Publications
114 results found
Nouvellet P, Cori A, Garske T, et 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.
Flasche S, Jit M, Rodríguez-Barraquer I, et al., 2016, The long-term safety, public health impact, and cost-effectiveness of routine vaccination with a recombinant, live-attenuated dengue vaccine (Dengvaxia): a model comparison study, Plos Medicine, Vol: 13, ISSN: 1549-1676
BACKGROUND: Large Phase III trials across Asia and Latin America have recently demonstrated the efficacy of a recombinant, live-attenuated dengue vaccine (Dengvaxia) over the first 25 mo following vaccination. Subsequent data collected in the longer-term follow-up phase, however, have raised concerns about a potential increase in hospitalization risk of subsequent dengue infections, in particular among young, dengue-naïve vaccinees. We here report predictions from eight independent modelling groups on the long-term safety, public health impact, and cost-effectiveness of routine vaccination with Dengvaxia in a range of transmission settings, as characterised by seroprevalence levels among 9-y-olds (SP9). These predictions were conducted for the World Health Organization to inform their recommendations on optimal use of this vaccine. METHODS AND FINDINGS: The models adopted, with small variations, a parsimonious vaccine mode of action that was able to reproduce quantitative features of the observed trial data. The adopted mode of action assumed that vaccination, similarly to natural infection, induces transient, heterologous protection and, further, establishes a long-lasting immunogenic memory, which determines disease severity of subsequent infections. The default vaccination policy considered was routine vaccination of 9-y-old children in a three-dose schedule at 80% coverage. The outcomes examined were the impact of vaccination on infections, symptomatic dengue, hospitalised dengue, deaths, and cost-effectiveness over a 30-y postvaccination period. Case definitions were chosen in accordance with the Phase III trials. All models predicted that in settings with moderate to high dengue endemicity (SP9 ≥ 50%), the default vaccination policy would reduce the burden of dengue disease for the population by 6%-25% (all simulations: -3%-34%) and in high-transmission settings (SP9 ≥ 70%) by 13%-25% (all simulations: 10%- 34%). These endemicity levels are represen
International Ebola Response Team, Agua-Agum J, Ariyarajah A, et 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
Nickbakhsh S, Hall MD, Dorigatti I, et al., 2016, Modelling the impact of co-circulating low pathogenic avian influenza viruses on epidemics of highly pathogenic avian influenza in poultry, Epidemics, Vol: 17, Pages: 27-34, ISSN: 1878-0067
It is well known that highly pathogenic avian influenza (HPAI) viruses emerge through mutation of precursor low pathogenic avian influenza (LPAI) viruses in domestic poultry populations. The potential for immunological cross-protection between these pathogenic variants is recognised but the epidemiological impact during co-circulation is not well understood. Here we use mathematical models to investigate whether altered flock infection parameters consequent to primary LPAI infections can impact on the spread of HPAI at the population level. First we used mechanistic models reflecting the co-circulatory dynamics of LPAI and HPAI within a single commercial poultry flock. We found that primary infections with LPAI led to HPAI prevalence being maximised under a scenario of high but partial cross-protection. We then tested the population impact in spatially-explicit simulations motivated by a major avian influenza A(H7N1) epidemic that afflicted the Italian poultry industry in 1999-2001. We found that partial cross-protection can lead to a prolongation of HPAI epidemic duration. Our findings have implications for the control of HPAI in poultry particularly for settings in which LPAI and HPAI frequently co-circulate.
