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How 8 Million Dar es Salaam Residents Lose Up to 5 Hours a Day to Traffic — TICGL
TICGL / TERI Research Paper · 2025

How More Than 8 Million Dar es Salaam Residents Lose Up to 5 Hours a Day to Traffic Congestion, Costing the City Economy an Estimated TZS 4 Billion Daily

A data-driven assessment of commuting time, congestion-related productivity loss, and economic implications for workers and businesses in Tanzania's commercial capital.

📍 Dar es Salaam, Tanzania 📅 Reference Period: 2023–2025 🏛 Tanzania Investment and Consultant Group Ltd (TICGL) Tanzania Economic Research Institute (TERI)
2.48–5.0 Hours lost per worker, per day Measured range across corridors
TZS 4 Bn Estimated daily productivity cost World Bank / DMDP reference figure
TTI = 2.19 Travel Time Index (peak vs. off-peak) Peak journeys take 2.19× longer

Dar es Salaam, Tanzania's commercial capital and fastest-growing city in East Africa, faces a deepening urban mobility crisis. Severe traffic congestion on its primary road corridors imposes significant time losses on the city's workers, traders, and business operators, translating into measurable productivity deficits and economic costs. Workers in Dar es Salaam lose an average of 2.48 to 5.0 hours per day to congestion-related travel delays, with a city-wide productivity cost estimated at approximately TZS 4 billion per day — equivalent to roughly 6 percent of the city's annual GDP. The paper identifies major congestion corridors, disaggregates the impact by worker category, and proposes evidence-based policy responses aligned with Tanzania's Fourth Five-Year Development Plan (FYDP IV) and Development Vision 2050.

Introduction: A City Under Structural Pressure

Dar es Salaam is one of the fastest-growing cities in sub-Saharan Africa, expanding at an annual rate of approximately 6.5 percent, with a metropolitan population approaching 8 million people as of 2025. It functions as Tanzania's commercial, financial, and industrial hub, contributing an estimated 17 to 20 percent of national GDP, with a per-capita GDP of TZS 5.8 million — more than double the national average.

Yet alongside this growth comes a deepening urban mobility crisis. The city's road infrastructure has not kept pace with rapid urbanisation, motorisation, and population growth. Approximately 70 percent of all registered vehicles in Tanzania operate within Dar es Salaam, placing an enormous burden on a road network designed for a fraction of current demand.

The economic significance of this congestion is rarely captured in formal economic accounts. Lost working hours, delayed business openings, missed client appointments, reduced delivery frequency, and excessive fuel expenditure are real costs borne by individuals and firms — but they are largely invisible in aggregate productivity statistics. This research makes those costs visible, measurable, and actionable for policymakers and urban planners.

"For a salaried worker, congestion means arriving late, leaving early, or working fewer effective hours. For a market trader, it means a delayed opening, fewer customers served, and reduced daily turnover. For a transport-dependent business, it means missed deliveries, higher fuel costs, and lower operational efficiency."

Dar es Salaam Population Growth Trend
Millions of residents, 2010–2030 (projected)
DSM Share of Tanzania's Registered Vehicles
Concentration of national vehicle fleet in Dar es Salaam

The Vehicle Fleet and Infrastructure Gap

An estimated 70 percent of all registered vehicles in Tanzania are located in Dar es Salaam. The total vehicle volume has been estimated at over 400,000, including more than 6,000 commuter buses (daladala). Yet the city's trunk road network was designed for a fraction of that load.

The average vehicular speed on major Dar es Salaam roads during peak hours has been measured at as low as 10 to 15 km/h — well below the free-flow benchmark of approximately 30 to 35 km/h on urban arterials. This means congestion effectively reduces average speeds by more than 50 percent during morning and evening peaks.

Average Road Speed: Free-Flow vs. Peak Hours (km/h)
Dar es Salaam major arterials — speed comparison by condition

BRT Status and the Infrastructure Gap

The Dar es Salaam Bus Rapid Transit (DART) system was introduced to provide high-capacity public transit on the Morogoro Road corridor. Phase 1, covering Kimara to Kivukoni, has been operational since 2016. However, only a single corridor is currently fully operational with dedicated busway infrastructure. The remaining major corridors — Kilwa Road, Nyerere Road, Mandela Road, and the northern approach routes — continue without BRT, leaving the overwhelming majority of workers dependent on daladala and private vehicles competing on the same road space.

