Using Routine Surveillance Data to Estimate the Epidemic Potential of Emerging Zoonoses: Application to the Emergence of US Swine Origin Influenza A H3N2v Virus

MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
PLoS Medicine (Impact Factor: 14.43). 03/2013; 10(3):e1001399. DOI: 10.1371/journal.pmed.1001399
Source: PubMed


Prior to emergence in human populations, zoonoses such as SARS cause occasional infections in human populations exposed to reservoir species. The risk of widespread epidemics in humans can be assessed by monitoring the reproduction number (average number of persons infected by a human case). However, until now, estimating required detailed outbreak investigations of human clusters, for which resources and expertise are not always available. Additionally, existing methods do not correct for important selection and under-ascertainment biases. Here, we present simple estimation methods that overcome many of these limitations.
Our approach is based on a parsimonious mathematical model of disease transmission and only requires data collected through routine surveillance and standard case investigations. We apply it to assess the transmissibility of swine-origin influenza A H3N2v-M virus in the US, Nipah virus in Malaysia and Bangladesh, and also present a non-zoonotic example (cholera in the Dominican Republic). Estimation is based on two simple summary statistics, the proportion infected by the natural reservoir among detected cases () and among the subset of the first detected cases in each cluster (). If detection of a case does not affect detection of other cases from the same cluster, we find that can be estimated by 1-; otherwise can be estimated by 1- when the case detection rate is low. In more general cases, bounds on can still be derived.
We have developed a simple approach with limited data requirements that enables robust assessment of the risks posed by emerging zoonoses. We illustrate this by deriving transmissibility estimates for the H3N2v-M virus, an important step in evaluating the possible pandemic threat posed by this virus. Please see later in the article for the Editors' Summary.

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    • "Many infectious diseases show microepidemiological geographical variation. Outbreaks of (emerging) infectious diseases may be geographically confined or start in small pockets that later give rise to larger outbreaks [1–4]. For endemic infectious diseases with stable disease transmission, considerable geographical heterogeneity in the intensity of transmission has been described [2, 5–8]. "
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    ABSTRACT: SUMMARY Understanding the spatial distribution of disease is critical for effective disease control. Where formal address networks do not exist, tracking spatial patterns of clinical disease is difficult. Geolocation strategies were tested at rural health facilities in western Kenya. Methods included geocoding residence by head of compound, participatory mapping and recording the self-reported nearest landmark. Geocoding was able to locate 72·9% [95% confidence interval (CI) 67·7-77·6] of individuals to within 250 m of the true compound location. The participatory mapping exercise was able to correctly locate 82·0% of compounds (95% CI 78·9-84·8) to a 2 × 2·5 km area with a 500 m buffer. The self-reported nearest landmark was able to locate 78·1% (95% CI 73·8-82·1) of compounds to the correct catchment area. These strategies tested provide options for quickly obtaining spatial information on individuals presenting at health facilities.
    Epidemiology and Infection 05/2014; 142(9):1-12. DOI:10.1017/S0950268814000946 · 2.54 Impact Factor
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    • "As a complementary method to estimate the R for influenza A/H7N9, we used an approach recently developed by Cauchemez et al. for zoonotic infections [20]. In this approach, R = 1-p, where p is the estimated proportion of infected patients arising from direct contact with the A/H7N9 reservoir (scenario 1 in [20]). This approach provides a conservative upper bound on R as it assumes that case detection probability is independent of cluster allocation (while in general, once an index case is identified, other infections in the family are more likely to be detected). "
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    ABSTRACT: On 31 March 2013, the first human infections with the novel influenza A/H7N9 virus were reported in Eastern China. The outbreak expanded rapidly in geographic scope and size, with a total of 132 laboratory-confirmed cases reported by 3 June 2013, in 10 Chinese provinces and Taiwan. The incidence of A/H7N9 cases has stalled in recent weeks, presumably as a consequence of live bird market closures in the most heavily affected areas. Here we compare the transmission potential of influenza A/H7N9 with that of other emerging pathogens and evaluate the impact of intervention measures in an effort to guide pandemic preparedness. We used a Bayesian approach combined with a SEIR (Susceptible-Exposed-Infectious-Removed) transmission model fitted to daily case data to assess the reproduction number (R) of A/H7N9 by province and to evaluate the impact of live bird market closures in April and May 2013. Simulation studies helped quantify the performance of our approach in the context of an emerging pathogen, where human-to-human transmission is limited and most cases arise from spillover events. We also used alternative approaches to estimate R based on individual-level information on prior exposure and compared the transmission potential of influenza A/H7N9 with that of other recent zoonoses. Estimates of R for the A/H7N9 outbreak were below the epidemic threshold required for sustained human-to-human transmission and remained near 0.1 throughout the study period, with broad 95% credible intervals by the Bayesian method (0.01 to 0.49). The Bayesian estimation approach was dominated by the prior distribution, however, due to relatively little information contained in the case data. We observe a statistically significant deceleration in growth rate after 6 April 2013, which is consistent with a reduction in A/H7N9 transmission associated with the preemptive closure of live bird markets. Although confidence intervals are broad, the estimated transmission potential of A/H7N9 appears lower than that of recent zoonotic threats, including avian influenza A/H5N1, swine influenza H3N2sw and Nipah virus. Although uncertainty remains high in R estimates for H7N9 due to limited epidemiological information, all available evidence points to a low transmission potential. Continued monitoring of the transmission potential of A/H7N9 is critical in the coming months as intervention measures may be relaxed and seasonal factors could promote disease transmission in colder months.
    BMC Medicine 10/2013; 11(1):214. DOI:10.1186/1741-7015-11-214 · 7.25 Impact Factor
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    • "As examined earlier for a different influenza [12], we have shown that the information of the proportion with a history of bird contact can be explicitly translated to an estimate of R. Among published studies of the transmissibility of avian and swine influenza in humans [12,15-18], only Cauchemez et al. [12] utilised the information of the number of reservoir-borne transmission among all cases to estimate the transmissibility. While Cauchemez et al. [12] examined the similar data without censoring and specifically for a subscritical process (i.e. "
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    ABSTRACT: Background As the human infections with novel influenza A(H7N9) virus have been reported from several different provinces in China, the pandemic potential of the virus has been questioned. The presence of human-to-human transmission has not been demonstrated, but the absence of demonstration does not guarantee that there is no such transmission. Methods A mathematical model of cluster size distribution is devised without imposing an assumption of subcriticality of the reproduction number and accounting for right censoring of new clusters. The proportion of cases with a history of bird contact is analytically derived, permitting us to fit the model to the observed data of confirmed cases. Using contact history with bird among confirmed cases (n = 129), we estimate the reproduction number of the novel influenza A(H7N9) from human to human. Results Analysing twenty confirmed cases with known exposure, the reproduction number for human-to-human transmission was estimated at 0.28 (95% CI: 0.11, 0.45). Sensitivity analysis indicated that the reproduction number is substantially below unity. Conclusions It is unlikely to observe an immediate pandemic of novel influenza A(H7N9) virus with human to human transmission. Continued monitoring of cases and animals would be the key to elucidate additional epidemiological characteristics of the virus.
    Theoretical Biology and Medical Modelling 05/2013; 10(1):30. DOI:10.1186/1742-4682-10-30 · 0.95 Impact Factor
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