Prof Ben Cooper

Research Area: Bioinformatics & Stats (inc. Modelling and Computational Biology)
Technology Exchange: Bioinformatics, Computational biology and Medical statistics
Scientific Themes: Tropical Medicine & Global Health and Immunology & Infectious Disease

Ben Cooper holds an MRC senior non-clinical research fellowship and is based at the Mahidol-Oxford Tropical Medicine Research Unit in Bangkok.  

His work uses mathematical modelling and statistical techniques to help understand infectious disease dynamics and evaluate potential control measures.  This involves developing mathematical models to help evaluate the likely impact and cost-effectiveness of control measures,  developing and applying new statistical approaches based on mechanistic  models for the analysis of longitudinal infectious disease data (increasingly making use of whole genome sequence data), and  designing and analysing epidemiological studies.  The major focus of this work is on antibiotic-resistant bacteria in resource-limited hospital settings.

Additional projects include within-host dynamics of Plasmodium vivax, ecological interactions of the nasopharyngeal flora, cost-effectiveness of seasonal influenza vaccination in Thailand, and dynamics and control of Hepatitis E infections in refugee camps.

 

Name Department Institution Country
Dr Paul Turner Tropical Medicine University of Oxford United Kingdom
Prof Lisa J White Tropical Medicine University of Oxford United Kingdom
Dr Direk Limmathurotsakul Tropical Medicine University of Oxford United Kingdom
Dr Sharon J Peacock Tropical Medicine University of Oxford United Kingdom
Dr Jonathan D Edgeworth Guy’s and St Thomas’ NHS Foundation Trust United Kingdom
Prof Marc Bonten University Medical Center Utrecht Netherlands
Prof Angela McLean Department of Zoology University of Oxford United Kingdom
Dr Craig MacLean Department of Zoology University of Oxford United Kingdom
Prof Nicholoas Graves QUT Australia
Dr Aronrag C Meeyai Mahidol University Thailand

Vlek AL, Cooper BS, Kypraios T, Cox A, Edgeworth JD, Auguet OT. 2013. Clustering of antimicrobial resistance outbreaks across bacterial species in the intensive care unit. Clin Infect Dis, 57 (1), pp. 65-76. Read abstract | Read more

BACKGROUND: There are frequent reports of intensive care unit (ICU) outbreaks due to transmission of particular antibiotic-resistant bacteria. Less is known about the burden of outbreaks of resistance due to horizontal transfer of mobile genetic elements between species. Moreover, the potential of existing statistical software as a preliminary means for detecting such events has never been assessed. This study uses a software package to determine the burden of species and resistance outbreaks in 2 adjacent ICUs and to look for evidence of clustering of resistance outbreaks consistent with interspecies transmission of resistance elements. METHODS: A retrospective analysis of data from 2 adjacent 15-bed adult ICUs between 2002 and 2009 was undertaken. Detection of bacterial species-groups and resistance outbreaks was conducted using SaTScan and WHONet-SaTScan software. Resampling and permutation methods were applied to investigate temporal clustering of outbreaks. RESULTS: Outbreaks occurred for 69% of bacterial species-groups (18/26), and resistance outbreaks were detected against 63% of antibiotics (10/16). Resistance outbreaks against 7 of 10 antibiotics were observed in multiple species-groups simultaneously and there was evidence of inter-species-group dependence for 4 of 7 antibiotics; background temporal changes in resistance did not explain the temporal aggregation of outbreaks in 3 of 7 antibiotics. CONCLUSIONS: Species outbreaks occurred for the majority of bacteria commonly identified in the ICU. There was evidence for frequent temporal clustering of resistance outbreaks consistent with interspecies transmission of resistance elements. Wider application of outbreak detection software combined with targeted sequencing of bacterial genomes is needed to understand the contribution of interspecies gene transfer to resistance emergence. Hide abstract