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BRT Coverage Gap: Of Dar es Salaam's five major arterial corridors, only the Morogoro Road Phase 1 corridor has dedicated BRT infrastructure. The remaining four corridors — serving the majority of commuters — have no segregated transit lanes, with all vehicles competing for the same road space.

Residential Origins and Economic Destination Corridors

Dar es Salaam's urban form is predominantly monocentric — employment and commercial activity are heavily concentrated in a central corridor stretching from the CBD (Posta, Kisutu, Kariakoo) northward through Masaki, Msasani, and Mikocheni. Residential growth pushes workers and traders into peripheral areas, which are poorly connected to employment centres by road.

ZoneKey Residential AreasEconomic DestinationsPrimary Corridor
NorthernTegeta, Wazo, Bunju, Mbezi Beach, Kawe, Goba, Mwenge, KinondoniCBD, Masaki, Msasani, MikocheniSam Nujoma / Ali Hassan Mwinyi Road
WesternKimara, Ubungo, Sinza, Kijitonyama, Mbezi LuisCBD, Kariakoo, Posta, UbungoMorogoro Road
South-WesternTabata, Segerea, Ukonga, Gongo la Mboto, Pugu, Buguruni, VingungutiCBD, Kariakoo, Industrial areasNyerere Road / Mandela Road
SouthernMbagala, Chamazi, Tandika, Temeke, MtoniCBD, Kariakoo, Port/KurasiniKilwa Road / Bandari Road
KigamboniKigamboni, MjimwemaCBD, Kurasini, PortFerry / Bridge link
Port-IndustrialKurasini, BandariCBD, Kariakoo, Industrial zonesKilwa Road / Nyerere Road link

Table 1: Study area breakdown — major residential origin zones mapped against primary economic destination clusters. Source: TICGL, JICA Dar Transport Master Plan.


Travel Time Evidence: Peak-Hour Burden by Corridor

The most comprehensive primary research on travel time loss in Dar es Salaam was conducted along the Morogoro Road and Nelson Mandela Road corridors. The measured Travel Time Index (TTI) was 2.19, which means a journey during peak hours takes on average 2.19 times longer than the same journey during off-peak conditions — a congestion surcharge of 119 percent on every peak-hour commute.

The same study found an asymmetric effect: workers spent approximately double the off-peak time travelling to work in the morning, but approximately triple the off-peak time returning home in the evening. This means the evening peak is significantly more severe than the morning peak, compounding fatigue and reducing available time for rest, family activity, and secondary economic engagement.

Travel Time Index: DSM vs. African Peer Cities
Congestion multiplier (1.0 = free flow; higher = worse)
Morning vs. Evening Peak Severity
Ratio of peak travel time to free-flow baseline

Corridor-Level Travel Time Matrix

The following matrix provides estimated travel times across major commuter corridors, comparing morning peak and off-peak conditions, based on the TTI of 2.19 applied to corridor-specific baseline distances.

OriginDestinationDistance (km)Off-Peak (min)Peak (min)Excess Time (min)
TegetaKariakoo / CBD24–2745–50120–13575–85
TegetaMasaki / Msasani20–2240–4595–11555–70
KimaraPosta / CBD20–2235–4575–10040–55
MbagalaKariakoo / CBD18–2035–4580–10545–60
UkongaKariakoo / CBD15–1830–4070–9540–55
Goba / Mbezi LuisMwenge12–1525–3560–8035–45
KigamboniPosta / CBD22–2540–5090–12050–70
TemekeKilwa Rd / CBD14–1730–4070–9040–50
Segerea / TabataNyerere Rd / CBD12–1525–3560–8035–45

Table 2: Author estimates based on measured TTI of 2.19 (Mpogole et al., 2016); corridor distances from JICA Dar Transport Master Plan. All figures approximate.

