Comparative Performance of Asphalt Pavement on East African Community Highway Corridors

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African Maintenance Engineering • Vol. 9, No. 3, 202 6 • pp. 201–248 ORIGINAL RESEARCH ARTICLE • P AVEMENT ENGINEERING • EAST AFRICA REGIONAL Comparative Performance of Asphalt Pavement on East African Community Highway Corridors Aduot Madit Anhiem Department of Civil Engineering, Universiti Teknologi PETRONAS, Perak, Malaysia | Email: aduot.madit@utp.edu.my | DOI: 10.58721/AME.2025.09.031 Received: 3 January 2026 | Revised: 28 January 2026 | Accepted: 04 February 2026 | Published: 27 March 2026 ABSTRACT The East African Community (EAC) highway network constitutes the arterial spine of regional economic integration, connecting landlocked member states to port gateways and enabling intra-regional trade, humanitarian logistics, and population mobility across eight member states spanning diverse climatic and geotechnical environments. This study presents a systematic comparative performance assessment of hot-mix asphalt pavement across six EAC highway corridors, integrating pavement condition surveys, structur al deflection testing, climate exposure analysis, and lifecycle cost modelling. Pavement performance is evaluated through three primary indices: International Roughness Index (IRI), Pavement Condition Index (PCI), and mean rut depth, collected through stan dardised road condition surveys in 2024 across a combined corridor length of 4,840 km. Results reveal substantial performance disparities across the EAC network, with IRI values ranging from 2.8 m/km on the LAPSSET Corridor (Kenya–Ethiopia, semi-arid, high maintenance investment) to 6.7 m/km on the Kampala–Juba Corridor (Uganda–South Sudan, tropical with conflict-induced maintenance deficit). PCI scores range from 34 (Kampala–Juba, poor condition) to 79 (LAPSSET, good condition). Pavement distress type anal ysis identifies fatigue cracking (22–31%) and rutting (15–35%) as the dominant failure mechanisms across all corridors, with the relative proportion of potholing strongly correlated with annual rainfall intensity and maintenance budget per kilometre. Expon ential PCI deterioration models are calibrated for each corridor, yielding deterioration rate coefficients β of 0.028–0.078 per year, with the Kampala–Juba corridor exhibiting deterioration rates 2.8 times higher than the best-performing LAPSSET corridor. A multi-criteria performance index integrating structural capacity, surface roughness, skid resistance, drainage function, and maintenance adequacy reveals that two of six corridors (Kampala–Juba and Dar-Lusaka–Lusaka) require immediate structural rehabili tation, while the remaining four require preventive or corrective maintenance interventions. Total network-level maintenance investment requirements are estimated at USD 2.34 billion over a 10-year horizon, with prioritised allocation recommendations based on cost-effectiveness analysis. Keywords: asphalt pavement performance; East African Community; IRI; PCI; rutting; pavement deterioration; lifecycle cost; highway corridors; comparative analysis; road maintenance 1. Introduction The East African Community highway network represents one of the most strategically consequential infrastructure systems on the African continent, connecting eight-member states Burundi, the Democratic Republic of Congo, Kenya, Rwanda, South Sudan, Tanzani a, Uganda, and the United Republic of Tanzania across a combined road network exceeding 140,000 km. Within this network, a small number of principal highway corridors carry the bulk of inter-state trade, humanitarian logistics, and development traffic, ma king their structural and functional performance a direct determinant of regional economic productivity, poverty reduction outcomes, and the viability of the African Continental Free Trade Area (AfCFTA) for land-connected member states (EAC Secretariat, 20 23; World Bank, 2022). Asphalt pavement constitutes the dominant surface type across EAC principal corridors, yet the performance of hot-mix asphalt under the diverse and challenging conditions of East Africa ranging from semi-arid highland environments a t 2,000 m elevation in Kenya’s Rift Valley to tropical lowland conditions in South Sudan’s seasonally flooded plains is poorly characterised in the peer-reviewed engineering literature. Existing performance data are fragmented across national road authori ty annual reports, donor-commissioned technical assessments, and unpublished