Optimizing health resource allocation for improving timely HIV diagnosis in China

Area of Science:

• Epidemiology
• Public Health
• Mathematical Modeling

Background:

• The Joint United Nations Programme on HIV/AIDS (UNAIDS) has set 95-95-95 targets for the HIV endgame by 2030.
• Timely HIV diagnosis is crucial for achieving these targets and controlling the epidemic.

Purpose of the Study:

• To investigate optimized resource allocation strategies for HIV testing in China.
• To maximize timely HIV diagnoses across 14 diverse populations.

Main Methods:

• Developed a mathematical model integrating epidemiological, demographic, and behavioral data.
• Evaluated various HIV testing resource allocation strategies.
• Identified an optimized allocation to maximize diagnoses within a fixed budget.

Main Results:

• An initial allocation strategy resulted in 45.5% timely diagnosis and a cost of $42,852 per case.
• Optimized allocation, prioritizing general females and men who have sex with men, increased timely diagnosis to 83.4% ($23,364/case).
• This strategy significantly reduced spending on general males while increasing testing in other key groups.

Conclusions:

• Optimizing HIV testing resource allocation is essential for improving timely diagnosis rates.
• Strategic reallocation can substantially reduce the cost per HIV case detected.
• Further investment can enhance testing coverage in lower-risk populations.