Researchers sound warning on MERS virus: Only a fraction of cases are being detected, study suggests

[Shiloh]

Source: http://www.theprovince.com/health/Re...330/story.html

Researchers sound warning on MERS virus: Only a fraction of cases are being detected, study suggests
THE CANADIAN PRESS November 12, 2013 4:03 PM

A new analysis of MERS case data suggests a large number of infections are going undetected, with the researchers estimating that for each case that has been found, five to 10 may have been missed.

The scientific paper, from European researchers, further suggests that transmission of the MERS (Middle East Respiratory Syndrome) virus is occurring at a rate close to the threshold where it would be considered able to pass from person to person in a sustained manner...

[sharon sanders]

Re: Researchers sound warning on MERS virus: Only a fraction of cases are being detected, study suggests

hat tip Shiloh


Middle East respiratory syndrome coronavirus: quantification of the extent of the epidemic, surveillance biases, and transmissibility

Simon Cauchemez PhD a †, Prof Christophe Fraser PhD a †, Maria D Van Kerkhove PhD a, Prof Christl A Donnelly ScD a, Steven Riley PhD a, Prof Andrew Rambaut PhD b, Vincent Enouf PhD c, Prof Sylvie van der Werf PhD c, Prof Neil M Ferguson DPhil a Corresponding AuthorEmail Address
Summary

Background
The novel Middle East respiratory syndrome coronavirus (MERS-CoV) had, as of Aug 8, 2013, caused 111 virologically confirmed or probable human cases of infection worldwide. We analysed epidemiological and genetic data to assess the extent of human infection, the performance of case detection, and the transmission potential of MERS-CoV with and without control measures.
Methods

We assembled a comprehensive database of all confirmed and probable cases from public sources and estimated the incubation period and generation time from case cluster data.

Using data of numbers of visitors to the Middle East and their duration of stay, we estimated the number of symptomatic cases in the Middle East. We did independent analyses, looking at the growth in incident clusters, the growth in viral population, the reproduction number of cluster index cases, and cluster sizes to characterise the dynamical properties of the epidemic and the transmission scenario.

Findings
The estimated number of symptomatic cases up to Aug 8, 2013, is 940 (95% CI 290—2200), indicating that at least 62% of human symptomatic cases have not been detected. We find that the case-fatality ratio of primary cases detected via routine surveillance (74%; 95% CI 49—91) is biased upwards because of detection bias; the case-fatality ratio of secondary cases was 20% (7—42). Detection of milder cases (or clinical management) seemed to have improved in recent months. Analysis of human clusters indicated that chains of transmission were not self-sustaining when infection control was implemented, but that R in the absence of controls was in the range 0·8—1·3. Three independent data sources provide evidence that R cannot be much above 1, with an upper bound of 1·2—1·5.

Interpretation
By showing that a slowly growing epidemic is underway either in human beings or in an animal reservoir, quantification of uncertainty in transmissibility estimates, and provision of the first estimates of the scale of the epidemic and extent of case detection biases, we provide valuable information for more informed risk assessment.

Funding
Medical Research Council, Bill & Melinda Gates Foundation, EU FP7, and National Institute of General Medical Sciences.

http://www.thelancet.com/journals/laninf/article/PIIS1473-3099(13)70304-9/fulltext#

[Giuseppe]

Re: Researchers sound warning on MERS virus: Only a fraction of cases are being detected, study suggests

[Source: The Lancet Infectious Diseases, full page: (LINK). Abstract, edited.]


The Lancet Infectious Diseases, Early Online Publication, 13 November 2013

doi:10.1016/S1473-3099(13)70304-9

Copyright ? 2013 Cauchemez et al. Open Access article distributed under the terms of CC BY Published by Elsevier Ltd. All rights reserved.

Middle East respiratory syndrome coronavirus: quantification of the extent of the epidemic, surveillance biases, and transmissibility

Original Text

Simon Cauchemez PhD a ?, Prof Christophe Fraser PhD a ?, Maria D Van Kerkhove PhD a, Prof Christl A Donnelly ScD a, Steven Riley PhD a, Prof Andrew Rambaut PhD b, Vincent Enouf PhD c, Prof Sylvie van der Werf PhD c, Prof Neil M Ferguson DPhil a


Summary

Background

The novel Middle East respiratory syndrome coronavirus (MERS-CoV) had, as of Aug 8, 2013, caused 111 virologically confirmed or probable human cases of infection worldwide. We analysed epidemiological and genetic data to assess the extent of human infection, the performance of case detection, and the transmission potential of MERS-CoV with and without control measures.