Worby CJ, Jeyaratnam D, Robotham JV, Kypraios T, O'Neill PD, De Angelis D, French G, Cooper BS. 2013. Estimating the effectiveness of isolation and decolonization measures in reducing transmission of methicillin-resistant Staphylococcus aureus in hospital general wards. Am J Epidemiol, 177 (11), pp. 1306-1313. Read abstract | Read more

Infection control for hospital pathogens such as methicillin-resistant Staphylococcus aureus (MRSA) often takes the form of a package of interventions, including the use of patient isolation and decolonization treatment. Such interventions, though widely used, have generated controversy because of their significant resource implications and the lack of robust evidence with regard to their effectiveness at reducing transmission. The aim of this study was to estimate the effectiveness of isolation and decolonization measures in reducing MRSA transmission in hospital general wards. Prospectively collected MRSA surveillance data from 10 general wards at Guy's and St. Thomas' hospitals, London, United Kingdom, in 2006-2007 were used, comprising 14,035 patient episodes. Data were analyzed with a Markov chain Monte Carlo algorithm to model transmission dynamics. The combined effect of isolation and decolonization was estimated to reduce transmission by 64% (95% confidence interval: 37, 79). Undetected MRSA-positive patients were estimated to be the source of 75% (95% confidence interval: 67, 86) of total transmission events. Isolation measures combined with decolonization treatment were strongly associated with a reduction in MRSA transmission in hospital general wards. These findings provide support for active methods of MRSA control, but further research is needed to determine the relative importance of isolation and decolonization in preventing transmission. Hide abstract

Meeyai A, Cooper B, Coker R, Pan W, Akarasewie P, Iamsirithaworn S. 2012. The effective reproduction number of Pandemic 2009 H1N1 influenza in Thailand: a spatiotemporal analysis INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES, 16 pp. E353-E354. | Read more

Cooper BS, Kypraios T, Batra R, Wyncoll D, Tosas O, Edgeworth JD. 2012. Quantifying type-specific reproduction numbers for nosocomial pathogens: evidence for heightened transmission of an Asian sequence type 239 MRSA clone. PLoS Comput Biol, 8 (4), pp. e1002454. Read abstract | Read more

An important determinant of a pathogen's success is the rate at which it is transmitted from infected to susceptible hosts. Although there are anecdotal reports that methicillin-resistant Staphylococcus aureus (MRSA) clones vary in their transmissibility in hospital settings, attempts to quantify such variation are lacking for common subtypes, as are methods for addressing this question using routinely-collected MRSA screening data in endemic settings. Here we present a method to quantify the time-varying transmissibility of different subtypes of common bacterial nosocomial pathogens using routine surveillance data. The method adapts approaches for estimating reproduction numbers based on the probabilistic reconstruction of epidemic trees, but uses relative hazards rather than serial intervals to assign probabilities to different sources for observed transmission events. The method is applied to data collected as part of a retrospective observational study of a concurrent MRSA outbreak in the United Kingdom with dominant endemic MRSA clones (ST22 and ST36) and an Asian ST239 MRSA strain (ST239-TW) in two linked adult intensive care units, and compared with an approach based on a fully parametric transmission model. The results provide support for the hypothesis that the clones responded differently to an infection control measure based on the use of topical antiseptics, which was more effective at reducing transmission of endemic clones. They also suggest that in one of the two ICUs patients colonized or infected with the ST239-TW MRSA clone had consistently higher risks of transmitting MRSA to patients free of MRSA. These findings represent some of the first quantitative evidence of enhanced transmissibility of a pandemic MRSA lineage, and highlight the potential value of tailoring hospital infection control measures to specific pathogen subtypes. Hide abstract

Birrell PJ, Ketsetzis G, Gay NJ, Cooper BS, Presanis AM, Harris RJ, Charlett A, Zhang XS, White PJ, Pebody RG, De Angelis D. 2011. Bayesian modeling to unmask and predict influenza A/H1N1pdm dynamics in London. Proc Natl Acad Sci U S A, 108 (45), pp. 18238-18243. Read abstract | Read more

