Introduction

Early treatment of HIV infection with combination antiretroviral therapy (ART) improves health outcomes in infected individuals and reduces transmission [1–4]. Many public health experts advocate for expanding treatment provision through a “test and treat” strategy [5, 6], in which HIV-infected individuals are offered ART regardless of clinical status. Such policies have had beneficial impacts on HIV-related outcomes in resource-rich settings [7]. Yet despite the dramatic expansion of ART in sub-Saharan Africa (SSA) during the last decade [8], the mortality rate in this region continues to exceed that in resource-rich settings [9–13]. In SSA, late presentation to care [14], treatment refusal despite eligibility [15], low rates of pre-ART linkage to care [16, 17], high rates of attrition [18, 19], and interrupted treatment [20] all contribute to poor outcomes and hinder scale-up efforts.

The success of a “test and treat” strategy in SSA will depend on thoughtful consideration of the structural barriers that impede the ability of HIV-infected individuals to get tested, link to HIV care, stay in care, and adhere to ART. “Voltage drops” [21] may occur along the continuum of care, leading to diminishing numbers getting tested, successfully linking to and remaining in care, and achieving sustained adherence to ART. Qualitative studies have found that patients in the region frequently cite difficulty obtaining reliable transportation to clinic as a reason for treatment default, poor ART adherence, and other adverse health outcomes [22–24]. We hypothesized that the presence of geographic and transportation-related barriers would be associated with unfavorable outcomes at all points along the continuum of HIV care, and that this effect would be observed across different sub-continental regions, time periods, and study populations. Guided by these hypotheses, we conducted this review to systematically assess the extent to which—and in what manner—geographic and transportation-related barriers affect HIV outcomes in SSA.

Methods

Search Strategy

All procedures were performed according to the PRISMA guidelines [25]. We searched PubMed and Web of Science for manuscripts that were published prior to August 2011, using title and abstract key words to identify studies that examined associations between geographic or transportation-related barriers and HIV outcomes in SSA (for search terms, see Appendix). We used the “Find Duplicates” function in EndNote X4 (Thomson Reuters, New York, NY, USA) to identify and eliminate duplicates. In addition, we manually searched all abstracts from the International Conference on HIV Treatment and Prevention Adherence of the International Association of Physicians in AIDS Care [now International Association of Providers of AIDS Care (IAPAC)] from 2002–2004 and from 2006–2011.

Study Selection and Eligibility Criteria

Two investigators (AJL and MJS), working independently and in duplicate, screened the first 150 abstracts. Agreement on the selection of studies for full-text review was acceptable (k = 0.74), so a single investigator (AJL) completed the remainder of the screening. After the initial screening of abstracts, a single investigator (AJL) obtained full-text journal articles for all records to select studies for inclusion in the final review. We searched PubMed and Google Scholar to identify IAPAC abstracts that had been subsequently published as full-length manuscripts. IAPAC abstracts that had not been subsequently published were also considered for inclusion in the final review. We included all identified manuscripts that were the result of original research that was based at least partially in SSA, described a study population that was either predominantly HIV-infected or prescribed ART for other reasons (e.g. post-exposure prophylaxis), and reported data relating to one of the following four outcomes of interest: (1) voluntary counseling and testing (VCT), (2) pre-ART linkage to care (as defined by Govindasamy et al. [26]), (3) loss to follow-up (LTFU) and/or mortality, and (4) ART adherence and/or viral suppression. Additionally, studies were categorized as eligible during a second round of screening if they described a relationship between at least one of these outcomes and a geographic or transportation-related exposure variable: (1) travel distance, (2) travel time, (3) transportation cost, or (4) rural versus urban setting. In cases where the manuscript or IAPAC abstract contained insufficient information to evaluate estimates of geographic or transportation-related barriers, we contacted the authors to obtain additional information. We also included a limited number of manuscripts and abstracts that were recommended by experts in the field but not identified in our systematic search. There were no language exclusion criteria. In the final compilation of reviewed manuscripts, we only included studies that were conducted in SSA, where the substantial majority of the world’s HIV-infected population resides [8], in order to maintain generalizability of our findings to this region.

