2022

• A Process-Based Model with Temperature, Water, and Lab-derived Data Improves Predictions of Daily Mosquito Density
  • Shutt, D. P., Goodsman, D. W., Hemez, Z. J. L., Conrad, J. R., Xu, C., Osthus, D., Russel, C., Hyman, J. M., Manore, C. A. “A Process-Based Model with Temperature, Water, and Lab-derived Data Improves Predictions of Daily Mosquito Density.” (2021). Submitted to Journal of Medical Entomology.

    2021

• In Review.[EpiGrid: Consistent parameterization of three diseases using a single model]
  • Mourant, J. R., Wilding, K., Conrad, J. R., Miner, J. C., Atchley, A. L., Fenimore, P. W. “EpiGrid: Consistent parameterization of three diseases using a single model.” (2021) In Review with PLoS ONE.}

    2020

• Preprint.Unlocking the Predictive Power of Heterogeneous Data to Build an Operational Dengue Forecasting System
  • Manore, C., Fairchild, G., Ziemann, A., Parikh, N., Kempfert, K., Martinez, K., Castro, L., Osthus, D., Siraj, A., Conrad, J., Generous, N., Del Valle, S. “Unlocking the Predictive Power of Heterogeneous Data to Build an Operational Dengue Forecasting System.” (2020) Submitted to the Royal Society.

    2019

• Understanding polynomial distributed lag models: truncation lag implications for a mosquito-borne disease risk model in Brazil
  • Conrad, J., Ziemann, A., Refeld, R., Parikh, N., Siraj, A., Generous, N., Del Valle, S., Fairchild, G. and Manore, C. “Understanding polynomial distributed lag models: truncation lag implications for a mosquito-borne disease risk model in Brazil.” Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imagery XXV. International Society for Optics and Photonics, 2019. 109860N.

    2018

• Predicting dengue incidence in Brazil using broad-scale spectral remote sensing imagery
  • Ziemann, A., Fairchild, G., Conrad, J., Manore, C., Parikh, N., Del Valle, S., and Generous, N. “Predicting dengue incidence in Brazil using broad-scale spectral remote sensing imagery.” IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2018. 2076-2078
• Unpublished. Parameters Estimation, Identification and Uncertainty Quantification for Epidemic Models
  • Unofficial report on paramter estimation, identification, and uncertainty quantification for the Suscepitble-Infected-Susceptible (SIS) and Suscepitble-Exposed-Infected-Susceptible (SEIS) models.
  • Both noise free data and noisy data are used for fitting the model parameters. Parameter identifiability analysis, sensitivity analysis and parameter uncertainty quantification are included.
• Unpublished. Public Health Analysis: An Assessment of Polynomial Distributed Lag in Mosquito-Born Disease Risk Modeling
  • The Public health analysis for the Tulane University School of Public Health and Tropical Medicine integrates and applies public health knowledge and competencies acquired during coursework for MSPH Biostatistics.
  • Using data for Ceara, Brazil, we construct a polynomial distributed lag model under different truncation lag criteria to predict reported dengue cases. Accurately predicting dengue cases provides the framework to develop forecasting models, which would provide public health professionals time to create targeted interventions for areas at high risk of dengue outbreaks.

    2017

• Unpublished. Honors Thesis: Mathematical Analysis for a Model to Control Chagas Disease: Fighting as Infection with an Infection
  • Honors thesis for the Tulane University Department of Public Health and Department of Mathematics. This involved substantial independent research and study under the direction of professors in each of the respective departments.
  • We construct a two strain infection model for Trypanosoma cruzi and Trypanosoma rangeli host-vector dynamics to analyze the necessary initial conditions necessary for T. rangeli to outcompete T. cruzi in a given host-vector population. Introduction of T. rangeli into at risk populations can reduce the invasion rate of T. cruzi.

    2016

• Modeling the Impact of Behavior Change on the Spread of Ebola
  • Conrad, J. R., Xue, L., Dewar, J., & Hyman, J. M. “Modeling the Impact of Behavior Change on the Spread of Ebola.” Mathematical and Statistical Modeling for Emerging and Re-emerging Infectious Diseases. Springer, Cham, 2016. 5-23.

    2014

• Unpublished. The Louisiana Institute of Public Health Tobacco Free Living Campaign
  • Needs assessment project of bar owners in New Orleans done with the support of the Louisiana Public Health Institute (LPHI).
  • As a result of this research, in January 2015, the New Orleans City Council unanimously passed and Mayor Landrieu signed into law the Smoke-Free Ordinance. More information on this law can be found here. More information on the Tobacco Free Living Campaign can be found here.