Evidence map›Paper›PMID 39495715›Full record

ArticlePLoS neglected tropical diseases2024

The role of connectivity on malaria dynamics across areas with contrasting control coverage in the Peruvian Amazon.

Gabriel Carrasco-Escobar, Diego Villa, Antony Barja, Rachel Lowe, Alejandro Llanos-Cuentas, Tarik Benmarhnia

Abstract read
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Article in PLoS neglected tropical diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Gabriel Carrasco-EscobarHerbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, California, United States of America.ORCID 0000-0002-6945-0419
Diego VillaHerbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, California, United States of America.
Antony BarjaHerbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, California, United States of America.
Rachel LoweCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.
Alejandro Llanos-CuentasInstituto de Medicina Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru.
Tarik BenmarhniaScripps Institution of Oceanography, University of California, San Diego, California, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Network analysis may improve the understanding of malaria epidemiology in rural areas of the Amazon region by explicitly representing the relationships between villages as a proxy for human population mobility. This study tests a comprehensive set of connectivity metrics and their relationship with malaria incidence across villages with contrasting PAMAFRO (a malaria control initiative) coverage levels in the Loreto department of Peru using data from the passive case detection reports from the Peruvian Ministry of Health between 2011 and 2018 at the village level. A total of 24 centrality metrics were computed and tested on 1608 nodes (i.e., villages/cities). Based on its consistency and stability, the betweenness centrality type outperformed other metrics. No appreciable differences in the distributions of malaria incidence were found when using different weights, including population, deforested area, Euclidian distance, or travel time. Overall, villages in the top quintile of centrality have a higher malaria incidence in comparison with villages in the bottom quintile of centrality (Mean Difference in cases per 1000 population; P. vivax = 165.78 and P. falciparum = 76.14). The mean difference between villages at the top and bottom centrality quintiles increases as PAMAFRO coverage increases for both P. vivax (Tier 1 = 155.36; Tier 2 = 176.22; Tier 3 = 326.08) and P. falciparum (Tier 1 = 48.11; Tier 2 = 95.16; Tier 3 = 139.07). The findings of this study support the shift in current malaria control strategies from targeting specific locations based on malaria metrics to strategies based on connectivity neighborhoods that include influential connected villages.

Indexed as

Malaria, FalciparumMalaria, VivaxRural PopulationHumansIncidenceMalariaPeruPlasmodium falciparumPlasmodium vivax

Identifiers

PMID39495715
PMCPMC11534198

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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.