Data Extraction

Using a standardized extraction form, data from all eligible studies were extracted by a single investigator (AJL). An initial attempt was made to aggregate study results for meta-analysis; however, substantial heterogeneity in the definition and measurement of study exposures and outcomes precluded this. Therefore, we proceeded with a systematic review. Beyond these quantitative studies, we sorted identified manuscripts into two additional categories of studies—(1) descriptive, and (2) qualitative. These studies were deemed to be important to understanding the geographic and transportation-related barriers to HIV care, but did not report an inferential statistical relationship. Manuscripts in these categories met all other inclusion criteria and were identified during the same systematic search process. We defined as descriptive any study that reported a proportion of respondents indicating a geographic or transportation-related factor to be a barrier to HIV care, but that did not estimate an association between this exposure and one of our outcomes of interest. If the authors estimated an association, the study was defined as quantitative. We defined as qualitative any study that reported general themes regarding geographic or transportation-related barriers to HIV care, but did not report specific proportions.

Data Analysis

In our primary analysis, we examined all eligible quantitative studies. One study [27] did not report data in the form of an odds ratio (OR); therefore, we calculated an OR using the data that were presented. Using author-provided definitions, we considered shorter distance, shorter travel time, lower transportation cost, and urban (versus rural) residence as the referent categories. Each estimate of association was categorized as an inverse effect (i.e. increasing distance, time, cost, or rural location was associated with worsened HIV outcomes such as lower rate of VCT completion, linkage, or adherence; or, greater rate of LTFU or mortality), a null effect, or a positive effect (i.e. increasing distance, time, cost, or rural location was associated with improved HIV outcomes such as higher rate of VCT completion, linkage, or adherence; or, lower rate of LTFU or mortality).

We summarized the percentage of studies demonstrating an inverse, null, or positive effect when categorized by study-level variables such as sub-continental region (Eastern Africa, Southern Africa, or Western Africa) as defined by the United Nations (UN); study population [HIV-infected adults, HIV-infected children, HIV/tuberculosis (TB) co-infected individuals receiving anti-TB therapy, or pregnant women receiving services for the prevention of maternal to child transmission of HIV (PMTCT)]; and study time period (pre–2003, 2003–2006, or post–2006). The study time period date ranges were selected based on 2003 being the initial year of the President’s Emergency Plan for AIDS Relief, and 2006 being the year in which member states at the UN High Level Meeting on AIDS resolved to scale up access to HIV care with a goal of universal access by 2010.

Assessment of Study Quality

For studies reporting a statistical association between a geographic or transportation-related barrier and an HIV outcome, we designed an assessment tool that accounted for seven parameters within the following four domains: (1) study design and population, (2) exposure measurement, (3) outcome measurement, and (4) data analysis.

Results

Study Selection

We identified 1,008 full-length manuscripts and 763 conference abstracts during our initial search. After excluding 1,487 records on the basis of the initial screen, we reviewed 273 full-length, published manuscripts and 11 IAPAC abstracts that had not yet been published as manuscripts. We also included six studies identified outside of our systematic screening protocol. A total of 66 studies were included in our review: 29 quantitative studies, 17 descriptive studies, 15 qualitative studies, and five studies that contained both descriptive/qualitative and quantitative data (Fig. 1). All studies included in the final review were conducted exclusively in SSA. Excluding two qualitative studies that did not report the number of participants, and accounting for studies that included more than one type of data, these studies involved 131,325 participants from 15 different countries in SSA.

Fig. 1
figure 1

PRISMA flow diagram of studies identified for review. Studies were identified using a systematic search of PubMed and Web of Science (WoS), as well as manual search of conference abstracts from the International Association of Physicians in AIDS Care (IAPAC) annual meeting from 2002 to 2011

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Study Characteristics: Descriptive Studies

In the descriptive studies (Table 1 [28–48]), participants commonly indicated geographic and transportation-related barriers as factors that promoted poor outcomes throughout the continuum of HIV care, including delaying or forgoing HIV testing (percent of study participants ranging from 4.9 to 20.7 %; three studies [28–30]), not successfully linking to HIV care (range 3.8–44 %; two studies [31, 32]), missing clinic visits or dropping out of care (range <5–20.1 %; four studies [33–36] ), or failing to adhere to ART (range 5–70 %; 12 studies [37–48]). These studies represented 72,642 subjects in ten countries: Botswana, Cote d’Ivoire, Kenya, Malawi, Nigeria, Tanzania, Togo, Uganda, Zambia, and Zimbabwe.

