68 results found
Fumanellil L, Ajelli M, Merler S, et al., 2016, Model-based comprehensive analysis of school closure policies for mitigating influenza epidemics and pandemics, Plos Computational Biology, Vol: 12, ISSN: 1553-7358
School closure policies are among the non-pharmaceutical measures taken into consideration to mitigate influenza epidemics and pandemics spread. However, a systematic review of the effectiveness of alternative closure policies has yet to emerge. Here we perform a model-based analysis of four types of school closure, ranging from the nationwide closure of all schools at the same time to reactive gradual closure, starting from class-by-class, then grades and finally the whole school. We consider policies based on triggers that are feasible to monitor, such as school absenteeism and national ILI surveillance system. We found that, under specific constraints on the average number of weeks lost per student, reactive school-by-school, gradual, and county-wide closure give comparable outcomes in terms of optimal infection attack rate reduction, peak incidence reduction or peak delay. Optimal implementations generally require short closures of one week each; this duration is long enough to break the transmission chain without leading to unnecessarily long periods of class interruption. Moreover, we found that gradual and county closures may be slightly more easily applicable in practice as they are less sensitive to the value of the excess absenteeism threshold triggering the start of the intervention. These findings suggest that policy makers could consider school closure policies more diffusely as response strategy to influenza epidemics and pandemics, and the fact that some countries already have some experience of gradual or regional closures for seasonal influenza outbreaks demonstrates that logistic and feasibility challenges of school closure strategies can be to some extent overcome.
Killingley B, Greatorex J, Digard P, et al., 2015, The environmental deposition of influenza virus from patients infected with influenza A(H1N1)pdm09: Implications for infection prevention and control, JOURNAL OF INFECTION AND PUBLIC HEALTH, Vol: 9, Pages: 278-288, ISSN: 1876-0341
Faye O, Andronico A, Faye O, et al., 2015, Use of Viremia to Evaluate the Baseline Case Fatality Ratio of Ebola Virus Disease and Inform Treatment Studies: A Retrospective Cohort Study., PLOS Medicine, Vol: 12, ISSN: 1549-1277
BACKGROUND: The case fatality ratio (CFR) of Ebola virus disease (EVD) can vary over time and space for reasons that are not fully understood. This makes it difficult to define the baseline CFRs needed to evaluate treatments in the absence of randomized controls. Here, we investigate whether viremia in EVD patients may be used to evaluate baseline EVD CFRs. METHODS AND FINDINGS: We analyzed the laboratory and epidemiological records of patients with EVD confirmed by reverse transcription PCR hospitalized in the Conakry area, Guinea, between 1 March 2014 and 28 February 2015. We used viremia and other variables to model the CFR. Data for 699 EVD patients were analyzed. In the week following symptom onset, mean viremia remained stable, and the CFR increased with viremia, V, from 21% (95% CI 16%-27%) for low viremia (V < 104.4 copies/ml) to 53% (95% CI 44%-61%) for intermediate viremia (104.4 ≤ V < 105.2 copies/ml) and 81% (95% CI 75%-87%) for high viremia (V ≥ 105.2 copies/ml). Compared to adults (15-44 y old [y.o.]), the CFR was larger in young children (0-4 y.o.) (odds ratio [OR]: 2.44; 95% CI 1.02-5.86) and older adults (≥45 y.o.) (OR: 2.84; 95% CI 1.81-4.46) but lower in children (5-14 y.o.) (OR: 0.46; 95% CI 0.24-0.86). An order of magnitude increase in mean viremia in cases after July 2014 compared to those before coincided with a 14% increase in the CFR. Our findings come from a large hospital-based study in Conakry and may not be generalizable to settings with different case profiles, such as with individuals who never sought care. CONCLUSIONS: Viremia in EVD patients was a strong predictor of death that partly explained variations in CFR in the study population. This study provides baseline CFRs by viremia group, which allow appropriate adjustment when estimating efficacy in treatment studies. In randomized controlled trials, stratifying analysis on viremia groups could reduce sample size requirements by 25%. We hypothesize that monitoring the
Gambhir M, Clark TA, Cauchemez S, et al., 2015, A Change in Vaccine Efficacy and Duration of Protection Explains Recent Rises in Pertussis Incidence in the United States, PLOS Computational Biology, Vol: 11, ISSN: 1553-734X
Over the past ten years the incidence of pertussis in the United States (U.S.) has risen steadily, with 2012 seeing the highest case number since 1955. There has also been a shift over the same time period in the age group reporting the largest number of cases (aside from infants), from adolescents to 7–11 year olds. We use epidemiological modelling and a large case incidence dataset to explain the upsurge. We investigate several hypotheses for the upsurge in pertussis cases by fitting a suite of dynamic epidemiological models to incidence data from the National Notifiable Disease Surveillance System (NNDSS) between 1990–2009, as well as incidence data from a variety of sources from 1950–1989. We find that: the best-fitting model is one in which vaccine efficacy and duration of protection of the acellular pertussis (aP) vaccine is lower than that of the whole-cell (wP) vaccine, (efficacy of the first three doses 80% [95% CI: 78%, 82%] versus 90% [95% CI: 87%, 94%]), increasing the rate at which disease is reported to NNDSS is not sufficient to explain the upsurge and 3) 2010–2012 disease incidence is predicted well. In this study, we use all available U.S. surveillance data to: 1) fit a set of mathematical models and determine which best explains these data and 2) determine the epidemiological and vaccine-related parameter values of this model. We find evidence of a difference in efficacy and duration of protection between the two vaccine types, wP and aP (aP efficacy and duration lower than wP). Future refinement of the model presented here will allow for an exploration of alternative vaccination strategies such as different age-spacings, further booster doses, and cocooning.
