Publications
115 results found
Sheppard RJ, Watson OJ, Pieciak R, et al., 2024, Author Correction: Using mortuary and burial data to place COVID-19 in Lusaka, Zambia within a global context., Nat Commun, Vol: 15
Meier-Scherling CPG, Watson OJ, Asua V, et al., 2024, Selection of artemisinin partial resistance Kelch13 mutations in Uganda in 2016-22 was at a rate comparable to that seen previously in South-East Asia., medRxiv
BACKGROUND: Artemisinin partial resistance, mediated by mutations in the Plasmodium falciparum Kelch13 protein (K13), rapidly spread in South-East Asia (SEA), undermining antimalarial efficacies of artemisinin-based combination therapies (ACT). Validated K13 mutations have recently arisen in Africa, but rates of increase are not well characterized. METHODS: We investigated K13 mutation prevalence at 16 sites in Uganda (2016-2022, 6586 samples), and five sites in SEA (2003-2018, 5465 samples) by calculating selection coefficients using Bayesian mixed-effect linear models. We then tested whether SEA K13 mutation prevalence could have been forecast accurately using up to the first five years of available data and forecast future K13 mutation prevalence in Uganda. FINDINGS: The selection coefficient for the prevalence of relevant K13 mutations (441L, 469F/Y, 561H, 675V) was estimated at s=0·383 (95% CrI: 0·247 - 0·528) per year, a 38% relative prevalence increase. Selection coefficients across Uganda were s=0·968 (0·463 - 1·569) for 441L, s=0·153 (-0·445 - 0·727) for 469F, s=0·222 (-0·011 - 0·398) for 469Y, and s=0·152 (-0·023 - 0·312) for 675V. In SEA, the selection coefficient was s=-0·005 (-0·852 - 0·814) for 539T, s=0·574 (-0·092 - 1·201) for 580Y, and s=0·308 (0·089 - 0·536) for all validated K13 mutations. Forecast prevalences for Uganda assuming constant selection neared fixation (>95% prevalence) within a decade (2028-2033) for combined K13 mutations. INTERPRETATION: The selection of K13 mutations in Uganda was at a comparable rate to that observed in SEA, suggesting K13 mutations may continue to increase quickly in Uganda. FUNDING: NIH R01AI156267, R01AI075045, and R01AI089674.
Hogan AB, Wu SL, Toor J, et al., 2023, Long-term vaccination strategies to mitigate the impact of SARS-CoV-2 transmission: A modelling study., PLoS Med, Vol: 20
BACKGROUND: Vaccines have reduced severe disease and death from Coronavirus Disease 2019 (COVID-19). However, with evidence of waning efficacy coupled with continued evolution of the virus, health programmes need to evaluate the requirement for regular booster doses, considering their impact and cost-effectiveness in the face of ongoing transmission and substantial infection-induced immunity. METHODS AND FINDINGS: We developed a combined immunological-transmission model parameterised with data on transmissibility, severity, and vaccine effectiveness. We simulated Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) transmission and vaccine rollout in characteristic global settings with different population age-structures, contact patterns, health system capacities, prior transmission, and vaccine uptake. We quantified the impact of future vaccine booster dose strategies with both ancestral and variant-adapted vaccine products, while considering the potential future emergence of new variants with modified transmission, immune escape, and severity properties. We found that regular boosting of the oldest age group (75+) is an efficient strategy, although large numbers of hospitalisations and deaths could be averted by extending vaccination to younger age groups. In countries with low vaccine coverage and high infection-derived immunity, boosting older at-risk groups was more effective than continuing primary vaccination into younger ages in our model. Our study is limited by uncertainty in key parameters, including the long-term durability of vaccine and infection-induced immunity as well as uncertainty in the future evolution of the virus. CONCLUSIONS: Our modelling suggests that regular boosting of the high-risk population remains an important tool to reduce morbidity and mortality from current and future SARS-CoV-2 variants. Our results suggest that focusing vaccination in the highest-risk cohorts will be the most efficient (and hence cost-effective) strateg
Bhatia S, Imai N, Watson OJ, et al., 2023, Lessons from COVID-19 for re-scalable data collection, Lancet Infectious Diseases, Vol: 23, Pages: E383-E388, ISSN: 1473-3099
Novel data and analyses have played an important role in informing the public health response to the COVID-19 pandemic. Existing surveillance systems were scaled up, and in some instances, new systems developed to meet the challenges posed by the magnitude of the pandemic. Here, we describe the routine and novel data that were used to address urgentpublic health questions during the pandemic, underscore challenges in sustainability and equity in data generation, and highlight key lessons learnt for designing scalable data collection systems to support decision-making during a public health crisis.As countries emerge from the acute phase of the pandemic, COVID-19 surveillance systems are being scaled down. However, as SARS-CoV-2 resurgence remains a threat to global health security, it is important that a minimal cost-effective system remains active that can be rapidly scaled up if necessary. We propose that a retrospective evaluation to identify the cost-benefit profile of the various data streams collected during the pandemic should be on the scientific research agenda.
