A long neglected world malaria map: Plasmodium vivax endemicity in 2010

Abstract

Background: Current understanding of the spatial epidemiology and geographical distribution of Plasmodium vivax is far less developed than that for P. falciparum, representing a barrier to rational strategies for control and elimination. Here we present the first systematic effort to map the global endemicity of this hitherto neglected parasite.

Methodology and findings: We first updated to the year 2010 our earlier estimate of the geographical limits of P. vivax transmission. Within areas of stable transmission, an assembly of 9,970 geopositioned P. vivax parasite rate (PvPR) surveys collected from 1985 to 2010 were used with a spatiotemporal Bayesian model-based geostatistical approach to estimate endemicity age-standardised to the 1-99 year age range (PvPR(1-99)) within every 5×5 km resolution grid square. The model incorporated data on Duffy negative phenotype frequency to suppress endemicity predictions, particularly in Africa. Endemicity was predicted within a relatively narrow range throughout the endemic world, with the point estimate rarely exceeding 7% PvPR(1-99). The Americas contributed 22% of the global area at risk of P. vivax transmission, but high endemic areas were generally sparsely populated and the region contributed only 6% of the 2.5 billion people at risk (PAR) globally. In Africa, Duffy negativity meant stable transmission was constrained to Madagascar and parts of the Horn, contributing 3.5% of global PAR. Central Asia was home to 82% of global PAR with important high endemic areas coinciding with dense populations particularly in India and Myanmar. South East Asia contained areas of the highest endemicity in Indonesia and Papua New Guinea and contributed 9% of global PAR.

Conclusions and significance: This detailed depiction of spatially varying endemicity is intended to contribute to a much-needed paradigm shift towards geographically stratified and evidence-based planning for P. vivax control and elimination.

Figure 1. Schematic overview of the mapping procedures and methods for Plasmodium vivax endemicity.

Blue boxes describe input data. Orange boxes denote models and experimental procedures; green boxes indicate output data (dashed lines represent intermediate outputs and solid lines final outputs). U/R = urban/rural; UNPP = United Nations Population Prospects. Labels S1-4 denote supplementrary information in Protocols S1, S2, S3, and S4.

Figure 2. The spatial distribution of Plasmodium vivax malaria endemicity in 2010.

Panel A shows the 2010 spatial limits of P. vivax malaria risk defined by PvAPI with further medical intelligence, temperature and aridity masks. Areas were defined as stable (dark grey areas, where PvAPI ≥0.1 per 1,000 pa), unstable (medium grey areas, where PvAPI <0.1 per 1,000 pa) or no risk (light grey, where PvAPI = 0 per 1,000 pa). The community surveys of P. vivax prevalence conducted between January 1985 and June 2010 are plotted. The survey data are presented as a continuum of light green to red (see map legend), with zero-valued surveys shown in white. Panel B shows the MBG point estimates of the annual mean PvPR_1–99 for 2010 within the spatial limits of stable P. vivax malaria transmission, displayed on the same colour scale. Areas within the stable limits in (A) that were predicted with high certainty (>0.9) to have a PvPR_1–99 less than 1% were classed as unstable. Areas in which Duffy negativity gene frequency is predicted to exceed 90% are shown in hatching for additional context.

Figure 3. Uncertainty associated with predictions of Plasmodium vivax endemicity.

Panel A shows the ratio of the posterior inter-quartile range to the posterior mean prediction at each pixel. Large values indicate greater uncertainty: the model predicts a relatively wide range of PvPR_1–99 as being equally plausible given the surrounding data. Conversely, smaller values indicate a tighter range of values have been predicted and, thus, a higher degree of certainty in the prediction. Panel B shows the same index multiplied by the underlying population density and rescaled to 0–1 to correspond to Panel A. Higher values indicate areas with high uncertainty and large populations.