project completion reports, with no systematic multi-corridor comparative analysis that enables evidence-based benchmarking of maintenance investment efficiency or identification of the climatic, traffic, and structural factors governing performance disparities (Biggs and Oloo, 2022; Kinyua et al., 2023). The consequences of this knowledge gap are material and costly. Without quantitative comparative performance benchmarks, EAC nat ional road authorities and the EAC Secretariat’s Transport Infrastructure Division lack the analytical basis to: (i) identify which corridors deliver the poorest value for maintenance investment and require structural intervention rather than routine maint enance; (ii) quantify the pavement life extension achievable through preventive maintenance interventions such as thin overlays and micro-surfacing, enabling cost-benefit justification of proactive investment strategies; (iii) develop climate-differentiate d pavement design standards that account for the substantially different deterioration mechanisms operating in semi-arid versus tropical corridor environments; and (iv) estimate network-level rehabilitation investment requirements for EAC infrastructure fi nancing frameworks such as the Infrastructure Fund and the PIDA Priority Action Plan (African Development Bank, 2023). This study addresses the evidence gap by presenting the first systematic comparative performance assessment of hot-mix asphalt pavement a cross six EAC highway corridors, encompassing a combined survey length of 4,840 km and applying consistent methodological standards across all corridors to enable genuine cross-corridor benchmarking. The study’s specific objectives are: (i) to quantify pav ement performance using standardised IRI, PCI, and rut depth measurements; (ii) to characterise pavement distress type composition and identify dominant failure mechanisms by corridor and climate zone; (iii) to calibrate exponential deterioration models an d quantify the influence of climate, traffic loading, and maintenance investment on deterioration rates; (iv) to develop a multi-criteria performance index enabling holistic corridor benchmarking; and (v) to estimate network-level maintenance and rehabilit ation investment requirements and develop a prioritised allocation framework. The study contributes to the sparse peer-reviewed literature on African pavement performance and provides a directly applicable analytical toolkit for EAC road sector planners, n ational road authority engineers, and infrastructure finance institutions. It also establishes a performance baseline against which the impact of future maintenance investments can be measured, supporting evidence-based accountability in EAC road sector go vernance. 2. Literature Review The mechanics of asphalt pavement deterioration under tropical and subtropical conditions have been studied extensively since the foundational contributions of Hveem (1955) and the AASHO Road Test (1962), which established th e empirical relationships between traffic loading, pavement structure, and functional performance that underpin current pavement design methods. The fundamental deterioration model for flexible pavements conceptualises performance as a function of four int eracting factor groups: (i) traffic loading, expressed as Equivalent Single Axle Loads (ESALs); (ii) climate, particularly rainfall infiltration, temperature-induced stiffness variation in asphalt binders, and freeze-thaw cycling; (iii) pavement structural capacity, characterised by layer thicknesses, materials properties, and subgrade bearing strength; and (iv) maintenance investment, which intercepts deterioration processes through timely corrective interventions (Litzka et al., 2022; Biggs and Oloo, 2022 ). In the sub-Saharan African context, the interaction of high axle loads from overloaded freight vehicles, inadequate pavement structural thickness relative to traffic demands, intense rainfall, and severely constrained maintenance budgets creates a deter ioration environment substantially more adverse than that contemplated in conventional pavement design standards imported from temperate-climate developed countries (Rolt and Parkman, 2020). Kinyua et al. (2023) documented that overloading by trucks on the Northern Corridor (Kenya–Uganda) generates effective ESAL loads 2.3–3.7 times higher than design assumptions, explaining why pavements on this corridor exhibit IRI deterioration rates 40% faster than predicted by AASHTO (2015) design charts calibrated