Table 1 Descriptive studies
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Study Characteristics: Qualitative Studies

Among the qualitative studies that we identified (Table 2 [24, 49–63]), participants described geographic and transportation-related barriers as factors that impeded successful navigation of several points along the continuum of HIV care, including pre-ART linkage to care (four studies [49–52]), retention in care once on ART (one study [53]), and maintenance of optimal adherence to ART (11 studies [24, 54–63]). In these studies, prominent themes included lack of money to pay for transportation to clinic [24, 49–54, 57, 59], being forced to decide between paying for transportation to clinic and basic necessities such as feeding one’s family or purchasing medications for opportunistic infection prophylaxis [52, 63], and the need to draw on social supports to overcome transportation barriers [62]. Poor road conditions [46], difficulty accessing reliable transportation [24], and the inability to take time off from work to travel long distances to clinic [51], were also described as factors that contributed to transportation difficulties. These studies represented at least 5,373 participants in ten countries: Botswana, Ethiopia, the Gambia, Kenya, Malawi, Namibia, Nigeria, South Africa, Tanzania, and Uganda.

Table 2 Qualitative studies
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Study Characteristics: Quantitative Studies

In the 34 quantitative studies (Table 3 [27, 36, 42–44, 59, 64–91]), there were 52 estimated associations between geographic or transportation-related barriers and HIV-related outcomes of interest: VCT [two (4 %)], pre-ART linkage to care [eight (15 %)], LTFU or mortality [17 (33 %)], and ART adherence or viral suppression [25 (48 %)]. Geographic or transportation-related barriers had an inverse association with HIV outcomes in 23 estimates (44 %), whereas 26 estimates (50 %) were null and three estimates (6 %) demonstrated a positive effect. When we evaluated these estimates by outcome of interest, we found an inverse association between geographic or transportation-related barriers and HIV outcomes for 2/2 (100 %) VCT estimates, 4/8 (50 %) pre-ART linkage estimates, 8/17 (47 %) LTFU or mortality estimates, and 9/25 (36 %) adherence or viral suppression estimates (Table 4). These studies represented 106,574 participants from nine countries: Ethiopia, Kenya, Malawi, Mozambique, Nigeria, South Africa, Tanzania, Uganda, and Zambia.

Table 3 Quantitative Studies
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Table 4 Quantitative studies grouped by exposure and outcome of interest
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Exposure and Outcome Heterogeneity

The frequency with which geographic and transportation-related barriers were estimated to have an inverse effect on HIV outcomes varied according to the method of exposure measurement, sub-continental region, time period, study population, number of study participants, and number of study sites (Table 5). Among the three estimates based on an objective measure of distance, two (67 %) demonstrated an inverse effect. Among the 12 estimates where the exposure was residence in a rural area, nine (75 %) demonstrated an inverse effect. In contrast, an inverse effect was shown in only 3/15 (20 %) estimates based on self-reported distance, 5/13 (38 %) based on self-reported travel time, and 0/4 (0 %) based on self-reported transportation cost. When analyzed by sub-continental region, an inverse effect was demonstrated in 13/35 (37 %) studies conducted in Eastern Africa, 3/8 (38 %) in Western Africa, and 7/9 (78 %) in Southern Africa. There was limited variability in the percentage of estimates demonstrating an inverse association when categorized by time period, with 5/8 (63 %) studies conducted prior to 2003, 17/36 (47 %) conducted from 2003 to 2006, and 15/32 (47 %) conducted after 2006 demonstrating an inverse effect. Similarly, there was limited variability in these findings between studies conducted in different patient populations, with the exception of studies of women enrolled in PMTCT care, where 0/3 (0 %) of studies found an inverse effect. An inverse effect was demonstrated with greater frequency in larger studies, with 2/15 (13 %) studies with n < 200, 8/19 (42 %) studies with n = 201–1,000, and 12/17 (72 %) studies with n > 1,000 demonstrating an inverse effect. Furthermore, multi-site studies [13/18 (72 %)] were more likely than single site studies [7/30 (23 %)] to demonstrate an inverse effect. Additionally, there was significant heterogeneity in the definition and measurement of both exposure and outcomes between studies (Table 6).

