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Small area estimation of county-level U.S. HIV-prevalent cases
Sazid S Khan1, Alexander C McLain2, Bankole A Olatosi3
1Department of Epidemiology and Biostatistics, Department of Epidemiology, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina; South Carolina Department of Alcohol and Other Drug Abuse Services, Columbia, SC.
Small area estimation (SAE) revealed that most rural U.S. counties have low Human Immunodeficiency Virus (HIV) prevalence. However, the U.S. South and coastlines show higher HIV burden, requiring targeted interventions.
Area of Science:
- Epidemiology
- Biostatistics
- Public Health
Background:
- HIV epidemic is increasingly recognized beyond urban centers.
- Incomplete HIV data exists for many rural U.S. counties.
- Accurate HIV prevalence estimates are crucial for national assessment.
Purpose of the Study:
- To estimate Human Immunodeficiency Virus (HIV) prevalence in U.S. counties.
- To address data gaps in rural HIV surveillance.
- To provide a comprehensive national assessment of the HIV burden.
Main Methods:
- Employed small area estimation (SAE) modeling.
- Utilized Centers for Disease Control and Prevention (CDC) National HIV Surveillance System data.
- Incorporated auxiliary HIV risk-indicator data and geospatial information.
- Conducted cross-validation to assess estimate precision.
Main Results:
- Most unreported counties (677) exhibited low HIV prevalence (quintiles 1-2).
- The U.S. South displayed high HIV prevalence levels (quintiles 4-5).
- Cross-validation confirmed good model precision, with 42% of residuals within ±10 HIV cases.
Conclusions:
- HIV prevalence is highest along U.S. coastlines and in the Southern states.
- SAE modeling offers a more complete picture of national HIV burden.
- Identified communities needing future targeted HIV interventions.
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