Background
An outbreak of novel A/H7N9 influenza virus infections rapidly unfolded in Eastern China, with the first laboratory-confirmed case identified in Shanghai on 31 March 2013 and a total of 132 laboratory-confirmed cases and 38 fatalities reported as of 3 June 2013 [
1,
2]. Although the number of new A/H7N9 cases has stalled since early May 2013, several features of this virus have heightened concerns for its pandemic potential and prompted an intense public health response from the Chinese authorities and international health organizations. Foremost, the rapid progression of new cases in urban centers in April 2013 and the severity of the disease have been worrisome. Although the exact route of transmission remains unclear, current evidence points to frequent spillovers from a yet-to-be-confirmed avian reservoir, suspected to involve poultry [
3‐
6]. Although genetic analyses of the novel virus have revealed potential signs of adaptation to mammalian hosts [
7], to date, sustained human-to-human transmission has not been established through contact tracing analysis [
3,
4] but cannot be ruled out. About 23% [
4] of the A/H7N9 patients report having no prior exposure to live animals, underscoring the potential role of transmission by the environment, aerosols and undocumented contacts with infected individuals. Further, recent experimental studies indicate that the A/H7N9 virus is able to spread efficiently among ferrets via direct contact, although airborne transmission is less efficient [
8].
A particular cause for concern is the fact that poultry infected with the A/H7N9 virus seem to exhibit relatively mild symptoms [
9], which may extend the infectious period in this host. This is in stark contrast to highly pathogenic A/H5N1 influenza viruses, which typically kill poultry within a few days. Silent and undetected A/H7N9 infections in poultry increase the likelihood of zoonotic infections which, in turn, enhance the potential for acquisition of sustained human-to-human transmission properties.
Preliminary studies suggest a low incidence of A/H7N9 infection in chickens and pigeons in affected areas [
1,
5]. Nevertheless, live bird markets were preemptively closed and sick birds culled since 6 April 2013 in Shanghai and 16 April 2013 in Zhejiang, which may have slowed down the progression of the outbreak [
10]. A quantification of the rate of viral transmission to humans and the effectiveness of intervention measures would be particularly useful to guide public health responses and provide a comprehensive risk assessment of the A/H7N9 threat.
The reproduction number, R, is a key epidemiological tool for assessing the transmission potential of an emerging infection and monitoring the likelihood of large-scale outbreaks. Estimates of R >1 signal the potential for an emerging pathogen to generate a major epidemic while R <1 indicates that transmission chains cannot be sustained in the population.
In the case of an emerging infection, obtaining near real time estimates of R is essential to guide intervention strategies. Bayesian estimation approaches [
11‐
13] are naturally well-suited for situations where epidemiological data are gradually accumulating, due to their flexibility to incorporate prior information. In these approaches, prior information is sequentially updated as more complete outbreak data become available, providing posterior distributions of the epidemiological parameters of interest [
11‐
13]. In contrast, more traditional 'epidemic curve fitting’ approaches have been typically used to provide retrospective estimates of
R once the outbreak is over [
14‐
19]. Alternative estimation approaches are based on detailed individual-level information on prior exposure to suspected animal reservoirs and/or contact with infected patients [
20‐
22].
In this report, we estimate the transmission potential of the influenza A/H7N9 virus by relying on daily official notifications of laboratory-confirmed cases in mainland China. In particular, we focus on assessing whether the progression of the outbreak is consistent with unsustained human-to-human transmission dynamics in line with R <1 and whether intervention measures may have reduced transmission. Further, we compare R estimates for A/H7N9 with those for other zoonotic pathogens that have recently caused pandemic concern.
Discussion
We have provided near real-time estimates of the transmission potential of the emerging A/H7N9 influenza outbreak in China by applying different methodological approaches to official notifications of laboratory-confirmed cases. Although there is relatively limited information in the A/H7N9 case data at this point, all available evidence points to R estimates well below 1.0 in Shanghai and Zhejiang provinces, where the majority of cases have been reported. Instead, a deceleration in growth rate in mid April is consistent with the effectiveness of preemptive live bird market closures initiated in early April. Comparison between A/H7N9 and other zoonotic threats suggests a relatively low transmission potential relative to that of other avian or swine influenza viruses and recent Nipah viruses, although further data are necessary to confirm this result.
Our Bayesian SEIR estimation approach assumes that all infections originate from human-to-human transmission and, hence, yields 'worst-case scenario’ R estimates. Our estimation framework was robust to assumptions about the duration of the infectious and latent periods, whether we considered a short serial interval characteristic of seasonal influenza [
25] or a prolonged disease course more consistent with early case descriptions [
4,
26]. In contrast, the Bayesian approach was very sensitive to assumptions regarding the prior distribution of R, which dominated the inference process. Using assumptions reasonably guided by information on prior patient exposure and the frequency of family clusters, this approach indicates a R well below the epidemic threshold (R = 1.0) in Eastern China. Further, simulation studies suggest that if the true R was above 0.6, we would see a greater shift from prior to posterior distributions than seen in the A/H7N9 data, confirming the low transmission potential of this virus.
