Imperial College London

Steven Riley

Faculty of MedicineSchool of Public Health

Professor of Infectious Disease Dynamics
 
 
 
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Contact

 

+44 (0)20 7594 2452s.riley

 
 
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Location

 

UG8Medical SchoolSt Mary's Campus

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Summary

 

Publications

Publication Type
Year
to

152 results found

Pepin KM, Hopken MW, Shriner SA, Spackman E, Abdo Z, Parrish C, Riley S, Lloyd-Smith JO, Piaggio AJet al., 2019, Improving risk assessment of the emergence of novel influenza A viruses by incorporating environmental surveillance, PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, Vol: 374, ISSN: 0962-8436

Journal article

Hay JA, Laurie K, White M, Riley Set al., 2019, Characterising antibody kinetics from multiple influenza infection and vaccination events in ferrets., PLoS Comput Biol, Vol: 15

The strength and breadth of an individual's antibody repertoire is an important predictor of their response to influenza infection or vaccination. Although progress has been made in understanding qualitatively how repeated exposures shape the antibody mediated immune response, quantitative understanding remains limited. We developed a set of mathematical models describing short-term antibody kinetics following influenza infection or vaccination and fit them to haemagglutination inhibition (HI) titres from 5 groups of ferrets which were exposed to different combinations of trivalent inactivated influenza vaccine (TIV with or without adjuvant), A/H3N2 priming inoculation and post-vaccination A/H1N1 inoculation. We fit models with various immunological mechanisms that have been empirically observed but have not previously been included in mathematical models of antibody landscapes, including: titre ceiling effects, antigenic seniority and exposure-type specific cross reactivity. Based on the parameter estimates of the best supported models, we describe a number of key immunological features. We found quantifiable differences in the degree of homologous and cross-reactive antibody boosting elicited by different exposure types. Infection and adjuvanted vaccination generally resulted in strong, broadly reactive responses whereas unadjuvanted vaccination resulted in a weak, narrow response. We found that the order of exposure mattered: priming with A/H3N2 improved subsequent vaccine response, and the second dose of adjuvanted vaccination resulted in substantially greater antibody boosting than the first. Either antigenic seniority or a titre ceiling effect were included in the two best fitting models, suggesting a role for a mechanism describing diminishing antibody boosting with repeated exposures. Although there was considerable uncertainty in our estimates of antibody waning parameters, our results suggest that both short and long term waning were present and would be i

Journal article

Rivers C, Chretien J-P, Riley S, Pavlin JA, Woodward A, Brett-Major D, Berry IM, Morton L, Jarman RG, Biggerstaff M, Johansson MA, Reich NG, Meyer D, Snyder MR, Pollett Set al., 2019, Using "outbreak science" to strengthen the use of models during epidemics, NATURE COMMUNICATIONS, Vol: 10, ISSN: 2041-1723

Journal article

Ben-Nun M, Riley P, Turtle J, Bacon DP, Riley Set al., 2019, Forecasting national and regional influenza-like illness for the USA, PLOS COMPUTATIONAL BIOLOGY, Vol: 15

Journal article

Suwannahitatorn P, Webster J, Riley S, Mungthin M, Donnelly Cet al., 2019, Uncooked fish consumption among those at risk of Opisthorchis viverrini infection in central Thailand, PLoS ONE, Vol: 14, Pages: 1-13, ISSN: 1932-6203

In contrast to northern and northeastern Thailand, central Thailand was believed not to be endemic for Opisthorchis viverrini (OV). Fieldwork conducted in a rural area of central Thailand revealed that the prevalence and incidence were relatively high compared with regional average data. We hypothesized that the behavioural-psycho-social background of the study population might play an important role in the high burden of the infection. As a result, a qualitative study was conducted to highlight potential social determinants of the infection dynamics to gain greater understanding of the risk behaviours and their contexts. A qualitative study using focus group discussion and in-depth interviews was conducted in Na-ngam Village, Chachoengsao Province from 2012–14. Framework analysis was used to explore associations between infection and thematic content. Social influence showed a strong impact on infection dynamics of OV infection. Our results revealed that Koi pla (chopped raw fish salad) remains a popular dish in the community, as the dish itself represents northeastern culture. The cultural norm had been transferred from ancestors to their descendants. Some elders complained that discontinuing the consumption of Koi pla went against old traditions with respect to cultural norms and socialization. In contrast, modern education teaches about hygiene including OV infection risks, and accordingly teenagers and young adults were reported to modify their lifestyles including their eating habits. Children are a potential key to pass knowledge to their parents and school-based education programs can serve as a practical hub for knowledge dissemination. However, health education alone might not lead to behavioural change in other age groups. Therefore, more efforts are needed to support the transformation.

