possible social and economic impact of hiv/aids epidemic on the republic of armenia

POSSIBLE SOCIAL AND ECONOMIC

IMPACT OF HIV/AIDS EPIDEMIC ON

THE REPUBLIC OF ARMENIA

A. Aharonyan

A. Torchyan

Yerevan 2007

Abbreviations

AIDS Acquired Immunodeficiency Syndrome

ART Antiretroviral Therapy

BBS Behavioral and Biological Surveillance

CJSC Closed Joint-Stock Company

EAP Economically Active Population

FSW Female Sex Worker

GDP Gross Domestic Product

HIV Human Immunodeficiency Virus

IDU Injecting Drug User

ILO International Labor Organization

MSM Men who have sex with men

NCAP National Center for AIDS Prevention

PRSP Poverty Reduction Strategy Paper

RA Republic of Armenia

RF Russian Federation

STI Sexually Transmitted Infection

STD Sexually Transmitted Disease

UN United Nations

UNDP United Nations Development Programme

WHO World Health Organization

i

TABLE OF CONTENTS

Preface...................................................................................................................................... iii

Executive Summary ..................................................................................................................iv

Chapter 1. PEVALENCE AND POSSIBLE SCENARIOS OF DEVELOPMENT OF THE

HIV/AIDS EPIDEMIC IN THE RA..........................................................................................1

Prevalence of HIV/AIDS in the World and in the RA...........................................................1

Possible Scenarios of Development of the HIV/AIDS Epidemic in the RA .........................4

Methodology ......................................................................................................................4

Scenarios............................................................................................................................9

Chapter 2. POSSIBLE SOCIAL AND ECONOMIC IMPACT OF THE HIV/AIDS

EPIDEMIC IN THE REPUBLIC OF ARMENIA...................................................................14

Correlation Between HIV/AIDS Epidemic and Social and Economic Development of a

Society..................................................................................................................................14

Impact on Labor Force ....................................................................................................17

Impact on State Budget and Social Contributions...........................................................21

Estimated Macroeconomic Costs of the HIV/AIDS Epidemic............................................27

Conclusion and Recommendations..........................................................................................35

BIBLIOGRAPHY....................................................................................................................38

ii

Preface

This study was conducted within the framework of the United Nations Development

Program (UNDP) on the basis of the development consultant mission report.1 The Study

evaluates the current prevalence of HIV/AIDS, the main factors contributing to and the trends

of spreading and the medium-term social and economic impact of the epidemic on the RA. It

evaluates the potential impact of the epidemic on population growth, employment, social and

health services, and the size and growth pace of the GDP. The Study focused on several

scenarios developed on the basis of information obtained from the RA NCAP, the RA

Government, the UNAIDS, the WHO, and other agencies.

Chapter 1 presents HIV/AIDS prevalence in a number of scenarios around

development of the epidemic, and analyzes the potential medium-term development impact

of the epidemic. Chapter 2 analyzes the potential social and economic impact of the

development of the epidemic of HIV/AIDS under the different scenarios.

1 Isaac Thompson, Reflection of HIV/AIDS Problems in the Republic of Armenia Poverty Reduction Strategy Paper, Mission Report, UNDP, February 2007.

iii

Executive Summary

The HIV/AIDS epidemic is a serious global problem. The HIV epidemic has

penetrated virtually all the states. According to UNAIDS data, as of December 2006, about

39.5 million people worldwide were living with HIV: the majority of them, 24.7 million

people, live in Sub-Saharan Africa. In Eastern Europe and Central Asia region including also

Armenia and countries of the former Soviet Union the number of HIV-infected people has

reached 1.7 million.

About 4.3 million people became HIV infected in the year of 2006, whereof 270

thousand are from our region.

Our region experiences the fastest growing HIV/AIDS epidemic in the world.

The registration of cases of human immunodeficiency virus infection in the RA has

started since 1988. From 1988 to 31 October, 2007, 521 HIV cases have been reported in the

RA among Armenian nationals.

HIV/AIDS situation assessment has shown that the estimated number of people living

with HIV in the country is 2800.

In the RA the main modes of HIV transmission are through injecting drug use

(48.0%) and heterosexual practice (44.9%). Besides, there are also registered cases of

mother-to-child HIV transmission as well as through blood transfusion and homosexual

practices.

The analyzes of the HIV prevalence trends show that, by 2015, the prevalence of HIV

in the 15-49 population may reach 0.57%, which is only 2.5-fold lower than the current HIV

prevalence in the Ukraine, which has the highest HIV prevalence in Europe and the former

Soviet Union and is moving towards a generalized state, during which the HIV infection

becomes fundamentally rooted in the whole population.

The HIV/AIDS epidemic has numerous social and economic consequences, because

of quite high rates of HIV-caused morbidity and mortality in the economically active

population.

Further spreading of the HIV in Armenia may slow down real annual GDP growth by

about 0.4% during 2007-2015 compared to the “No AIDS” scenario, and the 2015 GDP

growth may shrink by up to 15.6 billion Armenian drams. In general, aggregate GDP losses

during 2007-2015 may amount to 38.7 billion drams. Capital reserves’ growth may shrink by

up to 11.3 billion drams by 2015, while total losses of capital during 2007-2015 may amount

iv

to 27.7 billion drams. The epidemic will also affect the health sector by necessitating an

additional 1.5 billion drams of health costs in 2015. Total additional health costs during

2007-2015 may amount to 9.6-9.8 billion drams. As a result of the further development of

the epidemic, losses of the state budget in the form of foregone personal income tax payments

and social contributions may reach 2.65 billion in 2015, with total losses of up to 10.8 billion

during 2007-2015.

Decades of global experience combating the consequences of HIV/AIDS have shown

that any response is most likely to succeed at a time when the HIV prevalence is relatively

low.

The situation analysis in the RA has shown that in the years ahead, interventions to

prevent HIV/AIDS should be made in the following priority order:

1. Prevention programs among IDUs;

2. Prevention programs among men who have sex with men;

3. Prevention programs among sex workers;

4. Prevention and treatment of sexually transmitted diseases;

5. Prevention programs among young people of ages 15-24;

6. Prevention programs among people traveling abroad

An effective response to HIV/AIDS must include programs of awareness raising,

education, enhanced voluntary counseling and testing, encouraging use of and improving

access to condoms, and prevention and treatment of sexually transmitted diseases among the

population groups more liable to the risk, as well as the general population.

v

1

Chapter 1. PEVALENCE AND POSSIBLE SCENARIOS OF

DEVELOPMENT OF THE HIV/AIDS EPIDEMIC IN THE RA .

Prevalence of HIV/AIDS in the World and in the RA

The HIV/AIDS epidemic is a serious global problem. The HIV epidemic has

penetrated virtually all the states.2 According to UNAIDS data, as of December 2006, about

39.5 million people worldwide were living with HIV: the majority of them, 24.7 million

people, live in Sub-Saharan Africa. In Eastern Europe and Central Asia region including also

Armenia and countries of the former Soviet Union the number of HIV-infected people has

reached 1.7 million.3

About 4.3 million people became HIV infected in the year of 2006, whereof 270

thousand are from our region, which more than twelve-fold exceeds the number of new cases

in Western Europe and more than six-fold – the number of new cases in North America.3

Our region experiences the fastest growing HIV/AIDS epidemic in the world3.

The registration of cases of human immunodeficiency virus infection in the RA has

started since 1988.4 From 1988 to 31 October, 2007, 521 HIV cases have been reported in the

RA among Armenian nationals.5

During 2006, 66 new cases of HIV infection were registered among citizens of the

RA. During 2007, 92 new cases of HIV infection were registered among citizens of the RA.

Men constitute a major part in the total number of HIV cases – 389 cases (74.7%), women

make up 132 cases (25.3%). Eleven (2.1%) cases of HIV infection were registered among

children. The overwhelming majority of the HIV-infected individuals (72.4%) belong to the

age group of 20-39.6

In the RA the main modes of HIV transmission are through injecting drug use

(48.0%) and heterosexual practice (44.9%). Besides, there are also registered cases of

mother-to-child HIV transmission as well as through blood transfusion and homosexual

practices.6

2 2006 Report on the Global AIDS Epidemic, Joint United Nations Program on HIV. 3 AIDS epidemic update, Joint United Nations Programme on HIV/AIDS (UNAIDS) and World Health Organization (WHO), December 2006. 4 Busel A., Grigoryal S, et al, HIV Surveillance in the Republic of Armenia 2000-2002, Yerevan 2002. 5 Republic of Armenia Ministry of Health National AIDS Prevention Center. 6 Republic of Armenia Ministry of Health National AIDS Prevention Center.

