Background
The elimination of malaria is a current goal of the countries comprising the island of Hispaniola; namely, Haiti and the Dominican Republic. This effort is part of an overarching goal by these countries to create a malaria-free zone across the Caribbean by 2025 [
1]. The main malaria-causative parasite in this region is chloroquine-susceptible
Plasmodium falciparum transmitted mainly in Haiti by
Anopheles albimanus mosquitoes [
2]. Overall, malaria transmission in Haiti is low, with approximately 21,000 confirmed cases in 2016, the year when this study’s samples were collected, and a nationwide prevalence of 0.4% [
3,
4]]. The largest number of cases is reported in the southwestern Departments, particularly near coastal areas [
5]. As part of ongoing malaria elimination efforts, surveys have been carried out to understand the overall prevalence and transmission foci of the disease in Haiti.
In addition to the standard epidemiological measures of program progress, genetic tools offer additional understanding of
Plasmodium populations to help in tracking parasite movement and determining the impact of interventions in shrinking the
Plasmodium reservoir. The level of genetic diversity and its distribution could provide insights into parasite transmission and parasite population history. Moreover, genetic variation can be used to uniquely identify parasites that infect individuals in a particular region, establishing clusters of parasite lineages that can be followed over time and space after interventions are applied [
6‐
8].
In this context, the present study assessed the genetic diversity of samples collected during 2016 as a baseline for understanding current population structure in the selected study sites and providing additional information for the future development of a molecular database in Haiti that also includes drug resistance markers. The availability of such a molecular database, with the hope of adding future data collections, may be useful for various programme-related uses, such as tracking parasite movement within the country (e.g., parasite sink and source), evaluation of the efficacy of intervention strategies, and outbreak investigations which help the national programme to apply programme-level applications to progress towards the goal of malaria elimination.
Discussion
In 2016, an estimated 21,998 cases of malaria were reported in Haiti among a population of 10.8 million [
4]. The goal of malaria elimination in Hispaniola in the foreseeable future was supported by Malaria Zero, an alliance of partners including the Haitian Ministry of Health. In the preparatory operational phase of the country’s elimination plan, efforts are focused on identifying areas with ongoing relatively high transmission and risk of infection through improved surveillance, supplemental surveys as well as the development of new approaches to elimination. Once the high transmission areas are identified, targeted interventions such as targeted mass drug administration and indoor residual spraying could be deployed as additional interventions. The use of parasite genomic data could assist in prioritizing and sequencing high transmission areas for the additional interventions.
In addition to the traditional markers of transmission such as epidemiological signals, genetic analysis offers additional information about parasite drug resistance as well as the underlying parasite population structure. Genetic signals can be used for the identification and characterization of the
P. falciparum parasite population, to identify foci of transmission, detect outbreaks, and track parasite movement [
18,
19].
The present study analysed more than 600 samples collected in 2016 from three Departments in Haiti as part of an effort to characterize the parasite population in these regions. Based on its barcodes, Haiti’s parasite population was distinct from those of neighbouring countries in Central and South America, indicating that P. falciparum parasites are not commonly imported from neighbouring countries to Haiti and that the residual ancestral Haitian P. falciparum population is responsible for current transmission of malaria.
The low proportion of polygenomic infections supports the historically relatively low transmission rates reported in the country [
4]; however, the presence of polygenomic infections also indicates the potential for localized regions with increased risk of multiple infectious bites or co-transmission of two parasite types [
20]. The low number of polygenomic infections in this area might also give some indication of a mosquito barrier for co-transmission of multiple infections. However, the lack of reported travel history between sites further supports local transmission with limited outcrossing between parasite types (Additional file
1: Table S1).
The results also revealed similar and low levels of genetic diversity between Grand’Anse and Sud, each with a number of individual barcode-identical nodes. Nippes, however, had reduced genetic diversity compared to those of the other two sites, with an expanded node of barcode-identical parasites. Although the parasites were similar within Haiti, they were distinct from those sampled from South and Central America.
The overall low diversity in this population is suggestive of repeated, long-term inbreeding of parasite types or the expansion of a single clone or limited number of lineages due to differences in reproductive success due to host or vector-related factors, host or vector immune invasion, or other stochastic factors in this region.
While the genetic diversity (pi) was comparable between Sud and Grand’Anse, the number of pairwise differences differed significantly between Departments, with a lower mean number of differences in Grand’Anse (2.1077 ± 0.7743) than that in Sud (3.4645 ± 0.9596), suggesting differences between these parasite populations such as focal transmission (hotspots) or higher levels of crossover of parasite types, respectively.
In addition to aggregate statistical analysis, graph analysis revealed trends in the sample population consistent with long-term population inbreeding. The high proportion of related nodes within samples from Grand’Anse, Nippes, and Sud suggested that residual ancestral Haitian parasites primarily contribute to malaria transmission in this country. However, the limited number of parasites more distantly or not genetically related to these nodes may also themselves be informative. For example, they may represent evidence of local adaptation or evolution of parasites, which may become newly established lineages within the country over time.
The graph property of betweenness centrality revealed only one component [
21]. This property may be more informative in comparisons of additional longitudinal sampling in the same sites, increased numbers of sampling sites nationwide, and graphs of samples from other countries and regions.
