HIV with contact-tracing: a case study in Approximate Bayesian Computation

Missing data is a recurrent issue in epidemiology where the infection process may be partially observed. Approximate Bayesian Computation, an alternative to data imputation methods such as Markov Chain Monte Carlo integration, is proposed for making inference in epidemiological models. It is a likelihood-free method that relies exclusively on numerical simulations. ABC consists in computing a distance between simulated and observed summary statistics and weighting the simulations according to this distance. We propose an original extension of ABC to path-valued summary statistics, corresponding to the cumulated number of detections as a function of time. For a standard compartmental model with Suceptible, Infectious and Recovered individuals (SIR), we show that the posterior distributions obtained with ABC and MCMC are similar. In a refined SIR model well-suited to the HIV contact-tracing data in Cuba, we perform a comparison between ABC with full and binned detection times. For the Cuban data, we evaluate the efficiency of the detection system and predict the evolution of the HIV-AIDS disease. In particular, the percentage of undetected infectious individuals is found to be of the order of 40%

Household Responses to Pandemic (H1N1) 2009–related School Closures, Perth, Western Australia

Results from closures will determine the appropriateness and efficacy of this mitigation measure

Patterns of self-reported behaviour change associated with receiving voluntary counselling and testing in a longitudinal study from Manicaland, Zimbabwe.

Voluntary counselling and testing (VCT) is promoted as a potential HIV prevention measure. We describe trends in uptake of VCT for HIV, and patterns of subsequent behaviour change associated with receiving VCT in a population-based open cohort in Manicaland, Zimbabwe. The relationship between receipt of VCT and subsequent reported behaviour was analysed using generalized linear models with random effects. At the third survey, 8.6% of participants (1,079/12,533), had previously received VCT. Women who received VCT, both those positive and negative, reduced their reported number of new partners. Among those testing positive, this risk reduction was enhanced with time since testing. Among men, no behavioural risk reduction associated with VCT was observed. Significant increases in consistent condom use, with regular or non-regular partners, following VCT, were not observed. This study suggests that, among women, particularly those who are infected, behavioural risk reduction does occur following VCT

Variability in school closure decisions in response to 2009 H1N1: a qualitative systems improvement analysis

<p>Abstract</p> <p>Background</p> <p>School closure was employed as a non-pharmaceutical intervention against pandemic 2009 H1N1, particularly during the first wave. More than 700 schools in the United States were closed. However, closure decisions reflected significant variation in rationales, decision triggers, and authority for closure. This variability presents the opportunity for improved efficiency and decision-making.</p> <p>Methods</p> <p>We identified media reports relating to school closure as a response to 2009 H1N1 by monitoring high-profile sources and searching Lexis-Nexis and Google news alerts, and reviewed reports for key themes. News stories were supplemented by observing conference calls and meetings with health department and school officials, and by discussions with decision-makers and community members.</p> <p>Results</p> <p>There was significant variation in the stated goal of closure decision, including limiting community spread of the virus, protecting particularly vulnerable students, and responding to staff shortages or student absenteeism. Because the goal of closure is relevant to its timing, nature, and duration, unclear rationales for closure can challenge its effectiveness. There was also significant variation in the decision-making authority to close schools in different jurisdictions, which, in some instances, was reflected in open disagreement between school and public health officials. Finally, decision-makers did not appear to expect the level of scientific uncertainty encountered early in the pandemic, and they often expressed significant frustration over changing CDC guidance.</p> <p>Conclusions</p> <p>The use of school closure as a public health response to epidemic disease can be improved by ensuring that officials clarify the goals of closure and tailor closure decisions to those goals. Additionally, authority to close schools should be clarified in advance, and decision-makers should expect to encounter uncertainty disease emergencies unfold and plan accordingly.</p

Swine-Origin Influenza A Outbreak 2009 at Shinshu University, Japan

<p>Abstract</p> <p>Background</p> <p>A worldwide outbreak of swine flu H1N1 pandemic influenza occurred in April 2009. To determine the mechanism underlying the spread of infection, we prospectively evaluated a survey implemented at a local university.</p> <p>Methods</p> <p>Between August 2009 and March 2010, we surveyed 3 groups of subjects: 2318 children in six schools attached to the Faculty of Education, 11424 university students, and 3344 staff members. Subjects with influenza-like symptoms who were diagnosed with swine flu at hospitals or clinics were defined as swine flu patients and asked to make a report using a standardized form.</p> <p>Results</p> <p>After the start of the pandemic, a total of 2002 patients (11.7%) were registered in the survey. These patients included 928 schoolchildren (40.0%), 1016 university students (8.9%), and 58 staff members (1.7%). The incidence in schoolchildren was significantly higher than in the other 2 groups (<it>P </it>< 0.0001) but there were no within group differences in incidence rate between males and females. During the period of the survey, three peaks of patient numbers were observed, in November 2009, December 2009, and January 2010. The first peak consisted mainly of schoolchildren, whereas the second and third peaks included many university students. Staff members did not contribute to peak formation. Among the university students, the most common suspected route of transmission was club activity. Interventions, such as closing classes, schools, and clubs, are likely to affect the epidemic curves.</p> <p>Conclusion</p> <p>Schoolchildren and university students are vulnerable to swine flu, suggesting that avoidance of close contact, especially among these young people, may be effective way in controlling future severe influenza pandemics, especially at educational institutions.</p

