Publications
177 results found
Whittaker C, Chesnais CB, Pion SDS, et al., 2022, Factors associated with variation in single-dose albendazole pharmacokinetics: A systematic review and modelling analysis
<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Albendazole is an orally administered anti-parasitic medication with widespread usage in a variety of both programmatic and clinical contexts. Previous work has shown the drug to be characterised by significant inter-individual pharmacokinetic variation. This variation is thought to have important consequences for treatment success, but current understanding of the factors associated with this variation remains incomplete.</jats:p></jats:sec><jats:sec><jats:title>Methodology/Principal Findings</jats:title><jats:p>We carried out a systematic review to identify references containing temporally disaggregated data on the blood concentration of albendazole and/or (its pharmacologically-active metabolite) albendazole sulfoxide following a single oral dose. These data were then integrated into a mathematical modelling framework to infer key pharmacokinetic parameters and relate them to characteristics of the populations being treated. These characteristics included age, weight, sex, dosage, infection status, and whether patients had received a fatty meal prior to treatment or other drugs alongside albendazole. Our results highlight a number of factors systematically associated with albendazole pharmacokinetic variation including age, existing parasitic infection and receipt of a fatty meal. These factors impact different aspects of the drug’s pharmacokinetic profile. Whilst age is significantly associated with albendazole sulfoxide half-life, receipt of a fatty meal prior to treatment was associated with increased albendazole bioavailability (and by extension, peak blood concentration and total drug exposure following the dose). Parasitic infection (particularly echinococcosis and neurocysticercosis) was associated with altered pharmacokinetic parameters, with infected populations displaying distinct characteris
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.
Brizzi A, Whittaker C, Servo LMS, et al., 2022, Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals, Nature Medicine, Vol: 28, ISSN: 1078-8956
The SARS-CoV-2 Gamma variant of concern spread rapidly across Brazil since late 2020, causing substantial infection and death waves. We use individual-level patient records following hospitalisation with suspected or confirmed COVID-19 between 20 January 2020 and 26 July 2021 to document temporary, sweeping shocks in hospital fatality rates that followed Gamma’s spread across 14 state capitals, during which typically more than half of hospitalised patients aged 70 and over died. We show that such extensive shocks in COVID-19 in-hospital fatality rates also existed prior to detection of Gamma. Using a Bayesian fatality rate model, we find that the geographic and temporal fluctuations in Brazil’s COVID-19 in-hospital fatality rates were primarily associated with geographic inequities and shortages in healthcare capacity. We estimate that approximately half of the COVID-19 deaths in hospitals in the 14 cities could have been avoided without pre-pandemic geographic inequities and without pandemic healthcare pressure. Our results suggest that investments in healthcare resources, healthcare optimization, and pandemic preparedness are critical to minimize population wide mortality and morbidity caused by highly transmissible and deadly pathogens such as SARS-CoV-2, especially in low- and middle-income countries.
Whittaker C, Winskill P, Sinka M, et al., 2022, A novel statistical framework for exploring the population dynamics and seasonality of mosquito populations, Proceedings of the Royal Society B: Biological Sciences, Vol: 289, Pages: 1-10, ISSN: 0962-8452
Understanding the temporal dynamics of mosquito populations underlying vector-borne disease transmission is key to optimizing control strategies. Many questions remain surrounding the drivers of these dynamics and how they vary between species—questions rarely answerable from individual entomological studies (that typically focus on a single location or species). We develop a novel statistical framework enabling identification and classification of time series with similar temporal properties, and use this framework to systematically explore variation in population dynamics and seasonality in anopheline mosquito time series catch data spanning seven species, 40 years and 117 locations across mainland India. Our analyses reveal pronounced variation in dynamics across locations and between species in the extent of seasonality and timing of seasonal peaks. However, we show that these diverse dynamics can be clustered into four ‘dynamical archetypes’, each characterized by distinct temporal properties and associated with a largely unique set of environmental factors. Our results highlight that a range of environmental factors including rainfall, temperature, proximity to static water bodies and patterns of land use (particularly urbanicity) shape the dynamics and seasonality of mosquito populations, and provide a generically applicable framework to better identify and understand patterns of seasonal variation in vectors relevant to public health.
