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Characterizing local-scale heterogeneity of malaria risk: a case study in Bunkpurugu-Yunyoo district in northern Ghana.

Punam AmratiaPaul PsychasBenjamin AbuakuCollins AhorluJustin MillarSamuel OppongKwadwo KoramDenis Valle
Published in: Malaria journal (2019)
This high variability in malaria prevalence is striking, given that this small area (approximately 30 km × 40 km) was purportedly homogeneous based on country-level spatial analysis, suggesting that fine-scale parasitaemia data might be critical to guide district-level programmatic efforts to prevent and control malaria. Extrapolations results suggest that fine-scale parasitaemia data can be useful for spatial predictions in neighbouring unsampled districts and does not have to be collected every year to aid district-level operations, helping to alleviate concerns regarding the cost of fine-scale data collection.
Keyphrases
  • south africa
  • electronic health record
  • air pollution
  • plasmodium falciparum
  • big data
  • risk factors
  • deep learning