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

178 results found

Mills HL, Riley S, 2014, The Spatial Resolution of Epidemic Peaks, PLOS COMPUTATIONAL BIOLOGY, Vol: 10

Journal article

Kwok KO, Jiang C, Tan L, Justin L, Read JM, Zhu H, Guan Y, Cummings DA, Riley Set al., 2014, [An international collaborative study on influenza viruses antibody titers and contact patterns of individuals in rural and urban household of Guangzhou]., Zhonghua Liu Xing Bing Xue Za Zhi, Vol: 35, Pages: 433-436, ISSN: 0254-6450

OBJECTIVE: To describe the influenza viruses antibody levels and contact patterns of individuals in rural and urban regions of Guangzhou and to understand how contact patterns and other factors would correlate with the levels on the titers of antibody. METHODS: "Google Map" was used to randomly select the study points from the administrative areas in Guangzhou region. Each participant was required to provide 5 ml blood serum sample to be tested against different strains of H1N1 and H3N2 influenza viruses. RESULTS: 1) Using "Google map", 50 study points were selected but only 40 study points would meet the inclusion criteria. The cohort of this study consisted 856 households with 2 801 individuals. 1 821 participants (65% of the total number individuals in the cohort) completed the questionnaires. Among the 1 821 participants, 77.3% (1 407/1 821) and 22.7% (414/1 821) of them were from rural and urban areas respectively. There were more male participants in the rural but more female participants in the urban regions. Majority of the participants were from age group 18-59 followed by group 60 with aged 2-17 the least, in both rural and urban areas. 2) 78.1% (1 423/1 821) of the participants provided their serum samples. There appeared a strong correlation between age of the participants and the strength of their antibodies against that strain when a strain first circulated. In particular, seroprevalence was the highest at the age group 2-17. 3) 'Contact' was defined as persons having physical touch or/and conversation within one meter with the participants. Participants reported all having had large number of contacts. The proportion of participants having contacts with ten persons or above was the highest, ranging from 49.8% to 72.6%, particularly in age group 6-17. Compared to weekdays, participants had fewer contact persons on weekends. CONCLUSION: There was a strong correlation between the age of participants at the time when the strains first

Journal article

Kucharski A, Mills H, Pinsent A, Fraser C, Van Kerkhove M, Donnelly CA, Riley Set al., 2014, Distinguishing Between Reservoir Exposure and Human-to-Human Transmission for Emerging Pathogens Using Case Onset Data., PLoS Curr, Vol: 6

Pathogens such as MERS-CoV, influenza A/H5N1 and influenza A/H7N9 are currently generating sporadic clusters of spillover human cases from animal reservoirs. The lack of a clear human epidemic suggests that the basic reproductive number R0 is below or very close to one for all three infections. However, robust cluster-based estimates for low R0 values are still desirable so as to help prioritise scarce resources between different emerging infections and to detect significant changes between clusters and over time. We developed an inferential transmission model capable of distinguishing the signal of human-to-human transmission from the background noise of direct spillover transmission (e.g. from markets or farms). By simulation, we showed that our approach could obtain unbiased estimates of R0, even when the temporal trend in spillover exposure was not fully known, so long as the serial interval of the infection and the timing of a sudden drop in spillover exposure were known (e.g. day of market closure). Applying our method to data from the three largest outbreaks of influenza A/H7N9 outbreak in China in 2013, we found evidence that human-to-human transmission accounted for 13% (95% credible interval 1%-32%) of cases overall. We estimated R0 for the three clusters to be: 0.19 in Shanghai (0.01-0.49), 0.29 in Jiangsu (0.03-0.73); and 0.03 in Zhejiang (0.00-0.22). If a reliable temporal trend for the spillover hazard could be estimated, for example by implementing widespread routine sampling in sentinel markets, it should be possible to estimate sub-critical values of R0 even more accurately. Should a similar strain emerge with R0>1, these methods could give a real-time indication that sustained transmission is occurring with well-characterised uncertainty.