The tracking and projection of emerging epidemics is hindered by the disconnect between apparent epidemic dynamics, discernible from noisy and incomplete surveillance data, and the underlying, imperfectly observed, system. Behavior changes compound this, altering both true dynamics and reporting patterns, particularly for diseases with nonspecific symptoms, such as influenza. We disentangle these effects to unravel the hidden dynamics of the 2009 influenza A/H1N1pdm pandemic in London, where surveillance suggests an unusual dominant peak in the summer. We embed an age-structured model into a bayesian synthesis of multiple evidence sources to reveal substantial changes in contact patterns and health-seeking behavior throughout the epidemic, uncovering two similar infection waves, despite large differences in the reported levels of disease. We show how this approach, which allows for real-time learning about model parameters as the epidemic progresses, is also able to provide a sequence of nested projections that are capable of accurately reflecting the epidemic evolution. Hide abstract

Robotham JV, Graves N, Cookson BD, Barnett AG, Wilson JA, Edgeworth JD, Batra R, Cuthbertson BH, Cooper BS. 2011. Screening, isolation, and decolonisation strategies in the control of meticillin resistant Staphylococcus aureus in intensive care units: cost effectiveness evaluation BRITISH MEDICAL JOURNAL, 343 (oct05 3), pp. d5694-d5694. | Read more

Batra R, Cooper BS, Whiteley C, Patel AK, Wyncoll D, Edgeworth JD. 2010. Efficacy and limitation of a chlorhexidine-based decolonization strategy in preventing transmission of methicillin-resistant Staphylococcus aureus in an intensive care unit. Clin Infect Dis, 50 (2), pp. 210-217. Read abstract | Read more

BACKGROUND: Surface-active antiseptics, such as chlorhexidine, are increasingly being used as part of intervention programs to prevent methicillin-resistant Staphylococcus aureus (MRSA) transmission, despite limited evidence and potential for resistance. We report on the effect of an antiseptic protocol on acquisition of both endemic MRSA and an outbreak strain of MRSA sequence type 239 (designated TW). METHODS: Interrupted time-series data on MRSA acquisitions in two 15-bed intensive care units were analyzed using segmented regression models to estimate the effects of sequential introduction of an educational campaign, cohorting, and a chlorhexidine-based antiseptic protocol on transmission of TW and non-TW MRSA strains. Representative TW and non-TW MRSA strains were assessed for carriage of qacA/B genes and antiseptic susceptibility. RESULTS: The antiseptic protocol was associated with a highly significant, immediate 70% reduction in acquisition of non-TW MRSA strains (estimated model-averaged incidence rate ratio, 0.3; 95% confidence interval, 0.19-0.47) and an increase in acquisition of TW MRSA strains (estimated model-averaged incidence rate ratio, 3.85; 95% confidence interval, 0.80-18.59). There was only weak evidence of an effect of other interventions on MRSA transmission. All TW MRSA strains (21 of 21 isolates) and <5% (1 of 21 isolates) of non-TW MRSA strains tested carried the chlorhexidine resistance loci qacA/B. In vitro chlorhexidine minimum bactericidal concentrations of TW strains were 3-fold higher than those of non-TW MRSA strains, and in vivo, only patients with non-TW MRSA demonstrated a reduction in the number of colonization sites in response to chlorhexidine treatment. CONCLUSION: A chlorhexidine-based surface antiseptic protocol can interrupt transmission of MRSA in the intensive care unit, but strains carrying qacA/B genes may be unaffected or potentially spread more rapidly. Hide abstract

Kypraios T, O'Neill PD, Huang SS, Rifas-Shiman SL, Cooper BS. 2010. Assessing the role of undetected colonization and isolation precautions in reducing methicillin-resistant Staphylococcus aureus transmission in intensive care units. BMC Infect Dis, 10 (1), pp. 29. Read abstract | Read more