Table 5 Variability in estimates by study parameter
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Table 6 Heterogeneity in measurement and definition of exposures and outcomes
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Assessment of Study Quality and Risk for Bias

Of the 34 quantitative studies that we identified, 25 (74 %) involved a longitudinal cohort, four (12 %) were specifically designed to measure an association between a geographic or transportation-related barrier and an HIV outcome, five (15 %) reported an objectively measured exposure variable, 28 (82 %) reported an objectively measured outcome variable, 20 (59 %) performed a multivariable analysis to adjust for potential confounders, and six (18 %) adjusted for a marker of wealth in the multivariable analysis (Table 7). Among the 25 cohort studies in which accounting for LTFU, censoring, or missing data would be relevant to potential bias, 14 (56 %) adequately did so. Of the four studies that were specifically designed to measure an association between a geographic or transportation-related barrier and an HIV outcome, three (75 %) demonstrated an inverse effect. Of the ten studies that included a multivariable analysis, used an objectively measured outcome variable, and adequately accounted for LTFU, censoring, and missing data, seven (70 %) found an inverse effect.

Table 7 Assessment of study quality and risk of bias
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Discussion

In this systematic review of 66 studies representing over 130,000 persons receiving HIV care across 15 countries in SSA, we found that geographic and transportation-related barriers were associated with worse outcomes throughout the continuum of HIV care. These inverse associations were observed with variable frequency across different regions, different time periods, and among several sub-populations of HIV-infected individuals. In addition, geographic and transportation-related barriers were characterized as important by a large proportion of participants in descriptive and qualitative studies. This substantial body of evidence supports our hypothesis that geographic and transportation-related barriers contribute to poor outcomes for HIV-infected individuals in SSA at all points along the continuum of HIV care.

Overall, we found that ~50 % of estimates demonstrated an inverse association between a geographic or transportation-related barrier and an HIV-related outcome. This proportion varied across different study-level parameters, including sub-continental region, time period, study population, number of participants, and number of study sites. It is notable that studies with greater numbers of participants were more likely to report an inverse effect of geographic and transportation barriers on HIV outcomes, suggesting that smaller studies may not have had sufficient statistical power to estimate such an association with precision. Furthermore, in our assessment of study quality and risk for bias, we found that the higher quality studies were more likely than those of lesser quality to have reported an inverse association between geographic or transportation barriers and an HIV outcome.

Interpretation of our findings is subject to several important limitations. First, most of the quantitative observational studies that we identified were not designed to evaluate geographic or transportation-related barriers as the primary exposure of interest. In our analysis of study quality, we did find that studies specifically designed for this purpose were more likely to report an inverse association than those for which such an analysis was a secondary aim. Second, authors often neglected to adjust for potential confounding variables (or did not report the variables that were adjusted for). However, studies that did adjust for potential confounding variables were more likely to report an inverse effect than those that failed to do so. Third, our summary measures are crude relative to the pooled relative risks and odds ratios that would be calculated in a meta-analysis. However, as previously noted, the heterogeneity in study designs among the identified studies precluded a formal meta-analysis. A fourth and related limitation was the significant variability in measurement and definition of both exposure and outcome variables (as demonstrated in Table 6). Self-reported measures of geographic and transportation-related barriers, such as travel time, distance, and cost, are intrinsically subjective measures that may either under- or over-estimate true difficulties in health care access [92]. For example, in one recently published study of people on HIV treatment in rural Uganda, distance measures based on global positioning systems were inversely associated with missed clinic visits, while self-reported distance measures were not [93]. Additionally, most quantitative studies identified in this review defined the exposure variable as categorical or binary, rather than continuous. This resulted in a wide range of cut-off values when comparing relatively “shorter” versus “longer” travel distance and time, or relatively “higher” versus “lower” transportation cost. Finally, the null findings of some studies may have resulted from the design of the study itself. For example, Haberer et al. [82] found that, among HIV-infected children in Uganda, neither travel time nor transportation cost had a statistically significant association with ART adherence. It should be noted that participants living >20 km from clinic were excluded from that study, and that this was the most common reason for exclusion. If the effect of travel time on ART adherence were non-linear (e.g. no association below a certain threshold and an inverse effect at distances above the threshold), then the exclusion criteria of this study would preclude valid estimation of an association between distance and adherence.