The present study used genomic data from a set of SNPs to assess both aggregate data (genetic diversity and pairwise distances) as well as individual data (clonality/unique molecular barcodes, mono/polygenomic proportions, graph characteristics) to assess the characteristics of the parasite population in this region of Haiti. Previous studies have also used different genomic markers (microsatellites) to characterize the population structure of
P. falciparum in Haiti [
5,
22]. These studies reported genetic signals including a low proportion of multiply-infected individuals (polygenomic) individuals compared to single infections (monogenomic), consistent with the findings in the present study. Carter et al
. also observed low levels of population structure; however, they also reported high levels of genetic diversity and a lack of evidence of recent parasite population bottlenecks or increased inbreeding, in contrast to the findings of the present study. However, this difference may be due to differences in the types of markers used (microsatellites versus SNPs in the present study) [
5].
While some of these discordant findings may be due to differences between studies, including study sites, collection years, patient demographics, sampling and genetic markers used, to our knowledge, few studies have reported a very large number of highly related parasites as was observed in Nippes. There are several possible explanations for this finding. First, this could indicate the emergence and spread of a specific parasite type more reproductively successful than other parasites in the population, such as the emergence of drug resistance or reduced drug sensitivity. However, a previous study monitoring drug resistance alleles in these samples [
11] showed that all parasites were wild-type for
Pfcrt, the genetic marker associated with resistance to chloroquine, the drug primarily administered in Haiti [
3]. Additionally, only one mutation
Pfdhfr S108N (associated with antifolate resistance) was found in 47% of the samples. Other unknown parasite characteristics could have contributed to the differences in relative fitness of this parasite type, including those related to human hosts and mosquito vectors. Finally, this finding may simply be a stochastic event in which a single parasite type is propagated throughout the population. Previous studies have made similar observations of clonal types in other countries in which
P. falciparum transmission was reduced to low levels, including Peru, Ecuador, and Thailand [
23‐
25].
The limitations of this study include potential biases due to the passive case detection and the limited number of sites, which prevent generalization of the results even within Departments without additional sampling. Moreover, not all available samples were included in the analysis.
In addition, epidemiological data, particularly longitudinal data, would be useful to place these genetic patterns in context with incidence trends and to differentiate stochastic population effects from those caused by control efforts. Furthermore, evaluation of these samples using technologies other than SNP genotyping of a limited number of markers, including whole-genome sequencing or microsatellite typing, are warranted in future studies to potentially differentiate sub-sets of samples with lower levels of relatedness or shared regions of the genome and those evolving on a shorter evolutionary timescale.
Conclusions
The use of the population genetic approaches relies on the routine collection of parasite genetic data since the discriminatory power of the genotyping method depends on the local epidemiology and transmission setting. Since genetic signals can change over time, continued characterization of P. falciparum genetic diversity throughout Haiti will improve the field’s understanding of the parasite population structure and help to track movement of parasites as malaria elimination efforts progressively reduce ongoing malaria transmission in pursuit of malaria elimination in this region. These data are informative for the development of a molecular database in Haiti that includes drug resistance and other molecular markers from sites nationwide. This database, with the addition of data from future collections, may be useful for program-related activities such as tracking parasite movement within the country that could inform the prioritization and sequence of high transmission areas to be targeted, evaluation of the efficacy of intervention strategies, and outbreak investigations to understand the epidemiology and inform a response.
Population genetic data can inform these targeted control efforts, particularly when resources are limited. For instance, surveillance based on the genetic relatedness of parasites may show the emergence of a highly related or clonal population, as observed in the present study in Nippes. This genetic evidence is suggestive of local transmission, for which vector control efforts would likely be most effective. In contrast, a lack of clonality or the presence of higher proportions of polygenomic samples may suggest importation or a mobile or human population for which mass test-and-treat or other (human) drug-based measured may be warranted.
The selection of appropriate tools for genetic and genomic analysis is also based on the main goals of the national control programmes as well practical concerns such as budget. While declining costs for whole-genome sequencing appear to make this technology more attractive, as it offers ‘all the data’, the infrastructure required to support instruments and to perform analysis remain a hurdle in many settings, especially those interested in near-real-time data analysis for decision making. Furthermore, the whole-genome sequencing analysis tools for polygenomic samples require additional development to provide quantitative data on the number of genomes or the predominant alleles present in a sample. The fine-scale genetic relationships revealed by whole-genome sequencing are best suited for contexts with relatively fewer cases such that reactive case detection and follow-up can reveal more distantly related samples to track parasite movement and inbreeding across regions.
Thus, there remains a role for technologies such as the molecular barcode and microsatellite typing as more general and more easily accessible tools to identify larger-scale changes in parasite populations warranting further investigation and resources for infection control and elimination. Both SNP genotyping as used by the molecular barcode and microsatellite typing offer comparable information, although microsatellites vary on different evolutionary timescales due to their higher rates of mutation [
26] which, depending on the number and identity of the microsatellites, may not be as informative as a genome-wide set of SNPs for programme-level questions regarding changes in parasite population genetics.
These programmatic considerations and uses of parasite genomic information will become more important as the number of malaria cases decline, corresponding with a decrease in genetic diversity, as the country moves towards elimination.
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