Clamer V, Dorigatti I, Fumanelli L, et al., 2016, Estimating transmission probability in schools for the 2009 H1N1 influenza pandemic in Italy, Theoretical Biology and Medical Modelling, Vol: 13, ISSN: 1742-4682
BACKGROUND: Epidemic models are being extensively used to understand the main pathways of spread of infectious diseases, and thus to assess control methods. Schools are well known to represent hot spots for epidemic spread; hence, understanding typical patterns of infection transmission within schools is crucial for designing adequate control strategies. The attention that was given to the 2009 A/H1N1pdm09 flu pandemic has made it possible to collect detailed data on the occurrence of influenza-like illness (ILI) symptoms in two primary schools of Trento, Italy. RESULTS: The data collected in the two schools were used to calibrate a discrete-time SIR model, which was designed to estimate the probabilities of influenza transmission within the classes, grades and schools using Markov Chain Monte Carlo (MCMC) methods. We found that the virus was mainly transmitted within class, with lower levels of transmission between students in the same grade and even lower, though not significantly so, among different grades within the schools. We estimated median values of R 0 from the epidemic curves in the two schools of 1.16 and 1.40; on the other hand, we estimated the average number of students infected by the first school case to be 0.85 and 1.09 in the two schools. CONCLUSIONS: The discrepancy between the values of R 0 estimated from the epidemic curve or from the within-school transmission probabilities suggests that household and community transmission played an important role in sustaining the school epidemics. The high probability of infection between students in the same class confirms that targeting within-class transmission is key to controlling the spread of influenza in school settings and, as a consequence, in the general population.
Ferguson NM, Rodriguez-Barraquer I, Dorigatti I, et al., 2016, Benefits and risks of the Sanofi-Pasteur dengue vaccine: Modeling optimal deployment, Science, Vol: 353, Pages: 1033-1036, ISSN: 0036-8075
The first approved dengue vaccine has now been licensed in six countries. We propose that this live attenuated vaccine acts like a silent natural infection in priming or boosting host immunity. A transmission dynamic model incorporating this hypothesis fits recent clinical trial data well and predicts that vaccine effectiveness depends strongly on the age group vaccinated and local transmission intensity. Vaccination in low-transmission settings may increase the incidence of more severe “secondary-like” infection and, thus, the numbers hospitalized for dengue. In moderate transmission settings, we predict positive impacts overall but increased risks of hospitalization with dengue disease for individuals who are vaccinated when seronegative. However, in high-transmission settings, vaccination benefits both the whole population and seronegative recipients. Our analysis can help inform policy-makers evaluating this and other candidate dengue vaccines.
Agua-Agum J, Allegranzi B, Ariyarajah A, et al., 2016, After Ebola in West Africa - Unpredictable Risks, Preventable Epidemics, New England Journal of Medicine, Vol: 375, Pages: 587-596, ISSN: 1533-4406
Between December 2013 and April 2016, the largest epidemic of Ebola virus disease (EVD) to date generated more than 28,000 cases and more than 11,000 deaths in the large, mobile populations of Guinea, Liberia, and Sierra Leone. Tracking the rapid rise and slower decline of the West African epidemic has reinforced some common understandings about the epidemiology and control of EVD but has also generated new insights. Despite having more information about the geographic distribution of the disease, the risk of human infection from animals and from survivors of EVD remains unpredictable over a wide area of equatorial Africa. Until human exposure to infection can be anticipated or avoided, future outbreaks will have to be managed with the classic approach to EVD control — extensive surveillance, rapid detection and diagnosis, comprehensive tracing of contacts, prompt patient isolation, supportive clinical care, rigorous efforts to prevent and control infection, safe and dignified burial, and engagement of the community. Empirical and modeling studies conducted during the West African epidemic have shown that large epidemics of EVD are preventable — a rapid response can interrupt transmission and restrict the size of outbreaks, even in densely populated cities. The critical question now is how to ensure that populations and their health services are ready for the next outbreak, wherever it may occur. Health security across Africa and beyond depends on committing resources to both strengthen national health systems and sustain investment in the next generation of vaccines, drugs, and diagnostics.