Hogan A, Doohan P, Wu S, et al., 2023, Estimating long-term vaccine effectiveness against SARS-CoV-2 variants: a model-based approach, Nature Communications, Vol: 14, Pages: 1-10, ISSN: 2041-1723
With the ongoing evolution of the SARS-CoV-2 virus updated vaccines may be needed. We fitted a model linking immunity levels and protection to vaccine effectiveness data from England for three vaccines (Oxford/AstraZeneca AZD1222, Pfizer-BioNTech BNT162b2, Moderna mRNA-1273) and two variants (Delta, Omicron). Our model reproduces the observed sustained protection against hospitalisation and death from the Omicron variant over the first six months following dose 3 with the monovalent vaccines but projects a gradual waning to moderate protection after 1 year. Switching the fourth dose to a variant-matched vaccine against Omicron BA.1/2 is projected to prevent nearly twice as many hospitalisations and deaths over a 1-year period compared to administering the ancestral vaccine. This result is sensitive to the degree to which immunogenicity data can be used to predict vaccine effectiveness and uncertainty regarding the impact that infection-induced immunity (not captured here) may play in modifying future vaccine effectiveness.
Chemwor GC, Andagalu BM, Onyango IA, et al., 2023, Therapeutic response to artemisinin combination therapies among individuals with<i> Plasmodium</i><i> falciparum</i> single infection vs mixed<i> Plasmodium</i> species infections: a retrospective<i> posthoc</i> analysis in Kisumu County, western Kenya, Publisher: ELSEVIER SCI LTD
Bhatia S, Imai N, Watson OJ, et al., 2023, Lessons from COVID-19 for rescalable data collection (May, 10.1016/S1473-3099(23)00121-4, 2023), LANCET INFECTIOUS DISEASES, Vol: 23, Pages: E227-E227, ISSN: 1473-3099
Sheppard R, Watson OJ, Pieciak R, et al., 2023, Using mortuary and burial data to place COVID-19 in Lusaka, Zambia within a global context, Nature Communications, Vol: 14, Pages: 1-15, ISSN: 2041-1723
Reported COVID-19 cases and associated mortality remain low in many sub-Saharan countries relative to global averages, but true impact is difficult to estimate given limitations around surveillance and mortality registration. In Lusaka, Zambia, burial registration and SARS-CoV-2prevalence data during 2020 allow estimation of excess mortality and transmission. Relative to pre-pandemic patterns, we estimate age-dependent mortality increases, totalling 3,212 excess deaths (95% CrI: 2,104-4,591), representing an 18.5% (95% CrI: 13.0-25.2%) increase relative to pre-pandemic levels. Using a dynamical model-based inferential framework, we find that these mortalitypatterns and SARS-CoV-2 prevalence data are in agreement with established COVID-19 severity estimates. Our results support hypotheses that COVID-19 impact in Lusaka during 2020 was consistent with COVID-19 epidemics elsewhere, without requiring exceptional explanations for low reported figures. For more equitable decision-making during future pandemics, barriers to ascertaining attributable mortality in low-income settings must be addressed and factored into discourse around reported impact differences.
