The study, led by Mekonen Mekasha of Addis Ababa University together with professors Belay Simane and Engdawork Assefa, set out to answer a question that has dogged environmental policy in developing economies for decades: does Environmental Impact Assessment, or EIA, actually change what happens on the ground, or does it merely produce documents? To find out, the researchers deployed a concurrent parallel mixed-methods design, combining quantitative survey data from 103 technical experts working across the road sector with in-depth qualitative interviews of 16 senior officials drawn from federal and regional government agencies. This dual approach allowed the team to measure perceptions of effectiveness statistically while also probing the institutional reasons behind the numbers.

The analytical framework rested on four widely used dimensions of EIA effectiveness. Procedural effectiveness asks whether the legally required steps, screening, scoping, report preparation, review and approval, are carried out on schedule. Substantive effectiveness asks whether the process actually improves environmental outcomes, from protecting watersheds and wildlife corridors to reducing soil erosion along cut-and-fill slopes. Normative effectiveness concerns whether the process embodies values such as transparency, public participation and social equity. Transactive effectiveness, the least studied of the four, measures whether the costs of running the assessment system are justified by the benefits it delivers.

The results revealed a striking asymmetry. Procedural effectiveness scored relatively well: environmental impact statements are prepared, reviewed and cleared, and projects obtain the certificates that allow construction to proceed. But the other three dimensions lagged far behind. Mitigation measures recommended in assessment reports were frequently not carried through into construction contracts or supervision plans. Monitoring of predicted impacts during and after construction was sporadic at best, and in many cases effectively absent once the approval stage had been passed. Public consultation, where it occurred, tended to be superficial, announced late and conducted in forms that gave affected communities little genuine influence over project design or compensation decisions.

Behind these weaknesses, the researchers identified a consistent root cause: governance. Poor governance, characterized by a lack of accountability, institutional misalignment and weak enforcement, undermined the performance of the entire EIA system. The Environmental Protection Authority, nominally the regulator, often lacked the staff, technical capacity and political weight to challenge powerful road agencies. Responsibilities for environmental oversight were fragmented across federal and regional bodies with unclear boundaries, allowing responsibility to slip through institutional gaps. When violations occurred, enforcement mechanisms were so feeble that contractors faced few meaningful consequences for ignoring mitigation commitments.

The Modjo–Moyale corridor makes an ideal test case precisely because of its scale and ambition. Stretching hundreds of kilometers from the town of Modjo, south of Addis Ababa, toward the border town of Moyale, the route crosses sharply contrasting ecological zones, from the Rift Valley’s semi-arid lowlands to fertile highland plateaus. Road projects of this magnitude cut through farmland, disturb drainage patterns, generate large volumes of borrow pits and quarries, and open previously remote areas to rapid land-use change. Satellite-based research on Ethiopia’s broader road investment program has already documented how new roads accelerate agricultural expansion and land conversion, making robust environmental follow-up along such corridors not a luxury but a necessity.

The Ethiopian findings echo a broader pattern documented across East Africa and beyond. Studies in Rwanda, Uganda, Kenya and Namibia have similarly reported that EIA systems in the region are procedurally mature but substantively thin, with follow-up and monitoring identified as the weakest links almost everywhere. International best-practice principles for EIA follow-up, first codified by researchers in the mid-2000s, call for continuous monitoring, adaptive management and clear feedback loops between predicted and actual impacts. The Ethiopian case shows how difficult those principles are to institutionalize when the agencies charged with them are under-resourced and politically subordinate to the very projects they are meant to scrutinize.

What distinguishes the new study is its insistence that the remedy is not primarily technical. The authors conclude that the key barriers to effective EIA implementation in Ethiopia’s road sector arise from governance deficiencies rather than from gaps in scientific methodology or legal drafting. Ethiopia has had a mandatory EIA proclamation since 2002, and its assessment guidelines are broadly consistent with international norms. The problem, the researchers argue, lies in how power and accountability are distributed. Improving baseline surveys or adding more sophisticated impact-prediction models will accomplish little if nobody is obliged to act on the findings.

Accordingly, the study prescribes a set of targeted institutional interventions. First, transparency must be strengthened, with assessment reports, monitoring data and compliance records placed in the public domain so that civil society, the media and affected communities can act as external watchdogs. Second, public involvement must move from token consultation to substantive participation, in which community input demonstrably shapes project alignment, mitigation design and compensation schemes. Third, an independent and reliable monitoring system is needed, insulated from the construction agencies it oversees, with statutory authority to halt works, impose penalties and require corrective action when environmental conditions are breached.

