Publications
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Ali HA, Hartner A-M, Echeverria-Londono S, et al., 2022, Vaccine equity in low and middle income countries: a systematic review and meta-analysis, INTERNATIONAL JOURNAL FOR EQUITY IN HEALTH, Vol: 21
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- Citations: 24
Imai N, Gaythorpe K, Bhatia S, et al., 2022, COVID-19 in Japan, January – March 2020: insights from the first three months of the epidemic, BMC Infectious Diseases, Vol: 22, ISSN: 1471-2334
Background:Understanding the characteristics and natural history of novel pathogens is crucial to inform successful control measures. Japan was one of the first affected countries in the COVID-19 pandemic reporting their first case on 14 January 2020. Interventions including airport screening, contact tracing, and cluster investigations were quickly implemented. Here we present insights from the first 3 months of the epidemic in Japan based on detailed case data. Methods:We conducted descriptive analyses based on information systematically extracted from individual case reports from 13 January to 31 March 2020 including patient demographics, date of report and symptom onset, symptom progression, travel history, and contact type. We analysed symptom progression and estimated the time-varying reproduction number, Rt, correcting for epidemic growth using an established Bayesian framework. Key delays and the age-specific probability of transmission were estimated using data on exposures and transmission pairs. Results:The corrected fitted mean onset-to-reporting delay after the peak was 4 days (standard deviation: ±2 days). Early transmission was driven primarily by returning travellers with Rt peaking at 2.4 (95%CrI:1.6, 3.3) nationally. In the final week of the trusted period (16 – 23 March 2020), Rt accounting for importations diverged from overall Rt at 1.1 (95% CrI: 1.0, 1.2) compared to 1.5 (95% CrI: 1.3, 1.6) respectively. Household (39.0%) and workplace (11.6%) exposures were the most frequently reported potential source of infection. The estimated probability of transmission was assortative by age with individuals more likely to infect, and be infected by, contacts in a similar age group to them. Across all age groups, cases most frequently onset with cough, fever, and fatigue. There were no reported cases of patients <20 years old developing pneumonia or severe respiratory symptoms.Conclusions:Information collected in the early phases of an out
Okell L, Brazeau NF, Verity R, et al., 2022, Estimating the COVID-19 infection fatality ratio accounting for seroreversion using statistical modelling, Communications Medicine, Vol: 2, Pages: 1-13, ISSN: 2730-664X
Background: The infection fatality ratio (IFR) is a key statistic for estimating the burden of coronavirus disease 2019 (COVID-19) and has been continuously debated throughout the COVID-19 pandemic. The age-specific IFR can be quantified using antibody surveys to estimate total infections, but requires consideration of delay-distributions from time from infection to seroconversion, time to death, and time to seroreversion (i.e. antibody waning) alongside serologic test sensitivity and specificity. Previous IFR estimates have not fully propagated uncertainty or accounted for these potential biases, particularly seroreversion. Methods: We built a Bayesian statistical model that incorporates these factors and applied this model to simulated data and 10 serologic studies from different countries. Results: We demonstrate that seroreversion becomes a crucial factor as time accrues but is less important during first-wave, short-term dynamics. We additionally show that disaggregating surveys by regions with higher versus lower disease burden can inform serologic test specificity estimates. The overall IFR in each setting was estimated at 0.49 -2.53%.Conclusion: We developed a robust statistical framework to account for full uncertainties in the parameters determining IFR. We provide code for others to apply these methods to further datasets and future epidemics.
