1. MENTAL HEALTH BURDEN OF HIV/AIDS IN
DEVELOPING COUNTRIES
BY
DAVID M. NDETEI
PROFESSOR OF PSYCHIATRY
UNIVERSITY OF NAIROBI, KENYA
&
DIRECTOR, AFRICA MENTAL HEALTH FOUNDATION (AMHF)
Website: www.africamentalhealthfoundation.org

2. KENYA

3. 1) The WHO Executive Board during their 124th
session in a meeting on 20th November 2008
considered a report by the WHO Secretariat
entitled “HIV/AIDS and Mental Health”
I believe this report to be the most authoritative
summary of all the evidence linking HIV/AIDS
and mental health.

4. 2) OUTLINE
My talk will draw a lot from this report
Illustrate the global scale and then have a quick look at
Kenyan data
Summarize the priorities for action, opportunities and
challenges
I hope I will be able to convince you that indeed
we can live up to the challenge.

5. 3) First on Global scale

6. 4) Mental health and HIV/AIDS are closely
interlinked;
Mental health problems, including substance-
use disorders,
Associated with increased risk of HIV infection
and AIDS and interfere with their treatment,
Conversely some mental disorders occur as a
direct result of HIV infection

7. 5. Studies in both low- and high-income countries
have reported higher rates of depression in
HIV-positive people compared with HIV
negative control groups

8. 6) Some studies have reported behavioural risk
factors for transmission of HIV in between 30%
and 60% of people with severe mental illnesses.
The prevalence of mental illnesses in HIV-
infected individuals is substantially higher than in
the general population: -
High rates of sexual contact with multiple partners,
Injecting drug use,
Sexual contact with injecting drug users,
Sexual abuse (in which women are particularly
vulnerable to HIV infection),

9. Unprotected sex and low use of condoms.
Mental disorders may interfere with the ability to acquire
and/or use information about HIV/AIDS and thus to practice
safer behaviours or increase the likelihood of situations
occurring in which risk behaviours are more common.
Mental and substance-use disorders affect help-seeking
behaviour or uptake of diagnostic and treatment services for
HIV/AIDS. Mental illnesses have been associated with lower
likelihood of receiving antiretroviral medication.
Substance-use disorders affect both the progression of HIV
disease and the response to treatment.

10. 7) Therefore it is not surprising that there is a
high seroprevalence of HIV infection in people
with serious chronic mental illnesses

11. 8) HIV/AIDS and injection drugs use: -
About 10% of HIV cases worldwide are
attributable to injecting drug use
About three million injecting drug users
might be infected with HIV.

12. 9) The Burden:
HIV/AIDS is a significant cause of death and disability,
especially in low- and middle-income countries. UNAIDS
estimates that in 2007, 33 million people were living with
HIV.
HIV/AIDS imposes a significant psychological burden.
People with HIV often suffer from depression and anxiety
as they adjust to the impact of the diagnosis, for instance
shortened life expectancy, complicated therapeutic
regimens, stigmatization, and loss of social support,
family or friends.
HIV infection can be associated with high risk of suicide or
attempted suicide. The psychological predictors of
suicidal ideation in HIV-infected individuals include
concurrent substance-use disorders, past history of
depression and presence of hopelessness.

13. Apart from psychological impact, HIV infection has direct
effects on the central nervous system, and causes
neuropsychiatric complications including HIV
encephalopathy, depression, mania, cognitive disorder,
and frank dementia, often in combination.
Infants and children with HIV infection are more likely to
experience deficits in motor and cognitive development
compared with HIV negative children.
Cognitive impairment in HIV/AIDS has been associated
with greatly increased mortality, independent of other
factors such as baseline clinical stage, CD4+ cell count,
serum haemoglobin concentration, antiretroviral treatment,
and social and demographic characteristics.

14. (a) URBAN AREAS
Table 1: Methods/Routes Of Use Of Drugs (%)
Mombasa Malindi Nairobi Nakuru Kisumu
n=314 n=75 n=340 N=222 n=209
Swallow 33.4 16.0 47.4 59.5 72.2
Smoke 43.9 62.7 30.6 32.4 23.9
Snort/Sniff 5.7 0.0 5.0 5.0 1.4
Inject 12.1 21.3 15.9 0.9 1.9
Others 4.8 0.0 1.2 2.3 0.5
Oral (45.7% on average) and nasal (38.7%) were by far the
most common modes of consumption of drugs, followed by
parenteral administration (injectable) at 10.4% on average
(table 3).

