This paper estimates the economic impact of HIV/AIDS on the KwaZulu-Natal province and the rest of South Africa.We extended previous studies by employing: an integrated analytical framework that combined firm surveys of workers' HIV prevalence by sector and occupation; a demographic model that produced both population and workforce projections; and a regionalized economy-wide model linked to a survey-based micro-simulation module. This framework permits a full macro-microeconomic assessment.Results indicate that HIV/AIDS greatly reduces annual economic growth, mainly by lowering the long-run rate of technical change. However, impacts on income poverty are small, and inequality is reduced by HIV/AIDS. This is because high unemployment among low-income households minimises the economic costs of increased mortality. By contrast, slower economic growth hurts higher income households despite lower HIV prevalence.We conclude that the increase in economic growth that results from addressing HIV/AIDS is sufficient to offset the population pressure placed on income poverty. Moreover, incentives to mitigate HIV/AIDS lie not only with poorer infected households, but also with uninfected higher income households.Our findings reveal the substantial burden that HIV/AIDS places on future economic development in KwaZulu-Natal and South Africa, and confirms the need for policies to curb the economic costs of the pandemic. South Africa has one of the highest HIV prevalence rates in the world, and KwaZulu-Natal (KZN) is its worst afflicted province. Recent estimates indicate that 26.4% of KZN's working age population is HIV positive, compared to 15.9% in the rest of the country .Long-term trends in KZN are equally bleak. Recent evidence indicates that economic growth continues to lag behind the rest of the country, and that poverty is rising faster than in other provinces. Therefore, a key challenge for reviving economic development in South Africa, and in KZN in particular, is to understand the constraints imposed by HIV/AIDS on future economic growth and poverty reduction.Numerous studies estimate the micro-level impacts of the pandemic . First, we conducted a firm survey in four of KZN's largest sectors. Second, information on workers' HIV prevalence rates from the survey was used to calibrate an occupation-focused demographic model. Finally, the demographic projections were imposed on a regionalized dynamic computable general equilibrium (DCGE) model linked to a household survey-based micro-simulation model. This integrated macro-microeconomic framework permits a more robust empirically based assessment of the impacts of HIV/AIDS.The next section briefly describes the survey and demographic projections, as well as outlining the methodology, paying particular attention to the links between the demographic and DCGE models. The following section discusses the DCGE model's results and their implications for future socioeconomic development in South Africa. The final section summarizes the findings.The first stage of our analysis combines two demographic models. For a detailed description of the demographic model and projections, see . The firThe provincial version of the ASSA-2003 model from the Actuarial Society of South Africa  was usedHIV prevalence is concentrated among working age Africans, especially younger females (20 to 34 years) and slightly older males (35 to 49 years). By contrast, prevalence for the other racial groups is considerably lower for all age cohorts. Moreover, prevalence among Africans is heavily concentrated within KZN - a pattern that does not exist for other races. Given the large African and KZN population, it is clear that this province and population group forms the epicentre of South Africa's HIV pandemic. The effects of this concentration are evident in the population projections from the ASSA model  was developed to estimate size of the workforce with and without HIV/AIDS . The modHowever, the APM does combine the ASSA model's population projections with HIV test data from a firm survey to predict the impact of HIV/AIDS on the size of the workforce for different occupational groups. The changing sectoral composition of employment is endogenously determined by the DCGE model. It therefore provides the critical link between the population projections and the economic analysis in the next section.The calibration of the APM was based on the firm survey data collected during our study. Anonymous HIV tests were conducted for 15 companies in four economic sectors: agriculture, manufacturing, tourism and transport. The 15 companies were surveyed over three years: two in 2005, 11 in 2006, and two in 2007. For convenience, we treated all survey results as reflecting HIV prevalence in 2006. These are key sectors of the South African economy. Together, they comprise 59.1% and 44.7% of KZN and South Africa's gross domestic product respectively, and 55.8% and 49.1% of labour employment.A total of 6197 workers were tested, but only 4464 questionnaires were completed successfully. The sample had an overall HIV prevalence rate of 16.7%, with a 95% confidence interval of ± 1.1%. Table The survey reveals considerable heterogeneity across workers. Prevalence rates are typically highest for labourers  within the agriculture and tourism sectors. They are lowest for managers and professionals, with the exception of agriculture, where prevalence rates are similar for all three occupational groups. Prevalence is significantly higher for the middle-age cohort, which is consistent with observed national trends.vis-à-vis previous studies. It also provides a crucial link between the economic growth impacts of HIV/AIDS and its effects on employment, poverty and inequality. The next section describes how these demographic projections are incorporated within the economic modelling.The survey clearly indicates that it is inappropriate to make broad generalizations about the sectoral and occupational trends of HIV prevalence. Therefore, the inclusion of an empirically calibrated APM that produces occupation-based workforce projections greatly enhances the accuracy of our economic analysis HIV/AIDS affects economic growth and poverty via various impact channels. At the household level, a wide range of factors influence poverty, including: vulnerability from deteriorating livelihoods; heightened stigmatisation and a fragmentation of social networks; and lower investments in human capital and nutrition. These household-level effects need to be aggregated in order to estimate the overall impact of the pandemic.Moreover, while households are directly affected by HIV/AIDS, there are also broader implications for the economy as a whole. In our macro-microeconomic assessment, we account for not only households, but also other actors or institutions, such as firms, markets and government. However, broadening our analysis necessarily excludes some difficult-to-measure household-level impacts. Therefore, given our focus on economic growth, we concentrate on the income dimensions of poverty. Ultimately we identify five main impact channels for HIV/AIDS: population growth; labour supply; labour productivity; total factor productivity; and savings and investment. This section describes how these impact channels are captured in the economy-wide modelAdditional file s and region r  produce a level of output Q in time period t by employing the factors of production F under constant returns to scale (exogenous productivity α) and fixed production technologies (fixed factor shares δ)  (eq. ). Profitues (eq. ). Labourion (eq. ). Nationion (eq. ).Y are then either saved  or spent on consumption C   . Total  β) (eq. ). Consumre) (eq. ).P equilibrates national product markets, thus avoiding having to model inter-regional trade flows . A consThe model's variables and parameters are calibrated to observed data from a provincial social accounting matrix that captures the initial equilibrium structure of the KZN and Other SA economies in 2002. A social accounting matrix is a consistent database capturing all monetary flows in an economy in a given year. It contains information on the production technologies and demand structures of detailed sectors, regions and households, as well as government revenues and expenditures and foreign receipts and payments. Various datasets were used to build the 2002 provincial social accounting matrix for South Africa, including: national accounts; the 2000 Income and Expenditure Survey; the 2002 Labour Force Survey; and the South African Standard Industrial Database .The income and expenditure data was reconciled using cross-entropy estimation . ParametH increase at rates determined by the demographic model . Indivif is a composite for a worker's population group p, gender g, and occupation o. Population and labour supply in the DCGE model draws directly on the demographic projections DH and DL to capture the first two impact channels of HIV/AIDS. By increasing mortality, the pandemic reduces consumer demand and the productive capacity of the economy, both of which are likely to have adverse impacts on economic growth.Demographic compositions are drawn from the re-weighted 2000 Income and Expenditure Survey . SimilarDP or AIDS sick DA . Selected values of DP and DA for the entire population are given in the final two columns of Table The third impact channel is the effect of morbidity on workers' productivity. This is captured in (eq. ), where DP and DA are zero and labour productivity grows at μ. This growth rate is lower in the "AIDS" scenario because we assume that HIV-positive workers are half as productive as uninfected workers and that AIDS-sick workers are a fifth