Dabrera G, Allen H, Zaidi A, et al., 2022, Assessment of mortality and hospital admissions associated with confirmed infection with SARS-CoV-2 Alpha variant: a matched cohort and time-to-event analysis, England, October to December 2020, EUROSURVEILLANCE, Vol: 27, ISSN: 1025-496X
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- Citations: 5
Andrews N, Stowe J, Kirsebom F, et al., 2022, Covid-19 Vaccine Effectiveness against the Omicron (B.1.1.529) Variant, NEW ENGLAND JOURNAL OF MEDICINE, Vol: 386, Pages: 1532-1546, ISSN: 0028-4793
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- Citations: 1098
Laydon DJ, Cauchemez S, Hinsley WR, et al., 2022, Prophylactic and reactive vaccination strategies for healthcare workers against MERS-CoV
<jats:title>Abstract</jats:title><jats:p>Several vaccines candidates are in development against Middle East respiratory syndrome–related coronavirus (MERS-CoV), which remains a major public health concern. Using individual-level data on the 2013-2014 Kingdom of Saudi Arabia epidemic, we employ counterfactual analysis on inferred transmission trees (“who-infected-whom”) to assess potential vaccine impact. We investigate the conditions under which prophylactic “proactive” campaigns would outperform “reactive” campaigns (i.e. vaccinating either before or in response to the next outbreak), focussing on healthcare workers. Spatial scale is crucial: if vaccinating healthcare workers in response to outbreaks at their hospital only, proactive campaigns perform better, unless efficacy has waned significantly. However, campaigns that react at regional or national level consistently outperform proactive campaigns. Measures targeting the animal reservoir reduce transmission linearly, albeit with wide uncertainty. Substantial reduction of MERS-CoV morbidity and mortality is possible when vaccinating healthcare workers, underlining the need for at-risk countries to stockpile vaccines when available.</jats:p>
Nyberg T, Ferguson NM, Nash SG, et 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
Haw D, Forchini G, Doohan P, et al., 2022, Optimizing social and economic activity while containing SARS-CoV-2 transmission using DAEDALUS, Nature Computational Science, Vol: 2, Pages: 223-233, ISSN: 2662-8457
To study the trade-off between economic, social and health outcomes in the management of a pandemic, DAEDALUS integrates a dynamic epidemiological model of SARS-CoV-2 transmission with a multi-sector economic model, reflecting sectoral heterogeneity in transmission and complex supply chains. The model identifies mitigation strategies that optimize economic production while constraining infections so that hospital capacity is not exceeded but allowing essential services, including much of the education sector, to remain active. The model differentiates closures by economic sector, keeping those sectors open that contribute little to transmission but much to economic output and those that produce essential services as intermediate or final consumption products. In an illustrative application to 63 sectors in the United Kingdom, the model achieves an economic gain of between £161 billion (24%) and £193 billion (29%) compared to a blanket lockdown of non-essential activities over six months. Although it has been designed for SARS-CoV-2, DAEDALUS is sufficiently flexible to be applicable to pandemics with different epidemiological characteristics.
Killingley B, Mann AJ, Kalinova M, et al., 2022, Safety, tolerability and viral kinetics during SARS-CoV-2 human challenge in young adults, Nature Medicine, Vol: 28, Pages: 1031-1041, ISSN: 1078-8956
Since its emergence in 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused hundreds of millions of cases and continues to circulate globally. To establish a novel SARS-CoV-2 human challenge model that enables controlled investigation of pathogenesis, correlates of protection and efficacy testing of forthcoming interventions, 36 volunteers aged 18–29 years without evidence of previous infection or vaccination were inoculated with 10 TCID50 of a wild-type virus (SARS-CoV-2/human/GBR/484861/2020) intranasally in an open-label, non-randomized study (ClinicalTrials.gov identifier NCT04865237; funder, UK Vaccine Taskforce). After inoculation, participants were housed in a high-containment quarantine unit, with 24-hour close medical monitoring and full access to higher-level clinical care. The study’s primary objective was to identify an inoculum dose that induced well-tolerated infection in more than 50% of participants, with secondary objectives to assess virus and symptom kinetics during infection. All pre-specified primary and secondary objectives were met. Two participants were excluded from the per-protocol analysis owing to seroconversion between screening and inoculation, identified post hoc. Eighteen (~53%) participants became infected, with viral load (VL) rising steeply and peaking at ~5 days after inoculation. Virus was first detected in the throat but rose to significantly higher levels in the nose, peaking at ~8.87 log10 copies per milliliter (median, 95% confidence interval (8.41, 9.53)). Viable virus was recoverable from the nose up to ~10 days after inoculation, on average. There were no serious adverse events. Mild-to-moderate symptoms were reported by 16 (89%) infected participants, beginning 2–4 days after inoculation, whereas two (11%) participants remained asymptomatic (no reportable symptoms). Anosmia or dysosmia developed more slowly in 15 (83%) participants. No quantitative cor
Green WD, Ferguson NM, Cori A, 2022, Inferring the reproduction number using the renewal equation in heterogeneous epidemics, Journal of the Royal Society Interface, Vol: 19, ISSN: 1742-5662
Real-time estimation of the reproduction number has become the focus ofmodelling groups around the world as the SARS-CoV-2 pandemic unfolds.One of the most widely adopted means of inference of the reproductionnumber is via the renewal equation, which uses the incidence of infectionand the generation time distribution. In this paper, we derive a multi-typeequivalent to the renewal equation to estimate a reproduction numberwhich accounts for heterogeneity in transmissibility including throughasymptomatic transmission, symptomatic isolation and vaccination. Wedemonstrate how use of the renewal equation that misses these heterogeneitiescan result in biased estimates of the reproduction number. While thebias is small with symptomatic isolation, it can be much larger with asymptomatictransmission or transmission from vaccinated individuals if thesegroups exhibit substantially different generation time distributions to unvaccinatedsymptomatic transmitters, whose generation time distribution isoften well defined. The bias in estimate becomes larger with greater populationsize or transmissibility of the poorly characterized group. We applyour methodology to Ebola in West Africa in 2014 and the SARS-CoV-2 inthe UK in 2020–2021.