Spotlight: Worst-Affected Corridors

Tegeta → CBD Corridor
Via Sam Nujoma / Ali Hassan Mwinyi Road
135 min
Peak journey time
47 min
Off-peak baseline
5 hrs
Max daily round trip
Kimara → CBD Corridor
Via Morogoro Road (BRT Phase 1)
100 min
Peak journey time
40 min
Off-peak baseline
3.3 hrs
Max daily round trip
Mbagala → CBD Corridor
Via Kilwa Road
105 min
Peak journey time
40 min
Off-peak baseline
3.5 hrs
Max daily round trip
Kigamboni → CBD Corridor
Via Ferry / Kigamboni Bridge
120 min
Peak journey time
45 min
Off-peak baseline
4 hrs
Max daily round trip
Peak vs. Off-Peak Journey Times by Corridor
Minutes — midpoint estimates per origin-destination pair

The Tegeta Corridor: A Representative Case Study

A worker living in Tegeta and employed in the CBD — approximately 25 kilometres via Sam Nujoma or Ali Hassan Mwinyi Road — may complete the journey in 45 to 50 minutes during off-peak conditions. During morning peak hours (approximately 06:30 to 09:00), the same journey routinely requires 120 to 135 minutes, and during evening peak (approximately 16:30 to 20:00), delays can extend to 150 minutes or beyond.

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The Tegeta Time Calculation: On a round trip, a Tegeta-based worker may spend between 3.5 and 5.0 hours per day in transit. Against a nominal 8-hour working day, this means up to 62 percent of a worker's waking productive window is consumed by mobility alone — before any time is allocated to eating, household responsibilities, rest, or skill development.

Productive Hours Lost: Estimation by Worker Category

Dar es Salaam's labour force includes formal private sector employees, civil servants, self-employed traders, artisans, service providers, transport operators, and a large informal sector. The NBS Integrated Labour Force Survey estimates that the informal sector employs approximately 76 percent of Tanzania's workforce. Workers are grouped into four categories to capture the different ways congestion affects productive time.

A
Formal Salaried Employees
2.0–3.0 hrs/day lost
Office employees, civil servants, private sector professionals. Direct impact: late arrival, reduced effective working day. Some leave home as early as 03:00–04:00 to avoid peak hours, sacrificing sleep rather than working hours.
B
Self-Employed Traders & Market Operators
1.5–2.5 hrs/day lost
Market traders, informal sector operators, small-scale vendors. Time is directly monetised — a trader who opens one hour late loses one hour of trading time. Doubly exposed when making multiple supply trips.
C
SME Owners, Service Providers & Professionals
1.5–3.0 hrs/day lost
SME operators, legal, accounting, consulting, medical professionals. Impact extends beyond personal commute — staff lateness, missed client meetings, and delivery delays all compound the business-level time loss.
D
Transport-Dependent Businesses & Logistics
2.0–4.0 hrs/day lost
Freight haulers, delivery services, daladala operators. Under free-flow conditions, a vehicle might complete 6 delivery cycles per day; peak congestion reduces this to 3–4. Revenue falls, fuel costs rise.
Daily Hours Lost by Worker Category
Low and high estimate range per category
Annual Productive Hours Lost per Worker
Mid-point estimate over 312 working days

Aggregate Productive Hours Lost — Summary Table

Worker CategoryDaily Hrs LostMonthly Hrs Lost (26 days)Annual Hrs Lost (312 days)% of Annual Working Hrs
Formal Salaried Employees2.0 – 3.052 – 78624 – 93631 – 47%
Self-Employed Traders1.5 – 2.539 – 65468 – 78023 – 39%
SME Owners / Professionals1.5 – 3.039 – 78468 – 93623 – 47%
Transport / Logistics Operators2.0 – 4.052 – 104624 – 1,24831 – 62%
Average across categories2.48 – 3.064 – 78774 – 93639 – 47%

Table 3: Assumes 2,000 standard working hours per year (8 hrs/day × 250 working days). Hours lost are productive-equivalent hours, not total commute hours. Source: Mpogole et al. (2016); Elisonguo (2013); TICGL analysis.

What Does 47% Lost Working Time Mean?

A worker losing 47 percent of their annual working hours to congestion is effectively working for only 53 percent of their nominal working year — equivalent to just over six months of productive output from a twelve-month salary or business investment. For the city's aggregate economy, this is not a marginal inefficiency; it is a structural shortfall in human capital deployment at scale.

Transport / Logistics (max)
62%
Formal Employees (max)
47%
SME Owners (max)
47%
Traders (max)
39%
Average (mid)
43%

Figure: Percentage of annual working hours lost to congestion, by worker category (maximum estimates). Source: TICGL analysis.


The Economic Cost of Congestion-Related Time Loss

The most widely used methodology for valuing lost time in transport economics is the wage-based approach, which treats the opportunity cost of time as equivalent to the marginal value of an hour of labour. As of 2025, the mean urban wage in Tanzania was estimated at TZS 494,812 per month (approximately USD 189), implying a mean hourly wage of approximately TZS 2,378 per hour (assuming 208 working hours per month).

