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

• Published in: Malaria journal Vol. 22; no. 1; p. 38
• Main Authors: Rerolle, Francois, Dantzer, Emily, Phimmakong, Toula, Lover, Andrew, Hongvanthong, Bouasy, Phetsouvanh, Rattanaxay, Marshall, John, Sturrock, Hugh, Bennett, Adam
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 02.02.2023; BioMed Central; BMC
• Subjects: Care and treatment; Child; Diagnosis; Disease transmission; Distribution; Foresters; Forests; Global Positioning System; Global positioning systems; GPS; Health aspects; Heterogeneity; Human diseases; Humans; Laos; Malaria; Malaria - epidemiology; Mobility; Population; Population studies; Probability theory; Questionnaires; Risk; Risk Factors; Sociology; Towns; Tropical diseases; Vector-borne diseases; Vectors; Laos
• ISSN: 1475-2875; 1475-2875
• DOI: 10.1186/s12936-023-04468-8

In 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. Between 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. A 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. This 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.