Journal article

Kwok KO, Tang A, Wei VWI, Park WH, Yeoh EK, Riley Set al., 2019, Epidemic models of contact tracing: systematic review of transmission studies of severe acute respiratory syndrome and Middle East respiratory syndrome, Computational and Structural Biotechnology Journal, Vol: 17, Pages: 186-194, ISSN: 2001-0370

The emergence and reemergence of coronavirus epidemics sparked renewed concerns from global epidemiology researchers and public health administrators. Mathematical models that represented how contact tracing and follow-up may control Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) transmissions were developed for evaluating different infection control interventions, estimating likely number of infections as well as facilitating understanding of their likely epidemiology. We reviewed mathematical models for contact tracing and follow-up control measures of SARS and MERS transmission. Model characteristics, epidemiological parameters and intervention parameters used in the mathematical models from seven studies were summarized. A major concern identified in future epidemics is whether public health administrators can collect all the required data for building epidemiological models in a short period of time during the early phase of an outbreak. Also, currently available models do not explicitly model constrained resources. We urge for closed-loop communication between public health administrators and modelling researchers to come up with guidelines to delineate the collection of the required data in the midst of an outbreak and the inclusion of additional logistical details in future similar models.

Journal article

McGowan CJ, Biggerstaff M, Johansson M, Apfeldorf KM, Ben-Nun M, Brooks L, Convertino M, Erraguntla M, Farrow DC, Freeze J, Ghosh S, Hyun S, Kandula S, Lega J, Liu Y, Michaud N, Morita H, Niemi J, Ramakrishnan N, Ray EL, Reich NG, Riley P, Shaman J, Tibshirani R, Vespignani A, Zhang Q, Reed C, Influenza Forecasting Working Groupet al., 2019, Collaborative efforts to forecast seasonal influenza in the United States, 2015-2016., Sci Rep, Vol: 9

Since 2013, the Centers for Disease Control and Prevention (CDC) has hosted an annual influenza season forecasting challenge. The 2015-2016 challenge consisted of weekly probabilistic forecasts of multiple targets, including fourteen models submitted by eleven teams. Forecast skill was evaluated using a modified logarithmic score. We averaged submitted forecasts into a mean ensemble model and compared them against predictions based on historical trends. Forecast skill was highest for seasonal peak intensity and short-term forecasts, while forecast skill for timing of season onset and peak week was generally low. Higher forecast skill was associated with team participation in previous influenza forecasting challenges and utilization of ensemble forecasting techniques. The mean ensemble consistently performed well and outperformed historical trend predictions. CDC and contributing teams will continue to advance influenza forecasting and work to improve the accuracy and reliability of forecasts to facilitate increased incorporation into public health response efforts.

Journal article

Haw DJ, Cummings DAT, Lessler J, Salje H, Read JM, Riley Set al., 2019, Differential mobility and local variation in infection attack rate, PLOS COMPUTATIONAL BIOLOGY, Vol: 15

Journal article

Hay JA, Nouvellet P, Donnelly CA, Riley Set al., 2018, Potential inconsistencies in Zika surveillance data and our understanding of risk during pregnancy, PLoS Neglected Tropical Diseases, Vol: 12, ISSN: 1935-2727

BackgroundA significant increase in microcephaly incidence was reported in Northeast Brazil at the end of 2015, which has since been attributed to an epidemic of Zika virus (ZIKV) infections earlier that year. Further incidence of congenital Zika syndrome (CZS) was expected following waves of ZIKV infection throughout Latin America; however, only modest increases in microcephaly and CZS incidence have since been observed. The quantitative relationship between ZIKV infection, gestational age and congenital outcome remains poorly understood.Methodology/Principle findingsWe characterised the gestational-age-varying risk of microcephaly given ZIKV infection using publicly available incidence data from multiple locations in Brazil and Colombia. We found that the relative timings and shapes of ZIKV infection and microcephaly incidence curves suggested different gestational risk profiles for different locations, varying in both the duration and magnitude of gestational risk. Data from Northeast Brazil suggested a narrow window of risk during the first trimester, whereas data from Colombia suggested persistent risk throughout pregnancy. We then used the model to estimate which combination of behavioural and reporting changes would have been sufficient to explain the absence of a second microcephaly incidence wave in Bahia, Brazil; a population for which we had two years of data. We found that a 18.9-fold increase in ZIKV infection reporting rate was consistent with observed patterns.ConclusionsOur study illustrates how surveillance data may be used in principle to answer key questions in the absence of directed epidemiological studies. However, in this case, we suggest that currently available surveillance data are insufficient to accurately estimate the gestational-age-varying risk of microcephaly from ZIKV infection. The methods used here may be of use in future outbreaks and may help to inform improved surveillance and interpretation in countries yet to experience an out

Journal article

Wong JWH, Ip M, Tang A, Wei VWI, Wong SYS, Riley S, Read JM, Kwok KOet al., 2018, Prevalence and risk factors of community-associated methicillin-resistant Staphylococcus aureus carriage in Asia-Pacific region from 2000 to 2016: a systematic review and meta-analysis, Clinical Epidemiology, Vol: 10, Pages: 1489-1501, ISSN: 1179-1349