Individual-Level Cost Estimation

ParameterLow EstimateMid EstimateHigh EstimateBasis
Daily excess time lost (hrs)2.02.55.0Measured range from Dar studies
Mean hourly wage (TZS)1,8002,3784,200NBS / World Bank 2025 data
Daily monetary loss (TZS)3,6005,94521,000Hours lost × hourly wage
Monthly loss (TZS, 26 days)93,600154,570546,000Daily × 26
Annual loss (TZS, 312 days)1,123,2001,854,8406,552,000Daily × 312
Annual loss (USD equivalent)$430$710$2,510At TZS 2,610 / USD (2025)

Table 4: Individual-level congestion cost estimation. Source: NBS Tanzania Integrated Labour Force Survey; TICGL analysis.

Annual Individual Cost of Congestion (TZS)
Low, mid, and high scenario by estimate
City-Wide Daily Productivity Loss (TZS Billions)
Conservative, mid and World Bank reference scenarios

City-Wide Daily Economic Cost Estimate

Conservative Scenario
TZS 5.4 Bn/day
1.5M commuters × TZS 3,600/day avg loss
Mid Scenario
TZS 7.2 Bn/day
2.0M commuters × TZS 3,600/day avg loss
World Bank / DMDP Reference
TZS 4 Bn/day
≈ USD 1.8 million per day
At mid scenario, the annualised city-wide productivity loss exceeds TZS 2.0 trillion per year (approximately USD 780 million) — equivalent to roughly 6% of Dar es Salaam's estimated annual GDP.

The Broader Economic Multiplier

The direct wage-equivalent time loss is only one component of the true economic cost. Several additional channels amplify the aggregate impact:

Cost Channels: Congestion's Broader Economic Footprint
Relative estimated contribution to total economic impact (illustrative)
Wage/productivity loss
~55%
Fuel overconsumption
~18%
Vehicle wear/maintenance
~10%
Supply chain inefficiency
~10%
Health & fatigue costs
~7%

Figure: Illustrative breakdown of congestion's total economic impact. Direct wage-equivalent loss is quantified; other channels are estimated. Source: TICGL analysis based on literature review.


Business-Level Impacts: Traders, SMEs, and Transport Operators

For Dar es Salaam's market traders and small retailers, the day begins with the journey to market — either to pick up wholesale stock from Kariakoo, Tandika, or Mwenge markets, or to open a fixed location on time. Traffic congestion imposes an opening-time penalty on both activities.

Transport-dependent businesses face compounded exposure. A single delivery vehicle that might complete six delivery cycles per day under free-flow conditions may complete only three to four cycles under peak congestion — halving the operational output of that vehicle and its driver.

Sector-Specific Impact Analysis

SectorPrimary Congestion ImpactKey Productivity Loss ChannelSeverity
Retail / TradingLate opening; delayed stock pickup from wholesale marketsFewer customer transactions per day; reduced daily turnoverHigh
Construction / EngineeringDelayed material delivery; worker lateness affecting site start timeReduced site working hours; project schedule overruns; cost escalationHigh
Hospitality / Food ServiceDelayed food supply delivery; staff late arrival; reduced breakfast/lunch serviceLost covers; food waste; reduced revenue per seat per dayMedium–High
HealthcarePatient late arrival; staff commute delays; ambulance response time degradedReduced patient throughput; emergency response riskHigh
Financial / Professional ServicesClient appointments missed or shortened; staff unreliable attendanceFewer billable hours; lower client satisfaction; reduced deal flowMedium
Logistics / TransportFewer delivery cycles per vehicle per day; higher fuel burnRevenue loss per vehicle; higher operating cost; supply chain disruptionVery High
Manufacturing / IndustrialRaw material delivery delay; shift start disruptionReduced output per shift; energy and idle cost increaseMedium–High

Table 5: Sector-specific congestion impact analysis. Source: TICGL research synthesis.

Estimated Daily Revenue Loss by Business Type (TZS '000 per operator)
Illustrative mid-scenario estimates based on sector turnover and congestion delay assumptions

"Commuter bus owners bear a double burden: fewer trips per day and significantly higher fuel consumption due to idle time in congestion — compressing margins, reducing public transport reliability, and creating a self-reinforcing negative cycle for the workers who depend on it."