Imai N, Gaythorpe KAM, Bhatia S, et al., 2022, COVID-19 in Japan: insights from the first three months of the epidemic, Publisher: Cold Spring Harbor Laboratory
BackgroundUnderstanding the characteristics and natural history of novel pathogens is crucial to inform successful control measures. Japan was one of the first affected countries in the COVID-19 pandemic reporting their first case on 14 January 2020. Interventions including airport screening, contact tracing, and cluster investigations were quickly implemented. Here we present insights from the first 3 months of the epidemic in Japan based on detailed case data. MethodsWe conducted descriptive analyses based on information systematically extracted from individual case reports from 13 January to 31 March 2020 including patient demographics, date of report and symptom onset, symptom progression, travel history, and contact type. We analysed symptom progression and estimated the time-varying reproduction number, Rt, correcting for epidemic growth using an established Bayesian framework. Key delays and the age-specific probability of transmission were estimated using data on exposures and transmission pairs. ResultsThe corrected fitted mean onset-to-reporting delay after the peak was 4 days (standard deviation: ±2 days). Early transmission was driven primarily by returning travellers with Rt peaking at 2.4 (95%CrI:1.6, 3.3) nationally. In the final week of the trusted period, Rt accounting for importations diverged from overall Rt at 1.1 (95% CrI: 1.0, 1.2) compared to 1.5 (95% CrI: 1.3, 1.6) respectively. Household (39.0%) and workplace (11.6%) exposures were the most frequently reported potential source of infection. The estimated probability of transmission was assortative by age. Across all age groups, cases most frequently onset with cough, fever, and fatigue. There were no reported cases of patients <20 years old developing pneumonia or severe respiratory symptoms.ConclusionsInformation collected in the early phases of an outbreak are important in characterising any novel pathogen. Timely recognition of key symptoms and high-risk settings for transmi
Johnson R, Djaafara B, Haw D, et al., 2022, Report 51: Valuing lives, education and the economy in an epidemic: Societal benefit of SARS-CoV-2 booster vaccinations in Indonesia
Killingley B, Mann A, Kalinova M, et al., 2022, Safety, tolerability and viral kinetics during SARS-CoV-2 human challenge
<jats:title>Abstract</jats:title> <jats:p>To establish a novel SARS-CoV-2 human challenge model, 36 volunteers aged 18-29 years without evidence of previous infection or vaccination were inoculated with 10 TCID<jats:sub>50</jats:sub> of a wild-type virus (SARS-CoV-2/human/GBR/484861/2020) intranasally. Two participants were excluded from per protocol analysis due to seroconversion between screening and inoculation. Eighteen (~53%) became infected, with viral load (VL) rising steeply and peaking at ~5 days post-inoculation. Virus was first detected in the throat but rose to significantly higher levels in the nose, peaking at ~8.87 log<jats:sub>10</jats:sub> copies/ml (median, 95% CI [8.41,9.53). Viable virus was recoverable from the nose up to ~10 days post-inoculation, on average. There were no serious adverse events. Mild-to-moderate symptoms were reported by 16 (89%) infected individuals, beginning 2-4 days post-inoculation. Anosmia/dysosmia developed more gradually in 12 (67%) participants. No quantitative correlation was noted between VL and symptoms, with high VLs even in asymptomatic infection, followed by the development of serum spike-specific and neutralising antibodies. However, lateral flow results were strongly associated with viable virus and modelling showed that twice-weekly rapid tests could diagnose infection before 70-80% of viable virus had been generated. Thus, in this first SARS-CoV-2 human challenge study, no serious safety signals were detected and the detailed characteristics of early infection and their public health implications were shown. ClinicalTrials.gov identifier: NCT04865237.</jats:p>
Singanayagam A, Hakki S, Dunning J, et al., 2022, Community transmission and viral load kinetics of the SARS-CoV-2 delta (B.1.617.2) variant in vaccinated and unvaccinated individuals in the UK: a prospective, longitudinal, cohort study., The Lancet. Infectious diseases, Vol: 22, Pages: 183-195, ISSN: 1473-3099
