Publications
44 results found
Dye C, 2015, Goal-Directed Resuscitation in Septic Shock, NEW ENGLAND JOURNAL OF MEDICINE, Vol: 372, Pages: 189-189, ISSN: 0028-4793
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- Citations: 11
Turner HC, Walker M, French MD, et al., 2014, Neglected tools for neglected diseases: mathematical models in economic evaluations, TRENDS IN PARASITOLOGY, Vol: 30, Pages: 562-570, ISSN: 1471-4922
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- Citations: 24
WHO Ebola Response Team, 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, ISSN: 0028-4793
BACKGROUNDOn March 23, 2014, the World Health Organization (WHO) was notified of an outbreak of Ebola virus disease (EVD) in Guinea. On August 8, the WHO declared the epidemic to be a “public health emergency of international concern.”METHODSBy September 14, 2014, a total of 4507 probable and confirmed cases, including 2296 deaths from EVD (Zaire species) had been reported from five countries in West Africa — Guinea, Liberia, Nigeria, Senegal, and Sierra Leone. We analyzed a detailed subset of data on 3343 confirmed and 667 probable Ebola cases collected in Guinea, Liberia, Nigeria, and Sierra Leone as of September 14.RESULTSThe majority of patients are 15 to 44 years of age (49.9% male), and we estimate that the case fatality rate is 70.8% (95% confidence interval [CI], 69 to 73) among persons with known clinical outcome of infection. The course of infection, including signs and symptoms, incubation period (11.4 days), and serial interval (15.3 days), is similar to that reported in previous outbreaks of EVD. On the basis of the initial periods of exponential growth, the estimated basic reproduction numbers (R0) are 1.71 (95% CI, 1.44 to 2.01) for Guinea, 1.83 (95% CI, 1.72 to 1.94) for Liberia, and 2.02 (95% CI, 1.79 to 2.26) for Sierra Leone. The estimated current reproduction numbers (R) are 1.81 (95% CI, 1.60 to 2.03) for Guinea, 1.51 (95% CI, 1.41 to 1.60) for Liberia, and 1.38 (95% CI, 1.27 to 1.51) for Sierra Leone; the corresponding doubling times are 15.7 days (95% CI, 12.9 to 20.3) for Guinea, 23.6 days (95% CI, 20.2 to 28.2) for Liberia, and 30.2 days (95% CI, 23.6 to 42.3) for Sierra Leone. Assuming no change in the control measures for this epidemic, by November 2, 2014, the cumulative reported numbers of confirmed and probable cases are predicted to be 5740 in Guinea, 9890 in Liberia, and 5000 in Sierra Leone, exceeding 20,000 in total.CONCLUSIONSThese data indicate that without drastic improvements in control measures, the numbers of
Pinsent A, Blake IM, White MT, et al., 2014, Surveillance of low pathogenic novel H7N9 avian influenza in commercial poultry barns: detection of outbreaks and estimation of virus introduction time, BMC INFECTIOUS DISEASES, Vol: 14, ISSN: 1471-2334
BackgroundBoth high and low pathogenic subtype A avian influenza remain ongoing threats to the commercial poultry industry globally. The emergence of a novel low pathogenic H7N9 lineage in China presents itself as a new concern to both human and animal health and may necessitate additional surveillance in commercial poultry operations in affected regions.MethodsSampling data was simulated using a mechanistic model of H7N9 influenza transmission within commercial poultry barns together with a stochastic observation process. Parameters were estimated using maximum likelihood. We assessed the probability of detecting an outbreak at time of slaughter using both real-time polymerase chain reaction (rt-PCR) and a hemagglutinin inhibition assay (HI assay) before considering more intense sampling prior to slaughter. The day of virus introduction and R 0 were estimated jointly from weekly flock sampling data. For scenarios where R 0 was known, we estimated the day of virus introduction into a barn under different sampling frequencies.ResultsIf birds were tested at time of slaughter, there was a higher probability of detecting evidence of an outbreak using an HI assay compared to rt-PCR, except when the virus was introduced <2 weeks before time of slaughter. Prior to the initial detection of infection N s a m p l e = 50 (1%) of birds were sampled on a weekly basis once, but after infection was detected, N s a m p l e = 2000 birds (40%) were sampled to estimate both parameters. We accurately estimated the day of virus introduction in isolation with weekly and 2-weekly sampling.ConclusionsA strong sampling effort would be required to infer both the day of virus introduction and R 0. Such a sampling effort would not be required to estimate the day of virus introduction alone once R 0 was known, and sampling N s a m p l e = 50 of birds in the flock on a weekly or 2 weekly basis would be sufficient.