Policy Recommendations: From Evidence to Action

At an estimated TZS 4 to 7 billion per day in productivity value foregone — equivalent to approximately 6 percent of the city's GDP — Dar es Salaam's congestion-related productivity loss represents one of the largest unaddressed efficiency deficits in Tanzania's urban economy. Addressing it is a core economic development imperative directly relevant to the targets of FYDP IV and Development Vision 2050.

1
Infrastructure
Accelerate BRT Network Expansion Beyond Phase 1

The single most transformative intervention is the rapid expansion of the DART BRT network onto Kilwa Road (Southern Corridor), Nyerere Road (South-West), and the northern approach routes (Sam Nujoma / Ali Hassan Mwinyi). World Bank DMDP financing should be leveraged to accelerate corridor delivery, with PPP structures considered for station development and service operation.

2
Urban Policy
Establish Decentralised Economic Nodes

The monocentric structure of Dar es Salaam is a root cause of the congestion burden. Deliberate investment in secondary economic hubs — commercial and light industrial zones in Tegeta/Mbezi, Kigamboni, Ukonga/Gongo la Mboto, and Mbagala — would distribute the employment geography and reduce cross-city peak commutes. Consistent with FYDP IV's satellite city and secondary urban centre concepts.

3
Regulatory
Introduce Staggered Work Hours for Public Sector

A zero-capital, immediately implementable intervention: shift a portion of the government workforce to earlier (07:00) or later (09:30) start times, spreading peak demand across a wider time window and reducing the height of the morning peak. As the largest single employer in Dar es Salaam, the government can implement this unilaterally.

4
Regulatory
Promote Freight and Logistics Scheduling Outside Peak Hours

Require heavy and commercial vehicles to operate in designated time windows (before 06:00 and after 21:00 for centre-city deliveries), modelled on practices in Nairobi, Kampala, and Kigali. TANROADS and the municipal authorities have the regulatory mandate to implement such restrictions.

5
Technology / HR
Remote and Flexible Work Policy for the Private Sector

With mobile broadband penetration estimated at 80–85 percent nationally, a meaningful share of the formal sector workforce could perform some portion of their work remotely. Employer-led flexibility policies (work from home one or two days per week) would reduce the daily commuter volume without requiring infrastructure investment.

6
Engineering
Junction Upgrades and Traffic Signal Optimisation

Several of the worst congestion hotspots are attributable to poorly performing intersections. Targeted engineering interventions at key nodes — including grade-separated interchanges at Ubungo and Tazara — and modern adaptive traffic signal systems could significantly reduce localised bottlenecks at modest cost compared to new road construction.

7
Data & Research
Annual Congestion Cost Reporting and Data Collection

Tanzania's policymakers currently lack consistent, annually updated data on congestion levels, travel times, and productivity costs for Dar es Salaam. Establishing a formal annual congestion monitoring programme — drawing on GPS floating car data, DART operational data, and periodic commuter surveys — would enable evidence-based investment prioritisation. TICGL/TERI is positioned to contribute to this monitoring function.

Policy Intervention Matrix: Estimated Cost vs. Impact Potential
Indicative positioning of seven recommended interventions

Conclusion: Urban Mobility is an Economic Growth Strategy

Traffic congestion in Dar es Salaam is among the most costly and least-measured economic drains on Tanzania's fastest-growing city. The central findings of this research are unambiguous. Workers lose an average of 2.48 to 5.0 hours per day to congestion-related travel delays. Across a working month of 26 days, this implies a loss of 64 to 78 productive hours per worker — equivalent to nearly two full working weeks consumed annually by congestion alone.

The city-wide monetary cost is estimated conservatively at TZS 4 billion per day, equivalent to approximately TZS 1.2 to 2.0 trillion per year, or roughly 6 percent of Dar es Salaam's annual GDP.

The impact falls most heavily on peripheral corridor residents — particularly those living in Tegeta, Kimara, Mbagala, Ukonga, and Kigamboni — who face the longest commutes to the employment-dense CBD and northern business corridors. For market traders and informal sector operators, the impact is compounded through lost trading time, delayed market openings, reduced delivery cycles, and lower daily turnover.

"Tanzania's FYDP IV and Development Vision 2050 both identify urbanisation as a transformative driver of growth. That potential will not be realised if Dar es Salaam's workers continue to lose a third to half of their productive working time to roads. Urban mobility is not a secondary concern of development planning — it is a primary determinant of how productively a city's human capital can be deployed."

