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Healthcare Programmes for Truck Drivers in Sub-Saharan Africa: A Systematic Review and Meta-Analysis

  • Samanta Tresha Lalla-Edward ,

    Affiliation Wits Reproductive Health and HIV Institute, University of the Witwatersrand, Johannesburg, South Africa

  • Siyabulela Christopher Fobosi,

    Affiliation Wits Reproductive Health and HIV Institute, University of the Witwatersrand, Johannesburg, South Africa

  • Catherine Hankins,

    Affiliations Department of Global Health/Amsterdam Institute for Global Health and Development, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom

  • Kelsey Case,

    Affiliation Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom

  • W. D. Francois Venter,

    Affiliation Wits Reproductive Health and HIV Institute, University of the Witwatersrand, Johannesburg, South Africa

  • Gabriela Gomez

    Affiliations Department of Global Health/Amsterdam Institute for Global Health and Development, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands, Department of Global Health, London School of Hygiene and Tropical Medicine, London, United Kingdom



Truck drivers have unique health needs, and by virtue of their continuous travel, experience difficulty in accessing healthcare. Currently, planning for effective care is hindered by lack of knowledge about their health needs and about the impact of on-going programmes on this population’s health outcomes. We reviewed healthcare programmes implemented for sub-Saharan African truck drivers, assessed the evaluation methods, and examined impact on health outcomes.


We searched scientific and institutional databases, and online search engines to include all publications describing a healthcare programme in sub-Saharan Africa where the main clients were truck drivers. We consulted experts and organisations working with mobile populations to identify unpublished reports. Forest plots of impact and outcome indicators with unadjusted risk ratios and 95% confidence intervals were created to map the impact of these programmes. We performed a subgroup analysis by type of indicator using a random-effects model to assess between-study heterogeneity. We conducted a sensitivity analysis to examine both the summary effect estimate chosen (risk difference vs. risk ratio) and model to summarise results (fixed vs. random effects).


Thirty-seven publications describing 22 healthcare programmes across 30 countries were included from 5,599 unique records. All programmes had an HIV-prevention focus with only three expanding their services to cover conditions other primary healthcare services. Twelve programmes were evaluated and most evaluations assessed changes in input, output, and outcome indicators. Absence of comparison groups, preventing attribution of the effect observed to the programme and lack of biologically confirmed outcomes were the main limitations. Four programmes estimated a quantitative change in HIV prevalence or reported STI incidence, with mixed results, and one provided anecdotal evidence of changes in AIDS-related mortality and social norms. Most programmes showed positive changes in risk behaviours, knowledge, and attitudes. Our conclusions were robust in sensitivity analyses.


Diverse healthcare programmes tailored to the needs of truck drivers implemented in 30 sub-Saharan African countries have shown potential benefits. However, information gaps about availability of services and their effects impede further planning and implementation of effective healthcare programmes for truck drivers.


Transport workers, such as truck drivers, have specific healthcare needs. Globally, they bear a disproportionate health burden, including high rates of sexually transmitted infections (STI), cancer, cardiovascular diseases, chronic conditions (predominantly diabetes, obesity, backache, leg pains), respiratory diseases, and an array of mental health conditions (with the most common being depression, anxiety, chronic insomnia, personality disorders and post-traumatic stress disorder). Occupational factors that increase risk include irregular schedules, sedentary lifestyle due to long hours of driving/sitting, musculoskeletal and other injuries due to loading and unloading cargo, exposure to road accidents and deaths, extended periods of social isolation, unhealthy food choices on the road and poor access to healthcare [17].

In sub-Saharan Africa, transport corridors are essential for local economies due to lack of waterways and inadequate rail services. These corridors have been characterised as being affected by transience, unemployment, and poverty [810]. Because of the transcontinental nature of the transport industry, health programmes prioritising truck drivers require complementary national healthcare policies. Most countries in the region are aware of the susceptibility of transport workers to poor health outcomes and Ministries of Transport and Health have begun to develop strategic plans to address this issue [11]. However, public sector financial and human resources constraints have delayed progress [12].

