Plasmodium vivax Transmission in Africa

Abstract

Malaria in sub-Saharan Africa has historically been almost exclusively attributed to Plasmodium falciparum (Pf). Current diagnostic and surveillance systems in much of sub-Saharan Africa are not designed to identify or report non-Pf human malaria infections accurately, resulting in a dearth of routine epidemiological data about their significance. The high prevalence of Duffy negativity provided a rationale for excluding the possibility of Plasmodium vivax (Pv) transmission. However, review of varied evidence sources including traveller infections, community prevalence surveys, local clinical case reports, entomological and serological studies contradicts this viewpoint. Here, these data reports are weighted in a unified framework to reflect the strength of evidence of indigenous Pv transmission in terms of diagnostic specificity, size of individual reports and corroboration between evidence sources. Direct evidence was reported from 21 of the 47 malaria-endemic countries studied, while 42 countries were attributed with infections of visiting travellers. Overall, moderate to conclusive evidence of transmission was available from 18 countries, distributed across all parts of the continent. Approximately 86.6 million Duffy positive hosts were at risk of infection in Africa in 2015. Analysis of the mechanisms sustaining Pv transmission across this continent of low frequency of susceptible hosts found that reports of Pv prevalence were consistent with transmission being potentially limited to Duffy positive populations. Finally, reports of apparent Duffy-independent transmission are discussed. While Pv is evidently not a major malaria parasite across most of sub-Saharan Africa, the evidence presented here highlights its widespread low-level endemicity. An increased awareness of Pv as a potential malaria parasite, coupled with policy shifts towards species-specific diagnostics and reporting, will allow a robust assessment of the public health significance of Pv, as well as the other neglected non-Pf parasites, which are currently invisible to most public health authorities in Africa, but which can cause severe clinical illness and require specific control interventions.

Fig 1. Data assembly procedure.

The geographic extent of the analysis included the 47 malaria-endemic countries of sub-Saharan Africa: all WHO African Regional Office countries except Algeria (0 indigenous cases in 2013 [29]), but including Djibouti, the Republic of Sudan and Somalia. ECDC: European Centre for Disease Prevention and Control. *Prevalence survey analyses were limited to those with sample size ≥50.

Fig 2. Weighting of the different data types at Admin1 level.

Ranks refer to the relative strength of the evidence as an indicator of ongoing Pv transmission in an area. *The total number of returning traveller infections from each country was divided between the number of Admin1 regions per country. If there was less than 1 reported infection per Admin1, the weighting score was 0.5. Note that because the traveller infections data were retrospective and not sub-nationally specific, it was not possible to distinguish the Republic of Sudan from South Sudan, thus results were considered for Sudan pre-separation and the same score allocated to both countries based on the overall data.

Fig 3. The evidence base of Pv occurrence in sub-Saharan Africa.

All points represent a positive diagnosis of Pv. See S1–S3 Tables for original data.

Fig 4. Summaries of the overall category of evidence available for each data type at the Admin1 level.

Evidence categories are defined in Fig 3. Panel A represents evidence of Pv from infected vectors, Panel B sero-positivity, Panel C Pv community prevalence surveys, Panel D molecularly-diagnosed clinical cases, Panel E microscopy-diagnosed clinical cases and Panel F annual Pv incidence data. See S1–S3 Tables for original data.

Fig 5. Traveller infections mapped to probable country of infection.

The relative contribution of Pf and Pv infections is reflected in each pie chart (with charts sized by overall number of infections, transformed on a square-root scale). Numbers indicate the number of exported Pv infections identified by this study (corresponding to the dark blue segment of the pie chart). Infections date from 2000 to 2014; data sources and countries of importation are listed in Fig 1. Where species-specific information was available for mixed infections, these were considered to be separate infections, so a single individual would have contributed two or more infections to the total count of malaria parasite infections. Returning patients for whom a single country of probable infection could not be determined were excluded.

Fig 6. Composite map of the evidence of Pv transmission in sub-Saharan Africa, summarised to the Admin1 unit.

Fig 7. Spatial map of the distribution of the PvPAR.

The map resolution is 5 x 5 km, and the 3-dimensional scale was square-root transformed to allow plotting.

Fig 8. Characteristics of the PvPR dataset (n = 1,546).

Only surveys of ≥50 individuals are included, and PvPR values are adjusted to the 1–99 age range. Panel A shows the PvPR values, their spatial distribution and the diagnostic method used for each survey. Panel B is a scatterplot of the relationship between the proportion of the population at risk of Pv infection (represented by the proportion of the population Fy+) and the proportion of individuals infected with Pv (PvPR).

Fig 9. Published observations of molecularly-confirmed Pv infections in Duffy negative individuals across Africa (Fy-Pv+).

Yellow stars represent the number of Fy-Pv+ infections identified at each study location (including some as mixed infections with other Plasmodium species). Original citations and further details are given in S4 Table. Pie-charts summarise the predicted prevalence of the Duffy phenotypes in each country [41]. The background map is the predicted frequency of Duffy negativity [4]. Further Fy-Pv+ infections from western Kenya have been reported [42], but the diagnoses were inconclusive, so are not included in this map.

Fig 10. Observations of Pv across Africa in relation to the distributions of hypothesised ape reservoir hosts [63] (based on the IUCN Red List of Threatened Species distribution maps [66]) and regions of highest frequencies of Duffy negativity (Fy(a-b-)) [4].