BACKGROUND: Screening and isolation are central components of hospital methicillin-resistant Staphylococcus aureus (MRSA) control policies. Their prevention of patient-to-patient spread depends on minimizing undetected and unisolated MRSA-positive patient days. Estimating these MRSA-positive patient days and the reduction in transmission due to isolation presents a major methodological challenge, but is essential for assessing both the value of existing control policies and the potential benefit of new rapid MRSA detection technologies. Recent methodological developments have made it possible to estimate these quantities using routine surveillance data. METHODS: Colonization data from admission and weekly nares cultures were collected from eight single-bed adult intensive care units (ICUs) over 17 months. Detected MRSA-positive patients were isolated using single rooms and barrier precautions. Data were analyzed using stochastic transmission models and model fitting was performed within a Bayesian framework using a Markov chain Monte Carlo algorithm, imputing unobserved MRSA carriage events. RESULTS: Models estimated the mean percent of colonized-patient-days attributed to undetected carriers as 14.1% (95% CI (11.7, 16.5)) averaged across ICUs. The percent of colonized-patient-days attributed to patients awaiting results averaged 7.8% (6.2, 9.2). Overall, the ratio of estimated transmission rates from unisolated MRSA-positive patients and those under barrier precautions was 1.34 (0.45, 3.97), but varied widely across ICUs. CONCLUSIONS: Screening consistently detected >80% of colonized-patient-days. Estimates of the effectiveness of barrier precautions showed considerable uncertainty, but in all units except burns/general surgery and one cardiac surgery ICU, the best estimates were consistent with reductions in transmission associated with barrier precautions. Hide abstract

de Smet AMGA, Kluytmans JAJW, Cooper BS, Mascini EM, Benus RFJ, van der Werf TS, van der Hoeven JG, Pickkers P et al. 2009. Decontamination of the Digestive Tract and Oropharynx in ICU Patients New England Journal of Medicine, 360 (1), pp. 20-31. | Read more

Cooper BS, Medley GF, Bradley SJ, Scott GM. 2008. An augmented data method for the analysis of nosocomial infection data. Am J Epidemiol, 168 (5), pp. 548-557. Read abstract | Read more

The analysis of nosocomial infection data for communicable pathogens is complicated by two facts. First, typical pathogens more commonly cause asymptomatic colonization than overt disease, so transmission can be only imperfectly observed through a sequence of surveillance swabs, which themselves have imperfect sensitivity. Any given set of swab results can therefore be consistent with many different patterns of transmission. Second, data are often highly dependent: the colonization status of one patient affects the risk for others, and, in some wards, repeated admissions are common. Here, the authors present a method for analyzing typical nosocomial infection data consisting of results from arbitrarily timed screening swabs that overcomes these problems and enables simultaneous estimation of transmission and importation parameters, duration of colonization, swab sensitivity, and ward- and patient-level covariates. The method accounts for dependencies by using a mechanistic stochastic transmission model, and it allows for uncertainty in the data by imputing the imperfectly observed colonization status of patients over repeated admissions. The approach uses a Markov chain Monte Carlo algorithm, allowing inference within a Bayesian framework. The method is applied to illustrative data from an interrupted time-series study of vancomycin-resistant enterococci transmission in a hematology ward. Hide abstract

White RG, Ben SC, Kedhar A, Orroth KK, Biraro S, Baggaley RF, Whitworth J, Korenromp EL, Ghani A, Boily MC, Hayes RJ. 2007. Quantifying HIV-1 transmission due to contaminated injections. Proc Natl Acad Sci U S A, 104 (23), pp. 9794-9799. Read abstract | Read more