Rickelt S, Neyaz A, Condon C, et al., 2022, Agrin Loss in Barrett's Esophagus-Related Neoplasia and Its Utility as a Diagnostic and Predictive Biomarker., Clin Cancer Res, Vol: 28, Pages: 1167-1179
PURPOSE: There is an unmet need for identifying novel biomarkers in Barrett's esophagus that could stratify patients with regards to neoplastic progression. We investigate the expression patterns of extracellular matrix (ECM) molecules in Barrett's esophagus and Barrett's esophagus-related neoplasia, and assess their value as biomarkers for the diagnosis of Barrett's esophagus-related neoplasia and to predict neoplastic progression. EXPERIMENTAL DESIGN: Gene-expression analyses of ECM matrisome gene sets were performed using publicly available data on human Barrett's esophagus, Barrett's esophagus-related dysplasia, esophageal adenocarcinoma (ADCA) and normal esophagus. Immunohistochemical expression of basement membrane (BM) marker agrin (AGRN) and p53 was analyzed in biopsies of Barrett's esophagus-related neoplasia from 321 patients in three independent cohorts. RESULTS: Differential gene-expression analysis revealed significant enrichment of ECM matrisome gene sets in dysplastic Barrett's esophagus and ADCA compared with controls. Loss of BM AGRN expression was observed in both Barrett's esophagus-related dysplasia and ADCA. The mean AGRN loss in Barrett's esophagus glands was significantly higher in Barrett's esophagus-related dysplasia and ADCA compared with non-dysplastic Barrett's esophagus (NDBE; P < 0.001; specificity = 82.2% and sensitivity = 96.4%). Loss of AGRN was significantly higher in NDBE samples from progressors compared with non-progressors (P < 0.001) and identified patients who progressed to advanced neoplasia with a specificity of 80.2% and sensitivity of 54.8%. Moreover, the combination of AGRN loss and abnormal p53 staining identified progression to Barrett's esophagus-related advanced neoplasia with a specificity and sensitivity of 86.5% and 58.7%. CONCLUSIONS: We highlight ECM changes during Barrett's esophagus progression to neoplasia. BM AGRN loss is a novel diagnostic biomarker that can identify patients with NDBE at increased ris
Prete CA, Buss LF, Buccheri R, et al., 2022, Reinfection by the SARS-CoV-2 Gamma variant in blood donors in Manaus, Brazil, BMC Infectious Diseases, Vol: 22, ISSN: 1471-2334
BackgroundThe city of Manaus, north Brazil, was stricken by a second epidemic wave of SARS-CoV-2 despite high seroprevalence estimates, coinciding with the emergence of the Gamma (P.1) variant. Reinfections were postulated as a partial explanation for the second surge. However, accurate calculation of reinfection rates is difficult when stringent criteria as two time-separated RT-PCR tests and/or genome sequencing are required. To estimate the proportion of reinfections caused by Gamma during the second wave in Manaus and the protection conferred by previous infection, we identified anti-SARS-CoV-2 antibody boosting in repeat blood donors as a mean to infer reinfection.MethodsWe tested serial blood samples from unvaccinated repeat blood donors in Manaus for the presence of anti-SARS-CoV-2 IgG antibodies using two assays that display waning in early convalescence, enabling the detection of reinfection-induced boosting. Donors were required to have three or more donations, being at least one during each epidemic wave. We propose a strict serological definition of reinfection (reactivity boosting following waning like a V-shaped curve in both assays or three spaced boostings), probable (two separate boosting events) and possible (reinfection detected by only one assay) reinfections. The serial samples were used to divide donors into six groups defined based on the inferred sequence of infection and reinfection with non-Gamma and Gamma variants.ResultsFrom 3655 repeat blood donors, 238 met all inclusion criteria, and 223 had enough residual sample volume to perform both serological assays. We found 13.6% (95% CI 7.0–24.5%) of all presumed Gamma infections that were observed in 2021 were reinfections. If we also include cases of probable or possible reinfections, these percentages increase respectively to 22.7% (95% CI 14.3–34.2%) and 39.3% (95% CI 29.5–50.0%). Previous infection conferred a protection against reinfection of 85.3% (95% CI 71.3–92.