Blake IM, Martin R, Goel A, et al., 2014, The role of older children and adults in wild poliovirus transmission, Proceedings of the National Academy of Sciences of the United States of America, Vol: 111, Pages: 10604-10609, ISSN: 0027-8424
As polio eradication inches closer, the absence of poliovirus circulation in most of the world and imperfect vaccination coverage are resulting in immunity gaps and polio outbreaks affecting adults. Furthermore, imperfect, waning intestinal immunity among older children and adults permits reinfection and poliovirus shedding, prompting calls to extend the age range of vaccination campaigns even in the absence of cases in these age groups. The success of such a strategy depends on the contribution to poliovirus transmission by older ages, which has not previously been estimated. We fit a mathematical model of poliovirus transmission to time series data from two large outbreaks that affected adults (Tajikistan 2010, Republic of Congo 2010) using maximum-likelihood estimation based on iterated particle-filtering methods. In Tajikistan, the contribution of unvaccinated older children and adults to transmission was minimal despite a significant number of cases in these age groups [reproduction number, R = 0.46 (95% confidence interval, 0.42–0.52) for >5-y-olds compared to 2.18 (2.06–2.45) for 0- to 5-y-olds]. In contrast, in the Republic of Congo, the contribution of older children and adults was significant [R = 1.85 (1.83–4.00)], perhaps reflecting sanitary and socioeconomic variables favoring efficient virus transmission. In neither setting was there evidence for a significant role of imperfect intestinal immunity in the transmission of poliovirus. Bringing the immunization response to the Tajikistan outbreak forward by 2 wk would have prevented an additional 130 cases (21%), highlighting the importance of early outbreak detection and response.
Blake IM, Donnelly CA, 2014, A simple incidence-based method to avoid misinterpretation of bovine tuberculosis incidence trends in great britain., PLoS Curr, Vol: 6
The incidence of bovine tuberculosis (TB) in Great Britain has generally been increasing in recent decades. Routine ante-mortem testing of cattle herds is required for disease surveillance and control, due to the asymptomatic nature of the infection. The Department for Environment, Food and Rural Affairs (Defra) publishes TB incidence trends as the percentage of officially TB-free (OTF) herds tested per month with OTF status withdrawn due to post-mortem evidence of infection. This method can result in artefactual fluctuations. We have previously demonstrated an alternative method, that distributes incidents equally over the period of risk, provides a more accurate representation of underlying risk. However, this method is complex and it may not be sufficiently straightforward for use in the national statistics. Here we present a simple incidence-based method that adjusts for the time between tests and show it can provide a reasonable representation of the underlying risk without artefactual fluctuations.
Koukounari A, Moustaki I, Grassly NC, et al., 2013, Using a Nonparametric Multilevel Latent Markov Model to Evaluate Diagnostics for Trachoma, American Journal of Epidemiology, Vol: 177, Pages: 913-922, ISSN: 0002-9262
In disease control or elimination programs, diagnostics are essential for assessing the impact of interventions, refining treatment strategies, and minimizing the waste of scarce resources. Although high-performance tests are desirable, increased accuracy is frequently accompanied by a requirement for more elaborate infrastructure, which is often not feasible in the developing world. These challenges are pertinent to mapping, impact monitoring, and surveillance in trachoma elimination programs. To help inform rational design of diagnostics for trachoma elimination, we outline a nonparametric multilevel latent Markov modeling approach and apply it to 2 longitudinal cohort studies of trachoma-endemic communities in Tanzania (2000–2002) and The Gambia (2001–2002) to provide simultaneous inferences about the true population prevalence of Chlamydia trachomatis infection and disease and the sensitivity, specificity, and predictive values of 3 diagnostic tests for C. trachomatis infection. Estimates were obtained by using data collected before and after mass azithromycin administration. Such estimates are particularly important for trachoma because of the absence of a true “gold standard” diagnostic test for C. trachomatis. Estimated transition probabilities provide useful insights into key epidemiologic questions about the persistence of disease and the clearance of infection as well as the required frequency of surveillance in the postelimination setting.