Assessments of the importance of different routes of HIV-1 (HIV) transmission are vital for prioritization of control efforts. Lack of consistent direct data and large uncertainty in the risk of HIV transmission from HIV-contaminated injections has made quantifying the proportion of transmission caused by contaminated injections in sub-Saharan Africa difficult and unavoidably subjective. Depending on the risk assumed, estimates have ranged from 2.5% to 30% or more. We present a method based on an age-structured transmission model that allows the relative contribution of HIV-contaminated injections, and other routes of HIV transmission, to be robustly estimated, both fully quantifying and substantially reducing the associated uncertainty. To do this, we adopt a Bayesian perspective, and show how prior beliefs regarding the safety of injections and the proportion of HIV incidence due to contaminated injections should, in many cases, be substantially modified in light of age-stratified incidence and injection data, resulting in improved (posterior) estimates. Applying the method to data from rural southwest Uganda, we show that the highest estimates of the proportion of incidence due to injections are reduced from 15.5% (95% credible interval) (0.7%, 44.9%) to 5.2% (0.5%, 17.0%) if random mixing is assumed, and from 14.6% (0.7%, 42.5%) to 11.8% (1.2%, 32.5%) under assortative mixing. Lower, and more widely accepted, estimates remain largely unchanged, between 1% and 3% (0.1-6.3%). Although important uncertainty remains, our analysis shows that in rural Uganda, contaminated injections are unlikely to account for a large proportion of HIV incidence. This result is likely to be generalizable to many other populations in sub-Saharan Africa. Hide abstract

Cooper B. 2006. Poxy models and rash decisions. Proc Natl Acad Sci U S A, 103 (33), pp. 12221-12222. | Read more

Cooper BS, Pitman RJ, Edmunds WJ, Gay NJ. 2006. Delaying the international spread of pandemic influenza. PLoS Med, 3 (6), pp. e212. Read abstract | Read more

BACKGROUND: The recent emergence of hypervirulent subtypes of avian influenza has underlined the potentially devastating effects of pandemic influenza. Were such a virus to acquire the ability to spread efficiently between humans, control would almost certainly be hampered by limited vaccine supplies unless global spread could be substantially delayed. Moreover, the large increases that have occurred in international air travel might be expected to lead to more rapid global dissemination than in previous pandemics. METHODS AND FINDINGS: To evaluate the potential of local control measures and travel restrictions to impede global dissemination, we developed stochastic models of the international spread of influenza based on extensions of coupled epidemic transmission models. These models have been shown to be capable of accurately forecasting local and global spread of epidemic and pandemic influenza. We show that under most scenarios restrictions on air travel are likely to be of surprisingly little value in delaying epidemics, unless almost all travel ceases very soon after epidemics are detected. CONCLUSIONS: Interventions to reduce local transmission of influenza are likely to be more effective at reducing the rate of global spread and less vulnerable to implementation delays than air travel restrictions. Nevertheless, under the most plausible scenarios, achievable delays are small compared with the time needed to accumulate substantial vaccine stocks. Hide abstract

Cooper BS, Medley GF, Stone SP, Kibbler CC, Cookson BD, Roberts JA, Duckworth G, Lai R, Ebrahim S. 2004. Methicillin-resistant Staphylococcus aureus in hospitals and the community: stealth dynamics and control catastrophes. Proc Natl Acad Sci U S A, 101 (27), pp. 10223-10228. Read abstract | Read more

Methicillin-resistant Staphylococcus aureus (MRSA) represents a serious threat to the health of hospitalized patients. Attempts to reduce the spread of MRSA have largely depended on hospital hygiene and patient isolation. These measures have met with mixed success: although some countries have almost eliminated MRSA or remained largely free of the organism, others have seen substantial increases despite rigorous control policies. We use a mathematical model to show how these increases can be explained by considering both hospital and community reservoirs of MRSA colonization. We show how the timing of the intervention, the level of resource provision, and chance combine to determine whether control measures succeed or fail. We find that even control measures able to repeatedly prevent sustained outbreaks in the short-term can result in long-term control failure resulting from gradual increases in the community reservoir. If resources do not scale with MRSA prevalence, isolation policies can fail "catastrophically." Hide abstract

