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High sensitivity detection of Plasmodium species reveals positive correlations between infections of different species, shifts in age distribution and reduced local variation in Papua New Guinea

Ivo Mueller1 email, Simone Widmer2 email, Daniela Michel2 email, Seri Maraga1 email, David T McNamara3 email, Benson Kiniboro1 email, Albert Sie1 email, Thomas A Smith2 email and Peter A Zimmerman3 email

Papua New Guinea Institute of Medical Research, Goroka, PO Box 60, EHP 441, Papua New Guinea

Swiss Tropical Institute, Department of Medical Parasitology and Infection Biology, and Department of Public Health and Epidemiology, Socinstrasse 57, PO Box, CH-4002 Basel, Switzerland

Center for Global Health & Diseases, Case Western Reserve University, School of Medicine, Wolstein Research Building, 10900 Euclid Avenue, Cleveland, Ohio, 44106-7286, USA

author email corresponding author email

Malaria Journal 2009, 8:41doi:10.1186/1475-2875-8-41

Published: 11 March 2009

Abstract

Background

When diagnosed by standard light microscopy (LM), malaria prevalence can vary significantly between sites, even at local scale, and mixed species infections are consistently less common than expect in areas co-endemic for Plasmodium falciparum, Plasmodium vivax and Plasmodium malariae. The development of a high-throughput molecular species diagnostic assay now enables routine PCR-based surveillance of malaria infections in large field and intervention studies, and improves resolution of species distribution within and between communities.

Methods

This study reports differences in the prevalence of infections with all four human malarial species and of mixed infections as diagnosed by LM and post-PCR ligase detection reaction – fluorescent microsphere (LDR-FMA) assay in 15 villages in the central Sepik area of Papua New Guinea.

Results

Significantly higher rates of infection by P. falciparum, P. vivax, P. malariae and Plasmodium ovale were observed in LDR-FMA compared to LM diagnosis (p < 0.001). Increases were particularly pronounced for P. malariae (3.9% vs 13.4%) and P. ovale (0.0% vs 4.8%). In contrast to LM diagnosis, which suggested a significant deficit of mixed species infections, a significant excess of mixed infections over expectation was detected by LDR-FMA (p < 0.001). Age of peak prevalence shifted to older age groups in LDR-FMA diagnosed infections for P. falciparum (LM: 7–9 yrs 47.5%, LDR-FMA: 10–19 yrs 74.2%) and P. vivax (LM: 4–6 yrs 24.2%, LDR-FMA: 7–9 yrs 50.9%) but not P. malariae infections (10–19 yrs, LM: 7.7% LDR-FMA: 21.6%). Significant geographical variation in prevalence was found for all species (except for LM-diagnosed P. falciparum), with the extent of this variation greater in LDR-FMA than LM diagnosed infections (overall, 84.4% vs. 37.6%). Insecticide-treated bednet (ITN) coverage was also the dominant factor linked to geographical differences in Plasmodium species infection prevalence explaining between 60.6% – 74.5% of this variation for LDR-FMA and 81.8% – 90.0% for LM (except P. falciparum), respectively.

Conclusion

The present study demonstrates that application of molecular diagnosis reveals patterns of malaria risk that are significantly different from those obtained by standard LM. Results provide insight relevant to design of malaria control and eradication strategies.


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