Journal article

Pepin KM, Spackman E, Brown JD, Pabilonia KL, Garber LP, Weaver JT, Kennedy DA, Patyk KA, Huyvaert KP, Miller RS, Franklin AB, Pedersen K, Bogich TL, Rohani P, Shriner SA, Webb CT, Riley Set al., 2014, Using quantitative disease dynamics as a tool for guiding response to avian influenza in poultry in the United States of America, PREVENTIVE VETERINARY MEDICINE, Vol: 113, Pages: 376-397, ISSN: 0167-5877

Journal article

Cauchemez S, Fraser C, Van Kerkhove MD, Donnelly CA, Riley S, Rambaut A, Enouf V, van der Werf S, Ferguson NMet al., 2014, Middle East respiratory syndrome coronavirus: quantification of the extent of the epidemic, surveillance biases, and transmissibility, LANCET INFECTIOUS DISEASES, Vol: 14, Pages: 50-56, ISSN: 1473-3099

Journal article

, 2014, Ebola Virus Disease in West Africa — The First 9 Months of the Epidemic and Forward Projections, New England Journal of Medicine, Vol: 371, Pages: 1481-1495

Journal article

Pepin KM, Lloyd-Smith JO, Webb CT, Holcomb K, Zhu H, Guan Y, Riley Set al., 2013, Minimizing the threat of pandemic emergence from avian influenza in poultry systems, BMC INFECTIOUS DISEASES, Vol: 13, ISSN: 1471-2334

Journal article

Riley S, 2013, Complex Disease Dynamics and the Design of Influenza Vaccination Programs, PLOS MEDICINE, Vol: 10, ISSN: 1549-1277

Journal article

Van Kerkhove MD, Hirve S, Koukounari A, Mounts AWet al., 2013, Estimating age-specific cumulative incidence for the 2009 influenza pandemic: a meta-analysis of A(H1N1)pdm09 serological studies from 19 countries, Influenza and Other Respiratory Viruses, Vol: 7, Pages: 872-886, ISSN: 1750-2640

BACKGROUND: The global impact of the 2009 influenza A(H1N1) pandemic (H1N1pdm) is not well understood. OBJECTIVES: We estimate overall and age-specific prevalence of cross-reactive antibodies to H1N1pdm virus and rates of H1N1pdm infection during the first year of the pandemic using data from published and unpublished H1N1pdm seroepidemiological studies. METHODS: Primary aggregate H1N1pdm serologic data from each study were stratified in standardized age groups and evaluated based on when sera were collected in relation to national or subnational peak H1N1pdm activity. Seropositivity was assessed using well-described and standardized hemagglutination inhibition (HI titers >/=32 or >/=40) and microneutralization (MN >/= 40) laboratory assays. The prevalence of cross-reactive antibodies to the H1N1pdm virus was estimated for studies using sera collected prior to the start of the pandemic (between 2004 and April 2009); H1N1pdm cumulative incidence was estimated for studies in which collected both pre- and post-pandemic sera; and H1N1pdm seropositivity was calculated from studies with post-pandemic sera only (collected between December 2009-June 2010). RESULTS: Data from 27 published/unpublished studies from 19 countries/administrative regions - Australia, Canada, China, Finland, France, Germany, Hong Kong SAR, India, Iran, Italy, Japan, Netherlands, New Zealand, Norway, Reunion Island, Singapore, United Kingdom, United States, and Vietnam - were eligible for inclusion. The overall age-standardized pre-pandemic prevalence of cross-reactive antibodies was 5% (95%CI 3-7%) and varied significantly by age with the highest rates among persons >/=65 years old (14% 95%CI 8-24%). Overall age-standardized H1N1pdm cumulative incidence was 24% (95%CI 20-27%) and varied significantly by age with the highest in children 5-19 (47% 95%CI 39-55%) and 0-4 years old (36% 95%CI 30-43%). CONCLUSIONS: Our results offer unique insight into the global impact of the H1N1 pandemic a

Journal article

Strelioff CC, Vijaykrishna D, Riley S, Guan Y, Peiris JSM, Lloyd-Smith JOet al., 2013, Inferring patterns of influenza transmission in swine from multiple streams of surveillance data, PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, Vol: 280, ISSN: 0962-8452

Journal article

Cauchemez S, Van Kerkhove MD, Riley S, Donnelly CA, Fraser C, Ferguson NMet al., 2013, Transmission scenarios for Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and how to tell them apart, EUROSURVEILLANCE, Vol: 18, Pages: 7-13, ISSN: 1560-7917

