The hidden HIV epidemic: what do
mathematical models tell us?
The case of France
Virginie Supervie, Jacques Ndawinz & Dominique Costagliola
U943 Inserm & Pierre and Marie Curie University, Paris, France
Background
 Many HIV positive individuals are unaware of their infection.
 Undiagnosed HIV infection has serious implications for both the
individual and public health.
 Persons unaware of their HIV infection cannot benefit from timely
treatment.
 Persons living with undiagnosed HIV infections may transmit HIV
to others.
 Information on persons living with undiagnosed HIV infection is
essential for guiding screening policy and resource allocation
planning.
Methods to estimate the size of the hidden
HIV epidemic
 Direct method (based on prevalence surveys)
 Back-calculation method (based on reported numbers of
HIV/AIDS diagnoses)
 Method based on simultaneous HIV/AIDS diagnosis and CD4
cell count at diagnosis
Working Group on Estimation of HIV Prevalence in Europe (2011) HIV in hiding: methods and data
requirements for the estimation of the number of people living with undiagnosed HIV. AIDS 25, 1017-1023.
Original “back-calculation” approach, before
availability of treatment
What can this tell us
about how many people
were infected and when
they were infected ?
Observed number of
AIDS cases diagnosed
Calendar year
Source: Phillips A (2009) Estimation of the number of people with undiagnosed HIV infection in a country. HIV in
Europe Conference.
Original “back-calculation” approach, before
availability of treatment
Estimated number
of people infected
(incidence curve)
Observed number of
AIDS cases diagnosed
Calendar year
From the incidence curve it is possible to work out the size of the hidden
epidemic, by subtracting the number of deaths, the number of HIV-infected
individuals in care and those diagnosed but not yet in care.
Source: adapted from Phillips A (2009) Estimation of the number of people with undiagnosed HIV infection in a
country. HIV in Europe Conference.
Estimated HIV incidence in France by transmission
category (using extended back-calculation model)
Ndawinz JD, Costagliola D, Supervie V. (2011) New method for estimating HIV incidence and time from
infection to diagnosis using HIV surveillance data: results for France. AIDS 25:1905-13
Estimated distribution of time interval between
infection and diagnosis by transmission category
(using extended back-calculation model)
Ndawinz JD, Costagliola D, Supervie V. (2011) New method for estimating HIV incidence and time from
infection to diagnosis using HIV surveillance data: results for France. AIDS 25:1905-13
Estimated distribution of time interval between
infection and diagnosis by transmission category
(using extended back-calculation model)
The probability of not being diagnosed 10 years after the infection occurred is
very small among each transmission group (<5%); therefore, most people
infected before 2000 were aware of their HIV status at the end of 2010.
Estimated HIV incidence in France by transmission
category (using extended back-calculation model)
Extrapolating our estimated curves of HIV incidence over the whole 2000-2010
period, and using our estimated distribution of times from infection to diagnosis,
we obtained the size of the hidden epidemic in France in 2010.