The distribution of registered HIV cases in the RA according to the HIV infection

transmission modes:7

Transmission through injecting drug usage 48.0%

Transmission through heterosexual practices 44.9%

Mother-to-child transmission 1.9%

Transmission through blood 1.5%

Transmission through homosexual practices 0.4%

Unknown 3.3%

AIDS diagnosis was made to 202 patients with HIV (40 women, 5 children): 46 –

during 2006, 51 – during 2007. From the beginning of the epidemic 117 death cases have

been registered among HIV/AIDS patients. The death cases include 19 women and 3

children.7

All the individuals infected via injecting drug use were men. As a matter of fact, some

of them temporarily inhabited in the Russian Federation (Moscow, St. Petersburg, Irkoutsk,

Rostov, Surgut etc.) and the Ukraine (Odessa, Kiev, Mareupol etc.) and were probably

infected with HIV there. In addition, the majority of all the HIV-infected males (65.1%) are

individuals who practice injecting drug usage, whereas the majority of women were infected

through sexual contacts (98.7%).7

The maximum number of HIV cases was reported in Yerevan, the RA capital: 252

cases, which constitute 48.4% of all the registered cases. The number of registered cases in

Shirak Marz is the second-highest in Armenia – 9.8%.7

HIV/AIDS situation assessment has shown that the estimated number of people living

with HIV in the country is 2800.7

7 Republic of Armenia Ministry of Health National AIDS Prevention Center.

2

A breakdown of HIV and AIDS cases reported in all the Marzes of the RA8 is

presented in the table below (Table 1).

Table 1. HIV/AIDS Cases Reported in the RA, by Marzes9

Place HIV AIDS

N % N %

City of Yerevan 252 48.4 104 51.5

Gegharkunik 30 5.8 6 3.0

Shirak 51 9.8 17 8.4

Lori 46 8.8 18 8.9

Kotayk 22 4.2 12 5.9

Ararat 41 7.9 19 9.4

Armavir 35 6.7 16 7.9

Aragatsotn 13 2.5 5 2.5

Tavush 5 1.0 1 0.5

Syunik 13 2.5 3 1.5

Vayotz Dzor 3 0.6 - -

Unknown 10 1.9 1 0.5

Total 521 100 202 100

The HIV/AIDS epidemic in the RA is in the second - concentrated level8.

The HIV infection has high prevalence the majority of developing countries. The

HIV/AIDS epidemic has numerous social and economic consequences because of quite high

rates of HIV-caused morbidity and mortality in the economically active population.10

Estimates show that, before the year 2000, about 21 million people had died of AIDS, and

about 68 million will die during 2000-2020, unless wide-scale preventive and treatment

programs are carried out.11 The situation may even lead to an inadequacy of specialized labor

force in the country, which will become an obstacle to business and production development,

8 Republic of Armenia Ministry of Health National AIDS Prevention Center. 9 See Annex 1 for informational-statistical maps of HIV/AIDS Cases Reported in the RA. 10 Barnett T., Whiteside A., Guidelines for Studies of the Social and Economic Impact of HIV/AIDS, UNAIDS Best Practice Collection, Key Material, UANIDS, Geneva, Switzerland, 2000. 11 UNAIDS estimates for the next twenty years, HIV worldwide, AIDSmap, 18.06.2004.

3

as well as the prosperity of communities and households. Several African countries serve as

an example of this, where the situation has reached an extreme.12

Decades of global experience combating the consequences of HIV/AIDS have shown

that any response is most likely to succeed at a time when the HIV prevalence is relatively

low.13 Therefore, timely effective interventions can slow down and reverse the epidemic in

Armenia, and curb its impact on social and economic development.

Possible Scenarios of Development of the HIV/AIDS Epidemic in the RA

Methodology

For 2005-2015, the assessment of HIV prevalence and social and economic impact of

HIV/AIDS epidemic in the RA was performed using methods and computer software offered

by the UNAIDS.14 Statistical estimates were produced using the STATA software.15

The prevalence of HIV was assessed for each group of population at “higher” and

“lower” risk.16 The population at “higher” risk was defined to include IDUs, FSWs, MSM,

and male clients of FSW. The population at “lower” risk was defined to include the wives of

IDUs, male clients of FSWs, and MSM, non-regular partners of IDUs, as well as migrants

and their wives.

The results were used to estimate17 the HIV prevalence in the 15-49 age group. In

the estimates, it has been assumed that the sampling of populations at risk, which are

presented in the results of the Behavioral and Biological HIV Surveillance, reflects a picture

of the populations at risk in Armenia.

12 Barnett T., Whiteside A., Guidelines for Studies of the Social and Economic Impact of HIV/AIDS, UNAIDS Best Practice Collection, Key Material, UANIDS, Geneva, Switzerland, 2000. 13 The Socioeconomic Impact of HIV/AIDS in the Socialist Republic of Viet Nam, POLICY Project in collaboration with the Community of Concerned Partners, Viet Nam June 2003. 14 Methods and assumptions for estimates, UNAIDS, retrieved on 20.06.2007 from http://www.unaids.org/en/HIV_data/Methodology/default.asp 15 Intercooled Stata 9.2 for Windows, SataCorp LP 16 Using the Workbook Method to Make HIV/AIDS Estimates in Countries with Low-level or concentrated epidemics, Manual, World Health Organization, Geneva, 2007 17 Estimating National Adult Prevalence of HIV-1 in Concentrated Epidemics, manual, UNAIDS, WHO, 2007.

4

The HIV prevalence in IDUs and estimates for 2005-2015 were made by the logistic

function used in Workbook18 software, taking into account their estimated number in the

RA19 and the prevalence of HIV infection in this group in 2000, 2002, and 2005.20

Prevalence in their wives and non-regular partners was calculated21 taking into consideration

the annual frequency of sexual intercourse, the prevalence of condom use with spouses and

non-regular partners, and the probability of HIV transmission during one unprotected

intercourse.22 The number of women infected during the preceding year was added to the

number for the following year. The average life expectancy of women living with HIV

without ART was factored in.23 After the wife became infected, her husband was no longer

treated as a source of risk, and the infected woman was included in the calculations for so

long as she was alive. IDUs have been assumed to have the same average frequency of

intercourse and the same percentage of spousal condom use as the general population. The

change in the number of IDUs over the years was calculated using the EPP software.

The HIV prevalence in FSWs and estimates for 2005-2015 was made using the EPP24

software. The number of FSWs was calculated on the basis of estimates for our region,25 and

the prevalence of HIV was calculated using data received from the BBS and the “Medical-

Scientific Centre of Dermatology and STI” CJSC of the RA. HIV prevalence in male clients

of FSWs was calculated using the average number of customers per FSW per annum, the

prevalence of protected intercourse, and the probability of HIV transmission during one

intercourse in the event of the FSW having or not having a STI.26 Condom use and STI

18 Using the Workbook Method to Make HIV/AIDS Estimates in Countries with Low-level or concentrated epidemics, Manual, World Health Organization, Geneva, 2007 19 Epidemiological Fact Sheets of HIV/AIDS and Sexually Transmitted Infections, Armenia, World Health Organization, UNICEF, UNAIDS, December 2006 20 Busel A., Grigoryal S, et al, HIV Surveillance in the Republic of Armenia 2000-2002, Yerevan 2002 Grigoryan S., Hakobyan A. et. al., Results of Behavioral and Biological Surveillance in the Republic of Armenia 2002 and 2005, p 14, Armenian National AIDS Foundation, Yerevan 2006. 21 Using the Workbook Method to Make HIV/AIDS Estimates in Countries with Low-level or concentrated epidemics, Manual, World Health Organization, Geneva, 2007 22 Grigoryan S., Hakobyan A. et. al., Results of Behavioral and Biological Surveillance in the Republic of Armenia 2002 and 2005, p 14, Armenian National AIDS Foundation, Yerevan 2006. Abrahamyan R., Jilavyan G. et al. A Clinical and Epidemiological Survey of Cervical Pre-Cancer/Cancer and STI Incidence, UNFPA, Republic of Armenia Ministry of Health, Republic of Armenia National Statistics Service, and Republic of Armenia Institute for Perinatology, Obstetrics, and Gynecology. Modeling the Expected Short-Term Distribution of Incidence of HIV Infections by Exposure Groups, Manual, Joint United Nations Program in HIV/AIDS, 2007 23 Spectrum 2007, Overview and New Changes, UNAIDS Reference Group on Estimates, Modeling and Projections, 2007 24 Methods and assumptions for estimates, UNAIDS, retrieved on 20.06.2007 from http://www.unaids.org/en/HIV_data/Methodology/default.asp 25 Development of the software packages, EPP v2 and Spectrum, and Measuring and tracking the epidemic in countries where HIV is concentrated among populations at high risk of HIV, Report of a meeting of the UNAIDS Reference Group for Estimates, Modeling and Projections held in Sintra, December 8-10th 2004, UNAIDS 26 Grigoryan S., Hakobyan A. et. al., Results of Behavioral and Biological Surveillance in the Republic of Armenia 2002 and 2005, p 14, Armenian National AIDS Foundation, Yerevan 2006.

Busel A., Grigoryal S, et al, HIV Surveillance in the Republic of Armenia 2000-2002, Yerevan 2002

5

prevalence in FSWs prior to 2004 were calculated using the 2002 BBS data, and, for 2004

and the years that followed, using the 2005 BBS data. The number of clients infected during

the preceding year was added to the number for the following year, considering the average

life expectancy of men living with HIV.27 Prevalence in the wives of clients was calculated

using the same method as in case of the wives of IDUs. The proportion of married and

unmarried clients was taken from the 2005 Demographic and Health Survey.28 It is assumed

that the client that became infected with HIV will not again have intercourse with a FSW

living with HIV. The change in the number of FSWs over the years was calculated in

proportion to the population change.

