Modeling of HIV Transmission in Nasarawa State, Nigeria: An Analysis of Distribution of New Infections

Full text

Journal of US-China Medical Science 14 (2017) 116-122
doi: 10.17265/1548-6648/2017.03.003
Modeling of HIV Transmission in Nasarawa State,
Nigeria: An Analysis of Distribution of New Infections
Ishaku Ara Bako1, Abdulsamad Salihu2, Ifeanyi Okekearu2 and Jennifer Anyanti2
1. Department of Epidemiology and Community Health, College of Health Sciences, Benue State University, Makurdi, Benue State,
Nigeria
2. Society for Family Health (SFH), Abuja, FCT 970101, Nigeria
Abstract: The need to understand local HIV epidemics and linking the prevention and other interventions to evidences become very
important for the success of HIV response. The objective of the study was to estimate the distribution of new HIV infections among
adult population (15-49 yrs) and to identify the groups at highest risk of HIV infection in Nasarawa State Nigeria to inform HIV
prevention programme planning and Implementation. The study was based on the Modes of HIV Transmission (MOT) incidence model
recommended by the Joint United Nation’s Programme on AIDS (UNAIDS). Persons aged 15-49 years were divided into independent
groups based on their risky behaviours. Demographic, epidemiological and behavioral data were obtained for each risk group from
available survey reports/documents and inputed into the UNAID’s MOT Model spreadsheet.The model estimated that more than 45%
of new infections would occur amongst persons who reported “low risk” sex. The Injecting Drug Users, Female Sex Workers (FSW)
and Men having Sex with Men and their partners were estimated to contribute 20.7%. Persons reporting low risk sex practices, a
sub-population that includes cohabiting or married sexual partners need to be targeted with appropriate HIV prevention interventions
such as HIV Counselling and Testing, condom promotion, Interpersonal communications and other partner reduction strategies.
Key words: Risk group, incidence, modes of transmission.
1. Introduction
The HIV/AIDS epidemic is now in its 3rd decade
with an estimated 34 million people living with HIV
worldwide at the end of 2011. Sixty percent of all
people living with HIV reside in sub-Saharan Africa.
Nigeria has the second largest population of persons
living with HIV in the World with an estimated 3.1
million living with the disease [1]. Nasarawa state is
one of the states with high HIV/AIDS prevalence in
Nigeria. Estimates from Nigeria’s antenatal clinic HIV
sentinel survey shows the state has HIV prevalence of
7.5% compared to the national average of 4.1% [2].
One of the factors fuelling the epidemic in Nasarawa
state its proximity to Abuja, Nigeria’s federal capital.
This results to the influx of migrant populations into
the state.
Corresponding author: Ishaku Ara Bako (MBBS, FMCPH),
senior lecturer, research fields: epidemiology, medical statistics,
health services management.
HIV prevention interventions need to be targeted at
populations that are experiencing the highest burden of
new (incident) infections. The Joint United Nation’s
Programme on AIDS’ (UNAIDS) Modes of
Transmission (MOT) model uses national prevalence
and behavioural data to model the distribution of
incidence in key risk populations. It is an important
tool in supporting country and sub-national teams to
understand their epidemics to enable them make better
decisions on prioritization and definition of goals and
targets for effective scale up to Universal Access [3].
The UNAIDS in collaboration with the World Bank in
2007 assisted some countries in East and Southern
Africa to successfully apply the Incidence by Modes of
Transmission Model [4-6]. This was followed by
analysis in West African countries including Nigeria in
2008 [7-10]. Reports have indicated that substantial
heterogeneity exists within a country necessitating that
local data on HIV epidemic be used to inform local
D
DAVID PUBLISHING