McCabe R, Sheppard R, Abdelmagid N, et al., 2023, Alternative epidemic indicators for COVID-19 in three settings with incomplete death registration systems, Science Advances, Vol: 23, Pages: 1-10, ISSN: 2375-2548
Not all COVID-19 deaths are officially reported, and particularly in low-income and humanitarian settings, the magnitude of reporting gaps remains sparsely characterized. Alternative data sources, including burial site worker reports, satellite imagery of cemeteries, and social media–conducted surveys of infection may offer solutions. By merging these data with independently conducted, representative serological studies within a mathematical modeling framework, we aim to better understand the range of underreporting using examples from three major cities: Addis Ababa (Ethiopia), Aden (Yemen), and Khartoum (Sudan) during 2020. We estimate that 69 to 100%, 0.8 to 8.0%, and 3.0 to 6.0% of COVID-19 deaths were reported in each setting, respectively. In future epidemics, and in settings where vital registration systems are limited, using multiple alternative data sources could provide critically needed, improved estimates of epidemic impact. However, ultimately, these systems are needed to ensure that, in contrast to COVID-19, the impact of future pandemics or other drivers of mortality is reported and understood worldwide.
Paschalidis A, Watson O, Aydemir O, et al., 2023, <i>coiaf</i>: Directly estimating complexity of infection with allele frequencies, PLOS COMPUTATIONAL BIOLOGY, Vol: 19, ISSN: 1553-734X
Kirby R, Giesbrecht D, Karema C, et al., 2023, Examining the Early Distribution of the Artemisinin-Resistant Plasmodium falciparum kelch13 R561H Mutation in Areas of Higher Transmission in Rwanda., Open Forum Infect Dis, Vol: 10, ISSN: 2328-8957
BACKGROUND: Artemisinin resistance mutations in Plasmodium falciparum kelch13 (Pfk13) have begun to emerge in Africa, with Pfk13-R561H being the first reported in Rwanda in 2014, but limited sampling left questions about its early distribution and origin. METHODS: We genotyped P. falciparum positive dried blood spot (DBS) samples from a nationally representative 2014-2015 Rwanda Demographic Health Surveys (DHS) HIV study. DBS were subsampled from DHS sampling clusters with >15% P. falciparum prevalence, as determined by rapid testing or microscopy done during the DHS study (n clusters = 67, n samples = 1873). RESULTS: We detected 476 parasitemias among 1873 residual blood spots from a 2014-2015 Rwanda Demographic Health Survey. We sequenced 351 samples: 341/351 were wild-type (97.03% weighted), and 4 samples (1.34% weighted) harbored R561H that were significantly spatially clustered. Other nonsynonymous mutations found were V555A (3), C532W (1), and G533A (1). CONCLUSIONS: Our study better defines the early distribution of R561H in Rwanda. Previous studies only observed the mutation in Masaka as of 2014, but our study indicates its presence in higher-transmission regions in the southeast of the country at that time.