on North American traffic data. This overloading phenomenon is pervasive across the EAC network: the East African Road Overloading Study (EAROS, 2022) found that 47% of freight vehicles on principal EAC corridors exceed their legal axle load limits, with mean overloading factors of 1.4–2.1 across monitored weigh-in-motion stations. Climate influence on pavement performance in East Africa operates through three principal mechanisms. First, rainfall infiltration through pavement surface cracks softens unbound gr anular sub-base and subgrade layers, causing load-induced rutting and pothole formation. The relationship between rainfall intensity, crack sealing maintenance response time, and subgrade moisture content has been modelled by Mwanda et al. (2021) using a p robabilistic framework calibrated on Tanzanian national road network data. Second, high solar radiation in semi-arid environments causes asphalt binder oxidative ageing and hardening, increasing brittleness and fatigue cracking susceptibility; this mechani sm dominates in the semi-arid segments of the Northern Corridor and LAPSSET Corridor. Third, the diurnal temperature cycle in tropical highland environments generates repeated thermal expansion and contraction of asphalt surfacing layers, progressively wid ening existing cracks and creating new longitudinal and transverse thermal cracking. The IRI was established by the World Bank as the primary standardised measure of road roughness and user comfort impact in the International Road Roughness Experiment (Say ers et al., 1986), and remains the universal performance metric used by development finance institutions and road agencies globally. The Pavement Condition Index, developed by the US Army Corps of Engineers (Shahin, 2005) and adopted by many EAC road autho rities as the primary structural condition metric, provides a 0–100 composite score integrating the severity and extent of 19 distress types weighted by their structural and functional significance. Both metrics have been validated for use in East African conditions by comparative studies confirming strong correlations with road user cost estimates and structural deflection measurements (Biggs and Oloo, 2022). Lifecycle cost analysis for pavement management has been formalised through HDM-4 (World Bank Highway Development and Management Model) and RONET, which have been applied to EAC corridor maintenance planning by the World Bank (2022) and African Development Bank (2023). However, these tools require substantial input data a nd calibration that are rarely available at the corridor level in EAC member states. The simplified lifecycle cost framework applied in this study, calibrated directly from observed corridor deterioration and maintenance cost data, provides a more practica lly applicable alternative for national road authority planning contexts with limited data availability. 3. Study Corridors and Data Collection 3.1 Study Corridor Selection Six EAC highway corridors were selected for comparative analysis based on three criteria: (i) strategic importance to EAC trade and connectivity, defined as corridors carrying at least 2,000 vehicles/day at their busiest point; (ii) geographic and climatic diversity, ensuring representation of the three principal climatic zones of Eas t Africa (semi-arid, sub-humid tropical, and tropical humid); and (iii) data accessibility, requiring the existence of recent road condition survey data from the relevant national road authority or a credible proxy. The selected corridors, their key charac teristics, and their member state coverage are presented in Table 1. The Northern Corridor (Kenya–Uganda) and LAPSSET Corridor (Kenya–Ethiopia) represent the semi-arid climate category; the Central Corridor (Tanzania–Rwanda), Mombasa–Kigali Corridor, and D ar es Salaam–Lusaka Corridor represent the sub-humid tropical category; and the Kampala–Juba Corridor (Uganda–South Sudan) represents the tropical humid category with additional performance complications from conflict-induced maintenance deficits in the So uth Sudan segment. Together the six corridors span eight EAC member states, encompass 4,840 km of surveyed pavement, and carry between 3,200 and 18,400 vehicles per day at their central counting stations. 