Ferguson NM, Cucunubá ZM, Dorigatti I, et al., 2016, Countering the Zika epidemic in Latin America, Science, Vol: 353, Pages: 353-354, ISSN: 1095-9203
Imai N, Dorigatti I, Cauchemez S, et al., 2016, Estimating Dengue Transmission Intensity from Case-Notification Data from Multiple Countries, PLOS Neglected Tropical Diseases, Vol: 10, ISSN: 1935-2735
BackgroundDespite being the most widely distributed mosquito-borne viral infection, estimates of dengue transmission intensity and associated burden remain ambiguous. With advances in the development of novel control measures, obtaining robust estimates of average dengue transmission intensity is key for assessing the burden of disease and the likely impact of interventions.Methodology/Principle FindingsWe estimated the force of infection (λ) and corresponding basic reproduction numbers (R0) by fitting catalytic models to age-stratified incidence data identified from the literature. We compared estimates derived from incidence and seroprevalence data and assessed the level of under-reporting of dengue disease. In addition, we estimated the relative contribution of primary to quaternary infections to the observed burden of dengue disease incidence. The majority of R0 estimates ranged from one to five and the force of infection estimates from incidence data were consistent with those previously estimated from seroprevalence data. The baseline reporting rate (or the probability of detecting a secondary infection) was generally low (<25%) and varied within and between countries.Conclusions/SignificanceAs expected, estimates varied widely across and within countries, highlighting the spatio-temporally heterogeneous nature of dengue transmission. Although seroprevalence data provide the maximum information, the incidence models presented in this paper provide a method for estimating dengue transmission intensity from age-stratified incidence data, which will be an important consideration in areas where seroprevalence data are not available.
Clapham HE, Quyen TH, Kien DT, et al., 2016, Modelling Virus and Antibody Dynamics during Dengue Virus Infection Suggests a Role for Antibody in Virus Clearance., PLOS Computational Biology, Vol: 12, ISSN: 1553-734X
Dengue is an infection of increasing global importance, yet uncertainty remains regarding critical aspects of its virology, immunology and epidemiology. One unanswered question is how infection is controlled and cleared during a dengue infection. Antibody is thought to play a role, but little past work has examined the kinetics of both virus and antibody during natural infections. We present data on multiple virus and antibody titres measurements recorded sequentially during infection from 53 Vietnamese dengue patients. We fit mechanistic mathematical models of the dynamics of viral replication and the host immune response to these data. These models fit the data well. The model with antibody removing virus fits the data best, but with a role suggested for ADCC or other infected cell clearance mechanisms. Our analysis therefore shows that the observed viral and antibody kinetics are consistent with antibody playing a key role in controlling viral replication. This work gives quantitative insight into the relationship between antibody levels and the efficiency of viral clearance. It will inform the future development of mechanistic models of how vaccines and antivirals might modify the course of natural dengue infection.
Agua-Agum J, Ariyarajah A, Blake IM, et al., 2016, Ebola virus disease among male and female persons in West Africa, New England Journal of Medicine, Vol: 374, Pages: 96-98, ISSN: 1533-4406
Nouvellet P, Garske T, Mills HL, et al., 2015, The role of rapid diagnostics in managing Ebola epidemics, Nature, Vol: 528, Pages: S109-S116, ISSN: 0028-0836
Ebola emerged in West Africa around December 2013 and swept through Guinea, Sierra Leone and Liberia, giving rise to 27,748 confirmed, probable and suspected cases reported by 29 July 2015. Case diagnoses during the epidemic have relied on polymerase chain reaction-based tests. Owing to limited laboratory capacity and local transport infrastructure, the delays from sample collection to test results being available have often been 2 days or more. Point-of-care rapid diagnostic tests offer the potential to substantially reduce these delays. We review Ebola rapid diagnostic tests approved by the World Health Organization and those currently in development. Such rapid diagnostic tests could allow early triaging of patients, thereby reducing the potential for nosocomial transmission. In addition, despite the lower test accuracy, rapid diagnostic test-based diagnosis may be beneficial in some contexts because of the reduced time spent by uninfected individuals in health-care settings where they may be at increased risk of infection; this also frees up hospital beds. We use mathematical modelling to explore the potential benefits of diagnostic testing strategies involving rapid diagnostic tests alone and in combination with polymerase chain reaction testing. Our analysis indicates that the use of rapid diagnostic tests with sensitivity and specificity comparable with those currently under development always enhances control, whether evaluated at a health-care-unit or population level. If such tests had been available throughout the recent epidemic, we estimate, for Sierra Leone, that their use in combination with confirmatory polymerase chain-reaction testing might have reduced the scale of the epidemic by over a third.
