The Zika virus (ZIKV) epidemic in the Americas established ZIKV as a major public health threat and uncovered its association with severe diseases, including microcephaly. However, genetic epidemiology in some at-risk regions, particularly Central America and Mexico, remains limited. We report 61 ZIKV genomes from this region, generated using metagenomic sequencing with ZIKV-specific enrichment, and combine phylogenetic, epidemiological, and environmental data to reconstruct ZIKV transmission. These analyses revealed multiple independent ZIKV introductions to Central America and Mexico. One introduction, likely from Brazil via Honduras, led to most infections and the undetected spread of ZIKV through the region from late 2014. Multiple lines of evidence indicate biannual peaks of ZIKV transmission in the region, likely driven by varying local environmental conditions for mosquito vectors and herd immunity. The spatial and temporal heterogeneity of ZIKV transmission in Central America and Mexico challenges arbovirus surveillance and disease control measures.

In this study, we investigate the genetic diversity and transmission history of ZIKV in Central America and Mexico (hereafter referred to as CAM). We report 61 complete and partial ZIKV genome sequences, representing infections from returning travelers to the United States and autochthonous infections of residents of Mexico, Nicaragua, Honduras, Guatemala, and El Salvador. Using a combination of phylogenetic, epidemiological, and environmental data, we reveal the timing of the introduction and the spread of ZIKV in CAM and uncover the spatial and temporal heterogeneity of ZIKV transmission in the region.

Our current understanding of the genomic epidemiology of ZIKV in the Americas remains limited, in part due to the difficulties in recovering ZIKV genomes directly from clinical samples (). Despite millions of potential infections, only ∼400 full or partial (>1,500 nt) ZIKV genomes from the Americas have been reported. Genetic data from key affected locations remain scarce. Comparatively little is known about ZIKV genetic diversity in Central America and Mexico, where transmission was first reported in late 2015 () and where the estimated climatic suitability for Aedes sp. vectors is high (). Central America and Mexico have been predicted to be at high risk for ZIKV epidemics () and for infections among childbearing women ().

Multiplex PCR method for MinION and Illumina sequencing of Zika and other virus genomes directly from clinical samples.

Early genetic studies of the American ZIKV epidemic showed that it arose from a single Asian genotype lineage that was introduced to the Americas sometime between late 2013 and early 2014 (), and may have been imported from French Polynesia (). Phylogenetic analyses indicate that ZIKV was present in northeast Brazil by mid-2014, suggesting that ZIKV circulated and expanded its geographic range in the Americas for at least a year prior to its detection (). These genetic studies have clarified the timescale of the establishment and spread of ZIKV in Brazil, the Caribbean, and the United States ().

In May 2015, ZIKV cases were reported in the Americas for the first time, in Brazil. ZIKV was subsequently reported in many countries of South America (October 2015), Central America (November 2015), and the Caribbean (December 2015) (). To date, 47 of 55 countries and territories in the Americas have confirmed autochthonous ZIKV transmission (WHO situation report March 10, 2017). By the end of the epidemic, it is estimated that ZIKV will have infected ∼100 million people in the Americas (). The emergence of ZIKV in the Americas also revealed a link between ZIKV infection during pregnancy and fetal congenital malformations, including severe microcephaly (), an association now considered proven by the weight of available evidence (). ZIKV infection has also been associated with severe neurological and autoimmune complications, such as encephalitis and Guillain-Barré syndrome (). At least 24 countries in the Americas have reported cases of ZIKV-associated birth defects and 15 have reported ZIKV-linked neurological syndromes (WHO situation report March 10, 2017).

Zika virus (ZIKV), first discovered in 1947 in a Ugandan macaque, is an RNA virus of the Flavivirus genus. Vector-borne transmission of ZIKV occurs primarily from the bite of Aedes sp. mosquitoes, although transmission has also been described via blood transfusion, sexual contact, and from mother to child (). Until comparatively recently, reports of ZIKV infection in humans were limited to small outbreaks, resulting in relatively mild, self-limited disease known as Zika fever, whose symptoms include maculopapular rash, headache, conjunctivitis, and myalgia ().

