NEW: Dominic Kwiatkowski’s final paper... more
1168 Genomic surveillance of Plasmodium falciparum in the Kassena-Nankana Districts, Ghana

Location: Ghana (GH).


In the Kassena-Nankana Districts (KNDs) malaria is highly endemic with marked seasonal variation in transmission intensity. The high transmission season coincides with the rainy season, which is from July to October and low transmission season is from November through June. Malaria accounts for about 40% of out-patient attendance in health facilities across these districts. About 97% of malaria infections are caused by Plasmodium falciparum whilst 3% are mixed infections of P. falciparum and Plasmodium malariae. The dominant malaria vector in this area is Anopheles gambiae (80%) with secondary transmission by Anopheles funestus (20%). Previous case-control studies of severe malaria reported severe malarial anaemia as the most prevalent phenotype in this region. However, recent hospital data shows an upsurge in cerebral malaria cases. This has been attributed to interventions such as Indoor Residual Spraying, which was conducted across this area in 2014 and the effect of long lasting insecticidal bednets. The current alternative first-line treatments for uncomplicated malaria in Ghana include Artesunate-Amodiaquine, Artemether-Lumefantrine and Dihydroartemisinin-Piperaquine. Several antimalarial drug trials have previously been conducted in the KNDs. However, more recently malaria parasite surveillance studies have been carried out across these locations in the KNDs. Therefore, the SpotMalaria project is an opportunity to build upon these surveillance studies and expand existing malaria surveillance datasets from the four selected locations in the KNDs. The expanded data will then offer the opportunity for location specific profiling of anti-malarial drug resistance. In addition, the data can be used to track seasonal profiles of anti-malarial drug resistance genes in this area of marked seasonality in malaria transmission. Locations have been carefully chosen to enable the analysis of markers of geographical differentiation.