as productive. This is caused by lower on-the-job productivity and more days absent from work. Although the prevalence rates are estimated by the demographic model, the impact of morbidity on worker productivity must be assumed, because there are few empirical studies estimating workers' productivity losses from HIV/AIDS.In the "No AIDS" scenario, Given the findings of the impact of HIV/AIDS on tea pickers in Kenya, our assumptions may be an upper bound estimate of productivity losses. However, as seen in the next section, this impact channel is found to contribute the least to the overall economic impact of HIV/AIDS .systemic shocks to the economy  caused by omy (eq. ). For exomy . HIV/AIK. If HIV/AIDS reduces national income, then it lowers the level of savings and funds that can be invested in the economy, thus reducing the rate of capital accumulation and further reducing long-term economic growth.Investment from the previous period is then converted into new capital stocks using a fixed capital price κ (eq. ). This iThe simplified model illustrates how HIV/AIDS affects economic outcomes in our analysis. However, the full model drops certain assumptions. The full DCGE model is an extended version of the national model described in . ConstanThe model identifies 25 sectors in KZN and Other SA. The 25 sectors are mapped onto the four sectors in the firm survey. Most of the sectors in the DCGE model are in manufacturing, but we assume similar prevalence rates for mining. Similarly, we assign the tourism sector prevalence rates to the retail trade sector, and the transport sector prevalence rates to the remaining service sectors in the DCGE model. Intermediate demand in each sector (excluded in the simple model) is determined by fixed technology coefficients.Regional labour markets are further segmented across race, gender and three occupation-based skill categories. A nested demand system places skill levels above gender and age groups. All factors are assumed fully employed, and capital is immobile across sectors. New capital from past investment is allocated to regions and/or sectors according to profit rate differentials under a "putty-clay" specification (see ).The full model still assumes national product markets for most commodities. However, international trade is captured by allowing production and consumption to shift imperfectly between domestic and foreign markets depending on the relative prices of imports, exports and domestic goods. South Africa is a small country and so world prices are fixed and the current account balance is maintained by a flexible real exchange rate . Production and trade elasticities are econometrically estimated.Households maximise a Stone-Geary utility function such that a linear expenditure system determines consumption and permits non-unitary income elasticities. The latter are drawn from . HousehoFinally, the model includes a micro-simulation module in which each household in the 2000 Income and Expenditure Survey  is linkeIn summary, the full DCGE model captures the detailed sectoral and labour market structure of South Africa's economy as well as the linkages between production, employment and household incomes. Moreover, the results from the firm survey and demographic model are explicitly integrated within the economic analysis. Although not exhaustive, the five main impact channels captured by the DCGE model provide a reasonable approximation of the consequences of HIV/AIDS for growth, poverty and inequality.DH , DL (eq[DL (eq. ), and DP DM (eq. . Observe [μ (eq. ), φ (eq. [φ (eq. ) and π ad κ (eq. ). TogethTables Declines in the labour supply caused by HIV/AIDS are larger than declines in population growth . The average annual growth rate in GDP in KZN increases from 2.8% in the "AIDS" scenario to 4.44% in the "No AIDS" scenario . This is larger than the negative impact of HIV/AIDS on the rest of South Africa's GDP growth rate, which is reduced by 1.42% per year. Compounding these reductions in annual growth rates means that the KZN and the rest of the South African economies would be 43% and 37% smaller in 2025, respectively, than they could have been were it not for HIV/AIDS.Impacts differ by industry and region . Thus, the structural constraints that contribute to high unemployment in the rest of South Africa remain even in the absence of HIV/AIDS. More specifically, the results indicate that KZN and South Africa would continue to become more capital and skill intensive over time, even if the supply and productivity of lower skilled workers were not undermined by HIV/AIDS.It is also an apparent contradiction that poverty remains virtually unchanged in KZN under the "No AIDS" scenario despite an acceleration of per capita GDP growth by 0.5% (see Table The mean of both regions' curves is positive, reflecting the increase in aggregate per capita incomes in the "No AIDS" scenario. However, the fact that the growth incidence curves are upward sloping means that lower income households benefit less than higher income households in the "No AIDS" scenario. This suggests that income inequality would increase between 2002 and 2025 if HIV/AIDS were eliminated.A number of reasons explain this result. First, as mentioned earlier, the increased supply of lower skilled workers is offset by falling wages, leaving per capita incomes among households at the lower end of the distribution largely unchanged. The reverse is true for higher skilled workers whose wages rise with faster economic growth. Secondly, unemployment is high among working age adults living in poorer households. Therefore, reducing adult mortality may not reduce these households' dependency ratios, causing per capita incomes to fall. This is the case for lower income households in KZN, whose growth incidence curve is negative. While removing the effects of HIV/AIDS improves overall household welfare, it is detrimental for lower income household poverty in KZN, where unemployment is especially severe.A third reason for the increase in inequality is shown by measuring the contribution of the five impact channels to overall changes in GDP growth rates and poverty rates under the "No AIDS" scenario (see Table We have already discussed how increases in labour supply cause declines in lower skilled workers' wages, thus reducing the income gains from reduced mortality in the "No AIDS" scenario. Moreover, increased labour productivity and reduced health spending have only small effects on economic growth. Thus, the direct channels linking HIV/AIDS to poorer households are less important than the indirect TFP effects.The dominance of indirect impact channels is also evident in the poverty decomposition, which shows how the direct channels' contributions to poverty reduction are smaller than that of TFP growth. They are also far smaller than the downward pressure placed on per capita incomes by higher population growth. Thus it is TFP that drives the overall increase in growth and reduction in poverty in the rest of South Africa under the "No AIDS" scenario. However, TFP growth does not just benefit households with HIV-infected working adults. Rather, faster economic growth driven by TFP improvements drives up demand for all workers, including those whose HIV prevalence is initially low.Thus, the third reason why removing HIV/AIDS causes inequality to rise is that TFP benefits all households and workers regardless of whether they are infected by HIV. Higher income households therefore benefit from faster economic growth despite low infection rates. This finding highlights the importance of taking macroeconomic spillovers into account when assessing the overall impact of HIV/AIDS on growth and poverty.KwaZulu-Natal, together with the rest of South Africa, suffers from severe unemployment and poverty. Moreover, the province has one of the highest HIV prevalence rates in the world. This paper has estimated the impact of HIV/AIDS on economic growth and income poverty in KZN and the rest of South Africa. Drawing on the findings from a firm-level survey in four of KZN's major economic sectors, we integrated the projections from a demographic model within a regionalized DCGE model. This in turn was linked to a survey-based micro-simulation module in order to estimate poverty and distributional outcomes.This approach extends previous studies by: focusing on South Africa's most afflicted region; basing its projections on more reliable estimates of HIV prevalence for workers across occupational groups; and explicitly integrating demographic, economy-wide and survey-based models.The results indicate that HIV/AIDS undermines economic growth in South Africa. It lowers the GDP growth rate by 1.60% and 1.42% per year in KZN and the rest of South Africa, respectively. Cumulating these losses means that the KZN economy would be 43% smaller in 2025 than it would be in the absence of HIV/AIDS. The rest of the country's economy is similarly 37% smaller. While the detrimental growth effect is large, the impact of HIV/AIDS on the regional poverty headcounts is relatively small, and that inequality would be higher in the absence of HIV/AIDS.The small change in per capita incomes among the poor population should be interpreted alongside the 11.8 million who are projected to die as a result of HIV/AIDS between 2002 and 2025. Thus, the gains in economic growth in the absence of HIV/AIDS are sufficient to offset the pressure placed on poverty by a substantially larger population. Moreover, the incentive to mitigate the effects of HIV/AIDS lies not only with poorer households and those with infected members, but also with the uninfected and higher income households, who stand to benefit from faster economic growth and rising incomes. These findings reveal the significant burden that HIV/AIDS places on future economic development in KwaZulu-Natal and the rest of the South Africa, and underlines the need for policies and investments to curb the pandemic.The authors declare that they have no competing interests.JT developed the macroeconomic model, collected data, ran the simulations, produced the output tables and figures, and drafted the manuscript, JG conceived of the study and participated in its design and coordination and edited the manuscript, and GG participated in the study design and coordination. All authors have read and approved the final version of the manuscript.Simplified CGE model variables, parameters and equations. The information provided outlines the structure of the CGE model, its variables, parameters and equationsClick here for file


