one mathematical models estimated disease burden using standardised demographic and immunisation data. Impact was attributed to the year of vaccination through vaccine-activity-stratified impact ratios. Results: We estimate 97 (95%CrI[80, 120]) million deaths would be averted due to vaccination activities over 2000-2030, with 50 (95%CrI[41, 62]) million deaths averted by activities between 2000 and 2019. For children under-5 born between 2000 and 2030, we estimate 52 (95%CrI[41, 69]) million more deaths would occur over their lifetimes without vaccination against these diseases. Conclusions: This study represents the largest assessment of vaccine impact before COVID-19-related disruptions and provides motivation for sustaining and improving global vaccination coverage in the future. Funding: VIMC is jointly funded by Gavi, the Vaccine Alliance, and the Bill and Melinda Gates Foundation (BMGF) (BMGF grant number: OPP1157270 / INV-009125). Funding from Gavi is channelled via VIMC to the Consortium's modelling groups (VIMC-funded institutions represented in this paper: Imperial College London, London School of Hygiene and Tropical Medicine, Oxford University Clinical Research Unit, Public Health England, Johns Hopkins University, The Pennsylvania State University, Center for Disease Analysis Foundation, Kaiser Permanente Washington, University of Cambridge, University of Notre Dame, Harvard University, Conservatoire National des Arts et Métiers, Emory University, National University of Singapore). Funding from BMGF was used for salaries of the Consortium secretariat (auth
Gaythorpe K, Bhatia S, Mangal T, et al., 2021, Children’s role in the COVID-19 pandemic: a systematic review of early surveillance data on susceptibility, severity, and transmissibility, Scientific Reports, Vol: 11, Pages: 1-14, ISSN: 2045-2322
Background: SARS-CoV-2 infections have been reported in all age groups including infants, children, and adolescents. However, the role of children in the COVID-19 pandemic is still uncertain. This systematic review of early studies synthesises evidence on the susceptibility of children to SARS-CoV-2 infection, the severity and clinical outcomes in children with SARS-CoV-2 infection, and the transmissibility of SARS-CoV-2 by children in the early phases of the COVID-19 pandemic. Methods and findings: A systematic literature review was conducted in PubMed. Reviewers extracted data from relevant, peer-reviewed studies published up to July 4th 2020 during the first wave of the SARS-CoV-2 outbreak using a standardised form and assessed quality using the NIH Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. For studies included in the meta-analysis, we used a random effects model to calculate pooled estimates of the proportion of children considered asymptomatic or in a severe or critical state. We identified 2,775 potential studies of which 128 studies met our inclusion criteria; data were extracted from 99, which were then quality assessed. Finally, 29 studies were considered for the meta-analysis that included information of symptoms and/or severity, these were further assessed based on patient recruitment. Our pooled estimate of the proportion of test positive children who were asymptomatic was 21.1% (95% CI: 14.0 - 28.1%), based on 13 included studies, and the proportion of children with severe or critical symptoms was 3.8% (95% CI: 1.5 - 6.0%), based on 14 included studies. We did not identify any studies designed to assess transmissibility in children and found that susceptibility to infection in children was highly variable across studies.Conclusions: Children’s susceptibility to infection and onward transmissibility relative to adults is still unclear and varied widely between studies. However, it is evident that most children e
Williams LR, Ferguson NM, Donnelly CA, et al., 2021, Measuring vaccine efficacy against infection and disease in clinical trials: sources and magnitude of bias in COVID-19 vaccine efficacy estimates, Publisher: Cold Spring Harbor Laboratory
Background Phase III trials have estimated COVID-19 vaccine efficacy (VE) against symptomatic and asymptomatic infection. We explore the direction and magnitude of potential biases in these estimates and their implications for vaccine protection against infection and against disease in breakthrough infections.Methods We developed a mathematical model that accounts for natural and vaccine-induced immunity, changes in serostatus and imperfect sensitivity and specificity of tests for infection and antibodies. We estimated expected biases in VE against symptomatic, asymptomatic and any SARS-CoV-2 infections and against disease following infection for a range of vaccine characteristics and measurement approaches, and the likely overall biases for published trial results that included asymptomatic infections.Results VE against asymptomatic infection measured by PCR or serology is expected to be low or negative for vaccines that prevent disease but not infection. VE against any infection is overestimated when asymptomatic infections are less likely to be detected than symptomatic infections and the vaccine protects against symptom development. A competing bias towards underestimation arises for estimates based on tests with imperfect specificity, especially when testing is performed frequently. Our model indicates considerable uncertainty in Oxford-AstraZeneca ChAdOx1 and Janssen Ad26.COV2.S VE against any infection, with slightly higher than published, bias-adjusted values of 59.0% (95% uncertainty interval [UI] 38.4 to 77.1) and 70.9% (95% UI 49.8 to 80.7) respectively.Conclusion Multiple biases are likely to influence COVID-19 VE estimates, potentially explaining the observed difference between ChAdOx1 and Ad26.COV2.S vaccines. These biases should be considered when interpreting both efficacy and effectiveness study results.
