---

---

21.04.2026 15:25

Malaria on the rise again – Innovative tools needed to combat it

Anna Hein Presse- und Öffentlichkeitsarbeit
Bernhard-Nocht-Institut für Tropenmedizin

Hamburg, ahead of World Malaria Day on 25 April 2026 – Malaria remains widespread, with case numbers recently rising again. The Bernhard Nocht Institute for Tropical Medicine (BNITM) has been active in malaria research for decades and collaborates with numerous research groups to improve our understanding of the disease and the malaria parasite. The Data Science Center, founded in 2025, is also contributing to this effort by using new bioinformatic analysis tools and artificial intelligence to analyse large volumes of data and reveal complex relationships. This provides an crucial basis to advance malaria research further.

Despite decades of efforts to combat it, malaria remains a major global health threat. According to the World Health Organization’s (WHO) 2025 World Malaria Report, around 282 million cases and approximately 610,000 deaths were recorded worldwide in 2024. Recently, there has been a slight rise in the number of cases again. Children under the age of five in sub-Saharan Africa are particularly affected. While many millions of lives have been saved since 2000, progress is slowing down. Reasons for this include drug and insecticide resistance, the effects of climate change, and weak health systems. The WHO stresses that increased international efforts and innovative approaches are urgently needed to curb malaria in the long term.

“For over 100 years, the Bernhard Nocht Institute for Tropical Medicine has been dedicated to researching and combating malaria,” says Prof. Jürgen May, Chairman of the BNITM Board. “In view of stagnating progress and new challenges, it is clear how important new scientific approaches are. A key factor here is the use of modern data analysis. With our Data Science Center, we are developing bioinformatics tools that help us better understand the malaria parasite and its complex adaptation mechanisms. This opens up new avenues for research and the fight against malaria.”

Outwitting the immune system through transformation

The malaria parasite Plasmodium falciparum spends part of its life cycle in the bloodstream of humans. It invades red blood cells and uses them as a hiding place and site of reproduction. In this process, it attaches special parasite proteins, known as PfEMP1 (Plasmodium falciparum erythrocyte membrane protein 1), to the surface of the red blood cells. While these proteins make the infected cells recognisable to the human immune system, they also fulfil a crucial survival function. Without them, the infected blood cells would enter the spleen and be filtered out due to their altered properties. The PfEMP1 proteins ensure that the infected red blood cells stick to the walls of small blood vessels, thereby evading the spleen’s filtering function. The downside is that immune cells can recognise the infected red blood cells by the PfEMP1 proteins. To survive in humans for a longer period of time despite this, the parasite employs a clever trick: it can swap out the PfEMP1 proteins, much like a quick-change artist who constantly alters his appearance with a new outfit. This means the immune system must continually re-recognise and combat the pathogen. The malaria parasite can swap out the PfEMP1 proteins because its genome encodes around 60 variants of this protein in its var genes. It can therefore switch between many variants, though it produces only one protein variant at a time, which it places on the surface of the red blood cell.

Dr Anna Bachmann, head of a laboratory group at BNITM, is researching the var genes of the malaria parasite. “We are particularly interested in why some infections are mild while others are life-threatening,” says the biologist. “One decisive factor is the PfEMP1 proteins on the surface of infected red blood cells. Depending on which variant the parasite produces, these cells bind to the walls of small blood vessels with varying degrees of strength.” Some variants cause infected blood cells to accumulate in vital organs such as the brain, obstruct blood flow and trigger a strong immune response. This can lead to serious complications. Other variants bind less strongly and are more commonly associated with milder disease progression. “If we understand which variants are found where and when in the body, we can better understand how different disease courses arise,” says Bachmann.

Bioinformatics puzzle

To find out which var genes a malaria parasite actually uses during an infection, Anna Bachmann and her colleagues from the BNITM’s Data Science Center sequence the RNA from blood samples taken from malaria patients. In other words, they analyse the transcripts of the currently active genes. This is where the challenge begins: the malaria parasite’s var genes are among the most complex and variable gene families in existence. They differ greatly between individual parasites and encode many different domains. During sequencing, the researchers do not obtain complete var gene sequences, but only fragments of them. They must then piece these fragments together to form complete var genes, much like solving a jigsaw puzzle. Conventional analysis methods quickly reach their limits here. Bachmann and her team have improved bioinformatic approaches that enable them to correctly assemble the multitude of short sequence fragments and assign them to the individual var genes. In this way, the scientists reveal which variants are active in an infection.