We were surprised to find a small number of studies that demonstrated a paradoxically beneficial impact of geographic and transportation-related barriers on HIV outcomes [65, 70, 73]. It is notable that none of these three studies was specifically designed to estimate the effect of a geographic or transportation barrier on an HIV outcome. In certain cases, the findings were not fully inconsistent with our hypothesis that geographic and transportation barriers negatively affect HIV outcomes. For example, Geng et al. [70] found that among patients LTFU from clinic, greater distance to clinic was associated with increased likelihood of re-establishing care at different site. The authors hypothesized that this was due to emergence of new clinics as part of treatment decentralization in Uganda. Importantly, the reference clinic was the only ART provider in southwest Uganda in year 2000, while in 2009 (at the time of the study) there were over 60 rural treatment sites in the same region. Although Cook and colleagues found that greater distance to clinic was associated with a higher rate of linkage from PMTCT to early infant diagnosis care, this study excluded mothers who failed to enroll in adult HIV care after their pregnancy, which accounted for nearly half of the total sample [65]. Finally, although Massaquoi and colleagues found that patients treated at a rural health center were significantly less likely to default on ART than those treated at an urban center, the authors also found that rural patients had a significantly higher mortality rate compared to their urban counterparts [73]. Furthermore, this analysis was not adjusted to account for potential confounding variables.

Alternatively, these paradoxical findings may be explained in part by HIV-related stigma. HIV is highly stigmatized throughout SSA [94], with increasing evidence suggesting that the stigma of HIV is an important determinant of health-related behaviors, such as HIV testing [95], disclosure of sero-positivity to sexual partners or other social supports [96], retention in care [97], and HIV treatment adherence [98]. It is also possible that in certain settings some people may prefer to travel longer distances for their HIV care in order to maintain their anonymity, a phenomenon that has been discussed in HIV-related studies conducted in various African settings [99–101]. Thus a highly motivated population of patients who intentionally travel long distances to minimize stigma could account for a paradoxically positive association between distance and HIV-related outcomes.

Conclusions

We found that geographic and transportation-related barriers impede access to care at all points in the HIV care continuum. This systematic review has important implications for HIV policy and programming in SSA. The provision of HIV care across large rural catchment areas in many parts of SSA presents a significant challenge to scaling up services for HIV-infected individuals and retaining patients in care with optimal and durable adherence. Although the distance one lives from their HIV clinic is not a readily modifiable risk factor, geographic and transportation-related barriers could be attenuated by public health interventions that seek to improve the accessibility of HIV care facilities. Recommended measures to mitigate these effects have included strengthening investment in rural health care infrastructure [102], decentralization of HIV treatment services [103–105], adoption of simplified management protocols that can be administered at the level of the primary health clinic [106], decreasing visit frequency [107], implementation of mobile clinics [108], point-of-care testing [109], immediate referral [110], improving patient-provider communication of test results and other information [111], and provision of transportation stipends [112, 113].

Additionally, identification of standardized and validated measures of geographic and transportation-related barriers might improve risk-stratification and resource allocation to patients in the region. To optimize and expand HIV care delivery in SSA, it will be important to standardize the measurement of geographic and transportation-related barriers and to develop, evaluate, and scale up interventions to mitigate them. Different interventions will likely need to be designed to address different points in the continuum of HIV care. For example, point-of-care CD4 testing and immediate referral for treatment initiation are likely to be effective interventions for improving pre-ART linkage to care, whereas decreasing visit frequency may be a more effective intervention to help patients overcome geographic and transportation-related barriers to maintaining optimal ART adherence. Decentralization of treatment facilities will diminish the transportation time and cost for patients seeking regular and sustained HIV care. In areas where HIV care decentralization is underway, these efforts should be continued. We also urge policy-makers to aggressively pursue service decentralization, and to prioritize investment in the necessary rural health care infrastructure. Finally, interventions that seek to better monitor ART adherence in real time may help to overcome geographic and transportation-related barriers by identifying and allowing for targeting of patients who are at high risk for viral rebound and other poor outcomes. Such interventions are actively being explored [114–117].