Hamlet A, Ramos DG, Gaythorpe K, et al., 2021, Seasonality of agricultural exposure as an important predictor of seasonal yellow fever spillover in Brazil, Nature Communications, Vol: 12, Pages: 1-11, ISSN: 2041-1723
Yellow fever virus (YFV) is a zoonotic arbovirus affecting both humans and non-human primates (NHP’s) in Africa and South America. Previous descriptions of YF’s seasonality have relied purely on climatic explanations, despite the high proportion of cases occurring in people involved in agriculture. We use a series of random forest classification models to predict the monthly occurrence of YF in humans and NHP’s across Brazil, by fitting four classes of covariates related to the seasonality of climate and agriculture (planting and harvesting), crop output and host demography. We find that models captured seasonal YF reporting in humans and NHPs when they considered seasonality of agriculture rather than climate, particularly for monthly aggregated reports. These findings illustrate the seasonality of exposure, through agriculture, as a component of zoonotic spillover. Additionally, by highlighting crop types and anthropogenic seasonality, these results could directly identify areas at highest risk of zoonotic spillover.
Gaythorpe KAM, Toor J, Echeverria-Londono S, et al., 2021, Vaccines can save children with non-preventable diseases reply, LANCET, Vol: 397, Pages: 2251-2251, ISSN: 0140-6736
FitzJohn RG, Knock ES, Whittles LK, et al., 2021, Reproducible parallel inference and simulation of stochastic state space models using odin, dust, and mcstate [version 2; peer review: 2 approved], Wellcome Open Research, Vol: 5, ISSN: 2398-502X
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.
Morris AL, Ghani A, Ferguson N, 2021, Fine-scale estimation of key life-history parameters of malaria vectors: implications for next-generation vector control technologies, Parasites and Vectors, Vol: 14, Pages: 1-12, ISSN: 1756-3305
BackgroundMosquito control has the potential to significantly reduce malaria burden on a region, but to influence public health policy must also show cost-effectiveness. Gaps in our knowledge of mosquito population dynamics mean that mathematical modelling of vector control interventions have typically made simplifying assumptions about key aspects of mosquito ecology. Often, these assumptions can distort the predicted efficacy of vector control, particularly next-generation tools such as gene drive, which are highly sensitive to local mosquito dynamics.MethodsWe developed a discrete-time stochastic mathematical model of mosquito population dynamics to explore the fine-scale behaviour of egg-laying and larval density dependence on parameter estimation. The model was fitted to longitudinal mosquito population count data using particle Markov chain Monte Carlo methods.ResultsBy modelling fine-scale behaviour of egg-laying under varying density dependence scenarios we refine our life history parameter estimates, and in particular we see how model assumptions affect population growth rate (Rm), a crucial determinate of vector control efficacy.ConclusionsSubsequent application of these new parameter estimates to gene drive models show how the understanding and implementation of fine-scale processes, when deriving parameter estimates, may have a profound influence on successful vector control. The consequences of this may be of crucial interest when devising future public health policy.
