Publications
118 results found
Gaythorpe K, Imai N, Cuomo-Dannenburg G, et al., 2020, Report 8: Symptom progression of COVID-19
The COVID-19 epidemic was declared a Public Health Emergency of International Concern (PHEIC) by WHO on 30th January 2020 [1]. As of 8 March 2020, over 107,000 cases had been reported. Here, we use published and preprint studies of clinical characteristics of cases in mainland China as well as case studies of individuals from Hong Kong, Japan, Singapore and South Korea to examine the proportional occurrence of symptoms and the progression of symptoms through time.We find that in mainland China, where specific symptoms or disease presentation are reported, pneumonia is the most frequently mentioned, see figure 1. We found a more varied spectrum of severity in cases outside mainland China. In Hong Kong, Japan, Singapore and South Korea, fever was the most frequently reported symptom. In this latter group, presentation with pneumonia is not reported as frequently although it is more common in individuals over 60 years old. The average time from reported onset of first symptoms to the occurrence of specific symptoms or disease presentation, such as pneumonia or the use of mechanical ventilation, varied substantially. The average time to presentation with pneumonia is 5.88 days, and may be linked to testing at hospitalisation; fever is often reported at onset (where the mean time to develop fever is 0.77 days).
Thompson H, Imai N, Dighe A, et al., 2020, Report 7: Estimating infection prevalence in Wuhan City from repatriation flights
Since the end of January 2020, in response to the growing COVID-19 epidemic, 55 countries have repatriated over 8000 citizens from Wuhan City, China. In addition to quarantine measures for returning citizens, many countries implemented PCR screening to test for infection regardless of symptoms. These flights therefore give estimates of infection prevalence in Wuhan over time. Between 30th January and 1st February (close to the peak of the epidemic in Wuhan), infection prevalence was 0.87% (95% CI: 0.32% - 1.89%). As countries now start to repatriate citizens from Iran and northern Italy, information from repatriated citizens could help inform the level of response necessary to help control the outbreaks unfolding in newly affected areas.
Bhatia S, Imai N, Cuomo-Dannenburg G, et al., 2020, Report 6: Relative sensitivity of international surveillance, Report 6: Relative sensitivity of international surveillance
Since the start of the COVID-19 epidemic in late 2019, there are now 29 affected countries with over 1000 confirmed cases outside of mainland China. In previous reports, we estimated the likely epidemic size in Wuhan City based on air traffic volumes and the number of detected cases internationally. Here we analysed COVID-19 cases exported from mainland China to different regions and countries, comparing the country-specific rates of detected and confirmed cases per flight volume to estimate the relative sensitivity of surveillance in different countries. Although travel restrictions from Wuhan City and other cities across China may have reduced the absolute number of travellers to and from China, we estimated that about two thirds of COVID-19 cases exported from mainland China have remained undetected worldwide, potentially resulting in multiple chains of as yet undetected human-to-human transmission outside mainland China.
Volz E, Baguelin M, Bhatia S, et al., 2020, Report 5: Phylogenetic analysis of SARS-CoV-2
Genetic diversity of SARS-CoV-2 (formerly 2019-nCoV), the virus which causes COVID-19, provides information about epidemic origins and the rate of epidemic growth. By analysing 53 SARS-CoV-2 whole genome sequences collected up to February 3, 2020, we find a strong association between the time of sample collection and accumulation of genetic diversity. Bayesian and maximum likelihood phylogenetic methods indicate that the virus was introduced into the human population in early December and has an epidemic doubling time of approximately seven days. Phylodynamic modelling provides an estimate of epidemic size through time. Precise estimates of epidemic size are not possible with current genetic data, but our analyses indicate evidence of substantial heterogeneity in the number of secondary infections caused by each case, as indicated by a high level of over-dispersion in the reproduction number. Larger numbers of more systematically sampled sequences – particularly from across China – will allow phylogenetic estimates of epidemic size and growth rate to be substantially refined.