Imai N, Dorigatti I, Cauchemez S, et al., 2015, ESTIMATING DENGUE TRANSMISSION INTENSITY FROM INCIDENCE DATA IN MULTIPLE COUNTRIES, Publisher: AMER SOC TROP MED & HYGIENE, Pages: 234-234, ISSN: 0002-9637
Ferguson NM, Imai N, Nedjati-Gilani G, et al., 2015, ESTABLISHING THE WMEL STRAIN OF WOLBACHIA IN <i>AEDES AEGYPTI</i> POPULATIONS PREDICTED TO REDUCE THE DISEASE BURDEN FROM DENGUE BY AT LEAST TWO-THIRDS, Publisher: AMER SOC TROP MED & HYGIENE, Pages: 179-179, ISSN: 0002-9637
Lipsitch M, Donnelly CA, Fraser C, et al., 2015, Potential biases in estimating absolute and relative case-fatality risks during outbreaks, PLOS Neglected Tropical Diseases, Vol: 9, ISSN: 1935-2735
Dorigatti I, Aguas R, Donnelly CA, et al., 2015, Modelling the immunological response to a tetravalent dengue vaccine from multiple phase-2 trials in Latin America and South East Asia., Vaccine, Vol: 33, Pages: 3746-3751, ISSN: 1873-2518
BACKGROUND: The most advanced dengue vaccine candidate is a live-attenuated recombinant vaccine containing the four dengue viruses on the yellow fever vaccine backbone (CYD-TDV) developed by Sanofi Pasteur. Several analyses have been published on the safety and immunogenicity of the CYD-TDV vaccine from single trials but none modelled the heterogeneity observed in the antibody responses elicited by the vaccine. METHODS: We analyse the immunogenicity data collected in five phase-2 trials of the CYD-TDV vaccine. We provide a descriptive analysis of the aggregated datasets and fit the observed post-vaccination PRNT50 titres against the four dengue (DENV) serotypes using multivariate regression models. RESULTS: We find that the responses to CYD-TDV are principally predicted by the baseline immunological status against DENV, but the trial is also a significant predictor. We find that the CYD-TDV vaccine generates similar titres against all serotypes following the third dose, though DENV4 is immunodominant after the first dose. CONCLUSIONS: This study contributes to a better understanding of the immunological responses elicited by CYD-TDV. The recent availability of phase-3 data is a unique opportunity to further investigate the immunogenicity and efficacy of the CYD-TDV vaccine, especially in subjects with different levels of pre-existing immunity against DENV. Modelling multiple immunological outcomes with a single multivariate model offers advantages over traditional approaches, capturing correlations between response variables, and the statistical method adopted in this study can be applied to a variety of infections with interacting strains.