HIV prevalence in MSM was calculated using the data available for Yerevan for the

year 2000.29 Considering that in 2000, the majority of HIV cases were from Yerevan30 it was

decided to extrapolate the calculated number of cases for Yerevan to the whole of Armenia.

The projection prior to 2000 was carried out using the 2000 prevalence data, taking the year

1986 as the beginning of the epidemic.31 Subsequently, HIV prevalence was calculated32 on

the basis of the number of non-regular partners per annum, condom use, and STI prevalence.

To avoid the inflation of estimates, MSM, which have intercourse only with permanent

partners, are assumed not to contribute to spreading the HIV infection. Condom use and STI

prevalence in MSM prior to 2004 were calculated using the 2002 BBS data, and, for 2004

and the years that followed, using the 2005 BBS data. Prevalence in the wives of MSM was

calculated using the same method as in case of the wives of IDUs. The change in the number

of MSM over the years was calculated in proportion to the 15-49 male population change.

The prevalence of heterosexual HIV infection in migrants was estimated on the basis

of the annual number of returning labor migrants,33 data concerning their behavior abroad,34

Modeling the Expected Short-Term Distribution of Incidence of HIV Infections by Exposure Groups, Manual, Joint

United Nations Program in HIV/AIDS, 2007 27 Spectrum 2007, Overview and New Changes, UNAIDS Reference Group on Estimates, Modeling and Projections, 2007 28 National Statistical Service [Armenia], Ministry of Health [Armenia], and ORC Macro. 2006. Armenia Demographic and Health Survey 2005. Calveton, Maryland: National Statistical Service, Ministry of Health, and ORC Macro. 29 Epidemiological Fact Sheets of HIV/AIDS and Sexually Transmitted Infections, Armenia, World Health Organization, UNICEF, UNAIDS, December 2006 30 Republic of Armenia Ministry of Health National AIDS Prevention Center. 31 Estimating National Adult Prevalence of HIV-1 in Concentrated Epidemics, manual, UNAIDS, WHO, 2007. 32 Busel A., Grigoryal S, et al, HIV Surveillance in the Republic of Armenia 2000-2002, Yerevan 2002 Grigoryan S., Hakobyan A. et. al. Using the Workbook Method to Make HIV/AIDS Estimates in Countries with Low-level or concentrated epidemics, Manual, World Health Organization, Geneva, 2007 33 Minasyan A., Hancilova B., Labor Migration from Armenia in 2002-2005, A Sociological Survey on Households, OSCE and Advanced Social Technologies NGO, December 2005.

6

and HIV prevalence in the general population and FSWs at their main destinations (Moscow,

St. Petersburg, other parts of RF, and the Ukraine).35 The estimates began from 1999,

because in Russia (the main destination of migrants), the majority of HIV cases were reported

starting from 1999.36 The number of returning male labor migrants during 1999-2006 was

projected on the basis of the net emigration figure for those years. For the years that

followed, it was assumed to be constant. HIV prevalence in FSWs and the general

population abroad was considered to be the same according to data for 2004 and 2005. As

the share of FSWs in the number of non-regular partners was unknown, it was assumed that

the half of the non-regular partners were FSWs, while the remaining 50% were from the

general population. HIV prevalence in the wives of migrants was estimated using the same

method as for wives of IDUs.

The social and economic impact of HIV/AIDS epidemic was esimated using the

“Spectrum 3” software. 1986 was taken as the baseline year for the demographic

projection,37 which was two years before the first reported HIV case in Armenia.38

Projections have been made for up to 2015.

The software data input, which for Armenia had been calculated by the UN, was

partially used in the demographic projection.

The general birth rate for 2015 was assumed to be “high” (1.9) in view of the current

birth rate. An age breakdown of general fertility was taken from existing sources.39 The

same breakdown was maintained for up to 2015.

Net emigration for 2000-2006 was taken from data provided by the Migration Agency

of the RA Ministry of Territorial Administration.40 For 2007-2015, net emigration was

assumed to remain unchanged.

34 Grigoryan S., Hakobyan A. et. al., Results of Behavioral and Biological Surveillance in the Republic of Armenia 2002 and 2005, p 14, Armenian National AIDS Foundation, Yerevan 2006. 35 Sociological Impact of HIV/AIDS in Ukraine, International HIV/AIDS alliance in Ukraine, The World Bank, 2006 Summary country profile for HIV/AIDS treatment scale-up, Russian Federation, World Health Organization, December 2005 HIV and Sexually Transmitted Infections prevention among sex workers in Eastern Europe and Central Asia, Joint United Nations Program on HIV, 2006 Global Summary of AIDS Epidemic, Joint United Nations Program on HIV, December 2006. 36 Summary country profile for HIV/AIDS treatment scale-up, Russian Federation, World Health Organization, December 2005 37 Stover J., AIM version 4, A Computer Program for Making HIV/AIDS Projections and Examining the Social and Economic Impact of AIDS, Spectrum system of policy models, The Futures Group International, p. 8, March 2007 38 Grigoryan S., Hakobyan A. et. al., Results of Behavioral and Biological Surveillance in the Republic of Armenia 2002 and 2005, p 14, Armenian National AIDS Foundation, Yerevan 2006. 39 National Statistical Service [Armenia], Ministry of Health [Armenia], and ORC Macro. 2006. Armenia Demographic and Health Survey 2005. Calveton, Maryland: National Statistical Service, Ministry of Health, and ORC Macro. 40 The migration situation in the RA, Migration Agency, Ministry of Territorial Administration of Republic of Armenia

7

As a model of the infant mortality rate required by the “Spectrum” software, the

“Coale-Demeny North” model was chosen, which was the closest to the infant mortality rate

in Armenia.41

Data on HIV/AIDS prevalence in 15-49 age group was calculated by the

aforementioned methodology.

The number of pregnant women receiving treatment to prevent mother-to-child

(vertical) HIV transmission and the number of adults receiving ART were provided by the

NCAP of the RA Ministry of Health. For 2007-2015, it was assumed that the average

percentage of pregnant women living with AIDS receiving preventive treatment in the total

number of people needing treatment will remain the same as in 2005 and 2006. The

percentage of adults needing antiretroviral treatment in the total number of people needing

treatment was assumed to remain the same as in 2006. It is assumed that second-line

antiretroviral treatment will be provided to everyone who needs it. The number of pregnant

women and adults needing treatment was taken from the Spectrum software. The treatment

of children, too, was estimated using the method described above.

The feeding method of children born to women living with HIV (breastfeeding,

mixed, or artificial feeding) was estimated in accordance with the feeding method of known

women living with HIV42 and a breakdown of the different infant feeding methods in the

general population.43

The number of first-time identified tuberculosis cases during 1995-2006 was taken

from data of the Armenian National Statistics Service. Tuberculosis incidence with HIV (%)

was estimated using the existing sources.44 The 2006 value was taken for the period through

2015.

The percentage of never-married women of ages 15-19 was taken from the Armenia

Demographic and Health Survey.45 The percentage of married women with a monogamous

family was taken as 100, assuming that all married women in Armenia have one husband at a

time.

Other inputs were made in accordance with data generated by the software.

41 National Statistical Service [Armenia], Ministry of Health [Armenia], and ORC Macro. 2006. 42 Republic of Armenia Ministry of Health National AIDS Prevention Center. 43 National Statistical Service [Armenia], Ministry of Health [Armenia], and ORC Macro. 2006. 44 Republic of Armenia Ministry of Health National AIDS Prevention Center. 45 National Statistical Service [Armenia], Ministry of Health [Armenia], and ORC Macro. 2006.

8

Scenarios

The pessimistic, medium, and optimistic scenarios were built in accordance with the

upper limit, medium and lower limit values of estimates on HIV prevalence in populations at

risk. The results can be seen in the figure 1. Under the pessimistic scenario, the number of

people living with HIV in Armenia will be more than 11,000 in 2015. The prevalence of HIV

in the 15-49 population will be about 0.57%, which is only about 2.5-fold lower than the

current HIV prevalence in the Ukraine, which has the highest HIV prevalence in Europe and

the former Soviet Union and is moving from a concentrated state towards a generalized one.46

Under the medium and optimistic scenarios, prevalence in the 15-49 population will be

0.13% and 0.062%, respectively.

Figure 1. HIV Prevalence in the 15-49 Population, under Different Scenarios of HIV/AIDS Epidemic Development

0.00%0.05%0.10%0.15%0.20%0.25%0.30%0.35%0.40%0.45%0.50%0.55%0.60%

1985 1990 1995 2000 2005 2010 2015 2020

Optimis tic Medium Pess imis tic

The other scenarios were built subject to certain reservations for risk groups. In the

first case, it is assumed that, starting from 2005, HIV prevalence among IDUs will remain the

same. Considering that the current trends show that HIV prevalence among IDUs in Armenia

is gradually declining, the situation under our scenario should deteriorate (Figure 2).

46 Country Situation Analysis, Ukraine, Joint United Nations Program on HIV, 2007

9

Figure 2. Projected HIV prevalence in the 15-49 population, considering current trends of HIV prevalence among IDUs and that starting from 2005, HIV prevalence among

IDUs will remain the same

0.00%

0.02%

0.04%

0.06%

0.08%

0.10%

0.12%

0.14%

0.16%

0.18%

0.20%

1985 1990 1995 2000 2005 2010 2015 2020

Current the same among IDUs

Under the other scenarios, it is assumed that HIV prevalence among FSWs, MSM,

and migrants will remain unchanged after 2005. In this case, the situation will be more

favorable than under the current trends (Figure 3). This figure can be considered to reflect

the contribution of different groups at risk to the HIV epidemic development trends in

Armenia.

