Malaria in Pregnancy: integrative assessment of vector–host– pathogen dynamics in an endemic area of Western Kenya

Cooperating countries: Kenya and Austria

Coordinating institution: Medical University of Vienna, Edwin Kniha edwin.kniha@meduniwien.ac.at 

Partner institutions: Egerton University, Maseno University

Project duration: 

Budget: EUR 38.750

Abstract: 

Malaria remains a major public health threat in sub-Saharan Africa, disproportionately affecting pregnant women whose altered immunity increases susceptibility to Plasmodium infection, severe disease, and adverse birth outcomes. Placental malaria contributes to maternal anemia, fetal growth restriction, preterm delivery, and increased neonatal mortality. Western Kenya continues to experience high transmission, particularly in Busia County, where efficient vector species sustain perennial malaria risk. Persistent vector populations, insecticide resistance, environmental change, and gaps in preventive measures further elevate vulnerability among pregnant women.

Understanding malaria risk during pregnancy requires integrating clinical and entomological data that capture mosquito species composition, infection rates, feeding patterns, and seasonal dynamics. Household-level mosquito collections from pregnant women provide an opportunity to link fine-scale exposure patterns with individual clinical outcomes. A recently described mosquito symbiont, Microsporidia MB, blocks Plasmodium development in Anopheles mosquitoes and represents a promising biological control candidate. However, its prevalence, ecological determinants, and seasonal dynamics in high-transmission settings remain poorly characterized, and its potential influence on infection risk among pregnant women is unknown.

This project goal is to establish the ecological and epidemiological interactions between Microsporidia MB, Plasmodium infection, mosquito feeding behavior, and maternal health indicators in western Kenya. We will conduct entomological surveillance in households of pregnant women and determine Microsporidia MB prevalence, Plasmodium infection, mosquito species composition, and blood-meal sources using molecular tools, alongside development of a duplex qPCR assay for simultaneous detection of Plasmodium and Microsporidia MB. In parallel, we will assess relationships between malaria infection, hemoglobin, and micronutrient biomarkers by gravidity. Finally, we will analyze household- and community-level associations between MB presence, mosquito infection rates, maternal malaria risk, and nutritional status using spatial, mixed-effects, and machinelearning models. 

By linking ecological processes, vector biology, maternal health, and microbial symbionts within a One Health framework, the study will generate novel insights into natural transmission-blocking mechanisms and their potential for future interventions.