The trucking industry in sub-Saharan Africa is predominantly privately-run and has attracted international donor and domestic funding for work-related programmes tackling different aspects of truck drivers’ health needs. Increasingly, implementation has been proceeding across the region of healthcare programmes prioritising truck drivers and concentrating on services to increase awareness and identification of communicable (STI, HIV (including prevention of mother to child transmission (PMTCT), tuberculosis, and malaria) and chronic diseases (hypertension and diabetes), as well as general primary healthcare [1336]. Nevertheless, further planning for efficient implementation, scale-up, and sustainability of healthcare programmes for truck drivers is hindered by knowledge gaps about this population’s needs and the impact of existing healthcare services on health outcomes. In this review, our objective is to describe healthcare programmes implemented in sub-Saharan Africa prioritising truck drivers, assess the methods used to evaluate them, and evaluate their impact on truck drivers’ health outcomes.


We performed a systematic review of the published and unpublished literature following the registered protocol (CRD42014013327) on the international prospective register of systematic reviews, Prospero [37]. We adhered to the PRISMA guidelines for reporting of systematic reviews and meta-analyses; the PRISMA checklist is provided in S1 Table [38].

Search strategy and study selection

We searched scientific databases such as PubMed/Medline and ISI Web of Knowledge, institutional databases (University of Witwatersrand, Imperial College London, London School of Hygiene and Tropical Medicine, University of North Carolina), non-profit organisations and country-level reports (South African National AIDS Council, USAID-PEPFAR, NGO websites), and online search engines (google, google scholar) using a broad search strategy including both MeSH headings and free text (29 permutations of search terms related to: 1) the population (truck driver, lorry driver, long haul driver, long distance driver, driver); 2) intervention (health intervention); and 3) outcome (odds ratio, risk ratio, evaluation, cost-effectiveness, effect, impact, effectiveness)), with no date or language limitations. Experts and non-profit organisations working with truck drivers (or with migrant populations in general) were consulted separately to identify unpublished reports. We also reviewed country-level reports of funders and NGO (i.e. South African National AIDS Council, USAID-PEPFAR, NGO websites). Citations and bibliographies of records were reviewed to identify additional relevant material. All searches were run independently by two researchers (STLE and SCF). Results were downloaded, duplicates removed, and a database of all possible records organised for review by the end of January 2015.

Titles and abstracts were then screened by two independent reviewers (STLE and GG) to include all publications and reports describing a healthcare programme in sub-Saharan Africa providing services designed specifically for truck drivers. The full text records of all the material selected for further examination were assessed independently for inclusion. Two reviewers (STLE and GG) compared the final list of selected material.

Data extraction and analysis

We designed a pre-defined tool to extract data describing each programme, its evaluation method and reported results. Data included: implementation and evaluation years, implementation and evaluation locations, services provided, service providers, funders, evaluators, details of evaluation method, and reported results. One reviewer undertook the data extraction (STLE) and a second reviewer (GG) conducted a quality control check.

We present tabulated data describing current and past healthcare programmes, providing an overview of these programmes in the region by type and coverage over time. We then provide a critical assessment and a narrative review of the evaluation methods used. Methodological quality of each evaluation was assessed on the basis of study’s internal validity (sites and population included, sample size, and sampling method), data reported, and whether a comparison group was included in the analysis. Due to variation across studies in the ways of reporting evaluation results, all indicators reported were mapped against a logic model for programme evaluation connecting the following elements: inputs (e.g., staff), activities (e.g., trainings, services), outputs (e.g., clients served, tests conducted), and results ranging from intermediate outcomes (e.g., risk behaviour change) to long-term impact (e.g., reduction in STI incidence) [39].

Whenever possible, we calculated unadjusted risk ratios (RRs) and 95% confidence intervals (CIs) from data provided. We present these RRs and 95% Cl for all impact and outcome indicator results in forest plots to provide an overview of the potential impact these programmes have had on truck driver health. We performed a sensitivity analysis to assess the robustness of our findings to the choice of summary statistic and calculated unadjusted risk differences and 95% CI from data provided as an alternative. Because the results presented in the forest plots presented significant heterogeneity, we assessed the sources of between-study heterogeneity through a subgroup analysis by type of indicator. Outcome indicators were assessed in two broad categories: 1) indicators of risk behaviour (condom use, number of sexual partners, alcohol and drug use) and 2) indicators measuring knowledge, attitudes, and perceptions. Impact indicators included reported measures of HIV prevalence and STI incidence. We applied a random-effects model to calculate summary RRs and 95% Cl by subgroup. The robustness of our findings to this methodological decision was tested by re-running the analysis using a fixed-effects model to calculate summary statistics by subgroup. All analyses were conducted in STATA 12.