Figure 4 presents a clearer picture of the contributions of different groups at risk to the

development of HIV/AIDS epidemic in the RA. It is clear from Figure 4 that IDUs have the

greatest impact on HIV proliferation trends than other groups at risk. IDUs are followed by

MSM and FSWs. Migrants infected through heterosexual contact have the smallest impact.

10

Figure 3. Projected HIV prevalence in the 15-49 population, considering current trends of HIV prevalence among risk groups and that starting from 2005, HIV prevalence

among risk groups will remain the same

0.00%

0.02%

0.04%

0.06%

0.08%

0.10%

0.12%

0.14%

1985 1990 1995 2000 2005 2010 2015 2020

Current % among migrants constant% among FSWs constant % among MSM constant

Figure 4. Change in projected HIV prevalence in the 15-49 population in 2015, considering that starting from 2005, HIV prevalence among risk groups will remain the

same

0.00%

0.01%

0.02%

0.03%

0.04%

0.05%

0.06%

0.07%

% among IDUsconstant

% among MSMconstant

% among FSWsconstant

% among migrantsconstant

11

Considering that the probability of HIV transmission through intercourse is three

times higher in people living with HIV, which have STIs,47 it was decided to compare the

current trends with a hypothetical situation in which FSWs and MSM have had no STIs since

200048 (Figure 5). The Figure shows that the difference is insignificant.

Figure 5. Projected HIV Prevalence in the 15-49 Population with FSW and MSM Having or Not Having STIs

0.00%

0.02%

0.04%

0.06%

0.08%

0.10%

0.12%

0.14%

1985 1990 1995 2000 2005 2010 2015 2020

With STIs Without STIs

47 Modeling the Expected Short-Term Distribution of Incidence of HIV Infections by Exposure Groups, Manual, Joint United Nations Program in HIV/AIDS, 2007 48 Other risk groups were not taken into account due to the absence of data on STI incidence in such groups for one year.

12

The next scenario implies that the 2000-2002 HIV prevalence trends remain

unchanged (the National HIV/AIDS Prevention Program was implemented during 2002-

2006). To build this scenario, it was assumed that the growth pace of HIV prevalence in

IDUs remained the same as during 2000-2002. HIV prevalence in FSWs was projected on

the basis of data before 2002. STI prevalence and condom use in FSWs and MSM were

assumed to remain unchanged (Figure 6).

Figure 6. Projected HIV Prevalence in the 15-49 Population with Current Trends and 2000-2002 Trends of HIV Prevalence, According to the Medium Scenario

0.00%

0.05%

0.10%

0.15%

0.20%

0.25%

0.30%

0.35%

0.40%

0.45%

0.50%

1985 1990 1995 2000 2005 2010 2015 2020

Current Progress under 2000-2002 trend

Under this scenario, HIV/AIDS prevalence in the age group 15-49 could be about

twice higher in 2007 than the current situation (Figure 6).

Under the pessimistic scenario, HIV prevalence in 2015 would reach 1.54%, i.e.

worse than the current situation in the Ukraine, which has the highest HIV prevalence in

Europe and the former Soviet Union (Figure 7).

.

13

Figure 7. Projected HIV Prevalence in the 15-49 Population with Current Trends and 2000-2002 Trends of HIV Prevalence, According to the Medium Scenario

0.00%

0.20%

0.40%

0.60%

0.80%

1.00%

1.20%

1.40%

1.60%

1.80%

1985 1990 1995 2000 2005 2010 2015 2020

Pessimistic Progress under 2000-2002 trend

Chapter 2. POSSIBLE SOCIAL AND ECONOMIC IMPACT OF THE HIV/AIDS EPIDEMIC IN THE REPUBLIC OF ARMENIA

Correlation Between HIV/AIDS Epidemic and Social and Economic Development of a

Society

HIV/AIDS affects the development of society in numerous ways. Growing

prevalence of HIV/AIDS can also curb economic growth of a country. The economic impact

is based on the preliminary assumption that there is an established correlation between public

health and economic development,49 which justifies a stronger emphasis in poverty reduction

strategies on health.50

49 The correlation between health and economic growth was confirmed in papers by Cuddington and Hancock (1994), Haacker (2004), and others. 50 Russell, S. “The Economic Burden of Illness for Households in Development Countries: A review of studies focusing on malaria, tuberculosis, and human immunodeficiency virus/acquired immunodeficiency syndrome,” American Journal of Tropical Medicine and Hygiene 71 (S2, 2004):147–155.

14

There are numerous ways in which HIV/AIDS can affect macroeconomic growth.

The most evident and direct impact is that on productivity and the size of labor force caused

by disease and death of the economically active population.51 The epidemic can also affect

macroeconomic growth by changing the distribution of resources between consumption and

savings. Growing costs lower disposable income, which can contribute to a higher household

consumption/savings ratio, which in turn will undermine investment and economic growth.52

Moreover, HIV/AIDS affects macroeconomic performance through the so-called “side

effects.”53 The epidemic also affects the health sector by necessitating additional costs.

HIV/AIDS is characterized as a poverty disease. Not only poverty facilitates the

spread of HIV, but also the ensuing AIDS drives people into poverty or makes it difficult for

people to avoid poverty. Poverty greatly increases vulnerability to HIV/AIDS, and the

pandemic hits socially and economically vulnerable groups of the population harder, with

direct and indirect consequences for poverty reduction (concerning the correlation between

poverty and HIV/AIDS, see Figure 8).

First of all, the epidemic generally has a disproportionate impact on lower-income

individuals, which makes them more vulnerable and poorer. Secondly, by slowing down

economic growth, it minimizes the ability of poor people to avoid poverty. Extreme poverty

is closely correlated to HIV/AIDS. National poverty reduction strategies enable the

consideration of HIV/AIDS problems from the viewpoint of development, finding concurrent

and effective solutions for essential problems of both HIV/AIDS and poverty.

51 Greener, R, “The Impact of HIV/AIDS on Poverty and Inequality,” Chapter 5 in The Macro-economics of HIV/AIDS, Ed. Markus Haacker, International Monetary Fund, Washington DC, 2004. 52 Casale, M. and Whiteside, A. “The Impact of HIV/AIDS on Poverty, Inequality and Economic Growth,” IDRC Working Paper on Globalization, Growth and Poverty, March 2006 <http://www.idrc.ca/uploads/user-S/11438239471GGPWP3-AIDS.pdf>. 53 Nattrass, N., “Aids, Growth and Distribution in South Africa,”, Centre for Social Science Research, Aids and Society Research Unit, CSSR Working Paper No. 7, 2002.

15

Figure 8. Links between Poverty and HIV/AIDS

Poverty

− Desperation − Forced labor emigration − Limited accessibility of

public health − Limited opportunities of

education − Limited living conditions

(water, sewerage, and the like)

− Malnutrition − Survival risk behavior (sex

work and the like)

HIV/AIDS

− Direct and indirect costs of HIV

− Direct and indirect costs of mortality due to HIV/AIDS

− Falling productivity and absenteeism-caused loss of revenue

− Job loss − Changes in household

composition − Children detached from

school − Rejection by society

The study analyzes three main aspects of the social and economic impact of

HIV/AIDS in Armenia:

• First, an assessment of the impact on labor force and fiscal revenue. The sex and

gender structure of the population is taken from data generated for Armenia through

the Spectrum54 package.

• Second, an assessment of the impact on the health sector. Health costs and demand

for ART in Armenia are modeled with the use of the Spectrum package.

• Third, an assessment of the impact on economic growth of different scenarios of

HIV/AIDS epidemic development.

A baseline “No AIDS” scenario and three “with AIDS” scenarios (optimistic,

medium, and pessimistic) have been considered, which were built in accordance with the

maximum, minimum, and average values of estimates on HIV prevalence in populations at

risk.55 Spectrum output demographic data was used as input data for each scenario.

54 The Spectrum package was developed by The Futures Group in 1999, and Spectrum 2007 can be accessed at: <www.unaids.org/en/HIV_data/Epidemiology/epi_software2007.asp>£55 Details of the scenarios are presented in the first chapter of the report.

16

Impact on Labor Force

As a first step, the “No AIDS” scenario was considered: for this scenario, five-year

numbers of the working-age population, broken down by sex, were taken from the Spectrum

demographic projection. It has been estimated that the working-age population will grow by

228,559 (10.4%) during 2007-2015. The size of the economically active population was

projected on the basis of the 2005 actual numbers of labor force participation,56 as well as the

International Labor Organization (ILO) estimates of the size of the economically active

population in Armenia in 2010, broken down into 13 age groups.57 For the other years, the

labor force participation numbers were determined on the basis of the average annual growth

rate. The economically active population has been estimated to grow by 265,588 during

2007-2015. In the structure of labor force, the share of men will continue to grow (following

a growth trend, from 51.9% in 2001 to 52.4% in 2005), reaching 59.3% during the projected

period. To calculate the number of the employed, employment shares for the previous period

were used. Calculation was done on the basis of the following formula:

Est+1= EAPt+1 * (Est/EAPt)

Under this scenario, total employment will grow by 22.9% during the projected nine

years to reach 1.27 million people. Under the ILO methodology, the number of the employed

was determined as the difference between the economically active population and the number

of the employed. Details are presented in Table 2.

