ArticleMalaria journal2026
Costs of single-phase door-to-door insecticide-treated net mass distribution campaigns in Nigeria: a case study in Ondo and Anambra states.
Article in Malaria journal, 2026. 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
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe distribution of insecticide-treated nets (ITNs) through mass campaigns remains a cornerstone of malaria vector control. As new ITN products are introduced to address rising insecticide resistance, understanding the cost of such campaigns is essential for informed policy decisions. This study aimed to estimate the programmatic and annualized economic costs of campaigns that distributed pyrethroid-PBO ITNs in Ondo and Anambra States, Nigeria, using a single-phase, door-to-door strategy.
methodsA micro-costing approach was used to estimate campaign economic costs from the provider perspective. Financial costs were obtained retrospectively from campaign financial records, while opportunity costs were assessed through key informant interviews and focus group discussions. Shadow pricing was employed to value resources without market prices. We estimated the programmatic economic costs of delivering ITNs to households, and annualized costs, accounting for ITN lifespan beyond one year.
resultsA total of 2,965,125 pyrethroid-PBO nets were distributed in Ondo State and 3,850,316 in Anambra State. The programmatic economic cost of delivering an ITN to a household was estimated at $3.22 in Ondo and $3.19 in Anambra. Net procurement was the primary cost driver, accounting for 77% of the total costs of delivery to households in Ondo and 82% in Anambra. Unit distribution costs were $0.74 per net in Ondo and $0.57 in Anambra. Financial costs comprised 98% of total economic costs in Ondo and 97% in Anambra. Assuming an ITN lifespan of 2.5 years and a 3% annual discount rate, the annual economic cost was $1.36 per ITN distributed and $0.72 per person potentially protected in Ondo, and $1.34 and $0.69 respectively in Anambra. Sensitivity analysis indicated that ITN durability was the dominant factor influencing annual cost per person protected, while variations in discount rate (3-5%) had only modest effects.
conclusionITN campaign economic costs in this study were lower than most estimates from other African countries. While net procurement was the primary cost driver, the cost per year of effective protection was strongly influenced by ITN durability, highlighting the need for strategies that extend functional net lifespan. The findings provide essential inputs for cost-effectiveness analyses of campaign deployment of new generation nets when combined with epidemiological impact data.
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.