Ethics statement

The proposed study was approved by the University of the Witwatersrand Human Research Ethics Committee (M140506) as one of the objectives in a process evaluation project of North Star Alliance’s services in Southern Africa.


We included 37 publications from 5,599 identified unique records. The results of the searches and selection process are summarised in Fig 1.

Fig 1. Flow diagram of study selection.

n, number; HC, healthcare.

Overview of healthcare programmes for truck drivers

The selected publications described 22 healthcare programmes across 30 countries. Table 1 presents a summary description of each programme.

Table 1. Description of healthcare programmes for truck drivers in sub-Saharan Africa.

Although we searched for healthcare programmes in general and aimed to include any programme providing services for any health-related issues, all programmes identified cover HIV-related interventions, with only three programmes expanding their services to cover malaria, tuberculosis, or general primary care services (i.e. ROADS II, Corridors of Hope, and North Star Alliance) [17, 18, 27, 36, 4043]. The majority of the programmes rely strongly on peer educators and healthcare workers to offer HIV prevention services. These include behaviour change communication (BCC) (n = 15); condom marketing and distribution (n = 16); STI screening and/or syndromic treatment (n = 11); stigma reduction activities (n = 10); information, education, and communication (IEC) (n = 9); HIV testing and counselling (HTC) (n = 9) through outreach or site-based programmes, in addition to capacity building for community or local staff, PMTCT, family planning, income generation activities, and linkage to clinical and social support services in 11 programmes.

The African Medical and Research Foundation (AMREF) implemented the first healthcare programme for truck drivers in the region in 1989 in Tanzania [26]. This programme lasted four years and focused on IEC for HIV prevention. Shortly thereafter, in 1990, World Vision introduced a programme in Southern Africa (Mozambique, Swaziland, Zambia, and Zimbabwe) [30]. The World Vision programme is ongoing, making it the longest running truck driver healthcare programme in sub-Saharan Africa. Fourteen [2126, 28, 30, 31, 3335, 4448] of the 22 identified programmes were delivered within a single country setting, whilst four [1320, 27, 30, 36, 4043] programmes have broader geographical coverage, covering eight or more countries.

Programmes with a broad geographical coverage vary in their objectives and approach. The Corridors of Hope project, implemented in 11 countries, provides services to key populations (including truck drivers, female sex workers, and members of surrounding communities) along transport corridors and at border sites. The main focus of the project is comprehensive HIV prevention services and improved linkages and referral networks [43]. The ROADS II project, operational in eight countries, aims primarily to address HIV and other health issues in the communities around transport corridors by engaging with the communities and community leadership to ensure uptake of services provided at the programme’s SafeTstops [13]. The World Food Program’s HIV training programme, implemented in ten countries, is a train-the-trainer initiative for truck drivers and contract workers with a focus on BCC and activities to reduce stigma and discrimination [30]. The North Star Alliance Programme, active in 12 countries, is a primary healthcare programme delivered through stationary and mobile clinics operated by healthcare workers and peer educators [36]. Countries in Southern Africa with high HIV prevalence, such as Zambia, Zimbabwe, Tanzania, and Mozambique, had five or more programmes active nationally. Fig 2 illustrates the distribution of programmes per country against adult HIV prevalence in the general population and along main transport corridors in 2014 [49]. We observed a variety of funders, with domestic investments constituting a minority. Among international funders, USAID represents the largest investor, with just under half of the programmes (n = 9) funded or co-funded by this agency.

Fig 2. Country-level HIV prevalence and number of healthcare programmes for truck drivers [62].

The numbers shown per country represent the total number of healthcare programmes available in each country for truck drivers.

