Epidemiology Clinical Trial
Official title:
Movement and Migration Patterns Among a Cohort of Villagers From the Thailand-Myanmar Border
NCT number | NCT03087214 |
Other study ID # | SMRU1607 |
Secondary ID | |
Status | Completed |
Phase | |
First received | |
Last updated | |
Start date | March 14, 2017 |
Est. completion date | February 17, 2018 |
Verified date | January 2019 |
Source | University of Oxford |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
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).
Status | Completed |
Enrollment | 54 |
Est. completion date | February 17, 2018 |
Est. primary completion date | February 17, 2018 |
Accepts healthy volunteers | |
Gender | All |
Age group | 20 Years and older |
Eligibility |
Inclusion Criteria: - The participants are Karen or Burmese ethnic group - Participants must be above 20 years of age - Capable of keeping track of the device - Walking beyond village boundaries - Willing to consent to the study Exclusion Criteria: Individuals who do not meet inclusion criteria. |
Country | Name | City | State |
---|---|---|---|
Thailand | Shoklo Malaria Research Unit | Mae Sot | Tak |
Lead Sponsor | Collaborator |
---|---|
University of Oxford |
Thailand,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Time-stamped locations | A series of spatial data sets that can then be mapped and analyzed | 1 year | |
Primary | The latitude and longitude of the GPS logging reading. | The GPS logging devices will automatically take a reading every 30 minutes. | 1 year | |
Primary | The elevation of the GPS logging reading. | The GPS logging devices will automatically take a reading every 30 minutes. | 1 year | |
Primary | Date and time of the GPS logging reading. | The GPS logging devices will automatically take a reading every 30 minutes. | 1 year | |
Primary | Acceptability among participants about carrying the GPS logging device during | Participants will also be interviewed throughout the study period and one of the research questions | 1 year | |
Secondary | Questionnaires | Participants' reported travel histories comparing them to the GPS logger data. | 1 year |
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