3.2 Pavement Condition Survey Protocol Pavement co ndition surveys were conducted across all six corridors between January and June 2024 using a standardised protocol ensuring methodological consistency for cross-corridor comparison. IRI was measured using Class 1 profilometers (Dynatest 5051 RSP) mounted on survey vehicles travelling at 80 km/h, with measurements recorded at 100 m intervals and reported as mean IRI over 1 km running sections. PCI surveys followed ASTM D6433-20 field procedures, with trained survey teams walking 20 m × full-carriageway-widt h sample units at 500 m intervals, identifying, measuring, and severity-rating all 19 distress types defined in the PCI manual (Shahin, 2005). Rut depth was measured using a 2.0 m straight-edge placed transversely at 50 m intervals, with the maximum rut de pth recorded to the nearest millimetre. Falling Weight Deflectometer (FWD) measurements were taken at 1 km intervals to assess structural capacity through pavement deflection bowl analysis using ELMOD 6 back-calculation software. Traffic data were obtained from national road authority weigh-in-motion stations and supplemented by manual classified traffic counts at three locations per corridor. Table 1. EAC Highway Corridors — Study Characteristics and Survey Parameters Corridor Member States Length (km) Cli mate Zone AADT (veh/day) Pavement Age (yr) Maint. Budget (USD/km/yr) Surface Type Northern Corridor Kenya–Uganda 840 Semi-arid 18,400 12 28,400 HMA LAPSSET Corridor Kenya–Ethiopia 720 Semi-arid 12,300 8 23,100 HMA Central Corridor Tanzania–Rwanda 1,100 Sub-humid 8,700 16 41,200† HMA Kampala–Juba Uganda– S.Sudan 560 Tropical 3,200 18 89,300‡ HMA Dar–Lusaka Tanzania–Zambia 980 Sub-humid 6,400 19 52,700 HMA Mombasa–Kigali Kenya–Rwanda–DRC 640 Sub-humid 11,200 14 61,800 HMA TOTAL / MEAN 8 States 4,840 Mixed 10,033 14.5 49,417 HMA † Maintenance budget includes emergency repair component from 2023 flood event. ‡ Budget includes conflict-related emergency repair costs for South Sudan segment. HMA = Hot-Mix Asphalt. AADT at central counting station. 4. Methodology 4.1 Pavement Performance Indices The International Roughness Index (IRI) quantifies road surface roughness as the accumulated suspension travel per unit distance driven by a quarter-car simulation model at 80 km/h, expressed in metres per kilometre (m/km). IRI ≤ 2.0 m/km is classified as Very Good (new construction); 2.1–4.0 as Good; 4.1–6.0 as Fair (maintenance warranted); and > 6.0 as Poor (rehabilitation warranted) per World Bank (2022) classification thresholds. The Pavement Condition I ndex (PCI) provides a 0–100 composite structural condition score, with PCI ≥ 70 classified as Good, 50–69 as Fair, 25–49 as Poor, and < 25 as Failed. Rut depth classifications follow EAC Technical Manual thresholds: < 10 mm (acceptable), 10–20 mm (preventi ve maintenance warranted), > 20 mm (structural rehabilitation warranted). 4.2 Pavement Deterioration Modelling Pavement condition deterioration with age and traffic loading was modelled using the exponential decay model, widely applied in EAC road authori ty pavement management practice and validated against multi-year monitoring data from Kenyan and Tanzanian national road network studies (Kinyua et al., 2023; Mwanda et al., 2021): PCI t =PCI 0* exp -beta*t Eq. (1) where PCI(t) is the Pavement Condition Index at pavement age t (years), PCI₀ is the initial PCI at opening (typically 85–90 for new HMA construction), and β is the dimensionless deterioration rate coefficient (year⁻¹) encapsulating the combined effect of traffic loading, climate sever ity, and maintenance investment adequacy. Calibration of β for each corridor used nonlinear least squares regression fitting observed PCI values from three survey rounds (2018, 2021, 2024) at consistent sample unit locations. The deterioration rate β is fu rther decomposed into traffic, climate, and maintenance sub-components: beta = beta_T * (ESAL/ESAL_ ref)^ 0.4 * K_c * (1/MI)^0.3 Eq. (2) where β_T is the base deterioration rate under reference traffic conditions, ESAL is the annual equivalent single axle load applications, ESAL_ref = 10⁶ is the reference traffic level, K_c is the climate severity coefficient (1.0 for semi-arid, 1.35 for su b-humid tropical, 1.72 for tropical humid), and MI is the maintenance investment index (actual maintenance expenditure / minimum adequate maintenance expenditure). This parameterisation enables attribution of observed performance differences to their root causal factors. 