Dorigatti I, Okell L, Cori A, et al., 2020, Report 4: Severity of 2019-novel coronavirus (nCoV)
We present case fatality ratio (CFR) estimates for three strata of 2019-nCoV infections. For cases detected in Hubei, we estimate the CFR to be 18% (95% credible interval: 11%-81%). For cases detected in travellers outside mainland China, we obtain central estimates of the CFR in the range 1.2-5.6% depending on the statistical methods, with substantial uncertainty around these central values. Using estimates of underlying infection prevalence in Wuhan at the end of January derived from testing of passengers on repatriation flights to Japan and Germany, we adjusted the estimates of CFR from either the early epidemic in Hubei Province, or from cases reported outside mainland China, to obtain estimates of the overall CFR in all infections (asymptomatic or symptomatic) of approximately 1% (95% confidence interval 0.5%-4%). It is important to note that the differences in these estimates does not reflect underlying differences in disease severity between countries. CFRs seen in individual countries will vary depending on the sensitivity of different surveillance systems to detect cases of differing levels of severity and the clinical care offered to severely ill cases. All CFR estimates should be viewed cautiously at the current time as the sensitivity of surveillance of both deaths and cases in mainland China is unclear. Furthermore, all estimates rely on limited data on the typical time intervals from symptom onset to death or recovery which influences the CFR estimates.
Imai N, Cori A, Dorigatti I, et al., 2020, Report 3: Transmissibility of 2019-nCoV
Self-sustaining human-to-human transmission of the novel coronavirus (2019-nCov) is the only plausible explanation of the scale of the outbreak in Wuhan. We estimate that, on average, each case infected 2.6 (uncertainty range: 1.5-3.5) other people up to 18th January 2020, based on an analysis combining our past estimates of the size of the outbreak in Wuhan with computational modelling of potential epidemic trajectories. This implies that control measures need to block well over 60% of transmission to be effective in controlling the outbreak. It is likely, based on the experience of SARS and MERS-CoV, that the number of secondary cases caused by a case of 2019-nCoV is highly variable – with many cases causing no secondary infections, and a few causing many. Whether transmission is continuing at the same rate currently depends on the effectiveness of current control measures implemented in China and the extent to which the populations of affected areas have adopted risk-reducing behaviours. In the absence of antiviral drugs or vaccines, control relies upon the prompt detection and isolation of symptomatic cases. It is unclear at the current time whether this outbreak can be contained within China; uncertainties include the severity spectrum of the disease caused by this virus and whether cases with relatively mild symptoms are able to transmit the virus efficiently. Identification and testing of potential cases need to be as extensive as is permitted by healthcare and diagnostic testing capacity – including the identification, testing and isolation of suspected cases with only mild to moderate disease (e.g. influenza-like illness), when logistically feasible.
Tsuzuki S, Baguelin M, Pebody R, et al., 2020, Modelling the optimal target age group for seasonal influenza vaccination in Japan, VACCINE, Vol: 38, Pages: 752-762, ISSN: 0264-410X
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- Citations: 7
Hodgson D, Atkins KE, Baguelin M, et al., 2020, Estimates for quality of life loss due to Respiratory Syncytial Virus, INFLUENZA AND OTHER RESPIRATORY VIRUSES, Vol: 14, Pages: 19-27, ISSN: 1750-2640
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- Citations: 11
Bhatia S, Imai N, Cuomo-Dannenburg G, et al., 2020, Estimating the number of undetected COVID-19 cases among travellers from mainland China., Wellcome open research, Vol: 5, Pages: 143-143, ISSN: 2398-502X
Background: As of August 2021, every region of the world has been affected by the COVID-19 pandemic, with more than 196,000,000 cases worldwide.Methods: We analysed COVID-19 cases among travellers from mainland China to different regions and countries, comparing the region- and country-specific rates of detected and confirmed cases per flight volume to estimate the relative sensitivity of surveillance in different regions and countries.Results: Although travel restrictions from Wuhan City and other cities across China may have reduced the absolute number of travellers to and from China, we estimated that up to 70% (95% CI: 54% - 80%) of imported cases could remain undetected relative to the sensitivity of surveillance in Singapore. The percentage of undetected imported cases rises to 75% (95% CI 66% - 82%) when comparing to the surveillance sensitivity in multiple countries.Conclusions: Our analysis shows that a large number of COVID-19 cases remain undetected across the world. These undetected cases potentially resulted in multiple chains of human-to-human transmission outside mainland China.
