AfriCam Madagascar
As part of PREACTS’ AfriCam project, Mauricianot Randriamihaja is working on the design of a spatial modeling system that can prevent mosquito outbreaks, complementing community surveillance in Madagascar.
Mauricianot Randriamihaja, a PhD student from Madagascar, specializes in spatial modeling. He is currently completing his thesis entitled « Application of spatial modeling to improve community surveillance of infectious diseases in a rural district of Madagascar ». His research work, integrated into AfriCam as part of the partnership with the NGO Pivot, is supervised by Andres Garchitorena (PREACTS pilot for IRD) and Michelle Evans (Pivot). He will defend his thesis next December.
Using a system that combines field surveys, satellite images, and algorithms, his work facilitates decision-making to optimize active surveillance programs at the community level and reduce mosquito-larval habitats in the Ifanadiana district in southeastern Madagascar, thereby preventing the risk of malaria and dengue fever within communities.
PREZODE: What is the background of your research?
MauricianotRandriamihaja: The Ifanadiana region is particularly affected by malaria and dengue fever: the climate is very conducive to rice cultivation, and there are two harvests per year—in March/April and September/October. These seasons coincide with heavy rains, which are particularly intense in this part of the island. Flooding, especially in rice fields, encourages the proliferation of mosquitoes, which find suitable breeding grounds there; their population threatens farmers, rice growers, and neighboring communities with infectious vector-borne diseases.
With climate change, rising temperatures, and increased frequency and intensity of rainfall, the regularity of the seasons and episodes of field flooding are also being disrupted… Mosquito behavior is changing, and they are becoming more resistant to insecticides. It is therefore difficult to know when they will proliferate. The risks of malaria and dengue transmission are further increased by human activities, such as the use of unprotected water resources, the lack of drainage of stagnant water, and inadequate or non-existent use of mosquito nets (sometimes converted into fishing nets).
What does your research work entail?
My work is about spatial modeling. It integrates diverse fields of study, encompassing data collection, organization, and interpretation. For this modeling, we first conducted a large-scale monitoring of flooded rice fields using a participatory mapping approach of the district. The project encompasses 17,000 rice fields, 20,000 km of footpaths, and 100,000 buildings. This enabled us to perform an integrated spatial analysis, which entailed cross-referencing environmental, demographic, socio-economic, and serological data to identify the factors associated with the emergence of infectious diseases.
The second phase was the detection and modeling of vector habitats using satellite radar images. When combined with field data, this technology empowers us to create detailed models of flooded areas conducive to mosquito breeding. This imaging technique allows for visibility through cloud cover. Conventional imaging techniques are unable to differentiate between open water areas and young rice fields, where larvae develop.
What developments are we all looking forward to?
Combining this mapping with satellite data enables spatial modeling: we can predict areas at risk of flooding that are likely to be heavily infected, and alert communities ahead of mosquito larval development episodes. This technique optimizes surveillance and community action. The use of larvicides in rice fields is thus more rational, targeted, and effective.
How does your project align with PREZODE’s objectives?
At present, the project’s primary focus is on the Ifanadiana district in Madagascar, an area spanning 3,971 square kilometers, with over 17,000 rice fields, where malaria is prevalent. The surveillance system can be replicated and deployed on a larger scale to prevent certain mosquito-borne zoonoses. It is particularly well-suited for isolated regions, especially where irrigated agriculture plays a significant role in transmission and populations are significantly distant from roads and healthcare centers. Please find below the relevant details for your records.
This initiative contributes to enhancing healthcare services in rural areas. The information collected by this alert system is accessible via web applications, available to health workers and vector control operators, who can alert the population.
Mauricianot has already published his study in several publications: