Estimation of force of infection based on different epidemiological proxies: 2009/2010 Influenza epidemic in Malta

Information about infectious disease outbreaks is often gathered indirectly, from doctor's reports and health board records. It also typically underestimates the actual number of cases, but the relationship between the observed proxies and the numbers that drive the diseases is complicated, nonlinear and potentially time- and state-dependent. We use a combination of data collection from the 2009-2010 H1N1 outbreak in Malta, compartmental modelling and Bayesian inference to explore the effect of using various sources of information (consultations, doctor's diagnose, swabbing and molecular testing) on estimation of the effective basic reproduction ratio, Rt. Different proxies and different sampling rates (daily and weekly) lead to similar behaviour of Rt as the epidemic unfolds, although individual parameters (force of infection, length of latent and infectious period) vary. We also demonstrate that the relationship between different proxies varies as epidemic progresses, with the first period characterised by high ratio of consultations and influenza diagnoses to actual confirmed cases of H1N1. This has important consequences for modelling that is based on reconstructing influenza cases from doctor's reports

The design and implementation of Object Grammars

An Object Grammar is a variation on traditional BNF grammars, where the notation is extended to support declarative bidirectional mappings between text and object graphs. The two directions for interpreting Object Grammars are parsing and formatting. Parsing transforms text into an object graph by recognizing syntactic features and creating the corresponding object structure. In the reverse direction, formatting recognizes object graph features and generates an appropriate textual presentation. The key to Object Grammars is the expressive power of the mapping, which decouples the syntactic structure from the graph structure. To handle graphs, Object Grammars support declarative annotations for resolving textual names that refer to arbitrary objects in the graph structure. Predicates on the semantic structure provide additional control over the mapping. Furthermore, Object Grammars are compositional so that languages may be defined in a modular fashion. We have implemented our approach to Object Grammars as one of the foundations of the Ens (o) over bar system and illustrate the utility of our approach by showing how it enables definition and composition of domain-specific languages (DSLs). (C) 2014 Elsevier B.V. All rights reserved.</p

Toward Theoretical Techniques for Measuring the Use of Human Effort in Visual Analytic Systems

Visual analytic systems have long relied on user studies and standard datasets to demonstrate advances to the state of the art, as well as to illustrate the efficiency of solutions to domain-specific challenges. This approach has enabled some important comparisons between systems, but unfortunately the narrow scope required to facilitate these comparisons has prevented many of these lessons from being generalized to new areas. At the same time, advanced visual analytic systems have made increasing use of human-machine collaboration to solve problems not tractable by machine computation alone. To continue to make progress in modeling user tasks in these hybrid visual analytic systems, we must strive to gain insight into what makes certain tasks more complex than others. This will require the development of mechanisms for describing the balance to be struck between machine and human strengths with respect to analytical tasks and workload. In this paper, we argue for the necessity of theoretical tools for reasoning about such balance in visual analytic systems and demonstrate the utility of the Human Oracle Model for this purpose in the context of sensemaking in visual analytics. Additionally, we make use of the Human Oracle Model to guide the development of a new system through a case study in the domain of cybersecurity

Local variations in spatial synchrony of influenza epidemics

Background: Understanding the mechanism of influenza spread across multiple geographic scales is not complete. While the mechanism of dissemination across regions and states of the United States has been described, understanding the determinants of dissemination between counties has not been elucidated. The paucity of high resolution spatial-temporal influenza incidence data to evaluate disease structure is often not available. Methodology and Findings: We report on the underlying relationship between the spread of influenza and human movement between counties of one state. Significant synchrony in the timing of epidemics exists across the entire state and decay with distance (regional correlation = 62%). Synchrony as a function of population size display evidence of hierarchical spread with more synchronized epidemics occurring among the most populated counties. A gravity model describing movement between two populations is a stronger predictor of influenza spread than adult movement to and from workplaces suggesting that non-routine and leisure travel drive local epidemics. Conclusions: These findings highlight the complex nature of influenza spread across multiple geographic scales. © 2012 Stark et al

Internet Search Limitations and Pandemic Influenza, Singapore

10.3201/eid1610.100840Emerging Infectious Diseases16101647-EIDI

Do antibody responses to the influenza vaccine persist year-round in the elderly? A systematic review and meta-analysis.

