Multiannual patterns of influenza A transmission in Chinese live bird market systems

Abstract

Background: Avian influenza viruses (AIV) cause huge economic losses in poultry industries and pose a substantial threat to human health. However, predicting AIV epizootics and emergence in humans is confounded by insufficient empirical data on the ecology and dynamics of AIV in poultry systems. To address this gap, we quantified incidence patterns for 13 hemagglutinin subtypes of AIV using 6 years of surveillance data that were collected from ten different species of poultry and three different types of poultry holdings (contexts) - retail, wholesale, or farms.

Methods: We collected 42 646 samples in Shantou, China between 2000 and 2006. We screened samples for hemagglutinin subtypes 1-13 of AIV and Avian Paramyxovirus-type-1 (APMV-1) using monospecific antisera in hemagglutination inhibition tests. We analyzed the data to determine seasonality patterns, subtype-host, and subtype-subtype interactions as well as subtype bias in incidence in different contexts.

Results: H3, H6, H9, and APMV-1 were the most prevalent. No significant seasonality was found when all subtypes were considered together. For most AIV subtypes and APMV-1, there was subtype specificity for host, context, and coinfection partner. H5 showed the most generalized host usage pattern, followed by H9 and H6.

Conclusion: Subtype-specific patterns because of host, context, and other subtypes suggest that risk assessments that exclude these details are likely inaccurate. Surveillance should include longitudinal sampling of multiple host species in multiple contexts. Quantitative models of control strategies must consider multiple subtypes, hosts, and source contexts to assess the effectiveness of interventions.

Figure 1

Temporal trends in retail markets. (A) shows the monthly proportions for all host samples positive for: APMV‐1 (gray, dotted); the most prevalent Avian influenza viruses (AIV) subtypes (H3, black; H6, light gray; H9, black dotted); and H5 (dark gray). B shows the same analysis limited to ducks (An. platyrhynchos). The horizontal line marks the upper limit in plot A for comparison. C shows monthly proportion of samples positive for subtypes H1‐H13 or APMV‐1 for the three host species (as in Table 1) that were sampled consistently throughout the 6 years (see Figure S1 for the time series of sample sizes).

Figure 2

Autocorrelation functions for all subtypes together and separately in different hosts. The Pearson correlation coefficients for data lagged by each number on the x‐axis are plotted for subtypes isolated from ducks (DK + WDK; A, C, and E), chickens (CK + SCK; B and D), or quail (QA; B or F). A and B show correlations when all subtypes are aggregated, whereas C‐F show correlations for individual subtypes. Circles indicate significance of the autocorrelation when data are lagged by x‐axis values (α = 0.05). Values above 0 indicate positive correlation (i.e., the incidence at times i and j are either both high or both low), whereas values below 0 indicate negative correlations (i.e., the incidence at times i and j are opposite– one is high and one is low).

Figure 3

Patterns of host usage and context dependence. A shows host usage for host species that were sampled consistently over the longest time period. Only the last 3 years of retail market data (September 2003–September 2006) were included because this was the time period during which the most host species were sampled consistently (see Figure S1) and surveillance protocols were unchanged. Context dependence patterns for subtypes are shown in ducks (B) and chickens (C). Farms were excluded in C because chickens were not sampled intensely enough (see Figure S2). Gray boxes indicate a significantly positive relationship, black boxes are for significantly negative relationships, and white boxes indicate that the infection rate is proportional to the number of samples collected. Numbers inside the boxes: # of positive samples, number of monthly time points in analysis. Only subtypes for which there were adequate samples, and host species that were sampled consistently, were included in the analysis. Hosts are listed across the top (abbreviations as in Table 1). Subtypes are listed in the first column; Avian Paramyxovirus‐type‐1 is Avian Paramyxovirus‐type‐1. The total number of samples collected from each host species is listed along the bottom. The total number of positive samples for each subtype is in the last column. For each subtype, we excluded time points in which no positive samples were found (reflected in the second number in each box). Bird groups with multiple subspecies from the same species were pooled in A (a preliminary analysis showed that there were no differences between these groups). Alpha values were adjusted for multiple tests using a Bonferroni correction (α_A = 0.0071, α_B = 0.0167, α_C = 0.025).

Figure 4

Patterns of multi‐subtype infections in ducks in all contexts. Part A shows the distribution of numbers of subtypes per sample. For example, the first bar (black) indicates that there were 2603 single‐subtype infections in ducks. N is the total number of positive samples. The inset shows the distribution restricted to multi‐subtype infections only (no single positive samples). Part B shows counts of single‐ (black) and double‐subtype (gray) positives for each subtype (shown on x‐axis; numbers are Avian influenza viruses (AIV) subtypes 1–13). Counts of double positives are the total number that include each subtype (i.e., the sum of gray bars is greater than the total number of double infections). H12 and H13 are blank because they were only observed in infections with 3 or more subtypes. Part C shows partner bias in double infections. Rows are the focal subtypes and columns are their partners. Numbers in the boxes are the count of double infections with each partner; single infection counts are shown in the diagonal. Gray indicates subtype coinfections that occur more often than expected based on prevalence, whereas black indicates coinfections that occur less often than expected. Expected count for a given partner was based on its frequency in single and double infections, and significance was tested by a multinomial test (see Methods and Supporting information). Uncolored blocks represent combinations with either no significant bias in subtype coinfections or very weak trends. The last column indicates the percent of infections that are coinfections for focal subtypes. Part D shows a schematic relationship of coinfection compatibility (double infections only). Subtypes connected by a double arrow have significant associations with each other, whereas unconnected subtypes are found together less often than expected based on prevalence. One‐sided arrows indicate the direction of one‐sided associations. Circles indicate distinct phenotypic clusters of compatibility; that is, Avian Paramyxovirus‐type‐1 (APMV‐1) shows no association with AIV for coinfection and most subtypes of AIV show significant avoidance of APMV‐1. There is not enough sample size to classify H5.