15. TABLE 2(a) : PATTERN OF DRUG INJECTION (%)
Mombasa Malindi Nairobi Nakuru Kisumu
i. Annual prevalence rates of
IDUs
Once a week 1.1 0.5 12.9 6.1 4.3
More than once a week 1.7 9.3 34.9 3.3 11.2
Once a day 2.9 0.5 4.4 2.0 0
More than once a day 17.1 10.4 3.8 0.4 0
Non-injectors 77.1 89.6 44.0 88.2 84.5
ii. Injecting self alone. Yes 12.9 0.5 12.9 4.9 2.2
iii. Annual use of needle after
others. Yes
Once 5.1 9.3 26.1 3.7 12.6
Up to 5 times 3.7 0 3.8 1.2 0
More than 5 times 4.3 0.5 7.1 3.7 0
iv. Use of the needle after
others. Yes
One person 4.6 0 3.0 4.1 0.7
Upto 5 people 3.7 0 3.0 0.4 0
More than 5 people 3.7 0.5 6.6 2.4 0
v. Dispensing used needle to
others in 12 months. Yes
Once 3.7 2.7 17.0 2.0 32.5
Up to 5 times 2.9 0.9 3.3 1.6 0
More than 5 times 4.3 0.5 6.6 3.7 0

16. TABLE 2(b) : PATTERN OF DRUG INJECTION (%)
Mombasa Malindi Nairobi Nakuru Kisumu
vi. Cleaning needles before re-
use in 12 months. Yes
Every time 8.9 1.6 3.8 2.0 1.1
Sometimes 9.1 0 8.8 1.6 2.9
Never 4.3 0 11.3 14.6 1.1
vii. Bleaching needle in the
last 12 months. Yes
Every time 1.7 1.6 10.2 3.7 24.2
Sometimes 2.3 5.5 23.6 2.4 15.2
Never 20.3 2.7 30.8 19.9 24.9
viii. Equipment cleaning in
ways other than afore
mentioned. explain:
Boiling 4.9 0.5 3.6 4.9 0.4
Disinfectant 0.9 0 1.9 3.3 0
Direct heating 0 0 0.5 0.4 0
Other 10.6 0 0.5 0.8 0

17. TABLE 3a: NEEDLE SHARING BEHAVIOR
Use of a needle after someone
Study Sites else in the last 12 months (%)
Never Once Up to >5
5 times times
Mombasa 47.1 35.3 17.5 0.0
Malindi 0.0 0.0 0.0 100.0
Nairobi 37.1 17.1 14.3 31.4
Nakuru 73.3 13.3 6.7 6.7
Kisumu 80.0 0.0 0.0 0.0
Average 47.5 13.1 7.7 27.6
Those who knew that they were HIV positive used needles that
had just been used by somebody else. This practice was most
frequent in Malindi and Nairobi but was not found in Kisumu.

18. TABLE 3b: DRUG INJECTION & HIV STATUS
Others using needle before
HIV status +ve. respondent in the last 12 months (%)
No One Up to 5 >5
person person people people
Mombasa 46.7 26.7 26.7 0.0
Malindi 0.0 0.0 0.0 100.0
Nairobi 44.0 12.0 8.0 36.0
Nakuru 73.3 26.7 0.0 0.0
Kisumu 100.0 0.0 0.0 0.0
Average 52.8 13.1 6.9 27.2
Those who knew that they were HIV positive passed on the needles they had used
to others to also use. This practice was commonest in Malindi, followed by Nairobi
but was not found in Kisumu. Thus awareness in HIV transmission and positive in
HIV status was not reflected in the practice of sharing needles, at least on the part
of those who already knew their positive status. However the findings for Malindi
should be seen in the light of Table 3d below.

19. TABLE 3c: DRUG INJECTION & HIV STATUS
Other people using a needle after the respondent
HIV status in the last 12 months (%)
+ve. Never Once Up to 5 >5 times
times
Mombasa 66.7 6.7 26.7 0.0
Malindi 0.0 0.0 0.0 100.0
Nairobi 40.0 20.0 14.3 25.7
Nakuru 66.7 20.0 13.3 0.0
Kisumu 80.0 0.0 0.0 0.0
Average 50.7 9.3 10.9 2.5
This table reflects the findings of Table 3b.

20. TABLE 3d: DRUG INJECTION & HIV STATUS
Cleaning of needles before re-use in the last
HIV status +ve. 12 months (%)
No Every Someti Never
re-use time mes
Mombasa 21.4 7.1 28.6 42.9
Malindi 0.0 100.0 0.0 0.0
Nairobi 18.5 18.5 29.6 33.3
Nakuru 13.3 13.3 0.0 73.3
Kisumu 100.0 0.0 0.0 0.0
Average 30.6 27.8 11.6 30.0
Malindi cohort always cleaned their needles, thus putting into
practice their knowledge on the risks involved in sharing needles.
In Kisumu there was no sharing of needles. In all the other cohorts,
majority cleaned only sometimes or never.

