Published in:
Open Access 01-12-2009 | Research
Three different Plasmodium species show similar patterns of clinical tolerance of malaria infection
Published in: Malaria Journal | Issue 1/2009
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Background
In areas where malaria endemicity is high, many people harbour blood stage parasites without acute febrile illness, complicating the estimation of disease burden from infection data. For Plasmodium falciparum the density of parasitaemia that can be tolerated is low in the youngest children, but reaches a maximum in the age groups at highest risk of infection. There is little data on the age dependence of tolerance in other species of human malaria.
Methods
Parasite densities measured in 24,386 presumptive malaria cases at two local health centres in the Wosera area of Papua New Guinea were compared with the distributions of parasite densities recorded in community surveys in the same area. We then analyse the proportions of cases attributable to each of Plasmodium falciparum, P. vivax, and P. malariae as functions of parasite density and age using a latent class model. These attributable fractions are then used to compute the incidence of attributable disease.
Results
Overall 33.3%, 6.1%, and 0.1% of the presumptive cases were attributable to P. falciparum, P. vivax, and P. malariae respectively. The incidence of attributable disease and parasite density broadly follow similar age patterns. The logarithm of the incidence of acute illness is approximately proportion to the logarithm of the parasite density for all three malaria species, with little age variation in the relationship for P. vivax or P. malariae. P. falciparum shows more age variation in disease incidence at given levels of parasitaemia than the other species.
Conclusion
The similarities between Plasmodium species in the relationships between parasite density and risk of attributable disease are compatible with the hypothesis that pan-specific mechanisms may regulate tolerance to different human Plasmodia. A straightforward mathematical expression might be used to project disease burden from parasite density distributions assessed in community-based parasitological surveys.