Evidence map›Paper›PMID 37759213›Full record

ArticleMalaria journal2023

Cost and quality of operational larviciding using drones and smartphone technology.

Andy Hardy, Khamis Haji, Faiza Abbas, Juma Hassan, Abdullah Ali, Yussuf Yussuf, Jackie Cook, Laura Rosu, Arnon Houri-Yafin, Arbel Vigodny and 3 more

Open access · goldAbstract read
In one paragraph

Article in Malaria journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 2 pooled it
5.2field-weighted citation impact, top 4% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 2 syntheses or guidelines pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
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  4. Article
  5. EnhancingRemote sensing applications : society and environment · 2026
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  17. Updates on traditional methods for combating malaria and emergingFrontiers in cellular and infection microbiology · 2024
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 4 institutions in 2 countries.

Andy HardyDeptartment of Geography and Earth Sciences, Aberystwyth University, Aberystwyth, UK. ajh13@aber.ac.uk.
Khamis HajiDeptartment of Geography and Earth Sciences, Aberystwyth University, Aberystwyth, UK.
Faiza AbbasPharmAccess Foundation, Dar Es Salaam, Tanzania.
Juma HassanZanzibar Malaria Elimination Programme, Zanzibar, Tanzania.
Abdullah AliMinistry of Health, Revolutionary Government of Zanzibar, Zanzibar, Tanzania.
Yussuf YussufTanzanian Flying Labs, Dar Es Salaam, Tanzania.
Jackie CookMRC International Statistics and Epidemiology Group, London School Hygiene and Tropical Medicine, London, UK.
Laura RosuLiverpool School of Tropical Medicine, London, UK.
Arnon Houri-YafinZzapp Malaria, Jerusalem, Israel.
Arbel VigodnyZzapp Malaria, Jerusalem, Israel.
Gregory OakesDeptartment of Geography and Earth Sciences, Aberystwyth University, Aberystwyth, UK.
Silas MajambereValent BioSciences, Oslo, Norway.
Eve WorrallLiverpool School of Tropical Medicine, London, UK.
Aberystwyth University · GBLiverpool School of Tropical Medicine · GBLondon School of Hygiene & Tropical Medicine · GBZanzibar University · TZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLarval Source Management (LSM) is an important tool for malaria vector control and is recommended by WHO as a supplementary vector control measure. LSM has contributed in many successful attempts to eliminate the disease across the Globe. However, this approach is typically labour-intensive, largely due to the difficulties in locating and mapping potential malarial mosquito breeding sites. Previous studies have demonstrated the potential for drone imaging technology to map malaria vector breeding sites. However, key questions remain unanswered related to the use and cost of this technology within operational vector control.

methodsUsing Zanzibar (United Republic of Tanzania) as a demonstration site, a protocol was collaboratively designed that employs drones and smartphones for supporting operational LSM, termed the Spatial Intelligence System (SIS). SIS was evaluated over a four-month LSM programme by comparing key mapping accuracy indicators and relative costs (both mapping costs and intervention costs) against conventional ground-based methods. Additionally, malaria case incidence was compared between the SIS and conventional study areas, including an estimation of the incremental cost-effectiveness of switching from conventional to SIS larviciding.

resultsThe results demonstrate that the SIS approach is significantly more accurate than a conventional approach for mapping potential breeding sites: mean % correct per site: SIS = 60% (95% CI 32-88%, p = 0.02), conventional = 18% (95% CI - 3-39%). Whilst SIS cost more in the start-up phase, overall annualized costs were similar to the conventional approach, with a simulated cost per person protected per year of $3.69 ($0.32 to $15.12) for conventional and $3.94 ($0.342 to $16.27) for SIS larviciding. The main economic benefits were reduced labour costs associated with SIS in the pre-intervention baseline mapping of habitats. There was no difference in malaria case incidence between the three arms. Cost effectiveness analysis showed that SIS is likely to provide similar health benefits at similar costs compared to the conventional arm.

conclusionsThe use of drones and smartphones provides an improved means of mapping breeding sites for use in operational LSM. Furthermore, deploying this technology does not appear to be more costly than a conventional ground-based approach and, as such, may represent an important tool for Malaria Control Programmes that plan to implement LSM.

Indexed as

AnophelesMalariaAnimalsHumansLarvaMosquito VectorsSmartphoneTechnologyUnmanned Aerial Devices

Identifiers

PMID37759213
PMCPMC10523724
OpenAlexW4387102171

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.