Within-household clustering of genetically related Plasmodium falciparum infections in a moderate transmission area of Uganda.

BACKGROUND

Evaluation of genetic relatedness of malaria parasites is a useful tool for understanding transmission patterns, but patterns are not easily detectable in areas with moderate to high malaria transmission. To evaluate the feasibility of detecting genetic relatedness in a moderate malaria transmission setting, relatedness of Plasmodium falciparum infections was measured in cohort participants from randomly selected households in the Kihihi sub-county of Uganda (annual entomological inoculation rate of 27 infectious bites per person).

METHODS

All infections detected via microscopy or Plasmodium-specific loop mediated isothermal amplification from passive and active case detection during August 2011-March 2012 were genotyped at 26 microsatellite loci, providing data for 349 samples from 230 participants living in 80 households. Pairwise genetic relatedness was calculated using identity by state (IBS).

RESULTS

As expected, genetic diversity was high (mean heterozygosity [H] = 0.73), and the majority (76.5 %) of samples were polyclonal. Despite the high genetic diversity, fine-scale population structure was detectable, with significant spatiotemporal clustering of highly related infections. Although the difference in malaria incidence between households at higher (mean 1127 metres) versus lower elevation (mean 1015 metres) was modest (1.4 malaria cases per person-year vs. 1.9 per person-year, respectively), there was a significant difference in multiplicity of infection (2.2 vs. 2.6, p = 0.008) and, more strikingly, a higher proportion of highly related infections within households (6.3 % vs. 0.9 %, p = 0.0005) at higher elevation compared to lower elevation.

CONCLUSIONS

Genetic data from a relatively small number of diverse, multiallelic loci reflected fine scale patterns of malaria transmission. Given the increasing interest in applying genetic data to augment malaria surveillance, this study provides evidence that genetic data can be used to inform transmission patterns at local spatial scales even in moderate transmission areas.