Studies of the effectiveness of transport sector interventions in low‐ and middle‐income countries: An evidence and gap map
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Bibliographic record
Abstract
Background: . As these figures show, there is a significant backlog of transport infrastructure investment in both rural and urban areas, especially in sub-Saharan Africa. This situation is often exacerbated by weak governance and an inadequate regulatory framework with poor enforcement which lead to high costs and defective construction.The wellbeing of many poor people is constrained by lack of transport, which is called "transport poverty". Lucas et al. suggest that up to 90% of the world's population are transport poor when defined as meeting at least one of the following criteria: (1) lack of available suitable transport, (2) lack of transport to necessary destinations, (3) cost of necessary transport puts household below the income poverty line, (4) excessive travel time, or (5) unsafe or unhealthy travel conditions. Objectives: The aim of this evidence and gap map (EGM) is to identify, map, and describe existing evidence from studies reporting the quantitative effects of transport sector interventions related to all means of transport (roads, rail, trams and monorail, ports, shipping, and inland waterways, and air transport). Methods: The intervention framework of this EGM reframes Berg et al's three categories (infrastructure, prices, and regulations) broadly as infrastructure, incentives, and institutions as subcategories for each intervention category which are each mode of transport (road, rail trams and monorail, ports, shipping, and inlands waterways, and air transport). This EGM identifies the area where intervention studies have been conducted as well as the current gaps in the evidence base.This EGM includes ongoing and completed impact evaluations and systematic reviews (SRs) of the effectiveness of transport sector interventions. This is a map of effectiveness studies (impact evaluations). The impact evaluations include experimental designs, nonexperimental designs, and regression designs. We have not included the before versus after studies and qualitative studies in this map. The search strategies included both academic and grey literature search on organisational websites, bibliographic searches and hand search of journals.An EGM is a table or matrix which provides a visual presentation of the evidence in a particular sector or a subsector. The map is presented as a matrix in which rows are intervention categories (e.g., roads) and subcategories (e.g., infrastructure) and the column outcome domains (e.g., environment) and subcategories as (e.g., air quality). Each cell contains studies of the corresponding intervention for the relevant outcome, with links to the available studies. Included studies were coded according to the intervention and outcomes assessed and additional filters as region, population, and study design. Critical appraisal of included SR was done using A Measurement Tool to Assess Systematic Reviews (AMSTAR -2) rating scale. Selection Criteria: The search included both academic and grey literature available online. We included impact evaluations and SRs that assessed the effectiveness of transport sector interventions in low- and middle-income countries. Results: This EGM on the transport sector includes 466 studies from low- and middle-income countries, of which 34 are SRs and 432 impact evaluations. There are many studies of the effects of roads intervention in all three subcategories-infrastructure, incentives, and institutions, with the most studies in the infrastructure subcategories. There are no or fewer studies on the interventions category ports, shipping, and waterways and for civil aviation (Air Transport).In the outcomes, the evidence is most concentrated on transport infrastructure, services, and use, with the greatest concentration of evidence on transport time and cost (193 studies) and transport modality (160 studies). There is also a concentration of evidence on economic development and health and education outcomes. There are 139 studies on economic development, 90 studies on household income and poverty, and 101 studies on health outcomes.The major gaps in evidence are from all sectors except roads in the intervention. And there is a lack of evidence on outcome categories such as cultural heritage and cultural diversity and very little evidence on displacement (three studies), noise pollution (four studies), and transport equity (2). There is a moderate amount of evidence on infrastructure quantity (32 studies), location, land use and prices (49 studies), market access (29 studies), access to education facilities (23 studies), air quality (50 studies), and cost analysis including ex post CBA (21 studies).The evidence is mostly from East Asia and the Pacific Region (223 studies (40%), then the evidence is from the sub-Saharan Africa (108 studies), South Asia (96 studies), Latin America & Caribbean (79 studies). The least evidence is from Middle East & North Africa (30 studies) and Europe & Central Asia (20 studies). The most used study design is other regression design in all regions, with largest number from East Asia and Pacific (274). There is total 33 completed SRs identified and one ongoing, around 85% of the SR are rated low confidence, and 12% rated as medium confidence. Only one review was rated as high confidence. This EGM contains the available evidence in English. Conclusion: This map shows the available evidence and gaps on the effectiveness of transport sector intervention in low- and middle-income countries. The evidence is highly concentrated on the outcome of transport infrastructure (especially roads), service, and use (351 studies). It is also concentrated in a specific region-East Asia and Pacific (223 studies)-and more urban populations (261 studies). Sectors with great development potential, such as waterways, are under-examined reflecting also under-investment.The available evidence can guide the policymakers, and government-related to transport sector intervention and its effects on many outcomes across sectors. There is a need to conduct experimental studies and quality SRs in this area. Environment, gender equity, culture, and education in low- and middle-income countries are under-researched areas in the transport sector.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it