Table 2. Change in Labor Market Indicators, 2007-2015, “No AIDS” Scenario

“No AIDS” scenario

Item 2007 2015

Absolute growth

2007-2015 Percentage growth

Working-age population 2,197,736 2,426,295 228,560 10.4

Economically active

population

1,340,619 1,606,207 265,588 19.8

Employed 1,029,048 1,265,144 236,096 22.9

Unemployed 311,571 341,063 29,492 9.47

56 Labor Market in the Republic of Armenia 2002-2005. Republic of Armenia National Statistics Service, 2006. 57 “Economically active population by sex, 13 age groups (ILO estimates/projections,” Armenia, United Nations Statistics Division, <http://unstats.un.org/unsd/cdb/cdb_dict_xrxx.asp?def_code=36>.

17

As the next step, three epidemic scenarios (optimistic, medium, and pessimistic) were

considered. The projection showed that the working-age population, the economically active

population, and the number of the employed are growing more rapidly under the “No AIDS”

scenario than under any of the three epidemic scenarios.

The total working-age population is projected to increase by 224,000-228,000 from

2007 to 2015, depending on the scenario (Figure 9).

Additional losses of the working-age population due to the impact of HIV/AIDS

epidemic are presented in Table 3.

Depending on the scenario, the economically active population (EAP) number grows

under all three scenarios by 263,100-265,200. Figure 10 and Table 4, respectively, present

the absolute and relative additional losses of the economically active population due to the

impact of HIV/AIDS epidemic.

Figure 9. Projected Working-Age Population under Different Scenarios of HIV/AIDS Epidemic Development, 2007-2015 (thousand)

2,050

2,100

2,150

2,200

2,250

2,300

2,350

2,400

2,450

2007 2008 2009 2010 2011 2012 2013 2014 2015

No AIDS Optimistic Medium Pessimistic

18

Table 3. Estimated Loss of Working-Age Population Due to the HIV/AIDS Epidemic, 2007 and 2015 (comparable description)

Growth Additional Loss due to HIV/AIDS

Scenario

Working-age

population,

2007

Working-age

population,

2015 Total Total

% relative to

“No AIDS”

scenario

No AIDS 2,197,736 2,426,295 228,559 - -

Optimistic 2,197,480 2,425,500 228,020 539 0.022

Average 2,197,236 2,424,556 227,320 1,239 0.005

Pessimistic 2,196,490 2,421,399 224,909 3,650 0.15

Figure 10. Projected Losses of EAP under Different Scenarios of HIV/AIDS Epidemic Development, 2007-2015

-

500

1,000

1,500

2,000

2,500

3,000

3,500

2007 2008 2009 2010 2011 2012 2013 2014 2015

No AIDS-Opt. No AIDS-Med. No AIDS-Pess.

19

Table 4. Estimated Losses of EAP Due to the HIV/AIDS Epidemic, 2007 and 2015 (comparable description)

Growth Additional Losses Due to HIV/AIDS

Scenario EAP

2007

EAP

2015 Total Total

% relative to

“No AIDS”

scenario

No AIDS 1,340,619 1,606,207 265,588 - -

Optimistic 1,340,463 1,605,681 265,218 370 0.023

Average 1,340,314 1,605,056 264,742 844 0.053

Pessimistic 1,339,859 1,602,966 263,107 2,481 0.154

The employed population number, too, grows under all three scenarios, by 233,600-

235,700. Additional losses of the employed population due to the impact of HIV/AIDS are

presented in Figure 11 and Table 5.

Figure 11. Projected Loss of Employed Population under Different Scenarios of

HIV/AIDS Epidemic Development, 2007-2015

-

500

1,000

1,500

2,000

2,500

3,000

3,500

2007 2008 2009 2010 2011 2012 2013 2014 2015

No AIDS-Opt. No AIDS-Med. No AIDS-Pess.

20

Table 5. Estimated Losses of Employed Population Due to the HIV/AIDS Epidemic, 2007 and 2015 (comparable description)

Growth Additional Losses Due to HIV/AIDS

Scenario

Employed

population,

2007

Employed

population,

2015 Total Total

% relative to

“No AIDS”

scenario

No AIDS 1,029,048 1,265,144 236,097 - -

Optimistic 1,028,886 1,264,614 235,728 369 0.029

Average 1,028,733 1,263,994 235,261 836 0.066

Pessimistic 1,028,261 1,261,917 233,656 2,441 0.19

Impact on State Budget and Social Contributions

The study has evaluated the revenue losses (including unpaid income tax and social

contributions) and additional costs (including disability pensions, temporary incapacity

allowances, and orphanage care of children that lost both parents) of the state budget and

social insurance agencies caused by the epidemic. The decline in revenues and the upsurge in

costs are due to the impact of HIV/AIDS in terms of a lower number of the employed and a

higher number of persons that cannot work due to their health condition.

Revenue losses in the form of unpaid taxes and social contributions have been

estimated for the three scenarios of HIV/AIDS epidemic development (optimistic, medium,

and pessimistic).

Revenues not paid due to shrinking of the labor force were estimated on the basis of

the employment figures and projected average monthly wages under the three epidemic

scenarios during 2007-2015. The average personal income tax rate was assumed to be 11%,

which was assumed to remain unchanged through 2015. The results of this analysis are

presented in Tables 6 and 7.

Table 6 shows that the revenue loss grows over time, because employment growth

slows down during 2007-2015. On the whole, revenue losses of the budget and social

agencies in 2015 are estimated to reach 435-2,648 million drams, depending on the scenario,

and total losses during 2007-2015 are estimated to reach 2-10.8 billion drams.

21

Additional costs of the state budget and social agencies were estimated with three

components: payment of disability pensions to people living with HIV/AIDS and under-16

children living with HIV, temporary incapacity allowances to employed persons living with

HIV/AIDS, and state costs of orphanage care of children that lost both parents due to

HIV/AIDS.

Table 6. Employment Reduction Relative to “No AIDS” Baseline Scenario

2007 2008 2009 2010 2011 2012 2013 2014 2015

Optimistic

Total 162 211 259 312 360 403 449 490 530

Men 146 187 228 273 314 350 387 423 455

Women 16 24 31 39 46 53 62 67 76

Medium

Total 315 419 524 638 748 848 954 1,052 1,151

Men 283 372 462 559 653 735 822 906 986

Women 32 48 62 79 96 113 132 146 165

Pessimistic

Total 787 1,035 1,290 1,580 1,875 2,166 2,504 2,576 3,228

Men 707 918 1,138 1,385 1,636 1,876 2,158 2,451 2,764

Women 79 117 152 195 239 290 346 124 464

Difference (total)

Med. – Opt. 153 208 264 326 388 445 506 562 621

Pess. – Aver. 472 616 766 942 1,127 1,318 1,549 1,523 2,077

Pess. – Opt. 625 824 1,030 1,268 1,515 1,763 2,055 2,085 2,698

During the study, it was assumed that a person living with HIV develops AIDS in the

fifth year of the disease. This assumption is in line with survey assumptions for Russian

Federation and the Ukraine.58 Besides, it was assumed that 30% of people living with

HIV/AIDS become disabled and may apply to get a disability pension. Moreover, under-15 58 “Socioeconomic Impact of HIV/AIDS in Ukraine.” 2006. The World Bank. International HIV/AIDS Alliance in Ukraine;

Misikhina S., Pokrovsky P., Mashkilleyson N., Pomazkin D., A model of social policy costs of HIV/AIDS in the Russian Federation,” International Labor Office.

22

children living with HIV were also taken into account, because they enjoy the rights provided

by Armenian law for under-16 children with disabilities. To estimate the additional costs of

disability pensions under the three epidemic scenarios, data on the number of persons

becoming infected with HIV during 2000-2010 generated by Spectrum package was used. It

was assumed that 50% of those receiving the disability pension would continue receiving it in

the second year, and 30% - in the third year, as well. The additional costs of disability

pensions are presented in Table 8.

The study estimates supported the conclusion that, during 2007-2015, disability

pension costs may grow 1.6-4-fold: they will reach 29.5 million drams in 2015 under the

optimistic scenario and 180.62 million (1.77% of all disability pensions paid in Armenia in

2005) under the pessimistic scenario.59

The next component of additional costs is the temporary incapacity allowance paid to

people living with HIV/AIDS. These amounts were estimated on the basis of a number of

assumptions:

• The average annual number of sick days per employed person with HIV was assumed

to be 4.60

• Employees were assumed to be paid the full amount of their salary in case of

temporary incapacity.

• The ratio of the number of people living with HIV/AIDS to the number of working-

age people living with HIV/AIDS was assumed to correspond to the ratio of total

employed persons to the working-age population.

The estimates are based on average wage projections made by the Central Bank of

Armenia for the period up to 2015. The additional costs of temporary incapacity, estimated

under this method in connection with the spread of HIV/AIDS during 2007-2015 for each of

the three scenarios, are presented in Table 8. In 2015, these costs are between 17 and 140

million drams. In general, these costs are rather large under the pessimistic scenarios, when

they exceed 5-8-fold the costs under the optimistic scenario. Additional costs of the state

budget and social agencies in respect of disability pensions and temporary incapacity

allowances will total 278-1,564 million drams during 2007-2015, depending on the scenario.