Journal article

Kwok KO, Leung GM, Mak P, Riley Set al., 2013, Antiviral stockpiles for influenza pandemics from the household perspective: Treatment alone versus treatment with prophylaxis, EPIDEMICS, Vol: 5, Pages: 92-97, ISSN: 1755-4365

Journal article

Cowling BJ, Ho LM, Riley S, Leung GMet al., 2013, Statistical algorithms for early detection of the annual influenza peak season in Hong Kong using sentinel surveillance data., Hong Kong Med J, Vol: 19 Suppl 4, Pages: 4-5, ISSN: 1024-2708

In Hong Kong, influenza sentinel surveillance systems have been recently established. Methods that compare current data to data from recent weeks may be appropriate to indicate the start of peak influenza activity. These methods can produce reliable and timely alerts at the start of the annual influenza peak season.

Journal article

Riley S, Cowling BJ, Chan KH, Peiris JSM, Leung GMet al., 2013, Viral evolution from one generation of human influenza infection to the next., Hong Kong Med J, Vol: 19 Suppl 4, Pages: 6-10, ISSN: 1024-2708

1. In a sub-tropical epidemic, most of the apparent household secondary cases are actually secondary infections. 2. The consensus sequence for the entire influenza virus genome is not usually identical within the same household sample. Rather, there are commonly one or two nucleotide changes. 3. These results hint at an obvious generational threshold for adaptation at the level of the consensus sequence.

Journal article

Cowling BJ, Chan KH, Peiris JSM, Riley S, Leung GMet al., 2013, Viral shedding, clinical history and transmission of influenza., Hong Kong Med J, Vol: 19 Suppl 4, Pages: 19-23, ISSN: 1024-2708

1. During influenza infections, most viral shedding occurs within a few days of illness onset. 2. Children may be more infectious than adults because they shed more virus. 3. The degree of viral shedding (infectiousness) correlates with symptoms and tympanic temperature.

Journal article

Cowling B, Desenclos J-C, Riley S, Simonsen L, Viboud Cet al., 2013, PLOS Currents: Outbreaks --- For findings that the world just can't wait to see., PLoS Curr, Vol: 5

Journal article

Riley P, Ben-Nun M, Armenta R, Linker JA, Eick AA, Sanchez JL, George D, Bacon DP, Riley Set al., 2013, Multiple Estimates of Transmissibility for the 2009 Influenza Pandemic Based on Influenza-like-Illness Data from Small US Military Populations, PLOS COMPUTATIONAL BIOLOGY, Vol: 9

Journal article

Pepin KM, Wang J, Webb CT, Hoeting JA, Poss M, Hudson PJ, Hong W, Zhu H, Guan Y, Riley Set al., 2013, Anticipating the Prevalence of Avian Influenza Subtypes H9 and H5 in Live-Bird Markets, PLOS ONE, Vol: 8, ISSN: 1932-6203

Journal article

Pepin KM, Riley S, Grenfell BT, 2013, Effects of influenza antivirals on individual and population immunity over many epidemic waves, EPIDEMIOLOGY AND INFECTION, Vol: 141, Pages: 366-376, ISSN: 0950-2688

Journal article

Pepin KM, Wang J, Webb CT, Smith GJD, Poss M, Hudson PJ, Hong W, Zhu H, Riley S, Guan Yet al., 2013, Multiannual patterns of influenza A transmission in Chinese live bird market systems, INFLUENZA AND OTHER RESPIRATORY VIRUSES, Vol: 7, Pages: 97-107, ISSN: 1750-2640

Journal article

Van Kerkhove MD, Broberg E, Engelhardt OG, Wood J, Nicoll A, The CONSISE steering committeeet al., 2012, The consortium for the standardization of influenza seroepidemiology (CONSISE): a global partnership to standardize influenza seroepidemiology and develop influenza investigation protocols to inform public health policy., Influenza Other Respi Viruses

CONSISE - The consortium for the Standardization of Influenza Seroepidemiology - is a global partnership to develop influenza investigation protocols and standardize seroepidemiology to inform health policy. This international partnership was formed in 2011 and was created out of a need, identified during the 2009 H1N1 pandemic, for timely seroepidemiological data to better estimate pandemic virus infection severity and attack rates to inform policy decisions. CONSISE has developed into a consortium of two interactive working groups: epidemiology and laboratory, with a steering committee composed of individuals from several organizations. CONSISE has had two international meetings with more planned for 2013. We seek additional members from public health agencies, academic institutions and other interested parties.