Estimated undiagnosed HIV prevalence and rates in France in
2010 (using extended back-calculation model)
Persons living
with
undiagnosed HIV
Overall
Men who have sex
with men
Injecting drug users
28,800
(19,100-36,700)
9,000
(7,700-10,100)
500
(100-800)
French
heterosexuals
9,800
(5,200-13,500)
Women
4,200
(1,800-5,100)
Men
5,600
(3,400-8,400)
Non French-national
heterosexuals
9,500
(6,100-12,300)
Women
5,000
(3,600-6,000)
Men
4,500
(2,500-6,300)
Estimated undiagnosed HIV prevalence and rates in France in
2010 (using extended back-calculation model)
Persons living
with
undiagnosed HIV
Undiagnosed
prevalence rate
(per 10,000 population)
28,800
(19,100-36,700)
7
(5-9)
9,000
(7,700-10,100)
314
(269-352)
500
(100-800)
70
(14-112)
French
heterosexuals
9,800
(5,200-13,500)
3
(1-4)
Women
4,200
(1,800-5,100)
2
(1-3)
Men
5,600
(3,400-8,400)
3
(2-4)
Non French-national
heterosexuals
9,500
(6,100-12,300)
26
(17-34)
Women
5,000
(3,600-6,000)
29
(21-34)
Men
4,500
(2,500-6,300)
24
(13-33)
Overall
Men who have sex
with men
Injecting drug users
Estimated undiagnosed HIV prevalence and rates in France in
2010 (using extended back-calculation model)
Persons living
with
undiagnosed HIV
Undiagnosed
prevalence rate
(per 10,000 population)
28,800
(19,100-36,700)
7
(5-9)
9,000
(7,700-10,100)
314
(269-352)
500
(100-800)
70
(14-112)
French
heterosexuals
9,800
(5,200-13,500)
3
(1-4)
Non French-national
heterosexuals
9,500
(6,100-12,300)
26
(17-34)
Overall
Men who have sex
with men
Injecting drug users
Essential to design
and interpret HIV
screening
survey/program
Estimated undiagnosed HIV prevalence and rates in France in
2010 (using extended back-calculation model)
Persons living
with
undiagnosed HIV
Undiagnosed
prevalence rate
(per 10,000 population)
28,800
(19,100-36,700)
7
(5-9)
9,000
(7,700-10,100)
314
(269-352)
500
(100-800)
70
(14-112)
French
heterosexuals
9,800
(5,200-13,500)
3
(1-4)
Non French-national
heterosexuals
9,500
(6,100-12,300)
26
(17-34)
Overall
Men who have sex
with men
Injecting drug users
Essential to design
and interpret HIV
screening
survey/program
Non-targeted HIV screening survey in emergency departments in France:
- 12754 persons screened;
- All newly diagnosed HIV patients belonged to a traditional high-risk group:
- 7 MSM (out of 268 tested);
- 11 non French-national heterosexuals (out of 2658 tested);
- 0 out of 8430 French heterosexuals tested had undiagnosed HIV infection;
Were these results unexpected?
Estimated undiagnosed HIV prevalence and rates in France in
2010 (using extended back-calculation model)
HIV screening
Persons living
Undiagnosed
survey*
with
prevalence rate
undiagnosed HIV
(per 10,000 population)
28,800
(19,100-36,700)
7
(5-9)
9,000
(7,700-10,100)
314
(269-352)
500
(100-800)
70
(14-112)
French
heterosexuals
9,800
(5,200-13,500)
Non French-national
heterosexuals
9,500
(6,100-12,300)
Overall
Men who have sex
with men
Injecting drug users
Undiagnosed
prevalence rate
per 10000
7/268

(106-531)
3
(1-4)
0/8430

(0-4)
26
(17-34)
11/2658

(21-74)
The results of the survey were not unexpected and confirm that
we have to test a lot of French heterosexuals to find the ones
living with undiagnosed HIV infection.
D’Almeida KW et al. (2012) Modest public health impact of nontargeted human immunodeficiency virus screening
in 29 emergency departments. Arch Intern Med, 172:12-20.
Estimated undiagnosed HIV prevalence and rates in France in
2010 (using extended back-calculation model)
Persons living
with
undiagnosed HIV
Undiagnosed
prevalence rate
(per 10,000 population)
28,800
(19,100-36,700)
7
(5-9)
9,000
(7,700-10,100)
314
(269-352)
500
(100-800)
70
(14-112)
French
heterosexuals
9,800
(5,200-13,500)
3
(1-4)
Non French-national
heterosexuals
9,500
(6,100-12,300)
26
(17-34)
Overall
Men who have sex
with men
Injecting drug users
What could be a
cost-effective HIV
screening strategy?
A screening strategy
is cost-effective as
long as at least 0.1%*
of results are HIVpositive.