Objective: Community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) is an emerging global public health threat. In response to a highlighted strategic priority of the World Health Organization Global Action Plan on Antimicrobial Resistance, to “strengthen the knowledge and evidence base through surveillance and research”, we synthesized published articles to estimate CA-MRSA carriage prevalence in the Asia-Pacific region.Methods: A systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PROSPERO CRD:42017067399). We searched MEDLINE, EMBASE, and PubMed for articles published from 1 January 2000 to 19 May 2017, which reported CA-MRSA carriage (defined as either colonization or infection) in Asia-Pacific region from 2000 to 2016. Studies were stratified according to settings (community or hospital where CA-MRSA was isolated) and study populations (general public or subpopulations with specified characteristics). Ranges of CA-MRSA carriage prevalence were reported for study groups.Results: In total, 152 studies were identified. Large diversity was observed among studies in most study groups. In community-level studies, the CA-MRSA carriage prevalence among the general public ranged from 0% to 23.5%, whereas that ranged from 0.7% to 10.4% in hospital settings. From community-level studies, countries with the highest prevalence were India (16.5%–23.5%), followed by Vietnam (7.9%) and Taiwan (3.5%–3.8%). Children aged ≤6 (range: 0.5%–40.3%) and household members of CA-MRSA carriers (range: 13.0%–26.4%) are subgroups without specific health conditions but with much higher CA-MRSA carriage when compared to the general population.Conclusion: Our CA-MRSA prevalence estimates serve as the baseline for future national and international surveillance. The ranges of prevalence and characteristics associated with CA-MRSA carriage can inform health authoritie

Journal article

Hay JA, Laurie K, White M, Riley Set al., 2018, Characterising antibody kinetics from multiple influenza infection and vaccination events in ferrets, Publisher: Cold Spring Harbor Laboratory

<jats:title>Abstract</jats:title><jats:p>The strength and breadth of an individual’s antibody repertoire are important predictors of their response to influenza infection or vaccination. Although progress has been made in understanding qualitatively how repeated exposures shape the antibody mediated immune response, quantitative understanding remains limited. We developed a set of mathematical models describing short-term antibody kinetics following influenza infection or vaccination and fit them to haemagglutination inhibition (HI) titres from 5 groups of ferrets which were exposed to different combinations of trivalent inactivated influenza vaccine (TIV with or without adjuvant), A/H3N2 priming inoculation and post-vaccination A/H1N1 inoculation. We fit models with various immunological mechanisms that have been empirically observed but are yet to be included in mathematical models of antibody landscapes, including titre ceiling effects, antigenic seniority and exposure-type specific cross reactivity. Based on the parameter estimates of the best supported models, we describe a number of key immunological features. We found quantifiable differences in the degree of homologous and cross-reactive antibody boosting elicited by different exposure types. Infection and adjuvanted vaccination generally resulted in strong, broadly reactive responses whereas unadjuvanted vaccination resulted in a weak, narrow response. We found that the order of exposure mattered: priming with A/H3N2 improved subsequent vaccine response, and the second dose of adjuvanted vaccination resulted in substantially greater antibody boosting than the first. Either antigenic seniority or a titre ceiling effect were included in the two best fitting models, suggesting that a mechanism describing diminishing antibody boosting with repeated exposures improved the predictive power of the model. Although there was considerable uncertainty in our estimates of antibody waning paramet

Working paper

Kucharski AJ, Lessler J, Cummings DAT, Riley Set al., 2018, Timescales of influenza A/H3N2 antibody dynamics, PLoS Biology, Vol: 16, ISSN: 1544-9173

Human immunity influences the evolution and impact of influenza strains. Because individuals are infected with multiple influenza strains during their lifetime, and each virus can generate a cross-reactive antibody response, it is challenging to quantify the processes thatshape observed immune responses or to reliably detect recent infection from serologicalsamples. Using a Bayesian model of antibody dynamics at multiple timescales, we explaincomplex cross-reactive antibody landscapes by inferring participants’ histories of infectionwith serological data from cross-sectional and longitudinal studies of influenza A/H3N2 insouthern China and Vietnam. We find that individual-level influenza antibody profiles canbe explained by a short-lived, broadly cross-reactive response that decays within a yearto leave a smaller long-term response acting against a narrower range of strains. We alsodemonstrate that accounting for dynamic immune responses alongside infection history canprovide a more accurate alternative to traditional definitions of seroconversion for the estimation of infection attack rates. Our work provides a general model for quantifying aspectsof influenza immunity acting at multiple timescales based on contemporary serological dataand suggests a two-armed immune response to influenza infection consistent with competitive dynamics between B cell populations. This approach to analysing multiple timescalesfor antigenic responses could also be applied to other multistrain pathogens such as dengueand related flaviviruses.