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.
Walker PGT, Jost C, Ghani AC, et al., 2015, Estimating the Transmissibility of H5N1 and the Effect of Vaccination in Indonesia, TRANSBOUNDARY AND EMERGING DISEASES, Vol: 62, Pages: 200-208, ISSN: 1865-1674
Mansiaux Y, Salez N, Lapidus N, et al., 2015, Causal analysis of H1N1pdm09 influenza infection risk in a household cohort, JOURNAL OF EPIDEMIOLOGY AND COMMUNITY HEALTH, Vol: 69, Pages: 272-277, ISSN: 0143-005X
Faye O, Boelle P-Y, Heleze E, et al., 2015, Chains of transmission and control of Ebola virus disease in Conakry, Guinea, in 2014: an observational study, LANCET INFECTIOUS DISEASES, Vol: 15, Pages: 320-326, ISSN: 1473-3099
Tong SYC, Holden MTG, Nickerson EK, et al., 2015, Genome sequencing defines phylogeny and spread of methicillin-resistant <i>Staphylococcus aureus</i> in a high transmission setting, GENOME RESEARCH, Vol: 25, Pages: 111-118, ISSN: 1088-9051
Pelat C, Ferguson NM, White PJ, et al., 2014, Optimizing the Precision of Case Fatality Ratio Estimates Under the Surveillance Pyramid Approach, AMERICAN JOURNAL OF EPIDEMIOLOGY, Vol: 180, Pages: 1036-1046, ISSN: 0002-9262
Cauchemez S, Ferguson NM, Fox A, et al., 2014, Determinants of Influenza Transmission in South East Asia: Insights from a Household Cohort Study in Vietnam, PLOS PATHOGENS, Vol: 10, ISSN: 1553-7366
Cauchemez S, Ledrans M, Poletto C, et al., 2014, Local and regional spread of chikungunya fever in the Americas, EUROSURVEILLANCE, Vol: 19, Pages: 15-23, ISSN: 1025-496X
Churcher TS, Cohen JM, Novotny J, et al., 2014, PUBLIC HEALTH Measuring the path toward malaria elimination, Science, Vol: 344, Pages: 1230-1232, ISSN: 0036-8075
In many parts of the world, malaria elimination—defined by the World Health Organization (WHO) as the absence of locally acquired malaria cases in the country—is being considered as a target because of recent successes in reducing disease burden (1, 2). Rigorous evaluation of malaria elimination programs is essential for financial and political support to be maintained. Yet such evaluation remains challenging, and appropriate metrics to ascertain “success” are needed.
Jombart T, Aanensen DM, Baguelin M, et al., 2014, OutbreakTools: A new platform for disease outbreak analysis using the R software, Epidemics, Vol: 7, Pages: 28-34, ISSN: 1755-4365
The investigation of infectious disease outbreaks relies on the analysis of increasingly complex and diverse data, which offer new prospects for gaining insights into disease transmission processes and informing public health policies. However, the potential of such data can only be harnessed using a number of different, complementary approaches and tools, and a unified platform for the analysis of disease outbreaks is still lacking. In this paper, we present the new R package OutbreakTools, which aims to provide a basis for outbreak data management and analysis in R. OutbreakTools is developed by a community of epidemiologists, statisticians, modellers and bioinformaticians, and implements classes and methods for storing, handling and visualizing outbreak data. It includes real and simulated outbreak datasets. Together with a number of tools for infectious disease epidemiology recently made available in R, OutbreakTools contributes to the emergence of a new, free and open-source platform for the analysis of disease outbreaks.