<h4>Background</h4>The SARS-CoV-2 delta (B.1.617.2) variant is highly transmissible and spreading globally, including in populations with high vaccination rates. We aimed to investigate transmission and viral load kinetics in vaccinated and unvaccinated individuals with mild delta variant infection in the community.<h4>Methods</h4>Between Sept 13, 2020, and Sept 15, 2021, 602 community contacts (identified via the UK contract-tracing system) of 471 UK COVID-19 index cases were recruited to the Assessment of Transmission and Contagiousness of COVID-19 in Contacts cohort study and contributed 8145 upper respiratory tract samples from daily sampling for up to 20 days. Household and non-household exposed contacts aged 5 years or older were eligible for recruitment if they could provide informed consent and agree to self-swabbing of the upper respiratory tract. We analysed transmission risk by vaccination status for 231 contacts exposed to 162 epidemiologically linked delta variant-infected index cases. We compared viral load trajectories from fully vaccinated individuals with delta infection (n=29) with unvaccinated individuals with delta (n=16), alpha (B.1.1.7; n=39), and pre-alpha (n=49) infections. Primary outcomes for the epidemiological analysis were to assess the secondary attack rate (SAR) in household contacts stratified by contact vaccination status and the index cases' vaccination status. Primary outcomes for the viral load kinetics analysis were to detect differences in the peak viral load, viral growth rate, and viral decline rate between participants according to SARS-CoV-2 variant and vaccination status.<h4>Findings</h4>The SAR in household contacts exposed to the delta variant was 25% (95% CI 18-33) for fully vaccinated individuals compared with 38% (24-53) in unvaccinated individuals. The median time between second vaccine dose and study recruitment in fully vaccinated contacts was longer for infected individuals (medi
Hogan AB, Wu SL, Doohan P, et al., 2022, The value of vaccine booster doses to mitigate the global impact of the Omicron SARS-CoV-2 variant
<jats:title>Abstract</jats:title><jats:p>Vaccines have played a central role in mitigating severe disease and death from COVID-19 in the past 12 months. However, efficacy wanes over time and this loss of protection is being compounded by the emergence of the Omicron variant. By fitting an immunological model to population-level vaccine effectiveness data, we estimate that neutralizing antibody titres for Omicron are reduced by 3.9-fold (95% CrI 2.9–5.5) compared to the Delta variant. Under this model, we predict that 90 days after boosting with the Pfizer-BioNTech vaccine, efficacy against severe disease (admission to hospital) declines to 95.9% (95% CrI 95.4%–96.3%) against the Delta variant and 78.8% (95% CrI 75.0%–85.1%) against the Omicron variant. Integrating this immunological model within a model of SARS-CoV-2 transmission, we demonstrate that the size of the Omicron wave will depend on the degree of past exposure to infection across the population, with relatively small Omicron waves in countries that previously experienced a large Delta wave. We show that booster doses can have a major impact in mitigating the epidemic peak, although in many settings it remains possible that healthcare capacity could still be challenged. This is particularly the case in “zero-COVID” countries where there is little prior infection-induced immunity and therefore epidemic peaks will be higher. Where dose supply is limited, targeting boosters to the highest risk groups to ensure continued high protection in the face of waning immunity is of greater benefit than giving these doses as primary vaccination to younger age-groups. In many settings it is likely that health systems will be stretched, and it may therefore be necessary to maintain and/or reintroduce some level of NPIs to mitigate the worst impacts of the Omicron variant as it replaces the Delta variant.</jats:p>
Toor J, Li X, Jit M, et al., 2022, COVID-19 impact on routine immunisations for vaccine-preventable diseases: Projecting the effect of different routes to recovery