The aim of thisliterature review is to elucidate what is knownabout HIV/AIDS and stigma in Sub-Saharan Africa.Literature about HIV/AIDS and stigma inSub-Saharan Africa was systematically searchedin Pubmed, Medscape, and Psycinfo up to March31, 2009. No starting date limit was specified.The material was analyzed using Gilmore andSomerville's (1994) four processes ofstigmatizing responses: the definition of theproblem HIV/AIDS, identification of peopleliving with HIV/AIDS (PLWHA), linking HIV/AIDSto immorality and other negativecharacteristics, and finally behaviouralconsequences of stigma . It was found that thecultural construction of HIV/AIDS, based onbeliefs about contamination, sexuality, andreligion, plays a crucial role and contributesto the strength of distancing reactions anddiscrimination in society. Stigma prevents thedelivery of effective social and medical care andalso enhances the number of HIV infections. Morequalitative studies on HIV/AIDS stigma includingstigma in health care institutions inSub-Saharan Africa arerecommended. Although the current data show that the global HIV/AIDS epidemic is stabilizing, statistics still report an unacceptably high level of infection and progress is uneven in many countries . In 2007People living with HIV/AIDS (PLWHA) face not only medical problems but also social problems associated with the disease. One of the barriers to reaching those who are at risk or infected with HIV/AIDS is stigma . Stigma Currently, there is an increasing number of research on HIV-related stigma in Sub-Saharan Africa. It is being increasingly acknowledged, however, that effective treatment and care strategies require an understanding of the cultural context , 8 in whThe analyses in this review paper were based on Gilmore and Somerville's  classifiLiterature about HIV/AIDS stigma in Sub-Saharan Africa was systematically searched in Pubmed, Medscape, and Psycinfo up to March 31, 2009. No starting date was specified. A first search in Medline, PsycInfo and Pubmed with “HIV/AIDS”, “stigma” and “Africa” as key words gave 292 abstracts, of which 91 abstracts came from Medline, 57 from PsycInfo, and 144 from Pubmed; another search with “HIV/AIDS”, “discrimination” and “Africa” gave an additional 192 abstracts . A total of 484 abstracts were examined. From this list, papers relevant to the aim of this review were selected on the basis of their abstracts; uncertainties were reconciled through discussion with all the authors of this paper. The completeness of the search was checked by means of the reference lists of reviewed articles. Books or book chapters were included whenever applicable. Exclusion criteria included newspaper articles, campaign posters, articles not in the English language and articles not related to the topic. On the basis of this selection, 64 original articles were critically evaluated.HIV stigma as a phenomenon was considered to be the major topic of the review and was not limited to any geographical region. Although HIV/AIDS stigma is a general phenomenon which affects PLWHA in all parts of the world, in this paper, we focused on an analysis of the factors contributing to stigma identified from empirical studies in Sub-Saharan Africa, books, theoretical, and review papers. They include cultural constructions, stereotypes and specific beliefs, access to and the role of antiretroviral therapy, religion, and gender.Etymologically, the concept of “stigma” derives from a Greek word referring to a tattoo mark. It generally has two meanings. One derived from Christianity and denotes bodily marks which resemble those of the crucifixion of Jesus Christ—they are attributed to divine favour. The second meaning is secular, namely marks of disgrace, discredit, or infamy . Today, Stigma can be external or internal . ExternaThe problem. The problem  which Goffman [ Goffman  describe Goffman  describeIdentification of the person or group who are targeted for stigmatization. This means PLWHA must be recognizable and therefore have some identifying characteristics that can be used to recognise them correctly or erroneously, for example, loss of weight, skin rash, and so forth [so forth –19, 60. so forth  in the cApplication of stigma to the target person. Here specific persons are labelled with stigma. The stigma and the negative characteristics associated with it are perceived as belonging to them, for example, someone who is stigmatized is perceived as immoral [ immoral , 6, 20.  immoral  in the cThe outcome is usually a response to the stigmatized person such that they are distanced, disempowered or controlled by the stigmatizer. In this process, there is a change in the relationship or interaction between stigmatizer and the stigmatized [gmatized . In this literature review these four processes of stigmatization will be illustrated in an analysis of the various factors that affect HIV/AIDS stigma. Everywhere HIV/AIDS has been accompanied by stigma and discrimination but stigma in Sub-Saharan Africa seems to be particularly common , 7, 55. Factors that seem to mediate stigma include:cultural constructions, stereotypes and specific beliefs,access to and the role of antiretroviral therapy,religion,gender.The association with specific sexual behavior that is considered socially unacceptable by many people contributes to the stigma associated with HIV infection , 22, 25.HIV/AIDS is stigmatizing because it carries many symbolic associations with danger. Attribution of contagion, incurability, immorality and punishment for sinful acts is common in many societies , 22, 25.Self-diagnosis and self-treatment remain widespread , 30 owinKakokoolo (scarecrow), or Kamuyoola (was caught in a trap) in Uganda [ashawo (prostitute) in Nigeria. An individual's past social history may also be recalled to justify why they have AIDS [Stigmatization is a stereotyping response to negatively perceived characteristics of a person or group . The sten Uganda  and ashaave AIDS . PLWHA aave AIDS . Fear ofave AIDS –35 becauave AIDS , 36. Theave AIDS  The beliave AIDS .Although access to antiretroviral therapy (ART) has increased more than tenfold in low- and middle-income countries including Sub-Saharan Africa in the last six years , reachinA study carried out in Ghana showed that even though PLWHA regain their strength with ART and the physically devastating effect of HIV/AIDS is tempered, they still face psychological isolation and condemnation from their family, friends and society  because ART has also been shown to be less effective when initiated in someone with advanced disease  so delayIn Sub-Saharan African, many people are religious , 22, 28.Stigmatization has been linked with power , 9, 62. Society is more intolerant of females living with HIV/AIDS than of their male counterparts , 27, 35.Stigmatization can have many consequences for PLWHA and people affected by HIV/AIDS , 22, 47.Although current literature shows that stigma in some countries, for instance, the Republic of South Africa, has started to decline over the years , 16, espDespite the current progress of good prognostic health outcomes for HIV/AIDS, the Sub-Saharan African response still stands at a crossroads. In this paper, we contend that cultural constructions of HIV/AIDS, based on beliefs about contamination, sexuality and religion, play a crucial role and contribute to the strength of distancing reactions and discrimination in Sub-Saharan Africa by enhancing inequality. The public denial of HIV/AIDS is real and stems from a cultural undertone with a view which allows the pursuit of different treatment options, although denial on its own can be relative because it can be a way of coping with the disease while still acknowledging its existence. Denial can also be further enhanced when the PLWHA do not show some of the manifestations generally associated with HIV/AIDS by the community such as weight loss especially those on ART as people do not believe that they have HIV/AIDS even when they disclose their HIV status . PLWHA experience stigma throughout their lifetime. Issues of stigma, discrimination and denial are still poorly understood and often marginalized within national and international programs and responses , 62. StiThe identification of HIV patients poses a problem, because people try to hide the disease but perceivers assume that people have HIV if they are sicker than normal. Linking HIV/AIDS to immorality is common because of religious practices and a culture of serenity. This could be remedied by instituting programs that allow people to discuss sexuality based on their cultural norms and beliefs during which some of the myths surrounding HIV/AIDS can be corrected. Putting people in touch with individual and collective strength is a key strategy to mobilizing them in such complex issues such as stigma , 43, 46.