INTRODUCTION: The influenza vaccine is less immunogenic in older than younger adults, and the duration of protection is unclear. Determining if protection persists beyond a typical seasonal epidemic is important for climates where influenza virus activity is year-round. METHODS: A systematic review protocol was developed and registered with PROSPERO [CRD42015023847]. Electronic databases were searched systematically for studies reporting haemagglutination-inhibition (HI) titres 180-360days following vaccination with inactivated trivalent seasonal influenza vaccine, in adults aged ?65years. Geometric mean titre (GMT) and seroprotection (HI titre ?1:40) at each time point was extracted. A Bayesian model was developed of titre trajectories from pre-vaccination to Day 360. In the meta-analysis, studies were aggregated using a random-effects model to compare pre-vaccination with post-vaccination HI titres at Day 21-42 ('seroconversion'), Day 180 and Day 360. Potential sources of bias were systematically assessed, and heterogeneity explored. RESULTS: 2864 articles were identified in the literature search, of which nineteen met study inclusion/exclusion criteria. Sixteen studies contained analysable data from 2565 subjects. In the Bayesian model, the proportion of subjects seroprotected increased from 41-51% pre-vaccination to 75-78% at seroconversion. Seroprotection subsequently fell below 60% for all serotypes by Day 360: A/H1 42% (95% CI 38-46), A/H3 59% (54-63), B 47% (42-52). The Bayesian model of GMT trajectories revealed a similar pattern. By Day 360, titres were similar to pre-vaccination levels. In the meta-analysis, no significant difference in proportion of subjects seroprotected, 0 (-0.11, 0.11) or in log2GMT 0.30 (-0.02, 0.63) was identified by Day 360 compared with pre-vaccination. The quality of this evidence was limited to moderate on account of significant participant dropout. CONCLUSIONS: The review found consistent evidence that HI antibody responses following influenza vaccination do not reliably persist year-round in older adults. Alternative vaccination strategies could provide clinical benefits in regions where year-round protection is important

The feasibility of age-specific travel restrictions during influenza pandemics

<p>Abstract</p> <p>Background</p> <p>Epidemiological studies have shown that imposing travel restrictions to prevent or delay an influenza pandemic may not be feasible. To delay an epidemic substantially, an extremely high proportion of trips (~99%) would have to be restricted in a homogeneously mixing population. Influenza is, however, strongly influenced by age-dependent transmission dynamics, and the effectiveness of age-specific travel restrictions, such as the selective restriction of travel by children, has yet to be examined.</p> <p>Methods</p> <p>A simple stochastic model was developed to describe the importation of infectious cases into a population and to model local chains of transmission seeded by imported cases. The probability of a local epidemic, and the time period until a major epidemic takes off, were used as outcome measures, and travel restriction policies in which children or adults were preferentially restricted were compared to age-blind restriction policies using an age-dependent next generation matrix parameterized for influenza H1N1-2009.</p> <p>Results</p> <p>Restricting children from travelling would yield greater reductions to the short-term risk of the epidemic being established locally than other policy options considered, and potentially could delay an epidemic for a few weeks. However, given a scenario with a total of 500 imported cases over a period of a few months, a substantial reduction in the probability of an epidemic in this time period is possible only if the transmission potential were low and assortativity (i.e. the proportion of contacts within-group) were unrealistically high. In all other scenarios considered, age-structured travel restrictions would not prevent an epidemic and would not delay the epidemic for longer than a few weeks.</p> <p>Conclusions</p> <p>Selectively restricting children from traveling overseas during a pandemic may potentially delay its arrival for a few weeks, depending on the characteristics of the pandemic strain, but could have less of an impact on the economy compared to restricting adult travelers. However, as long as adults have at least a moderate potential to trigger an epidemic, selectively restricting the higher risk group (children) may not be a practical option to delay the arrival of an epidemic substantially.</p

The role of symptomatic presentation in influenza A transmission risk

Computer models can be useful in planning interventions against novel strains of influenza. However such models sometimes make unsubstantiated assumptions about the relative infectivity of asymptomatic and symptomatic cases, or conversely assume there is no impact at all. Using household-level data from known-index studies of virologically confirmed influenza A infection, the relationship between an individual's infectiousness and their symptoms was quantified using a discrete-generation transmission model and Bayesian Markov chain Monte Carlo methods. It was found that the presence of particular respiratory symptoms in an index case does not influence transmission probabilities, with the exception of child-to-child transmission where the donor has phlegm or a phlegmy coughR.W. was supported by a New Colombo Plan scholarship from the Australian Department of Foreign Affairs and Trade (DFAT). K.P. and A.R.C. were supported by funding from the Ministry of Education, Ministry of Health, Ministry of Defence, and the National University Health System, all Singapore (grant nos. CDPHRG/ 0009/2014, NUHSR0/2013/142IH7N9104, PROJECT MODUS 9014100379). B.J.C. was supported by the National Institute of General Medical Sciences (grant U54 GM088558), a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. T11-705/14N), and a commissioned grant from the Health and Medical Research Fund from the Government of the Hong Kong Special Administrative Region. The original household trial in Hong Kong was supported by the United States Centers for Disease Control and Prevention (grant no. 1 U01 CI000439)

Age-related risk of household transmission of COVID-19 in Singapore.

Prior to the implementation of social distancing measures, we monitored the close family contacts of the first 400 cases of COVID-19 in Singapore for SARS-CoV-2 infection to determine the risk of infection with age. Adjusting for gender and household size, the risk of COVID-19 infection in household contacts was found to increase with age