Evidence map›Paper›PMID 36732769›Full record

ArticleMalaria journal2023

Characterizing mobility patterns of forest goers in southern Lao PDR using GPS loggers.

Francois Rerolle, Emily Dantzer, Toula Phimmakong, Andrew Lover, Bouasy Hongvanthong, Rattanaxay Phetsouvanh, John Marshall, Hugh Sturrock, Adam Bennett

Abstract 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 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
  2. Forest-Going as a Risk Factor for Confirmed Malaria in Champasak Province, Lao PDR: A Case-Control Study.International journal of environmental research and public health · 2024
    Article
  3. Article
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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

9 authors.

Francois RerolleMalaria Elimination Initiative, The Global Health Group, University of California, San Francisco, CA, USA. francois.rerolle@ucsf.edu.
Emily DantzerMalaria Elimination Initiative, The Global Health Group, University of California, San Francisco, CA, USA.
Toula PhimmakongCenter for Malariology, Parasitology and Entomology, Ministry of Health, Vientiane, Lao People's Democratic Republic.
Andrew LoverDepartment of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA, USA.
Bouasy HongvanthongCenter for Malariology, Parasitology and Entomology, Ministry of Health, Vientiane, Lao People's Democratic Republic.
Rattanaxay PhetsouvanhCenter for Malariology, Parasitology and Entomology, Ministry of Health, Vientiane, Lao People's Democratic Republic.
John MarshallDivisions of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, CA, USA.
Hugh SturrockMalaria Elimination Initiative, The Global Health Group, University of California, San Francisco, CA, USA.
Adam BennettMalaria Elimination Initiative, The Global Health Group, University of California, San Francisco, CA, USA.

Funding

Bill and Melinda Gates Foundation OPP1116450
6 · The paper itself

Abstract

backgroundIn the Greater Mekong Subregion (GMS), forest-going populations are considered high-risk populations for malaria and are increasingly targeted by national control programmes' elimination efforts. A better understanding of forest-going populations' mobility patterns and risk associated with specific types of forest-going trips is necessary for countries in the GMS to achieve their objective of eliminating malaria by 2030.

methodsBetween March and November 2018, as part of a focal test and treat intervention (FTAT), 2,904 forest-goers were recruited in southern Lao PDR. A subset of forest-goers carried an "i-Got-U" GPS logger for roughly 2 months, configured to collect GPS coordinates every 15 to 30 min. The utilization distribution (UD) surface around each GPS trajectory was used to extract trips to the forest and forest-fringes. Trips with shared mobility characteristics in terms of duration, timing and forest penetration were identified by a hierarchical clustering algorithm. Then, clusters of trips with increased exposure to dominant malaria vectors in the region were further classified as high-risk. Finally, gradient boosting trees were used to assess which of the forest-goers' socio-demographic and behavioural characteristics best predicted their likelihood to engage in such high-risk trips.

resultsA total of 122 forest-goers accepted carrying a GPS logger resulting in the collection of 803 trips to the forest or forest-fringes. Six clusters of trips emerged, helping to classify 385 (48%) trips with increased exposure to malaria vectors based on high forest penetration and whether the trip happened overnight. Age, outdoor sleeping structures and number of children were the best predictors of forest-goers' probability of engaging in high-risk trips. The probability of engaging in high-risk trips was high (~ 33%) in all strata of the forest-going population.

conclusionThis study characterized the heterogeneity within the mobility patterns of forest-goers and attempted to further segment their role in malaria transmission in southern Lao People's Democratic Republic (PDR). National control programmes across the region can leverage these results to tailor their interventions and messaging to high-risk populations and accelerate malaria elimination.

Indexed as

MalariaChildForestsHumansLaosRisk Factors

Identifiers

PMID36732769
PMCPMC9893532

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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.