The concept of risk dominates the HIV/AIDS literature pertaining to People Who Use Injection Drugs (PWUID). In contrast the associated concept of worry is infrequently applied, even though it can produce important perspectives of PWUID's lives. This study asked a sample (n = 105) of PWUID enrolled in a Victoria, British Columbia needle exchange program to evaluate their degree of worry about fourteen factors they may encounter in their daily lives.Exploratory factor analysis was used to analyze their responses.Factor analysis delineated three factors: 1) overall personal security, 2) injection drug use-specific risks including overdosing and vein collapse and, 3) contracting infectious diseases associated with injection drug use (e.g. HIV/AIDS and hepatitis C).PWUID in this study not only worry about HIV/AIDS but also about stressful factors in their daily life which have been linked to both increased HIV/AIDS risk behaviour and decreased anti-retroviral treatment adherence. The importance PWUID give to this broad range of worry/concerns emphasizes the need to place HIV/AIDS intervention, education, and treatment programs within a broader harm-reduction framework that incorporates their perspectives on both worry and risk. Injection drug use is a driving force in historic HIV epidemics in North America and emerging epidemics in Asia and Eastern Europe , and is In contrast to this long-standing concern with the concept of risk there has been relatively little development of a related concept, that of worry, in the HIV/AIDS literature. A notable exception is Smith and Watkins' ,11 substet al. ), our results again emphasize the need to address larger structural problems which form risks and worries for PWUID. Unfortunately in the present case the closure of the AVI-SOS fixed site needle exchange facility limits the organization's ability to address these broader programs. Throughout its existence the fixed-site provided a suite of services, ranging from providing hot meals through access to street nurses, referrals to housing/shelter organizations, personal counsellors and HIV/HCV testing to simply providing a safe, dry, warm place. With its closure AVI-SOS must attempt to provide these services via newly established outreach services which cannot individually offer the array of services provided by the now defunct fixed-site; which this analysis reveals their clientele want and need.In conclusion, combined with the historically more frequently applied concept of risk, consideration and inclusion of PWUID's panoply of everyday worries into broader-based harm reduction interventions could provide important insights or "windows" into their lives and yield effective programs featuring the convergence of PWUID perspectives and public health goals.The authors declare that they have no competing interests.HE, EKG, JL, RS and EAR designed the study questionnaire, constructed the research design, collected the data upon which this analysis is based, and interpreted analysis results. LC, RS and EAR completed the statistical analysis, and wrote the manuscript draft. All authors read and approved the final manuscript.


This editorial comments on selected progress made in combating the acquired immune deficiency syndrome (AIDS) after 26 years and some of the remaining challenges. It has been 26 years since the acquired immune deficiency syndrome (AIDS) was first recognized (see review ). In theMore than a quarter century of AIDS later, where do we stand against this disease? A couple of advances amongst many warrant measured optimism. First, we have made remarkable strides in developing antiviral drugs or antiretrovirals (ARVs). Since 1996, ARVs have saved an estimated 3 million life-years in the United States alone. An upside to this therapeutic advance is that currently more than 2 million HIV-positive people are being treated with ARVs. While drug resistant viruses continue to be a significant issue , the GloThere have also been two notable recent disappointments. The first is the serious setback of the failed clinical vaccine trial from the collaborative efforts of Merck & Co., Inc., the US National Institute of Allergy and Infectious Diseases (NIAID), and the HIV Vaccine Trials Network (HVTN). In this sizable clinical trial, 49 of 914 vaccinated men tested positive for HIV, compared to 33 of 922 men who received a placebo vaccine . These rth World AIDS Day is "leadership". This is a day to consider how we can exercise leadership on new innovations and vision. With increased globalization, today's world is much different from what it was 26 years ago; and very likely, the world will be further different in 26 more years. Several respected sources have projected that by 2040 China will have overtaken the United States to become the world's largest economy with India capturing third place. Official AIDS statistics in 2005 place China's HIV-cases at 650,000. With her population of 1.3 billion people, China's future HIV numbers will surely rise [The theme of this 20ely rise . NeverthToday is also a day for the AIDS/HIV medical and research communities to reflect on new ideas, new targets  and to c


Regional incidence trends in regular heroin use are important for assessing the effectiveness of drug policies and for forecasting potential future epidemics.To estimate incidence trends we applied both the more traditional Reporting Delay Adjustment (RDA) method as well as the new and less data demanding General Inclusion Function (GIF) method. The latter describes the probability of an individual being in substitution treatment depending on time since the onset of heroin use. Data on year of birth, age at first regular heroin use and date of admission to and cessation of substitution treatment was available from 1997 to 2006 for 11 of the 26 regions (cantons) of Switzerland. For the remaining cantons, we used the number of patients in 5-year age group categories published in annual statistics between 1999 and 2006.Application of the RDA and GIF methods on data from the whole of Switzerland produced equivalent incidence trends. The GIF method revealed similar incidence trends in all of the Swiss cantons. Imputing a constant age of onset of 21 years resulted in almost equal trends to those obtained when real age of onset was used. The cantonal incidence estimates revealed that in the mid 80s there were high incidence rates in various regions distributed throughout all of the linguistic areas in Switzerland. During the following years these regional differences disappeared and the incidence of regular heroin use stabilized at a low level throughout the country.It has been demonstrated that even with incomplete data the GIF method allows to calculate accurate regional incidence trends. A lack of information about trends in the incidence of regular heroin use hinders effective drug policy and public health action. Yet incidence trends are still unknown almost everywhere in the world. Various estimation methods have been developed to estimate the incidence of heroin use -4, howevTo explore if the GIF method yields plausible incidence estimates in other regions, we decided to apply it to other Swiss cantons. There are several advantages of using other areas in Switzerland to test the GIF method. First, even though incidence trends in regular heroin use are unknown in almost all regions, drug mortality trends and the stable number of patients in substitution treatment suggest that prevalence trends are similar throughout Switzerland. Second, each of the 26 cantons in Switzerland is individually responsible for treatment provision and data collection. Third, the size of the population of regular heroin users differs vastly between cantons. For example, in 2003, the annual number of individuals in methadone treatment in various cantons ranged from 3 to 3,592 . TherefoUnfortunately, not every Swiss canton has a methadone treatment register that includes data on the year of first regular heroin use. Since heroin use usually occurs early in life , when daThus, the aims of this paper are to: (i) estimate the incidence of regular heroin use for the whole of Switzerland using the Reporting Delay Adjustment (RDA) method; (ii) ascertain a General Inclusion Function (GIF) for the whole of Switzerland by using the annual number of patients in substitution treatment; (iii) apply the GIF function to treatment data from different calendar years, using data on 'year of first heroin use' as well as 'year of birth'; and (iv) examine if assuming a constant age of onset leads to acceptable incidence trend approximations in all Swiss cantons.Open drug scenes started to develop in Switzerland in the early 1980s, mainly in the city of Zurich, but also in other German speaking parts of Switzerland. The French and Italian speaking parts of Switzerland were not affected. Thus, linguistic regions may differ concerning the development of the heroin wave. In February 1995, the last open drug scenes in Zurich, Solothurn, and Olten were closed; those in Bern, Basel-Stadt, and St. Gallen had been closed earlier [The Swiss law on narcotics requires that treatment providers obtain permission from cantonal health authorities to prescribe opioids to people dependent on heroin. The law also requires a register of substitution treatments provided to opioid dependent persons. Each of the 26 Swiss cantons is responsible for methadone treatment provision and data collection. The Swiss Federal Office of Public Health has collated and published annual statistics from all cantons since 1999 . Since 2th of January 2008, n = 812; Solothurn, 17th of January 2008, n = 621). We did not approach most of the remaining 13 cantons because they had limited sample sizes, generally having less than 100 individuals in treatment. Data from the 11 cantons fully included in this part of the study represented about 70% of the Swiss population in methadone treatment. These 11 cantons were spread throughout different linguistic areas and included both urban and rural parts of Switzerland.Data from this database and other datasets were analyzed, if cantonal health authorities agreed to participate in the study. The following 11 cantons were enrolled: Bern, Fribourg, Genève, Graubünden, Neuchâtel, Schaffhausen, Solothurn, St. Gallen, Ticino, Vaud, Zug, and Zurich. Additionally, we obtained the exact year of birth of all patients in treatment on a specific day for 2 cantons  patients with a known year of first regular heroin use. For the RDA method we used all available data from the 11 cantons included in this study. For the GIF method we only used data from those calendar years that had similar numbers of admissions and cessations. This ensured that in the analyses, we only included data from years in