Cauchemez S, Van Kerkhove MD, Archer BN, et al., 2014, School closures during the 2009 influenza pandemic: national and local experiences, BMC INFECTIOUS DISEASES, Vol: 14
Jombart T, Cori A, Didelot X, et al., 2014, Bayesian Reconstruction of Disease Outbreaks by Combining Epidemiologic and Genomic Data, PLOS COMPUTATIONAL BIOLOGY, Vol: 10, ISSN: 1553-734X
Cauchemez S, Fraser C, Van Kerkhove MD, et 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
Cori A, Ferguson NM, Fraser C, et al., 2013, A New Framework and Software to Estimate Time-Varying Reproduction Numbers During Epidemics, AMERICAN JOURNAL OF EPIDEMIOLOGY, Vol: 178, Pages: 1505-1512, ISSN: 0002-9262
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
Gambhir M, Swerdlow DL, Finelli L, et al., 2013, Multiple Contributory Factors to the Age Distribution of Disease Cases: A Modeling Study in the Context of Influenza A(H3N2v), CLINICAL INFECTIOUS DISEASES, Vol: 57, Pages: S23-S27, ISSN: 1058-4838
Cauchemez S, Van Kerkhove MD, Riley S, et 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
Nouvellet P, Donnelly CA, Nardi MD, et al., 2013, Rabies and Canine Distemper Virus Epidemics in the Red Fox Population of Northern Italy (2006-2010), PLOS One, Vol: 8, ISSN: 1932-6203
Since 2006 the red fox (Vulpes vulpes) population in north-eastern Italy has experienced an epidemic of canine distemper virus (CDV). Additionally, in 2008, after a thirteen-year absence from Italy, fox rabies was re-introduced in the Udine province at the national border with Slovenia. Disease intervention strategies are being developed and implemented to control rabies in this area and minimise risk to human health. Here we present empirical data and the epidemiological picture relating to these epidemics in the period 2006–2010. Of important significance for epidemiological studies of wild animals, basic mathematical models are developed to exploit information collected from the surveillance program on dead and/or living animals in order to assess the incidence of infection. These models are also used to estimate the rate of transmission of both diseases and the rate of vaccination, while correcting for a bias in early collection of CDV samples. We found that the rate of rabies transmission was roughly twice that of CDV, with an estimated effective contact between infected and susceptible fox leading to a new infection occurring once every 3 days for rabies, and once a week for CDV. We also inferred that during the early stage of the CDV epidemic, a bias in the monitoring protocol resulted in a positive sample being almost 10 times more likely to be collected than a negative sample. We estimated the rate of intake of oral vaccine at 0.006 per day, allowing us to estimate that roughly 68% of the foxes would be immunised. This was confirmed by field observations. Finally we discuss the implications for the eco-epidemiological dynamics of both epidemics in relation to control measures.
Lapidus N, de Lamballerie X, Salez N, et al., 2013, Factors Associated with Post-Seasonal Serological Titer and Risk Factors for Infection with the Pandemic A/H1N1 Virus in the French General Population, PLOS ONE, Vol: 8, ISSN: 1932-6203
Cauchemez S, Epperson S, Biggerstaff M, et al., 2013, Using Routine Surveillance Data to Estimate the Epidemic Potential of Emerging Zoonoses: Application to the Emergence of US Swine Origin Influenza A H3N2v Virus, PLOS MEDICINE, Vol: 10, ISSN: 1549-1277
Cauchemez S, Horby P, Fox A, et al., 2012, Influenza Infection Rates, Measurement Errors and the Interpretation of Paired Serology, PLOS PATHOGENS, Vol: 8, ISSN: 1553-7366
Walker P, Cauchemez S, Hartemink N, et al., 2012, Outbreaks of H5N1 in poultry in Thailand: the relative role of poultry production types in sustaining transmission and the impact of active surveillance in control, JOURNAL OF THE ROYAL SOCIETY INTERFACE, Vol: 9, Pages: 1836-1845, ISSN: 1742-5689
Cremin I, Cauchemez S, Garnett GP, et al., 2012, Patterns of uptake of HIV testing in sub-Saharan Africa in the pre-treatment era, TROPICAL MEDICINE & INTERNATIONAL HEALTH, Vol: 17, Pages: e26-e37, ISSN: 1360-2276
Lapidus N, de lamballerie X, Salez N, et al., 2012, Integrative study of pandemic A/H1N1 influenza infections: design and methods of the CoPanFlu-France cohort, BMC PUBLIC HEALTH, Vol: 12, ISSN: 1471-2458
Yu H, Cauchemez S, Donnelly CA, et al., 2012, Transmission Dynamics, Border Entry Screening, and School Holidays during the 2009 Influenza A (H1N1) Pandemic, China, EMERGING INFECTIOUS DISEASES, Vol: 18, Pages: 758-766, ISSN: 1080-6040
Cauchemez S, Ferguson NM, 2012, Methods to infer transmission risk factors in complex outbreak data, JOURNAL OF THE ROYAL SOCIETY INTERFACE, Vol: 9, Pages: 456-469, ISSN: 1742-5689
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