21. TABLE 3e: DRUG INJECTION & HIV STATUS
Bleaching needles before use in
HIV status +ve. the last 12 months (%)
Every Someti Never
time mes
Mombasa 0.0 0.0 100.0
Malindi 0.0 0.0 100.0
Nairobi 16.2 35.1 48.6
Nakuru 0.0 13.3 86.7
Kisumu 20.0 0.0 80.0
Average 7.2 9.7 83.1
Bleaching of needles was a practice found only in upcountry
cohorts.

22. TABLE 3f: DRUG INJECTION & HIV STATUS
Sharing of equipment
HIV status +ve. other than needles (%).
Yes No
Mombasa 10.7 14.3
Malindi 50.0 0.0
Nairobi 16.1 33.3
Nakuru 0.0 2.8
Kisumu 0.0 100.0
Average 35.4 29.5
Drug injectors who knew they were HIV positive shared
equipments related to drug use other than needles in all
the cohorts except in Nakuru and Kisumu.

23. TABLE 3g: DRUG INJECTION & HIV STATUS
Sexual intercourse without a condom under
HIV status +ve. influence of drugs. (%)
Not at all Sometimes Always
Mombasa 44.0 16.0 40.0
Malindi 0 0 0
Nairobi 56.0 36.0 8.0
Nakuru 22.2 38.9 38.9
Kisumu 50.0 33.3 16.7
Average 43.1 31.1 25.9
In spite of knowing that they were HIV positive the cohorts
practiced unprotected sex in the majority of the cases. There is
therefore no relation between knowing they are HIV positive and
the practice of safe sex.

24. TABLE 4: USE OF CONDOMS VS HIV STATUS (%)
Mombasa Malindi Nairobi Nakuru Kisumu
Frequency of use a
condom whenever you
have sex Vs. awareness of
HIV status
Not at all 20.0 35.0 22.4 27.1 32.3
Sometimes 42.1 35.0 55.2 43.9 41.2
Always 37.9 28.8 22.4 29.0 26.5
Frequency of use of
condom whenever you
have sex Vs. HIV status
Not at all 19.0 37.5 27.7 30.8 34.5
Sometimes 53.2 29.2 47.7 48.7 34.6
Always 27.8 33.2 24.6 20.5 26.9
Whether they were aware of HIV status or not, the majority did not
use condom during sex, again reflecting a gap between knowledge
on HIV transmission and practice.

25. LABORATORY RESULTS
Note: No. = Number
A total of 120 were recruited, 111 males and 9 females
No. of drug abusers tested 120 Percentage
HEPATITIS C + 73 60.83
HIV + 50 41.66
No. of IDU’s tested 101 Percentage
HEPATITIS C + 71 70.29
HIV + 50 49.50
Of the total sample of 120, seventy three tested positive for
Hepatitis C (60.83%) and 50 tested positive for HIV
(41.66%). Out of that sample 101 were I.D.U’s. All who
tested positive for HIV (50) were IDU’s (49.5%), and
70.29% who tested positive for Hepatitis C were I.D.U’s.

26. AGE DISTRIBUTION
(A)
Age No. of drug abusers tested 120 Percentage
17 – 30 65 54.2
31 – 40 43 35.8
41 – 52 12 10

27. (B)
Age No. of drug HCV
abusers tested HIV + Percentage + Percentage
17 - 30 65 27 22.5 39 32.5
31 - 40 43 19 15.83 29 24.16
41 - 52 12 4 3.33 5 4.16
TOTAL 120 50 44.66 73 60.82

28. (C)
No. of drug HIV HCV
Age abusers tested + Percentage + Percentage
17 - 30 65 27 26.73 39 38.61
31 - 40 43 19 18.81 27 26.73
41 - 52 12 4 3.96 5 4.95
TOTAL 101 50 49.5 71 79.29

29. (D)
No. of drug
abusers HIV HCV
Age tested 120 + Percentage + Percentage
17 - 30 65 27 41.53 39 60
31 - 40 43 19 44.1 29 67.44
41 - 52 12 4 33.33 5 41.66

30. (E)
No. of drug
Age abusers
tested 120 HIV + Percentage HCV + Percentage
17 - 30 65 27 41.53 39 60
31 - 40 43 19 44.1 27 62.79
41 - 52 12 4 33.33 5 41.66

31. GENDER
(A)
Gender No. of drug abusers Percentage
tested 120
MALE 111 92.5
FEMALE 9 7.5
(B)
Gender No. of IDU tested 101 Percentage
MALE 94 93.06
FEMALE 7 6.94
The low turnout of females to participate in the study can be
attributed to the following:-
1. Their low number in general.
2. Their fear of being tested, as many of them are also
commercial sex workers.
3. Little attention has been paid to them as an affected group
up to now.