which a register had been fully operational.The RDA method aims to estimate and to correct for those heroin users from each onset cohort, who have not yet shown up in opioid substitution treatment. It assumes a stable probability distribution that describes the time between onset of heroin use and first treatment. If we assume that almost every regular heroin user enters his first substitution treatment (if ever) within 10 years, a treatment register of ten years would be sufficient to estimate a full probability distribution of that 'delay' or 'lag'. To estimate the lag time period between first regular heroin use and first substitution treatment we applied the method proposed by Hickman and colleagues . To avoi20 years).The RDA method underestimates incidence because it does not account for those heroin users, who do not show up in treatment. Thus, we applied a cessation correction of 4% per year, based on the assumption that each heroin user observed in treatment is representative of all those who had died or stopped heroin use before having had the possibility to enter treatment. For example, if a total of 44 individuals, who entered treatment in 1997, reported initiating regular heroin use in 1977, this suggests that 100 individuals had started regularly using heroin in 1977 . Since the data revealed a preference for reporting even years of regular heroin onset, we computed a three-period moving average using the former, the current, and the following values. The resulting treatment probabilities were plotted by time since onset of regular heroin use.Pannum), depending on time since onset (in years):To estimate incidence for each calendar year separately, we applied an approximation formula for the General Inclusion Function. This formula describes the probability of being in treatment at least 1 day during a year (-1) describes the steep rise in probability during the first years; after some decades the decline approximates 4% per year (0.96(time-0.2)).The components of this approximation formula can be interpreted as follows: 0.7 is a linear scale factor and sets the peak to 0.457; the term (1 – (time-0.2)The mean age at first regular heroin use was approximately 21 years in all cantons over all treatment years. Thus, we estimated the number of affected individuals in each birth cohort in cantons providing detailed data by supposing a constant age of onset of 21 years and applying the approximation formula for the General Inclusion Function.Shifting the time scale by 21 years – the mean age of onset of regular heroin use – allowed comparisons to be made between incidence estimates based on age of onset data and those based on birth cohort data. Theoretically, the narrower the age of onset distribution, the more similar the two forms of incidence estimates.Between 1999 and 2006, 24 out of 26 cantons published the number of patients in treatment by 5-year age group categories over at least several years . To estiIn cantons for which we could recalculate the numbers of patients in treatment using treatment case register data, we found some differences in the size of age groups. Since we were interested in how well the procedure using 5-year age group categories fitted estimates using numbers of patient of each birth cohort from treatment case registers, we used our own calculated annual numbers of 5-year age group categories.For 11 cantons we had complete methadone treatment register data from 1998 to 2006  individuals initiating regular heroin use.Using year of birth and assuming onset of regular heroin use at the age of 21 years led to reasonably good approximations of incidence estimates obtained by real age of onset. If we suppose that any short peak of heroin incidence will affect young people at around the age of 20, it follows that birth cohort incidence curves will be less steep and smoother than year of onset incidence curves. The results from different Swiss cantons showed some support for this assumption, with birth cohort trend estimates peaking a few years earlier at lower levels.Given the relatively high proportion of missing data on age of onset, the variation in the proportion of missing data between cantons and the fact that the mean age of those patients with missing data on age of onset was about 3 years higher than that of patients with available data, we must be careful when comparing incidence trends between cantons. If data concerning age of onset is of poor quality, using year of birth and calculating incidence by birth cohort, may lead to better estimates. Among our incidence estimates, the canton of St. Gallen is a good example, where a rather pronounced difference between birth cohort estimates and year of onset estimates point to possible weaknesses in the quality of data on age of onset. However, even if birth cohort estimates are more robust, they do not necessarily correspond fully to onset incidence trends.In almost all cantons with elevated incidence levels, the birth cohorts of the late 60s and the early 70s were most affected by heroin use. Due to the small size of some cantons and some data of debatable quality, we think that grouping estimates into 7-year periods is more appropriate than speculating about the 'irregularities' of estimated trends. Despite this low time resolution, our representation of the spread of the 'heroin epidemic' in its spatial and temporal dimensions is still meaningful. It clearly reveals that there were several regions with higher incidence rates during the 80s. These 'centers' are distributed throughout all linguistic regions of Switzerland. This might be surprising since open drug scenes have only been known to exist in the German part of Switzerland. Thus, we have no indication of whether the 'heroin wave' begun in the eastern or in the northern part of Switzerland, nor whether it spread from a centre – for example, from Zurich, with its more prominent open drug scenes. Over the last 2 decades, the former spatial differences seem to have disappeared and the incidence of regular heroin use has stabilized at a comparatively low level throughout Switzerland.Apart from the afore-mentioned limitations, our approach should not be understood as providing the 'best possible estimate' of the incidence of regular heroin use for each canton of Switzerland. In this paper, we neglected the number of opioid users in heroin-assisted treatment programs. This form of treatment exists in about half of all cantons in Switzerland, most often in the German part . But as Using a simple method to estimate the incidence of heroin use, we were able to show that it is also possible to estimate incidence trends in relatively small areas and with incomplete data.As to the spread of the heroin wave in Switzerland, in all cantons incidence peaked at the beginning of the 90s. Those cantons with higher incidence rates during the 80s were not necessarily those cantons where open drug scenes were present. Over the last 2 decades the former spatial differences in Switzerland seem to have disappeared, and the incidence of regular heroin use has stabilized at a comparatively low level throughout Switzerland.The authors declare that they have no competing interests.CN was the main contributor to the design of the study and did the statistical analyses. All authors participated in the execution of the study and the writing of the manuscript. All authors read and approved the final manuscript.


The Federal Ministry of Health of Ethiopia is implementing an ambitious and rapid scale-up of health care services for the prevention, care and treatment of HIV/AIDS in public facilities. With support from the United States President's Emergency Plan for AIDS Relief, 38 830 service providers were trained, from early 2005 until December 2007, in HIV-related topics. Anecdotal evidence suggested high attrition rates of providers, but reliable quantitative data have been limited.With that funding, Jhpiego supports a Training Information Monitoring System, which stores training information for all HIV/AIDS training events supported by the same funding source. Data forms were developed to capture information on providers' working status and were given to eight partners who collected data during routine site visits on individual providers about working status; if not working at the facility, date of and reason for leaving; and source of information.Data were collected on 1744 providers  in 53 hospitals and 45 health centres in 10 regional and administrative states. The project found that 32.6% of the providers were no longer at the site, 57.6% are still working on HIV/AIDS services at the same facility where they were trained and 10.4% are at the facility, but not providing HIV/AIDS services. Of the providers not at the facility, the two largest groups were those who had left for further study (27.6%) and those who had gone to another public facility (17.6%). Of all physicians trained, 49.2% had left the facility. Regional and cadre variation was found, for example Gambella had the highest percent of providers no longer at the site (53.7%) while Harari had the highest percentage of providers still working on HIV/AIDS (71.6%).Overall, the project found that the information in the Training Information Monitoring System can be used to track the working status of trained providers. Data generated from the project are being shared with key stakeholders and used for planning and monitoring the workforce, and partners have agreed to continue collecting data. The attrition rates found in this project imply an increased need to continue to conduct in-service training for HIV/AIDS in the short term. For long-term solutions, retention strategies should be developed and implemented, and opportunities to accelerate the incorporation of HIV/AIDS training in pre-service institutions should be explored. Further study on reasons why providers leave sites and why providers are not working on HIV at the sites where they were trained, in addition to our project findings, can provide valuable data for development of national and regional strategies and retention schemes. Project findings suggest that the development of national and region-specific human resources for health strategy and policies could address important human resources issues found in the project. Ethiopia has a population of approximately 77 million people, with nearly 83% living in rural areas . EthiopiThe existing human resources (HR) for health crisis can significantly impede Ethiopia's attempts to attain ambitious targets to scale up primary health care services, as well as to reach goals for universal access to HIV/AIDS prevention, care and treatment services by 2010. A 2003 study noted that, given current HR, there would be a 14%–66% gap in physicians necessary to address both basic health services and direct HIV/AIDS care needed to reach HIV/AIDS prevention, care and treatment goals of the Ethiopian government, the United States President's Emergency Plan for AIDS Relief (PEPFAR) and the Global Fund to Fight AIDS, Tuberculosis and Malaria [Human capacity building – including training service providers in all areas of HIV prevention, care and treatment – is a significant component of PEPFAR Ethiopia support to the Federal Ministry of Health (FMOH) HIV/AIDS programme. From April 2007 to March 2008, PEPFAR planned to support training of 124 920 persons in all areas of HIV/AIDS prevention, treatment, care and support . While not all of these individuals are health care workers – many are community-based workers and other cadres of workers – this still represents a massive training and human capacity building effort for HIV/AIDS. Over the past two years, training budgets accounted for 30%–40% of the total PEPFAR funding for Ethiopia.