Projected Cumulative Productivity Loss Without Intervention (TZS Trillion)
Modelled annual accumulation 2025–2035, assuming population growth of 6.5% p.a. and no major infrastructure improvement

🇹🇿
Muhtasari wa Kiswahili
Kwa wasomaji wa lugha ya Kiswahili — TICGL / TERI
🚦
Tatizo Kuu
Dar es Salaam inakabiliwa na msongamano mkubwa wa magari ambao unawasababishia wakaazi zaidi ya milioni 8 kupoteza saa 2.48 hadi 5.0 kila siku katika misongamano ya barabarani. Hii inamaanisha kwamba mfanyakazi mmoja hupoteza saa za kazi za thamani — bila kupata malipo — tu kwa sababu ya msongamano wa usafiri.
💰
Gharama ya Uchumi
Kwa mujibu wa Benki ya Dunia na takwimu za mradi wa DMDP, gharama ya uzalishaji iliyopotea kila siku jijini Dar es Salaam inakadiriwa kufikia TZS bilioni 4 — sawa na dola za Marekani milioni 1.8 kwa siku. Kwa mwaka mzima, hasara hii inaweza kuzidi TZS trilioni 1.2 hadi 2.0, sawa na asilimia 6 ya Pato la ndani la Dar es Salaam.
📊
Kiwango cha Msongamano (TTI)
Kiwango cha TTI (Travel Time Index) kilichopimwa Dar es Salaam ni 2.19. Hii inamaanisha kwamba safari inayochukua dakika 30 wakati wa usiku au mapema asubuhi, inachukua dakika 66 wakati wa msongamano wa asubuhi — ongezeko la asilimia 119. Ukanda wa Tegeta unakabiliwa zaidi — safari ya kilomita 25 inaweza kuchukua dakika 135 au zaidi.
🏪
Athari kwa Wafanyabiashara
Wafanyabiashara wa masoko ya Kariakoo, Tandika, na Mwenge wanafungua maduka yao baadaye kutokana na msongamano. Hii inamaanisha kupoteza muda wa biashara wa saa 1 hadi 2 kila siku. Kwa mwezi mzima, mfanyabiashara mmoja anaweza kupoteza saa 52 hadi 78 za biashara — sawa na wiki zaidi ya moja na nusu ya wakati wa kufanya biashara.
🚌
Msongamano na BRT
Mfumo wa DART (BRT) bado unafanya kazi kwenye njia moja tu — Morogoro Road (Kimara–Kivukoni). Njia nyingine nne kuu — Kilwa Road, Nyerere Road, Mandela Road, na Sam Nujoma Road — hazina mfumo wa usafiri wa haraka (BRT), hivyo watumiaji wengi wanategemea daladala ambazo zinashindana na magari mengine barabarani. Hii ni sababu kuu ya msongamano.
💡
Mapendekezo ya Sera
TICGL/TERI inapendekeza: (1) Kupanua mtandao wa BRT haraka kwenye njia nyingine; (2) Kuanzisha vituo vya kiuchumi kwenye maeneo ya nje ya jiji kupunguza safari za mbali; (3) Kufanya mabadiliko ya muda wa kuanza kazi serikalini; (4) Kudhibiti magari mazito kufanya kazi usiku; (5) Kuruhusu kazi za nyumbani kwa sekta ya kibinafsi; (6) Kuboresha taa za barabarani na makutano muhimu. Hizi ni hatua zinazoweza kutekelezwa sasa hivi, na zinalingana na FYDP IV na Dira 2050.