The stakes extend well beyond a single road corridor. Ethiopia’s road network is the backbone of a national development strategy that aims to connect landlocked production zones to ports and regional markets, and international lenders including the World Bank and the African Development Bank finance a substantial share of that expansion. If environmental assessment remains a procedural formality, the cumulative costs, degraded watersheds, lost biodiversity, eroded soils and unresolved community grievances, will accumulate silently across thousands of kilometers of asphalt. Conversely, if the governance reforms identified in this study are implemented, the authors argue, EIA could be transformed from a bureaucratic checkpoint into a cornerstone of sustainable development, ensuring that the country’s remarkable infrastructure growth does not come at the expense of the landscapes and livelihoods it traverses.

Subject of Research: Effectiveness of Environmental Impact Assessment in Ethiopian road infrastructure projects

Article Title: Environmental Impact Assessment Effectiveness in Ethiopian Road Infrastructure Projects: Evidence from the Modjo–Moyale Interregional Road Corridor

Article References: Mekasha, M., Simane, B., & Assefa, E. (2026). Environmental Impact Assessment Effectiveness in Ethiopian Road Infrastructure Projects: Evidence from the Modjo–Moyale Interregional Road Corridor. Environmental Management, 76(10), Article 323. https://doi.org/10.1007/s00267-026-02594-y

Image Credits: AI Generated

DOI: 10.1007/s00267-026-02594-y

Keywords: environmental impact assessment, Ethiopia, road infrastructure, Modjo–Moyale corridor, governance, environmental management, public participation, monitoring, sustainable development, East Africa, institutional capacity, environmental policy

The research team, led by Mengistu Abebe Messelu, conducted a multi-center, institution-based cross-sectional study using a mixed sequential explanatory design between March 1 and July 30, 2024. Five public hospitals were randomly selected from the zone’s twelve hospitals, and 428 emergency department patients or their attendants completed interviewer-administered questionnaires, a response rate of 95.3 percent. Quantitative data were captured with KoboCollect and analyzed in STATA version 17, using binary logistic regression with adjusted odds ratios to isolate the factors driving ambulance use. The qualitative arm added in-depth interviews with twelve patients and attendants and key-informant interviews with eight officials, clinicians, and Red Cross workers, analyzed thematically until saturation was reached.

The statistical analysis pointed to four independent determinants of ambulance utilization. Patients who knew the ambulance call number had 2.68 times higher odds of using the service, those who presented at night had 6.60 times higher odds, those with a triage score of seven or above had 9.76 times higher odds, and those with prior ambulance experience had 2.99 times higher odds. Each finding carries a practical message. Knowledge of the emergency number roughly doubles the chance of calling an ambulance, familiarity with the service builds trust that translates into repeat use, and severity of illness, as captured by triage acuity, remains the strongest predictor of all.

The night-time effect is particularly telling. With fewer transport options and less accessible care after dark, patients and families perceive the ambulance as the fastest and most reliable route to the emergency department, a pattern consistent with large observational studies of emergency call behavior in high-income countries. In daytime hours, when bajajs, buses, and commercial vehicles are readily available, most patients opt for these alternatives, even though only three percent of participants owned a car and 60.5 percent owned a mobile phone. Strikingly, 80.1 percent of participants did not know the ambulance call number at all, a knowledge gap the authors identify as one of the most fixable barriers in the entire system.

The qualitative interviews revealed why availability, not merely awareness, lies at the heart of the problem. Although more than 120 ambulances nominally operate across the zone’s 21 districts and 480 kebeles, respondents described vehicles that were chronically unavailable, mechanically broken, or diverted to non-emergency duties. One 38-year-old man told interviewers that ambulances were not performing their primary tasks of transporting laboring mothers and injured patients, but instead served government officials and transported wood and coal. A 45-year-old participant said ambulances were being used for security services and for carrying non-emergency or deceased patients for the financial gain of drivers. More than half of survey respondents, 58.2 percent, cited simple unavailability as the reason they could not use an ambulance.

Armed conflict emerged as a dominant structural barrier. Ongoing fighting in the Amhara region, particularly between the Fano armed group and government forces, has made it impossible or perilous to move ambulances between districts and health facilities. A 41-year-old attendant explained that ambulances once served anyone with medical illness, obstetric emergencies, or accidental trauma, but that the conflict had made transport to hospital effectively unattainable. Interviewees also reported that ambulances feared attack, could not move freely between woredas and kebeles, and were sometimes commandeered by armed groups. The study authors caution that conducting research during active conflict may itself have led to an underestimation of true utilization, since emergency transport was routinely diverted or disrupted.