32. (C)
GENDER # OF IDU # HIV + # HEPATITIS C +
TESTED
MALE 94 46 66
FEMALE 7 6 5
Out of the 7 female IDU’s, six tested positive for
HIV/Aids and 5 tested positive for Hepatitis C. Out of
the 94 male IDU’s, 46 tested positive for HIV/Aids and
66 tested positive for Hepatitis C.
Of the total sample of 120, seventy three tested
positive for Hepatitis C (60.83%) and 50 tested
positive for HIV (41.66%). Out of that sample 101
were IDUs. All those who tested positive for HIV (50)
were IDUs (49.5%).

33. (B) IN A RURAL SETTING
Table 1a: - HIV/AIDS STATISTICS FOR THE STUDY SITES
Reporting Period KIBWEZI (EXPERIMENTAL SITE) MTITO ANDEI (CONTROL SITE)
Grand Grand
ST Children Adults Totals Totals Children Adults Totals Totals
JAN 2010 - DEC 31 2010 0-14yrs >14yrs 0-14yrs >14yrs
F M F M F M F M F M F M
Number of new PMCT clients 0 0 20 0 20 20 1 0 26 0 21 21
patients enrolled VCT clients 6 2 10 6 16 8 24 8 3 46 16 54 19 73
within the month TB patients 0 1 6 8 6 9 15 0 0 3 3 3 3 6
1 for HIV care by In patients 0 0 1 0 1 0 1 0 0 15 5 15 5 20
entry point within CWC 5 1 0 0 5 1 6 1 1 0 0 1 1 2
the reporting All others 13 27 237 98 250 125 375 24 7 134 48 124 55 179
period Sub-total 24 31 274 112 298 143 441 34 11 224 72 218 83 301
Cumulative Number of persons
2 enrolled in HIV care at this facility
within the reporting period 70 102 770 362 840 464 1304* 76 69 617 195 693 264 957*
Number of patients WHO stage 1 1 1 5 0 6 1 7 5 5 18 5 23 10 33
starting ARVs by WHO stage 2 5 5 31 1 36 6 42 5 4 32 5 37 9 46
3 WHO stage within WHO stage 3 2 4 27 4 29 8 37 3 3 44 10 47 13 60
the reporting WHO stage 4 0 0 1 0 1 0 1 3 1 5 0 8 1 9
period Sub-total 8 10 64 5 72 15 87 16 13 99 20 115 33 148
Cumulative Number of persons
4 started on ARVs at this facility
during the reporting period 41 41 325 187 366 228 594* 42 46 391 94 433 140 573*
Pregnant
Total Number of
women 0 2 2 2 0 10 10 10
5 patients currently
All others 41 41 325 187 366 228 594 40 38 320 87 360 125 485
on ARVs
Sub-total 41 41 327 187 368 228 596* 40 38 330 87 370 125 495*
Number of persons who are enrolled
and eligible for ART but have not
6
been started on ART during the
reporting period 0 0 0 0 0 0 0 21 10 113 43 134 53 187
Post exposure Sexual assault 2 0 6 3 8 3 11 4 0 4 1 8 1 9
prophylaxis(PEP) Occupational 0 0 0 0 0 0 0 0 0 0 0 0 0 0
7 Within the All others 0 0 0 0 0 0 0 1 0 3 7 4 7 11
reporting period Sub-total 2 0 6 3 8 3 11 5 0 7 8 12 8 20
Total Number of Cotrimoxazole 70 102 770 362 840 464 1304 68 65 556 172 624 237 861
patients currently Fluconazole 0 0 0 0 0 0 0 0 2 15 10 15 12 27
8 on prophylaxis
during the
reporting period Sub-total 70 102 770 362 840 464 1304* 68 67 571 182 639 249 888*