The viral genetic ( Figure 2 ) and epidemiological ( Figure 3 ) results presented above both indicated the presence of two ZIKV epidemics in the CAM region, most notably in Honduras, Guatemala, and Belize ( Figure 3 ). To explore whether this unexpected pattern was due to spatial heterogeneity, we sought city-wide regional data on ZIKV incidence. Such information was available for Honduras, which accounted for >50% of reported ZIKV cases in CAM. Specifically, total numbers of suspected ZIKV cases were available for the two main cities of Honduras (Distrito Central, 1.19 million inhabitants, and San Pedro Sula, 1.07 million inhabitants; data from 2016 Honduran Ministry of Health situation reports). The case numbers are shown in Figure 4 A together with estimated mosquito suitability scores specific to each city. Remarkably, the two peaks in ZIKV cases observed at the national level ( Figure 3 ) corresponded to distinct, single epidemics in each city; cases in San Pedro Sula are almost exclusively in winter while those reported in Distrito Central were overwhelmingly during the summer ( Figure 4 A). The mosquito suitability scores for the two main cities were asynchronous, with suitability in San Pedro Sula peaking between November and February, and in Distrito Central between May and October ( Figure 4 A). For Honduras, reported ZIKV cases and mosquito suitability scores were much more strongly associated at the local than at the national level ( Figures 3 and 4 A). Notably, the ZIKV epidemic in San Pedro Sula ended abruptly in March as predicted suitability rapidly declined. The difference in the vector suitability scores between these two cities likely results from their distinct geographies, as Distrito Central is situated in the central highlands of Honduras and San Pedro Sula in the Atlantic lowlands ( Figure 4 B), the average precipitation in winter being much higher in the latter than in the former (see Discussion).

(A) Maps of Central America centered on Honduras showing population density (left panel) and elevation (right panel). In the bottom panel, the bar plots show notified Zika virus cases per week for the two main cities of Honduras highlighted on the population density map. For each bar plot, dashed lines indicate the estimated climatic vector suitability score for the two cities.

We observed a strong association between estimated vector suitability and weekly suspected ZIKV cases for Mexico, Nicaragua, and Costa Rica (R> 0.5; p < 0.001; Figure 3 and Table S2 ), a trend previously reported in different Brazilian regions (). However, Belize, El Salvador, Guatemala, Honduras, and Panama did not show any such association (R< 0.3; p > 0.01; Figure 3 and Table S2 ). Suspected cases peaked twice in Belize, Guatemala, and Honduras, once between May and October (corresponding to the annual peak of mosquito suitability) and once between November and March. Unexpectedly, this latter rise in cases corresponded to a period of low predicted vector suitability, and a similar winter peak was also observed in El Salvador.

To better understand these temporal patterns, we computed, for each country, a measure of environmental suitability for the vector Aedes aegypti through time. The score was derived from monthly temperature, relative humidity, and precipitation data, as previously described (). We observed high climatic suitability scores between May and October for most Central American countries (Belize, Guatemala, Honduras, El Salvador, Nicaragua) and Mexico. Honduras was found to have the highest average suitability score ( Figure 3 ). Vector suitability scores in Costa Rica and Panama were typically lower and exhibited less seasonal variation. The scores in Figure 3 represent average suitability across each country, except for Mexico, for which the suitability score represents only those 11 federal states that correspond to 95% of confirmed ZIKV cases (Chiapas, Colima, Guerrero, Hidalgo, Morelos, Nuevo León, Oaxaca, Quintana Roo, Tabasco, Veracruz, and Yucatán).

Potential for Zika virus introduction and transmission in resource-limited countries in Africa and the Asia-Pacific region: a modelling study.

To place the above genomic findings in their epidemiological context, we analyzed available national-level epidemiological data for countries in the CAM region. Weekly suspected ZIKV cases from Central American countries and confirmed cases for Mexico from 2015 to 2017 were extracted from the Pan American Health Organization (PAHO) epidemiological reports (June 2017; Figure 3 ). The date of first detection of ZIKV in each country ranged from November 2015 in El Salvador to May 2016 in Belize. Countries reported a variety of epidemic trajectories; Costa Rica, Mexico, and Nicaragua exhibited one epidemic peak in late summer 2016, while two peaks in transmission (winter and summer) were observed in Belize, Honduras, and Guatemala. (Note that here we use Northern Hemisphere definitions of summer and winter, which correspond approximately to wet and dry seasons in tropical regions north of the equator.) Suspected ZIKV cases in El Salvador peaked only once, at the beginning of January 2016, while those in Panama showed no clear temporal pattern during 2016. These data should be interpreted cautiously because (1) case reporting varies among countries, (2) syndromic surveillance may not be able to distinguish between ZIKV and other infections with similar symptoms, and (3) reporting intensity may vary through time, e.g., during national holidays.

Each panel corresponds to a country within the Central America and Mexico region. In each panel, the bar plots show notified Zika virus cases per week until May 2017 (plots adapted from PAHO); dashed lines indicate the estimated climatic vector suitability score, averaged across the country (see STAR Methods for details); and a small colored arrowhead indicates the date of earliest confirmation of autochthonous Zika virus cases in that country.