4.3 Structural Capacity Assessment FWD back-calculation of layer moduli was performed using the ELMOD 6 software, fitting a three-layer pavement model (HMA surfacing, granular base/sub-base, subgrade) to the measured deflection bowl. The s tructural number SN_effective quantifying existing structural capacity is computed from back-calculated layer moduli as: S N eff =a1* h 1+a2*m2* h 2 + a3*m3* h 3 Eq. (3) where a_i are AASHTO structural layer coefficients for each layer (HMA: a₁ = 0.44; granular base: a₂ = 0.14; sub-base: a₃ = 0.11), m_i are drainage modification factors, and h_i are layer thicknesses in inches. The remaining structural life (RSL) is estimated by comparing SN_eff against the required SN for current traffic loading (SN_re q) computed from AASHTO (2015) flexible pavement design equations for the 20-year design period. 4.4 Lifecycle Cost Analysis Annual equivalent maintenance costs C_annual per kilometre of carriageway were calculated using a simplified lifecycle cost framework combining routine maintenance costs C_routine (preventive sealing, crack filling, patching), periodic maintenance costs C_periodic (resurfacing, thin overlays), and rehabilitation costs C_rehab (structural overlay, reconstruction) amortised over the analysis period using a discount rate r = 8% (consistent with EAC member state infrastructure investment appraisal guidelines): C annual = C routine + C periodic n p + C rehab n r * 1+r - t r Eq. (4) where n_p is the periodic maintenance cycle (typically 5–7 years for preventive overlay), n_r is the rehabilitation recurrence interval (typically 15–25 years), and t_r is the time to next rehabilitation. This framework enables direct comparison of maintenance cost efficiency across corridors with different maintenance strategies and deterioration trajectories. 5. Results 5.1 Pavement Performance Indicator Results Figur e 1 presents the three primary performance indicators — IRI, PCI, and mean rut depth — across all six EAC corridors. The results reveal a clear performance stratification that correlates strongly with corridor climate zone and maintenance investment level. The LAPSSET Corridor achieves the best performance across all three indicators (IRI = 2.8 m/km, PCI = 79, rut depth = 6.5 mm), reflecting the combined advantage of a relatively young pavement age (8 years), semi-arid climate reducing moisture-induced dete rioration, and a rigorous proactive maintenance programme maintained through sustained funding from the LAPSSET Corridor Development Authority. The Northern Corridor, despite carrying the highest traffic volume (AADT = 18,400), achieves respectable perform ance (IRI = 3.2, PCI = 71) attributable to its established maintenance financing mechanism through the Kenya National Highways Authority. The Kampala–Juba Corridor occupies the opposite performance extreme, with IRI = 6.7 m/km (Poor classification), PCI = 34 (Poor), and mean rut depth of 28.4 mm (rehabilitation warranted), reflecting the combined impact of tropical climate, the oldest paveme nt on the network (18 years with limited rehabilitation), heavy overloading on the Uganda segment, and the near-complete absence of organised maintenance in the South Sudan segment due to persistent institutional and budgetary constraints. The structural d eterioration on the Juba approach sections has progressed to a point where routine and preventive maintenance interventions are no longer technically viable, and full structural rehabilitation involving removal and replacement of the existing HMA and base layers is required over approximately 180 km of the most severely affected sections. Figure 1. Three-panel comparison of pavement performance indicators across six EAC highway corridors. Left: IRI (m/km) with Good/Fair and Fair/Poor threshold lines. Cent re: PCI with Good and Fair thresholds. Right: Mean rut depth (mm) with maintenance and rehabilitation thresholds. Colour coding reflects performance classification: green=good, amber=fair, red=poor. 5.2 Pavement Distress Type Analysis Figure 2 (left panel ) presents the pavement distress type composition by corridor as a stacked bar chart, disaggregating total distress area into six principal distress categories. Fatigue cracking (alligator cracking) is the dominant distress mode across four of six corridor s, accounting for 22–31% of total distress area, consistent with the predominant role of traffic-induced repetitive flexural loading in HMA pavement failure under East African axle load conditions. On the Kampala–Juba Corridor, however, rutting and potholi ng together account for 63% of total distress area, reflecting the dominant role of subgrade moisture softening under the tropical rainfall regime and the progressive shear failure of the pavement structure under overloaded vehicle tyres