Ben A, Watson OJ, Onyango I, et al., 2023, Malaria Transmission Dynamics in a High-Transmission Setting of Western Kenya and the Inadequate Treatment Response to Artemether-Lumefantrine in an Asymptomatic Population, CLINICAL INFECTIOUS DISEASES, Vol: 76, Pages: 704-712, ISSN: 1058-4838
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Andagalu B, Watson OJ, Onyango I, et al., 2023, Reply to Blanken et al, CLINICAL INFECTIOUS DISEASES, Vol: 76, Pages: 557-559, ISSN: 1058-4838
Kirby R, Giesbrecht D, Karema C, et al., 2022, Examining the early distribution of the artemisinin-resistant<i>Plasmodium falciparum</i>kelch13 R561H mutation in Rwanda
<jats:title>Abstract</jats:title><jats:p>Artemisinin resistance mutations in<jats:italic>Plasmodium falciparum kelch13</jats:italic>(<jats:italic>Pfk13</jats:italic>) have begun to emerge in Africa.<jats:italic>Pfk13-</jats:italic>R561H was the first reported African mutation found in Rwanda in 2014, but limited sampling left questions about its early distribution and origin. We detected 476 parasitemias among 1873 residual blood spots from a 2014-15 Rwanda Demographic Health Survey. We sequenced 351 samples revealing 341/351 were wild type (97.03% weighted) and 4 samples (1.34% weighted) harbored R561H which were significantly spatially clustered. Our study better defines the early distribution of R561H in Rwanda and suggests that the origin may have involved higher-transmission regions.</jats:p>
Watson OJ, Gao B, Nguyen TD, et al., 2022, Pre-existing partner-drug resistance to artemisinin combination therapies facilitates the emergence and spread of artemisinin resistance: a consensus modelling study, The Lancet Microbe, Vol: 3, Pages: e701-e710, ISSN: 2666-5247
BACKGROUND: Artemisinin-resistant genotypes of Plasmodium falciparum have now emerged a minimum of six times on three continents despite recommendations that all artemisinins be deployed as artemisinin combination therapies (ACTs). Widespread resistance to the non-artemisinin partner drugs in ACTs has the potential to limit the clinical and resistance benefits provided by combination therapy. We aimed to model and evaluate the long-term effects of high levels of partner-drug resistance on the early emergence of artemisinin-resistant genotypes. METHODS: Using a consensus modelling approach, we used three individual-based mathematical models of Plasmodium falciparum transmission to evaluate the effects of pre-existing partner-drug resistance and ACT deployment on the evolution of artemisinin resistance. Each model simulates 100 000 individuals in a particular transmission setting (malaria prevalence of 1%, 5%, 10%, or 20%) with a daily time step that updates individuals' infection status, treatment status, immunity, genotype-specific parasite densities, and clinical state. We modelled varying access to antimalarial drugs if febrile (coverage of 20%, 40%, or 60%) with one primary ACT used as first-line therapy: dihydroartemisinin-piperaquine (DHA-PPQ), artesunate-amodiaquine (ASAQ), or artemether-lumefantrine (AL). The primary outcome was time until 0·25 580Y allele frequency for artemisinin resistance (the establishment time). FINDINGS: Higher frequencies of pre-existing partner-drug resistant genotypes lead to earlier establishment of artemisinin resistance. Across all models, a 10-fold increase in the frequency of partner-drug resistance genotypes on average corresponded to loss of artemisinin efficacy 2-12 years earlier. Most reductions in time to artemisinin resistance establishment were observed after an increase in frequency of the partner-drug resistance genotype from 0·0 to 0·10. INTERPRETATION: Partner-drug resistance in ACTs facil
Watson O, Barnsley G, Toor J, et al., 2022, Global impact of the first year of COVID-19 vaccination: a mathematical modelling study, Lancet Infectious Diseases, Vol: 22, Pages: 1293-1302, ISSN: 1473-3099
Background:The first COVID-19 vaccine outside a clinical trial setting was administered on Dec 8, 2020. To ensure global vaccine equity, vaccine targets were set by the COVID-19 Vaccines Global Access (COVAX) Facility and WHO. However, due to vaccine shortfalls, these targets were not achieved by the end of 2021. We aimed to quantify the global impact of the first year of COVID-19 vaccination programmes.Methods:A mathematical model of COVID-19 transmission and vaccination was separately fit to reported COVID-19 mortality and all-cause excess mortality in 185 countries and territories. The impact of COVID-19 vaccination programmes was determined by estimating the additional lives lost if no vaccines had been distributed. We also estimated the additional deaths that would have been averted had the vaccination coverage targets of 20% set by COVAX and 40% set by WHO been achieved by the end of 2021.Findings:Based on official reported COVID-19 deaths, we estimated that vaccinations prevented 14·4 million (95% credible interval [Crl] 13·7–15·9) deaths from COVID-19 in 185 countries and territories between Dec 8, 2020, and Dec 8, 2021. This estimate rose to 19·8 million (95% Crl 19·1–20·4) deaths from COVID-19 averted when we used excess deaths as an estimate of the true extent of the pandemic, representing a global reduction of 63% in total deaths (19·8 million of 31·4 million) during the first year of COVID-19 vaccination. In COVAX Advance Market Commitment countries, we estimated that 41% of excess mortality (7·4 million [95% Crl 6·8–7·7] of 17·9 million deaths) was averted. In low-income countries, we estimated that an additional 45% (95% CrI 42–49) of deaths could have been averted had the 20% vaccination coverage target set by COVAX been met by each country, and that an additional 111% (105–118) of deaths could have been averted had the 40% target set by