McCabe R, Kont M, Schmit N, et al., 2021, Modelling ICU capacity under different epidemiological scenarios of the COVID-19 pandemic in three western European countries, International Journal of Epidemiology, Vol: 50, Pages: 753-767, ISSN: 0300-5771
Background: The coronavirus disease 2019 (COVID-19) pandemic has placed enormous strain on intensive care units (ICUs) in Europe. Ensuring access to care, irrespective of COVID-19 status, in winter 2020/21 is essential.Methods: An integrated model of hospital capacity planning and epidemiological projections of COVID-19 patients is used to estimate the demand for and resultant spare capacity of ICU beds, staff, and ventilators under different epidemic scenarios in France, Germany, and Italy across the 2020/21 winter period. The effect of implementing lockdowns triggered by different numbers of COVID-19 patients in ICU under varying levels of effectiveness is examined, using a ‘dual-demand’ (COVID-19 and non-COVID-19) patient model.Results: Without sufficient mitigation, we estimate that COVID-19 ICU patient numbers will exceed those seen in the first peak, resulting in substantial capacity deficits, with beds being consistently found to be the most constrained resource. Reactive lockdowns could lead to large improvements in ICU capacity during the winter season, with pressure being most effectively alleviated when lockdown is triggered early and sustained under a higher level of suppression. The success of such interventions also depends on baseline bed numbers and average non-COVID-19 patient occupancy.Conclusions: Reductions in capacity deficits under different scenarios must be weighed against the feasibility and drawbacks of further lockdowns. Careful, continuous decision-making by national policymakers will be required across the winter period 2020/21.
Hogan AB, Winskill P, Watson OJ, et al., 2021, Within-country age-based prioritisation, global allocation, and public health impact of a vaccine against SARS-CoV-2: a mathematical modelling analysis, Vaccine, Vol: 39, Pages: 2995-3006, ISSN: 0264-410X
The worldwide endeavour to develop safe and effective COVID-19 vaccines has been extraordinary, and vaccination is now underway in many countries. However, the doses available in 2021 are likely to be limited. We extended a mathematical model of SARS-CoV-2 transmission across different country settings to evaluate the public health impact of potential vaccines using WHO-developed target product profiles. We identified optimal vaccine allocation strategies within- and between-countries to maximise averted deaths under constraints on dose supply. We found that the health impact of SARS-CoV-2 vaccination depends on the cumulative population-level infection incidence when vaccination begins, the duration of natural immunity, the trajectory of the epidemic prior to vaccination, 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. However, with a larger supply, if vaccination can occur while other interventions are maintained, the optimal strategy switches to targeting key transmitters to indirectly protect the vulnerable. As supply increases, vaccines that reduce or block infection have a greater impact than those that prevent disease alone due to the indirect protection provided to high-risk groups. Given a 2 billion global dose supply in 2021, we find that a strategy in which doses are allocated to countries proportional to population size is close to optimal in averting deaths and aligns with the ethical principles agreed in pandemic preparedness planning.
Faria NR, Mellan TA, Whittaker C, et al., 2021, Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil, Science, Vol: 372, Pages: 815-821, ISSN: 0036-8075
Cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in Manaus, Brazil, resurged in late 2020 despite previously high levels of infection. Genome sequencing of viruses sampled in Manaus between November 2020 and January 2021 revealed the emergence and circulation of a novel SARS-CoV-2 variant of concern. Lineage P.1 acquired 17 mutations, including a trio in the spike protein (K417T, E484K, and N501Y) associated with increased binding to the human ACE2 (angiotensin-converting enzyme 2) receptor. Molecular clock analysis shows that P.1 emergence occurred around mid-November 2020 and was preceded by a period of faster molecular evolution. Using a two-category dynamical model that integrates genomic and mortality data, we estimate that P.1 may be 1.7- to 2.4-fold more transmissible and that previous (non-P.1) infection provides 54 to 79% of the protection against infection with P.1 that it provides against non-P.1 lineages. Enhanced global genomic surveillance of variants of concern, which may exhibit increased transmissibility and/or immune evasion, is critical to accelerate pandemic responsiveness.