34. Table 1b: - HIV/AIDS STATISTICS FOR THE STUDY SITES
Reporting Period KIBWEZI (EXPERIMENTAL SITE) MTITO ANDEI (CONTROL SITE)
Children Adults >14yrs Totals Children Adults >14yrs Totals
ST 0-14yrs Grand 0-14yrs Grand
JAN 2011 - MAY 31 2011 Totals Totals
F M F M F M F M F M F M
1 Number of f new PMCT clients 0 7 7 7 0 4 4 4
patients enrolled VCT clients 2 0 6 1 8 1 9 3 1 8 6 11 7 18
within the month TB patients 0 0 3 3 3 3 6 0 0 0 1 0 1 1
for HIV care by In patients 0 0 0 0 0 0 0 3 0 23 7 26 7 33
entry point within CWC 0 0 0 0 0 0 0 0 0 0
the reporting All others 5 7 47 13 52 20 72 5 5 37 10 42 15 57
period Sub-total 7 7 63 17 70 24 94 11 1 12 5 18 6 24
2 Cumulative Number of persons
enrolled in HIV care at this facility
within the reporting period 77 109 833 379 910 488 1,398* 87 75 689 219 776 294 1,070*
3 Number of patients WHO stage 1 0 0 1 0 1 0 1 0 0 6 1 6 1 7
starting ARVs by WHO stage 2 2 5 5 3 7 8 15 0 2 20 4 20 6 26
WHO stage within WHO stage 3 0 0 10 8 10 8 18 3 1 23 6 26 7 33
the reporting WHO stage 4 0 1 0 0 0 1 1 0 0 6 1 6 1 7
period Sub-total 2 6 16 11 18 17 35 3 3 55 12 58 15 73
4 Cumulative Number of persons
started on ARVs at this facility
within the reporting period 43 47 341 198 384 245 629* 45 49 446 106 491 155 646*
5 Total Number of Pregnant
patients currently women 0 2 2 2 0 16 16 16
on ARVs within All others 43 47 338 198 381 245 626 43 41 375 99 418 140 558
the reporting
period Sub-total 43 47 340 198 383 245 628* 43 41 391 99 434 140 574*
6 Number of persons who are enrolled
and eligible for ART but have not
been started on ART within the
reporting period 0 0 0 4 0 4 4 7 0 40 14 47 14 61
7 Post exposure Sexual assault 0 0 0 1 0 1 1 3 0 9 2 12 2 14
prophylaxis(PEP) Occupational 0 0 0 0 0 0 0 0 0 0 0 0 0 0
within the All others 0 0 0 0 0 0 0 0 0 0 0 0 0 0
reporting period Sub-total 0 0 0 1 0 1 1 3 0 9 2 12 2 14
8 Total Number of Cotrimoxazole 77 109 827 379 904 488 1392 79 70 628 197 707 267 974
patients currently Fluconazole 0 0 0 0 0 0 0 12 13 25 11 37 24 61
on prophylaxis
within the
reporting period Sub-total 77 109 827 379 904 488 1,392* 91 83 653 208 744 291 1,035*
*Cumulative grand totals for the reporting period

35. CONCLUSIONS BASED ON KENYAN EXPERIENCE
1) IDUs is an emerging phenomenon in Kenya, and there is
urgent need for intervention practice to keep it in check
2) There is a high correlation between IDUs and HIV in
Kenya: -
Laboratory tests on a cohort of IDUs in Mombasa
found that 49.5% were HIV positive. This was a
specially highly motivated cohort requested to come
forward for testing and may therefore have been a
cause of underestimation of the percentage of
linkages.
An average of 68-88% of different cohorts of IDUs very
active in drug abuse and injecting drug abuse were
HIV positive.

36. 3) There is an urgent need to prevent IDU from becoming
a major vector of HIV in Kenya
4) This study indicates homosexuality as an emerging
sexual practice in Kenya. This was particularly found
amongst youth, drug users and IDUs
5) In spite of knowledge on how HIV is transmitted, this is
not reflected in both drug abuse and sexual activity
pattern
6) The research indicates that drug abuse predisposes to
risky sexual behaviour. This in turn fuels more drug
abuse. This was confirmed by qualitative data

37. Recommendations
1) There is an urgent need to develop new policy on IDU
and its relationship to HIV.
2) There is an urgent need to translate policy into action in
a comprehensive inclusive way.
3) Urgent research is required to bridge the gap between
knowledge and practice in relation to drug abuse,
injecting drug use, sexual practice and HIV.
4) Timely interventions are indicated to limit the spread of
HIV among drug users and Injecting Drug Users.

38. GENERAL PRIORITIES FOR ACTION
1) Integration of mental health and HIV/AIDS
diagnostic, information and mental health
systems: -
Integrated training tools for diagnosis
Joint management
Supervision

39. 2) Appropriate policy to back the integration
3) Operational research so that developing countries can
have their own data
It is unacceptable that despite the fact that developing
countries carry more than 90% of the burden of
HIV/AIDS, little information about the interaction
between HIV/AIDS and mental health is available from
low and middle-income countries.

40. YES WE CAN!!!