The challenges of modeling and forecasting the spread of COVID-19

The coronavirus disease 2019 (COVID-19) pandemic has placed epidemic modeling at the forefront of worldwide public policy making. Nonetheless, modeling and forecasting the spread of COVID-19 remains a challenge. Here, we detail three regional-scale models for forecasting and assessing the course of the pandemic. This work demonstrates the utility of parsimonious models for early-time data and provides an accessible framework for generating policy-relevant insights into its course. We show how these models can be connected to each other and to time series data for a particular region. Capable of measuring and forecasting the impacts of social distancing, these models highlight the dangers of relaxing nonpharmaceutical public health interventions in the absence of a vaccine or antiviral therapies

Would school closure for the 2009 H1N1 influenza epidemic have been worth the cost?: a computational simulation of Pennsylvania

<p>Abstract</p> <p>Background</p> <p>During the 2009 H1N1 influenza epidemic, policy makers debated over whether, when, and how long to close schools. While closing schools could have reduced influenza transmission thereby preventing cases, deaths, and health care costs, it may also have incurred substantial costs from increased childcare needs and lost productivity by teachers and other school employees.</p> <p>Methods</p> <p>A combination of agent-based and Monte Carlo economic simulation modeling was used to determine the cost-benefit of closing schools (vs. not closing schools) for different durations (range: 1 to 8 weeks) and symptomatic case incidence triggers (range: 1 to 30) for the state of Pennsylvania during the 2009 H1N1 epidemic. Different scenarios varied the basic reproductive rate (R₀) from 1.2, 1.6, to 2.0 and used case-hospitalization and case-fatality rates from the 2009 epidemic. Additional analyses determined the cost per influenza case averted of implementing school closure.</p> <p>Results</p> <p>For all scenarios explored, closing schools resulted in substantially higher net costs than not closing schools. For R₀= 1.2, 1.6, and 2.0 epidemics, closing schools for 8 weeks would have resulted in median net costs of $21.0 billion (95$8.0 - $45.3 billion). The median cost per influenza case averted would have been$14,185 ($5,423 -$30,565) for R₀= 1.2, $25,253 ($9,501 - $53,461) for R₀= 1.6, and$23,483 ($8,870 -$50,926) for R₀= 2.0.</p> <p>Conclusions</p> <p>Our study suggests that closing schools during the 2009 H1N1 epidemic could have resulted in substantial costs to society as the potential costs of lost productivity and childcare could have far outweighed the cost savings in preventing influenza cases.</p

Dynamics of multi-stage infections on networks

This paper investigates the dynamics of infectious diseases with a nonexponentially distributed infectious period. This is achieved by considering a multistage infection model on networks. Using pairwise approximation with a standard closure, a number of important characteristics of disease dynamics are derived analytically, including the final size of an epidemic and a threshold for epidemic outbreaks, and it is shown how these quantities depend on disease characteristics, as well as the number of disease stages. Stochastic simulations of dynamics on networks are performed and compared to output of pairwise models for several realistic examples of infectious diseases to illustrate the role played by the number of stages in the disease dynamics. These results show that a higher number of disease stages results in faster epidemic outbreaks with a higher peak prevalence and a larger final size of the epidemic. The agreement between the pairwise and simulation models is excellent in the cases we consider

Reconstruction of 60 Years of Chikungunya Epidemiology in the Philippines Demonstrates Episodic and Focal Transmission.

Proper understanding of the long-term epidemiology of chikungunya has been hampered by poor surveillance. Outbreak years are unpredictable and cases often misdiagnosed. Here we analyzed age-specific data from 2 serological studies (from 1973 and 2012) in Cebu, Philippines, to reconstruct both the annual probability of infection and population-level immunity over a 60-year period (1952-2012). We also explored whether seroconversions during 2012-2013 were spatially clustered. Our models identified 4 discrete outbreaks separated by an average delay of 17 years. On average, 23% (95% confidence interval [CI], 16%-37%) of the susceptible population was infected per outbreak, with >50% of the entire population remaining susceptible at any point. Participants who seroconverted during 2012-2013 were clustered at distances of 350 000 infections were missed by surveillance systems. Serological studies could supplement surveillance to provide important insights on pathogen circulation

Quantifying Type-Specific Reproduction Numbers for Nosocomial Pathogens: Evidence for Heightened Transmission of an Asian Sequence Type 239 MRSA Clone

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