Mishra S, Mindermann S, Sharma M, et al., 2021, Report 44: Recent trends in SARS-CoV-2 variants of concern in England, Report 44: Recent trends in SARS-CoV-2 variants of concern in England, Publisher: Imperial College London, 44
Since its emergence in Autumn 2020, the SARS-CoV-2 Variant of Concern (VOC) B.1.1.7 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, whether, and how these additional VOCs pose a threat in settings where B.1.1.7 is currently dominant is vital. This is particularly true for England, which has high coverage from vaccines that are likely more protective against B.1.1.7 than some other VOCs. We examine trends in B.1.1.7’s prevalence in London and other English regions using passive-case detection PCR data, cross-sectional community infection surveys, genomic surveillance, and wastewater monitoring. Our results suggest shifts in the composition of SARS-CoV-2 lineages driving transmission in England between March and April 2021. Local transmission of non-B.1.1.7 VOCs may be increasing; this warrants urgent further investigation.
Volz E, Mishra S, Chand M, et al., 2021, Assessing transmissibility of SARS-CoV-2 lineage B.1.1.7 in England, Nature, Vol: 593, Pages: 266-269, ISSN: 0028-0836
The SARS-CoV-2 lineage B.1.1.7, designated a Variant of Concern 202012/01 (VOC) by Public Health England1, originated in the UK in late Summer to early Autumn 20202. Whole genome SARS-CoV-2 sequence data collected from community-based diagnostic testing shows an unprecedentedly rapid expansion of the B.1.1.7 lineage during Autumn 2020, suggesting a selective advantage. We find that changes in VOC frequency inferred from genetic data correspond closely to changes inferred by S-gene target failures (SGTF) in community-based diagnostic PCR testing. Analysis of trends in SGTF and non-SGTF case numbers in local areas across England shows that the VOC has higher transmissibility than non-VOC lineages, even if the VOC has a different latent period or generation time. The SGTF data indicate a transient shift in the age composition of reported cases, with a larger share of under 20 year olds among reported VOC than non-VOC cases. Time-varying reproduction numbers for the VOC and cocirculating lineages were estimated using SGTF and genomic data. The best supported models did not indicate a substantial difference in VOC transmissibility among different age groups. There is a consensus among all analyses that the VOC has a substantial transmission advantage with a 50% to 100% higher reproduction number.
Dorigatti I, Lavezzo E, Manuto L, et al., 2021, SARS-CoV-2 antibody dynamics, within-household transmission and the impact of contact tracing from community-wide serological testing in the Italian Municipality of Vo’, Publisher: Elsevier BV
Background: In February and Mach 2020, two mass swab testing campaigns conducted in Vo’, Italy demonstrated the extent of asymptomatic SARS-CoV-2 infection and the feasibility of epidemic suppression.Methods: We tested 86% of the Vo’ population (2,602 subjects) in May with three immuno-assays detecting antibodies against the spike (S) and nucleocapsid (N) antigens, a neutralisation assay and Polymerase Chain Reaction (PCR). Subjects testing positive to PCR in February/March or a serological assay in May were tested again in November.Findings: Combining the results obtained with the three assays, we estimate a seroprevalence of 3.5% (95% Credible Interval (CrI) 2.8%-4.3%) in May. In November, all assays showed a reduction in antibody titres, though 98.8% (95% Confidence Interval (CI) 93.7%-100.0%) of sera still reacted against at least one antigen. Conversely, 18.6% (95% CI 11.0%-28.5%) showed a marked increase of antibody or viral neutralisation reactivity between May and November, linked to documented or likely re-exposures. We found significant differences in the magnitude and persistence of the antibody response by age group but not by symptom occurrence, hospitalisation, or sex. Analysis of the serostatus of 1,118 households indicated a 27.3% (95% CrI 19.2%-34.6%) probability of SARS-CoV-2 transmission among household members and that 81.8% (95% CrI 55.9%-95.2%) of transmission could be attributed to 20% of infections. Contact tracing correctly identified 44% of the infected subjects and had limited impact on the epidemic.Interpretation: We find evidence of antibody persistence up to nine months post infection. Different assays provided significantly different seroprevalence estimates, making it challenging to compare seroprevalence estimates globally. Due to the high population susceptibility and the limited impact of contact tracing, rigorous testing and improvements in contact tracing are essential to control SARS-CoV-2.Funding: Veneto Region, Med