©), which stores key participant and training information for all PEPFAR-funded training events. This paper describes a project that uses training data from the TIMS database to follow up providers after training to assess whether they are still working in HIV/AIDS-related services. The objective of this project was to assess the usefulness and feasibility of collecting these data for monitoring and planning of HIV/AIDS services.With funding from PEPFAR, through the United States Centers for Disease Control and Prevention (CDC), Jhpiego supports a Training Information Monitoring System  and CDC Ethiopia require that PEPFAR-implementing partners report training data for entry into TIMS. As of the beginning of the project in January 2007, 26 partners had reported training information – totaling 31 284 trained providers and 1038 courses.With input from key stakeholders, Jhpiego developed a tool to collect information about trained providers on: HIV/AIDS working status (yes/no); percentage level of effort for HIV/AIDS services; if not working on HIV/AIDS, reasons why not and date of departure from the facility (when applicable); and the method of collecting data . Each tool was completed for the individual hospital or health centre with information on the service provider trained, date of training, course name, profession and gender. Jhpiego staff pretested this data collection tool prior to the project and made minor changes before the project's rollout.Eight PEPFAR partners, including Jhpiego, were selected to participate in the project based on their role in the direct implementation of clinical HIV/AIDS services for hospitals and health centres. Since the selected partners regularly visit sites where HIV/AIDS services are delivered, the planned supervision visits were used to collect data for the project. Data collection occurred between February and June 2007. The original data set chosen for the project included 6353 providers who were either trained by the partners participating in the project or were working at the facilities where those partners were supporting HIV service implementation. Public and military hospitals were included in the data set because PEPFAR supports HIV/AIDS services at these facilities. In addition, some of the partners participating in the project had been asked by the MOH's HIV/AIDS Prevention and Control Office and other government stakeholders to support HIV services at private hospitals; thus, the analysis also included trained HIV/AIDS service providers from private hospitals.Jhpiego provided the partners with forms containing the name, profession and courses attended for each of the participants so that follow-up data could be collected on an individual basis at each facility. In some cases, training information was not yet entered into TIMS, and the partners collected all training information about the providers and their HIV/AIDS working status during their routine site visits. The method of data collection  was also recorded to help understand the quality of HR records kept by the hospital and to monitor the quality of data collected. The completed forms were sent to Jhpiego, where Jhpiego staff compiled and entered the data and conducted the analysis by means of SPSS and SAS software.Some partners reported being unable to find information on some providers, and these providers were removed from the analysis. In addition, if partners did not have scheduled visits to some of the facilities they supported, data were not collected from those sites and those providers were excluded from the analysis.The partners were asked to complete an evaluation form to gather feedback on the usefulness of the data, the ease or difficulty of collecting the data, and the perceived use of these data during regular programme monitoring. This information will be used to help determine whether this type of data collection will occur on a routine basis as part of the TIMS programme.The responses for several variables – training focus, qualification and reason for not being at the site – were grouped into "other" if the sample size was small and represented less than 2% of the total sample. Approximately 26% of the responses for reasons why they were not working at the site were "don't know," and these responses were left in the analysis because they represent data where it was known people had left, but the reason was unknown. For people who were working in HIV, data were collected on their percentage of time working in HIV (1%–100%); however, for this analysis everyone was grouped as working in HIV regardless of their levels of effort.Attrition in this analysis is defined as the provider's no longer working at the site at the time of the supervision visit. Responses for reason for leaving included: left for further study, joined a nongovernmental organization (NGO), joined the private sector, transferred to another public facility, other  and unknown. Breaking down attrition as defined above, there are two groups of health care workers: those leaving the public health sector entirely or for reasons unknown, and those transferring to another public facility. Of those who transferred to another public facility, we are unsure if they are still providing HIV/AIDS services, and there are no formal systems for providers who transfer to a new facility to report prior training courses they have attended. They are considered part of the attrition category. Ultimately, in the overall analysis, we focus on the providers who have left the site , since the loss of those providers requires managers to train new providers as replacements.The data were analysed by means of SAS software. Summary statistics were generated with gender, type of provider, type of facility, working status and reasons for leaving as the categorical variable. Chi-square was performed to analyse comparisons by variables potentially related to attrition. For the chi-square analysis, attrition was further grouped by HIV-working status into "working in HIV" and "not working in HIV." The latter category included individuals who were at the site but were not providing HIV services, grouped with those who were no longer at the site. The chi-square was also performed using a grouping of those "at the site" and "not at the site", but the results of the analysis were similar. The HIV-working status was used because it more accurately reflects the concept being discussed. Working status was analysed based on work location by grouping regions into established regions ); Tigray; and emerging regions . We also reviewed working status by qualification and by number of courses taken.Of the 6353 service providers with information provided, a total of 1744 service providers were followed up from 53 hospitals and 45 health centres in 10 of 11 regional and administrative states. Nearly 88% of the providers worked in a hospital and 59% were male. Fifty-seven percent were nurses and/or midwives, while 14% were physicians; all other professions each represented less than 10% of the sample. Of the 1744 providers, 1344 had taken only one HIV course, while the remaining 400 had taken at least two courses  and "not working in HIV" (42.7%). This was analysed by established regions versus emerging regions. We found that providers who had been working at facilities in emerging regions when they were trained were less likely still to be working at those sites than those working in established regions (p < .0001).In addition to an analysis by region, we explored attrition and the reported destination by profession. Pharmacists and lab personnel were the most likely to have joined the private sector ; while 32% and 28%, respectively, had transferred to other public facilities. Sixteen percent of physicians joined the private sector, and were also the most likely (19%) to have joined an NGO. Nurses and/or midwives were the most likely to have left for further study (35%).  health offices. Diploma-level health care workers are eligible for the accelerated programme.) However, when overall working status by nurses and/or midwives was compared to all other professions, the difference was statistically significant for physicians and specialists (p < .0001) and administrators and management (p = .0091), with both groups less likely still to be working in HIV than those in the nurse and/or midwife group Table . FinallySixty percent of the partners found that collecting these data during site visits was not burdensome. All partners agreed to collect this information in the future and recommended that these data be collected on a semiannual basis. Eighty percent of partners reported that they would use the information for planning and monitoring purposes.Given the significant resources devoted to training health care workers in Ethiopia, tracking whether providers trained to deliver HIV/AIDS services are indeed providing those services in public facilities is important for monitoring and evaluation of programme implementation and for programme planning. TIMS in Ethiopia provides an opportunity to capture this information in a meaningful and collaborative context.This project noted a very high attrition rate, with 32% of providers having left their original work sites – overall, 24.6% were no longer in the public sector. This rate is alarmingly high, and further exploration into "push and pull" factors is warranted. Physicians had the highest attrition, with more than 49% no longer at the sites and fewer than 6% having transferred to another public facility. This rate is almost twice as high as that found in a 2006 study from Ethiopia's FMOH, which reported an attrition rate from the public sector of 26% for physicians [Ten percent of health providers who had left the facility were reported to have