Dalvie NC, Biedermann AM, Rodriguez-Aponte SA, et al., 2022, Scalable, methanol-free manufacturing of the SARS-CoV-2 receptor-binding domain in engineered Komagataella phaffii., Biotechnol Bioeng, Vol: 119, Pages: 657-662
Prevention of COVID-19 on a global scale will require the continued development of high-volume, low-cost platforms for the manufacturing of vaccines to supply ongoing demand. Vaccine candidates based on recombinant protein subunits remain important because they can be manufactured at low costs in existing large-scale production facilities that use microbial hosts like Komagataella phaffii (Pichia pastoris). Here, we report an improved and scalable manufacturing approach for the SARS-CoV-2 spike protein receptor-binding domain (RBD); this protein is a key antigen for several reported vaccine candidates. We genetically engineered a manufacturing strain of K. phaffii to obviate the requirement for methanol induction of the recombinant gene. Methanol-free production improved the secreted titer of the RBD protein by >5X by alleviating protein folding stress. Removal of methanol from the production process enabled to scale up to a 1200 L pre-existing production facility. This engineered strain is now used to produce an RBD-based vaccine antigen that is currently in clinical trials and could be used to produce other variants of RBD as needed for future vaccines.
Brito AF, Semenova E, Dudas G, et al., 2021, Global disparities in SARS-CoV-2 genomic surveillance.
Genomic sequencing provides critical information to track the evolution and spread of SARS-CoV-2, optimize molecular tests, treatments and vaccines, and guide public health responses. To investigate the spatiotemporal heterogeneity in the global SARS-CoV-2 genomic surveillance, we estimated the impact of sequencing intensity and turnaround times (TAT) on variant detection in 167 countries. Most countries submit genomes >21 days after sample collection, and 77% of low and middle income countries sequenced <0.5% of their cases. We found that sequencing at least 0.5% of the cases, with a TAT <21 days, could be a benchmark for SARS-CoV-2 genomic surveillance efforts. Socioeconomic inequalities substantially impact our ability to quickly detect SARS-CoV-2 variants, and undermine the global pandemic preparedness.
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.
Mousa A, Winskill P, Watson OJ, et al., 2021, Social contact patterns and implications for infectious disease transmission: a systematic review and meta-analysis of contact surveys, eLife, Vol: 10, ISSN: 2050-084X
Background: Transmission of respiratory pathogens such as SARS-CoV-2 depends on patterns of contact and mixing across populations. Understanding this is crucial to predict pathogen spread and the effectiveness of control efforts. Most analyses of contact patterns to date have focussed on high-income settings.Methods: Here, we conduct a systematic review and individual-participant meta-analysis of surveys carried out in low- and middle-income countries and compare patterns of contact in these settings to surveys previously carried out in high-income countries. Using individual-level data from 28,503 participants and 413,069 contacts across 27 surveys we explored how contact characteristics (number, location, duration and whether physical) vary across income settings.Results: Contact rates declined with age in high- and upper-middle-income settings, but not in low-income settings, where adults aged 65+ made similar numbers of contacts as younger individuals and mixed with all age-groups. Across all settings, increasing household size was a key determinant of contact frequency and characteristics, with low-income settings characterised by the largest, most intergenerational households. A higher proportion of contacts were made at home in low-income settings, and work/school contacts were more frequent in high-income strata. We also observed contrasting effects of gender across income-strata on the frequency, duration and type of contacts individuals made.Conclusions: These differences in contact patterns between settings have material consequences for both spread of respiratory pathogens, as well as the effectiveness of different non-pharmaceutical interventions.