Journal article

Wong JWH, Ip M, Tang A, Wei VWI, Wong SYS, Riley S, Read J, Kwok KOet al., 2018, Prevalence and risk factors of community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) carriage in Asia-Pacific region from 2000 to 2016: A systematic review and meta-analysis, Clinical Epidemiology, Vol: 10, Pages: 1489-1501, ISSN: 1179-1349

Objective: Community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) is an emerging global public health threat. In response to a highlighted strategic priority of the World Health Organization Global Action Plan on Antimicrobial Resistance, to “strengthen the knowledge and evidence base through surveillance and research”, we synthesized published articles to estimate CA-MRSA carriage prevalence in the Asia-Pacific region.Methods: A systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PROSPERO CRD:42017067399). We searched MEDLINE, EMBASE, and PubMed for articles published from 1 January 2000 to 19 May 2017, which reported CA-MRSA carriage (defined as either colonization or infection) in Asia-Pacific region from 2000 to 2016. Studies were stratified according to settings (community or hospital where CA-MRSA was isolated) and study populations (general public or subpopulations with specified characteristics). Ranges of CA-MRSA carriage prevalence were reported for study groups.Results: In total, 152 studies were identified. Large diversity was observed among studies in most study groups. In community-level studies, the CA-MRSA carriage prevalence among the general public ranged from 0% to 23.5%, whereas that ranged from 0.7% to 10.4% in hospital settings. From community-level studies, countries with the highest prevalence were India (16.5%–23.5%), followed by Vietnam (7.9%) and Taiwan (3.5%–3.8%). Children aged ≤6 (range: 0.5%–40.3%) and household members of CA-MRSA carriers (range: 13.0%–26.4%) are subgroups without specific health conditions but with much higher CA-MRSA carriage when compared to the general population.Conclusion: Our CA-MRSA prevalence estimates serve as the baseline for future national and international surveillance. The ranges of prevalence and characteristics associated with CA-MRSA carriage can inform health authoritie

Journal article

Cremin Í, Watson O, Heffernan A, Imai N, Ahmed N, Bivegete S, Kimani T, Kyriacou D, Mahadevan P, Mustafa R, Pagoni P, Sophiea M, Whittaker C, Beacroft L, Riley S, Fisher Met al., 2018, An infectious way to teach students about outbreaks, Epidemics, Vol: 23, Pages: 42-48, ISSN: 1755-4365

The study of infectious disease outbreaks is required to train today’s epidemiologists. A typical way to introduce and explain key epidemiological concepts is through the analysis of a historical outbreak. There are, however, few training options that explicitly utilise real-time simulated stochastic outbreaks where the participants themselves comprise the dataset they subsequently analyse. In this paper, we present a teaching exercise in which an infectious disease outbreak is simulated over a five-day period and subsequently analysed. We iteratively developed the teaching exercise to offer additional insight into analysing an outbreak. An R package for visualisation, analysis and simulation of the outbreak data was developed to accompany the practical to reinforce learning outcomes. Computer simulations of the outbreak revealed deviations from observed dynamics, highlighting how simplifying assumptions conventionally made in mathematical models often differ from reality. Here we provide a pedagogical tool for others to use and adapt in their own settings.

Journal article

Wei VWI, Wong JYT, Perera RAPM, Kwok KO, Fang VJ, Barr IG, Peiris JSM, Riley S, Cowling BJet al., 2018, Incidence of influenza A(H3N2) virus infections in Hong Kong in a longitudinal sero-epidemiological study, 2009-2015, PLOS ONE, Vol: 13, ISSN: 1932-6203

Journal article

Kwok KO, Read JM, Tang A, Chen H, Riley S, Kam KMet al., 2018, A systematic review of transmission dynamic studies of methicillin-resistant Staphylococcus aureus in non-hospital residential facilities, BMC Infectious Diseases, Vol: 18, ISSN: 1471-2334

BackgroundNon-hospital residential facilities are important reservoirs for MRSA transmission. However, conclusions and public health implications drawn from the many mathematical models depicting nosocomial MRSA transmission may not be applicable to these settings. Therefore, we reviewed the MRSA transmission dynamics studies in defined non-hospital residential facilities to: (1) provide an overview of basic epidemiology which has been addressed; (2) identify future research direction; and (3) improve future model implementation.MethodsA review was conducted by searching related keywords in PUBMED without time restriction as well as internet searches via Google search engine. We included only articles describing the epidemiological transmission pathways of MRSA/community-associated MRSA within and between defined non-hospital residential settings.ResultsAmong the 10 included articles, nursing homes (NHs) and correctional facilities (CFs) were two settings considered most frequently. Importation of colonized residents was a plausible reason for MRSA outbreaks in NHs, where MRSA was endemic without strict infection control interventions. The importance of NHs over hospitals in increasing nosocomial MRSA prevalence was highlighted. Suggested interventions in NHs included: appropriate staffing level, screening and decolonizing, and hand hygiene. On the other hand, the small population amongst inmates in CFs has no effect on MRSA community transmission. Included models ranged from system-level compartmental models to agent-based models. There was no consensus over the course of disease progression in these models, which were mainly featured with NH residents /CF inmates/ hospital patients as transmission pathways. Some parameters used by these models were outdated or unfit.ConclusionsImportance of NHs has been highlighted from these current studies addressing scattered aspects of MRSA epidemiology. However, the wide variety of non-hospital residential settings suggest th