Christen P, D'Aeth J, Lochen A, et al., 2021, The J-IDEA pandemic planner: a framework for implementing hospital provision interventions during the COVID-19 pandemic, Medical Care, Vol: 59, Pages: 371-378, ISSN: 0025-7079
Background : Planning for extreme surges in demand for hospital care of patientsrequiring urgent life-saving treatment for COVID-19, whilst retaining capacity for otheremergency conditions, is one of the most challenging tasks faced by healthcareproviders and policymakers during the pandemic. Health systems must be wellpreparedto cope with large and sudden changes in demand by implementinginterventions to ensure adequate access to care. We developed the first planning toolfor the COVID-19 pandemic to account for how hospital provision interventions (suchas cancelling elective surgery, setting up field hospitals, or hiring retired staff) will affectthe capacity of hospitals to provide life-saving care.Methods : We conducted a review of interventions implemented or considered in 12 European countries in March-April 2020, an evaluation of their impact on capacity, anda review of key parameters in the care of COVID-19 patients. This information wasused to develop a planner capable of estimating the impact of specific interventions ondoctors, nurses, beds and respiratory support equipment. We applied this to ascenario-based case study of one intervention, the set-up of field hospitals in England,under varying levels of COVID-19 patients.Results : The J-IDEA pandemic planner is a hospital planning tool that allows hospitaladministrators, policymakers and other decision-makers to calculate the amount ofcapacity in terms of beds, staff and crucial medical equipment obtained byimplementing the interventions. Flexible assumptions on baseline capacity, the numberof hospitalisations, staff-to-beds ratios, and staff absences due to COVID-19 make theplanner adaptable to multiple settings. The results of the case study show that whilefield hospitals alleviate the burden on the number of beds available, this intervention isfutile unless the deficit of critical care nurses is addressed first.Discussion : The tool supports decision-makers in delivering a fast and effectiveresponse to
Laydon D, Mishra S, Hinsley W, et al., 2021, Modelling the impact of the Tier system on SARS-CoV-2 transmission in the UK between the first and second national lockdowns, BMJ Open, Vol: 11, ISSN: 2044-6055
Objective To measure the effects of the tier system on the COVID-19 pandemic in the UK between the first and second national lockdowns, before the emergence of the B.1.1.7 variant of concern.Design This is a modelling study combining estimates of real-time reproduction number Rt (derived from UK case, death and serological survey data) with publicly available data on regional non-pharmaceutical interventions. We fit a Bayesian hierarchical model with latent factors using these quantities to account for broader national trends in addition to subnational effects from tiers.Setting The UK at lower tier local authority (LTLA) level. 310 LTLAs were included in the analysis.Primary and secondary outcome measures Reduction in real-time reproduction number Rt.Results Nationally, transmission increased between July and late September, regional differences notwithstanding. Immediately prior to the introduction of the tier system, Rt averaged 1.3 (0.9–1.6) across LTLAs, but declined to an average of 1.1 (0.86–1.42) 2 weeks later. Decline in transmission was not solely attributable to tiers. Tier 1 had negligible effects. Tiers 2 and 3, respectively, reduced transmission by 6% (5%–7%) and 23% (21%–25%). 288 LTLAs (93%) would have begun to suppress their epidemics if every LTLA had gone into tier 3 by the second national lockdown, whereas only 90 (29%) did so in reality.Conclusions The relatively small effect sizes found in this analysis demonstrate that interventions at least as stringent as tier 3 are required to suppress transmission, especially considering more transmissible variants, at least until effective vaccination is widespread or much greater population immunity has amassed.