Wang C, Cui A, Bukenya M, et al., 2021, Reprogramming NK cells and macrophages via combined antibody and cytokine therapy primes tumors for elimination by checkpoint blockade., Cell Rep, Vol: 37
Treatments aiming to augment immune checkpoint blockade (ICB) in cancer often focus on T cell immunity, but innate immune cells may have important roles to play. Here, we demonstrate a single-dose combination treatment (termed AIP) using a pan-tumor-targeting antibody surrogate, half-life-extended interleukin-2 (IL-2), and anti-programmed cell death 1 (PD-1), which primes tumors to respond to subsequent ICB and promotes rejection of large established tumors in mice. Natural killer (NK) cells and macrophages activated by AIP treatment underwent transcriptional reprogramming; rapidly killed cancer cells; governed the recruitment of cross-presenting dendritic cells (DCs) and other leukocytes; and induced normalization of the tumor vasculature, facilitating further immune infiltration. Thus, innate cell-activating therapies can initiate critical steps leading to a self-sustaining cycle of T cell priming driven by ICB.
Dhar MS, Marwal R, Radhakrishnan VS, et al., 2021, Genomic characterization and epidemiology of an emerging SARS-CoV-2 variant in Delhi, India, SCIENCE, Vol: 374, Pages: 995-+, ISSN: 0036-8075
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- Citations: 161
Mlcochova P, Kemp SA, Dhar MS, et al., 2021, SARS-CoV-2 B.1.617.2 Delta variant replication and immune evasion, NATURE, Vol: 599, Pages: 114-+, ISSN: 0028-0836
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- Citations: 625
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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- Citations: 50
Brizzi A, Whittaker C, Servo LMS, et al., 2021, Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals
The SARS‐CoV‐2 Gamma variant spread rapidly across Brazil, causing substantial infection and death wa ves. We use individual‐level patient records following hospitalisation with suspected or confirmed COVID‐19 to document the extensive shocks in hospital fatality rates that followed Gamma’s spread across 14 state capitals, and in which more than half of hospitalised patients died over sustained time pe riods. We show that extensive fluctuations in COVID‐19 in‐hospital fatality rates also existed prior to Gamma’s detection, and were largely transient after Gamma’s detection, subsiding with hospital d emand. Using a Bayesian fatality rate model, we find that the geo‐graphic and temporal fluctuations in Brazil’s COVID‐19 in‐hospital fatality rates are primarily associated with geo‐graphic inequities and shortages in healthcare c apacity. We project that approximately half of Brazil’s COVID‐19 deaths in hospitals could have been avoided without pre‐pandemic geographic inequities and without pandemic healthcare pressure. Our results suggest that investments in healthcare resources, healthcare optimization, and pandemic preparedness are critical to minimize population wide mortality and morbidity caused by highly trans‐missible and deadly pathogens such as SARS‐CoV‐2, especially in low‐ and middle‐income countries.
Whittaker C, Ratmann O, Dye C, et al., 2021, Altered demographic profile of hospitalizations during the second COVID-19 wave in Amazonas, Brazil, The Lancet Regional Health - Americas, Vol: 2, ISSN: 2667-193X
Dalvie NC, Rodriguez-Aponte SA, Hartwell BL, et al., 2021, Engineered SARS-CoV-2 receptor binding domain improves manufacturability in yeast and immunogenicity in mice., Proc Natl Acad Sci U S A, Vol: 118
Global containment of COVID-19 still requires accessible and affordable vaccines for low- and middle-income countries (LMICs). Recently approved vaccines provide needed interventions, albeit at prices that may limit their global access. Subunit vaccines based on recombinant proteins are suited for large-volume microbial manufacturing to yield billions of doses annually, minimizing their manufacturing cost. These types of vaccines are well-established, proven interventions with multiple safe and efficacious commercial examples. Many vaccine candidates of this type for SARS-CoV-2 rely on sequences containing the receptor-binding domain (RBD), which mediates viral entry to cells via ACE2. Here we report an engineered sequence variant of RBD that exhibits high-yield manufacturability, high-affinity binding to ACE2, and enhanced immunogenicity after a single dose in mice compared to the Wuhan-Hu-1 variant used in current vaccines. Antibodies raised against the engineered protein exhibited heterotypic binding to the RBD from two recently reported SARS-CoV-2 variants of concern (501Y.V1/V2). Presentation of the engineered RBD on a designed virus-like particle (VLP) also reduced weight loss in hamsters upon viral challenge.
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.
