The Indian Journal of Tuberculosis - LRS Institute of Tuberculosis ...

4 V. SIVARAMAN ETAL
(c) India
The Indian Council of Medical Research
(ICMR) in collaboration with the Directorate
General of Health Services has built up a network
of 43 surveillance and 5 reference centres to carry
out a serosurveillance of HIV infection in the
country. Of the 580,824 high-risk group persons
screened during October 1985 to October 1990,
4,082 (7.0 per 1000) were found to be HIV
positive, including 57 AIDS patients 11 - Extensive
disseminated tuberculosis was seen only in 2
patients 113
Our group in Pondicherry screened 225
tuberculosis patients admitted in TB Sanatorium,
and the method outlined by Murray 13 , a
computerised mathematical model has been
developed to estimate the impact of HIV
infection on tuberculosis epidemiology within a
wide range of assumptions :
(1) Seroprevalance of HIV in general
population varies from 0.07 to 1.75 per 1000 (i.e.
1 to 25% of the general population is at risk and 7
per 1000 among them develop HIV infection).
(2) Seroprevalence of HIV among TB
patients varies from 1% to 6% (corresponding to
95% confidence limits of our Pondicherry
patients).
Figure 2 shows the estimated impact of coinfection
with HIV on the incidence of TB
Fig. 1. Conceptual mode] of inter relationship of HIV infection and tuberculosis
Pondicherry and suspected to be harbouring HIV
infection and found 6 to be seropositives 12 .
Applying the 95% confidence limits to this selective
study, we can assume that roughly between
1% to 6% of the tuberculous patients might be
HIV seropositive in this area. The assumption,
based on so limited and selective data has been
made in order to understand the relationship
between HIV infection and tuberculosis,
A conceptual model of the inter relationship
between HIV and tuberculosis is shown in figure
1, along with the flow rates applicable to the
Indian epidemiological conditions. Based on this
disease. For a given Seroprevalance, the incidence
among TB population shows very little variation
when the seroprevalence in the community varies.
Figure 3 shows time trend of the prevalence of
TB under Indian conditions, with 3 different
seroprevalence of HIV infection. The HIV
related increase in the prevalence of tuberculosis
may be considerable (The graph is computer
generated from the model described by
Sivaraman et al 14 The input parameters are the
same as the program A but the incidence rate is
higher and is derived by the method described by
Murray 13 ).