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

119 results found

Cori A, Donnelly CA, Dorigatti I, Ferguson NM, Fraser C, Garske T, Jombart T, Nedjati-Gilani G, Nouvellet P, Riley S, Van Kerkhove MD, Mills HL, Blake IMet al., 2017, Key data for outbreak evaluation: building on the Ebola experience., Philos Trans R Soc Lond B Biol Sci, Vol: 372

Following the detection of an infectious disease outbreak, rapid epidemiological assessment is critical for guiding an effective public 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 in the West African Ebola epidemic and prior emerging infectious disease outbreaks to set out a checklist of data needed to: (1) quantify severity and transmissibility; (2) characterize heterogeneities in transmission and their determinants; and (3) assess the effectiveness of different interventions. We differentiate data needs into individual-level data (e.g. a detailed list of reported cases), exposure data (e.g. identifying where/how cases may have been infected) and population-level data (e.g. size/demographics of the population(s) affected and when/where interventions were implemented). A remarkable amount of individual-level and exposure data 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 when and where) posed challenges to the assessment of (3). Here we highlight recurrent data issues, give practical suggestions for addressing these issues and discuss priorities for improvements in data collection in future outbreaks.This article is part of the themed issue 'The 2013-2016 West African Ebola epidemic: data, decision-making and disease control'.

JOURNAL ARTICLE

Garske T, Cori A, Ariyarajah A, Blake IM, Dorigatti I, Eckmanns T, Fraser C, Hinsley W, Jombart T, Mills HL, Nedjati-Gilani G, Newton E, Nouvellet P, Perkins D, Riley S, Schumacher D, Shah A, Van Kerkhove MD, Dye C, Ferguson NM, Donnelly CAet al., 2017, Heterogeneities in the case fatality ratio in the West African Ebola outbreak 2013-2016., Philos Trans R Soc Lond B Biol Sci, Vol: 372

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.This article is part of the themed issue 'The 2013-2016 West African Ebola epidemic: data, decision-making and disease control'.

JOURNAL ARTICLE

Kucharski A, Riley S, 2017, Reducing uncertainty about flavivirus infections, LANCET INFECTIOUS DISEASES, Vol: 17, Pages: 13-15, ISSN: 1473-3099

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

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

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

Yuan HY, 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

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.

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Agua-Agum J, Allegranzi B, Ariyarajah A, Aylward RB, Blake IM, Barboza P, Bausch D, Brennan RJ, Clement P, Coffey P, Cori A, Donnelly CA, Dorigatti I, Drury P, Durski K, Dye C, Eckmanns T, Ferguson NM, Fraser C, Garcia E, Garske T, Gasasira A, Gurry C, Gutierrez GJ, Hamblion E, Hinsley W, Holden R, Holmes D, Hugonnet S, Jombart T, Kelley E, Santhana R, Mahmoud N, Mills HL, Mohamed Y, Musa E, Naidoo D, Nedjati-Gilani G, Newton E, Norton I, Nouvellet P, Perkins D, Perkins M, Riley S, Schumacher D, Shah A, Minh T, Varsaneux O, Van Kerkhove MDet al., 2016, After Ebola in West Africa - Unpredictable Risks, Preventable Epidemics, NEW ENGLAND JOURNAL OF MEDICINE, Vol: 375, Pages: 587-596, ISSN: 0028-4793

JOURNAL ARTICLE

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 J-M, 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 Transmission in West Africa: A Retrospective Observational Study, PLOS MEDICINE, Vol: 13, ISSN: 1549-1676

JOURNAL ARTICLE

Agua-Agum J, Ariyarajah A, Blake IM, Cori A, Donnelly CA, Dorigatti I, Dye C, Eck-Manns T, Ferguson NM, Fraser C, Garske T, Hinsley W, Jombart T, Mills HL, Nedjati-Gilani G, Newton E, Nouvellet P, Perkins D, Riley S, Schumacher D, Shah A, Thomas LJ, Van Kerkhove MDet al., 2016, Ebola Virus Disease among Male and Female Persons in West Africa, NEW ENGLAND JOURNAL OF MEDICINE, Vol: 374, Pages: 96-98, ISSN: 0028-4793

JOURNAL ARTICLE

Cauchemez S, Nouvellet P, Cori A, Jombart T, Garske T, Clapham H, Moore S, Mills HL, Salje H, Collins C, Rodriquez-Barraquer I, Riley S, Truelove S, Algarni H, Alhakeem R, AlHarbi K, Turkistani A, Aguas RJ, Cummings DAT, Van Kerkhove MD, Donnelly CA, Lessler J, Fraser C, Al-Barrak A, Ferguson NMet al., 2016, Unraveling the drivers of MERS-CoV transmission, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, Vol: 113, Pages: 9081-9086, ISSN: 0027-8424

JOURNAL ARTICLE

Jiang CQ, Lessler J, Kim L, Kwok KO, Read JM, Wang S, Tan L, Hast M, Zhu H, Guan Y, Riley S, Cummings DAet al., 2016, Cohort Profile: A study of influenza immunity in the urban and rural Guangzhou region of China: the Fluscape Study., Int J Epidemiol