Journal article

Kwok KO, Cowling B, Wei V, Riley S, Read JMet al., 2018, Temporal variation of human encounters and the number of locations in which they occur: a longitudinal study of Hong Kong residents, Journal of the Royal Society Interface, Vol: 15, ISSN: 1742-5662

Patterns of social contact between individuals are important for the transmission of many pathogens and shaping patterns of immunity at the population scale. To refine our understanding of how human social behaviour may change over time, we conducted a longitudinal study of Hong Kong residents. We recorded the social contact patterns for 1450 individuals, up to four times each between May 2012 and September 2013. We found individuals made contact with an average of 12.5 people within 2.9 geographical locations, and spent an average estimated total duration of 9.1 h in contact with others during a day. Distributions of the number of contacts and locations in which contacts were made were not significantly different between study waves. Encounters were assortative by age, and the age mixing pattern was broadly consistent across study waves. Fitting regression models, we examined the association of contact rates (number of contacts, total duration of contact, number of locations) with covariates and calculated the inter- and intra-participant variation in contact rates. Participant age was significantly associated with the number of contacts made, the total duration of contact and the number of locations in which contact occurred, with children and parental-age adults having the highest rates of contact. The number of contacts and contact duration increased with the number of contact locations. Intra-individual variation in contact rate was consistently greater than inter-individual variation. Despite substantial individual-level variation, remarkable consistency was observed in contact mixing at the population scale. This suggests that aggregate measures of mixing behaviour derived from cross-sectional information may be appropriate for population-scale modelling purposes, and that if more detailed models of social interactions are required for improved public health modelling, further studies are needed to understand the social processes driving intra-individual vari

Journal article

Pinsent A, Pepin KM, Zhu H, Guan Y, White MT, Riley Set al., 2017, The persistence of multiple strains of avian influenza in live bird markets., Proceedings of the Royal Society B: Biological Sciences, Vol: 284, ISSN: 1471-2954

Multiple subtypes of avian influenza (AI) and novel reassortants are frequently isolated from live bird markets (LBMs). However, our understanding of the drivers of persistence of multiple AI subtypes is limited. We propose a stochastic model of AI transmission within an LBM that incorporates market size, turnover rate and the balance of direct versus environmental transmissibility. We investigate the relationship between these factors and the critical community size (CCS) for the persistence of single and multiple AI strains within an LBM. We fit different models of seeding from farms to two-strain surveillance data collected from Shantou, China. For a single strain and plausible estimates for continuous turnover rates and transmissibility, the CCS was approximately 11 800 birds, only a 4.2% increase in this estimate was needed to ensure persistence of the co-infecting strains (two strains in a single host). Precise values of CCS estimates were sensitive to changes in market turnover rate and duration of the latent period. Assuming a gradual daily sell rate of birds the estimated CCS was higher than when an instantaneous selling rate was assumed. We were able to reproduce prevalence dynamics similar to observations from a single market in China with infection seeded every 5-15 days, and a maximum non-seeding duration of 80 days. Our findings suggest that persistence of co-infections is more likely to be owing to sequential infection of single strains rather than ongoing transmission of both strains concurrently. In any given system for a fixed set of ecological and epidemiological conditions, there is an LBM size below which the risk of sustained co-circulation is low and which may suggest a clear policy opportunity to reduce the frequency of influenza co-infection in poultry.

Journal article

Lau MSY, Gibson GJ, Adrakey H, McClelland A, Riley S, Zelner J, Streftaris G, Funk S, Metcalf J, Dalziel BD, Grenfell BTet al., 2017, A mechanistic spatio-temporal framework for modelling individual-to-individual transmission-With an application to the 2014-2015 West Africa Ebola outbreak, PLOS COMPUTATIONAL BIOLOGY, Vol: 13

Journal article

Kwok KO, Riley S, Perera RAPM, Wei VWI, Wu P, Wei L, Chu DKW, Barr IG, Peiris JSM, Cowling BJet al., 2017, Relative incidence and individual-level severity of seasonal influenza A H3N2 compared with 2009 pandemic H1N1, BMC INFECTIOUS DISEASES, Vol: 17, ISSN: 1471-2334

Background:Two subtypes of influenza A currently circulate in humans: seasonal H3N2 (sH3N2, emerged in 1968) and pandemic H1N1 (pH1N1, emerged in 2009). While the epidemiological characteristics of the initial wave of pH1N1 have been studied in detail, less is known about its infection dynamics during subsequent waves or its severity relative to sH3N2. Even prior to 2009, few data was available to estimate the risk of severe outcomes following infection with one circulating influenza strain relative to another.Methods:We analyzed antibodies in quadruples of sera from individuals in Hong Kong collected between July 2009 and December 2011, a period that included three distinct influenza virus epidemics. We estimated infection incidence using these assay data and then estimated rates of severe outcomes per infection using population-wide clinical data.Results:Cumulative incidence of infection was high among children in the first epidemic of pH1N1. There was a change towards the older age group in the age distribution of infections for pH1N1 from the first to the second epidemic, with the age distribution of the second epidemic of pH1N1 more similar to that of sH3N2. We found no serological evidence that individuals were infected in both waves of pH1N1. The risks of excess mortality conditional on infection were higher for sH3N2 than for pH1N1, with age-standardized risk ratios of 2.6 [95% CI: 1.8, 3.7] for all causes and 1.5 [95% CI: 1.0, 2.1] for respiratory causes throughout the study period.Conclusions:Overall increase in clinical incidence of pH1N1 and higher rates of severity in older adults in post pandemic waves were in line with an age-shift in infection towards the older age groups. The absence of repeated infection is good evidence that waning immunity did not cause the second wave. Despite circulating in humans since 1968, sH3N2 is substantially more severe per infection than the pH1N1 strain. Infection-based estimates of individual-level severity have a rol

