Genetic surveillance has the potential to provide useful information for malaria transmission epidemiology, particularly in the elimination context where detecting ongoing local transmission and identifying the origin of imported infections may be relevant. Using an extended panel of microsatellite markers, our results reveal importation of diverse parasite populations from different regions of sub-Saharan Africa to Jiangsu province of China. Reassuringly, and consistent with epidemiology inferred from the travel history of cases, we found no evidence for local transmission – nearly all closely related infections were identified in people who traveled to the same or neighboring country near the same time. While the absence of local transmission has been well documented in Jiangsu, these results highlight the potential utility of related methods for surveillance in areas where the lack of transmission is less clear, e.g. in areas which have only recently achieved elimination and/or where surveillance systems are not as robust. Although the receptivity of P. falciparum malaria is limited in Jiangsu province[11, 30], persistent importation could result in a reemergence of local transmission, highlighting the need to sustain a stringent surveillance efforts in receptive areas of China[32, 33].
Chinese travelers importing malaria spent an average of a year in the respective African countries, and of those 47% reported symptomatic malaria episodes during their stay. Despite the duration of stay and the risk of infections, genetic characterization of imported cases revealed a limited number of genotypes per imported infection despite the high diversity of genotypes in the local parasite populations, suggesting limited superinfection of the travelers. In contrast to reports characterizing the diversity of locally detected cases, the average number of distinct genotypes per infection did not differ among cases imported from different regions of sub-Saharan Africa[17, 34, 35].
Due to the physical proximity of the newly designed markers with the existing loci, we expected strong pairwise linkage disequilibrium between flanking microsatellites, however the pairwise LD was very low even among loci within 1000 bp on the same chromosome, suggesting very high rate of recombination in P. falciparum parasites in sub-Saharan Africa as described previously[36, 37]. This observation is further evidenced by high genetic diversity in imported infection, similar to the level reported from local parasite populations[34, 38, 39] and the lack of detectable geographic clusters. Furthermore, imported infections exhibited significant differentiation only in those imported from East vs. West and East vs. Southern Africa countries, consistent with previous reports[17, 37].
Multi-locus genotyping data, combined with statistical methods of inference, have been employed to address key questions of genetic identity and population membership, even when the overall level of genetic differentiation among populations is low[29, 40–42]. Such methods have been commonly used to assess temporal and spatial clustering of P. falciparum as well as P. vivax populations at a continental as well as village levels[15, 43–46]. However, these methods have not been standardized for the classification of imported vs. local malaria cases. In this study, it was relatively trivial to document the lack of closely related infections, given the use of highly diverse genetic markers which provided robust data even in polyclonal infections, the setting of a robust surveillance system capturing all or nearly all cases, and importation of parasites from diverse, relatively high transmission areas. However, while one often has the agency to choose appropriate genetic markers, the other conditions are not always met highlighting the need to develop more formal methods for distinguishing local versus imported cases.
Current methods rely on reported travel history to identify the origin of imported infections, but such data are often incomplete in areas where surveillance is weak. The strong surveillance system in China allowed us to evaluate the value of genetic data to accurately assign imported cases to their geographic origins. We were able to identify the origins of infections better than expected by chance, highlighting the potential of genetic data to identify and assign the geographic origins of imported infections. However, the assignment in this case was not accurate enough to be useful for surveillance. The lower assignment accuracy observed in this study could be improved by 1) specifically identifying a panel of geographically informative loci; 2) developing sensitive and high throughput laboratory methods to genotype these loci and 3) development of formalized analytical tools that can incorporate polyclonal infections to perform accurate classification of local, imported and introduced cases as well as identify the origin of imported infections.
Expanding the genetic epidemiology toolkit is a timely task to obtain a better insight into the spatial and temporal dynamics of transmission as well as for accurate classification of local and imported infections. Using an expanded microsatellite panel, we confirmed the absence of local transmission in the Jiangsu province and demonstrated the potential for genetic data to identify the origin of imported malaria infections. More formalized methods would allow surveillance systems in eliminating countries to track infections and develop targeted policies to limit the risk of re-introduction of P. falciparum malaria from eliminating countries.