Dengue diversity across spatial and temporal scales: Local structure and the effect of host population size

Abstract

A fundamental mystery for dengue and other infectious pathogens is how observed patterns of cases relate to actual chains of individual transmission events. These pathways are intimately tied to the mechanisms by which strains interact and compete across spatial scales. Phylogeographic methods have been used to characterize pathogen dispersal at global and regional scales but have yielded few insights into the local spatiotemporal structure of endemic transmission. Using geolocated genotype (800 cases) and serotype (17,291 cases) data, we show that in Bangkok, Thailand, 60% of dengue cases living <200 meters apart come from the same transmission chain, as opposed to 3% of cases separated by 1 to 5 kilometers. At distances <200 meters from a case (encompassing an average of 1300 people in Bangkok), the effective number of chains is 1.7. This number rises by a factor of 7 for each 10-fold increase in the population of the "enclosed" region. This trend is observed regardless of whether population density or area increases, though increases in density over 7000 people per square kilometer do not lead to additional chains. Within Thailand these chains quickly mix, and by the next dengue season viral lineages are no longer highly spatially structured within the country. In contrast, viral flow to neighboring countries is limited. These findings are consistent with local, density-dependent transmission and implicate densely populated communities as key sources of viral diversity, with home location the focal point of transmission. These findings have important implications for targeted vector control and active surveillance.

Figure 1

(A) Map of Thailand showing location of case data (P-Pathum Thani, R-Ratchaburi, H–Hat Yai, L–Lampang, N-Nakhon Ratchesima, B-Bangkok). S–serotype data available, G–genotype data available. (B) Geolocated case data from Bangkok province. In total there were 7,511 DENV1, 4,265 DENV2, 3,371 DENV3 and 2,144 DENV4 cases. (C)–(F) Maximum Credibility Clade trees for DENV1 (N=306), DENV2 (N=210), DENV3 (N=157) and DENV4 (N=127). The colors of the tips represent the source of the virus. (G) Median spatial distance between virus-pairs from Bangkok separated by different total evolutionary times. The shaded area represents 95% confidence intervals. The number of transmission generations separating virus-pairs (top axis) is calculated by dividing the total evolutionary time by 20 days, the mean generation time for dengue.

Figure 2

(A) The proportion of case-pairs, sick within six months of each other that come from the same transmission chain when separated by different spatial distances within Bangkok. The estimates are calculated using either serotype (closed squares) or genotype (open circles) data (21). The error bars represent 95% confidence intervals. (B) The proportion of case-pairs, sick within six months of each other that are homotypic (caused by the same serotype) at different distance ranges where both cases are in Bangkok (blue) or when one is in Bangkok and the other is in another province (purple). The error bars represent 95% confidence intervals. (C) The proportion of case-pairs that are homotypic where both come from the same province (upwards facing triangle) and where they come from different provinces (downward facing triangle). The letters in panel (C) represent the provinces from Figure 1. The error bars represent 95% confidence intervals. (D) Difference in the probability that a case that is aged either <5y or 5–10y shares the same chain as another case within different spatial distances of their home versus the probability that a case that is aged >10y shares the same chain within that same distance. The shaded area represents 95% confidence intervals. (E) Difference in the probability that a female case shares the same chain as another case within different spatial distances versus the probability that a male case shares the same chain within that same distance. The shaded area represents 95% confidence intervals.

Figure 3

(A) Number of discrete transmission chains circulating within a six-month period for different mean population sizes within Bangkok (blue) and across other provinces (red) calculated using either serotype (S) or genotype (G) data. Each intra-Bangkok estimate is the mean number of chains for different distances between cases (top axis). The mean population surrounding a case at that distance is on the bottom axis. (B) The number of transmission chains for fixed areas (radius of 0.5, 1 or 1.5km) with different population sizes within that area. The blue squares represent the mean number of chains within a fixed area across all population sizes from panel (A). (C) Number of chains at different population densities (in 000s/km2) relative to the expected number of chains irrespective of population density for different sized areas (the colors are consistent with panel (B)). The shaded area represents 95% confidence intervals for an area with radius 1.5km. (D) Number of transmission chains for different sized areas from simulations of density-dependent endemic transmission in a spatially heterogeneous population of 500,000 individuals where transmission occurs at <50m and is 2 times greater in the densest areas (population density of >20,000 individuals per km2) than elsewhere.

Figure 4

Relative risk that a pair of viruses have an MRCA within a defined period. Each point represents the risk that a pair of viruses isolated from cases sick within six months of each other and living a particular spatial distance apart have an MRCA within a defined evolutionary timeframe (g1–g2) relative to the risk that a pair of distal Bangkok cases (defined as two cases from Bangkok separated by >10km) have an MRCA in the same g1-g2 range. Each panel represents a different g1–g2 range: (A) MRCA <6m (i.e., g1=0, g2=6m); (B) MRCA 6m–2y; (C) MRCA 2–5y; (D) MRCA 5–10y. ‘Intra-prov’ refers to pairs of viruses that both come from the same province outside Bangkok. ‘Inter-prov’ refers to cases where one virus comes from Bangkok and the other from a different province. ‘SE Asia’ refers to where one virus is from Bangkok and the other from another country in mainland SE Asia (Vietnam, Malaysia, Singapore, Cambodia, Myanmar). The error bars represent 95% confidence intervals. The open triangle in panel A represents a value of 0.