Watson O, Alhaffar M, Mehchy Z, et al., 2021, Leveraging community mortality indicators to infer COVID-19 mortality and transmission dynamics in Damascus, Syria, Nature Communications, Vol: 12, Pages: 1-10, ISSN: 2041-1723
The COVID-19 pandemic has resulted in substantial mortality worldwide. However, to date, countries in the Middle East and Africa have reported considerably lower mortality rates than in Europe and the Americas. Motivated by reports of an overwhelmed health system, we estimate the likely under-ascertainment of COVID-19 mortality in Damascus, Syria. Using all-cause mortality data, we fit a mathematical model of COVID-19 transmission to reported mortality, estimating that 1.25% of COVID-19 deaths (sensitivity range 1.00% – 3.00%) have been reported as of 2 September 2020. By 2 September, we estimate that 4,380 (95% CI: 3,250 – 5,550) COVID-19 deaths in Damascus may have been missed, with 39.0% (95% CI: 32.5% – 45.0%) of the population in Damascus estimated to have been infected. Accounting for under-ascertainment corroborates reports of exceeded hospital bed capacity and is validated by community-uploaded obituary notifications, which confirm extensive unreported mortality in Damascus.
Ragonnet-Cronin M, Boyd O, Geidelberg L, et al., 2021, Genetic evidence for the association between COVID-19 epidemic severity and timing of non-pharmaceutical interventions, Nature Communications, Vol: 12, Pages: 1-7, ISSN: 2041-1723
Unprecedented public health interventions including travel restrictions and national lockdowns have been implemented to stem the COVID-19 epidemic, but the effectiveness of non- pharmaceutical interventions is still debated. We carried out a phylogenetic analysis of more than 29,000 publicly available whole genome SARS-CoV-2 sequences from 57 locations to estimate the time that the epidemic originated in different places. These estimates were examined in relation to the dates of the most stringent interventions in each location as well as to the number of cumulative COVID-19 deaths and phylodynamic estimates of epidemic size. Here we report that the time elapsed between epidemic origin and maximum intervention is associated with different measures of epidemic severity and explains 11% of the variance in reported deaths one month after the most stringent intervention. Locations where strong non-pharmaceutical interventions were implemented earlier experienced 30 much less severe COVID-19 morbidity and mortality during the period of study.
Hogan AB, Winskill P, Watson OJ, et al., 2021, Within-country age-based prioritisation, global allocation, and public health impact of a vaccine against SARS-CoV-2: a mathematical modelling analysis, Publisher: Cold Spring Harbor Laboratory
The worldwide endeavour to develop safe and effective COVID-19 vaccines has been extraordinary, and vaccination is now underway in many countries. However, the doses available in 2021 are likely to be limited. We extended a mathematical model of SARS-CoV-2 transmission across different country settings to evaluate the public health impact of potential vaccines using WHO-developed target product profiles. We identified optimal vaccine allocation strategies within- and between-countries to maximise averted deaths under constraints on dose supply. We found that the health impact of SARS-CoV-2 vaccination depends on the cumulative population-level infection incidence when vaccination begins, the duration of natural immunity, the trajectory of the epidemic prior to vaccination, 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. However, with a larger supply, if vaccination can occur while other interventions are maintained, the optimal strategy switches to targeting key transmitters to indirectly protect the vulnerable. As supply increases, vaccines that reduce or block infection have a greater impact than those that prevent disease alone due to the indirect protection provided to high-risk groups. Given a 2 billion global dose supply in 2021, we find that a strategy in which doses are allocated to countries proportional to population size is close to optimal in averting deaths and aligns with the ethical principles agreed in pandemic preparedness planning.