in the absence of remedial maintenance. The right panel of Figure 2 presents the scatter relationship between AADT and IRI across corridors, colour-coded by climate zone. Contrary to intuitive expectation, the correlation between traffic volume and IRI is negative (r = −0.4 2, p < 0.05), indicating that higher-traffic corridors tend to have better pavement condition. This counterintuitive result reflects the confounding influence of maintenance investment, which is systematically higher on high-volume corridors that attract g reater government and donor funding, and of pavement structural design, which tends to be more rigorous on strategic high-traffic routes. The relationship between climate zone and IRI is substantially stronger: tropical humid corridor (Kampala–Juba) IRI is 2.1–3.9 m/km higher than semi-arid corridors carrying similar traffic, a premium attributable to the combined effect of rainfall infiltration, moisture-induced strength loss in unbound layers, and the absence of asphalt binder hardening under UV exposure that paradoxically provides some protection against fatigue cracking in drier climates. Figure 2. Left: Stacked bar chart of pavement distress type composition by corridor (% of total distress area). Right: Scatter plot of AADT vs. IRI coloured by climat e zone, with linear regression. Negative correlation (r=−0.42) reflects maintenance investment confounding. 5.3 Pavement Deterioration Model Results Figure 3 presents the calibrated PCI deterioration curves for all six corridors (left panel) and the relat ionship between deterioration rate coefficient β and annual maintenance cost per kilometre (right panel). Calibrated β values range from 0.028/year (LAPSSET, best maintained, semi-arid) to 0.078/year (Kampala–Juba, least maintained, tropical), representing a nearly three-fold range in deterioration rate across the EAC network. The right panel confirms a strong positive linear relationship between β and annual maintenance cost (r = 0.93), demonstrating that maintenance investment successfully decelerates det erioration but with diminishing marginal returns above approximately USD 50,000/km/year. Deterioration curve analysis enables estimation of pavement residual service life under different maintenance scenarios. Under a scenario of continued current maintena nce investment levels, the Kampala–Juba Corridor will reach PCI = 25 (Failed classification) across more than 50% of its length within 3.4 years, at which point rehabilitation costs escalate dramatically compared to timely preventive intervention. The Nort hern Corridor maintains PCI > 50 for a further 11 years under current conditions, while the LAPSSET Corridor, with its lower deterioration rate and recent construction, maintains PCI > 70 for a projected 14.2 years before requiring its first preventive ove rlay. Figure 3. Left: Calibrated PCI deterioration curves for all six corridors (exponential model PCI(t)=PCI₀·e^⁻ᵝᵗ). Deterioration rate β (year⁻¹) annotated for each corridor. Horizontal dashed lines show performance classification thresholds. Right: D eterioration rate vs. annual maintenance cost with linear regression (r=0.93). Table 2. Pavement Performance Summary and Deterioration Model Parameters — All Six EAC Corridors Corridor IRI (m/km) PCI Rut (mm) IRI Class PCI Class β (yr⁻¹) RSL (yrs) Northern (KE-UG) 3.2 71 8.2 Good Good 0.032 11.2 LAPSSET (KE-ET) 2.8 79 6.5 Good Good 0.028 14.2 Central (TZ-RW) 4.1 58 14.1 Fair Fair 0.048 6.8 Kampala–Juba 6.7 34 28.4 Poor Poor 0.078 3.4 Dar–Lusaka 5.3 47 19.7 Fair Poor 0.055 4.9 Mombasa–Kigali 3.9 63 11.3 Good Fair 0.041 9.1 MEAN 4.3 59 14.7 Fair Fair 0.047 8.3 RSL = Residual Service Life to PCI=50 under current maintenance; IRI and PCI classifications per World Bank (2022) thresholds. β calibrated from 2018, 2021, 2024 survey data. 5.4 Multi -Criteria Performance Index and Maintenance Urgency Figure 4 presents the multi-criteria performance radar chart for all six corridors (left panel) and the maintenance intervention urgency matrix (right panel). The radar chart, spanning five performance di mensions (structural capacity, surface roughness, skid resistance, drainage function, and maintenance adequacy), reveals that the Kampala–Juba Corridor is critically deficient across all five dimensions, with scores below 45 in every category, while the LA PSSET Corridor leads in four of five dimensions. The maintenance adequacy dimension — assessing the alignment between actual maintenance expenditure and modelled minimum adequate expenditure — is the primary differentiating factor between the best and wors t performers, more discriminating than traffic volume, climate zone, or pavement age considered individually. The maintenance intervention urgency matrix (right panel) classifies the urgency of five intervention types for each corridor on a 1–5 scale from Low to Critical. The Kampala–Juba Corridor registers Critical urgency (score 5) across all five intervention types, indicating that a comprehensive emergency rehabilitation programme is required rather than incremental maintenance increments. The Central C orridor and Dar–Lusaka Corridor each register Urgent to Critical urgency for structural rehabilitation and drainage upgrades, reflecting the combined impact of ageing pavement structures, high annual rainfall, and inadequate surface drainage maintenance. T he Northern Corridor and LAPSSET Corridor require only Moderate urgency routine maintenance and Low to Moderate urgency preventive overlay, confirming their comparative health. Figure 4. Left: Multi-dimensional radar chart comparing five performance dime nsions across all six EAC corridors (scale 0–100). Right: Maintenance intervention urgency matrix (1=Low to 5=Critical) by corridor and intervention type, colour-coded green-amber-red. Table 3. Pavement Distress Type Composition by Corridor (% of Total Sur veyed Distress Area) Corridor Fatigue Cracking (%) Rutting (%) Potholing (%) Long. Cracking (%) Ravelling (%) Edge Break (%) Northern (KE-UG) 28 18 12 22 11 9 LAPSSET (KE-ET) 31 15 8 25 14 7 Central (TZ-RW) 22 26 18 16 12 6 Kampala–Juba 15 35 28 8 9 5 Dar–Lusaka 20 29 22 12 10 7 Mombasa–Kigali 26 21 15 18 13 7 MEAN 24 24 17 17 12 7 Percentages represent proportion of total surveyed distress area in each category. Distress types identified per ASTM D6433-20 field procedure. All rows sum to 100%. 6. Investment Requirements and Prioritised Allocation Based on the deterioration model projections, multi-criteria performance assessment, and lifecycle cost analysis, network-level pavement maintenance and rehabilitation investment requirements over a 10- year horizon (2025–2034) were estimated for all six corridors at three investment scenario levels: Minimum (routine maintenance only, no structural intervention), Adequate (preventive maintenance where warranted, structural rehabilitation for corridors wit h RSL < 5 years), and Optimal (proactive preventive maintenance programme for all corridors plus full rehabilitation of Kampala–Juba and Dar–Lusaka critical sections). Under the Optimal scenario, total network-level investment requirements are USD 2.34 bil lion over 10 years, compared with USD 1.87 billion under the Adequate scenario and USD 1.24 billion under the Minimum scenario. The higher initial investment in the Optimal scenario yields a projected 34% reduction in total lifecycle costs over the 20-year analysis period, driven by the substantially lower unit cost of preventive maintenance interventions (thin overlays: USD 35,000–60,000/km) compared with structural rehabilitation (USD 280,000–450,000/km) when applied before the PCI deteriorates below the optimal intervention threshold. Table 4. 10-Year Maintenance and Rehabilitation Investment Requirements by Corridor and Scenario (USD millions) Corridor Length (km) Min. Scenario Adequate Scenario Optimal Scenario Priority Rank Primary Intervention Kampala–Juba 560 USD 142M USD 312M USD 389M 1 — Critical Emergency rehab + drainage Dar–Lusaka 980 USD 198M USD 387M USD 448M 2 — Urgent Structural overlay + subgrade Central Corridor 1,100 USD 187M USD 342M USD 398M 3 — High Preventive overlay + drainage Mombasa–Kigali 640 USD 98M USD 187M USD 224M 4 — Moderate Crack sealing + thin overlay Northern Corridor 840 USD 142M USD 247M USD 287M 5 — Moderate Preventive maintenance LAPSSET Corridor 720 USD 117M USD 198M USD 234M 6 — Low Routine maintenance only TOTAL 4,840 USD 884M USD 1,673M USD 1,980M — — Investment estimates in 2024 USD; 15% contingency included. Min=routine maintenance only; Adequate=preventive+structural rehabilitation for RSL<5yr corridors; Optimal=full proactive programme. Discount rate 8%. 7. Discussion The most significant finding of this study is the magnitude of the performance differential between the best-maintained (LAPSSET: IRI = 2.8, PCI = 79, β = 0.028) and worst-maintained (Kampala–Juba: IRI = 6.7, PCI = 34, β = 0.078) corridors on the EAC network. This 2.8-fold difference in deterioration rate, occurring on corridors with broadly similar pavement design standards, cann