Universal screening of the whole French population would not be costeffective because the undiagnosed prevalence rate is 0.07% (95% CI:
0.05%-0.09%) in the general population.
*Yazdanpanah Y et al. (2010) Routine HIV Screening in France: Clinical Impact and Cost-Effectiveness. PLoS
ONE 5(10): e13132.
Estimated undiagnosed HIV prevalence and rates in France in
2010 (using extended back-calculation model)
Persons living
with
undiagnosed HIV
Undiagnosed
prevalence rate
(per 10,000 population)
28,800
(19,100-36,700)
7
(5-9)
9,000
(7,700-10,100)
314
(269-352)
500
(100-800)
70
(14-112)
French
heterosexuals
9,800
(5,200-13,500)
3
(1-4)
Non French-national
heterosexuals
9,500
(6,100-12,300)
26
(17-34)
Overall
Men who have sex
with men
Injecting drug users
What could be a
cost-effective HIV
screening strategy?
A screening strategy
is cost-effective as
long as at least 0.1%
of results are HIVpositive.
Pr. Y. Yazdanpanah suggested universal testing among men. Is that
strategy cost-effective?
According to our estimates, undiagnosed prevalence rate is 0.10%
(95% CI: 0.07%-0.13%) among men.
CD4 count distributions among undiagnosed HIVinfected individuals in 2010 in France
Total (n=28800) CD4 count
19% 41% <200 200‐350 20% 20% 350‐500 >500 Among people living with undiagnosed HIV infection:
- 59% were eligible for ART;
- 39% were late presenters;
- 19% had advanced HIV disease;
CD4 count distributions among undiagnosed HIVinfected individuals in 2010 in France
Non‐French heterosexual women (n=5000) MSM (n=9000) 13% 47% 19% 18% CD4 count
20% 19% 20% 41% IDUs (n=500) 20% 350‐500 >500 French heterosexual men (n=5600) 36% 19% 23% 21% 17% 46% 21% 20% 36% <200 200‐350 20% 15% 45% Total (n=28800) 42% 21% French heterosexual women (n=4200) Non‐French heterosexual men (n=4500) 23% 18% 19% 21% 20% Lower % of individuals with CD4 counts > 500 and higher % of individuals with
CD4 counts < 200 among heterosexual men than among other transmission
categories.
Estimated number and percentage of HIV-infected
persons engaged in selected stages of the
continuum of HIV care in France in 2010
150,200
100%
121,400
81%
111,300
74%
96,800
84,200
64%
81%
92%
87%
56%
87%
Data from health insurance scheme (CNAMTS) and French Hospital Database on HIV ANRS-CO4
Estimated number and percentage of HIV-infected
persons engaged in selected stages of the
continuum of HIV care in France and in US*
100% 100% 100% France US 81% 80% 80% 74% 64% 60% 56% 41% 40% 36% 28% 20% 0% HIV‐infected diagnosed in care on ART virally suppressed *Cohen SM et al. (2011) Vital sign: HIV prevention through care and treatment – United States. MMRW, 60:161823.
Estimated number and percentage of HIV-infected
persons engaged in selected stages of the
continuum of HIV care in France and in US*
100% 100% 100% France US 81% 80% 80% 74% 64% 60% 56% 41% 40% 36% 81%
20% 92%
81%
87%
51%
87%
89%
28% 77%
0% HIV‐infected diagnosed in care on ART virally suppressed *Cohen SM et al. (2011) Vital sign: HIV prevention through care and treatment – United States. MMRW, 60:161823.
Estimated number and percentage of HIV-infected
MSM engaged in selected stages of the continuum
of HIV care in France in 2010
51,100
100%
42,100
39,000
82%
34,000
76%
30,300
67%
82%
93%
87%
59%
89%
Although 59% of HIV-infected MSM were virally suppressed
incidence of HIV infection did not decrease among MSM
Conclusion
 28,800 undiagnosed HIV-infected individuals. Similar to
the 32,000* recently estimated by InVS. This represents
about 20% of HIV-infected people.