<jats:title>A<jats:sc>bstract</jats:sc></jats:title><jats:sec><jats:title>Introduction</jats:title><jats:p>Over the past two decades, vaccination programmes for vaccine-preventable diseases (VPDs) have expanded across low- and middle-income countries (LMICs). However, the rise of COVID-19 resulted in global disruption to routine immunisation (RI) activities. Such disruptions could have a detrimental effect on public health, leading to more deaths from VPDs, particularly without mitigation efforts. Hence, as RIs resume, it is important to estimate the effectiveness of different approaches for recovery.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>We apply an impact extrapolation method developed by the Vaccine Impact Modelling Consortium to estimate the impact of COVID-19-related disruptions with different recovery scenarios for ten VPDs across 112 LMICs. We focus on deaths averted due to RIs occurring in the years 2020-2030 and investigate two recovery scenarios relative to a no-COVID-19 scenario. In the recovery scenarios, we assume a 10% COVID-19-related drop in RI coverage in the year 2020. We then linearly interpolate coverage to the year 2030 to investigate two routes to recovery, whereby the immunization agenda (IA2030) targets are reached by 2030 or fall short by 10%.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>We estimate that falling short of the IA2030 targets by 10% leads to 11.26% fewer fully vaccinated persons (FVPs) and 11.34% more deaths over the years 2020-2030 relative to the no-COVID-19 scenario, whereas, reaching the IA2030 targets reduces these proportions to 5% fewer FVPs and 5.22% more deaths. The impact of the disruption varies across the VPDs with diseases where coverage expands drastically in future years facing a smaller detrimental effect.</jats:p></jats:sec><
Lalvani A, Hakki S, Singanayagam A, et al., 2022, Transmissibility of SARS-CoV-2 among fully vaccinated individuals reply, LANCET INFECTIOUS DISEASES, Vol: 22, Pages: 18-19, ISSN: 1473-3099
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Ferguson N, Ghani A, Hinsley W, et al., 2021, Report 50: Hospitalisation risk for Omicron cases in England
To assess differences in the risk of hospitalisation between the Omicron variant of concern (1) and the Delta variant, we analysed data from all PCR-confirmed SARS-CoV-2 cases in England with last test specimen dates between 1st and 14th December inclusive. Variant was defined using a combination of S-gene Target Failure (SGTF) and genetic data. Case data were linked by National Health service (NHS) number to the National Immunisation Management System (NIMS) database, the NHS Emergency Care (ECDS) and Secondary Use Services (SUS) hospital episode datasets. Hospital attendance was defined as any record of attendance at a hospital by a case in the 14 days following their last positive PCR test, up to and including the day of attendance. A secondary analysis examined the subset of attendances with a length of stay of one or more days. We used stratified conditional Poisson regression to predict hospitalisation status, with demographic strata defined by age, sex, ethnicity, region, specimen date, index of multiple deprivation and in some analyses, vaccination status. Predictor variables were variant (Omicron or Delta), reinfection status and vaccination status. Overall, we find evidence of a reduction in the risk of hospitalisation for Omicron relative to Delta infections, averaging over all cases in the study period. The extent of reduction is sensitive to the inclusion criteria used for cases and hospitalisation, being in the range 20-25% when using any attendance at hospital as the endpoint, and 40-45% when using hospitalisation lasting 1 day or longer or hospitalisations with the ECDS discharge field recorded as “admitted” as the endpoint (Table 1). These reductions must be balanced against the larger risk of infection with Omicron, due to the reduction in protection provided by both vaccination and natural infection. A previous infection reduces the
Ferguson N, Ghani A, Cori A, et al., 2021, Report 49: Growth, population distribution and immune escape of Omicron in England