Evaluations of healthcare programmes for truck drivers

Of the 22 programmes identified, just over half (n = 12) were evaluated in 17 countries [2123, 2527, 2932, 34, 4043, 45, 4852]. A detailed description of the evaluation methods is provided in Table 2.

Table 2. Description of methods used during programme evaluations.

Evaluations were conducted between 1990 and 2012 in single countries, with the exception of two programmes that were evaluated across several countries [32, 51]. Programmes tended to be evaluated only once, excluding the Corridors of Hope project that underwent five evaluations, three external and two internal, during the period 2000 to 2009 [27, 4043]. External evaluators performed five of the 12 evaluations [31, 32, 34, 50, 51]. Methodological approaches and their quality varied across studies from qualitative appraisals, including focus group discussions and interviews, to quantitative designs such as pre- and post-intervention surveys, statistical analysis of routinely-collected data, and trend analysis of repeated cross-sectional surveys. Sampling strategies, when used, and sample sizes also varied across evaluations. Due to the mobility of this population, most of the evaluations had to adjust their sample size and sample method to make use of simple random or purposive sampling. We assessed major limitations in the majority of evaluation studies. These included: 1) absence of control or comparison groups (n = 10),[21, 22, 26, 27, 29, 31, 32, 34, 4043, 45, 48, 50, 51] hindering the attribution of any effect observed to the programme, and 2) the lack of biological data measurements (e.g. HIV/STI testing), introducing biases in reporting of some of the evaluated outcomes (n = 4) [22, 23, 26, 27, 32, 4043, 53].

A detailed description of the 75 indicators reported in 12 programme evaluations can be found in Table 3, with the reported results in Table 4. Four programmes reported on inputs and activities available within programmes (i.e. number of sites established, staff trained and resources used) [32, 34, 50, 51]. Only two programmes [50, 51] provided information on costs, however they did not evaluate the programme’s cost-effectiveness. All programmes reported output (n = 42) or outcome indicators (n = 16). Output indicators generally described the volume of services provided and clients reached. Six programmes provided sufficient data on outcome or impact indicators to be included in the meta-analysis. A total of five programmes, evaluated in Benin, Ethiopia, Ghana, Ivory Coast, Kenya, Nigeria, Tanzania, Togo and Zambia, reported one or more impact indicator results [21, 26, 32, 42, 50]. These impact indicators included changes in HIV prevalence for one programme and STI incidence for four [21, 26, 32, 42] programmes. However, only one study conducted biological STI testing. It provided syphilis serology for all patients and further investigation for symptomatic patients, including culture for Neisseria gonorrhoeae and Haemophilus ducreyi, and antigen detection of Chlamydia trachomatis [21]. The other programmes relied on self-reported symptoms. One programme reported changes in AIDS-related mortality, stigma, and social norms using qualitative data [50].

Table 3. Mapping of programme results using a programme evaluation framework [39].

Table 4. Evaluation results of programmes reporting changes in indicator results for TD populations only.

Impact of healthcare programmes

In Figs 3 and 4 we provide an overview of the potential impact on truck driver health by programme by plotting the RRs and 95% CI for all reported outcomes and impact indicators.

Fig 3. Relative risk in impact indicators by programme.

ID, identification; RR, relative risk; 95% CI, 95% confidence interval; HIV, human immunodeficiency virus; STI, sexually transmitted infection; OCAL, The HIV/AIDS project for the Abidjan-Lagos Corridor, currently Organisation du Corridor Abidjan-Lagos project; AMREF, African Medical & Research Foundation; BRRP, Behavioural risk-reduction programme; COH, Corridors of Hope.

Fig 4. Relative risk in outcome indicators by programme.

ID, identification; RR, relative risk; 95% CI, 95% confidence interval; HIV, human immunodeficiency virus; STI, sexually transmitted infection; OCAL, The HIV/AIDS project for the Abidjan-Lagos Corridor, currently Organisation du Corridor Abidjan-Lagos project; AMREF, African Medical & Research Foundation; BRRP, Behavioural risk-reduction programme; COH, Corridors of Hope; HRCI, High Risk Corridor Initiative; Nigeria, Improving HIV/AIDS knowledge and risk behaviours of drivers; m, months; SP, sexual partner; MOT, modes of transmission; SW, sex worker; AIDS, acquired immunodeficiency syndrome.

