Started 2015

SpotMalaria is a new project harnessing genomic technologies to monitor the global evolution of malaria parasites, delivering knowledge that will increase the efficiency of malaria elimination and eradication efforts.

Objectives & Coordination

Malaria control and elimination programmes often face practical obstacles that can be tackled more effectively with information about the parasite population.

Novel laboratory methods and analytical tools make it possible to rapidly sequence and genotype Plasmodium genomes from dried blood spots (DBS) collected from malaria patients – allowing for more comprehensive coverage in malaria endemic areas.

SpotMalaria connects with local and national partners to create sampling and reporting networks to collect large numbers of dried blood spots, using a simple standardised operating procedure (SOP) that is easy to implement in the field.

Our main goal is to provide partners with actionable information to support malaria control interventions. We use state-of-the-art genetic and genomic technologies to rapidly genotype Plasmodium falciparum samples isolated from the finger-prick blood samples.

Our partners receive a Genetic Report Card for each sample that they contribute, showing whether the parasites carry mutations that make them resistant to antimalarial drugs such as artemisinin or its ACT partner drugs. This allows our partners to rapidly detect changes in drug efficacy and to respond to these changes.

Currently, we provide a rapid report on over 20 genetic variations that are relevant to drug resistance in several genes:

  • kelch13 propeller mutations (resistance to artemisinin)
  • pfexo mutation (associated with piperaquine resistance)
  • pfcrt and pfmdr1 mutations (resistance to chloroquine, amodiaquine, mefloquine)
  • pfdhps and pfdhfr mutations (resistance to antifolates)
  • arps10mdr2fdcrt326 mutations (genetic background for kelch13 mutations)

In the next phase ofwork we will also report on the variations which are used to analyse similarity, and to identify expanding strains and the geographic origins of samples. We use a set of highly informative single nucleotide polymorphisms (SNPs) to “barcode” parasites, from which we can estimate complexity of infection. We are also able to determine if an infection comprises additional species of Plasmodium, such as P. vivax, P. malariae, P. ovale, and P. knowlesi.

The next project phase will focus on developing easy to use tools that incorporate genetic report card data in the context of the ever-growing database of genotyped malaria parasites. We are also working on methods that allow expansion of genotyping to global partner sites to speed up genotyping time. Additionally, we are working on genotyping methods for typing a similar set of informative loci in P. vivax DBS samples.

Our partners

In the early phases of this project, we’re working closely with two networks of scientists, clinicians and public health teams who are helping us to refine the product needs. We have expanded our scope and while still working closely with these networks, we now have partners and collaborations from 24 different countries in Asia, Africa, and South America.


GenRe Mekong logoGenRe-Mekong is funded by the Bill & Melinda Gates Foundation to support malaria elimination efforts in the Greater Mekong Subregion, which straddles regions of Cambodia, Vietnam, Laos, Thailand, and South China. GenRe-Mekong aims to supply strategically important information from genetic data to national control programmes and other elimination projects, in the most easily implementable, timely, comprehensive and cost-effective manner possible.

Plasmodium Diversity Network Africa (PDNA)

The prospect of malaria elimination in Africa presents unique challenges. Malaria is more common and acquired immunity can mean that drug pressure is lower, in addition to the non-biological factors, for example social and political factors, that can affect transmission dynamics. While drug resistance is a large problem, there is also a need to determine how parasite genetics both influence and are influenced by these differences across African populations. To answer these questions, we're partnering with researchers from the PDNA to establish important baseline genetic data across as many populations as possible.

Ghansah et al. Monitoring parasite diversity for malaria elimination in sub-Saharan Africa. Science, 2014; 345(6202): 1297-8. DOI: 10.1126/science.1259423.

Read more about the PDNA.

Sampling locations

  • Bangladesh (BD)
  • Cambodia (KH)
  • Ghana (GH)
  • Benin (BJ)
  • Brazil (BR)
  • Cameroon (CM)
  • Colombia (CO)
  • Congo (Democratic Republic of the Congo) (CD)
  • Ethiopia (ET)
  • The Gambia (GM)
  • Guinea (GN)
  • India (IN)
  • Indonesia (ID)
  • Kenya (KE)
  • Laos (LA)
  • Malaysia (MY)
  • Mali (ML)
  • Myanmar (MM)
  • Peru (PE)
  • Senegal (SN)
  • Sudan (SD)
  • Tanzania (TZ)
  • Thailand (TH)
  • Vietnam (VN)


For partners that have publications using data produced by the project we ask that the following statement is included in the acknowledgements.

This publication uses data from the MalariaGEN SpotMalaria Project as described online; the project is coordinated by the MalariaGEN Resource Centre with funding from Wellcome (206194, 090770). The authors would like to thank the staff of Wellcome Sanger Institute Sample Management, Genotyping, Sequencing and Informatics teams for their contribution.

These acknowledgements will be updated when a citable publication is available. If you have any questions please email project contact.