To estimate the growth of the Omicron variant of concern (1) and its immune escape (2–9) characteristics, we analysed data from all PCR-confirmed SARS-CoV-2 cases in England excluding those with a history of recent international travel. We undertook separate analyses according to two case definitions. For the first definition, we included all cases with a definitive negative S-gene Target Failure (SGTF) result and specimen dates between 29/11/2021 and 11/12/2021 inclusive. For the second definition, we included cases with a positive genotype result and specimen date between 23/11/2021 and 11/12/2021 inclusive. We chose a later start date for the SGTF definition to ensure greater specificity of SGTF for Omicron.We used logistic and Poisson regression to identify factors associated with testing positive for Omicron compared to non-Omicron (mostly Delta) cases. We explored the following predictors: day, region, symptomatic status, sex, ethnicity, age band and vaccination status. Our results suggest rapid growth of the frequency of the Omicron variant relative to Delta, with the exponential growth rate of its frequency estimated to be 0.34/day (95% CI: 0.33-0.35) [2.0 day doubling time] over the study period from both SGTF and genotype data. The distribution of Omicron by age, region and ethnicity currently differs markedly from Delta, with 18–29-year-olds, residents in the London region, and those of African ethnicity having significantly higher rates of infection with Omicron relative to Delta.Hospitalisation and asymptomatic infection indicators were not significantly associated with Omicron infection, suggesting at most limited changes in severity compared with Delta.To estimate the impact of Omicron on vaccine effectiveness (VE) for symptomatic infection we used conditional Poisson regression to estimate the hazard ratio of being an Omicron case (using SGTF definition) compared with Delta, restricting our analysis to symptomatic cases and matching by da
Hogan A, Wu SL, Doohan P, et al., 2021, Report 48: The value of vaccine booster doses to mitigate the global impact of the Omicron SARS-CoV-2 variant
Vaccines have played a central role in mitigating severe disease and death from COVID-19 in the past 12 months. However, efficacy wanes over time and this loss of protection will be compounded by the emergence of the Omicron variant. By fitting an immunological model to population-level vaccine effectiveness data, we estimate that neutralizing antibody titres for Omicron are reduced by 4.5-fold (95% CrI 3.1–7.1) compared to the Delta variant. This is predicted to result in a drop in vaccine efficacy against severe disease (hospitalisation) from 96.5% (95% CrI 96.1%–96.8%) against Delta to 80.1% (95% CrI 76.3%–83.2%) against Omicron for the Pfizer-BioNTech booster by 60 days post boost if NAT decay at the same rate following boosting as following the primary course, and from 97.6% (95% CrI 97.4%-97.9%) against Delta to 85.9% (95% CrI 83.1%-88.3%) against Omicron if NAT decay at half the rate observed after the primary course. Integrating this immunological model within a model of SARS-CoV-2 transmission, we show that booster doses will be critical to mitigate the impact of future Omicron waves in countries with high levels of circulating virus. They will also be needed in “zero-COVID” countries where there is little prior infection-induced immunity in order to open up safely. Where dose supply is limited, targeting boosters to the highest risk groups to ensure continued high protection in the face of waning immunity is of greater benefit than giving these doses as primary vaccination to younger age-groups. In all scenarios it is likely that health systems will be stretched. It may be essential, therefore, to maintain and/or reintroduce NPIs to mitigate the worst impacts of the Omicron variant as it replaces the Delta variant. Ultimately, Omicron variant-specific vaccines are likely to be required.
McCabe R, Kont MD, Watson O, et al., 2021, Communicating uncertainty in epidemic models, Epidemics: the journal of infectious disease dynamics, Vol: 37, Pages: 1-6, ISSN: 1755-4365
While mathematical models of disease transmission are widely used to inform public health decision-makers globally, the uncertainty inherent in results are often poorly communicated. We outline some potential sources of uncertainty in epidemic models, present traditional methods used to illustrate uncertainty and discuss alternative presentation formats used by modelling groups throughout the COVID-19 pandemic. Then, by drawing on the experience of our own recent modelling, we seek to contribute to the ongoing discussion of how to improve upon traditional methods used to visualise uncertainty by providing a suggestion of how this can be presented in a clear and simple manner.