Communication and infrastructure failures compounded the crisis. In rural kebeles, where half of participants lived, unreliable electricity makes it hard to charge phones, patchy mobile networks make calls to dispatchers unreliable, and ambulance drivers frequently did not answer or were unreachable. Many residents did not know the direct numbers of ambulance drivers or health extension workers. Road infrastructure posed an equally severe obstacle, particularly in villages off the main roads, where seasonal rains turn tracks to mud. One 35-year-old mother described waiting so long for an ambulance during labor that she was forced to deliver at home, while another recalled a driver claiming he was stuck in the mud as a patient deteriorated. These narratives echo qualitative findings from Libreville, Gabon, where infrastructure flaws were likewise identified as the leading barrier to prehospital care.

The 16.6 percent utilization rate in East Gojjam sits below figures from other Ethiopian settings, including Jimma at 39.5 percent, Addis Ababa at roughly 20 to 23 percent, and Southwest Ethiopia at 79 percent for pregnant and laboring women, differences the authors attribute to road quality, community awareness, response times, and the presence of private ambulance operators in urban centers. By contrast, the figure exceeds Ghana’s Accra, where only 4.5 percent of respondents had ever used an ambulance, likely because Ethiopia’s government-subsidized service removes cost barriers. The stakes of closing this gap are enormous. Globally, adequate emergency medical services are estimated to prevent up to 45 percent of deaths and 35 percent of disability-adjusted life years, and roughly one-third of maternal deaths in low- and middle-income countries are directly attributed to the absence of emergency transport. With about 74 percent of ischemic heart disease deaths occurring before hospital arrival, prehospital care is often the only chance of survival.

The community itself proposed the remedies. Participants called for sufficient ambulances for every kebele and health institution, stationing vehicles at health facilities rather than administrative offices to slash response times, and publicizing emergency numbers through mass media and traditional gatherings such as Idir and Ekub. The researchers echo these recommendations, urging increased ambulance fleets, decentralized ambulance stations at kebele or health center level, round-the-clock coordination among hospitals, health centers, and health posts, regular monitoring of vehicle functionality and crew performance, and sustained public awareness campaigns. Above all, they stress that resolving the armed conflict and securing emergency medical transport is the prerequisite for any lasting improvement, and they call for longitudinal studies that adjust for socioeconomic status, distance to care, and comorbidity to track whether these interventions finally move the needle on a system in which five of every six emergency patients are still left to find their own way to the hospital.

Beyond its headline findings, the study offers a methodological template for emergency care research in fragile settings. The sequential explanatory design allowed the quantitative results to shape the qualitative sampling, with participants for in-depth interviews selected purposively to explain, rather than merely describe, the patterns observed in the survey data. Statistical rigor was reinforced by entering only variables with a p-value below 0.25 in bivariable analysis into the multivariable model, and by confirming model fit with the Hosmer–Lemeshow goodness-of-fit test, a safeguard against overfitting in a modest sample of 428 respondents.

The research also situates East Gojjam within a broader epidemiological transition underway in Ethiopia. While road traffic injuries and obstetric emergencies have long dominated the prehospital burden, the growing prevalence of cardiovascular disease and diabetes raises the stakes further, since time-sensitive conditions such as acute myocardial infarction depend heavily on rapid transport to definitive care. The World Health Organization and the African Federation for Emergency Medicine have both emphasized that timely physical access to health facilities is a foundational element of emergency care systems in low- and middle-income countries, making ambulance availability a policy priority rather than a logistical afterthought.

The scale of the study area underscores how thin emergency coverage remains. East Gojjam Zone is home to nearly 2.5 million people distributed across 632,353 households, served by one comprehensive specialized hospital, one general hospital, nine primary hospitals, 102 health centers, and 406 health posts. Even with more than 120 ambulances nominally in operation, the effective ratio of vehicles to population and geography leaves rural kebeles acutely exposed. The Ethiopian Federal Ministry of Health has invested in ambulance distribution and regional dispatch centers over the past decade, yet the study suggests these assets frequently function as transport-only vehicles without trained crews, equipment, or supplies, limiting their clinical value even when they do arrive.

