Contrasting the epidemiological and evolutionary dynamics of influenza spatial transmission

Abstract

In the past decade, rapid increases in the availability of high-resolution molecular and epidemiological data, combined with developments in statistical and computational methods to simulate and infer migration patterns, have provided key insights into the spatial dynamics of influenza A viruses in humans. In this review, we contrast findings from epidemiological and molecular studies of influenza virus transmission at different spatial scales. We show that findings are broadly consistent in large-scale studies of inter-regional or inter-hemispheric spread in temperate regions, revealing intense epidemics associated with multiple viral introductions, followed by deep troughs driven by seasonal bottlenecks. However, aspects of the global transmission dynamics of influenza viruses are still debated, especially with respect to the existence of tropical source populations experiencing high levels of genetic diversity and the extent of prolonged viral persistence between epidemics. At the scale of a country or community, epidemiological studies have revealed spatially structured diffusion patterns in seasonal and pandemic outbreaks, which were not identified in molecular studies. We discuss the role of sampling issues in generating these conflicting results, and suggest strategies for future research that may help to fully integrate the epidemiological and evolutionary dynamics of influenza virus over space and time.

Figure 1.

Map of the total number of viral gene sequences available in the public domain for influenza A/H3N2 (n = 42 075), 2009 pandemic A/H1N1 (42 246), seasonal influenza A/H1N1 (n = 16 998), influenza B (n = 9964), by country. The map serves to illustrate the geographical gaps in sampling of molecular data, especially in Africa. Note also the unbalanced sampling frequency by subtype, in particular the intense collection efforts for pandemic A/H1N1 virus over a short period of time (3 years at the time of this study), relative to the other subtypes that have circulated for over 30 years. Numbers are coded according to the scale on the bottom of the figure, increasing from yellow to dark red. White areas denote countries with no data. Maps are based on a GenBank search performed on 10 July 2012 with the keywords ‘human’, ‘type A, H3N2’, ‘type A, H1N1 (excluding 2009 pandemic H1N1)’, ‘type B’ and ‘type A, 2009 pandemic H1N1 only’.

Figure 2.

Bayesian skyride analysis depicting the fluctuating levels of relative genetic diversity in A/H3N2 influenza virus from 2002 to 2006 in New York State, USA (blue), Hong Kong (red), Southeast Asia (pink) and New Zealand (NZ, green). Localities are arranged from top to bottom by latitude. The x-axis shows time from youngest sampled sequence to the lower 95% credible interval of the age of the tree linking these sequences, whereas the y-axis depicts relative genetic diversity (N_et), where N_e is the effective population size, and t is the generation time. Note the marked seasonal bottlenecks in the Northern (New York) and Southern (New Zealand) Hemispheres compared with the lower and more constant levels of genetic diversity observed in more tropical regions. Adapted from Bahl et al. [6] with permission.