Baguelin M, 2020, The Analysis of Serological Data with Transmission Models, HANDBOOK OF INFECTIOUS DISEASE DATA ANALYSIS, Editors: Held, Hens, ONeill, Wallinga, Publisher: CRC PRESS-TAYLOR & FRANCIS GROUP, Pages: 315-334
Jeffrey B, Walters CE, Ainslie KEC, et al., 2020, Anonymised and aggregated crowd level mobility data from mobile phones suggests that initial compliance with COVID-19 social distancing interventions was high and geographically consistent across the UK., Wellcome Open Res, Vol: 5, ISSN: 2398-502X
Background: Since early March 2020, the COVID-19 epidemic across the United Kingdom has led to a range of social distancing policies, which have resulted in reduced mobility across different regions. Crowd level data on mobile phone usage can be used as a proxy for actual population mobility patterns and provide a way of quantifying the impact of social distancing measures on changes in mobility. Methods: Here, we use two mobile phone-based datasets (anonymised and aggregated crowd level data from O2 and from the Facebook app on mobile phones) to assess changes in average mobility, both overall and broken down into high and low population density areas, and changes in the distribution of journey lengths. Results: We show that there was a substantial overall reduction in mobility, with the most rapid decline on the 24th March 2020, the day after the Prime Minister's announcement of an enforced lockdown. The reduction in mobility was highly synchronized across the UK. Although mobility has remained low since 26th March 2020, we detect a gradual increase since that time. We also show that the two different datasets produce similar trends, albeit with some location-specific differences. We see slightly larger reductions in average mobility in high-density areas than in low-density areas, with greater variation in mobility in the high-density areas: some high-density areas eliminated almost all mobility. Conclusions: These analyses form a baseline from which to observe changes in behaviour in the UK as social distancing is eased and inform policy towards the future control of SARS-CoV-2 in the UK.
Chatzilena A, van Leeuwen E, Ratmann O, et al., 2019, Contemporary statistical inference for infectious disease models using Stan, Epidemics: the journal of infectious disease dynamics, Vol: 29, ISSN: 1755-4365
This paper is concerned with the application of recent statistical advances to inference of infectious disease dynamics. We describe the fitting of a class of epidemic models using Hamiltonian Monte Carlo and variational inference as implemented in the freely available Stan software. We apply the two methods to real data from outbreaks as well as routinely collected observations. Our results suggest that both inference methods are computationally feasible in this context, and show a trade-off between statistical efficiency versus computational speed. The latter appears particularly relevant for real-time applications.
Endo A, van Leeuwen E, Baguelin M, 2019, Introduction to particle Markov-chain Monte Carlo for disease dynamics modellers, EPIDEMICS, Vol: 29, ISSN: 1755-4365
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- Citations: 29
Panovska-Griffiths J, Grieco L, van Leeuwen E, et al., 2019, Are we prepared for the next influenza pandemic? Lessons from modelling different preparedness policies against four pandemic scenarios, JOURNAL OF THEORETICAL BIOLOGY, Vol: 481, Pages: 223-232, ISSN: 0022-5193
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- Citations: 12
Hodgson D, Pebody R, Panovska-Griffiths J, et al., 2019, Cost-effectiveness of the next generation of RSV intervention strategies
<jats:title>ABSTRACT</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>With a suite of promising new RSV prophylactics on the horizon, including long-acting monoclonal antibodies and new vaccines, it is likely that one or more of these will replace the current monoclonal Palivizumab programme. However, choosing the optimal intervention programme will require balancing the costs of the programmes with the health benefits accrued.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>To compare the next generation of RSV prophylactics, we integrated a novel transmission model with an economic analysis. We estimated key epidemiological parameters by calibrating the model to seven years of historical epidemiological data using a Bayesian approach. We determined the cost-effective and affordable maximum purchase price for a comprehensive suite of intervention programmes.