Okell L, Whittaker C, Ghani A, et al., 2021, Global patterns of submicroscopic Plasmodium falciparum malaria infection: insights from a systematic review and meta-analysis of population surveys, The Lancet Microbe, Vol: 2, Pages: e366-e374, ISSN: 2666-5247
Background: Adoption of molecular techniques to detect Plasmodium falciparum infection has revealed many previously undetected (by microscopy) yet transmissible low-density infections. The proportion of these infections is typically highest in low transmission settings, but drivers of submicroscopic infection remain unclear. Here, we update a previously conducted systematic review of asexual P. falciparum prevalence by microscopy and polymerase chain reaction (PCR) in the same population. We conduct a meta-analysis to explore potential drivers of submicroscopic infection and identify the locations where submicroscopic infections are most common. Methods: PubMed and Web of Science databases were searched up to 11th October 2020 for cross-sectional studies reporting data on asexual P.falciparum prevalence by both microscopy and PCR. Surveys of pregnant women, where participants had been chosen based on symptoms/treatment or that did not involve a population from a defined location were excluded. Both the number of individuals tested and positive by microscopy and PCR for P. falciparum infection were extracted from each reference. Bayesian regression modelling was used to explore determinants of the size of the submicroscopic reservoir including geography, seasonality, age, methodology and current/historical patterns of transmission.Findings: A total of 166 references containing 551 cross-sectional survey microscopy/PCR prevalence pairs were included. Our results highlight that submicroscopic infections predominate in low transmission settings across all settings, but also reveal marked geographical variation, with the proportion of infections that are submicroscopic being highest in South American surveys and lowest in West African studies. Whilst current transmission levels partly explain these results, we find that historical transmission intensity also represents a crucial determinant of the size of the submicroscopic reservoir, as does the demographic structure of
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
Hawryluk I, Hoeltgebaum H, Mishra S, et al., 2021, Gaussian process nowcasting: application to COVID-19 mortality reporting, 37th Conference on Uncertainty in Artificial Intelligence, UAI 2021, Publisher: PMLR, Pages: 1258-1268
Updating observations of a signal due to the delays in the measurementprocess is a common problem in signal processing, with prominent examples in awide range of fields. An important example of this problem is the nowcasting ofCOVID-19 mortality: given a stream of reported counts of daily deaths, can wecorrect for the delays in reporting to paint an accurate picture of thepresent, with uncertainty? Without this correction, raw data will often misleadby suggesting an improving situation. We present a flexible approach using alatent Gaussian process that is capable of describing the changingauto-correlation structure present in the reporting time-delay surface. Thisapproach also yields robust estimates of uncertainty for the estimatednowcasted numbers of deaths. We test assumptions in model specification such asthe choice of kernel or hyper priors, and evaluate model performance on achallenging real dataset from Brazil. Our experiments show that Gaussianprocess nowcasting performs favourably against both comparable methods, andagainst a small sample of expert human predictions. Our approach hassubstantial practical utility in disease modelling -- by applying our approachto COVID-19 mortality data from Brazil, where reporting delays are large, wecan make informative predictions on important epidemiological quantities suchas the current effective reproduction number.
