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*Applications will be reviewed on a rolling-basis.

CDC Office and Location: A fellowship opportunity is available with the Division of HIV Prevention (DHP) of the National Center for HIV, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), at the Centers for Disease Control and Prevention (CDC) in Atlanta, Georgia. 

The Centers for Disease Control and Prevention (CDC) is one of the major operation components of the Department of Health and Human Services. CDC works to protect America from health, safety and security threats, both foreign and in the U.S. Whether diseases start at home or abroad, are chronic or acute, curable or preventable, human error or deliberate attack, CDC fights disease and supports communities and citizens to do the same.

Research Project: The fellow will have a number of opportunities to train and participate in the team’s modeling efforts. We anticipate that the fellow could complete one major project during a 12-month time frame. The Fellow will be involved in multi-disciplinary projects and collaborations with scientists across the division. Major modeling activities may include: development of policy- and program-relevant research questions, model refinement and extension, identification of appropriate data inputs, model calibration, uncertainty analyses, manuscript writing, and oral presentations.

Key models and functions performed by the Prevention Modeling and Economics Team include:

A dynamic compartmental model of HIV in the United States: The HIV Optimization and Prevention Economics (HOPE) Model

  • The model uses differential equations that are implemented and solved in MATLAB. These differential equations represent the transmission of HIV to susceptible individuals and the progression of infected individuals through the stages of HIV and along the steps of the HIV care continuum. The model considers HIV prevention interventions aimed at both HIV-uninfected and HIV-infected individuals. It includes risks from sexual and injection drug contacts.

An agent-based model characterizing HIV disease progression and transmission in the United States: Progression and Transmission of HIV (PATH)

  • This is an agent-based simulation model in NetLogo. HIV-infected persons are individually tracked from infection to death, and they progress through different stages of disease and steps of care and treatment. Uninfected persons are simulated as populations stratified by risk and gender. A Bernoulli process model is used to estimate HIV transmissions, and newly infected persons are added to the simulation for subsequent individual tracking.

Optimization of scarce resources to reduce HIV incidence

  • The HOPE model, described in A, includes a linear optimization component programmed in MATLAB. Currently, the optimization component is designed to allocate a budget over several interventions related to PrEP and the HIV care continuum, with the goal of preventing as many new cases of HIV as possible. The model also allows allocation among populations at risk for HIV. In addition, the team has developed an Excel-based resource allocation model for state and local health department use. It combines a linear programming model with a Bernoulli process model, using Visual Basic and Solver. It allows for local inputs for budget, epidemiology, program effects, and costs.

Learning Objectives

  • Apply modeling and decision analytic skills to HIV prevention
  • Understand how national HIV prevention recommendations are supported through quantitative evaluation of policy alternatives
  • Translate scientific findings and modeling results, so that they are transparent to decision makers
  • Increase understanding of costing procedures, specifically, and of economic evaluation generally, as they relate to HIV prevention
  • Identify methods for finding the best economic, behavioral, and epidemiological data to support economic evaluations of HIV prevention activities
  • Gain familiarity with the epidemiology of HIV in the United States
  • Understand strengths and weaknesses of various HIV prevention approaches
  • Improve skills in oral presentations and manuscript writing
  • Strengthen skills in collaborating within multi-disciplinary teams
Mentor(s): The mentor for this opportunity is Paul Farnham ( If you have questions about the nature of the research please contact the mentor(s).

Anticipated Appointment Start Date: As soon as a qualified candidate is identified.  Start date is flexible and will depend on a variety of factors.

Appointment Length: The appointment will initially be for one year, but may be renewed upon recommendation of CDC and is contingent on the availability of funds.

Level of Participation: The appointment is full-time.

Participant Stipend: The participant will receive a monthly stipend commensurate with educational level and experience.

Citizenship Requirements: This opportunity is available to U.S. citizens, Lawful Permanent Residents (LPR), and foreign nationals. Non-U.S. citizen applicants should refer to the Guidelines for Non-U.S. Citizens Details page of the program website for information about the valid immigration statuses that are acceptable for program participation.

ORISE Information: This program, administered by ORAU through its contract with the U.S. Department of Energy (DOE) to manage the Oak Ridge Institute for Science and Education (ORISE), was established through an interagency agreement between DOE and CDC. Participants do not become employees of CDC, DOE or the program administrator, and there are no employment-related benefits. Proof of health insurance is required for participation in this program. Health insurance can be obtained through ORISE.

The successful applicant(s) will be required to comply with Environmental, Safety and Health (ES&H) requirements of the hosting facility, including but not limited to, COVID-19 requirements (e.g. facial covering, physical distancing, testing, vaccination).

Questions: Please visit our Program Website. After reading, if you have additional questions about the application process please email and include the reference code for this opportunity.