Malaria Exposure in Ann Township, Myanmar, as a Function of Land Cover and Land Use: Combining Satellite Earth Observations and Field Surveys

Abstract

Despite progress toward malaria elimination in the Greater Mekong Subregion, challenges remain owing to the emergence of drug resistance and the persistence of focal transmission reservoirs. Malaria transmission foci in Myanmar are heterogeneous and complex, and many remaining infections are clinically silent, rendering them invisible to routine monitoring. The goal of this research is to define criteria for easy-to-implement methodologies, not reliant on routine monitoring, that can increase the efficiency of targeted malaria elimination strategies. Studies have shown relationships between malaria risk and land cover and land use (LCLU), which can be mapped using remote sensing methodologies. Here we aim to explain malaria risk as a function of LCLU for five rural villages in Myanmar's Rakhine State. Malaria prevalence and incidence data were analyzed through logistic regression with a land use survey of 1,000 participants and a 30-m land cover map. Malaria prevalence per village ranged from 5% to 20% with the overwhelming majority of cases being subclinical. Villages with high forest cover were associated with increased risk of malaria, even for villagers who did not report visits to forests. Villagers living near croplands experienced decreased malaria risk unless they were directly engaged in farm work. Finally, land cover change (specifically, natural forest loss) appeared to be a substantial contributor to malaria risk in the region, although this was not confirmed through sensitivity analyses. Overall, this study demonstrates that remotely sensed data contextualized with field survey data can be used to inform critical targeting strategies in support of malaria elimination. Plain Language Summary While much progress has been made in recent years toward eliminating malaria in Myanmar, full elimination remains a challenge that is amplified by the emerging of drug-resistant malaria parasites. The lack of clinical symptoms in many people infected with malaria makes it extremely challenging to find the remaining reservoirs of the disease in the country. Previous studies identified some linkages between the prevalence of malaria and land cover and land use (LCLU) patterns. Satellite monitoring of LCLU could thus help identify potential areas where malaria elimination activities should be deployed. In this study, blood samples and surveys on land use activities (farming, visiting forests, etc.), collected in five villages in Myanmar's Rakhine State, were used to establish and describe the relationship between satellite-observed LCLU patterns surrounding the village and malaria prevalence. Results indicate that villages surrounded by lands with high amounts of forest cover were strongly associated with increased risk of malaria, even for villagers who did not report frequent visits to forested lands. Overall, this study demonstrates that satellite imagery data can be an important tool in support of targeted malaria elimination.

Temporal Dynamics of Subclinical Malaria in Different Transmission Zones of Myanmar

“…The regression analyses in this study support previous work showing that in this region, targeting certain groups based on older age, male gender, high-risk occupation, and frequent engagement in other outdoor activities, like collecting water and time spent in the forest, may improve the effectiveness of these screen-and-treat strategies. The high heterogeneity seen in prevalence of subclinical malaria even in adjacent villages is consistent with previous research, 14 and suggests that elimination efforts should target specific foci within geographical units such as at the township level.…”

“…Previous studies from the region have identified risk factors for subclinical malaria infection, including age (young adults) and male gender, 6 , 13 as well as occupations that involve outdoor exposure, such as farming and logging. 13 , 14 In preparation for a larger cohort study aiming to measure the transmission potential of subclinical malaria, we evaluated the dynamics of subclinical malaria over a period of 6–12 weeks, using weekly or biweekly follow-up, respectively, at three epidemiologically distinct sites in Myanmar. The aims were to determine whether low-density, subclinical malaria infections persisted over time and could be reliably detected using usPCR with successive testing, and whether certain demographic characteristics are associated with the prevalence and persistence of infection.…”

A Disease Control-Oriented Land Cover Land Use Map for Myanmar

“…Previous work has established some linkages between the LCLU types and malaria risks. Specifically, deforestation and agricultural development have been shown to influence mosquito species abundance and malaria incidence through changes to the ecology of vector species as well as the nature and stage of the agricultural development determining patterns of human contact with vectors [ 7 , 15 , 16 ].…”

“…In addition to capturing and highlighting the areas where malaria exposure and transmission are more likely, LCLU maps could also be of great importance for malaria treatment efforts because they could provide information about the distribution of human settlements at large spatial scales. This is especially crucial for rural villages with low economic well-being and limited access to care [ 16 , 17 ]. However, creating LCLU maps that offer meaningful information about village distribution across the country is challenging because (1) it requires the mapping to be implemented at a 30-meter or higher resolution to ensure the successful mapping of remote villages (according to our personal observations, many remote villages in Myanmar are fairly small in extent and consist of a few buildings with small footprints), which are known to serve as the remnant pools of malaria [ 18 ], and (2) villages are quite similar to many bare ground features (e.g., riverbanks, bare mountain tops) in terms of their spectral signature.…”

A GeoHealth Call to Action: Moving Beyond Identifying Environmental Injustices to Co‐Creating Solutions

“…The inclusion and elevation of community priorities is a key principle of the field of Environmental Justice. As has been shown in many scientific and research contexts, the inclusion of historically marginalized communities in geoscience research results in higher quality research and broad, critical, and timely societal impacts (Ballard & Huntsinger, 2006; Bonney et al., 2009; Dalbotten et al., 2017; Danielsen et al., 2014; Harris et al., 2021; Hoffman‐Hall et al., 2020; Moysey, 2011; Pierotti & Wildcat, 2000; Price & Lee, 2013; Ramirez‐Andreotta et al., 2014, 2016; Shirk et al., 2012; Smythe et al., 2010; Southern et al., 2022).…”