Whittaker C, Watson O, Alvarez-Moreno C, et al., 2022, Understanding the Potential Impact of Different Drug Properties On SARS-CoV-2 Transmission and Disease Burden: A Modelling Analysis, Clinical Infectious Diseases, Vol: 75, Pages: e224-e233, ISSN: 1058-4838
BackgroundThe public health impact of the COVID-19 pandemic has motivated a rapid search for potential therapeutics, with some key successes. However, the potential impact of different treatments, and consequently research and procurement priorities, have not been clear.MethodsUsing a mathematical model of SARS-CoV-2 transmission, COVID-19 disease and clinical care, we explore the public-health impact of different potential therapeutics, under a range of scenarios varying healthcare capacity, epidemic trajectories; and drug efficacy in the absence of supportive care.ResultsThe impact of drugs like dexamethasone (delivered to the most critically-ill in hospital and whose therapeutic benefit is expected to depend on the availability of supportive care such as oxygen and mechanical ventilation) is likely to be limited in settings where healthcare capacity is lowest or where uncontrolled epidemics result in hospitals being overwhelmed. As such, it may avert 22% of deaths in high-income countries but only 8% in low-income countries (assuming R=1.35). Therapeutics for different patient populations (those not in hospital, early in the course of infection) and types of benefit (reducing disease severity or infectiousness, preventing hospitalisation) could have much greater benefits, particularly in resource-poor settings facing large epidemics.ConclusionsAdvances in the treatment of COVID-19 to date have been focussed on hospitalised-patients and predicated on an assumption of adequate access to supportive care. Therapeutics delivered earlier in the course of infection that reduce the need for healthcare or reduce infectiousness could have significant impact, and research into their efficacy and means of delivery should be a priority.
Ghafari M, Watson OJ, Karlinsky A, et al., 2022, A framework for reconstructing SARS-CoV-2 transmission dynamics using excess mortality data, NATURE COMMUNICATIONS, Vol: 13
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Paschalidis A, Watson OJ, Aydemir O, et al., 2022, coiaf: directly estimating complexity of infection with allele frequencies
<jats:title>Abstract</jats:title><jats:p>In malaria, individuals are often infected with different parasite strains; the complexity of infection (COI) is defined as the number of genetically distinct parasite strains in an individual. Changes in the mean COI in a population have been shown to be informative of changes in transmission intensity with a number of probabilistic likelihood and Bayesian models now developed to estimate the COI. However, rapid, direct measures based on heterozygosity or <jats:italic>FwS</jats:italic> do not properly represent the COI. In this work, we present two new methods that use easily calculated measures to directly estimate the COI from allele frequency data. Using a simulation framework, we show that our methods are computationally efficient and comparably accurate to current methods in the literature. Through a sensitivity analysis, we characterize how the bias and accuracy of our two methods are impacted by the distribution of parasite densities and the assumed sequencing depth and number of sampled loci. We further estimate the COI globally from <jats:italic>Plasmodium falciparum</jats:italic> sequencing data using our developed methods and compare the results against the literature. We show significant differences in estimated COI globally between continents and a weak relationship between malaria prevalence and COI.</jats:p><jats:sec><jats:title>Author summary</jats:title><jats:p>Computational models, used in conjunction with rapidly advancing sequencing technologies, are increasingly being used to help inform surveillance efforts and understand the epidemiological dynamics of malaria. One such important metric, the complexity of infection (COI), indirectly quantifies the level of transmission. Existing “gold-standard” COI measures rely on complex probabilistic likelihood and Bayesian models. As an alternative, we have developed the statistics
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.
