Discrete time modelling of disease incidence time series by using Markov chain Monte Carlo methods

Summary.  A stochastic discrete time version of the susceptible–infected–recovered model for infectious diseases is developed. Disease is transmitted within and between communities when infected and susceptible individuals interact. Markov chain Monte Carlo methods are used to make inference about these unobserved populations and the unknown parameters of interest. The algorithm is designed specifically for modelling time series of reported measles cases although it can be adapted for other infectious diseases with permanent immunity. The application to observed measles incidence series motivates extensions to incorporate age structure as well as spatial epidemic coupling between communities.     

Incorporating Time‐Dose‐Response into Legionella Outbreak Models

A novel method was used to incorporate in vivo host–pathogen dynamics into a new robust outbreak model for legionellosis. Dose‐response and time‐dose‐response (TDR) models were generated for Legionella longbeachae exposure to mice via the intratracheal route using a maximum likelihood estimation approach. The best‐fit TDR model was then incorporated into two L. pneumophila outbreak models: an outbreak that occurred at a spa in Japan, and one that occurred in a Melbourne aquarium. The best‐fit TDR from the murine dosing study was the beta‐Poisson with exponential‐reciprocal dependency model, which had a minimized deviance of 32.9. This model was tested against other incubation distributions in the Japan outbreak, and performed consistently well, with reported deviances ranging from 32 to 35. In the case of the Melbourne outbreak, the exponential model with exponential dependency was tested against non‐time‐dependent distributions to explore the performance of the time‐dependent model with the lowest number of parameters. This model reported low minimized deviances around 8 for the Weibull, gamma, and lognormal exposure distribution cases. This work shows that the incorporation of a time factor into outbreak distributions provides models with acceptable fits that can provide insight into the in vivo dynamics of the host‐pathogen system.     

College students with congenital heart disease: A critical time for transition

As medical and surgical advances improve, more young adults with congenital heart disease (CHD) are attending college. This case study illustrates some of the issues that these young adults may face as they attend college and discusses the role that college health practitioners can play in easing that transition. Participants: A case of a male with CHD presenting to the college health clinic with a new onset headache. Methods: The authors discuss some of the unique challenges that college health practitioners may face when caring for students with CHD. In addition, they make recommendations on how best to care for these patients and how best to coordinate care with CHD students other care providers. Results: This student with a history of coarctation of the aorta presented with new onset headaches and was found to have high blood pressure. He was diagnosed with recurrent coarctation, underwent percutaneous treatment with stenting and quickly resumed classes. Conclusions: As more students with CHD enter college, college health providers will need to understand some of the health risks that CHD students face. In addition, understanding some of the optimal ways to coordinate care with CHD providers can ease the transition that CHD students face as they enter college.     

Predicting Future Commitment to Care for Frail Parents Among Employed Caregivers

A study of 133 full time employees with parent care responsibilities investigated various factors that could reduce this group's future caregiving commitment to aging parents. Study factors included: caregiver attributes, level of caregiving involvement, job stress, tensions between the caregiver and the dependent parent, caregiver's level of physical and mental strain, and limited support from family and friends. The relationship between the caregiver and the parent was the best predictor of sustained commitment to caregiving. One aspect of the employees' work experience made a small, but important contribution to respondents' future care plans. Those employees who frequently adjusted their work schedule and routine to accommodate parent care demands were less likely to sustain their caregiving commitment. Reasons for these findings are explored and implications for social policy and clinical practice are discussed.     

Machine Learning for Drug Overdose Surveillance

ABSTRACT

We describe two recently proposed machine learning approaches for discovering emerging trends in fatal accidental drug overdoses. The Gaussian Process Subset Scan (Herlands, McFowland, Wilson, & Neill, 2017 Neill, D. B. (2017). Multidimensional tensor scan for drug overdose surveillance. Journal of Public Health Informatics, 9(1), e20. doi:10.5210/ojphi.v9i1.7598[Crossref] , [Google Scholar]) enables early detection of emerging patterns in spatio-temporal data, accounting for both the complex, correlated nature of the data and the fact that detecting subtle patterns requires integration of information across multiple spatial areas and multiple time steps. We apply this approach to 17 years of county-aggregated data for monthly opioid overdose deaths in the New York City metropolitan area, showing clear advantages in the utility of discovered patterns as compared to typical anomaly detection approaches. To detect and characterize emerging overdose patterns that differentially affect a subpopulation of the data, including geographic, demographic, and behavioral patterns (e.g., which combinations of drugs are involved), we apply the Multidimensional Tensor Scan (Neill, 2017 Neill, D. B. (2017). Multidimensional tensor scan for drug overdose surveillance. Journal of Public Health Informatics, 9(1), e20. doi:10.5210/ojphi.v9i1.7598[Crossref] , [Google Scholar]) to 8 years of case-level overdose data from Allegheny County, Pennsylvania. We discover previously unidentified overdose patterns which reveal unusual demographic clusters, show impacts of drug legislation, and demonstrate potential for early detection and targeted intervention. These approaches to early detection of overdose patterns can inform prevention and response efforts, as well as understanding the effects of policy changes.     

