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. 2018 Nov 6;115(45):E10625-E10633.
doi: 10.1073/pnas.1808798115. Epub 2018 Oct 18.

Epidemiology of the silent polio outbreak in Rahat, Israel, based on modeling of environmental surveillance data

Andrew F Brouwer  1 , Joseph N S Eisenberg  2 , Connor D Pomeroy  1 , Lester M Shulman  3   4 , Musa Hindiyeh  3 , Yossi Manor  3 , Itamar Grotto  5   6 , James S Koopman  1 , Marisa C Eisenberg  2
Affiliations

Epidemiology of the silent polio outbreak in Rahat, Israel, based on modeling of environmental surveillance data

Andrew F Brouwer et al. Proc Natl Acad Sci U S A. .

Abstract

Israel experienced an outbreak of wild poliovirus type 1 (WPV1) in 2013-2014, detected through environmental surveillance of the sewage system. No cases of acute flaccid paralysis were reported, and the epidemic subsided after a bivalent oral polio vaccination (bOPV) campaign. As we approach global eradication, polio will increasingly be detected only through environmental surveillance. We developed a framework to convert quantitative polymerase chain reaction (qPCR) cycle threshold data into scaled WPV1 and OPV1 concentrations for inference within a deterministic, compartmental infectious disease transmission model. We used this approach to estimate the epidemic curve and transmission dynamics, as well as assess alternate vaccination scenarios. Our analysis estimates the outbreak peaked in late June, much earlier than previous estimates derived from analysis of stool samples, although the exact epidemic trajectory remains uncertain. We estimate the basic reproduction number was 1.62 (95% CI 1.04-2.02). Model estimates indicate that 59% (95% CI 9-77%) of susceptible individuals (primarily children under 10 years old) were infected with WPV1 over a little more than six months, mostly before the vaccination campaign onset, and that the vaccination campaign averted 10% (95% CI 1-24%) of WPV1 infections. As we approach global polio eradication, environmental monitoring with qPCR can be used as a highly sensitive method to enhance disease surveillance. Our analytic approach brings public health relevance to environmental data that, if systematically collected, can guide eradication efforts.

Keywords: environmental surveillance; mathematical model; poliovirus; silent transmission; vaccination.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
(A) Each qPCR amplification cycle doubles the number of targeted DNA segments. (B) qPCR cycles are repeated until the number of copies of the DNA sequence (copy number) crosses the threshold number τ. The number of cycles needed to cross this threshold is called the cycle threshold (CT), denoted y. The initial copy number is denoted W.
Fig. 2.
Fig. 2.
An SEIR-type model for poliovirus, incorporating vaccination and environmental surveillance. The model represents infection by two strains of poliovirus (OPV1 as part of bOPV, with subscript o, and WPV1, with subscript w). Individuals infected with OPV1 acquire it through vaccination (superscript v) or transmission (superscript t). Model equations are given in Eqs. 3 and 4, and parameters are in Table 1.
Fig. 3.
Fig. 3.
PCR CT data and model fits for (A) WPV1 and (B) OPV1 strains in sewage. The PCR detection limit corresponds to about a CT of 40, and experiments were run to 60. The ribbons give the CIs for the maximum-likelihood trajectory using likelihood-based estimates of the 95% confidence parameter region. The gray bars give the approximate time periods of the bOPV campaigns.
Fig. 4.
Fig. 4.
Modeled fractions of the population that were infected with WPV1, OPV1 through vaccination, and OPV1 through transmission. The ribbons give the CIs for the maximum-likelihood trajectory using likelihood-based estimates of the 95% confidence parameter region. The gray bars give the approximate time periods of the bOPV campaigns.
Fig. 5.
Fig. 5.
(A) Prevalence of WPV1 in stool of a convenience sample of under 10-y olds in Southern Israel, where point size is scaled to sample size, with weekly weighted moving average and 95% Clopper–Pearson CIs for the data points and the weekly average. (B) Modeled fraction of infectious people (with 95% CI for the maximum-likelihood estimate) based on environmental surveillance data in Rahat, Israel (WPV1 CT values transformed by the model) and the stool sample prevalence (CIs faded for readability). The environmental surveillance data suggest an earlier peak than the stool samples do. The stool samples and environmental surveillance represent different populations during the same outbreak.
Fig. 6.
Fig. 6.
Simulated cumulative incidence (fraction) of the population infected with WPV1 and OPV1 virus strains over the course of the outbreak as a function of the vaccination campaign start date. The relative campaign timing and rates are held constant while the start date changes. The gray bars give the dates of the bOPV campaigns. Earlier vaccination dates result in a larger fraction of individuals infected with the vaccine strain and a smaller fraction with the wild strain.
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