Geographic and temporal stability of HIV seroprevalence among pregnant women in Bujumbura, Burundi.

OBJECTIVE: To establish whether HIV seroprevalence in Bujumbura is stable or continuing to increase. METHODS: HIV seroprevalence data among pregnant women from 1986 were compared with comparable data from 1991-1992. RESULTS: HIV seroprevalence among antenatal clinic attendees at three sites was 10.5, 28.0 and 11.9% in 1986, compared with 7.7, 25.6 and 12.4%, respectively, in 1991-1992. A weighted least squares analysis showed significant differences in HIV seroprevalence between the different sites (chi 2, 71.71; P > 0.0001), but no evidence of any differences between the 1986 and the 1991-1992 prevalence levels (chi 2, 0.51; P = 0.6). CONCLUSIONS: Bujumbura appears to be in the endemic phase of the spread of HIV. The stable geographic variation among clinic populations in Bujumbura suggests the need for focused interventions, and a general need for surveillance data to be gathered from numerous sites so to identify those with the highest incidence of HIV infection.

PIP: The authors compared HIV seroprevalence data among pregnant women from 1986 with comparable data from 1991-92 to establish whether HIV seroprevalence in Bujumbura is stable or continuing to increase. They found HIV seroprevalence among antenatal clinic attendees at 3 sites to be 10.5%, 28.9%, and 11.9% in 1986, compared with 7.7%, 25.6%, and 12.4%, respectively, in 1991-92. Significant differences were found between the different sites in HIV seroprevalence, but not between the 1986 and 1991-92 prevalence levels. HIV therefore appears to be endemic in Bujumbura. The stable geographic variation among clinic populations suggests the need for and appropriateness of focused interventions, as well as a general need for surveillance data to be gathered from numerous sites in order to identify those with the highest incidence of HIV infection.

Systematic restaining of sputum smears for quality control is useful in Burundi.

SETTING: Routine tuberculosis control services in Burundi. OBJECTIVE: To determine whether systematic restaining of sputum smears for acid-fast bacilli (AFB) prior to rechecking quality assessment is necessary. DESIGN: Blinded rechecking of peripheral routine smears, including a second control of discordants, before and after restaining. RESULTS: Without restaining, 10/825 (1.2%) negative, and 59/189 (31.2%) positive results were declared false. After restaining, there were 34 (4.1%) false negatives and 13 (6.9%) false positives, both highly significant changes. Before restaining, quantification of positive smears was usually considered too high, while after restaining 41 out of 42 positives were found to have too low readings. CONCLUSIONS: Despite mild climatic conditions in Burundi, restaining all slides before rechecking revealed an unrecognised, widespread problem of false negatives, rather than false positives. This indicated the need for critical re-appraisal of the standard procedure using cold staining, rather than re-training, as would have been inferred from results without restaining. Systematic restaining of all slides prior to rechecking may be more widely needed in National Tuberculosis Programmes to cover all possible serious causes of error. Cold staining should be avoided in field programmes since its performance is easily affected by frequently encountered adverse factors.

[The prevalence of HIV and risk behavior of prostitutes living in 2 populous regions of Bujumbura (Burundi)]. / Prévalence du VIH et comportements à risque chez les prostituées vivant dans deux quartiers populeux de Bujumbura (Burundi).

This study was designed to determine the prevalence of HIV infection and associated high-risk behavior in female sex workers in two areas of Bujumbura (Bwiza and Musanga), Burundi. Between June 15th and July 15th 1993, 320 female sex workers responded to an anonymous questionnaire and gave a blood sample on filter paper for detection of HIV antibodies. The mean age of the prostitutes was 24.6 (+/- 5.9) years (range 15 to 46). The HIV infection rate was 42.2% (135 of the 320). Univariate analysis showed that the proportion of HIV-infected female sex workers was higher in the Musaga area than in Bwiza (48.3% versus 34.3%; p = 0.012). The prevalence of HIV infection increased with age (24.3% for those aged between 15 and 19; 40.8% for those aged between 20 and 24 and more than 51.4% infected in the over 25 age-group; p < 0.001). The median number of sexual partners in the preceding month was 3 (range 1 to 50) and was not correlated with HIV infection (Wilcoxon's test: p = 0.516). HIV infection was highly correlated with a previous history of STDs (62.7% versus 32.7%; p < 0.001) and was also correlated with STD symptoms (87.5% versus 51.7%; p = 0.01). The only factors correlated with HIV infection in multivariate analysis were age (p = 0.008; Trend's test) and previous history of STDs (p < 0.001). Only 40.2% (127 of 316) of the female sex workers had used condoms with their clients during the preceding month. Intervention strategies to combat HIV transmission among individuals with high levels of sexual activity in Burundi should focus on the female sex workers and their clients, particularly the manual laborers, drivers, soldiers, prisoners and other men who regularly use prostitutes. The prevention of HIV infection in individuals of high-risk groups is the best strategy to reduce HIV transmission in the general population of developing countries.

Validation of a method to estimate age-specific human immunodeficiency virus (HIV) incidence rates in developing countries using population-based seroprevalence data.

The authors have conducted an analysis to validate a computer model that uses age-specific human immunodeficiency virus (HIV) prevalence data to estimate age-specific HIV incidence rates. Data for the analysis are from a cohort study of volunteer male workers in Bujumbura, the capital city of Burundi. Testing for HIV prevalence was conducted at baseline, and HIV-negative subjects were retested annually from 1990 to 1993 to determine rates of seroconversion. Input parameters required for the model include age-specific HIV prevalence and estimates of age-specific mortality rates for HIV-negative and HIV-positive subjects. Incidence rate estimates from the model were 2.0, 2.7, 1.0, 1.5, and 1.8 per 100 person-years for age groups 20-24, 25-29, 30-34, 35-39, and 40-44 years, respectively. Corresponding observed incidence rates for the same age groups were 1.6, 1.8, 2.2, 2.3, and 1.5 per 100 person-years, respectively. Most observed incidence rates fell within the 95% confidence limits of the model estimates. Expected numbers of cases within age intervals did not differ significantly from observed number of cases. The authors conclude that the model proved to be successful in approximating observed incidence rates and that it is a useful tool, particularly in countries where prevalence data are available and where HIV prevalence has stabilized, which is when the underlying assumptions in the model are best met. The model provides crucial information about incidence rates that might not be evident from prevalence data alone.

PIP: The authors conducted an analysis to validate a computer model which uses age-specific HIV prevalence data to estimate age-specific HIV incidence rates. Data for the analysis are from a cohort study of volunteer male workers in Bujumbura, Burundi. Subjects were tested at baseline for infection with HIV, with the HIV-negative subjects retested annually from 1990 to 1993 to determine rates of seroconversion. The computer model requires the input of age-specific HIV prevalence and estimates of age-specific mortality rates for HIV-negative and HIV-positive subjects. The model produced incidence rate estimates of 2.0, 2.7, 1.0, 1.5, and 1.8 per 100 person-years for age groups 20-24, 25-29, 30-34, 35-39, and 40-44 years, respectively. Corresponding observed incidence rates for the same age groups were 1.6, 1.8, 2.2, 2.3, and 1.5 per 100 person-years, respectively. Most observed incidence rates fell within the 95% confidence limits of the model's estimates such that the expected numbers of cases within age intervals failed to differ significantly from the observed numbers of cases. The authors believe that the model successfully approximated the observed incidence rates. It may therefore be highly useful in countries where prevalence data are available and where HIV prevalence has stabilized.