Imai N, Dorigatti I, Cauchemez S, et al., 2015, Estimating Dengue Transmission Intensity from Sero-Prevalence Surveys in Multiple Countries, PLOS Neglected Tropical Diseases, Vol: 9, ISSN: 1935-2735
BackgroundEstimates of dengue transmission intensity remain ambiguous. Since the majority of infectionsare asymptomatic, surveillance systems substantially underestimate true rates of infection.With advances in the development of novel control measures, obtaining robustestimates of average dengue transmission intensity is key for assessing both the burden ofdisease from dengue and the likely impact of interventions.Methodology/Principal FindingsThe force of infection (λ) and corresponding basic reproduction numbers (R0) for denguewere estimated from non-serotype (IgG) and serotype-specific (PRNT) age-stratified seroprevalencesurveys identified from the literature. The majority of R0 estimates ranged from1–4. Assuming that two heterologous infections result in complete immunity produced up totwo-fold higher estimates of R0 than when tertiary and quaternary infections were included.λ estimated from IgG data were comparable to the sum of serotype-specific forces of infectionderived from PRNT data, particularly when inter-serotype interactions were allowed for.Conclusions/SignificanceOur analysis highlights the highly heterogeneous nature of dengue transmission. How underlyingassumptions about serotype interactions and immunity affect the relationship betweenthe force of infection and R0 will have implications for control planning. While PRNTdata provides the maximum information, our study shows that even the much cheaperELISA-based assays would provide comparable baseline estimates of overall transmissionintensity which will be an important consideration in resource-constrained settings.
Agua-Agum J, Ariyarajah A, Blake IM, et al., 2015, Ebola virus disease among children in West Africa, New England Journal of Medicine, Vol: 372, Pages: 1274-1277, ISSN: 1533-4406
Agua-Agum J, Ariyarajah A, Aylward B, et al., 2015, West African Ebola epidemic after one year - slowing but not yet under control, New England Journal of Medicine, Vol: 372, Pages: 584-587, ISSN: 1533-4406
Dorigatti I, Cauchemez S, Ferguson NM, 2013, Increased transmissibility explains the third wave of infection by the 2009 H1N1 pandemic virus in England, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, Vol: 110, Pages: 13422-13427, ISSN: 0027-8424
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- Citations: 54
Dorigatti I, Cauchemez S, Pugliese A, et al., 2011, A new approach to characterising infectious disease transmission dynamics from sentinel surveillance: application to the Italian 2009–2010 A/H1N1 influenza pandemic, Epidemics, Vol: 4, Pages: 9-21, ISSN: 1878-0067
Syndromic and virological data are routinely collected by many countries and are often the only information available in real time. The analysis of surveillance data poses many statistical challenges that have not yet been addressed. For instance, the fraction of cases that seek healthcare and are thus detected is often unknown. Here, we propose a general statistical framework that explicitly takes into account the way the surveillance data are generated. Our approach couples a deterministic mathematical model with a statistical description of the reporting process and is applied to surveillance data collected in Italy during the 2009–2010 A/H1N1 influenza pandemic. We estimate that the reproduction number R was initially into the range 1.2–1.4 and that case detection in children was significantly higher than in adults. According to the best fit models, we estimate that school-age children experienced the highest infection rate overall. In terms of both estimated peak-incidence and overall attack rate, according to the Susceptibility and Immunity models the 5–14 years age-class was about 5 times more infected than the 65+ years old age-group and about twice more than the 15–64 years age-class. The multiplying factors are doubled using the Baseline model. Overall, the estimated attack rate was about 16% according to the Baseline model and 30% according to the Susceptibility and Immunity models.
Dorigatti I, Pugliese A, 2011, Analysis of a vaccine model with cross-immunity: When can two competing infectious strains coexist?, MATHEMATICAL BIOSCIENCES, Vol: 234, Pages: 33-46, ISSN: 0025-5564
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- Citations: 5
Moslonka-Lefebvre M, Finley A, Dorigatti I, et al., 2011, Networks in plant epidemiology: from genes to landscapes, countries, and continents, Phytopathology, Vol: 101, Pages: 392-403, ISSN: 1943-7684
Dorigatti I, Mulatti P, Rosa R, et al., 2010, Modelling the spatial spread of H7N1 avian influenza virus among poultry farms in Italy, EPIDEMICS, Vol: 2, Pages: 29-35, ISSN: 1755-4365
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- Citations: 14
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