We used the Bayesian birth-death skyline model () to estimate temporal changes in R, the effective reproductive number of the CAM clade of ZIKV, directly from virus sequence data ( Figure 2 C). For each point in time, Rrepresents the average number of secondary infections caused by a case (hence R> 1 and R< 1 represents epidemic growth and decline, respectively). We observed four periods of epidemic growth (estimated R> 1; red dotted line in Figure 2 C) within 2015 and 2016, although only the second and fourth periods were statistically significant, with a ≥95% posterior probability that R> 1. The first period coincided with ZIKV spread from Honduras to other CAM countries. The second growth period, mid-2015, reached a median R> 2 and coincided with the within-country movement in Mexico ( Figure 2 C). This second period also corresponded to a rapid radiation of ZIKV lineages in clade B ( Figure 2 A) and preceded the first reported cases of ZIKV in CAM. The third period occurred immediately prior to the rapid increase in reported ZIKV cases in CAM in early 2016 (). The fourth growth period corresponded to the epidemic observed during April–July 2016 in CAM ().

We used a discrete trait analysis to infer the ancestral location of each phylogeny branch (). This indicated that the most likely location of the common ancestor of clade B was Honduras ( Figure 2 A; posterior probability = 0.97). This result was unlikely to be an artifact of sampling intensity because clade B contained more sequences from Mexico (n = 47) than from Honduras (n = 31) and because random subsampling of the dataset confirmed that Honduras as the ancestral node location was the most likely scenario ( Figure S4 ). Despite being smaller and less populous than Mexico, Honduras accounted for >50% of all suspected ZIKV cases in the CAM region (WHO, 2017). Our phylogeographic analysis estimated that ZIKV was introduced to Honduras from Brazil around July to September 2014 ( Figure 2 B), and that subsequent dissemination of ZIKV to Guatemala and Nicaragua and to southern Mexico likely occurred in late 2014 to early 2015 (December 2014 to February/March 2015). The state-level sampling of viruses from Mexico indicated that ZIKV was most likely first introduced into Mexico (from Honduras) via the southern state of Chiapas. Our reconstruction suggested that ZIKV subsequently spread within Mexico, from Chiapas to Oaxaca and Guerrero states, and that this within-country movement occurred in mid-2015 (April/May to July 2015) ( Figure 2 B).

A regression of genetic divergence against sampling time confirmed that the dataset was suitable for molecular clock analysis ( Figure S2 ; R= 0.65). To reconstruct the dissemination of ZIKV within CAM, we used a well-established Bayesian molecular clock phylogeographic approach (). The resulting maximum clade credibility tree was largely consistent with previous studies ( Figure 2 A; see also Figure S3 ) () and with the ML phylogeny ( Figure S2 ). As before, most sequences from CAM were placed in a single clade (clade B in Figure 2 A; posterior probability = 1.0). We estimated the date of the most recent common ancestor (MRCA) of clade B to be December 2014 ( Figure 2 A; 95% highest posterior density [HPD] = September 2014 to March 2015), diverging from Brazilian strains around July 2014 (node A in Figure 2 A; 95% HPD = March 2014 to November 2014; posterior probability = 0.8). Hence we estimated that the clade B lineage was exported from Brazil to Central America between July and December 2014. This timescale was approximately three months earlier than that estimated in previous studies (), a refinement likely due to the larger number of strains from CAM included in this analysis. Four ZIKV strains from Panama and Mexico did not result from the clade B introduction and were instead likely introduced from Colombia or the Caribbean during the second half of 2015 (clade C; Figure 2 A).

(C) Effective reproductive number (R e ) through time, estimated using a birth-death skyline approach. The black line, darker shading, and lighter shading represent, respectively, the median posterior estimate of R e , and its 50% and 95% highest posterior density credible intervals. Circled numbers indicate the four periods of epidemic dynamics mentioned in the main text.

(B) Earliest inferred dates of Zika virus introduction to and within Central America and Mexico. Each box-and-whisker plot corresponds to the earliest movement between a pair of locations with well-supported virus lineage migration (left color, source location; right color, destination location). Letters indicate federal states of Mexico (C, Chiapas; O, Oaxaca; G, Guerrero).

(A) A maximum clade credibility phylogeny estimated from complete and partial Zika virus sequences from the Americas (see STAR Methods for details). For visual clarity, basal Asian and Pacific lineages are not displayed, and two large clades (corresponding to groups of sequences in South America and the Caribbean) have been collapsed and their positions indicated by purple and brown squares, respectively. Violin plots show the posterior distributions of the estimated dates of nodes A and B (see main text). Branch colors indicate the most probable ancestral lineage locations of isolates from the Central America and Mexico region. Circles at internal nodes denote clade posterior probabilities >0.75. For selected nodes, colored numbers show the posterior probabilities of inferred ancestral locations, while black numbers are the clade posterior probabilities.