</jats:p></jats:sec><jats:sec><jats:title>Findings</jats:title><jats:p>Our transmission model suggests that maternal protection of infants is seasonal, with 2-14% of infants born with protection against RSV. Our economic analysis found that to cost-effectively and affordably replace the current monoclonal antibody Palivizumab programme with long-acting monoclonal antibodies, the purchase price per dose would have to be less than around £4,350 but dropping to £200 for vaccinated heightened risk infants or £90 for all infants. A seasonal maternal vaccine would have to be priced less than £85 to be cost-effective and affordable. While vaccinating pre-school and school-age children is likely not cost-effective relative to elderly vaccination programmes, vaccinating the elderly is not likely to be affordable. Conversely, vaccinating infants at 2 months seasonally would be cost-effective and affordable if priced less than £80.</jats:p></
Robert A, Camacho A, Edmunds WJ, et al., 2019, Control of Ebola virus disease outbreaks: Comparison of health care worker-targeted and community vaccination strategies, Epidemics, Vol: 27, Pages: 106-114, ISSN: 1755-4365
BackgroundHealth care workers (HCW) are at risk of infection during Ebola virus disease outbreaks and therefore may be targeted for vaccination before or during outbreaks. The effect of these strategies depends on the role of HCW in transmission which is understudied.MethodsTo evaluate the effect of HCW-targeted or community vaccination strategies, we used a transmission model to explore the relative contribution of HCW and the community to transmission. We calibrated the model to data from multiple Ebola outbreaks. We quantified the impact of ahead-of-time HCW-targeted strategies, and reactive HCW and community vaccination.ResultsWe found that for some outbreaks (we call “type 1″) HCW amplified transmission both to other HCW and the community, and in these outbreaks prophylactic vaccination of HCW decreased outbreak size. Reactive vaccination strategies had little effect because type 1 outbreaks ended quickly. However, in outbreaks with longer time courses (“type 2 outbreaks”), reactive community vaccination decreased the number of cases, with or without prophylactic HCW-targeted vaccination. For both outbreak types, we found that ahead-of-time HCW-targeted strategies had an impact at coverage of 30%.ConclusionsThe vaccine strategies tested had a different impact depending on the transmission dynamics and previous control measures. Although we will not know the characteristics of a new outbreak, ahead-of-time HCW-targeted vaccination can decrease the total outbreak size, even at low vaccine coverage.
Kombe IK, Munywoki PK, Baguelin M, et al., 2019, Model-based estimates of transmission of respiratory syncytial virus within households, Epidemics: the journal of infectious disease dynamics, Vol: 27, Pages: 1-11, ISSN: 1755-4365
IntroductionRespiratory syncytial virus (RSV) causes a significant respiratory disease burden in the under 5 population. The transmission pathway to young children is not fully quantified in low-income settings, and this information is required to design interventions.MethodsWe used an individual level transmission model to infer transmission parameters using data collected from 493 individuals distributed across 47 households over a period of 6 months spanning the 2009/2010 RSV season. A total of 208 episodes of RSV were observed from 179 individuals. We model competing transmission risk from within household exposure and community exposure while making a distinction between RSV groups A and B.ResultsWe find that 32–53% of all RSV transmissions are between members of the same household; the rate of pair-wise transmission is 58% (95% CrI: 30–74%) lower in larger households (≥8 occupants) than smaller households; symptomatic individuals are 2–7 times more infectious than asymptomatic individuals i.e. 2.48 (95% CrI: 1.22–5.57) among symptomatic individuals with low viral load and 6.7(95% CrI: 2.56–16) among symptomatic individuals with high viral load; previous infection reduces susceptibility to re-infection within the same epidemic by 47% (95% CrI: 17%–68%) for homologous RSV group and 39% (95%CrI: -8%-69%) for heterologous group; RSV B is more frequently introduced into the household, and RSV A is more rapidly transmitted once in the household.DiscussionOur analysis presents the first transmission modelling of cohort data for RSV and we find that it is important to consider the household social structuring and household size when modelling transmission. The increased infectiousness of symptomatic individuals implies that a vaccine against RSV related disease would also have an impact on infection transmission. Together, the weak cross immunity between RSV groups and the possibility of different transmission niches could form p