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

JOURNAL ARTICLE

Pinsent A, Fraser C, Ferguson NM, Riley Set al., 2016, A systematic review of reported reassortant viral lineages of influenza A, BMC INFECTIOUS DISEASES, Vol: 16, ISSN: 1471-2334

JOURNAL ARTICLE

Pitzer VE, Aguas R, Riley S, Loeffen WLA, Wood JLN, Grenfell BTet al., 2016, High turnover drives prolonged persistence of influenza in managed pig herds, JOURNAL OF THE ROYAL SOCIETY INTERFACE, Vol: 13, ISSN: 1742-5689

JOURNAL ARTICLE

Riley P, Cost AA, Riley S, 2016, Intra-Weekly Variations of Influenza-Like Illness in Military Populations, MILITARY MEDICINE, Vol: 181, Pages: 364-368, ISSN: 0026-4075

JOURNAL ARTICLE

Riley S, 2016, Making high-res Zika maps, NATURE MICROBIOLOGY, Vol: 1

JOURNAL ARTICLE

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

JOURNAL ARTICLE

Agua-Agum J, Ariyarajah A, Blake IM, Cori A, Donnelly CA, Dorigatti I, Dye C, Eckmanns T, Ferguson NM, Fowler RA, Fraser C, Garske T, Hinsley W, Jombart T, Mills HL, Murthy S, Nedjati-Gilani G, Nouvellet P, Pelletier L, Riley S, Schumacher D, Shah A, Van Kerkhove MDet al., 2015, Ebola Virus Disease among Children in West Africa, NEW ENGLAND JOURNAL OF MEDICINE, Vol: 372, Pages: 1274-1277, ISSN: 0028-4793

JOURNAL ARTICLE

Bedford T, Riley S, Barr IG, Broor S, Chadha M, Cox NJ, Daniels RS, Gunasekaran CP, Hurt AC, Kelso A, Klimov A, Lewis NS, Li X, McCauley JW, Odagiri T, Potdar V, Rambaut A, Shu Y, Skepner E, Smith DJ, Suchard MA, Tashiro M, Wang D, Xu X, Lemey P, Russell CAet al., 2015, Global circulation patterns of seasonal influenza viruses vary with antigenic drift, NATURE, Vol: 523, Pages: 217-U206, ISSN: 0028-0836

JOURNAL ARTICLE

Britton T, House T, Lloyd AL, Mollison D, Riley S, Trapman Pet al., 2015, Five challenges for stochastic epidemic models involving global transmission, EPIDEMICS, Vol: 10, Pages: 54-57, ISSN: 1755-4365

JOURNAL ARTICLE

Chretien J-P, Riley S, George DB, 2015, Mathematical modeling of the West Africa Ebola epidemic, eLife, Vol: 4, ISSN: 2050-084X

As of November 2015, the Ebola virus disease (EVD) epidemic that began in West Africa in late 2013 is waning. The human toll includes more than 28,000 EVD cases and 11,000 deaths in Guinea, Liberia, and Sierra Leone, the most heavily-affected countries. We reviewed 66 mathematical modeling studies of the EVD epidemic published in the peer-reviewed literature to assess the key uncertainties models addressed, data used for modeling, public sharing of data and results, and model performance. Based on the review, we suggest steps to improve the use of modeling in future public health emergencies.

JOURNAL ARTICLE

Eames K, Bansal S, Frost S, Riley Set al., 2015, Six challenges in measuring contact networks for use in modelling, EPIDEMICS, Vol: 10, Pages: 72-77, ISSN: 1755-4365

JOURNAL ARTICLE

Kucharski AJ, Lessler J, Read JM, Zhu H, Jiang CQ, Guan Y, Cummings DAT, Riley Set al., 2015, Estimating the Life Course of Influenza A (H3N2) Antibody Responses from Cross-Sectional Data, PLOS BIOLOGY, Vol: 13, ISSN: 1545-7885

JOURNAL ARTICLE

Kucharski AJ, Mills HL, Donnelly CA, Riley Set al., 2015, Transmission Potential of Influenza A(H7N9) Virus, China, 2013-2014, EMERGING INFECTIOUS DISEASES, Vol: 21, Pages: 852-855, ISSN: 1080-6040

JOURNAL ARTICLE

Lau MSY, Cowling BJ, Cook AR, Riley Set al., 2015, Inferring influenza dynamics and control in households, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, Vol: 112, Pages: 9094-9099, ISSN: 0027-8424

JOURNAL ARTICLE

Lipsitch M, Donnelly CA, Fraser C, Blake IM, Cori A, Dorigatti I, Ferguson NM, Garske T, Mills HL, Riley S, Van Kerkhove MD, Hernan MAet al., 2015, Potential Biases in Estimating Absolute and Relative Case-Fatality Risks during Outbreaks, PLOS NEGLECTED TROPICAL DISEASES, Vol: 9, ISSN: 1935-2735

JOURNAL ARTICLE

Lloyd-Smith JO, Funk S, McLean AR, Riley S, Wood JLNet al., 2015, Nine challenges in modelling the emergence of novel pathogens, EPIDEMICS, Vol: 10, Pages: 35-39, ISSN: 1755-4365

JOURNAL ARTICLE

This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.

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