ArticleCureus2025
The Spatial Distribution and Distance-Based Regulatory Compliance of Private Medicine Outlets in Two Urban Districts of Dar es Salaam, Tanzania.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and objective Pharmacies and Accredited Drug Dispensing Outlets (ADDOs) play a central role in expanding access to essential medicines in low- and middle-income countries. In Tanzania, national regulations mandate minimum separation distances to prevent excessive clustering and help ensure that all communities have reasonable access to essential medicines. However, the extent of compliance in rapidly urbanizing districts remains unclear. This study aimed to examine the spatial distribution of private medicine outlets (PMOs) in the Kinondoni and Ubungo districts of Dar es Salaam and assess adherence to regulatory distance requirements. Methods A cross-sectional geospatial survey was conducted across 18 urban centers. Outlet coordinates were collected through field enumeration using REDCap (Research Electronic Data Capture) mobile tools between July 14, 2019, and September 6, 2019. Official ward boundary shapefiles were obtained from the National Bureau of Statistics. Spatial patterns were analyzed by mapping PMO locations, estimating ward-level densities, calculating nearest-neighbor distances, and evaluating compliance with Tanzania's minimum-distance regulations of 150 m for same-type outlets and 500 m for ADDO-pharmacy pairs. Results A total of 377 PMOs were mapped, comprising 232 (61.5%) ADDOs and 145 (38.5%) pharmacies. The outlet distribution was highly uneven: some wards demonstrated dense clustering, while others showed sparse coverage. The median nearest-neighbor distance was 753 m, although distances ranged from <1.0 m to over 6.0 km. Overall, 110 (29.2%) of the outlets fell below the regulatory spacing thresholds. Compliance levels were similar across outlet types. Conclusions Marked clustering and substantial non-compliance with minimum distance regulations were observed in Kinondoni and Ubungo. While dense clustering may improve convenience in some neighborhoods, persistent gaps in other areas suggest emerging spatial inequities. Geospatially informed regulatory planning is required to enhance equitable access to essential medicines. The observed 29.2% non-compliance rate highlights a meaningful regulatory gap, indicating that existing minimum-distance rules are not consistently implemented. This has practical implications for market saturation, potential unfair competition, and uneven access across neighborhoods, reinforcing the need for targeted inspections and more proactive spatial oversight.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.