“Gaining a better understanding of which PfEMP1 variants a parasite produces and how they are linked to severe disease progression opens up new possibilities for us,” says Bachmann. “In the long term, such findings could help us to better assess the risk of severe malaria in individual patients, allowing for closer monitoring and more targeted treatment. They also help us to better understand the disease mechanisms of malaria as a whole.”

Digital methods decode the malaria parasite

Prof. Thomas Otto, head the Department Computational Infection Biology at the BNITM’s Data Science Center since September 2025, has been developing bioinformatics tools for malaria research for many years. For example, in earlier work with his team, he analysed the global diversity of Plasmodium falciparum var genes on a large scale for the first time. Using artificial intelligence, Otto and his team have developed a method that assigns var genes to specific groups with different characteristics – information that could otherwise only be obtained through additional, time-consuming and costly methods. This method also works when only parts of the var genes are available, as in genetic analyses carried out by the Bachmann laboratory group. In a further study, his team used modern bioinformatics methods to analyse individual immune cells in malaria patients in detail. This revealed that certain immune cells are particularly strongly activated in affected children and that inflammatory signalling pathways are heightened. This is a key mechanism that helps determine the severity of a malaria infection.

“The genetic diversity of the malaria parasite is enormous. This is precisely what makes it so elusive,” says Otto. “Using bioinformatic methods and artificial intelligence, we can systematically capture this complexity. This gives us a much clearer picture of Plasmodium falciparum than before and offers hope that we can combat malaria in a more effectively in the long term.”

Publications

Andradi-Brown C. et al. A novel computational pipeline for var gene expression augments the discovery of changes in the Plasmodium falciparum transcriptome during transition from in vivo to short-term in vitro culture. eLife 2024. DOI: 10.7554/eLife.87726

Otto T. D. et al. Evolutionary analysis of the most polymorphic gene family in falciparum malaria. Wellcome Open Res. 2019. DOI: 10.12688/wellcomeopenres.15590.1

Pangilinan E. A. et al. upsML: A high-accuracy machine learning classifier for predicting Plasmodium falciparum var gene upstream groups. PLoS One 2026. DOI: 10.1371/journal.pone.0344557

Morang’a C. M. et al. scRNA-seq reveals elevated interferon responses and TNF-α signalling via NF-κB in monocytes in children with uncomplicated malaria. Experimental Biology and Medicine 2025, DOI: 10.3389/ebm.2024.10233

About the Bernhard Nocht Institute for Tropical Medicine (BNITM)

The BNITM is Germany’s largest institution for research, healthcare and teaching in the field of tropical and emerging infectious diseases. Current research priorities include malaria, haemorrhagic fever viruses, neglected tropical diseases (NTDs), immunology, epidemiology and the clinical aspects of tropical infections, as well as the mechanisms of virus transmission by mosquitoes. For handling highly pathogenic viruses and infected insects, the Institute has laboratories of the highest biosafety level (BSL-4) and a biosafety insectarium (BSL-3). In numerous countries of the Global South, the BNITM supports the development of (mobile) laboratory capacities.

---

Wissenschaftliche Ansprechpartner:

Prof. Dr. Jürgen May
Board of Directors (Chair)
Bernhard Nocht Institute for Tropical Medicine
Tel.: +49 40 285380-260
chair@bnitm.de

Dr. Anna Bachmann
Lab Group Leader
Data Science Center
Bernhard Nocht Institute for Tropical Medicine
Tel.: +49 40 285380-439
bachmann@bnitm.de

Prof. Dr. Thomas Otto
Head of Department Computational Infection Biology
Data Science Center
Bernhard Nocht Institute for Tropical Medicine
thomas.otto@bnitm.de

---

---

Merkmale dieser Pressemitteilung:
Journalisten, Studierende, Wissenschaftler, jedermann
Biologie, Informationstechnik, Medizin
überregional
Forschungsergebnisse, Forschungsprojekte
Englisch

---