 About 40,000 HIV-infected individuals are not in HIV care.
 About 60% of undiagnosed HIV-infected individuals are
eligible for antiretroviral treatment.
 Although 56% of HIV-infected persons are virally
suppressed, HIV incidence is not decreasing.
 Increasing HIV testing opportunities is thus essential.
*Cazein F et al. (2012) Prevalence and Characteristics of Individuals With Undiagnosed HIV Infection in France:
Evidence From a Survey on Hepatitis B and C Seroprevalence. JAIDS, 60:e114-e116.
Acknoledgements
 Andrew Phillips
 Sara Lodi
Awareness of HIV infection and transmission of
HIV (Adapted from Marks G. et al. AIDS (2006) with
French estimated data)
19%
unaware of HIV
infection
Account for:
81%
aware of HIV
infection
People living with
HIV/AIDS: 150,200
43%*
of new HIV
infections
57%*
of new HIV
infections
New infections
each year : 7,500
* Assuming no reduction in the prevalence of non protected sex acts with individuals at risk of HIV
infection among diagnosed HIV-positive individuals
Awareness of HIV infection and transmission of
HIV (Adapted from Marks G. et al. AIDS (2006) with
French estimated data)
19%
unaware of HIV
infection
Account for:
81%
aware of HIV
infection
People living with
HIV/AIDS: 150,200
64%*
of new HIV
infections
36%*
of new HIV
infections
New infections
each year : 7,500
* Assuming 57% reduction in the prevalence of non protected sex acts with individuals at risk of
HIV infection among diagnosed HIV-positive individuals
CD4 count distributions among undiagnosed HIVinfected individuals
 To estimate the distribution of CD4 counts among
undiagnosed HIV-infected individuals we combined:
 data on CD4 cell count decline*
 year of infection of undiagnosed HIV-infected
individuals
 We assigned to each HIV-infected individuals still
undiagnosed in 2010 a value of CD4 cell count based
on the time elapsed between 2010 and the year of
infection of this individual
*Lodi S. et al. (2011) Time From Human Immunodeficiency Virus Seroconversion to Reaching CD4 Cell Count
thresholds <200, <350, and <500 Cells/mm3: Assessment of Need Following Changes in Treatment Guidelines.
CID, 53:817-825.
Curve linking infection to AIDS, without treatment
Expected number of new AIDS cases per year after 1000
people infected - illustration
2
3
10 25 40 65
80 90 100 100 100 90 80 70
55 30
25 15 10
5
5
Curve known from
seroconverter cohorts
0
5
10
Years from infection
15
20
Source: Philips A. (2009) Estimation of the number of people with undiagnosed HIV infection in a country. HIV in
Europe Conference.
Curve linking infection to AIDS, without treatment
Expected number of new AIDS cases per year after 1000
people infected - illustration
2
3
10 25 40 65
80 90 100 100 100 90 80 70
55 30
25 15 10
5
5
Curve known from
seroconverter cohorts
0
5
10
Years from infection
15
20
BC uses reported number of AIDS cases and information on the incubation
period to “work backwards” and infer the numbers of persons infected in
previous years that would reproduce the observed AIDS surveillance data.
Source: Philips A. (2009) Estimation of the number of people with undiagnosed HIV infection in a country. HIV in
Europe Conference.
Extended back-calculation approach
Question changes…
from:
infection
AIDS
How many people must be infected, and when must they
have been infected, in order to produce the numbers of new
AIDS we have observed ?
to:
infection
HIV diagnosis
How many people must be infected, and when must they
have been infected, and what must the probability of getting
diagnosed have been, in order to produce the numbers of
new HIV diagnoses we have observed ?
Source: Philips A. (2009) Estimation of the number of people with undiagnosed HIV infection in a country. HIV in
Europe Conference.