Cooper B, Lipsitch M. 2004. The analysis of hospital infection data using hidden Markov models. Biostatistics, 5 (2), pp. 223-237. Read abstract | Read more

Surveillance data for communicable nosocomial pathogens usually consist of short time series of low-numbered counts of infected patients. These often show overdispersion and autocorrelation. To date, almost all analyses of such data have ignored the communicable nature of the organisms and have used methods appropriate only for independent outcomes. Inferences that depend on such analyses cannot be considered reliable when patient-to-patient transmission is important. We propose a new method for analysing these data based on a mechanistic model of the epidemic process. Since important nosocomial pathogens are often carried asymptomatically with overt infection developing in only a proportion of patients, the epidemic process is usually only partially observed by routine surveillance data. We therefore develop a 'structured' hidden Markov model where the underlying Markov chain is generated by a simple transmission model. We apply both structured and standard (unstructured) hidden Markov models to time series for three important pathogens. We find that both methods can offer marked improvements over currently used approaches when nosocomial spread is important. Compared to the standard hidden Markov model, the new approach is more parsimonious, is more biologically plausible, and allows key epidemiological parameters to be estimated. Hide abstract

Cooper BS, Stone SP, Kibbler CC, Cookson BD, Roberts JA, Medley GF, Duckworth G, Lai R, Ebrahim S. 2004. Isolation measures in the hospital management of methicillin resistant Staphylococcus aureus (MRSA): systematic review of the literature. BMJ, 329 (7465), pp. 533. Read abstract | Read more

OBJECTIVE: To evaluate the evidence for the effectiveness of isolation measures in reducing the incidence of methicillin resistant Staphylococcus aureus (MRSA) colonisation and infection in hospital inpatients. DESIGN: Systematic review of published articles. DATA SOURCES: Medline, Embase, CINAHL, Cochrane Library, System for Information on Grey Literature in Europe (SIGLE), and citation lists (1966-2000). REVIEW METHODS: Articles reporting MRSA related outcomes and describing an isolation policy were selected. No quality restrictions were imposed on studies using isolation wards or nurse cohorting. Other studies were included if they were prospective or employed planned comparisons of retrospective data. RESULTS: 46 studies were accepted; 18 used isolation wards, nine used nurse cohorting, and 19 used other isolation policies. Most were interrupted time series, with few planned formal prospective studies. All but one reported multiple interventions. Consideration of potential confounders, measures to prevent bias, and appropriate statistical analysis were mostly lacking. No conclusions could be drawn in a third of studies. Most others provided evidence consistent with a reduction of MRSA acquisition. Six long interrupted time series provided the strongest evidence. Four of these provided evidence that intensive control measures including patient isolation were effective in controlling MRSA. In two others, isolation wards failed to prevent endemic MRSA. CONCLUSION: Major methodological weaknesses and inadequate reporting in published research mean that many plausible alternative explanations for reductions in MRSA acquisition associated with interventions cannot be excluded. No well designed studies exist that allow the role of isolation measures alone to be assessed. None the less, there is evidence that concerted efforts that include isolation can reduce MRSA even in endemic settings. Current isolation measures recommended in national guidelines should continue to be applied until further research establishes otherwise. Hide abstract

Lipsitch M, Cohen T, Cooper B, Robins JM, Ma S, James L, Gopalakrishna G, Chew SK et al. 2003. Transmission dynamics and control of severe acute respiratory syndrome. Science, 300 (5627), pp. 1966-1970. Read abstract | Read more

Severe acute respiratory syndrome (SARS) is a recently described illness of humans that has spread widely over the past 6 months. With the use of detailed epidemiologic data from Singapore and epidemic curves from other settings, we estimated the reproductive number for SARS in the absence of interventions and in the presence of control efforts. We estimate that a single infectious case of SARS will infect about three secondary cases in a population that has not yet instituted control measures. Public-health efforts to reduce transmission are expected to have a substantial impact on reducing the size of the epidemic. Hide abstract

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