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Epidemiological Analysis & Public Health Research

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Federal

Contract Overview

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This subcontract, titled Epidemiological Analysis and Public Health Research, supports prime contractors on CDC DNPAO projects through the Department of Health and Human Services. The scope of work involves performing advanced epidemiological analyses and public health research, specifically focusing on maternal-child nutrition. Key responsibilities include downloading and formatting surveillance data from sources such as NHANES, NHIS, BRFSS, YRBS, and NSCH, as well as designing hypothesis tests using regression models, conducting microsimulation modeling, and performing systematic reviews. The successful provider must demonstrate proficiency in R and Python to deliver critical outputs, including data tables, scientific manuscripts, and surveillance reports. The work is based in Atlanta and falls under NAICS code 541715. Interested parties should note the response deadline of November 10, 2026.

General Info

Epidemiological research on maternal-child nutrition for CDC projects using R and Python.

NAICS

541715 - Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)

Place of Performance

Atlanta, GA, USA

Set-Aside

NONE

Documents

This scope was carved out of CDC_DNPAO_Epi_Surveillance.

The full solicitation package (2 documents), including the RFP, is on the prime solicitation, not on this scope.

View the prime solicitation

CDC Advancing Nutrition, Physical Activity, and Obesity and Chronic Disease Prevention through Epidemiology, Surveillance and Data Modernization

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Timeline

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Organization & Contact Information

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AgencyDepartment Of Health And Human Services → CDC Office Of Acquisition Services
ContactsNo contacts available
OfficeN/A
Office AddressN/A
ContactsNo contact information available

Full Description

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Performs advanced epidemiological analyses and public health research for prime contractors on CDC DNPAO projects. Downloads and formats surveillance data from NHANES, NHIS, BRFSS, YRBS, and NSCH; designs hypothesis tests using regression models; and conducts microsimulation modeling and systematic reviews. Requires proficiency in R and Python and expertise in maternal-child nutrition. Delivers data tables, scientific manuscripts, and surveillance reports.

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