Thorrington D, van Leeuwen E, Ramsay M, et al., 2019, Assessing optimal use of the standard dose adjuvanted trivalent seasonal influenza vaccine in the elderly, VACCINE, Vol: 37, Pages: 2051-2056, ISSN: 0264-410X
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- Citations: 11
Hughes J, Allen RC, Baguelin M, et al., 2018, Transmission of equine influenza virus during an outbreak is characterized by frequent mixed infections and loose transmission bottlenecks., PLoS Pathogens, Vol: 8, Pages: e1003081-e1003081, ISSN: 1553-7366
The ability of influenza A viruses (IAVs) to cross species barriers and evade host immunity is a major public health concern. Studies on the phylodynamics of IAVs across different scales - from the individual to the population - are essential for devising effective measures to predict, prevent or contain influenza emergence. Understanding how IAVs spread and evolve during outbreaks is critical for the management of epidemics. Reconstructing the transmission network during a single outbreak by sampling viral genetic data in time and space can generate insights about these processes. Here, we obtained intra-host viral sequence data from horses infected with equine influenza virus (EIV) to reconstruct the spread of EIV during a large outbreak. To this end, we analyzed within-host viral populations from sequences covering 90% of the infected yards. By combining gene sequence analyses with epidemiological data, we inferred a plausible transmission network, in turn enabling the comparison of transmission patterns during the course of the outbreak and revealing important epidemiological features that were not apparent using either approach alone. The EIV populations displayed high levels of genetic diversity, and in many cases we observed distinct viral populations containing a dominant variant and a number of related minor variants that were transmitted between infectious horses. In addition, we found evidence of frequent mixed infections and loose transmission bottlenecks in these naturally occurring populations. These frequent mixed infections likely influence the size of epidemics.
Leen G, Baguelin M, 2018, Bayesian coalescent inference of in-host evolution using Next Generation Sequencing
<jats:title>Abstract</jats:title><jats:p>Within an infected individual, influenza virus exists as a heterogeneous population of variants. When representing the viral population as a consensus sequence, information about minority variants is lost. However, using next generation sequencing (NGS), it is possible to identify nucleotide substitutions which segregate at low frequencies in the viral population, and can give insight into the within-host processes that drive the virus’s evolution, and is a step towards understanding the dynamics of the disease. During the course of an infection, mutations may occur, and at each segregating site, the frequency of the derived allele in the population will fluctuate. We develop a method which can use information about the relative frequencies of mutations in NGS data from a viral population sampled at multiple time points, to infer past population dynamics with a Bayesian skyline model. By using coalescent theory, we analytically derive the joint allele frequency spectrum for a population across multiple time points, and relate this to the coalescent intervals generated from the skyline model. We demonstrate the model on data taken from populations of equine influenza virus sampled during an infection, and show that it is possible to infer a posterior distribution of effective viral population size through time. We also show how the model can be used to infer the probability that a mutation occurred within-host, as opposed to being an ancestral mutation which occurred prior to infection.</jats:p><jats:sec id="s1"><jats:title>Author Summary</jats:title><jats:p>When a host is infected by a virus, many particles of the infecting agent enter the body of the host. This viral population is composed of many closely related viruses that continue diversifying by mutating while reproducing in the host. New sequencing technologies allow the quantifying of the proportion of th