Modeling the impact of supra-structural network nodes: The case of anonymous syringe sharing and HIV among people who inject drugs

Networks are well understood as crucial to the diffusion of HIV among injection drug users (IDUs), but quasi-anonymous risk nodes - such as shooting galleries - resist measurement and incorporation into empirical analyses of disease diffusion. Drawing on network data from 767 IDUs in Bushwick, Brooklyn, we illustrate the use of calibrated agent-based models (CABMs) to account for network structure, injection practices, and quasi-anonymous transmission in shooting galleries. Results confirm the importance of network structure and actor heterogeneity to the magnitude and speed of HIV transmission. Models further demonstrate that quasi-anonymous injections in shooting galleries increase the speed of HIV diffusion across the whole network and have the greatest impact on HIV seroconversion levels for IDUs at the network periphery. Shooting galleries are shown to be transmission hubs that operate independently of traceable structural ties, linking otherwise unconnected network components. CABMs potentially increase understandings of HIV diffusion dynamics by infusing computer simulations with empirical data.     

疾病、文化抑或其他?——同性恋研究的人类学视角

客观存在的同性恋群体长期以来属于人类学研究的禁区,其承受的污名和歧视使触碰这一领域的学者规模和作品数量相对稀少,这种情况在中国人类学界尤为明显。从学科认识论来看,同性恋研究经历了"性逆转"、"性倒错"的医学范式;异性恋框架主导的文化影响模式;建构学派的历史、政治、经济视角批判;以及酷儿理论的全盘颠覆和开放式探索。     

Malaria in Pacific populations: seen but not heard?

Most Pacific Island countries are located in the tropics, where there is an abundance of mosquitoes with the potential to carry debilitating or life-threatening vector-borne diseases. This article examines three Melanesian countries in which malaria is endemic—Papua New Guinea, Solomon Islands and Vanuatu—but the threat posed by the spread of malaria gives the issues a broader significance to the Pacific region. After discussing the spatial distribution and prevalence of malaria in the Pacific, the article examines a number of health interventions through which people have sought to control malaria. Although the disease was nearly eradicated in the Pacific in the 1970s, it is no longer in retreat. The article concludes by examining why there are still grounds for cautious optimism, and the challenges that Pacific Island countries face in reducing the impact of malaria on their populations. There is a need for prompt and concerted action on malaria at the national, regional and international levels if the public health concerns arising from the disease are to be adequately addressed.     

Bayesian parameter inference for stochastic SIR epidemic model with hyperbolic diffusion

This paper is concerned with the Bayesian estimation parameters of the stochastic SIR (Susceptible-Infective-Removed) epidemic model from the trajectory data. Specifically, the data from the count of both infectives and susceptibles is assumed to be available on some time grid as the epidemic progresses. The diffusion approximation of the appropriate jump process is then used to estimate missing data between every pair of observation times. If the time step of imputations is small enough, we derive the posterior distributions of the infection and recovery rates using the Milstein scheme. The paper also presents Markov-chain Monte Carlo (MCMC) simulation that demonstrates that the method provides accurate estimates, as illustrated by the synthetic data from SIR epidemic model and the real data.     

自然资源丰裕与产业结构扭曲:影响机制与多维测度

本文从资源丰裕度和资源依赖度两个方面,分析了自然资源对产业结构合理化、多元化和高级化的影响。研究表明,资源丰裕度的增加提高了产业结构的合理化,阻碍了产业结构的多元化,但对产业结构高级化没有显著影响;资源依赖度的增加不仅降低了产业结构的合理化,而且阻碍了产业结构的多元化和高级化,使产业结构处于扭曲状态。因此本文认为,"资源诅咒"主要是通过资源依赖来传导,而并非资源丰裕。