Malaria Vector Genomic Surveillance
Genomic Surveillance Unit
Archive Page
This page is maintained as a historical record and is no longer being updated.
About us
We were data scientists and software developers with a strong interest in entomology and genomics. We were passionate about making genomic data accessible and usable by public health partners around the world. We primarily used Python, Jupyter notebooks, and Google CoLab cloud computing to manipulate malaria vector data.
Our work
Malaria vector control, particularly in Africa, was going through a period of major change. New insecticides were being brought into use through a new generation of long-lasting insecticide-treated nets (LLINs) and indoor residual spraying (IRS) products. These new tools were effective, but past experience suggested that mosquitoes would evolve resistance and, without preemptive action, these tools would not remain effective for long.
To keep on top of insecticide resistance, we built data products that track genetic changes in Anopheles mosquito populations — the mosquitoes which transmit malaria — in Africa and Southeast Asia.
The most recent versions of the largest Anopheles dataset — for the An. gambiae complex of species in Africa — contained more than 13,000 whole genome sequences from samples collected by partners working in 33 institutions across 25 countries. These are were continually updated, with regular new data releases.
The mosquito genome contains hundreds of millions of bases. That makes it about ten times larger than the malaria parasite genome, and ten times smaller than the human genome. This presents a unique set of challenges when it comes to collecting, storing, and analysing malaria vector data. To make the data more accessible, we created a set of cloud-native software tools, coded in Python, that allow anyone with an internet connection and a laptop to access and analyse the data. In association with the Pan-African Mosquito Control Association (PAMCA), we also developed a set of online training workshops and established a bioinformatics fellowship program to help to build genomic surveillance capacity in Africa.
Another major challenge in vector control is that, in many cases, public health authorities don’t have a clear idea of which species are present and transmitting malaria. This is especially true in Southeast Asia, where mosquito species diversity is very high. The ANOSPP project focused on mosquito diversity in Africa, whereas the Vector Observatory – Asia focused on Asia.
Our people
Previous group lead
Dr Alistair Miles
Malaria Vector Surveillance Lead