The programmes reported mixed results on impact indicators with two [26, 32, 53] out of four programmes [21, 26, 32, 42, 53] showing an increase in reported prevalence of STIs. Results for outcome indicators were consistent across the programmes, with decreases in reported risk behaviours or misconceptions and negative attitudes towards people living with HIV. All programmes reported substantial increases in output indicators, such as the number of HTC sessions or the numbers of condoms distributed (Table 4).

Finally, in Fig 5 we present a subgroup analysis exploring the heterogeneity in the results by type of indicator reported. While the indicators reported did not explain all the heterogeneity present in the results (with all p values <0.001 for all subgroups analysed), the main impact of these programmes can be shown as a significant reduction in risk behaviours and negative attitudes and misconceptions reported against people living with HIV, with all RRs below one. Alternative S1, S2 and S3 Figs are presented in the supplementary material plotting risk differences and 95% CI for all outcomes and impact indicators and using a fixed-effects model as an alternative to the random effects model, respectively. Our results were robust to these sensitivity analyses.

Fig 5. Subgroup analysis, summary relative risk estimates by type of indicator.

ID, identification; RR, relative risk; 95% CI, 95% confidence interval; HIV, human immunodeficiency virus; OCAL, The HIV/AIDS project for the Abidjan-Lagos Corridor, currently Organisation du Corridor Abidjan-Lagos project; STI, sexually transmitted infection; BRRP, Behavioural risk-reduction programme; AMREF, African Medical & Research Foundation; COH, Corridors of Hope; Nigeria, Improving HIV/AIDS knowledge and risk behaviours of drivers; HRCI, High Risk Corridor Initiative.


In this systematic review we describe 22 healthcare programmes prioritising truck drivers that have been implemented in 30 countries across sub-Saharan Africa. These healthcare programmes included short-term interventions of narrow scope, such as limited primary health care and diagnosis of communicable diseases. A minority of healthcare programmes expanded the scope to include gender based violence reduction and palliative care. While most countries had or have healthcare programmes for truck drivers that provide services of HIV prevention and diagnosis, no antiretroviral treatment (ART) services have been offered on site. This provision of vertical services reflects the overall regional HIV disease burden and the particular focus of donors, while the lack of ART provision of reflects the logistical challenges of treatment provision across borders. Regionally, HIV prevalence estimates among truck drivers have been reported as high. Studies from Nigeria show a 10% HIV prevalence among truck drivers [54] while South African surveys have reported HIV prevalence estimates in truck drivers who were clients of female sex workers as high as 56% [55] and in truck drivers in general as 26% [56], in 2001 and 2003/4 respectively [57]. This increased vulnerability to acquiring and transmitting HIV among truck drivers has prompted UNAIDS and national governments to identify them as a key population, prioritising this group in their HIV programmes, as does South Africa’s National Strategic Plan on HIV, TB and STIs 2012–2016 [11], for example. However, the majority of the programmes in this review did not actively seek to identify people living with HIV (through HTC) and link them to care, but rather focussed on healthcare messaging and BCC. Although this is in keeping with findings of the 2012 review of sex worker programmes in Africa [58], healthcare programmes for truck drivers have seen a progression in scope from 2001 onwards reflected in the increasing (though still insufficient) number of services delivered from satellite and mobile clinics. The World Health Organisation and UNAIDS focus on increasing testing and linkage to ART care can be translated, among truck drivers, into 90% of truck drivers living with HIV being aware of their HIV-positive status, 90% of HIV-positive truck drivers being on ART, and 90% of truck drivers on ART achieving viral suppression [59]. In the absence of data, and with the very limited coverage of these programs, it seems that there is a considerable way to go from what appears to be a low baseline for all three of these indicators in truck-driver populations in sub-Saharan Africa.