Subject of Research: Ambulance service utilization and its barriers among emergency patients in Northwest Ethiopia

Article Title: Utilization of ambulance services in Northwest Ethiopia: a mixed sequential explanatory study of practice, barriers, and community-led perceived solutions

Article References: Messelu, M. A., Amlak, B. T., Tiruneh, B. G., Nibret, G., Yechale, M., Alem, D. T., Amha, H., Gedfew, M., Gete, M., Ayenew, T., Birhanie, S. A., & Ayenew, T. (2026). Utilization of ambulance services in Northwest Ethiopia: a mixed sequential explanatory study of practice, barriers, and community-led perceived solutions. Journal of Emergency and Disaster Medicine, 2(1), Article 17. https://doi.org/10.1007/s44467-026-00019-8

Image Credits: AI Generated

DOI: 10.1007/s44467-026-00019-8

Keywords: ambulance services, emergency medical services, Ethiopia, prehospital care, armed conflict, triage, mixed methods, health barriers, road infrastructure, community solutions, East Gojjam, global health

The study set out to answer a question that has long frustrated geoscientists working in the Hindu Kush and Karakoram regions: when data are scarce and terrain is extreme, which mapping approach best identifies dangerous ground? The researchers compared three widely used techniques—the Analytical Hierarchy Process (AHP), a knowledge-driven method that translates expert judgment into numerical weights; and two bivariate statistical models, the Frequency Ratio (FR) and the Statistical Index (SI), which derive weights empirically from the observed relationship between past landslides and terrain characteristics. What makes their comparison unusually rigorous is the experimental design. Rather than allowing each method to use its own data or assumptions, the team forced all three models to work from the same landslide inventory, the same eight conditioning factors, the same 12.5-meter spatial resolution, the same training and testing split, and a common validation dataset.

Building the foundation for this comparison was itself a substantial undertaking. Between 2017 and 2025, the researchers compiled a multi-temporal inventory of 90 landslides along the corridor, combining satellite image interpretation, documentary records, and repeated field visits to verify each mapped failure. The fieldwork documented a sobering variety of slope failures: rotational slides with well-defined scarps, shallow translational slides, debris slides accumulating talus at their bases, and rockfall debris piling up against the road at the toes of fractured rock faces. The geology of the region—part of the Kohistan Island Arc, squeezed between the Main Mantle Thrust and Main Karakoram Thrust—provides ample raw material for instability, with tectonically disturbed volcanic, metavolcanic, metasedimentary, and intrusive rocks all represented along the route.

With the inventory in hand, the team prepared eight landslide-conditioning factors from a 12.5-meter digital elevation model and geological mapping: slope angle, elevation, aspect, curvature, profile curvature, lithology, drainage density, and relative relief. Before modeling, they tested the factors for redundancy using Spearman’s rank correlation and the Variance Inflation Factor, a standard diagnostic for multicollinearity. The results were reassuring: VIF values ranged from just 1.01 to 2.43, far below the conventional threshold of 10, meaning no factor was duplicating the information carried by the others. Lithology showed the highest VIF at 2.43, followed by slope at 2.12, but all eight variables could be retained without concern that overlapping signals would distort the model weights.

The pattern of empirical associations that emerged from the data reads like a field guide to slope failure in the region. Slope angle showed one of the clearest relationships, with the 30–45 degree class recording the highest frequency ratio of 1.712, and slopes steeper than 45 degrees registering the highest statistical index value. Drainage density proved even more potent: the highest class, 0.309 to 0.5, returned both the highest FR (2.433) and the highest SI (1.673), reflecting how dense stream networks concentrate runoff, undercut slope toes, and raise pore-water pressures during rainfall. Relative relief—the local difference between maximum and minimum elevation—showed a similarly strong association, with the 2097–2277 meter class reaching an FR of 2.059. These relationships are geomorphologically intuitive: steep, deeply dissected terrain provides the gravitational energy and the water pathways that slope failures require.

Lithology added its own decisive fingerprint. The Barawal Banda Slate, a fine-grained, foliated slate and phyllite unit with pervasive cleavage, showed the strongest association with mapped landslides among the well-behaved comparisons, with an FR of 1.457. The rock’s low intact strength and well-developed anisotropic failure surfaces parallel to its foliation make it a natural candidate for instability, and the data confirmed that intuition. West- and southwest-facing slopes also showed elevated susceptibility, plausibly reflecting stronger afternoon solar heating, repeated thermal stress on fractured rock, and differences in moisture retention and vegetation. Convex profile curvature classes, where flow accelerates and lateral support diminishes, added a further local concentration of risk. No single factor told the whole story; the danger zones emerged where multiple unfavorable conditions stacked on top of one another.

When the three models were run and their outputs classified into five susceptibility levels from very low to very high, all three converged on the same broad geography: the northwestern sector of the corridor is the principal hotspot, where steep, highly dissected terrain, dense drainage, high relative relief, and weak lithological units coincide. But the models differed in how sharply they discriminated. In the AHP implementation, slope angle received the highest expert weight at 32.1 percent, followed by drainage density at 21.7 percent and relative relief at 20.1 percent, with a consistency ratio of 0.0737 confirming internally coherent expert judgments. The FR and SI models, by contrast, let the landslide inventory itself speak, assigning each factor class a weight based purely on its observed association with past failures.

