Because malaria is transmitted by mosquitoes, environmental conditions such as temperature, rainfall and land use affect the transmission potential of malaria. RAI-funded research developed an environmental surveillance database and interactive platform to enable improved targeting of active surveillance and interventions to high-risk areas. The study showed how heterogeneous malaria dynamics are at the local level and that areas with agricultural use near abundant forest were at particularly high risk of transmission.
Operational research funded by RAI aimed to improve our understanding of how environmental conditions influence malaria transmission to improve active surveillance systems. Shoklo Malaria Research Unit, a field-based research unit and health services provider operating along the Thai-Myanmar border, carried the research out in collaboration with the French National Research Institute for Sustainable Development (IRD). The study took place in high malaria burden townships in Kayin State, Eastern Myanmar, where the climate is warm and humid, with seasonal monsoons. However, the technology could be adapted to other endemic areas in the region or even be deployed for other diseases.
The researchers constructed a database to analyse the relationship between environments and landscapes on the one hand, and malaria epidemiology and entomology on the other hand (image below). They developed an interactive platform to allow for visualisation of the data and enable easier use in decision making. Multiple open-source data types were fed into the database and kept updated automatically. The epidemiological data consisted of the weekly incidence of clinical malaria from the village malaria posts and malaria prevalence surveys, while the entomological data included vector diversity and abundance. The researchers analysed Sentinel-2 satellite images to gather data about land use and land cover, including vegetation growth, crops, water bodies, flooding and human modifications such as buildings, logging, cultivation and mining. The land use/land cover data was subsequently validated with field observations. Other environmental data points included in the system were elevation, slope, rainfall and temperature.
The researchers used the database to quantify the risk of malaria persistence or resurgence associated with different types of environments. Among the 1,205 malaria posts examined in the study, only 78 exhibited seasonality in malaria transmission. The researchers classified villages into low-incidence, medium-incidence and high-incidence groups. Low-incidence villages had only sporadic cases or residual transmission, while high-incidence villages experienced persistent high transmission. Medium-incidence villages had rainy season-, cold season-, or outbreak-related peaks in malaria transmission. Overall, malaria dynamics were associated with village proximity to specific landscapes combining abundant forest with patches of land used for agriculture. This association could be driven by increased exposure to mosquitoes while undertaking agricultural practices in combination with increased abundance of mosquitoes due to the proximity to the forest.
This study highlighted the local heterogeneity of malaria and contributes to the identification of conditions favourable to persistence or resurgence. A better understanding of the associations between environmental factors and malaria dynamics could be used to micro-stratify surveillance and control interventions to high-risk zones. Integrating environmental surveillance into early warning systems for malaria may also aid in the identification of subnational areas at risk of resurgence and re-establishment.
Publications
- EASIMES – Environment analysis and surveillance to improve malaria elimination strategies: https://sesstim.univ-amu.fr/projet/m2si