Mangal T, Whittaker C, Nkhoma D, et al., 2021, The potential impact of intervention strategies on COVID-19 transmission in Malawi: a mathematical modelling study, BMJ Open, Vol: 11, ISSN: 2044-6055
BackgroundCOVID-19 mitigation strategies have been challenging to implement in resource-limited settings due to the potential for widespread disruption to social and economic well-being. Here we predict the clinical severity of COVID-19 in Malawi, quantifying the potential impact of intervention strategies and increases in health system capacity.MethodsThe infection fatality ratios (IFR) were predicted by adjusting reported IFR for China accounting for demography, the current prevalence of comorbidities and health system capacity. These estimates were input into an age-structured deterministic model, which simulated the epidemic trajectory with non-pharmaceutical interventions and increases in health system capacity. Findings The predicted population-level IFR in Malawi, adjusted for age and comorbidity prevalence, is lower than estimated for China (0.26%, 95% uncertainty interval [UI] 0.12 – 0.69%, compared with 0.60%, 95% CI 0.4% – 1.3% in China), however the health system constraints increase the predicted IFR to 0.83%, 95% UI 0.49% – 1.39%. The interventions implemented in January 2021 could potentially avert 54,400 deaths (95% UI 26,900 – 97,300) over the course of the epidemic compared with an unmitigated outbreak. Enhanced shielding of people aged ≥ 60 years could avert a further 40,200 deaths (95% UI 25,300 – 69,700) and halve ICU admissions at the peak of the outbreak. A novel therapeutic agent, which reduces mortality by 0.65 and 0.8 for severe and critical cases respectively, in combination with increasing hospital capacity could reduce projected mortality to 2.5 deaths per 1,000 population (95% UI 1.9 – 3.6).ConclusionWe find the interventions currently used in Malawi are unlikely to effectively prevent SARS-CoV-2 transmission but will have a significant impact on mortality. Increases in health system capacity and the introduction of novel therapeutics are likely to further reduce the projected numbers of deaths.
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.
Smith TP, Flaxman S, Gallinat AS, et al., 2021, Temperature and population density influence SARS-CoV-2 transmission in the absence of nonpharmaceutical interventions, Proceedings of the National Academy of Sciences of USA, Vol: 118, Pages: 1-8, ISSN: 0027-8424
As COVID-19 continues to spread across the world, it is increasingly important to understand the factors that influence its transmission. Seasonal variation driven by responses to changing environment has been shown to affect the transmission intensity of several coronaviruses. However, the impact of the environment on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains largely unknown, and thus seasonal variation remains a source of uncertainty in forecasts of SARS-CoV-2 transmission. Here we address this issue by assessing the association of temperature, humidity, ultraviolet radiation, and population density with estimates of transmission rate (R). Using data from the United States, we explore correlates of transmission across US states using comparative regression and integrative epidemiological modeling. We find that policy intervention (“lockdown”) and reductions in individuals’ mobility are the major predictors of SARS-CoV-2 transmission rates, but, in their absence, lower temperatures and higher population densities are correlated with increased SARS-CoV-2 transmission. Our results show that summer weather cannot be considered a substitute for mitigation policies, but that lower autumn and winter temperatures may lead to an increase in transmission intensity in the absence of policy interventions or behavioral changes. We outline how this information may improve the forecasting of COVID-19, reveal its future seasonal dynamics, and inform intervention policies.
Djaafara A, Whittaker C, Watson OJ, et al., 2021, Using syndromic measures of mortality to capture the dynamics of COVID-19 in Java, Indonesia in the context of vaccination roll-out, BMC Medicine, Vol: 19, ISSN: 1741-7015
Background: As in many countries, quantifying COVID-19 spread in Indonesia remains challenging due to testing limitations. In Java, non-pharmaceutical interventions (NPIs) were implemented throughout 2020. However, as a vaccination campaign launches, cases and deaths are rising across the island. Methods: We used modelling to explore the extent to which data on burials in Jakarta using strict COVID-19 protocols (C19P) provide additional insight into the transmissibility of the disease, epidemic trajectory, and the impact of NPIs. We assess how implementation of NPIs in early 2021 will shape the epidemic during the period of likely vaccine roll-out. Results: C19P burial data in Jakarta suggest a death toll approximately 3.3 times higher than reported. Transmission estimates using these data suggest earlier, larger, and more sustained impact of NPIs. Measures to reduce sub-national spread, particularly during Ramadan, substantially mitigated spread to more vulnerable rural areas. Given current trajectory, daily cases and deaths are likely to increase in most regions as the vaccine is rolled-out. Transmission may peak in early 2021 in Jakarta if current levels of control are maintained. However, relaxation of control measures is likely to lead to a subsequent resurgence in the absence of an effective vaccination campaign. Conclusions: Syndromic measures of mortality provide a more complete picture of COVID-19 severity upon which to base decision-making. The high potential impact of the vaccine in Java is attributable to reductions in transmission to date and dependent on these being maintained. Increases in control in the relatively short-term will likely yield large, synergistic increases in vaccine impact.
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.
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.
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.
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.
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.
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