Journal article

Garske T, Cori A, Ariyarajah A, Blake I, Dorigatti I, Eckmanns T, Fraser C, Hinsley W, Jombart T, Mills H, Nedjati-Gilani G, Newton E, Nouvellet P, Perkins D, Riley S, Schumacher D, Shah A, Van Kerkhove M, Dye C, Ferguson N, Donnelly Cet al., 2017, Heterogeneities in the case fatality ratio in the West African Ebola outbreak 2013 – 2016, Philosophical Transactions of the Royal Society B: Biological Sciences, Vol: 372, ISSN: 1471-2970

The 2013–2016 Ebola outbreak in West Africa is the largest on record with 28 616 confirmed, probable and suspected cases and 11 310 deaths officially recorded by 10 June 2016, the true burden probably considerably higher. The case fatality ratio (CFR: proportion of cases that are fatal) is a key indicator of disease severity useful for gauging the appropriate public health response and for evaluating treatment benefits, if estimated accurately. We analysed individual-level clinical outcome data from Guinea, Liberia and Sierra Leone officially reported to the World Health Organization. The overall mean CFR was 62.9% (95% CI: 61.9% to 64.0%) among confirmed cases with recorded clinical outcomes. Age was the most important modifier of survival probabilities, but country, stage of the epidemic and whether patients were hospitalized also played roles. We developed a statistical analysis to detect outliers in CFR between districts of residence and treatment centres (TCs), adjusting for known factors influencing survival and identified eight districts and three TCs with a CFR significantly different from the average. From the current dataset, we cannot determine whether the observed variation in CFR seen by district or treatment centre reflects real differences in survival, related to the quality of care or other factors or was caused by differences in reporting practices or case ascertainment.

Journal article

Cori A, Donnelly CA, dorigatti, ferguson NM, fraser, garske, jombart, Nedjati-Gilani G, Nouvellet, Riley, Van Kerkhove, Mills, Blake IMet al., 2017, Key data for outbreak evaluation: building on the Ebola experience, Philosophical Transactions of the Royal Society B: Biological Sciences, Vol: 372, ISSN: 1471-2970

Following the detection of an infectious disease outbreak, rapid epidemiological assessmentis critical to guidean effectivepublic health response. To understand the transmission dynamics and potential impact of an outbreak, several types of data are necessary. Here we build on experience gained inthe West AfricanEbolaepidemic and prior emerging infectious disease outbreaksto set out a checklist of data needed to: 1) quantify severity and transmissibility;2) characterise heterogeneities in transmission and their determinants;and 3) assess the effectiveness of different interventions.We differentiate data needs into individual-leveldata (e.g. a detailed list of reported cases), exposure data(e.g.identifying where / howcases may have been infected) and populationlevel data (e.g.size/demographicsof the population(s)affected andwhen/where interventions were implemented). A remarkable amount of individual-level and exposuredata was collected during the West African Ebola epidemic, which allowed the assessment of (1) and (2). However,gaps in population-level data (particularly around which interventions were applied whenand where)posed challenges to the assessment of (3).Herewehighlight recurrent data issues, give practical suggestions for addressingthese issues and discuss priorities for improvements in data collection in future outbreaks.

Journal article

Yuan H-Y, Baguelin M, Kwok KO, Arinaminpathy N, van Leeuwen E, Riley Set al., 2017, The impact of stratified immunity on the transmission dynamics of influenza, Epidemics, Vol: 20, Pages: 84-93, ISSN: 1755-4365

Although empirical studies show that protection against influenza infection in humans is closely related to antibody titres, influenza epidemics are often described under the assumption that individuals are either susceptible or not. Here we develop a model in which antibody titre classes are enumerated explicitly and mapped onto a variable scale of susceptibility in different age groups. Fitting only with pre- and post-wave serological data during 2009 pandemic in Hong Kong, we demonstrate that with stratified immunity, the timing and the magnitude of the epidemic dynamics can be reconstructed more accurately than is possible with binary seropositivity data. We also show that increased infectiousness of children relative to adults and age-specific mixing are required to reproduce age-specific seroprevalence observed in Hong Kong, while pre-existing immunity in the elderly is not. Overall, our results suggest that stratified immunity in an aged-structured heterogeneous population plays a significant role in determining the shape of influenza epidemics.

