Evidence map›Paper›PMID 32046732›Full record

ArticleInternational journal of health geographics2020

A network analysis framework to improve the delivery of mosquito abatement services in Machala, Ecuador.

Catherine A Lippi, Liang Mao, Anna M Stewart-Ibarra, Naveed Heydari, Efraín Beltrán Ayala, Nathan D Burkett-Cadena, Jason K Blackburn, Sadie J Ryan

Abstract read
In one paragraph

Article in International journal of health geographics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Article
  4. Review
  5. Article
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

8 authors.

Catherine A LippiQuantitative Disease Ecology and Conservation (QDEC) Lab Group, Department of Geography, University of Florida, Gainesville, FL, USA. clippi@ufl.edu.ORCID 0000-0002-7988-0324
Liang MaoDepartment of Geography, University of Florida, Gainesville, FL, USA.
Anna M Stewart-IbarraInterAmerican Institute for Global Change Research, Department of Montevideo, Montevideo, Uruguay.ORCID 0000-0002-3383-4672
Naveed HeydariInstitute for Global Health and Translational Science, State University of New York Upstate Medical University, Syracuse, NY, USA.
Efraín Beltrán AyalaUnidad Académica de Ciencias Químicas y de la Salud, Universidad Técnica de Machala, Machala, Ecuador.
Nathan D Burkett-CadenaFlorida Medical Entomology Laboratory, University of Florida, Vero Beach, FL, USA.ORCID 0000-0001-6168-1637
Jason K BlackburnEmerging Pathogens Institute, University of Florida, Gainesville, FL, USA.ORCID 0000-0003-0928-4831
Sadie J RyanQuantitative Disease Ecology and Conservation (QDEC) Lab Group, Department of Geography, University of Florida, Gainesville, FL, USA. sjryan@ufl.edu.ORCID 0000-0002-4308-6321

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVector-borne disease places a high health and economic burden in the American tropics. Comprehensive vector control programs remain the primary method of containing local outbreaks. With limited resources, many vector control operations struggle to serve all affected communities within their districts. In the coastal city of Machala, Ecuador, vector control services, such as application of larvicides and truck-mounted fogging, are delivered through two deployment facilities managed by the Ecuadorian Ministry of Health. Public health professionals in Machala face several logistical issues when delivering mosquito abatement services, namely applying limited resources in ways that will most effectively suppress vectors of malaria, dengue, and encephalitis viruses.

methodsUsing a transportation network analysis framework, we built models of service areas and optimized delivery routes based on distance costs associated with accessing neighborhoods throughout the city. Optimized routes were used to estimate the relative cost of accessing neighborhoods for mosquito control services in Machala, creating a visual tool to guide decision makers and maximize mosquito control program efficiency. Location-allocation analyses were performed to evaluate efficiency gains of moving service deployment to other available locations with respect to distance to service hub, neighborhood population, dengue incidence, and housing condition.

resultsUsing this framework, we identified different locations for targeting mosquito control efforts, dependent upon management goals and specified risk factors of interest, including human population, housing condition, and reported dengue incidence. Our models indicate that neighborhoods on the periphery of Machala with the poorest housing conditions are the most costly to access. Optimal locations of facilities for deployment of control services change depending on pre-determined management priorities, increasing the population served via inexpensive routes up to 34.9%, and reducing overall cost of accessing neighborhoods up to 12.7%.

conclusionsOur transportation network models indicate that current locations of mosquito control facilities in Machala are not ideal for minimizing driving distances or maximizing populations served. Services may be optimized by moving vector control operations to other existing public health facilities in Machala. This work represents a first step in creating a spatial tool for planning and critically evaluating the systematic delivery of mosquito control services in Machala and elsewhere.

Indexed as

Models, TheoreticalMosquito ControlMosquito VectorsTransportationAnimalsDisease OutbreaksEcuadorHousingHumansMalariaPublic HealthRisk FactorsEcuadorGISNetwork analysisService deliveryVector control

Identifiers

PMID32046732
PMCPMC7014633

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.