joined the private sector, and an additional 10% were reported to have joined an NGO. The 10.6% of providers who remained at the site but were not working in HIV requires further attention and emphasizes the potential need to better target training resources and improve selection of health care workers to be trained. In one region, Tigray, where 18.9% of workers were reassigned within a facility, staff from the Regional Health Bureau reported that they considered training as a tool to improve retention (Tadesse Y: Report on a Retention Fact Finding Visit to Mekelle. December 2007). This finding suggests that other factors beyond HIV/AIDS-related service delivery needs may influence the selection of providers for training.We also found considerable regional variation in attrition rates. Recognition of these trends and regional differences can influence decision-making at the regional and national levels to ensure that HIV/AIDS services are adequately staffed.Through this project, we found that using information gathered in a standardized way by PEPFAR partners during routine supervision visits and entered into the TIMS database demonstrates an innovative and effective way to monitor the HIV/AIDS workforce. Such monitoring contributed to the partners' ability to ensure coverage of trained providers to deliver services and helped inform planning for replacement training, where applicable, at little additional cost. Partners requested region- and site-specific analyses for use in planning for replacement training and have also used these data to negotiate with regional health bureaux for effective retention strategies. The collection of all training data in one central database allowed access to a comprehensive list of providers trained at individual sites, regardless of which organization supported the training, and facilitated comprehensive site-level HIV/AIDS workforce assessments.In the absence of a national human resource information system (HRIS), the findings of this project provided the potential to look at the working status of a large country-wide cohort of providers and helped facilitate and inform planning by regional health bureaux and the FMOH, which will ensure that adequate numbers of staff are available to deliver comprehensive HIV/AIDS services and develop evidence-based retention strategies.Furthermore, routine analysis of TIMS follow-up data may inform and provide a means to monitor the effectiveness of retention strategies. The TIMS database can also facilitate mapping of the workforce to support the use of these data for general as well as HIV/AIDS-specific workforce planning.The attrition found through this project suggests that a stop-gap approach to train more service providers may be necessary to meet HIV/AIDS service demand. However, this is not a sustainable solution and requires significant resources to maintain a standard level of trained providers. Other options include task shifting of certain care responsibilities to lower-level cadres of health care workers or creation of a specialized cadre of HIV/AIDS workers. Various retention schemes should be developed, implemented and evaluated at both a national and regional level. Current human resource practices in the health sector should be reviewed and national guidelines/policies regarding human resources for health should be developed to address problem areas identified through this project.As the need for HIV/AIDS services continues to increase in Ethiopia, more trained professionals will be needed, highlighting the need to focus efforts towards greater integration of HIV/AIDS content into pre-service education to ensure that new graduates have the base knowledge, skills and attitudes to provide various HIV/AIDS-related services.Despite the large TIMS data set of trained providers, there is a significant lag time for reporting and data entry into TIMS, with only 38 380 persons in the database as of December 2007, compared to the projected 124 920 people who are to be trained by March 2008. However, the lag time is comparable across partners and regions and, therefore, the sample analysed in this study is believed to be representative.It is important to note that the numbers generated concerning attrition in this project are specific to providers trained in HIV/AIDS services in Ethiopia, and may not be generalized to other service areas or the Ethiopian workforce in general. There may be some characteristics of these individuals that make them different from other health care workers who have not had HIV/AIDS training opportunities.The majority of data was collected orally from health care workers rather than from administrative records. Data were collected from official HR records at only a few sites, highlighting the need to support site-level HR management at public facilities. Information was not available for the individuals who had left sites where they had received training, but had transferred to another public sector site. It is possible they are still working in HIV and, therefore, do not represent true attrition from the HIV/AIDS public health care sector. However, their transfer still has significant site-level implications for maintaining services and high-quality care.Finally, data were not collected on the reasons why providers left the facility, in addition to where they went, or were still at the facility but not working on HIV/AIDS, limiting the scope of information usable to develop targeted retention schemes.The project successfully demonstrated that data found in TIMS can be used for following providers trained in HIV/AIDS to assess their HIV/AIDS working status and evaluate attrition. With longer follow-up, there is an opportunity to collect information on time and geographical trends. Key government stakeholders are actively using this information for HIV/AIDS workforce planning.Based on the project findings, we recommend that tracking of trained HIV/AIDS health care workers through the use of TIMS be rolled out to all health care facilities. The data should be routinely analysed and disseminated to key stakeholders, to inform planning for HIV/AIDS training needs and development of retention schemes. Data on the reasons why providers leave the facility and why trained providers are not working on HIV at the facility post training should be collected to have a broader understanding of the "push and pull" factors in order to develop targeted retention schemes.The study findings also highlight the need for national and regional specific policies and guidelines regarding human resources for health to be developed and implemented at all levels to address problem areas found in the study. This study points out the need to strengthen and expand pre-service programmes aimed at incorporating HIV/AIDS competences into the curriculum. This study also highlights the need for the FMOH and individual regions to consider a national HR information system to track movements of all health workers in Ethiopia.The authors declare that they have no competing interests.MEM contributed to the conception, design, implementation and analysis of project findings and dissemination of findings, as well as writing the manuscript. CAH contributed to the conception, design and statistical analysis of project data as well as overall technical and monitoring-and-evaluation-related support for the project and writing the manuscript. AP contributed to the conception, design and implementation of the project as well as overall guidance and oversight of project implementation and dissemination of findings. AP also contributed to the manuscript. YA contributed to the conception, design, implementation and overall guidance and support for the project. YA also contributed to and reviewed the manuscript. MN contributed to the implementation and analysis of the findings and reviewed the manuscript. PF contributed to the conception, design, implementation and overall support for the project. PF also reviewed the manuscript. JA contributed to the design and overall support for project implementation. JA also critically reviewed the manuscript and has given the final approval for Jhpiego/JHU publication.


We studied the incidence of tuberculosis, AIDS, AIDS deaths and AIDS-TB co-infection at the population level in Rio de Janeiro, Brazil where universal and free access to combination antiretroviral therapy has been available since 1997.This was a retrospective surveillance database match of Rio de Janeiro databases from 1995–2004. Proportions of tuberculosis occurring within 30 days and between 30 days and 1 year after AIDS diagnosis were determined. Generalized additive models fitted with cubic splines with appropriate estimating methods were used to describe rates and proportions over time. Overall, 90,806 tuberculosis cases and 16,891 AIDS cases were reported; 3,125 tuberculosis cases within 1 year of AIDS diagnosis were detected. Tuberculosis notification rates decreased after 1997 from a fitted rate  of 166.5 to 138.8 in 2004. AIDS incidence rates increased 26% between 1995 and 1998 (30.7 to 38.7) followed by a 33.3% decrease to 25.8 in 2004. AIDS mortality rates decreased dramatically after antiretroviral therapy was introduced between 1995 (27.5) and 1999 (13.4). The fitted proportion (fP) of patients with tuberculosis diagnosed within one year of AIDS decreased from 1995 (24.4%) to1998 (15.2%), remaining stable since. Seventy-five percent of tuberculosis diagnoses after an AIDS diagnosis occurred within 30 days of AIDS diagnosis.Our results suggest that while combination ART should be considered an essential component of the response to the HIV and HIV/tuberculosis epidemics, it may not be sufficient alone to prevent progression from latent TB to active disease among HIV-infected populations. When tuberculosis is diagnosed prior to or at the same time as AIDS and ART has not yet been initiated, then ART is ineffective as a tuberculosis prevention strategy for these patients. Earlier HIV/AIDS diagnosis and ART initiation may reduce TB incidence in HIV/AIDS patients. More specific interventions will be required if HIV-related tuberculosis incidence is to continue to decline. The impact of the human immunodeficiency virus/acquired immune deficiency syndrome (HIV/AIDS) epidemic on tuberculosis (TB) incidence has been catastrophic, underscoring the need for new approaches to controlling these overlapping diseases In Brazil, antiretrovirals have been available free of charge for HIV patients since 1991 and combination therapy including protease inhibitors since 1997. Rio de Janeiro presents a unique setting to evaluate the population level impact of ART on the incidence of HIV-related tuberculosis. If combination ART significantly reduces active tuberculosis