Independent validation on the withheld 25 percent testing subset delivered the study’s headline result. The Statistical Index model achieved the highest area under the receiver operating characteristic curve, an ROC–AUC of 0.903—considered excellent discrimination—followed by the Frequency Ratio model at 0.881 and the expert-based AHP at 0.847. In other words, the simplest, purely empirical approach outperformed structured expert judgment in this setting. The SI model also proved remarkably efficient in its spatial allocation: it classified only 12.2 percent of the study area as very high susceptibility while capturing 57.7 percent of the mapped landslides within that class, precisely the kind of concentrated warning that road managers need. The authors are careful, however, to note that without confidence intervals or formal pairwise significance tests, SI should be described as the best performer in this experiment rather than as statistically proven superior.

The practical implications extend well beyond an academic comparison of methods. The maps give engineers and disaster-management authorities in Upper Dir a defensible, reproducible screening tool for prioritizing slope monitoring, drainage improvement, detailed geotechnical investigation, and road-maintenance budgets along a corridor where alternative access routes are scarce and every closure carries real consequences for isolated communities. Sections of road crossing contiguous high and very high susceptibility cells should be first in line for inspection and stabilization, particularly after major rainfall or snowmelt episodes. The authors also stress the limits of the analysis: with only 90 mapped events, no rainfall or seismic predictors, and no temporal validation, the maps indicate where failures are likely, not when or how large. Still, the framework—three interpretable models tested on identical data—offers a template that other data-poor mountain regions, from the Himalaya to the Andes, can adapt. In an era when climate change is intensifying the rainfall that triggers landslides across high-mountain Asia, knowing precisely which kilometers of road to watch first may prove to be the cheapest insurance available.

The distinction between susceptibility and hazard is worth emphasizing for readers encountering these maps. Susceptibility, as produced here, is a purely spatial statement: given the terrain and geological conditions observed today, which locations possess the combination of attributes most conducive to failure. It deliberately excludes timing, magnitude, and runout, which would require rainfall thresholds, seismic triggers, and dynamic runout modeling that the current inventory cannot support. This is why the authors frame their product as a screening tool rather than a forecast, and why they caution against reading the very high class as a prediction of imminent failure.

The statistical logic underlying the two bivariate models also merits brief explanation. Both FR and SI operate class by class: each factor class receives a weight reflecting the proportion of landslide pixels it contains relative to its share of the study area. The Frequency Ratio expresses this as a simple ratio, while the Statistical Index takes its logarithm, which compresses extreme values and can stabilize model behavior when class areas vary widely. Because both models treat each factor independently, they cannot capture interactions—for instance, a steep slope may be far more dangerous under one lithology than another—a limitation that machine-learning approaches address at the cost of greater data demands and reduced transparency.

The regional geological setting amplifies the value of such screening. The Kohistan Island Arc records the collisional history between the Indian and Eurasian plates, and the rocks it preserves—slates, volcanics, and batholithic intrusions—have been repeatedly sheared, fractured, and altered. Tectonic fabrics such as cleavage and foliation create planes of weakness that orient failure surfaces, meaning geology and topography interact rather than act independently. In corridors like Sheringal–Kumrat, where road cuts expose these weakened materials directly to weathering and infiltration, even modest increases in seasonal precipitation can translate into measurable slope instability, reinforcing the case for targeted, map-guided maintenance.

Subject of Research: Landslide susceptibility assessment along the Sheringal–Kumrat Road corridor in Upper Dir, northern Pakistan, comparing AHP and bivariate statistical models

Article Title: Landslide susceptibility assessment along Sheringal Road, Upper Dir Northern Pakistan using AHP and bivariate statistical models

Article References: Khan, S., Anjum, N., Bibi, H., Rauf, M., Ullah, W., Khan, A., Jadoon, H. K., & Yaqoob, A. (2026). Landslide susceptibility assessment along Sheringal Road, Upper Dir Northern Pakistan using AHP and bivariate statistical models. Discover Geoscience, 4(1), Article 353. https://doi.org/10.1007/s44288-026-00725-w

Image Credits: AI Generated

DOI: 10.1007/s44288-026-00725-w

Keywords: landslide susceptibility, AHP, frequency ratio, statistical index, GIS, remote sensing, Upper Dir, Pakistan, Hindu Kush, ROC–AUC, road infrastructure, geohazard mapping