Mathematical models will be developed for disease control through contact investigation, using individual- based simulations. Realistic contact investigation strategies will be analyzed for pathogens that may be transmissible from asymptomatic carriers as well as transmitted prior to symptoms. It will be determined how extensive or how targeted contact investigation should be, and what information should be systematically collected in future contact investigations. The models also include specific questions regarding the effect of behavior change during a contact investigation. Such models will be applied to tuberculosis transmission (because of the availability of contact investigation expertise and the availability of molecular epidemiogical data at the population level). Such models will also be applied in the setting of community-based trials of trachoma elimination, because such trials provide possibly the only experimental human settings wherein we may monitor the reemergence of an infectious disease. Specific testable predictions are outlined in the proposal.
Our project is designed to improve planning for decision making and emergency preparedness by developing specific operational models to explore the best way to control epidemics using contact investigation (or related methods, including ring vaccination), and to improve data collection during contact investigations. We are proposing to use tuberculosis and trachoma in developing empirical case studies.
| Lietman, Thomas M; Worden, Lee; Liu, Fengchen et al. (2018) The distribution of district-level leprosy incidence in India is geometric-stable, consistent with subcriticality. Epidemics 24:21-25 |
| Ramirez, David A; Porco, Travis C; Lietman, Thomas M et al. (2018) Ocular Injury in United States Emergency Departments: Seasonality and Annual Trends Estimated from a Nationally Representative Dataset. Am J Ophthalmol 191:149-155 |
| Grantz, Kyra H; Chabaari, Winnie; Samuel, Ramolotja Kagiso et al. (2018) Spatial distribution of leprosy in India: an ecological study. Infect Dis Poverty 7:20 |
| Ackley, Sarah F; Hacker, Jill K; Enanoria, Wayne T A et al. (2018) Genotype-Specific Measles Transmissibility: A Branching Process Analysis. Clin Infect Dis 66:1270-1275 |
| Pinsent, Amy; Liu, Fengchen; Deiner, Michael et al. (2017) Probabilistic forecasts of trachoma transmission at the district level: A statistical model comparison. Epidemics 18:48-55 |
| Deiner, Michael S; Fathy, Cherie; Kim, Jessica et al. (2017) Facebook and Twitter vaccine sentiment in response to measles outbreaks. Health Informatics J :1460458217740723 |
| Worden, Lee; Porco, Travis C (2017) Products of Compartmental Models in Epidemiology. Comput Math Methods Med 2017:8613878 |
| Deiner, Michael S; Lietman, Thomas M; Porco, Travis C (2017) Uncertainties in Big Data When Using Internet Surveillance Tools and Social Media for Determining Patterns in Disease Incidence-Reply. JAMA Ophthalmol 135:402-403 |
| Worden, Lee; Schwartz, Ira B; Bianco, Simone et al. (2017) Hamiltonian Analysis of Subcritical Stochastic Epidemic Dynamics. Comput Math Methods Med 2017:4253167 |
| Gao, Daozhou; Lietman, Thomas M; Dong, Chao-Ping et al. (2017) Mass drug administration: the importance of synchrony. Math Med Biol 34:241-260 |
Showing the most recent 10 out of 51 publications