Sonabend R, Whittles LK, Imai N, et al., 2021, Non-pharmaceutical interventions, vaccination, and the SARS-CoV-2 delta variant in England: a mathematical modelling study, The Lancet, Vol: 398, Pages: 1825-1835, ISSN: 0140-6736
Background:England's COVID-19 roadmap out of lockdown policy set out the timeline and conditions for the stepwise lifting of non-pharmaceutical interventions (NPIs) as vaccination roll-out continued, with step one starting on March 8, 2021. In this study, we assess the roadmap, the impact of the delta (B.1.617.2) variant of SARS-CoV-2, and potential future epidemic trajectories.Methods:This mathematical modelling study was done to assess the UK Government's four-step process to easing lockdown restrictions in England, UK. We extended a previously described model of SARS-CoV-2 transmission to incorporate vaccination and multi-strain dynamics to explicitly capture the emergence of the delta variant. We calibrated the model to English surveillance data, including hospital admissions, hospital occupancy, seroprevalence data, and population-level PCR testing data using a Bayesian evidence synthesis framework, then modelled the potential trajectory of the epidemic for a range of different schedules for relaxing NPIs. We estimated the resulting number of daily infections and hospital admissions, and daily and cumulative deaths. Three scenarios spanning a range of optimistic to pessimistic vaccine effectiveness, waning natural immunity, and cross-protection from previous infections were investigated. We also considered three levels of mixing after the lifting of restrictions.Findings:The roadmap policy was successful in offsetting the increased transmission resulting from lifting NPIs starting on March 8, 2021, with increasing population immunity through vaccination. However, because of the emergence of the delta variant, with an estimated transmission advantage of 76% (95% credible interval [95% CrI] 69–83) over alpha, fully lifting NPIs on June 21, 2021, as originally planned might have led to 3900 (95% CrI 1500–5700) peak daily hospital admissions under our central parameter scenario. Delaying until July 19, 2021, reduced peak hospital admissions by three fol
Echeverria-Londono S, Li X, Toor J, et al., 2021, How can the public health impact of vaccination be estimated?, BMC PUBLIC HEALTH, Vol: 21
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Whittaker C, Walker PGT, Alhaffar M, et al., 2021, Under-reporting of deaths limits our understanding of true burden of covid-19, BMJ-BRITISH MEDICAL JOURNAL, Vol: 375, ISSN: 0959-535X
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Vollmer MAC, Radhakrishnan S, Kont MD, et al., 2021, The impact of the COVID-19 pandemic on patterns of attendance at emergency departments in two large London hospitals: an observational study, BMC Health Services Research, Vol: 21, Pages: 1-9, ISSN: 1472-6963
Background Hospitals in England have undergone considerable change to address the surgein demand imposed by the COVID-19 pandemic. The impact of this on emergencydepartment (ED) attendances is unknown, especially for non-COVID-19 related emergencies.Methods This analysis is an observational study of ED attendances at the Imperial CollegeHealthcare NHS Trust (ICHNT). We calibrated auto-regressive integrated moving averagetime-series models of ED attendances using historic (2015-2019) data. Forecasted trendswere compared to present year ICHNT data for the period between March 12, 2020 (whenEngland implemented the first COVID-19 public health measure) and May 31, 2020. Wecompared ICHTN trends with publicly available regional and national data. Lastly, wecompared hospital admissions made via the ED and in-hospital mortality at ICHNT duringthe present year to the historic 5-year average.Results ED attendances at ICHNT decreased by 35% during the period after the firstlockdown was imposed on March 12, 2020 and before May 31, 2020, reflecting broadertrends seen for ED attendances across all England regions, which fell by approximately 50%for the same time frame. For ICHNT, the decrease in attendances was mainly amongst thoseaged <65 years and those arriving by their own means (e.g. personal or public transport) andnot correlated with any of the spatial dependencies analysed such as increasing distance frompostcode of residence to the hospital. Emergency admissions of patients without COVID-19after March 12, 2020 fell by 48%; we did not observe a significant change to the crudemortality risk in patients without COVID-19 (RR 1.13, 95%CI 0.94-1.37, p=0.19).Conclusions Our study findings reflect broader trends seen across England and give anindication how emergency healthcare seeking has drastically changed. At ICHNT, we findthat a larger proportion arrived by ambulance and that hospitalisation outcomes of patientswithout COVID-19 did not differ from previous years. The ext
DAeth J, Ghosal S, Grimm F, et al., 2021, Optimal national prioritization policies for hospital care during the SARS-CoV-2 pandemic, Nature Computational Science, Vol: 1, Pages: 521-531, ISSN: 2662-8457
In response to unprecedent surges in the demand for hospital care during the SARS-CoV-2 pandemic, health systems have prioritized COVID patients to life-saving hospital care to the detriment of other patients. In contrast to these ad hoc policies, we develop a linear programming framework to optimally schedule elective procedures and allocate hospital beds among all planned and emergency patients to minimize years of life lost. Leveraging a large dataset of administrative patient medical records, we apply our framework to the National Health System in England and show that an extra 50,750-5,891,608 years of life can be gained in comparison to prioritization policies that reflect those implemented during the pandemic. Significant health gains are observed for neoplasms, diseases of the digestive system, and injuries & poisoning. Our open-source framework provides a computationally efficient approximation of a large-scale discrete optimization problem that can be applied globally to support national-level care prioritization policies.