References and Data Sources

  1. Basondole, A. (n.d.). Traffic congestion estimates for Dar es Salaam. Unpublished report.
  2. Elisonguo, A. D. (2013). The Social-Economic Impact of Road Traffic Congestion in Dar es Salaam Region. Mzumbe University, Morogoro.
  3. IMF (2025). World Economic Outlook. International Monetary Fund, Washington DC.
  4. JICA (2008). Dar es Salaam Transport Policy and System Development Master Plan. Technical Report. Japan International Cooperation Agency / Pacific Consultants International, Tokyo.
  5. Kiunsi, R. B. (2013). A Review of Traffic Congestion in Dar es Salaam City from the Physical Planning Perspective. Ardhi University, Dar es Salaam.
  6. Mpogole, H., Mwamfupe, D., & Mwakatobe, A. (2016). Traffic Congestion in Dar es Salaam: Implications for Workers' Productivity. Journal of Sustainable Development, Canadian Center of Science and Education.
  7. Msigwa, R. (2013). Challenges facing urban transportation in Dar es Salaam. Academic Journal of Interdisciplinary Studies, 2(3), 145–155.
  8. NBS (2023). Tanzania Integrated Labour Force Survey 2022/23. National Bureau of Statistics, Dar es Salaam.
  9. TICGL (2025). Economics of Cities in Tanzania. Tanzania Investment and Consultant Group Ltd / Tanzania Economic Research Institute. www.ticgl.com.
  10. TomTom (2025). TomTom Traffic Index 2025: Annual Report on Global Urban Congestion. TomTom International BV, Amsterdam.
  11. World Bank (2019). Untying Dar es Salaam's Traffic Knots, One Feeder Road at a Time. World Bank Feature Story, 1 April 2019.
  12. World Bank (2024). Tanzania Country Overview. World Bank, Washington DC.

Msongamano wa Dar es Salaam: Wafanyakazi Zaidi ya Milioni 8 Wanapoteza Hadi Saa 5 kwa Siku — Na Jiji Linapoteza TZS Bilioni 4 Kila Siku

Na Amran Bhuzohera, Mchumi | TICGL / Tanzania Economic Research Institute (TERI) | Simu: +255 768 699 002

Dar es Salaam ni mojawapo ya miji inayokua haraka zaidi Afrika ya Kusini mwa Jangwa la Sahara — ikua kwa kasi ya asilimia 6.5 kwa mwaka, na idadi ya watu inayokaribia milioni 8 kufikia mwaka 2025. Mji huu ndiyo injini ya uchumi wa Tanzania, ukichangia asilimia 17 hadi 20 ya Pato la Taifa (GDP). Lakini pamoja na ukuaji huu mkubwa, kuna tatizo moja kubwa ambalo linaendelea kupuuzwa katika takwimu rasmi za uchumi:

Msongamano wa barabara unaibia Tanzania nguvu kazi ya thamani ya TZS bilioni 4 kila siku moja.

Hilo ndilo jibu la utafiti wa kina uliofanywa na TICGL na Tanzania Economic Research Institute (TERI), unaotoa tathmini ya kina ya muda unaopotea kwa msongamano, hasara ya uzalishaji na athari za kiuchumi kwa wafanyakazi na biashara jijini Dar es Salaam.

Je, Hali Halisi ni Nini? — Mambo 5 Makubwa ya Kuelewa

1
Kila mfanyakazi anapoteza saa 2.48 hadi 5.0 kwa siku — bila malipo

Utafiti unaonyesha kwamba wafanyakazi wanaotumia usafiri wa umma kwenye barabara za Morogoro Road na Nelson Mandela Road wanapoteza wastani wa saa 2.48 hadi 5.0 kwa siku. Kwa mwezi wa siku 26 za kazi, hii inamaanisha saa 64 hadi 78 zilizopotea — sawa na wiki karibu mbili kamili za kazi zinazomezwa na barabara kila mwezi. Travel Time Index (TTI) iliyopimwa Dar es Salaam ni 2.19 — ongezeko la asilimia 119 kwa kila safari ya muda wa kilele.

2
Gharama kwa jiji ni TZS bilioni 4 kila siku — sawa na asilimia 6 ya GDP ya Dar es Salaam

Ukipima hasara ya uzalishaji kwa wafanyakazi milioni 1.5 hadi 2.0 wanaosafiri kila siku, na kuzidisha kwa mshahara wa wastani wa saa (TZS 2,378), matokeo ni: hali ya wastani TZS bilioni 7.2 kwa siku; kumbukumbu ya Benki ya Dunia / DMDP: TZS bilioni 4 kwa siku; na kwa mwaka mzima zaidi ya TZS trilioni 1.2 hadi 2.0 — takriban asilimia 6 ya GDP ya Dar es Salaam.

3
Ukanda wa Tegeta ni mfano mzuri wa tatizo hili

Mfanyakazi anayeishi Tegeta na kufanya kazi CBD — kilomita 25 — anaweza kukamilisha safari hiyo kwa dakika 45 hadi 50 wakati wa usiku. Lakini wakati wa kilele cha asubuhi, safari hiyo hiyo inachukua dakika 120 hadi 135. Kwa safari ya kwenda na kurudi, mfanyakazi wa Tegeta anaweza kutumia saa 3.5 hadi 5.0 kwa siku barabarani tu — hadi asilimia 62 ya muda wake wa uzalishaji.