Gaythorpe KAM, Hamlet A, Jean K, et al., 2021, The global burden of yellow fever, ELIFE, Vol: 10, ISSN: 2050-084X
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Mishra S, Flaxman S, Volz E, et al., 2021, mrc-ide/sarscov2-b.1.1.7: Assessing transmissibility of SARS-CoV-2 lineage B.1.1.7 in England
Code for our nature paper Assessing transmissibility of SARS-CoV-2 lineage B.1.1.7 in England
Unwin HJT, Cori A, Imai N, et al., 2021, Using next generation matrices to estimate the proportion of infections that are not detected in an outbreak
<jats:p>Contact tracing, where exposed individuals are followed up to break ongoing transmission chains, is a key pillar of outbreak response for infectious disease outbreaks. Unfortunately, these systems are not fully effective, and infections can still go undetected as people may not remember all their contacts or contacts may not be traced successfully. A large proportion of undetected infections suggests poor contact tracing and surveillance systems, which could be a potential area of improvement for a disease response. In this paper, we present a method for estimating the proportion of infections that are not detected during an outbreak. Our method uses next generation matrices that are parameterized by linked contact tracing data and case line-lists. We validate the method using simulated data from an individual-based model and then investigate two case studies: the proportion of undetected infections in the SARS-CoV-2 outbreak in New Zealand during 2020 and the Ebola epidemic in Guinea during 2014. We estimate that only 5.26% of SARS-CoV-2 infections were not detected in New Zealand during 2020 (95% credible interval: 0.243 – 16.0%) but depending on assumptions 39.0% or 37.7% of Ebola infections were not detected in Guinea (95% credible intervals: 1.69 – 87.0% or 1.7 – 80.9%).</jats:p>
Laydon DJ, Mishra S, Hinsley WR, et al., 2021, Impact of the Tier system on SARS-CoV-2 transmission in the UK between the first and second national lockdowns
<jats:title>Abstract</jats:title><jats:sec><jats:title>Objective</jats:title><jats:p>Measure the effects of the Tier system on the COVID-19 pandemic in the UK between the first and second national lockdowns, before the emergence of the B.1.1.7 variant of concern.</jats:p></jats:sec><jats:sec><jats:title>Design</jats:title><jats:p>Modelling study combining estimates of the real-time reproduction number <jats:italic>R</jats:italic><jats:sub><jats:italic>t</jats:italic></jats:sub> (derived from UK case, death and serological survey data) with publicly available data on regional non-pharmaceutical interventions. We fit a Bayesian hierarchical model with latent factors using these quantities, to account for broader national trends in addition to subnational effects from Tiers.</jats:p></jats:sec><jats:sec><jats:title>Setting</jats:title><jats:p>The UK at Lower Tier Local Authority (LTLA) level.</jats:p></jats:sec><jats:sec><jats:title>Primary and secondary outcome measures</jats:title><jats:p>Reduction in real-time reproduction number <jats:italic>R</jats:italic><jats:sub><jats:italic>t</jats:italic></jats:sub>.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Nationally, transmission increased between July and late September, regional differences notwithstanding. Immediately prior to the introduction of the tier system, <jats:italic>R</jats:italic><jats:sub><jats:italic>t</jats:italic></jats:sub> averaged 1.3 (0.9 – 1.6) across LTLAs, but declined to an average of 1.1 (0.86 – 1.42) two weeks later. Decline in transmission was not solely attributable to Tiers. Tier 1 had negligible effects. Tiers 2 and 3 respectively reduced transmission by 6% (5%-7%) and 2
Nouvellet P, Bhatia S, Cori A, et al., 2021, Reduction in mobility and COVID-19 transmission, Nature Communications, Vol: 12, ISSN: 2041-1723
In response to the COVID-19 pandemic, countries have sought to control SARS-CoV-2 transmission by restricting population movement through social distancing interventions, thus reducing the number of contacts.Mobility data represent an important proxy measure of social distancing, and here, we characterise the relationship between transmission and mobility for 52 countries around the world.Transmission significantly decreased with the initial reduction in mobility in 73% of the countries analysed, but we found evidence of decoupling of transmission and mobility following the relaxation of strict control measures for 80% of countries. For the majority of countries, mobility explained a substantial proportion of the variation in transmissibility (median adjusted R-squared: 48%, interquartile range - IQR - across countries [27-77%]). Where a change in the relationship occurred, predictive ability decreased after the relaxation; from a median adjusted R-squared of 74% (IQR across countries [49-91%]) pre-relaxation, to a median adjusted R-squared of 30% (IQR across countries [12-48%]) post-relaxation.In countries with a clear relationship between mobility and transmission both before and after strict control measures were relaxed, mobility was associated with lower transmission rates after control measures were relaxed indicating that the beneficial effects of ongoing social distancing behaviours were substantial.