Modeling of HIV Transmission in Nasarawa State, Nigeria: An Analysis of Distribution of New Infections
117
HIV interventions [11]. However, there is lack of
information on HIV incidence to inform HIV and
AIDS prevention interventions [12-14].
The Modes of HIV analysis in Nasarawa State was
an attempt to apply the UNAIDS’ model to define the
pattern of new HIV infection at a sub national level. It
was aimed at understanding the local epidemic in
Nasarawa State using available HIV prevalence,
demographic and behavioural data and thus to improve
the scope, relevance and comprehensiveness of the
state HIV prevention efforts. Specifically, the
Modes of Transmission review was to identify the
distribution of the most recent infections and the
populations at greatest risk for infection through
incidence modelling and to make recommendations for
prevention, policy and programmatic actions to ensure
a stronger and more effective state level prevention
strategy.
2. Materials and Methods
The project was conducted by a state team,
supported by the Department for International
Development-funded Enhancing Nigeria’s Response to
HIV and AAIDS Programme (DFID/ENR) programme
with guidance from an MOT modelling consultant.
2.1 Modes of Transmission Model
The purpose of the model was to calculate the
expected short-term (one year) incidence of HIV
infections among the adult population by mode of
transmission. The calculation was based on the current
prevalence of HIV infection, the number of individuals
in particular risk groups, and the risk of exposure to
infection within each group. The model utilized a
spreadsheet based on the UNAIDS Reference Group
on Estimates, Modelling and Projections [15].
Key documents that provided inputs for the model
include the following: 2005 and 2008 Antenatal Care
Serological Surveillance Surveys, the Nigerian
Demography and Health Survey (NDHS) 2008, the
Nigerian HIV/AIDS and Reproductive Health Survey
(NARHS) 2003 and 2005, the National Behavioural
Surveillance Survey (BSS) 2005, the country’s first
Integrated Bio-Behavioural Surveillance Survey
(IBBSS) 2007 and the country’s first population based
HIV sero-prevalence surveillance survey (NARHS
plus 2007). Where Nasarawa State representative data
did not exist, North Central geopolitical zonal values
were used or results of surveys that included proximal
states. Where no zonal or proximal data were not
available, reliable in-country research findings were
used.
These values were then shared with stakeholders
within the State through a stakeholders’ workshop and
externally through correspondence for input and
consensus. These inputs were used to finalise the
model.
2.2 Inputs
2.2.1 Percentage of Population with Risk Behaviour
The adult (15-49 years) population in Nasarawa was
divided into groups based on their highest risk factor
from the main transmission modes in the country:
sexual transmission (heterosexual and homosexual)
and sharing needles during intravenous drug use.
Initially the general adult (15-49 years) population,
disaggregated by sex, was differentiated by their sexual
activity over the last 12 months. Based on data from the
NDHS 2008, and NARHS plus 2007, they were
divided into those that did not have sex in the last 12
months; those that had sex but with only marital partner
and those that had non-marital sex. For this assessment,
the definition of commercial sex was agreed to be the
“exchange of gifts or money for sex”.
The percentage of men who have sex with men
(MSM) was determined from the high-risk group
surveys (IBBSS 2007) conducted in the country. The
fraction of persons that reported injecting drug use was
determined from the general population behavioural
survey (NARHS 2003).
2.2.2 Sexual Partners of Persons within High Risk
Groups

Modeling of HIV Transmission in Nasarawa State, Nigeria: An Analysis of Distribution of New Infections
118
The MOT model aims to show the effect of risk not
only from the perspective of the person who has sex or
other risk behaviours associated with HIV infection,
but also the effect of their behaviours on their sexual
partners.
(1) Sexual partners of male injecting drug users: To
estimate the percentage of females who were stable
partners of IDUs, the percentage of IDUs who reported
living with their sexual partners, independently of
whether they were married or not, was multiplied by
the percentage of the male population who were IDUs:
this was equal to 0.25 * 0.4 = 0.10%. This information
was taken from the IBBSS 2007.
(2) Sexual partners of female injecting drug users:
Unfortunately, the IBBSS did not provide reliable
information on female IDUs’ sexual characteristics.
We were more interested in regular sexual partners of
female IDUs. We made an approximation, that 70.6%
of female partners of IDU were either married or living
with their partners. This was because in the NHDS
2008, this percentage of women was reported to be in
marital or cohabiting union.
(3) Sexual partners of MSM: This was obtained from
percentage of MSM were married or living with
partners.
(4) Sexual partners of clients of Female sex workers:
Partners of clients of sex workers were estimated from
the percentage of clients of sex worker who were
married according to the NDHS. These partners of
FSW clients were hitherto assumed to have been low
risk.
(5) Sexual partners of men and women engaging
casual heterosexual sex: To estimate the number of
persons who were engaging in casual sex we assumed
the default values in the model i.e. that 80% of persons
engaging in casual sex had a regular partner.
2.3 HIV Prevalence
Prevalence amongst the general population was
based on the 2007 NARHS plus population based
sero-prevalence survey conducted in the country.
Nasarawa state had a prevalence of 6.8%. The
prevalence amongst the high-risk groups was based on
the 2007 Integrated Behavioural and Biological survey
conducted amongst High Risk groups in Nigeria. The
prevalence amongst partners of high-risk groups
(partners of FSWs) was estimated by studying the
relationship between sexual behaviour and HIV
prevalence in West African countries and limited
research in Nigeria and deducing the possible
prevalence amongst these groups based on the
prevalence amongst the general population and the
high risk groups.
2.4 STI Prevalence
Sexually Transmitted Infections (STIs) are known to
affect the rate of transmission of HIV during sex. The
prevalence of STI in the population and its distribution
amongst the various groups will affect the rate of HIV
transmission through sex. The prevalence of infection
was estimated by the percentage of the various groups
that reported having unusual genital discharge or a
genital ulcer in the last 12 months. The percentage for
the general population was obtained from the 2008
NDHS while the percentages for the high-risk groups
were obtained from the IBBSS 2007.
2.5 Number of Sexual Partners and Acts per Partner
per Year
An assumption was made that the average sexually
active person had about 100 acts of sexual intercourse a
year as in the latest NDHS surveys where this question
was asked the reported number varied between 50 and
100 sex acts per year.
According to the IBBSS 2007, brothel based FSW
and non-brothel based FSW had on average 34 and 25
clients per week respectively. As the sample, sizes of
these two groups were quite close it was assumed that
each represented half of the FSW population and it was
estimated that FSW had an average of 2 clients per day
for 20 days. Assuming, FSW take 12 weeks off due to
menstrual periods. Their total number of clients per