Hodgson D, Atkins KE, Baguelin M, et al., 2018, Estimates for quality of life loss due to RSV
<jats:title>Abstract</jats:title><jats:p>A number of vaccines against Respiratory Syncytial Virus (RSV) infection are approaching licensure. Deciding which RSV vaccine strategy, if any, to introduce, will partly depend on cost-effectiveness analyses, which compares the relative costs and health benefits of a potential vaccination programme. Health benefits are usually measured in Quality Adjusted Life Year (QALY) loss, however, there are no QALY loss estimates for RSV that have been determined using standardised instruments. Moreover, in children under the age of five years in whom severe RSV episodes predominantly occur, there are no appropriate standardised instruments to estimate QALY loss. We estimated the QALY loss due to RSV across all ages by developing a novel regression model which predicts the QALY loss without the use of standardised instruments. To do this, we conducted a surveillance study which targeted confirmed episodes in children under the age of five years (confirmed cases) and their household members who experienced symptoms of RSV during the same time (suspected cases.) All participants were asked to complete questions regarding their health during the infection, with the suspected cases aged 5–14 and 15+ years old additionally providing Health-Related Quality of Life (HR-QoL) loss estimates through completing EQ-5D-3L-Y and EQ-5D-3L instruments respectively. The questionnaire responses from the suspected cases were used to calibrate the regression model. The calibrated regression model then used other questionnaire responses to predict the HR-QoL loss without the use of EQ-5D instruments. The age-specific QALY loss was then calculated by multiplying the HR-QoL loss on the worst day predicted from the regression model, with estimates for the duration of infection from the questionnaires and a scaling factoring for disease severity. Our regression model for predicting HR-QoL loss estimates that for the worst day of infecti
Mendes D, Mesher D, Pista A, et al., 2018, Understanding differences in cervical cancer incidence in Western Europe: comparing Portugal and England, EUROPEAN JOURNAL OF PUBLIC HEALTH, Vol: 28, Pages: 343-347, ISSN: 1101-1262
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- Citations: 7
Opatowski L, Baguelin M, Eggo RM, 2018, Influenza interaction with cocirculating pathogens and its impact on surveillance, pathogenesis, and epidemic profile: A key role for mathematical modelling, PLoS Pathogens, Vol: 14, ISSN: 1553-7366
Evidence is mounting that influenza virus interacts with other pathogens colonising or infecting the human respiratory tract. Taking into account interactions with other pathogens maybe critical to determining the real influenza burden and the full impact of public health policies targeting influenza. This is particularly true for mathematical modelling studies, whichhave become critical in public health decision-making. Yet models usually focus on influenzavirus acquisition and infection alone, thereby making broad oversimplifications of pathogenecology. Herein, we report evidence of influenza virus interactions with bacteria and virusesand systematically review the modelling studies that have incorporated interactions.Despite the many studies examining possible associations between influenza andStreptococcus pneumoniae, Staphylococcus aureus, Haemophilus influenzae, Neisseriameningitidis, respiratory syncytial virus (RSV), human rhinoviruses, human parainfluenzaviruses, etc., very few mathematical models have integrated other pathogens alongsideinfluenza. The notable exception is the pneumococcus–influenza interaction, for which several recent modelling studies demonstrate the power of dynamic modelling as an approachto test biological hypotheses on interaction mechanisms and estimate the strength of thoseinteractions.We explore how different interference mechanisms may lead to unexpected incidencetrends and possible misinterpretation, and we illustrate the impact of interactions on publichealth surveillance using simple transmission models. We demonstrate that the development of multipathogen models is essential to assessing the true public health burden of influenza and that it is needed to help improve planning and evaluation of control measures.Finally, we identify the public health, surveillance, modelling, and biological challenges andpropose avenues of research for the coming years.