59 For 2005, the average disability pension amount and the number of those receiving disability pensions are taken from the Armenia Statistical Yearbook 2006. 60 This number has been matched with the number of planned tests of HIV/AIDS patients, which is 4 when the number of CD+ cells is below 350, and 2 when the number is above 350. Besides, it is close to 3.9—the number used in the “Socioeconomic Impact of HIV/AIDS in Ukraine” (2006) survey.

23

Table 7. Revenue Losses of State Budget and Social Agencies Due to HIV/AIDS-Caused Employment Reduction, 2007-2015

2007 2008 2009 2010 2011 2012 2013 2014 2015

Optimistic

Unpaid personal income tax 15,939,235 24,192,776 34,090,748 46,323,806 60,160,356 75,376,197 91,406,734 108,896,403 128,279,109

Unpaid social contributions 38,109,263 57,842,728 81,507,879 110,756,010 143,837,942 180,217,634 218,545,191 260,361,401 306,703,689

Medium


Unpaid social contributions 74,174,867 115,015,453 164,640,038 226,558,682 298,636,318 379,128,646 464,943,982 558,653,870 665,750,661

Pessimistic


Unpaid social contributions 185,150,926 284,014,132 405,398,922 560,833,056 748,341,468 968,245,637 1,219,736,958 1,367,266,115 1,867,191,373

Difference between scenarios

Unpaid personal income tax (medium – optimistic) 15,084,473 23,912,547 34,770,105 48,434,578 64,744,568 83,194,720 103,056,529 124,761,109 150,171,737

Unpaid personal income tax (pessimistic – medium) 46,415,842 70,683,858 100,697,632 139,810,575 188,089,606 246,398,741 315,692,880 338,202,840 502,503,720

Unpaid personal income tax (pessimistic – optimistic) 61,500,315 94,596,405 135,467,737 188,245,153 252,834,174 329,593,462 418,749,408 462,963,949 652,675,457

Unpaid social contributions (medium – optimistic) 36,065,605 57,172,725 83,132,159 115,802,672 154,798,376 198,911,013 246,398,791 298,292,470 359,046,972

Unpaid social contributions (pessimistic – medium) 110,976,059 168,998,679 240,758,883 334,274,375 449,705,150 589,116,991 754,792,976 808,612,245 1,201,440,712

Unpaid social contributions (pessimistic – optimistic) 147,041,663 226,171,405 323,891,043 450,077,047 604,503,526 788,028,003 1,001,191,767 1,106,904,714 1,560,487,684

24

Table 8. Additional Costs of State Budget and Social Agencies Due to HIV/AIDS, 2007-2015

2007 2008 2009 2010 2011 2012 2013 2014 2015

Optimistic

Disability pension 16,305,150 11,859,692 10,305,403 11,766,815 15,803,719 20,353,304 25,275,308 29,253,243 29,533,948

Temporary incapacity allowance 5,292,974 6,707,520 8,063,340 9,496,986 10,932,163 12,338,297 13,632,184 15,074,876 17,100,286

Average



Pessimistic



Difference between scenarios

Disability pension (medium – optimistic) 6,029,590 6,746,707 7,933,546 9,340,562 11,079,656 13,460,636 16,386,367 19,056,695 11,114,936

Disability pension (pessimistic – medium) 22,766,058.99 28,782,844.08 40,403,051.95 56,667,040.33 74,984,261.96 93,885,819.01 112,593,893.89 132,030,652.74 139,972,412

Disability pension (pessimistic – optimistic) 28,795,648.77 35,529,551.00 48,336,598.22 66,007,602.41 86,063,918.44 107,346,455.40 128,980,261.17 151,087,348.19 151,087,348

Temp. incapacity allowance (medium – optimistic) 5,824,390 6,803,235 7,894,917 8,968,713 10,151,750 11,373,831 13,109,870 15,708,031 15,708,031

Temp. incapacity allowance (pessimistic – medium) 23,345,085 31,152,986 38,847,551 48,730,574 60,521,098 73,434,211 88,225,257 107,741,647 107,741,647

Temp. incapacity allowance (pessimistic – optimistic) 29,169,475 37,956,221 46,742,468 57,699,287 70,672,848 84,808,042 101,335,127 123,449,678 123,449,678

25

The next estimated component of non-health costs is the cost of orphanage care of

children that will lose both parents due to HIV/AIDS. For purposes of the study, it has been

assumed that all of these children will need state-funded care. The estimate was made on the

basis of Spectrum’s data on the number of children who will lose both parents during 2007-

2015 and the average actual daily orphanage care cost per child (3,000 drams), which was

inflation-adjusted for the future years. These additional costs vary between 19 and 124

million drams, depending on the scenario (Figure 12). Under the pessimistic scenarios, the

costs would be 6.5-fold higher than under the optimistic one.

Figure 12. Estimated Additional Costs of Orphanage Care, 2007-2015 (drams million)

0

20

40

60

80

100

120

140

2007 2008 2009 2010 2011 2012 2013 2014 2015

Optimistic Medium Pessimistic

Table 9 presents total estimates of additional non-health costs/losses of the 2015 state

budget under the three scenarios. The HIV/AIDS epidemic-related health costs are

estimated in the next section.

26

Table 9. Total Additional Non-Health Costs/Losses Related to HIV/AIDS Epidemic Development, 2015 (drams million)

Optimistic Average Pessimistic

Revenue losses 434.98 944.2 2,648.14

Additional costs, of which:

Disability pensions 29.5 48.6 180.6

Temporary incapacity

allowances 17.1 32.8 140.55

Orphanage costs 19.15 43.78 124.5

Total costs 65.75 125.18 445.65

Total 500.73 1,069.38 3,093.79

Thus, total additional non-health costs/losses will reach 500.8-3,093.8 million in

2015; the sum of losses/costs during 2007-2015 will reach 2.4-13.2 billion drams, depending

on the scenario.

Estimated Macroeconomic Costs of the HIV/AIDS Epidemic

This study has estimated the macroeconomic costs of the HIV/AIDS epidemic on the

basis of a neoclassical growth model—the Solow model. The analysis was carried out using

a classical one-sector two factor growth model to project the economic growth trajectory in

Armenia under each of the three scenarios of the HIV/AIDS epidemic.

The literature on estimates of the macroeconomic costs of the HIV/AIDS epidemic

mainly presents three groups of models that are applied in this sector. The models include

neoclassical growth models, different types of quantifiable overall balance macroeconomic

models, and macroeconometric models.61 According to some surveys, in different countries,

the contraction of annual GDP growth due to HIV/AIDS may reach 0.3-5%, while per capita

GDP growth may contract by as much as 1%.62 The estimates for the Ukraine indicate that,

61 Haacker, M. ed. 2004. The Macroeconomics of HIV/AIDS. Washington, DC: International Monetary Fund; Cuddington, J. T., and J. D. Hancock. 1994. “Assessing the Impact of AIDS on the Growth Path of the Malawian Economy.” Journal of Development Economics 43(2): 363-68; Cuddington, J. T., J. D. Hancock, and C. A. Rogers.1994. “A Dynamic Aggregate Model of the AIDS Epidemic with Possible Policy Interventions.” Journal of Policy Modeling 16(5): 473-96; Haacker, M. 2004. HIV/AIDS: Impact on the Social Fabric and the Economy.” In The Macroeconomics of HIV/AIDS, ed. M. Haacker. 62 “The macroeconomic impact of HIV/AIDS under alternative intervention scenarios (with specific reference to ART) on the South African economy.” June 2006. Bureau for Economic Research. University of Stellenbosch.

27

in 2014, output may contract by 0.7-1.3%, while average annual growth during 2004-2014

may slow down by 0.06-0.11%.63

This study applies the simple growth model used for the Ukraine64 in order to make

estimates for the “No AIDS” and the three epidemic scenarios. This model is similar to the

model developed for Russia by the World Bank.65 The demographic and epidemiological

data estimated in the previous sections and the labor force quantitative projections have been

used as input data for the model.

The model used is as follows: output (Y) depends on labor force (L) and capital (K) in

accordance with the Kobb-Douglas production function:

Yt=At *Ktα * Lt

β,

where A is total factor productivity, which is assumed to be 2-3% in the model.66 The share

of capital (α) is assumed to be 0.333, while the share of labor force (β) is 0.667.67 Capital

growth is estimated using the following formula:

Kt=Kt-1 * (1-δ) +It-1

where depreciation is assumed to be 5% (5%) (δ=0.05).

Investments consist of public and private investments:

It = It private + It public

Investments are equal to savings, while consumption is determined using the residual

method, by deducting savings from output.

It =St

Yt= It + St£

The tax rate (τ) is assumed to be equal to the average actual rate of all taxes (17.5%).

Private investment, as a share of output, was determined using the following formula:

It private =stprivate * (1-τ) Yt,

where stprivate is assumed to be 30%.

