Regional connectivity drove bidirectional transmission of SARS-CoV-2 in the Middle East during travel restrictions

Abstract

Regional connectivity and land travel have been identified as important drivers of SARS-CoV-2 transmission. However, the generalizability of this finding is understudied outside of well-sampled, highly connected regions. In this study, we investigated the relative contributions of regional and intercontinental connectivity to the source-sink dynamics of SARS-CoV-2 for Jordan and the Middle East. By integrating genomic, epidemiological and travel data we show that the source of introductions into Jordan was dynamic across 2020, shifting from intercontinental seeding in the early pandemic to more regional seeding for the travel restrictions period. We show that land travel, particularly freight transport, drove introduction risk during the travel restrictions period. High regional connectivity and land travel also drove Jordan's export risk. Our findings emphasize regional connectedness and land travel as drivers of transmission in the Middle East.

Fig. 1. Investigating the first year of the SARS-CoV-2 pandemic in Jordan.

A Reported daily cases in Jordan (bar graph, left axis) and time-varying effective reproduction number (ribbon, right axis). B Number of sequences generated in this study from Jordan (bar graph, left axis) and weekly rolling mean sampling fraction for Jordan (line, right axis). C Timeline of non-pharmaceutical interventions in Jordan (see Methods for definitions). D Geographic distribution of sequences generated in the current study, relative to population density of Jordan and its major sampled cities. E Overall sampling fraction for all Middle Eastern countries and number of publicly available SARS-CoV-2 sequences on GISAID for Middle Eastern countries.

Fig. 2. Phylogeographic analysis of SARS-CoV-2 in Jordan.

A A representative time-calibrated phylogeny. Branches are colored by region-level geographic state reconstruction. Internal nodes annotated with black point represent posterior support >0.75. B The estimated number of introductions or Markov jumps into Jordan from source regions summarized across three replicates for the three downsampling strategies annotated in color. EII: Epidemiological incidence informed; RE: Regional enrichment; III: Introduction Intensity Index informed—see Methods for full definition. C Posterior median number of introductions into Jordan binned by month from each region, summarized across all datasets. D Lineage frequency profile over time for 579 sequences generated in this study, classified by the Pangolin nomenclature. Only major lineages in Jordan and variants of concern are listed in the legend. Dashed line indicates when variant screening was implemented.

Fig. 3. Dynamic introduction risk shifts to regional seeding during the period of travel restrictions in 2020.

A The density of estimated introductions (Markov jumps) into Jordan over time from source regions by downsampling strategy (EII, III, RE) summarizing three replicates each. See Supplementary Fig. 6 for all replicates. EII: Epidemiological incidence informed; RE: Regional enrichment; III: Introduction Intensity Index informed. For legend see (B). B Volume of monthly air passengers destined for Jordan across 2020 by region (bar, left axis) and percentage of incoming volume originating from the Middle Eastern region (line, right axis). C Percentage of incoming air travel from the Middle East by country across 2020. D Incoming land-based travel by vehicle type for each bordering country across 2020. Time period of land border closure (light blue) annotated.

Fig. 4. Land-based regional connectivity drives introduction risk during the period of travel restrictions.

A Estimated introduction (importation) Intensity Index (II) for 2020, divided into the Middle East and the remaining (Global, non-Middle Eastern). Countries grouped by region, except Middle Eastern countries in the bottom panel, which are country-level. Legend in A applies to C. B Contribution of land and air travel to II in (A) for highest ranked regional countries. C Temporal synchrony between introductions estimated from genomic data (across all downsampling strategies and randomizations) and the weekly rolling average estimated introduction index (II) across the four regions summarizing the countries with the 20 highest individual-level II in (A) for the period prior to travel restrictions (top panel) and the period travel restrictions were in place (bottom panel). The normalized time series for the genomic estimates of introduction are depicted in light gray, with a line per seed and downsampling strategy, and the estimated introduction index (II) for each region are annotated in color. D The dynamic time warp distance between the query genomic estimate and each region’s III across all downsampling strategies and randomizations for the period prior to travel restrictions. E The dynamic time warp distance between the query genomic estimate and each region’s II across all downsampling strategies and randomizations for the period travel restrictions were in place.

Fig. 5. Land-based regional connectivity drives introduction risk during the period of travel restrictions.

A The effect of travel restrictions on introduction risk. Counterfactual estimated Introduction Intensity Index (II) for 2020 should travel restrictions not have been implemented, assuming travel volumes of January–February were extended from March to September. The counterfactual II is annotated in faded colors. B Contribution of land and air travel to counterfactual II for highest ranked regional countries.

Fig. 6. Land-based regional connectivity drives export risk from Jordan.

A Volume of monthly air passengers traveling from Jordan across 2020 by region (bar, left axis) and percentage of outgoing volume destined for the Middle Eastern region (line, right axis). B Percentage of outgoing air travel to the Middle East by country across 2020. C Outgoing land-based travel by vehicle type for each bordering country across 2020. Time period of land border closure (light blue) annotated. D Dissimilarity between weekly binned lineage frequency profiles as presence-absence of lineages between Jordan and its Middle Eastern neighbors by Bray–Curtis dissimilarity. Bray–Curtis dissimilarity is bound between 0 and 1, with 0 indicating the countries have the same composition and 1 indicates countries do not share any lineages. E Estimated Exportation Intensity Index for 2020. F Contribution of land and air travel to the EII of Jordan’s neighboring countries.