Disease Modeling Commons^™

Forecasting The Global Burden Of Alzheimer's Disease, Ron Brookmeyer, Elizabeth Johnson, Kathryn Ziegler-Graham, H. Michael Arrighi

Johns Hopkins University, Dept. of Biostatistics Working Papers

Background: The goal was to forecast the global burden of Alzheimer’s disease and evaluate the potential impact of interventions that delay disease onset or progression. Methods: A stochastic multi-state model was used in conjunction with U.N. worldwide population forecasts and data from epidemiological studies on risks of Alzheimer’s disease.

Findings: In 2006 the worldwide prevalence of Alzheimer’s disease was 26.6 million. By 2050, prevalence will quadruple by which time 1 in 85 persons worldwide will be living with the disease. We estimate about 43% of prevalent cases need a high level of care equivalent to that of a nursing home. …

A Comparative Analysis Of The Chronic Effects Of Fine Particulate Matter, Sorina E. Eftim, Holly Janes, Aidan Mcdermott, Jonathan M. Samet, Francesca Dominici

Johns Hopkins University, Dept. of Biostatistics Working Papers

The American Cancer Society study (ACS) and the Harvard Six Cities study (SCS) are the two landmark cohort studies for estimating the chronic effects of fine particulate matter PM2.5 on mortality. To date, no comparative analysis of these studies has been carried out using a different study design, study period, data, and modeling approach. In this paper, we estimate the chronic effects of PM on mortality for the period 2000-2002 by using mortality data from Medicare and \PM levels from the National Air Pollution Monitoring Network for the same counties included in the SCS and the ACS. We use a …

Bivariate Binomial Spatial Modelling Loa Loa Prevalence In Tropical Africa, Ciprian M. Crainiceanu, Peter J. Diggle, Barry Rowlingson

Johns Hopkins University, Dept. of Biostatistics Working Papers

We present a state-of-the-art application of smoothing for dependent bivariate binomial spatial data to Loa loa prevalence mapping in West Africa. This application is special because it starts with the non-spatial calibration of survey instruments, continues with the spatial model building and assessment and ends with robust, tested software that will be used by the field scientists of the World Health Organization for online prevalence map updating. From a statistical perspective several important methodological issues were addressed: (a) building spatial models that are complex enough to capture the structure of the data but remain computationally usable; (b)reducing the computational burden …

Bayesian Hierarchical Distributed Lag Models For Summer Ozone Exposure And Cardio-Respiratory Mortality, Yi Huang, Francesca Dominici, Michelle L. Bell

Johns Hopkins University, Dept. of Biostatistics Working Papers

In this paper, we develop Bayesian hierarchical distributed lag models for estimating associations between daily variations in summer ozone levels and daily variations in cardiovascular and respiratory (CVDRESP) mortality counts for 19 U.S. large cities included in the National Morbidity Mortality Air Pollution Study (NMMAPS) for the period 1987 - 1994.

At the first stage, we define a semi-parametric distributed lag Poisson regression model to estimate city-specific relative rates of CVDRESP associated with short-term exposure to summer ozone. At the second stage, we specify a class of distributions for the true city-specific relative rates to estimate an overall effect by …

A Hypothesis Test For The End Of A Common Source Outbreak, Ron Brookmeyer, Xiaojun You

Johns Hopkins University, Dept. of Biostatistics Working Papers

The objective of this paper is to develop a hypothesis testing procedure to determine whether a common source outbreak has ended. We do not assume that the calendar date of exposure to the pathogen is known. We assume an underlying parametric model for the incubation period distribution of a 2-paramter exponential model with a guarantee time, although the parameters are not assumed to be known. The hypothesis testing procedure is based on the spacings between ordered calendar dates of disease onset of the cases. A simulation study was performed to evaluate the robustness of the methods to a lognormal model …

Effect Of Misreported Family History On Mendelian Mutation Prediction Models, Hormuzd A. Katki

Johns Hopkins University, Dept. of Biostatistics Working Papers

People with familial history of disease often consult with genetic counselors about their chance of carrying mutations that increase disease risk. To aid them, genetic counselors use Mendelian models that predict whether the person carries deleterious mutations based on their reported family history. Such models rely on accurate reporting of each member's diagnosis and age of diagnosis, but this information may be inaccurate. Commonly encountered errors in family history can significantly distort predictions, and thus can alter the clinical management of people undergoing counseling, screening, or genetic testing. We derive general results about the distortion in the carrier probability estimate …

Optimization Of Breast Cancer Screening Modalities, Yu Shen, Giovanni Parmigiani

Johns Hopkins University, Dept. of Biostatistics Working Papers

Mathematical models and decision analyses based on microsimulations have been shown to be useful in evaluating relative merits of various screening strategies in terms of cost and mortality reduction. Most investigations regarding the balance between mortality reduction and costs have focused on a single modality, mammography. A systematic evaluation of the relative expenses and projected benefit of combining clinical breast examination and mammography is not at present available. The purpose of this report is to provide methodologic details including assumptions and data used in the process of modeling for complex decision analyses, when searching for optimal breast cancer screening strategies …

Modeling The Incubation Period Of Anthrax, Ron Brookmeyer, Elizabeth Johnson, Sarah Barry

Johns Hopkins University, Dept. of Biostatistics Working Papers

Models of the incubation period of anthrax are important to public health planners because they can be used to predict the delay before outbreaks are detected, the size of an outbreak and the duration of time that persons should remain on antibiotics to prevent disease. The difficulty is that there is little direct data about the incubation period in humans. The objective of this paper is to develop and apply models for the incubation period of anthrax. Mechanistic models that account for the biology of spore clearance and germination are developed based on a competing risks formulation. The models predict …

Cross-Calibration Of Stroke Disability Measures: Bayesian Analysis Of Longitudinal Ordinal Categorical Data Using Negative Dependence, Giovanni Parmigiani, Heidi W. Ashih, Gregory P. Samsa, Pamela W. Duncan, Sue Min Lai, David B. Matchar

Johns Hopkins University, Dept. of Biostatistics Working Papers

It is common to assess disability of stroke patients using standardized scales, such as the Rankin Stroke Outcome Scale (RS) and the Barthel Index (BI). The Rankin Scale, which was designed for applications to stroke, is based on assessing directly the global conditions of a patient. The Barthel Index, which was designed for general applications, is based on a series of questions about the patient’s ability to carry out 10 basis activities of daily living. As both scales are commonly used, but few studies use both, translating between scales is important in gaining an overall understanding of the efficacy of …