Commentary
By Jia Kangbai, PV Special Correspondent,Cuttington University, Suakoko, Liberia.
Managers of both HIV infection and society increasingly need to know how social changes will affect HIV prevalence.
The biological mechanisms that link changing society to changing HIV prevalence through changes in HIV incidence and effects on demography are simple.
HIV spread has often been associated with poverty in a society , as well as level of education and disposable income.
Gathering sufficient data to build a detailed model to predict the impact of social changes on HIV prevalence is far from trivial as an HIV epidemiologist may not have the luxury of spending years collecting data, but a simple risk-assessment framework that can predict the impact of society changes on HIV prevalence is worthwhile.
Managing HIV incidence through manipulating social attitudes has recently become a focus for HIV prevention.
Global HIV infection is largely due to socioeconomic influences.
Thus a substantial proportion of global HIV infection is associated with social attitudes and given that economic status intensifies social behaviors, HIV incidence is under considerable threat because of the existing global economy.
During the 1980s and 1990s, a marked increase in HIV prevalence strongly associated with social attitudes created considerable alarm.
So great has been the public concern that governments have begun to channel resources into mitigating the negative influence of social attitudes on HIV/AIDS.
The importance of positive social intervention on HIV transmission is indicated in the drop of HIV cases in Senegal, Uganda and Thailand.
Also, given the way social behaviours change the infection rate (by both increasing HIV infection incidence and rate of transmission), and the impact of social changes on HIV prevalence, it is increasingly important to predict HIV prevalence’s response to social changes.
Predicting disease response to social changes is sometimes difficult because of inherently complex biology. Disease prevalence response also depends on a web of interactions within a community at different spatial scales.
Thus to construct a detailed mechanistic and cutting-edge model may take so long that it may not produce any answer. What is needed here is a simple approach that recognizes risk assessments of the effects social changes will have on HIV prevalence that is quick to implement, and that is spatially restricted, able to asses the impact of HIV prevalence in a multiracial setting, and usable where existing data may be insufficient in terms of quality and quantity.
Like any good ideas, this approach is elegantly simple: what will be the increase in HIV prevalence that will result to any given social change?
Human beings inhabite a community endgame in many social activities: commercial sex work, drinking alcohol, smoking, homosexuality, bisexuality etc. Typically we know enough about human biology to estimate whether a given social change will have a negative impact on HIV prevalence.
Human risk to HIV infection depends not only on the number of negative social changes but also on the ratio between those humans who are at high risk of infection and those that are at low risk of becoming infected with HIV; this can be easily being incorporated into a risk score by simple weighting factor.
Having developed a methodology, it is easy to see how two risk groups in a community will be affected by changes in social attitudes.
First the widespread engagement in unsafe sex behaviours will increase the risk for HIV infection in the non exposed group because of the increase in risky behaviours in the risk group population.
Secondly with increase in both risk groups in a community, the overall community HIV prevalence will thus increase.
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