Journal article

Lau MSY, Dalziel BD, Funk S, McClelland A, Tiffany A, Riley S, Metcalf CJE, Grenfell BTet al., 2017, Spatial and temporal dynamics of superspreading events in the 2014-2015 West Africa Ebola epidemic, Proceedings of the National Academy of Sciences of the United States of America, Vol: 114, Pages: 2337-2342, ISSN: 0027-8424

The unprecedented scale of the Ebola outbreak in WesternAfrica (2014–2015) has prompted an explosion of efforts tounderstand the transmission dynamics of the virus and to analyzethe performance of possible containment strategies. Modelshave focused primarily on the reproductive numbers of thedisease that represent the average number of secondary infectionsproduced by a random infectious individual. However,these population-level estimates may conflate important systematicvariation in the number of cases generated by infectedindividuals, particularly found in spatially localized transmissionand superspreading events. Although superspreading featuresprominently in first-hand narratives of Ebola transmission, itsdynamics have not been systematically characterized, hinderingrefinements of future epidemic predictions and explorations oftargeted interventions. We used Bayesian model inference to integrateindividual-level spatial information with other epidemiologicaldata of community-based (undetected within clinical-caresystems) cases and to explicitly infer distribution of the cases generatedby each infected individual. Our results show that superspreadersplay a key role in sustaining onward transmission ofthe epidemic, and they are responsible for a significant proportion(∼61%) of the infections. Our results also suggest age as akey demographic predictor for superspreading. We also show thatcommunity-based cases may have progressed more rapidly thanthose notified within clinical-care systems, and most transmissionevents occurred in a relatively short distance (with median valueof 2.51 km). Our results stress the importance of characterizingsuperspreading of Ebola, enhance our current understanding ofits spatiotemporal dynamics, and highlight the potential importanceof targeted control measures.

Journal article

Nouvellet P, Cori A, Garske T, Blake IM, Dorigatti I, Hinsley W, Jombart T, Mills HL, Nedjati-Gilani G, Van Kerkhove MD, Fraser C, Donnelly CA, Ferguson NM, Riley Set al., 2017, A simple approach to measure transmissibility and forecast incidence, Epidemics, Vol: 22, Pages: 29-35, ISSN: 1755-4365

Outbreaks of novel pathogens such as SARS, pandemic influenza and Ebola require substantial investments in reactive interventions, with consequent implementation plans sometimes revised on a weekly basis. Therefore, short-term forecasts of incidence are often of high priority. In light of the recent Ebola epidemic in West Africa, a forecasting exercise was convened by a network of infectious disease modellers. The challenge was to forecast unseen “future” simulated data for four different scenarios at five different time points. In a similar method to that used during the recent Ebola epidemic, we estimated current levels of transmissibility, over variable time-windows chosen in an ad hoc way. Current estimated transmissibility was then used to forecast near-future incidence. We performed well within the challenge and often produced accurate forecasts. A retrospective analysis showed that our subjective method for deciding on the window of time with which to estimate transmissibility often resulted in the optimal choice. However, when near-future trends deviated substantially from exponential patterns, the accuracy of our forecasts was reduced. This exercise highlights the urgent need for infectious disease modellers to develop more robust descriptions of processes – other than the widespread depletion of susceptible individuals – that produce non-exponential patterns of incidence.

Journal article

Pepin KM, Kay SL, Golas BD, Shriner SS, Gilbert AT, Miller RS, Graham AL, Riley S, Cross PC, Samuel MD, Hooten MB, Hoeting JA, Lloyd-Smith JO, Webb CT, Buhnerkempe MGet al., 2017, Inferring infection hazard in wildlife populations by linking data across individual and population scales, ECOLOGY LETTERS, Vol: 20, Pages: 275-292, ISSN: 1461-023X

Journal article

Kucharski A, Riley S, 2016, Reducing uncertainty about flavivirus infections, LANCET INFECTIOUS DISEASES, Vol: 17, Pages: 13-15, ISSN: 1473-3099

Journal article

International Ebola Response Team, Agua-Agum J, Ariyarajah A, Aylward B, Bawo L, Bilivogui P, Blake IM, Brennan RJ, Cawthorne A, Cleary E, Clement P, Conteh R, Cori A, Dafae F, Dahl B, Dangou JM, Diallo B, Donnelly CA, Dorigatti I, Dye C, Eckmanns T, Fallah M, Ferguson NM, Fiebig L, Fraser C, Garske T, Gonzalez L, Hamblion E, Hamid N, Hersey S, Hinsley W, Jambei A, Jombart T, Kargbo D, Keita S, Kinzer M, George FK, Godefroy B, Gutierrez G, Kannangarage N, Mills HL, Moller T, Meijers S, Mohamed Y, Morgan O, Nedjati-Gilani G, Newton E, Nouvellet P, Nyenswah T, Perea W, Perkins D, Riley S, Rodier G, Rondy M, Sagrado M, Savulescu C, Schafer IJ, Schumacher D, Seyler T, Shah A, Van Kerkhove MD, Wesseh CS, Yoti Zet al., 2016, Exposure patterns driving Ebola transmissions in West Africa: a retrospective observational study, PLOS Medicine, Vol: 13, ISSN: 1549-1277