Modeling of HIV Transmission in Nasarawa State, Nigeria: An Analysis of Distribution of New Infections
119
year was: 600.
The number of sex partners per year was calculated
by determining the average number of partners that
people in each group had based on their responses to
questions in the various surveys conducted in the
country. People reporting no sexual activity in the last
12 months were presumed to have no sexual partner;
those reporting only marital sex were presumed to have
only one sexual partner and those stating that they had
had non-marital sex were assumed to have more than
one.
2.6 Percentage of Acts Protected (%)
These are the number of sex acts in which the
persons took precaution against HIV infection by using
a condom; this is approximated by determining the
percentage of last acts of sex in which a condom was
used. These were obtained from the IBBSS and the
NDHS 2003 & NARHS 2005. Condom use among
persons in the low risk group was presumed to be the
same for the state as the current use of condoms
reported in the NARHS+ 2007 for North Central zone.
3. Results
The model estimated that 3,335 new infections
would occur in the following one year amongst the
15-49 years adult population (Table 1).
The exposure groups with the highest incidence risk
were persons who reported low risk sex in the previous
year. They were estimated to account for about 47% of
all new infections. About 23% of infections would
occur amongst people who are sexual partners of
high-risk groups (female sex partners of MSM;
partners of IDUs, partners of clients of female sex
workers and partners of persons who have casual
high-risk sex (Table 1, Fig. 1).
Directly, IDU, FSW and MSM with their partners,
contribute as much as 21% of new infections. New
infections arising from commercial (transactional) sex
accounted for 8% of new cases, of which of clients
dominated with 4.9% of all new cases.
Persons who had casual sex and their partners
accounted for about 32% (9.8% and 21.8%
respectively) of new infections. Medical injections and
blood transfusion together accounted 0.9% (0.32% and
0.61% respectively) (Fig. 1).
Table 1 Incidence of HIV infections in one year among adults in Nasarawa Nigeria, 2010.
Adult risk category
Total number with risk behaviour
Incidence
% of incidence
Incidence per 100,000
Injecting Drug Use (IDU)
1,303
201
6.04
15,461
Partners IDU
600
6
0.17
956
Sex workers
4,344
61
1.82
1,394
Clients
16,508
164
4.92
993
Partners of Clients
5,613
42
1.26
750
MSM
3,041
205
6.13
6,728
Female partners of MSM
1,186
13
0.39
1,107
Casual heterosexual sex
152,919
328
9.83
214
Partners CHS
122,335
727
21.79
594
Low-risk heterosexual
318,598
1,558
46.71
489
No risk
242,412
0
0.00
0
Medical injections
868,860
11
0.32
1
Blood transfusions
8,689
20
0.61
234
Estimated total adult population
868,860
3,335
100.00
384