incidence among populations with HIV/AIDS, then the global scale up of HIV therapy could contribute to improved tuberculosis control. Conversely, the lack of an appreciable effect would suggest that alternative strategies are needed.We studied the incidence of active tuberculosis, AIDS, AIDS deaths and tuberculosis with AIDS in the same year in Rio de Janeiro from 1995–2004 using surveillance databases maintained by the City Health Secretariat. Reporting of tuberculosis and AIDS is mandatory, and both ART and anti-tuberculosis drugs are distributed exclusively by the government. By measuring rates of both tuberculosis and AIDS in the population of an entire large city, we would be able to assess trends in AIDS-related tuberculosis in the era of combination antiretroviral therapy.Three official databases (described below) of the City Health Secretariat of Rio de Janeiro were used to determine total number of AIDS cases, tuberculosis cases, AIDS deaths and AIDS/tuberculosis cases between 1995 and 2004, and the annual incidences of each. The official databases of AIDS and tuberculosis cases reported to the Health Department  are Brazilian nation-wide mandatory reporting systems for AIDS, tuberculosis, and deaths, respectively. The AIDS data have been maintained in an electronic database in the City Health Department since the first AIDS case was reported in 1982, as has been the situation for tuberculosis cases reported since 1995 and for deaths since 1979. Patients are included in databases when they are diagnosed with either AIDS or tuberculosis according to the Brazilian guidelines at the time of diagnosis. Information collected includes demographic and specific clinical information, including name, date of birth, mother's name and date of diagnosis. The forms are completed by a health professional in a primary care unit or in a hospital on the day the individual is diagnosed with the disease. The forms are then sent to the City Health Department and entered into a main electronic database, developed by the Brazilian Ministry of Health. Information on mortality is also kept in an electronic database and is based on the death certificate, completed by the attending physician at the time of death. In Brazil, tuberculosis is diagnosed in patients presenting with signs and symptoms compatible with tuberculosis on the basis of chest radiographs, sputum acid-fast bacilli smears, and response to anti-tuberculosis therapy In order to identify tuberculosis cases among AIDS patients, both the information about tuberculosis at the time of notification and a database linkage between AIDS and tuberculosis databases was performed. The primary components of the matching algorithm were patient name (last and first), mother's name, and date-of-birth. Briefly, a hierarchical algorithm combining an adaptation of the Soundex phonetic algorithm to the Portuguese language and a similarity score for strings implemented in the library difflib from Python Patients were considered to have tuberculosis at the same time as their AIDS diagnosis if they either had tuberculosis mentioned in their AIDS report form or if they had a tuberculosis episode found through linkage up to 30 days before AIDS diagnosis. In another definition, we also included those who had tuberculosis up to 30 days after AIDS diagnosis as having tuberculosis at AIDS diagnosis. These definitions were necessary because the surveillance systems are separate and so are physicians who report AIDS and/or tuberculosis, even in the same heath care facility, and small delays in reporting one or the other condition is expected. The two definitions were combined to provide the number of simultaneous diagnoses.To determine the proportion of AIDS patients who were diagnosed with tuberculosis within one year following their AIDS diagnosis, annual cohorts of patients diagnosed with AIDS in a calendar year were defined as denominators with tuberculosis diagnosed within up to one year since AIDS diagnosis among this population as numerators. Municipal surveillance estimates of number of AIDS patients receiving combination ART have been used to overlay graphs generated for this analysis. Generalized additive models (GAM) Between 1995 and 2004, 90,806 tuberculosis cases and 16,891 AIDS cases were reported in Rio de Janeiro. Initially, the AIDS registry listed 2,160 patients with a concurrent tuberculosis diagnosis. The 90,806 patients recorded in the tuberculosis registry were merged with 14,371 AIDS patients who did not have tuberculosis reported at AIDS diagnosis. This merge yielded an additional 1,962 coinfected cases. After comparing the registries and removing duplicates and recurrences, we found 3,125 AIDS cases who had one tuberculosis episode within one year of AIDS reporting, with 2,436 diagnosed within the first 30 days and 689 between 30 days and one year. The 3,125 tuberculosis episodes within one year of AIDS notification between 1995 and 2003 constituted 3.45% of all tuberculosis patients and 18.5% of all AIDS patients during that time.Tuberculosis notification rates  had a slThe proportion of patients with tuberculosis diagnosed within one year of AIDS diagnosis (including those between 0 and 30 days) over this time period is shown in In The population burden of AIDS-related tuberculosis in Rio de Janeiro decreased significantly between 1995 and 1998, however little change occurred between 1998 and 2003 despite the widespread increased distribution of HAART for AIDS patients during this time. Active tuberculosis notification rates have been steadily decreasing in Rio de Janeiro as has overall AIDS incidence. AIDS mortality has also been stable since 1999 despite the increase in HAART distribution. Though the proportion of patients developing tuberculosis after AIDS declined between 1993 and 2002, the magnitude of decrease was substantially less than that seen with other opportunistic infections, such as pneumocystis pneumonia and toxoplasmosis Overall AIDS mortality in Rio de Janeiro fell by 50% from 1995 to 1999, remaining somewhat stable since then. Beginning in 1997, combined antiretroviral use in Rio de Janeiro increased substantially. The declining trend in mortality in Brazil before the widespread availability of HAART was well documented both at the individual level Two significant changes in the AIDS definition in Rio de Janeiro occurred during the study period. First, in 1995, the definition was modified to include as an AIDS diagnosis any death certificate that mentioned AIDS as a basic cause of death. This was not previously done and is likely the reason for increased incidence of AIDS/tuberculosis co-infection between 1995 and 1996. Many AIDS patients die from tuberculosis and prior to 1996, a co-infected patient who died, but had not been reported to the Health Department as AIDS would have been counted only as a co-infection death, but not an AIDS case. This measure aimed to increase coverage of the surveillance system and in fact increased the amount of AIDS incidence in Brazil.A second significant change in the AIDS definition in Rio de Janeiro occurred during the study period in 1998. At this time patients who were HIV infected and had a CD4 count <350 were considered to have AIDS. The number of AIDS cases peaked in 1998 in response to the definition change. If the change in definition had not occurred, it is likely that proportion trends would have stabilized beginning in 1997, rather than 1998. The potential effectiveness of ART in reducing tuberculosis incidence appears to have been relatively unfazed by this definition change. However, the proportion of AIDS patients diagnosed with tuberculosis within one year of AIDS diagnosis has been relatively stable for quite some time. Thus, it is possible that there is a limit to the effectiveness of antiretroviral therapy in reducing tuberculosis incidence at the population level.The proportion of AIDS patients diagnosed with tuberculosis dropped substantially during the first several years of the study period, while the number of coinfected cases decreased markedly throughout the entire study period. Thus, it is likely that combined ART use influenced the overall decrease in tuberculosis incidence during the study period, or, at the very least helped prevent steep increases in tuberculosis incidence that would have otherwise occurred. AIDS-related tuberculosis in Rio de Janeiro decreased during the study period, whereas it increased in other countries with high rates of co-infection where ART was not available A limitation in this study is that the linkage was conducted with the AIDS registry rather than an HIV registry because HIV is not a reportable infection in Brazil. Even though our analysis may underestimate the true burden of co-infection among HIV-infected patients, similar trends in co-infection are observed when we included tuberculosis cases diagnosed between one and three years prior to AIDS diagnosis (data not shown). It is likely that tuberculosis diagnosed within 1 year, and possibly up to three years, prior to an AIDS diagnosis represents HIV-TB co-infection. Thus, even though inclusion in our analysis relies on an AIDS diagnosis, it is likely that our data closely resemble HIV-TB co-infection.A second limitation is the ecologic approach of investigating the association between decreasing co-infection and increased usage of antiretroviral therapy, in which associations should be seen with caution, since this kind of approach lacks a causal chain of events and could lead to the so-called ecologic fallacy. We did not link individual patient data with antiretroviral data, thus conclusions based on these analyses are primarily based on observation of trends in disease and number of patients receiving ART. Even though we do not have direct measures of HAART coverage in Brazil, we believe that it is high, since by law the government is obligated to provide free medication to all patients eligible for treatment according to Brazilian guidelines. Antiretroviral therapy has been shown to effectively reduce risk of tuberculosis in HIV-infected patients in cohort studies Our data suggest that antiretroviral therapy, when distributed to a large proportion of the HIV-infected population, reduces the incidence of tuberculosis. However, tuberculosis remains a common problem, with 15% of AIDS cases experiencing and episode of tuberculosis in the year following diagnosis, most within 30 days. Because tuberculosis is so often an early complication of HIV, many patients will not have been given ART prior to becoming ill with tuberculosis. Further interventions are necessary to significantly reduce the tuberculosis burden among HIV-infected persons. Treatment of latent tuberculosis infection among HIV-infected patients