NCT03087214

Human Movement Patterns on the Thailand-Myanmar Border

Completed Last updated 8 January 2019

What this trial tests

trial in Epidemiology in 54 participants. Completed in 17 February 2018.

Timeline

14 March 2017

Primary endpoint
17 February 2018

17 February 2018

Quick facts

Lead sponsor	University of Oxford
Status	Completed
Study type	OBSERVATIONAL
Enrollment	54
Start date	14 March 2017
Primary completion	17 February 2018
Estimated completion	17 February 2018
Sites	1 location across Thailand

Conditions studied

• Epidemiology — all drugs for Epidemiology →

Sponsor

University of Oxford

Who can join

20 and older, any sex, with Epidemiology. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

The epidemiology and ecology of malaria in humans includes complex interactions between human hosts and mosquito vectors. These interactions are spatio-temporal in nature and are heavily dependent on transportation capabilities and seasonal conditions. Where and when infections are acquired is not well understood in the Greater Mekong Subregion (GMS), where there are numerous vectors, many with different behaviours and habitats. For example, many infections appear to be associated with forests or forest edges and some of the most important mosquito vectors in the region are forest dwellers (Obsomer, Defourny, and Coosemans 2007). Interventions that target houses at night-time (e.g. mosquito nets), have had limited success in the GMS, most likely because at least some infections are acquired during the day or outside of the home (Dolan et al. 1993; Luxemburger et al. 1994).

While overall malaria incidence in the region appears to be declining, the disease remains persistent in small subregions, for example along international borders joining Thailand with Myanmar. It will be crucial for elimination efforts to address the persistent malaria in these regions, most likely requiring the use of novel and spatially targeted approaches.

Increasingly, spatial data and analyses are used in disease research (Linard and Tatem 2012; Pybus et al. 2016; Tatem et al. 2012), however most spatial analyses are at aggregate scales, using data from provincial or state levels. More detailed studies have a single geographic reference point per individual in the study, frequently the home (Mosha et al. 2014; Parker et al. 2015). These studies allow researchers to investigate potential clustering of cases within and between houses ("hotspots") (Bejon et al. 2014; Bousema et al. 2012; Mosha et al. 2014). Even these detailed studies typically ignore the spaces in which people spend time outside of their home and where they may acquire infection: schools; places of worship and work; forest camps and temporary shelters. Given that many malaria infections in the GMS are acquired outside of the home, in areas that are not usually mapped, this information is important for developing strategies to prevent transmission and will be crucial for achieving elimination.

Researchers in other substantive areas have already begun mapping the movement patterns of study subjects so that exposure to a variety of environmental exposures outside of the home can be assessed (Matthews and Yang 2013; Vazquez-Prokopec et al. 2010). Early approaches relied on travel surveys or travel diaries, both having bias of unknown magnitude. Modern wearable global positioning satellite (GPS) instruments (loggers or trackers) and geographic information science (GIS) enable detailed mapping and quantification of human movement patterns. Through analysing differences in the movement patterns between humans who do versus those that do not acquire infectious diseases, it may be possible to identify a narrower set of geographic spaces in which disease transmission is occurring. Public health interventions could then target those risk areas.

Most of these detailed studies have been done in economically developed settings and urban environments. Infectious diseases such as malaria remain persistent in resource-poor, rural, and remote areas - the very regions that are least likely to be studied with detailed approaches (Sachs and Malaney 2002).

Publications & conference data

1 peer-reviewed publication reference this trial (live from Europe PMC):

1. Human movement patterns of farmers and forest workers from the Thailand-Myanmar border.
   Tun STT, Min MC, Aguas R, Fornace K, et al · · 2021 · PMID 37990719 · DOI 10.12688/wellcomeopenres.16784.2