Genomic analyses of malaria have advanced considerably over the past two decades. However, in recent years, the main challenge has shifted from generating sequencing data to analyzing those data in a standardized manner. The lack of interoperable tools and common workflows makes it difficult to compare results and limits their application in public health.

A recent manuscript brings together recommendations from several experts on how to evaluate and document analytical processes, as well as how to standardize their reproducibility. The paper highlights eight key applications or use cases, including surveillance of antimalarial drug resistance, monitoring malaria transmission, identifying the origin of infections, among others.

The authors also review the bioinformatics tools currently available and emphasize the need to develop shared standards for genomic data analysis. In response, they introduce PGEforge, a community-driven platform that brings together tools, tutorials, and reproducible workflows to facilitate collaboration among research groups.

Why does this matter?

Standardizing tools, data formats, and analytical workflows enables the integration and comparison of genomic data generated by different laboratories, regions, and countries. This strengthens scientific collaboration, improves molecular surveillance of Plasmodium drug resistance and transmission, and supports coordinated strategies for malaria control and elimination.

Serological surveillance uses host immune responses to detect evidence of exposure to malaria parasites and to characterize patterns of transmission within populations. By measuring antibodies against Plasmodium antigens, serological approaches can provide information on cumulative exposure, identify areas with ongoing or recent transmission, and reveal transmission patterns that may not be captured through routine case detection alone.

This kind of surveillance is particularly valuable in settings approaching malaria elimination, where parasite prevalence becomes low and infections may be asymptomatic, or below the detection limit of conventional diagnostic methods. Because antibodies can persist after parasite clearance, serological data provide an indirect measure of previous parasite exposure and can help identify residual transmission, evaluate the impact of control interventions, and monitor changes in transmission intensity over time.

Recent advances in serological tools, that include multiplex assays and the identification of antigens associated with recent or cumulative exposure, have improved the ability to characterize malaria transmission. These approaches allow the simultaneous evaluation of antibody responses against multiple Plasmodium targets, providing more detailed information on exposure patterns and supporting surveillance activities in low-transmission settings.

However, as with other methodologies, it's important to consider its limitations. Antibody responses may persist for extended periods after infection, making it difficult to distinguish recent exposure from historical infection. In addition, antibody responses vary according to the parasite species, transmission intensity, and host factors. Therefore, serological evidence alone cannot confirm the presence of active infection and requires integration with molecular, epidemiological data.

Serological surveillance is becoming an increasingly useful component of malaria surveillance systems, particularly in areas moving toward elimination. The integration of serological, genomic, and epidemiological information can improve the identification of residual transmission, support targeted interventions, and strengthen decision-making as programs progress toward malaria elimination.

This month, the Infectious Diseases and Public Health Field School brought together students from around the world with diverse academic backgrounds, ranging from basic sciences, such as biology and molecular biology, to applied disciplines, including epidemiology and medicine.

During this 10-day program, participants engaged in hands-on field research in the Amazon and worked closely with local communities. Based on participants' feedback, this immersive experience broadened their understanding of the research workflow, from sample collection to laboratory analysis, while highlighting the importance of sociocultural factors in One Health research and evidence-based decision-making.

In addition to the field activities, the program included a lecture on developing policy briefs and translating research findings into recommendations that can inform public health decision-makers.