Assessing the economic impact of HIV/AIDS on Nigerian households: a propensity score matching approach.
OBJECTIVE
We used a novel approach to assess the impact of HIV/AIDS on individuals' healthcare utilization and spending in the Oyo and Plateau states of Nigeria and income foregone from work time lost.


METHODS
Data from a 2004 random survey of over 6400 individuals were compared with a sample of 482 individuals living with HIV/AIDS. Estimating the effect of HIV is complicated by the fact that our sample of HIV-positive individuals was non-random; there are selection effects, both in acquiring HIV and being in our sample of HIV-positive people, which was based on contacts through non-governmental organizations. To overcome these, we compared HIV-positive people with a control group with similar observed characteristics, using propensity score matching. The matched HIV-negative individuals had worse health and greater health spending than the full HIV-negative group. This suggests that our HIV sample would not have had 'average' outcomes even if they had not acquired HIV.


RESULTS
Compared with our matched control group, HIV is associated with significantly increased morbidity, healthcare utilization, public health facility use, lost work time and family time devoted to care-giving. Direct private healthcare costs and indirect income loss per HIV-positive individual were 36 065 Naira, approximately 56% of annual income per capita in affected households. Approximately 40% of these costs were income losses associated with sickness and care-giving. 10% of the cost of HIV is accounted for by public subsidies for health. The largest single cost, representing 54% of the total economic burden of HIV, is for out-of-pocket expenses for healthcare.
Mahal
Ajay
A
Harvard School of Public Health, Department of Population and International Health, Boston, Massachusetts, USA. amahal@hsph.harvard.edu
Canning
David
D
Odumosu
Kunle
K
Okonkwo
Prosper
P
D000163:Acquired Immunodeficiency Syndrome / Q000191:economics; D000328:Adult; D017028:Caregivers / Q000191:economics; D016022:Case-Control Studies; D017281:Cost of Illness; D003625:Data Collection / Q000379:methods; D003906:Developing Countries; D005191:Family Characteristics; D005260:Female; D015658:HIV Infections / Q000191:economics*; D006760:Hospitalization; D006801:Humans; D016015:Logistic Models; D008297:Male; D009017:Morbidity; D009549:Nigeria; D010342:Patient Acceptance of Health Care; D015983:Selection Bias; D012959:Socioeconomic Factors