Adjusting ante-natal clinic data for improved estimates of HIV prevalence among women in sub-Saharan Africa.
OBJECTIVE
To find a simple and robust method for adjusting ante-natal clinic data on HIV prevalence to represent prevalence in the general female population in the same age range, allowing for fertility differences by HIV status.


BACKGROUND
HIV prevalence comparisons for pregnant women and women in the general community show that prevalence in the latter is significantly higher than in the former. An adjustment procedure is needed that is specific for the demographic and epidemiological circumstances of a particular population, making maximum use of data that can easily be collected in ante-natal clinics or are widely available from secondary sources.


METHODS
Birth interval length data are used to allow for subfertility among HIV-positive women. To allow for infertility, relative HIV prevalence ratios for fertile and infertile women obtained in community surveys in populations with similar levels of contraception use are applied to demographic survey data that describe the structure of the population not at risk of child-bearing.


RESULTS
For populations with low contraception use, the procedure yields estimates of general female HIV prevalence of 35-65% higher than the observed ante-natal prevalence, depending on population structure. Results were verified using general population prevalence data collected in Kisesa (Tanzania) and Masaka (Uganda). For high contraception use populations, adjusted values range from 15% higher to 5% lower, but only limited verification has been possible so far.


CONCLUSIONS
The procedure is suitable for estimating general female HIV prevalence in low contraception use populations, but the high contraception variant needs further testing before it can be applied widely.
Zaba
B W
BW
Centre for Population Studies, London School of Hygiene and Tropical Medicine, UK.
Carpenter
L M
LM
Boerma
J T
JT
Gregson
S
S
Nakiyingi
J
J
Urassa
M
M
D000293:Adolescent; D000328:Adult; D015982:Bias; D003267:Contraception / Q000706:statistics & numerical data; D003625:Data Collection; D003710:Demography; D005260:Female; D005298:Fertility; D015658:HIV Infections / Q000150:complications / Q000453:epidemiology*; D006801:Humans; D007246:Infertility / Q000150:complications; D008427:Maternal Health Services; D008954:Models, Biological; D009035:Mothers; D011159:Population Surveillance / Q000379:methods*; D011247:Pregnancy; D015995:Prevalence; D015203:Reproducibility of Results; D012307:Risk Factors; D013636:Tanzania / Q000453:epidemiology; D014454:Uganda / Q000453:epidemiology