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Articles 1 - 9 of 9
Full-Text Articles in Disease Modeling
A Likelihood Based Method For Real Time Estimation Of The Serial Interval And Reproductive Number Of An Epidemic, Laura Forsberg White, Marcello Pagano
A Likelihood Based Method For Real Time Estimation Of The Serial Interval And Reproductive Number Of An Epidemic, Laura Forsberg White, Marcello Pagano
Harvard University Biostatistics Working Paper Series
No abstract provided.
Spatio-Temporal Analysis Of Areal Data And Discovery Of Neighborhood Relationships In Conditionally Autoregressive Models, Subharup Guha, Louise Ryan
Spatio-Temporal Analysis Of Areal Data And Discovery Of Neighborhood Relationships In Conditionally Autoregressive Models, Subharup Guha, Louise Ryan
Harvard University Biostatistics Working Paper Series
No abstract provided.
A Comparative Analysis Of The Chronic Effects Of Fine Particulate Matter, Sorina E. Eftim, Holly Janes, Aidan Mcdermott, Jonathan M. Samet, Francesca Dominici
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 …
Hierarchical Models For Combining Ecological And Case-Control Data, Sebastien Haneuse, Jon Wakefield
Hierarchical Models For Combining Ecological And Case-Control Data, Sebastien Haneuse, Jon Wakefield
UW Biostatistics Working Paper Series
The ecological study design suffers from a broad range of biases that result from the loss of information regarding the joint distribution of individual-level outcomes, exposures and confounders. The consequent non-identifiability of individual-level models cannot be overcome without additional information; we combine ecological data with a sample of individual-level case-control data. The focus of this paper is hierarchical models to account for between-group heterogeneity. Estimation and inference pose serious compu- tational challenges. We present a Bayesian implementation, based on a data augmentation scheme where the unobserved data are treated as auxiliary variables. The methods are illustrated with a dataset of …
Disease Mapping And Spatial Regression With Count Data, Jon Wakefield
Disease Mapping And Spatial Regression With Count Data, Jon Wakefield
UW Biostatistics Working Paper Series
In this paper we provide critical reviews of methods suggested for the analysis of aggregate count data in the context of disease mapping and spatial regression. We introduce a new method for picking prior distributions, and propose a number of refinements of previously-used models. We also consider ecological bias, mutual standardization, and choice of both spatial model and prior specification. We analyze male lip cancer incidence data collected in Scotland over the period 1975–1980, and outline a number of problems with previous analyses of these data. A number of recommendations are provided. In disease mapping studies, hierarchical models can provide …
Bivariate Binomial Spatial Modelling Loa Loa Prevalence In Tropical Africa, Ciprian M. Crainiceanu, Peter J. Diggle, Barry Rowlingson
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 …
Different Public Health Interventions Have Varying Effects, Paula Diehr, Anne B. Newman, Liming Cai, Ann Derleth
Different Public Health Interventions Have Varying Effects, Paula Diehr, Anne B. Newman, Liming Cai, Ann Derleth
UW Biostatistics Working Paper Series
Objective: To compare performance of one-time health interventions to those that change the probability of transitioning from one health state to another. Study Design and Setting: We used multi-state life table methods to estimate the impact of eight types of interventions on several outcomes. Results: In a cohort beginning at age 65, curing all the sick persons at baseline would increase life expectancy by 0.23 years and increase years of healthy life by .54 years. An equal amount of improvement could be obtained with a 12% decrease in the probability of getting sick, a 16% increase in the probability of …
Regression Analysis For The Partial Area Under The Roc Curve, Tianxi Cai, Lori E. Dodd
Regression Analysis For The Partial Area Under The Roc Curve, Tianxi Cai, Lori E. Dodd
Harvard University Biostatistics Working Paper Series
No abstract provided.
Optimal Therapy Regimens For Treatment-Resistant Mutations Of Hiv, Weiqing Gu, Helen Moore
Optimal Therapy Regimens For Treatment-Resistant Mutations Of Hiv, Weiqing Gu, Helen Moore
All HMC Faculty Publications and Research
In this paper, we use control theory to determine optimal treatment regimens for HIV patients, taking into account treatment-resistant mutations of the virus. We perform optimal control analysis on a model developed previously for the dynamics of HIV with strains of various resistance to treatment (Moore and Gu, 2005). This model incorporates three types of resistance to treatments: strains that are not responsive to protease inhibitors, strains not responsive to reverse transcriptase inhibitors, and strains not responsive to either of these treatments. We solve for the optimal treatment regimens analytically and numerically. We find parameter regimes for which optimal dosing …