BACKGROUND: The ongoing West African Ebola epidemic began in December 2013 in Guinea, probably from a single zoonotic introduction. As a result of ineffective initial control efforts, an Ebola outbreak of unprecedented scale emerged. As of 4 May 2015, it had resulted in more than 19,000 probable and confirmed Ebola cases, mainly in Guinea (3,529), Liberia (5,343), and Sierra Leone (10,746). Here, we present analyses of data collected during the outbreak identifying drivers of transmission and highlighting areas where control could be improved.METHODS AND FINDINGS: Over 19,000 confirmed and probable Ebola cases were reported in West Africa by 4 May 2015. Individuals with confirmed or probable Ebola ("cases") were asked if they had exposure to other potential Ebola cases ("potential source contacts") in a funeral or non-funeral context prior to becoming ill. We performed retrospective analyses of a case line-list, collated from national databases of case investigation forms that have been reported to WHO. These analyses were initially performed to assist WHO's response during the epidemic, and have been updated for publication. We analysed data from 3,529 cases in Guinea, 5,343 in Liberia, and 10,746 in Sierra Leone; exposures were reported by 33% of cases. The proportion of cases reporting a funeral exposure decreased over time. We found a positive correlation (r = 0.35, p < 0.001) between this proportion in a given district for a given month and the within-district transmission intensity, quantified by the estimated reproduction number (R). We also found a negative correlation (r = -0.37, p < 0.001) between R and the district proportion of hospitalised cases admitted within ≤4 days of symptom onset. These two proportions were not correlated, suggesting that reduced funeral attendance and faster hospitalisation independently influenced local transmission intensity. We were able to identify 14% of potential source contacts as cases in the

Journal article

Lipsitch M, Barclay W, Raman R, Russell CJ, Belser JA, Cobey S, Kasson PM, Lloyd-Smith JO, Maurer-Stroh S, Riley S, Beauchemin CAA, Bedford T, Friedrich TC, Handel A, Herfst S, Murcia PR, Roche B, Wilke CO, Russell CAet al., 2016, Viral factors in influenza pandemic risk assessment, eLife, Vol: 5, ISSN: 2050-084X

The threat of an influenza A virus pandemic stems from continual virus spillovers from reservoir species, a tiny fraction of which spark sustained transmission in humans. To date, no pandemic emergence of a new influenza strain has been preceded by detection of a closely related precursor in an animal or human. Nonetheless, influenza surveillance efforts are expanding, prompting a need for tools to assess the pandemic risk posed by a detected virus. The goal would be to use genetic sequence and/or biological assays of viral traits to identify those non-human influenza viruses with the greatest risk of evolving into pandemic threats, and/or to understand drivers of such evolution, to prioritize pandemic prevention or response measures. We describe such efforts, identify progress and ongoing challenges, and discuss three specific traits of influenza viruses (hemagglutinin receptor binding specificity, hemagglutinin pH of activation, and polymerase complex efficiency) that contribute to pandemic risk.

Journal article

Truelove S, Zhu H, Lessler J, Riley S, Read JM, Wang S, Kwok KO, Guan Y, Jiang CQ, Cummings DAet al., 2016, A comparison of hemagglutination inhibition and neutralization assays for characterizing immunity to seasonal influenza A, Influenza Other Respiratory Viruses, Vol: 10, Pages: 518-524, ISSN: 1750-2640

BACKGROUND: Serum antibody to influenza can be used to identify past exposure and measure current immune status. The two most common methods for measuring this are the hemagglutination inhibition assay (HI) and the viral neutralization assay (NT), which have not been systematically compared for a large number of influenza viruses. METHODS: 151 study participants from near Guangzhou, China were enrolled in 2009 and provided serum. HI and NT assays were performed for 12 historic and recently circulating strains of seasonal influenza A. We compared titers using Spearman correlation and fit models to predict NT using HI results. RESULTS: We observed high positive mean correlation between HI and NT assays (Spearman's rank correlation, rho=0.86) across all strains. Correlation was highest within subtypes and within close proximity in time. Overall, an HI=20 corresponded to NT=10, and HI=40 corresponded to NT=20. Linear regression of log(NT) on log(HI) was statistically significant, with age modifying this relationship. Strain-specific area under a curve (AUC) indicated good accuracy (>80%) for predicting NT with HI. CONCLUSIONS: While we found high overall correspondence of titers between NT and HI assays for seasonal influenza A, no exact equivalence between assays could be determined. This was further complicated by correspondence between titers changing with age. These findings support generalized comparison of results between assays and give further support for use of the hemagglutination inhibition assay over the more resource intensive viral neutralization assay for seasonal influenza A, though attention should be given to the effect of age on these assays. This article is protected by copyright. All rights reserved.

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