Blake IM, Donnelly CA, 2012, Estimating risk over time using data from targeted surveillance systems: Application to bovine tuberculosis in Great Britain, EPIDEMICS, Vol: 4, Pages: 179-186, ISSN: 1755-4365
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- Citations: 2
Solomon AW, Engels D, Bailey RL, et al., 2012, A Diagnostics Platform for the Integrated Mapping, Monitoring and Surveillance of Neglected Tropical Diseases: Rationale and Target Product Profiles, PLoS Neglected Tropical Diseases
Gambhir M, Basanez MG, Blake IM, et al., 2010, Modelling trachoma for control programmes, Modelling Parasite Transmission and Control, Editors: Michael, Spear, Publisher: Austin, Texas: Landes Bioscience, ISBN: 9781441960641
Blake IM, Burton MJ, Solomon AW, et al., 2010, Targeting Antibiotics to Households for Trachoma Control, PLOS NEGLECTED TROPICAL DISEASES, Vol: 4, ISSN: 1935-2735
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- Citations: 16
Gambhir M, Basanez M-G, Blake IM, et al., 2010, Modelling Trachoma for Control Programmes, MODELLING PARASITE TRANSMISSION AND CONTROL, Vol: 673, Pages: 141-156, ISSN: 0065-2598
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- Citations: 6
Gambhir M, Basanez M-G, Burton MJ, et al., 2009, The Development of an Age-Structured Model for Trachoma Transmission Dynamics, Pathogenesis and Control, PLOS Neglected Tropical Diseases, Vol: 3, ISSN: 1935-2735
Background: Trachoma, the worldwide leading infectious cause of blindness, is due to repeated conjunctival infection with Chlamydia trachomatis. The effects of control interventions on population levels of infection and active disease can be promptly measured, but the effects on severe ocular sequelae require long-term monitoring. We present an age-structured mathematical model of trachoma transmission and disease to predict the impact of interventions on the prevalence of blinding trachoma.Methodology/Principal Findings: The model is based on the concept of multiple reinfections leading to progressive conjunctival scarring, trichiasis, corneal opacity and blindness. It also includes aspects of trachoma natural history, such as an increasing rate of recovery from infection and a decreasing chlamydial load with subsequent infections that depend upon a (presumed) acquired immunity that clears infection with age more rapidly. Parameters were estimated using maximum likelihood by fitting the model to pre-control infection prevalence data from hypo-, meso- and hyperendemic communities from The Gambia and Tanzania. The model reproduces key features of trachoma epidemiology: 1) the age-profile of infection prevalence, which increases to a peak at very young ages and declines at older ages; 2) a shift in this prevalence peak, toward younger ages in higher force of infection environments; 3) a raised overall profile of infection prevalence with higher force of infection; and 4) a rising profile, with age, of the prevalence of the ensuing severe sequelae (trachomatous scarring, trichiasis), as well as estimates of the number of infections that need to occur before these sequelae appear.Conclusions/Significance: We present a framework that is sufficiently comprehensive to examine the outcomes of the A (antibiotic) component of the SAFE strategy on disease. The suitability of the model for representing population-level patterns of infection and disease sequelae is discussed in
Blake IM, Burton MJ, Bailey RL, et al., 2009, Estimating Household and Community Transmission of Ocular <i>Chlamydia trachomatis</i>, PLOS NEGLECTED TROPICAL DISEASES, Vol: 3, ISSN: 1935-2735
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- Citations: 38
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