Public investment was calculated in the following way:

It public=stpublic * max (0, CBSt),

63 “Socioeconomic Impact of HIV/AIDS in Ukraine.” 64 “Socioeconomic Impact of HIV/AIDS in Ukraine.” 65 Ruehl, C., V. Pokrovsky and V. Vinogradov. 2002. “The Economic Consequences of HIV in Russia.” World Bank, Moscow, Russia. 66 Saumya Mitra, Douglas Andrew, Gohar Gyulumyan, Paul Holden, Bart Kaminski, Yevgeny Kuznetsov, Ekaterine Vashakmadze. The Caucasian Tiger: Sustaining Economic Growth in Armenia. 2007. The International Bank for Reconstruction and Development. The World Bank. For instance, a 2% increase is typical of economies like Korea. 67 Mnatzakanyan Rolan, Mkrtchyan Ashot, Assessing the Real GDP Gap for the Armenian Economy, Republic of Armenia Central Bank, Newsletter 2007.

28

where spublic is the share of public investment (22.8% in the model), and CBSt is the current

budget surplus, which is determined by deducting debt amortization, minimal public

spending (assumed to be 20% of GDP), and costs of diagnosing, treatment, and testing

HIV/AIDS from tax revenue. Budget size is determined in the following way:

Bt = τYt – Itpublic – (1+i) Dt-1 – MPEt –HEt£

The scenarios used in the model are based on the following assumptions concerning

access to antiretroviral treatment:

• The optimistic scenario assumes that the number of people receiving antiretroviral

treatment will grow during 2007-2015 from 20% to 60% of all those who need it;

• The medium scenario assumes that this ratio grows from 10% to 40%;

• Under the pessimistic scenario, it is assumed to grow from 6% to 13%.

Additional health sector costs due to the spreading of the HIV/AIDS epidemic are

estimated with three components: antiretroviral treatment costs, diagnostic costs, and

testing costs. Antiretroviral treatment costs were estimated using Spectrum data on the

number of people receiving such treatment under each of the epidemic scenarios. People

receiving both first-line and second-line therapy were considered. For the projected period,

the treatment cost per patient was assumed to remain unchanged from the present level, i.e.

1,710,000 drams for first-line and 3,338,000 drams for second-line therapy.68

Diagnostic costs were estimated by multiplying the Spectrum data69 on the annual

number of new HIV/AIDS cases by the average cost of diagnosing one person (102,300

drams according to data provided by the National HIV/AIDS Prevention Center). This cost

has been assumed to remain unchanged during the whole projection period. Total costs of

testing were estimated by multiplying the annual number of tested persons by the average

cost per test (9,300 drams according to data provided by the National HIV/AIDS

Prevention Center). The total number of persons being tested under each scenario was

estimated in different ways, assuming that it will be about 60,000 in 2007. Under the

optimistic scenario, it was assumed to grow by 5% per annum in the years ahead. Under

the medium scenario, it was assumed to grow by 4%. Under the pessimistic scenario, it

was assumed to grow by 4% per annum until 2011 and remain unchanged thereafter.

Given these assumptions, additional health costs related to the HIV/AIDS epidemic will be

1.4-1.5 billion drams in 2015, depending on the scenario. Total additional health costs

68 Treatment prices were provided by the Republic of Armenia National AIDS Prevention Center. 69 Under the optimistic scenario it was assumed that each year, all new infected people will apply for a diagnosis; under the medium scenario – 30% of new infected, and under the pessimistic scenario – 15%.

29

during 2007-2015 will reach 9.6-9.8 billion drams. Starting from 2012-2013, cost under

the optimistic scenario is higher than costs under the medium and pessimistic scenario, due

to the higher number of persons tested and diagnosed. Detailed data is presented in Table

10. These costs are estimated to account for about 4.65-4.87% of the 2005 health costs of

the budget,70 depending on the scenario. One should consider that the scenarios vary

considerably in terms of output data on the epidemic (Table 11).

The neoclassical growth model has produced the following comparative data for 2015

relative to the “No AIDS” scenario:

• Nominal GDP growth will contract by 2.7-15.6 billion drams (0.04-0.21%) in 2015,

depending on the scenario. The total loss due to contraction of GDP growth during

2007-2015 will reach 12.8-38.7 billion, depending on the scenario.

• Nominal capital growth will contract by 2.5-11.3 billion drams (0.03-0.12%) in 2015,

and the total loss due to capital growth contraction during 2007-2015 will reach 10.1-

27.7 billion drams, depending on the scenario.

• Per capita GDP will shrink by 0.01%, 0.02%, and 0.06% under the optimistic,

medium, and pessimistic scenarios, respectively.

• Average annual GDP growth during 2007-2015 will slow down by 0.4-0.43%,

depending on the scenario.

• In 2015, the number of the employed will shrink by 3,228. The total loss of the

number of the employed during 2007-2015 will reach about 17,000.

• Labor force growth will slow down by 0.04%, 0.09%, and 0.26% under the

optimistic, medium, and pessimistic scenarios, respectively.

Detailed data for 2007-2015 is presented in Tables 12 and 13. These comparably not

high loses is explained by the concentrated stage of the epidemic and its still low prevalence

in Armenia. Results are consistent with findings of research in other countries.71 In any

event, losses of GDP, capital, and labor force under the pessimistic scenario will be 5-6-fold

higher in 2015 than under the optimistic scenario (Table 12).

70 Republic of Armenia Statistical Yearbook 2006, Republic of Armenia National Statistics Service, 2007. 71 Martin Wall, “Estimating the Economic Impact of HIV/AIDS on the Countries of the Former Soviet Union.” 2003. Overseas Development Institute, London.

30

Table 10. Estimated Health Costs of HIV/AIDS Diagnosis and Treatment,

2007-2015 (drams million)

2007 2008 2009 2010 2011 2012 2013 2014 2015

Optimistic

Antiretroviral

treatment 139.8 199.2 258.5 321.2 389.0 458.3 531.0 603.8 679.8

Diagnostic and

testing costs 566.9 597.1 627.1 656.4 688.2 720.1 755.4 794.2 834.9

Total 706.7 796.2 885.6 977.6 1,077.1 1,178.5 1,286.5 1,397.9 1,514.7

Average

Antiretroviral

treatment 141.5 202.6 261.9 326.4 392.4 463.5 536.2 610.6 686.6

Diagnostic and

testing costs 562.8 586.2 610.0 633.9 657.0 682.6 710.0 739.7 770.5

Total 704.3 788.8 871.9 960.3 1,049.4 1,146.1 1,246.2 1,350.3 1,457.1

Pessimistic

Antiretroviral

treatment 148.4 212.8 275.6 341.7 411.2 485.7 558.4 638.0 717.4

Diagnostic and

testing costs 569.8 593.8 618.1 642.6 667.1 667.9 669.2 671.6 674.6

Total 718.2 806.6 893.7 984.3 1,078.3 1,153.6 1,227.6 1,309.6 1,392.0

Difference (total)

Opt. – Med. 2.40 7.42 13.72 17.33 27.68 32.41 40.35 47.59 57.56

Med.– Pess. -13.9 -17.8 -21.8 -24.1 -28.9 -7.5 18.5 40.7 65.1

Opt.– Pess. -11.5 -10.4 -8.1 -6.7 -1.2 24.9 58.9 88.3 122.7

31

Table 11. Comparison of Some Indicators under Different Scenarios of HIV/AIDS Epidemic Development, 2015

Ratio Item Optimistic Medium Pessimistic

Med./Opt. Pess./Med. Pess./Opt.

Number of people living

with HIV 1,342 2,575 11,155 1.9 4.3 8.3

HIV prevalence in the

adult (15 and above)

population (in %)

0.05 0.09 0.4 1.8 4.4 8.0

HIV prevalence in 15–49

age group

(in %)

0.06 0.13 0.57 2.2 4.4 9.5

Number of new HIV

cases 102 292 1,538 2.9 5.3 15.1

Number of adults

needing antiretroviral

treatment

579 922 2,716 1.6 2.9 4.7

Number of annual AIDS

death cases 70 166 623 2.4 3.8 8.9

Total AIDS death cases 864 1,873 5,244 2.2 2.8 6.1

Number of orphans due

to AIDS 308 680 1,975 2.2 2.9 6.4

32

Table 12. Estimated Macroeconomic Indicators (drams billion)

2007 2008 2009 2010 2011 2012 2013 2014 2015

No AIDS

GDP 2,895.8 3,439.3 3,948.5 4,509.9 5,060.1 5,622.3 6,230.4 6,817.6 7,480.0 Capital 2,155.3 2,764.2 3,477.9 4,281.2 5,183.4 6,176.6 7,259.3 8,438.3 9,703.8 Labor force

(thousand) 1,029.0 1,100.4 1,132.2 1,171.8 1,193.4 1,210.0 1,233.0 1,242.0 1,265.1

Optimistic


(thousand) 1,028.9 1,100.1 1,131.9 1,171.5 1,193.0 1,209.6 1,232.6 1,241.5 1,264.6

Medium


(thousand) 1,028.7 1,099.9 1,131.7 1,171.1 1,192.7 1,209.2 1,232.1 1,241.0 1,264.0

Pessimistic


(thousand) 1,028.3 1,099.3 1,130.9 1,170.2 1,191.5 1,207.9 1,230.5 1,239.5 1,261.9

GDP difference (relative to “No AIDS” scenario)

Optimistic 0.38 0.55 0.82 1.06 1.34 1.63 1.97 2.33 2.73 Medium 0.69 1.03 1.53 2.04 2.64 3.29 4.04 4.86 5.76 Pessimistic 1.65 2.48 3.58 4.88 6.42 8.18 10.33 11.81 15.64 Capital difference (relative to “No AIDS” scenario)

Optimistic 0.18 0.26 0.57 0.75 0.97 1.25 1.59 2.00 2.48 Medium 0.22 0.38 0.81 1.15 1.60 2.17 2.87 3.73 4.75 Pessimistic 0.38 0.77 1.53 2.34 3.43 4.84 6.63 8.85 11.33 Labor force difference (relative to “No AIDS” scenario, thousand people)

Optimistic 0.16 0.21 0.26 0.31 0.36 0.40 0.45 0.49 0.53 Medium 0.32 0.42 0.52 0.64 0.75 0.85 0.95 1.05 1.15 Pessimistic 0.79 1.04 1.29 1.58 1.88 2.17 2.50 2.58 3.23

33

Table 13. Comparison of Growth Model Outcomes by Scenario, 2015

Difference Relative to

“No AIDS” Scenario Item No AIDS Opt. Medium Pess.