Sabino EC, Buss LF, Carvalho MPS, et al., 2021, Resurgence of COVID-19 in Manaus, Brazil, despite high seroprevalence, LANCET, Vol: 397, Pages: 452-455, ISSN: 0140-6736
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Ciavarella C, Ferguson NM, 2021, Deriving fine-scale models of human mobility from aggregated origin-destination flow data, PLoS Computational Biology, Vol: 17, Pages: 1-18, ISSN: 1553-734X
The spatial dynamics of epidemics are fundamentally affected by patterns of human mobility. Mobile phone call detail records (CDRs) are a rich source of mobility data, and allow semi-mechanistic models of movement to be parameterised even for resource-poor settings. While the gravity model typically reproduces human movement reasonably well at the administrative level spatial scale, past studies suggest that parameter estimates vary with the level of spatial discretisation at which models are fitted. Given that privacy concerns usually preclude public release of very fine-scale movement data, such variation would be problematic for individual-based simulations of epidemic spread parametrised at a fine spatial scale. We therefore present new methods to fit fine-scale mathematical mobility models (here we implement variants of the gravity and radiation models) to spatially aggregated movement data and investigate how model parameter estimates vary with spatial resolution. We use gridded population data at 1km resolution to derive population counts at different spatial scales (down to ∼ 5km grids) and implement mobility models at each scale. Parameters are estimated from administrative-level flow data between overnight locations in Kenya and Namibia derived from CDRs: where the model spatial resolution exceeds that of the mobility data, we compare the flow data between a particular origin and destination with the sum of all model flows between cells that lie within those particular origin and destination administrative units. Clear evidence of over-dispersion supports the use of negative binomial instead of Poisson likelihood for count data with high values. Radiation models use fewer parameters than the gravity model and better predict trips between overnight locations for both considered countries. Results show that estimates for some parameters change between countries and with spatial resolution and highlight how imperfect flow data and spatial population distr
Li X, Mukandavire C, Cucunuba ZM, et al., 2021, Estimating the health impact of vaccination against ten pathogens in 98 low-income and middle-income countries from 2000 to 2030: a modelling study, The Lancet, Vol: 397, Pages: 398-408, ISSN: 0140-6736
BackgroundThe past two decades have seen expansion of childhood vaccination programmes in low-income and middle-income countries (LMICs). We quantify the health impact of these programmes by estimating the deaths and disability-adjusted life-years (DALYs) averted by vaccination against ten pathogens in 98 LMICs between 2000 and 2030.Methods16 independent research groups provided model-based disease burden estimates under a range of vaccination coverage scenarios for ten pathogens: hepatitis B virus, Haemophilus influenzae type B, human papillomavirus, Japanese encephalitis, measles, Neisseria meningitidis serogroup A, Streptococcus pneumoniae, rotavirus, rubella, and yellow fever. Using standardised demographic data and vaccine coverage, the impact of vaccination programmes was determined by comparing model estimates from a no-vaccination counterfactual scenario with those from a reported and projected vaccination scenario. We present deaths and DALYs averted between 2000 and 2030 by calendar year and by annual birth cohort.FindingsWe estimate that vaccination of the ten selected pathogens will have averted 69 million (95% credible interval 52–88) deaths between 2000 and 2030, of which 37 million (30–48) were averted between 2000 and 2019. From 2000 to 2019, this represents a 45% (36–58) reduction in deaths compared with the counterfactual scenario of no vaccination. Most of this impact is concentrated in a reduction in mortality among children younger than 5 years (57% reduction [52–66]), most notably from measles. Over the lifetime of birth cohorts born between 2000 and 2030, we predict that 120 million (93–150) deaths will be averted by vaccination, of which 58 million (39–76) are due to measles vaccination and 38 million (25–52) are due to hepatitis B vaccination. We estimate that increases in vaccine coverage and introductions of additional vaccines will result in a 72% (59–81) reduction in lifetime mortality in t
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