Pons-Salort M, John J, Watson OJ, et al., 2022, Reassessing reported deaths and estimated infection attack rate during the first 6 months of the COVID-19 epidemic, Delhi, India., Emerging Infectious Diseases, Vol: 28, ISSN: 1080-6040
India reported >10 million coronavirus disease (COVID-19) cases and 149,000 deaths in 2020. To reassess reported deaths and estimate incidence rates during the first 6 months of the epidemic, we used a severe acute respiratory syndrome coronavirus 2 transmission model fit to data from 3 serosurveys in Delhi and time-series documentation of reported deaths. We estimated 48.7% (95% credible interval 22.1%-76.8%) cumulative infection in the population through the end of September 2020. Using an age-adjusted overall infection fatality ratio based on age-specific estimates from mostly high-income countries, we estimated that just 15.0% (95% credible interval 9.3%-34.0%) of COVID-19 deaths had been reported, indicating either substantial underreporting or lower age-specific infection-fatality ratios in India than in high-income countries. Despite the estimated high attack rate, additional epidemic waves occurred in late 2020 and April-May 2021. Future dynamics will depend on the duration of natural and vaccine-induced immunity and their effectiveness against new variants.
Olivera Mesa D, Hogan A, Watson O, et al., 2022, Modelling the impact of vaccine hesitancy in prolonging the need for Non-Pharmaceutical Interventions to control the COVID-19 pandemic, Communications Medicine, Vol: 2, ISSN: 2730-664X
Background: Vaccine hesitancy – a delay in acceptance or refusal of vaccines despite availability – has the potential to threaten the successful roll-out of SARS-CoV-2 vaccines globally. In this study we aim to understand the likely impact of vaccine hesitancy on the control of the COVID-1924pandemic. Methods: We modelled the potential impact of vaccine hesitancy on the control of the pandemic and the relaxation of non-pharmaceutical interventions (NPIs) by combining an epidemiological model of SARS-CoV-2 transmission with data on vaccine hesitancy from population surveys.Results: Our simulations suggest that the mortality over a 2-year period could be up to 7.6 times higher in countries with high vaccine hesitancy compared to an ideal vaccination uptake if NPIs are relaxed. Alternatively, high vaccine hesitancy could prolong the need for NPIs to remain in place.Conclusions: While vaccination is an individual choice, vaccine hesitant individuals have a substantial impact on the pandemic trajectory, which may challenge current efforts to control COVID-19. In order to prevent such outcomes, addressing vaccine hesitancy with behavioural interventions is an important priority in the control of the COVID-19 pandemic.
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>
Favas C, Jarrett P, Ratnayake R, et al., 2022, Country differences in transmissibility, age distribution and case-fatality of SARS-CoV-2: a global ecological analysis, INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES, Vol: 114, Pages: 210-218, ISSN: 1201-9712
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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.
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.
Paschalidis A, Watson OJ, Verity RJ, et al., 2021, COMPLEXITY OF INFECTION ESTIMATION WITH ALLELE FREQUENCIES, Publisher: AMER SOC TROP MED & HYGIENE, Pages: 216-216, ISSN: 0002-9637
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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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.
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