Journal article

Read JM, Edmunds WJ, Riley S, Lessler J, Cummings DATet al., 2012, Close encounters of the infectious kind: methods to measure social mixing behaviour, EPIDEMIOLOGY AND INFECTION, Vol: 140, Pages: 2117-2130, ISSN: 0950-2688

Journal article

Laurie KL, Huston P, Riley S, Katz JM, Willison DJ, Mounts AW, Hoschler K, Miller E, Vandemaele K, Van Kerkhove MD, Nicoll Aet al., 2012, Influenza serological studies to inform public health action: best practices to optimise timing, quality and reporting, Influenza and Other Respiratory Viruses

Journal article

Lessler J, Riley S, Read JM, Wang S, Zhu H, Smith GJD, Guan Y, Jiang CQ, Cummings DATet al., 2012, Evidence for Antigenic Seniority in Influenza A (H3N2) Antibody Responses in Southern China, PLOS PATHOGENS, Vol: 8, ISSN: 1553-7374

Journal article

Van Kerkhove MD, Riley S, Lipsitch M, Guan Y, Monto AS, Webster RG, Zambon M, Nicoll A, Peiris JSM, Ferguson NMet al., 2012, Comment on "Seroevidence for H5N1 Influenza Infections in Humans: Meta-Analysis", SCIENCE, Vol: 336, ISSN: 0036-8075

Journal article

Riley R, Leung GM, Cowling BJ, 2012, Public health interventions to control the spread of a directly transmitted human pathogen within and between Hong Kong and Guangzhou., Hong Kong Med J, Vol: 18 Suppl 2, Pages: 37-38, ISSN: 1024-2708

The ability to detect and differentiate between fast and slow spatial spread of infectious disease depends on the density of the surveillance network. 2. The results of this study suggest that more concentrated surveillance networks are required in Guangzhou compared with other regions, such as Thailand and Europe, as long-distance travel is less frequent.

Journal article

Riley S, Leung GM, Ho LM, Cowling BJet al., 2012, Transmission of Japanese encephalitis virus in Hong Kong., Hong Kong Med J, Vol: 18 Suppl 2, Pages: 45-46, ISSN: 1024-2708

1. Pigs are likely to be the main amplifying host for Japanese encephalitis virus. 2. The success of a swine vaccination programme depends on the timing of the loss of maternal antibody protection and seasonal dynamics of the vector population. 3. Vaccination may be ineffective in the face of strong natural infection because of the variability in timing of the loss of maternal antibody protection.4. Evidence in support of swine vaccination as a human health intervention was not found.

Journal article

Bahl J, Nelson MI, Chan KH, Chen R, Vijaykrishna D, Halpin RA, Stockwell TB, Lin X, Wentworth DE, Ghedin E, Guan Y, Malik Peiris JS, Riley S, Rambaut A, Holmes EC, Smith GJDet al., 2011, Temporally structured metapopulation dynamics and persistence of influenza A H3N2 virus in humans., Proc Natl Acad Sci USA

Journal article

Perera RAPM, Riley S, Ma SK, Zhu H-C, Guan Y, Peiris JSMet al., 2011, Seroconversion to Pandemic (H1N1) 2009 Virus and Cross-Reactive Immunity to Other Swine Influenza Viruses., Emerging Infect Dis, Vol: 17, Pages: 1897-1899

Journal article

Lipsitch M, Finelli L, Heffernan RT, Leung GM, Redd SCet al., 2011, IMPROVING THE EVIDENCE BASE FOR DECISION MAKING DURING A PANDEMIC: THE EXAMPLE OF 2009 INFLUENZA A/H1N1, BIOSECURITY AND BIOTERRORISM-BIODEFENSE STRATEGY PRACTICE AND SCIENCE, Vol: 9, Pages: 89-115, ISSN: 1538-7135

Journal article

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