Opt. Med. Pess.

Pess.-Opt.

GDP

(AMD billion) 7479.97 7,477.24 7,474.21 7,464.33 -2.73 -5.76 -15.64 -12.91

GDP index

(2005 = 100) 333.33 333.21 333.08 332.64 -0.12 -0.25 -0.69 -0.57

Per capita GDP

(drams

thousand)

2,171.43 2,171.17 2,170.93 2,170.21 -0.26 -0.5 -1.22 -0.96

Per capita GDP

index

(2005 = 100)

311.36 311.32 311.29 311.19 -0.04 -0.07 -0.17 -0.13

Average annual

GDP growth

rate, 2007-2015,

(in %)

113 112.59 112.587 112.573 -0.41 -0.413 -0.427 -0.017

Per capita GDP

average growth

rate

111.156 111.155 111.154 111.150 -0.001 -0.002 -0.006 -0.005

Capital

(drams billion) 9,703.77 9,701.29 9,699.03 9,692.44 -2.48 -4.74 -11.33 -8.85

Capital index

(2005=100) 947.81 947.56 947.34 946.7 -0.25 -0.47 -1.11 -0.86

Employed

(thousand

people)

1,265.14 1,264.61 1,263.99 1,261.92 -0.53 -1.15 -3.22 -2.69

Employment

index

(2005 = 100)

115.24 115.20 115.14 114.95 -0.04 -0.1 -0.29 -0.25

34

Conclusion and Recommendations

An assessment of the social and economic impact of HIV/AIDS prevalence during

2007-2015 shows that, unless the epidemic is curbed in Armenia, its spreading can negatively

affect the population and the economy, slowing down average annual growth of the nominal

GDP by about 0.4%.

The study shows that a possible epidemic may reduce the supply of labor force and

increase government spending on health and social security. Therefore, the government must

play an essential role in disseminating appropriate information, financing interventions to

reduce risk behavior, caring and supporting people living with HIV/AIDS, reducing

discrimination against them in society, and providing for a favorable atmosphere. The

international experience confirms the existence of effective responses to the HIV/AIDS

pandemic. Recent studies and the experience of different countries have proven that

government intervention is particularly effective, when it is targeted at increasing awareness

and reducing risky behavior in population groups that are the most likely to become

infected.72

Some steps have already been taken in this direction in Armenia. In 1989, the

National AIDS Prevention Center was created. In 1997, the Republic of Armenia Law on

Prevention of the Disease Caused by the Human Immunodeficiency Virus was adopted.

During 2002-2006, the first National HIV/AIDS Prevention Program was carried out, and in

April 2007, a new 2007-2011 National HIV/AIDS Response Program was endorsed.

However, this National Program is not related to the PRSP; they neither complement one

another nor share goals and priorities. Therefore, it is necessary to incorporate the main

provisions of the National HIV/AIDS Program in the PRSP; the PRSP should contain an

overview of the HIV/AIDS epidemiological situation and address the epidemic as a constraint

on development, which needs to be solved by means of certain policies and budgetary

allocations.

The importance and effectiveness of preventive programs can be indirectly shown

using the projected scenario, under which the 2000-2002 HIV prevalence trends remain

unchanged, i.e. the situation remains the same as before the implementation of the 2002-2006

72 Jenkins, C., H. Rahman, T. Saidel, S. Jana, and A. M. Z. Hussain. 2001.“Measuring the Impact of Needle Exchange Programs among Injecting Drug Users though the National Behavioral Surveillance in Bangladesh.” AIDS Education and Prevention 13(5):452–61; Kahn, J. 1996. “The Cost-Effectiveness of HIV-Prevention Targeting: How Much More Bang for the Buck?” Am J Public Health 86(12):1709–12.

35

National HIV/AIDS Prevention Program. Under this scenario, , HIV/AIDS prevalence in the

15-49 population could be about twice higher in 2007 (see Figure 6).

Under the projected scenarios and characteristics of risk groups, the HIV/AIDS

response priorities are as follows:

1. Prevention programs among IDUs. The Study has found that IDUs are the most

significant contributors to the spreading of the HIV epidemic in Armenia (Figure 4). Even if

the incidence of HIV in this group is held constant from 2005, the prevalence of HIV in the

general population will be about 1.5-fold higher in 2015 than it would be if the current trends

were sustained (Figure 2).

2. Prevention programs among men who have sex with men. Men who have sex with

men (MSM) make up the next group that is a significant contributor to HIV prevalence.

Considering the relatively large size of this group, the exposure of their vast majority to high-

risk behavior,73 and the very limited coverage of this group by preventive programs,74 it is of

special importance to carry out preventive measures for this group.

3. Prevention programs among sex workers. Sex workers play a major role in

spreading HIV/AIDS, as well. Considering that only 49% of sex workers have knowledge

about HIV prevention, and about 65% of them routinely use condoms75, it is essential to carry

out preventive programs among this group. It is also important to carry out awareness-raising

and preventive programs among men who use services of sex workers.

4. Prevention and treatment of sexually transmitted diseases. It is a known fact that

having an STD increases the likelihood of HIV transmission during intercourse about three-

fold76. Considering the projected “No STI” scenario, under which HIV prevalence drops

considerably (Figure 5), it is important to treat and prevent STDs. Moreover, considering

that STDs and HIV have a common transmission mode, preventing one will effectively lead

to prevention of the other.

5. Prevention programs among young people of ages 15-24. The response to

HIV/AIDS should also include preventive measures targeted at young people of ages 15-24,

because only 28.2% of them possess knowledge about HIV prevention. Besides, this is the

73 Grigoryan S., Hakobyan A. et. al., Results of Behavioral and Biological Surveillance in the Republic of Armenia 2002 and 2005, p 14, Armenian National AIDS Foundation, Yerevan 2006. 74 Country Situation Analysis, Armenia, Joint United Nations Program on HIV, 2007 75 Grigoryan S., Hakobyan A. et. al., Results of Behavioral and Biological Surveillance in the Republic of Armenia 2002 and 2005, p 14, Armenian National AIDS Foundation, Yerevan 2006. 76 Modeling the Expected Short-Term Distribution of Incidence of HIV Infections by Exposure Groups, Manual, Joint United Nations Program in HIV/AIDS, 2007

36

age when the vast majority of drug users, sex workers, and men who have sex with men

become exposed to high risk77.

6. Prevention programs among people traveling abroad. The labor migration is a

significant and important issue in Armenia.78 Considering that the main destinations of the

labor migrants are countries with high prevalence of HIV infection,79, ,80 81 about 40% of

sexually active migrants reported having sex with non-regular partner in the past year, about

one-third of IDUs started using drugs in other countries, and a part of the IDUs living with

HIV infection temporarily inhabited in the Russian Federation and the Ukraine and were

probably infected with HIV there,82 it is necessary to carry out preventive measures among

people traveling abroad.

An effective response to HIV/AIDS must include programs of awareness raising,

education, enhanced voluntary counseling and testing, encouraging use of and improving

access to condoms, and prevention and treatment of sexually transmitted diseases among both

the general population and population at risk.

77 Grigoryan S., Hakobyan A. et. al., Results of Behavioural and Biological Survelliance in the Republic of Armenia 2002 and 2005, p 14, Armenian National AIDS Foundation, Yerevan 2006. 78 Minasyan A., Hancilova B., Labor Migration from Armenia in 2002-2005, A Sociological Survey on Households, OSCE and Advanced Social Technologies NGO, December 2005. 79 Minasyan A., Hancilova B., Labor Migration from Armenia in 2002-2005, A Sociological Survey on Households, OSCE and Advanced Social Technologies NGO, December 2005. 80 Country Situation Analysis, Ukraine, Joint United Nations Program on HIV, 2007 81 Country Situation Analysis, Russian Federation, Joint United Nations Program on HIV, 2007 82 Grigoryan S., Hakobyan A. et. al., Results of Behavioural and Biological Survelliance in the Republic of Armenia 2002 and 2005, p 14, Armenian National AIDS Foundation, Yerevan 2006.

37

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Annex 1

43

possible social and economic impact of hiv/aids epidemic on the republic of armenia

Documents