Evaluating social protection mitigation effects on HIV/AIDS and Tuberculosis through a mathematical modelling study

Area of Science:

• Epidemiology
• Mathematical Modeling
• Public Health Policy

Background:

• Global economic downturns, including the COVID-19 pandemic and inflation, disproportionately affect low- and middle-income countries (LMICs).
• Poverty is a significant driver of infectious diseases such as HIV/AIDS and Tuberculosis (TB).
• Brazil, a large and unequal LMIC, faces substantial risks to public health due to economic instability.

Purpose of the Study:

• To develop mathematical models for HIV/AIDS and TB in Brazil.
• To forecast the impact of increased poverty on disease incidence and mortality up to 2030.
• To evaluate the effectiveness of poverty-reduction policies in mitigating these impacts.

Main Methods:

• Integrated economic forecasting with mathematical and epidemiological modeling.
• Simulated three intervention scenarios: economic crisis with no, moderate, or strong social protection.
• Analyzed projected incidence and mortality rates for HIV/AIDS and TB.

Main Results:

• Without social protection, HIV/AIDS incidence and mortality could rise by 13% and 21% respectively by 2030.
• Without social protection, TB incidence and mortality could increase by 16% and 22% respectively by 2030, compared to moderate protection.
• Strong social protection could avert over 230,000 cases and 34,000 deaths from AIDS and TB in Brazil over the next decade.

Conclusions:

• Robust social protection policies are essential to counteract the rise in HIV/AIDS and TB during economic downturns.
• Mathematical modeling provides a critical tool for forecasting disease burden and policy impact.
• Addressing poverty is key to controlling infectious diseases in LMICs amidst global economic challenges.