Figure 1. The incidence of malaria and spatial connectivity in the Chittagong Hill Tracts (CHT) Region.
(A) The average monthly incidence per 1000 population of P. falciparium malaria from 2015 to 2016 as reported by the NMEP. Incidence was highest in the eastern portion of the CHT (shown in relation to the country borders) and decreased westward. (B) The forest coverage (%). (C) Unions sharing at least one parasite with identical genetic barcodes. (D) Top 50% of most traveled routes reported between pairs of locations from the travel survey data. (E) Top 1% of routes traveled between pairs of locations from the mobile phone data. Unions were colored grey where data was collected on genetic (C), travel survey (D) or mobile phone data (E).
Figure 1—figure supplement 1. Sample distribution.
(A) District map in the CHT. Sample distribution of genetic (B), travel survey (C) and mobile phone (D) data.
Figure 1—figure supplement 2. Drug resistant markers and the proportion of identical parasites showing spatial signal.
(A) The drug resistance-related markers were significantly associated with latitude, including PGB mutations that were found in genetic background of K13 mutations that lead to artemisinin resistance (Pearson’s correlation test, p-value=1.58 × 10–5, r=–0.601), DHFR mutations that mediated pyrimethamine resistance (Pearson’s correlation test, p-value=0.0018, r=–0.453), and the proportion of the haplotype of IRNxx [DHFR] and xGExx [DHPS], which was shown to be associated with treatment failure for the combination of pyrimethamine and sulfadoxine (Pearson’s correlation test, p-value=0.035, r=–0.335). Red dotted line is the fitted linear regression line. (B) The unions were clustered based on genetic information, the proportion of identical parasites between locations, using Infomap (Rosvall and Bergstrom, 2011). Unions without genetic data are shown in white; unions that had genetic data but did not cluster with any other union are shown in grey; the remaining colors represent the identified cluster (i.e. unions in the same cluster were colored using the same color).
Figure 1—figure supplement 3. Commonly used genetic measures show little spatial signal.
(A) Pattern of genetic variation was presented by the first two principal components from principal component analysis (PCA) analysis. The color shows the average PC1 or PC2 values for each union (white means no data). There was no clear spatial trend in PC1 or PC2 values. (B) Unions with lowest 1% average pairwise difference were connected. (C) The average complexity of infection for each union. (D) Genetic barcodes of parasites in international travelers were not distinguishable from people who did not travel or only traveled within Bangladesh, from PCA analysis. The case from Mozambique was an immigrant and was an outlier in the plot. (E)-(F) Average pairwise SNP difference (%) (E) and FST (F) were not associated with geographic distance. FST was calculated for both barcodes and drug markers using Weir and Cockerham's method (Weir and Cockerham, 1984) between all union pairs with sample sizes > 20.