4
Biashara ndogo, madereva na wafanyabiashara wa masoko ndio wanaohisi zaidi

Dereva wa daladala anafanya safari 3 hadi 4 tu kwa siku badala ya 6 — nusu ya mapato yanayowezekana. Wafanyabiashara wa masoko ya Kariakoo, Tandika na Mwenge wanafungua maduka yao baadaye — wateja wachache, mapato madogo. Biashara za ujenzi, hospitali na usafirishaji zinabeba mzigo mara mbili: safari chache na mafuta mengi zaidi.

5
Mji wa monocentric ndiyo chanzo kikuu cha tatizo

Dar es Salaam ina muundo wa monocentric — ajira zimejikusanyika eneo moja tu: CBD hadi Masaki, Msasani na Mikocheni. Wakati huo huo, nyumba zinaendelea kujengwa mbali — Tegeta, Kimara, Mbagala, Ukonga, Kigamboni. Zaidi ya hayo, asilimia 70 ya magari yote yaliyosajiliwa Tanzania yako Dar es Salaam — mzigo mkubwa mno kwa barabara zilizoundwa kwa kiwango kidogo.

⚠️
TICGL Warning: Je, Dar es Salaam inaweza kuendelea kuwa injini ya uchumi wa Tanzania huku ikipoteza TZS trilioni 2 kwa mwaka kwa msongamano tu? Kama msongamano huu utaendelea bila jibu madhubuti, na idadi ya watu ikifikia milioni 10 ifikapo 2030, basi hasara ya uzalishaji itaendelea kukua kwa kasi zaidi kuliko uchumi wenyewe.

Hitimisho la TICGL

Msongamano wa Dar es Salaam si tatizo la usafiri tu — ni tatizo la kiuchumi la msingi ambalo linaathiri uwezo wa jiji kutumia kikamilifu nguvu kazi yake, biashara zake na uwekezaji wake. Hasara ya TZS bilioni 4 kwa siku haionekani kwenye akaunti yoyote ya Serikali — lakini inahisiwa kila siku na kila mfanyakazi anayetumia masaa yake kwenye barabara badala ya ofisini, dukani au shambani.

"Mjadala kuhusu uchumi wa Dar es Salaam haupaswi kuishia kwenye swali la 'GDP imekua kiasi gani?' bali uendelee kwenye swali muhimu zaidi: Je, mfanyakazi wa Dar es Salaam anaweza kufanya kazi kwa ufanisi kamili wakati saa 3 hadi 5 za siku yake zinateketezwa na barabara? Hapo ndipo kipimo halisi cha uwezo wa uchumi wa Dar es Salaam kitakapoanzia."

TICGL / Tanzania Economic Research Institute (TERI) | www.ticgl.com | Dar es Salaam, Tanzania. Makala hii imetayarishwa kwa madhumuni ya utafiti na ushiriki wa kisera. Matumizi yake yanakubaliwa kwa idhini.


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TICGL / TERI Research Paper · 2025

Unataka Kupata Nakala Kamili ya Utafiti Huu?

Utafiti kamili wa "Time Lost in Traffic and Its Impact on Productive Economic Activity in Dar es Salaam" unajumuisha data kamili ya corridor-level, mfumo wote wa kihesabu (TTI, ACET, PHLm, MVTL), uchambuzi wa kina wa sekta zote na mapendekezo yaliyokamilika ya kisera — yaliyoundwa na TICGL / Tanzania Economic Research Institute (TERI).

Data kamili ya travel time kwa corridor 9
Hesabu kamili za PHLm, MVTL na BOHL
Uchambuzi wa uchumi — kwa sekta 7
Mapendekezo 7 ya kisera yaliyokamilika
Marejeo yote ya kisayansi na vyanzo vya data
Inafaa kwa watafiti, wawekezaji na watunga sera
✉️ Omba Utafiti Kamili — amran@ticgl.com

Bonyeza kitufe hapo juu ili ufungue barua pepe yako tayari imejazwa. Tuma ombi lako na tutawasiliana nawe haraka iwezekanavyo. · amran@ticgl.com

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