The sequence alignment ( Data S1 ) used for phylogenetic analyses comprised the 61 ZIKV sequences generated here, plus 298 published and available sequences, as of June 2017. We first estimated a maximum-likelihood (ML) phylogeny with bootstrap node support values ( Figure S2 ). This tree revealed that 102 of the 107 ZIKV sequences from CAM fell into a single monophyletic clade (clade B in Figure S2 ; bootstrap score = 65%), which also contained two sequences from the United States (see). This CAM clade was most closely related to ZIKV sequences from Brazil (clade A in Figure S2 ). Four ZIKV sequences from Panama and one from Mexico did not fall within clade B and were instead placed within a different clade (clade C in Figure S2 ; bootstrap score = 85%). Within clade C, Panama sequences were most closely related to those from Colombia, whereas the Mexico sequence groups were related to strains from Martinique. Thus, ZIKV had been introduced to CAM from other locations on multiple occasions, but most CAM infections descended from just one importation event (clade B).

Many sequenced samples had low genome coverage ( Table S1 ). Coverage was variable for samples with Ct values >30 ( Table S1 ), and missing regions appeared to be randomly distributed across the ZIKV genome ( Figure 1 C). We undertook a preliminary phylogenetic analysis to explore the trade-off between minimum genome coverage and the number of sequences included in the alignment ( Figure S1 ). Specifically, we measured ZIKV phylogenetic accuracy on pseudoreplicate alignments in which the number and incompleteness of genomes was varied. A notable decrease in phylogenetic accuracy was observed when partial genome coverage was reduced from 40% to 20% ( Figure S1 ). Following this, we chose to retain only those ZIKV sequences with >30% genome coverage. Other analyses confirmed that our dataset contained sufficient phylogenetic and temporal information for further analysis (see Figure S2 ). This resulted in a final dataset of 61 sequences with an average genome coverage of 82.6% ( Figure 1 C and Table S1 ).

The remaining 14 ZIKV samples, all from Nicaragua ( Table S1 ), were processed in a separate laboratory using an alternative mNGS method that employed bait probe capture of metagenomic libraries without the use of spiked primers (). Coverage of the consensus ZIKV genomes generated from the Nicaraguan samples ranged from 1% to 100%, with an average of 47% ( Table S1 ).

An approach that combined metagenomic next-generation sequencing (mNGS) () with a newly developed “spiked” primer enrichment strategy (see STAR Methods ) was applied to 81 of the 95 qRT-PCR-positive samples. This strategy successfully identified mNGS reads that matched ZIKV in 71 of those 81 samples. Coverage of the consensus ZIKV genomes generated from each sample ranged from 2% to 100%, with an average of 64% ( Table S1 ). Further bait capture probe enrichment for ZIKV genome recovery was attempted on 10 samples, whose original genome coverages ranged from 9% to 73%. Bait capture probe enrichment expanded coverage for all cases but one, with an average gain of 10.3% (0.0%–22.3%) coverage ( Table S1 ).

Serum and urine samples obtained from patients living in, or who had traveled to, CAM and who exhibited symptoms consistent with ZIKV infection ( Table S1 ) were screened for ZIKV by real-time qRT-PCR. A total of 95 specimens, sampled between January and August 2016, were qRT-PCR positive (59 from Mexico, 16 from Nicaragua, 9 from Honduras, 8 from Guatemala, 3 from El Salvador; Figures 1 A and 1B ; Table S1 ). For 52 Mexico samples, the federal states where samples were collected were known (Campeche, Chiapas, Guerrero, Oaxaca, and Yucatán). Positive samples were collected, on average, 2 days after symptom onset ( Table S1 ), consistent with previous ZIKV studies in Brazil () and Colombia (). This period likely reflects the narrow 3-day overlap between ZIKV viremia (which persists for ∼9 days after infection) and the onset of symptoms (at ∼6 days after infection) (). The median cycle threshold (Ct) value of qRT-PCR-positive samples was 36, similar to previous studies (), and corresponded to a low RNA titer approaching the detection threshold for PCR ( Table S1 ).

(C) Consensus genome coverage of the Zika virus sequences generated in this study. Sequences are colored according to their sampling location and the Zika virus genome structure is shown above the plot.

(B) The temporal and geographic distribution of Zika virus qRT-PCR-positive samples tested in this study. Samples are colored according to their sampling location.

(A) Map of Central America and Mexico. Colored circles indicate the sampling locations of Zika virus sequences generated in this study, and the locations of publicly available sequences from Central America and Mexico.

Discussion

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