Modeling of HIV Transmission in Nasarawa State, Nigeria: An Analysis of Distribution of New Infections
120
Fig. 1 Estimated Proportion of New HIV Infection among adult risk groups population in Nasarawa State Nigeria, 2010.
4. Discussion
More than 45% of the infections occur amongst
persons practicing “low risk” sex. This finding is
higher than what was found from other countries and
National estimates from Nigeria. In the West African
sub region, about 30% of all new infections occur in
people who have low risk behaviour. It was estimated
to be 36% for Nigeria, 28% (Benin), 28% (Ghana), and
24% in Côte d'Ivoire [15], 44.1% (Kenya) [16], 56%
(Iran) [17]. This could be accounted for by among other
reasons low HCT rate; only 36.1% of men and 34.1%
of women in the state ever tested for HIV [18]. HIV
infection acquired because of previous or present
high-risk behaviours or relationships by one of the sex
partners is easily transmitted to unsuspecting partners.
The presumed perceived low risk of infection amongst
persons who themselves are keeping to one partner
faithfully, needs to be addressed. The notion that one is
safe because he or she is doing the right thing needs to
be revised to educate people that they are not safe until
their partners are also faithful. There is a need to ensure
that people are aware of the HIV status and the sexual
practices of their partners. Any form of doubt needs to
be addressed through the use of condoms during sex.
About 24% of new HIV infections were estimated to
occur amongst people who are sexual partners of
high-risk groups (female sex partners of MSM;
partners of IDUs, partners of clients of female sex
workers and partners of persons who have casual
high-risk sex). This finding did not agree with a
previous study which showed that in North Africa and
Middle East, Sex workers and IDUs contribute the
highest proportion of new HIV infection [19]. In Kenya,
6.04
0.17
1.82
4.92
1.26
6.13
0.39
9.83
21.79
46.71
0
0.32
0.61
0 10 20 30 40 50
Injecting Drug Use (IDU)
Partners IDU
Sex workers
Clients
Partners of Clients
MSM
Female partners of MSM
Casual heterosexual sex
Partners CHS
Low-risk heterosexual
No risk
Medical injections
Blood transfusions

Modeling of HIV Transmission in Nasarawa State, Nigeria: An Analysis of Distribution of New Infections
121
sex workers and their clients, IDUs, MSM and prison
population contribute 33% of new infections [20].
Partners of CHS, IDUs and of FSWs’ clients are people
who ordinarily should have been classified as low risk
but are now at a higher risk of acquiring HIV infection
because of their relationships with people known to
practice high risk sex and therefore not very visible as
high-risk groups.
In spite of the fact that the majority of the infections
were due to the HIV transmission amongst the general
population, the high-risk groups still contribute a
significant portion of the new HIV infections. Directly,
IDU, FSW and MSM with their partners, contribute as
much as 21% of new infections. This is quite
significant because these groups constitute only about
3% of the adult population.
The modeling exercise in Nasarawa State has
brought out a number of limitations in the application
of the UNAIDS Model particularly at a sub-national
level. The Model does not take into account the
heterogeneity in risk behaviours within each risk group
as individuals were placed in groups considered to be
the highest risk. However, effect of multiple exposures
in same individuals on HIV transmission probability
may be higher than effect of the highest risk alone. In
addition, there was limited state specific data at the
time of the modeling necessitating the use data from
contiguous states or zonal averages which may not be
exactly true for the state. As new data become available
and because the pattern of HIV transmission changes
over time [14], it is imperative that MoT analysis is
repeated on a regular basis. Finally, the analysis used
findings from surveys which relied on self reported
behaviours with possibilities of bias. However, the
exercise provided an opportunity to build the capacity
of stakeholders from the state on MOT analysis and as
more data become available, subsequent exercise
would be conducted with minimal support from outside
the state. The findings from this study could also be
used as an advocacy tool to government and donors to
solicit for appropriate funding for the state HIV
prevention interventions.
HIV Counselling and Testing (HCT) needs to be
scaled up rapidly to the general population in the state.
Efforts must be made to get couples to undergo couple
HCT. Condom use should be socially marketed to be
the norm in any sexual relationship especially where
the partners don’t know their HIV status. There is need
to overcome all barriers to condom usage including
socio-cultural factors and poor availability.
Opportunities for mass campaign and social movement
should be explored with religious and community
leaders to discourage multiple partnering as a threat to
individual and public health. Community based HIV
prevention interventions such as Interpersonal
Communications (IPC), Society Tackling AIDS
through Rights (STAR), Peer Education Plus (PEP)
model, Priority for Local AIDS Control Efforts
(PLACE) and Voice For Humanity (VFH) which has
already been piloted in the state should be scaled up
rapidly to increase HIV knowledge and effect
appropriate behavioural change among the general
population. Budgeting for HIV Prevention should take
distribution of new infections into consideration and
based on the relative magnitude of the mode of
transmission. There is need to carry out state specific
surveys to estimate the size and characteristics of
injecting drug users, men having sex with men and
their partners as well as clients of sex workers to use for
future MOT analysis. National HIV related biological
and behaviours surveys should be disaggregated by
state to enable findings to be more useful at the state
level.
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