van Leeuwen E, Klepac P, Thorrington D, et al., 2017, fluEvidenceSynthesis: An R package for evidence synthesis based analysis of epidemiological outbreaks, PLOS COMPUTATIONAL BIOLOGY, Vol: 13, ISSN: 1553-734X
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- Citations: 13
Opatowski L, Baguelin M, Eggo R, 2017, Influenza interaction with cocirculating pathogens, and its impact on surveillance, pathogenesis and epidemic profile: a key role for mathematical modeling, Publisher: bioRxiv
ABSTRACT Evidence is mounting that influenza virus, a major contributor to the global disease burden, interacts with other pathogens infecting the human respiratory tract. Taking into account interactions with other pathogens may be critical to determining the real influenza burden and the full impact of public health policies targeting influenza. That necessity is particularly true for mathematical modeling studies, which have become critical in public health decision-making, despite their usually focusing on lone influenza virus acquisition and infection, thereby making broad oversimplifications regarding pathogen ecology. Herein, we review evidence of influenza virus interaction with bacteria and viruses, and the modeling studies that incorporated some of these. Despite the many studies examining possible associations between influenza and Streptococcus pneumoniae, Staphylococcus aureus, Haemophilus influenzae, Neisseria meningitides , respiratory syncytial virus, human rhinoviruses, human parainfluenza viruses, etc., very few mathematical models have integrated other pathogens alongside influenza. A notable exception is the recent modeling of the pneumococcus-influenza interaction, which highlighted potential influenza-related increased pneumococcal transmission and pathogenicity. That example demonstrates the power of dynamic modeling as an approach to test biological hypotheses concerning interaction mechanisms and estimate the strength of those interactions. We explore how different interference mechanisms may lead to unexpected incidence trends and misinterpretations. Using simple transmission models, we illustrate how existing interactions might impact public health surveillance systems and demonstrate that the development of multipathogen models is essential to assess the true public health burden of influenza, and help improve planning and evaluation of control measures. Finally, we identify the public health needs, surveillance, modeling and biological c
Thorrington D, van Leeuwen E, Ramsay M, et al., 2017, Cost-effectiveness analysis of quadrivalent seasonal influenza vaccines in England, BMC Medicine, Vol: 15, ISSN: 1741-7015
BackgroundAs part of the national seasonal influenza vaccination programme in England and Wales, children receive a quadrivalent vaccine offering protection against two influenza A strains and two influenza B strains. Healthy children receive a quadrivalent live attenuated influenza vaccine (QLAIV), whilst children with contraindications receive the quadrivalent inactivated influenza vaccine (QIIV). Individuals aged younger than 65 years in the clinical risk populations and elderly individuals aged 65+ years receive either a trivalent inactivated influenza vaccine (TIIV) offering protection from two A strains and one B strain or the QIIV at the choice of their general practitioner.The cost-effectiveness of quadrivalent vaccine programmes is an open question. The original analysis that supported the paediatric programme only considered a trivalent live attenuated vaccine (LAIV). The cost-effectiveness of the QIIV to other patients has not been established. We sought to estimate the cost-effectiveness of these programmes, establishing a maximum incremental total cost per dose of quadrivalent vaccines over trivalent vaccines.MethodsWe used the same mathematical model as the analysis that recommended the introduction of the paediatric influenza vaccination programme. The incremental cost of the quadrivalent vaccine is the additional cost over that of the existing trivalent vaccine currently in use.ResultsIntroducing quadrivalent vaccines can be cost-effective for all targeted groups. However, the cost-effectiveness of the programme is dependent on the choice of target cohort and the cost of the vaccines: the paediatric programme is cost-effective with an increased cost of £6.36 per dose, though an extension to clinical risk individuals younger than 65 years old and further to all elderly individuals means the maximum incremental cost is £1.84 and £0.20 per dose respectively.ConclusionsQuadrivalent influenza vaccines will bring substantial health benefi
Zhang X-S, Pebody R, Charlett A, et al., 2017, Estimating and modelling the transmissibility of Middle East Respiratory Syndrome CoronaVirus during the 2015 outbreak in the Republic of Korea, INFLUENZA AND OTHER RESPIRATORY VIRUSES, Vol: 11, Pages: 434-444, ISSN: 1750-2640
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- Citations: 18
Kucharski AJ, Baguelin M, 2017, The role of human immunity and social behavior in shaping influenza evolution, PLoS Pathogens, Vol: 13, ISSN: 1553-7366
Mbala P, Baguelin M, Ngay I, et al., 2017, Evaluating the frequency of asymptomatic Ebola virus infection, PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, Vol: 372, ISSN: 0962-8436
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- Citations: 11
Houlihan CF, McGowan CR, Dicks S, et al., 2017, Ebola exposure, illness experience, and Ebola antibody prevalence in international responders to the West African Ebola epidemic 2014-2016: A cross-sectional study, PLOS MEDICINE, Vol: 14, ISSN: 1549-1277
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- Citations: 20
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