We also observe that, in terms of evaluations, just above half of these programmes have been evaluated to date and, of these, most looked only at input or outcome indicators. The evaluation methodologies relied on routinely-collected data and were constrained by low evaluation budgets. In planning for scale-up of programmes, Ministries of Health need to know which interventions, delivered in which way, and at what cost were more effective and efficient. Rigorous measurement of programme outcomes and impact is therefore needed to be able to support wider implementation of programmes. Yet, only six programmes reported sufficient data to analyse outcome or impact indicators. Moreover, programmes prioritising truck drivers have failed to demonstrate an attributable impact on STI incidence or HIV prevalence, due to study designs that lack control arms and heterogeneous trends in HIV risk reduction. However, the programmes overall could be considered to have had a positive effect on risk behaviours, knowledge, and attitudes, albeit the issue of attribution also remains open for these outcomes. For continuous improvement of programme delivery, monitoring and evaluation (M&E) needs to be built into all programmes at the design stage [60]. In the absence of good M&E frameworks, these programmes lose out on valuable process information and are less able to identify and address gaps and make informed decisions regarding operations management and service delivery, including effective and efficient use of resources.

The majority of the programmes were funded by agencies external to the country of implementation and for limited periods of time. Only three programs were funded by trucking companies/bodies. This funding situation influences the evaluation aim and objectives. Firstly, the need to report specific indicators for programme monitoring and reporting is donor-dictated, influencing the evaluation design and generally streamlining data collection to be compliant with donor priorities. Since main indicators are input, output, and outcome monitoring data, programmes remain deficient in measures to evaluate impact unless a separate study is envisaged. Secondly, programmes that are proven efficient and have an impact should be scaled-up. Yet scalability and sustainability are real concerns where implementing countries and relevant stakeholders are not closely involved and have no ownership of programmes.

Our study presents several limitations. First, we aimed to describe healthcare programmes prioritising truck drivers based on information available. Due to the nature of the documents reviewed, we were unable to assess the quality of services provided in these programmes and we limited our quality assessment to the methodologies employed where an evaluation was conducted. Additionally, we focused on reports and programme descriptions available publicly. This might have limited the completeness of our mapping. However, we contacted stakeholders and efforts were made to include all grey literature. We performed a meta-analysis to summarise the results of programme evaluations. We aimed therefore to quantify the impact these programmes have had on truck driver health indicators. However, due to the diversity of indicators reported, we were able to use the meta-analysis results to make qualitative statements as to where the programmes had a positive impact. Finally, we found an important heterogeneity in the results presented. We explored this heterogeneity in a subgroup analysis by type of indicator reported. Other covariates that could help explain the heterogeneity observed include the study setting, study type or even the choice of measurement. Due to the limited number of studies in each of these sub categories, we were unable to produce subgroup analyses for all covariates or to run a meta-regression to quantify their impact on the variance.


Diverse healthcare programmes prioritising truck drivers have been implemented in 30 sub-Saharan African countries since 1989. Just over half of these healthcare programmes have been evaluated. Among those evaluated, potential benefits to truck drivers have been shown. However, information gaps about availability of services and their effects impede further planning and implementation of effective healthcare programmes for truck drivers.

Collaborative efforts among workplaces, governments, and trucking governing bodies are essential to the design of effective programmes. Given the mobility associated with this population’s occupation, inter-governmental collaboration is imperative to facilitate service delivery along the trucking corridors and ensure continuity of care. The interconnected nature of the transportation network provides a unique opportunity that should be taken advantage of to establish stronger linkages to healthcare programmes and provision of services for this important population. Without this, truck drivers will be left behind in the move to achieve the global targets for access and linkage to care in sub-Saharan Africa.

Supporting Information

S1 Fig. Risk differences in impact indicators by programme.


S2 Fig. Risk differences in outcome indicators by programme.


S3 Fig. Subgroup analysis, summary relative risk estimates by type of indicator (fixed effects model).



The authors are grateful to Professor Joep Lange who provided advice during the design phase of this study and helped secure the funding. Professor Lange passed away on board the MH17 flight to Melbourne in 2014.

Author Contributions

Conceived and designed the experiments: STLE WDFV GG. Performed the experiments: STLE SCF KC GG. Analyzed the data: STLE GG. Contributed reagents/materials/analysis tools: STLE SCF KC GG. Wrote the paper: STLE SCF KC CH WDFV GG.


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