Alternative estimation approaches based on individual level contact tracing and prior exposure suggest a range of R of 0.03 to 0.53, in line with a recent modeling study analyzing the cluster size distribution of A/H7N9 cases [
22]. These low R estimates are consistent with the results of intense efforts by the Chinese health authorities to monitor contacts of infected cases, which have so far revealed only limited instances of secondary transmission [
4]. While the occurrence of three (perhaps four) family clusters of A/H7N9 cases is consistent with short chains of human to human transmission, these clusters do not rule out exposure to common environmental or animal sources. Taken together, information from contact surveys [
4] and available R estimates are consistent with a predominance of spillover events from a hypothetical reservoir.
We observed a reduction in the growth rate of H7N9 cases in mid to late April, coinciding with the closure of live bird markets in Shanghai, Zhejiang and large Chinese cities in response to the evolving outbreak. The deceleration in the growth rate was significant in our data as early as 18 April, a period when the effectiveness of these measures was still being debated [
45]. Our model is ill-equipped, however, to predict the progression of the outbreak in the coming weeks if intervention measures are relaxed [
46], as information is lacking on the residual prevalence of A/H7N9 in poultry populations in China. Further, we cannot rule out a subsequent rise in A/H7N9 transmission potential in the coming months, as seasonal factors could affect virus prevalence in the (presumed) avian reservoir and promote avian-to-human and possibly human-to-human transmission [
47,
48].
We have provided transmissibility estimates for influenza A/H7N9 and other zoonoses using several approaches, which rely on very different assumptions. The Bayesian SEIR model-fitting approach is based on the progression of case incidence; our analyses suggest that currently available A/H7N9 data provide relatively limited information, so that the inference process is heavily dependent on the prior (see also more extreme priors in Additional file
1: Figure S6). This likely stems from the small number of A/H7N9 cases available for study (n = 70 in the two main provinces), in part resulting from the low transmission potential of A/H7N9. Simulations were particularly helpful in showing that if the true R was above 0.6, then we would have most likely identified a shift in the posterior distribution. The lack of observed shift is further evidence that R is low and most likely below 0.6.
In the context of subcritical outbreaks (R <1), alternative methods based on contact tracing and exposure information are attractive, although they depend heavily on prior knowledge of the ecology of the disease. These methods rely on estimates of the proportions of cases arising from human-to-human transmission versus direct exposure to the reservoir [
20,
21] and, hence, assume that the reservoir is well known and that onset dates and serial intervals can be accurately determined. Further, methods relying on cluster size distribution are more sensitive to reporting schemes than growth rate methods (for example, if clusters are more likely to be reported once a family member is infected) [
22].
Information regarding the reservoir of A/H7N9 and the natural history of this disease is still limited, as would be the case for any emerging zoonosis with limited prior experience. It is intriguing that 23% of A/H7N9 cases do not report any prior contact with poultry (suggesting R is approximately 0.23), and yet clusters are extremely infrequent (suggesting R closer to 0). These conflicting findings could be reconciled with additional information on the prevalence of asymptomatic infections; unfortunately, recent serological information is currently lacking. Overall, all R estimation methods tend to produce high uncertain ranges for A/H7N9. In a similar context, early estimates of the transmissibility of the MERS-CoV virus using a related approach were relatively broad, with confidence intervals ranging between 0.5 and 1.1 [
49]. A quantitative comparison of the performances of these approaches would be useful in the future as these methods are increasingly applied to characterize the pandemic potential of emerging pathogens (see also [
22]).
This study is subject to limitations. First, A/H7N9 incidence could be underreported. However, serological surveys conducted at the end of 2012 in China and Vietnam revealed low levels of prior infections [
50,
51]. Moreover, influenza-like-illness surveillance suggests that A/H7N9 infection was an uncommon cause of illness in any age group during March and April 2013 in the most affected areas of China [
52]. Our estimates are resilient to underreporting issues as long as the observed case series closely tracks the true course of the outbreak. If case detection had improved over time with increased detection capabilities, this would have artificially quickened the progression of reported cases and, in turn, spuriously overestimated the epidemic growth rate and R. Hence, because of likely increased sampling intensity as the outbreak progressed, we can view our R estimates as upper bounds of the true value.
Second, we have used a simple model to estimate R, relying on a SEIR transmission model typically used for human diseases, while in fact there is likely very little transmission between humans. Our simulations suggest that in the context of frequent spillover events arising from a reservoir, our estimates of R are inflated (consistent with providing worst-case scenarios of the true human-to-human transmission potential of A/H7N9). However, our approach accurately predicts whether an emerging pathogen remains below the critical epidemic threshold (R <1). A more refined approach could integrate more information regarding the hypothetical reservoir and the probability of contacts with humans, and could estimate the relative contribution of each component to overall disease transmission. The yet unresolved nature of the reservoir of A/H7N9 and its ecology hampers the calibration of such models.
Third, our model assumes homogeneous mixing, which may not be valid. We have focused on province-specific data, which provides a better approximation of well-mixed populations than nationally-aggregated data, especially as most cases arose from large cities (especially Shanghai). Still, there could be residual spatial heterogeneity, which may artificially decrease the estimated R. Overall, our very generic model only requires information on the date of symptoms onset and could be applicable to a variety of emerging infections that include spillovers from a putative reservoir and human-to-human transmission.
Competing interests
The authors declare they have no competing interests.
Authors’ contributions
GC and CV designed the experiments/the study. GC, LS, ST, MM and CV analyzed the data. GC and CV wrote the first draft of the paper. GC, LS, ST, MM and CV contributed to the writing of the paper. All authors read and approved the final manuscript.