Bhatia S, Parag K, Wardle J, et al., 2021, Global predictions of short- to medium-term COVID-19 transmission trends : a retrospective assessment
<jats:title>Abstract</jats:title> <jats:p>From 8th March to 29th November 2020, we produced weekly estimates of SARS-CoV-2 transmissibility and forecasts of deaths due to COVID-19 for 81 countries with evidence of sustained transmission. We also developed a novel heuristic to combine weekly estimates of transmissibility to produce forecasts over a 4-week horizon. We evaluated the robustness of the forecasts using relative error, coverage probability, and comparisons with null models. During the 39-week period covered by this study, both the short- and medium-term forecasts captured well the epidemic trajectory across different waves of COVID-19 infections with small relative errors over the forecast horizon. The model was well calibrated with 56.3\% and 45.6\% of the observations lying in the 50\% Credible Interval in 1-week and 4-week ahead forecasts respectively. We could accurately characterise the overall phase of the epidemic up to 4-weeks ahead in 84.9\% of country-days. The medium-term forecasts can be used in conjunction with the short-term forecasts of COVID-19 mortality as a useful planning tool as countries continue to relax public health measures.</jats:p>
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' (vol 12, 4383, 2021), Nature Communications, Vol: 12, Pages: 1-1, ISSN: 2041-1723
Mishra S, Scott JA, Laydon DJ, et al., 2021, Comparing the responses of the UK, Sweden and Denmark to COVID-19 using counterfactual modelling, SCIENTIFIC REPORTS, Vol: 11, Pages: 1-9, ISSN: 2045-2322
The UK and Sweden have among the worst per-capita COVID-19 mortality in Europe. Sweden stands out for its greater reliance on voluntary, rather than mandatory, control measures. We explore how the timing and effectiveness of control measures in the UK, Sweden and Denmark shaped COVID-19 mortality in each country, using a counterfactual assessment: what would the impact have been, had each country adopted the others’ policies? Using a Bayesian semi-mechanistic model without prior assumptions on the mechanism or effectiveness of interventions, we estimate the time-varying reproduction number for the UK, Sweden and Denmark from daily mortality data. We use two approaches to evaluate counterfactuals which transpose the transmission profile from one country onto another, in each country’s first wave from 13th March (when stringent interventions began) until 1st July 2020. UK mortality would have approximately doubled had Swedish policy been adopted, while Swedish mortality would have more than halved had Sweden adopted UK or Danish strategies. Danish policies were most effective, although differences between the UK and Denmark were significant for one counterfactual approach only. Our analysis shows that small changes in the timing or effectiveness of interventions have disproportionately large effects on total mortality within a rapidly growing epidemic.
Ohrnberger J, Segal A, Forchini G, et al., 2021, The impact of a COVID-19 lockdown on work productivity under good and poor compliance, European Journal of Public Health, Vol: 31, Pages: 1009-1015, ISSN: 1101-1262
BackgroundIn response to the COVID-19 pandemic, governments across the globe have imposed strict social distancing measures. Public compliance to such measures is essential for their success yet the economic consequences of compliance are unknown. This is the first study to analyse the effects of good compliance compared to poor compliance to a COVID-19 suppression strategy (i.e. lockdown) on work productivity. MethodsWe estimate the differences in work productivity comparing a scenario of good compliance with one of poor compliance to the UK government COVID-19 suppression strategy. We use projections of the impact of the UK suppression strategy on mortality and morbidity from an individual-based epidemiological model combined with an economic model representative of the labour force in Wales and England. ResultsWe find that productivity effects of good compliance significantly exceed those of poor compliance and increase with the duration of the lockdown. After three months of the lockdown, work productivity in good compliance is £398.58 million higher compared with that of poor compliance. 75% of the differences is explained by productivity effects due to morbidity and non-health reasons and 25% attributed to avoided losses due to pre-mature mortality.ConclusionGood compliance to social distancing measures exceeds positive economic effects, in addition to health benefits. This is an important finding for current economic and health policy. It highlights the importance to set clear guidelines for the public, to build trust and support for the rules and if necessary, to enforce good compliance to social distancing measures.
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