Jessica Conrad Hammer, PhD, MSPH

Postdoctoral Researcher at Los Alamos National Laboratory

T-6 Theoretical Biology & Biophysics Group

drawing

About:

I am a mathematics, biostatistics, and public health professional who enjoys working on research teams to develop creative solutions, transforming how we analyze and view complex disease problems. I am fluent in LaTex, C++, Python, Matlab, R, and SAS coding. My passion is using deterministic and statistical modeling to interpret real world problems on a simpler theoretical basis.

Read my CV

Professional Organizations:

I am a proud member of the following organizations: Big Brothers Big Sisters Mountain Region, the Eta Chapter of the Delta Omega National Honorary Society in Public Health, the Tulane University Circle of Omicron Delta Kappa Honors Fraternity, and the American Society of Tropical Medicine & Hygiene (ASTMH).

Talks

2021

  • Lessons from Previous Epidemics: Understanding Space and Time, invited talk for AIM Student Seminars, University of Michigan, Ann Arbor, MI, September 17, 2021
  • Introduction to Disease Modeling, invited talk for AIM Student Seminars, University of Michigan, Ann Arbor, MI, October 30, 2020
  • Networks in Disease Modeling, informational talk for COMM 307: Social Networks, University of Michigan, Ann Arbor, MI, September 30, 2020

    2019

  • Mardi Gras in New Orleans, informational talk for Rotary Club of Los Alamos, Los Alamos, NM, March 5, 2019
  • Spatial Statistical Modeling Analysis of Incidence Correlated with Other Factors, given at New Orleans Workshop on Modeling the Spread of Infectious Diseases, Tulane University, New Orleans, LA, February 22, 2019

    2018

  • Dengue Modeling in Brazil, given at the Center for Nonlinear Studies (CNLS) at Los Alamos National Laboratory (LANL), Los Alamos, NM, August 20, 2018
  • Using Satellite Imagery and Internet Data for Dengue Surveillance in Brazil, given at 42nd Society of Industrial and Applied Mathematics: Southeastern Atlantic Sectional (SIAM-SEAS) Conference, Chapel Hill, North Carolina, March 10, 2018
  • Using Satellite Imagery and Internet Data for Dengue Surveillance in Brazil, given at 2017 American Geophysical Union (AGU) Fall Meeting, New Orleans, LA, December 11, 2017
  • Mathematical Analysis for a Model to Control Chagas Disease: Fighting as Infection with an Infection, given at 2017 American Society of Tropical Medicine and Hygiene (ASTMH) Annual Meeting , New Orleans, LA, December 11, 2017
  • Using Satellite Imagery and Internet Data for Dengue Surveillance in Brazil, given at ICMA VI: Sixth International Conference on Mathematical Modeling and Analysis of Populations in Biological Systems (ICMA-VI) Fall Meeting, New Orleans, LA, December 11, 2017
  • Three Examples of how Mathematical Models can Help Understand and Control the Spread of Infectious Diseases, given at the CNLS at LANL, Los Alamos, NM, August 17, 2017

    2016

  • Minimizing recidivism by optimizing profit: a theoretical case study of incentivized reform in a Louisiana prison, given at Applied Mathematics Seminar, Vassar College, NY, October 28, 2016
  • Minimizing recidivism by optimizing profit: a theoretical case study of incentivized reform in a Louisiana prison, given at private presentation for the Ministry of Eduacation, San Salvador, El Salvador, February 24, 2016
  • Minimizing recidivism by optimizing profit: a theoretical case study of incentivized reform in a Louisiana prison, given at El Primer Congreso Internacional de Modelaje Matematico, Simon A. Levin Mathematical, Computational, and Modeling Sciences Center, San Salvador, El Salvador, February 23, 2016
  • Minimizing recidivism by optimizing profit: a theoretical case study of incentivized reform in a Louisiana prison, given at 2015 Society of Advancement of Chicano/Hispanics and Native Americans in Science (SACNAS) National Conference, Washington D.C., October 30, 2015
  • Modeling the Impact of Behavior Change on the Spread of Ebola, given at 2015 Tulane University School of Science and Engineering (SSE) Research Day, New Orleans, LA, February 20, 2015
PDFs

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.
Code

Sample Python Lab

  • Introduction to Spatial SIR Modeling with Python here

MSRI Summer School 2022: Algebraic Geometry Labs

  • Day 1: Lecture Slides are here.
  • Lab 1: Parameter Estimation with Python here. Partial solutions here.

  • Day 2: Lecture Slides are here.
  • Lab 2: Numerical Identifiability with Python here. Partial solutions here.
video
Contact

Contact

  • Personal Email: jrconrad@umich.edu
  • Work Email: jconrad4@lanl.gov