Methods

We assembled a comprehensive database of all confirmed and probable cases from public sources and estimated the incubation period and generation time from case cluster data. Using data of numbers of visitors to the Middle East and their duration of stay, we estimated the number of symptomatic cases in the Middle East. We did independent analyses, looking at the growth in incident clusters, the growth in viral population, the reproduction number of cluster index cases, and cluster sizes to characterise the dynamical properties of the epidemic and the transmission scenario.


Findings

The estimated number of symptomatic cases up to Aug 8, 2013, is 940 (95% CI 290?2200), indicating that at least 62% of human symptomatic cases have not been detected. We find that the case-fatality ratio of primary cases detected via routine surveillance (74%; 95% CI 49?91) is biased upwards because of detection bias; the case-fatality ratio of secondary cases was 20% (7?42). Detection of milder cases (or clinical management) seemed to have improved in recent months. Analysis of human clusters indicated that chains of transmission were not self-sustaining when infection control was implemented, but that R in the absence of controls was in the range 0?8?1?3. Three independent data sources provide evidence that R cannot be much above 1, with an upper bound of 1?2?1?5.


Interpretation

By showing that a slowly growing epidemic is underway either in human beings or in an animal reservoir, quantification of uncertainty in transmissibility estimates, and provision of the first estimates of the scale of the epidemic and extent of case detection biases, we provide valuable information for more informed risk assessment.


Funding

Medical Research Council, Bill & Melinda Gates Foundation, EU FP7, and National Institute of General Medical Sciences.
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a MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, UK; b Institute of Evolutionary Biology, Ashworth Laboratories, University of Edinburgh, Edinburgh, UK; c Institut Pasteur, Unit of Molecular Genetics of RNA Viruses, UMR3569 CNRS, Universit? Paris Diderot Sorbonne Paris Cit?, Paris, France

Correspondence to: Prof Neil M Ferguson, MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, Norfolk Place, London W2 1PG, UK

? These authors contributed equally to this study


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[Giuseppe]

Re: Researchers sound warning on MERS virus: Only a fraction of cases are being detected, study suggests

[Source: The Lancet Infectious Diseases, full page: (LINK). Edited.]


The Lancet Infectious Diseases, Early Online Publication, 13 November 2013

doi:10.1016/S1473-3099(13)70283-4

Copyright © 2013 Fisman et al. Open Access article distributed under the terms of CC BY-NC-ND Published by Elsevier Ltd. All rights reserved.

The epidemiology of MERS-CoV

Original Text

David N Fisman a, Ashleigh R Tuite a
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“The oldest and strongest emotion of mankind is fear, and the oldest and strongest kind of fear is fear of the unknown”, Howard Phillips Lovecraft
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Coping with, and trying to understand, emerging epidemics has been part of the human experience since time immemorial. The concern that attends the emergence of a novel infectious disease might be substantial, but fears often subside as the disease becomes better understood, partly because initial findings tend to be biased towards cases and case clusters with more severe outcomes.1—3 Epidemiologists and microbiologists are currently working to better characterise the outbreak of Middle Eastern respiratory syndrome (MERS) coronavirus infection that made its initial appearance in a health-care-based outbreak in Jordan in 2012.4 The understanding of the natural history and epidemiology of an emerging infectious disease allows us to predict its behaviour and identify control strategies. In The Lancet Infectious Diseases, the study by Simon Cauchemez and colleagues5 is timely and important, since it provides us with such information about the emerging MERS outbreak.

We were impressed by the extent to which Cauchemez and co-authors did their analyses using limited publicly available data. Whereas decision makers often ask infectious disease modellers to provide an epidemiological crystal ball that shows what will happen, these investigators use modelling more appropriately, as a method for the quantification and management of uncertainty. What does their analysis tell us?

A key epidemiological parameter early in an emerging epidemic is the basic reproductive number (R0), which describes the average number of new cases of infection generated by one primary case in a susceptible population.6 R0 affects the growth rate of an outbreak and the total number of people infected by the end of the outbreak. When R0 is lower than 1, a sustained epidemic will not occur. Using epidemiological and genetic data, the authors estimated that R0 was small (consistent with earlier estimates),7, 8 but might be slightly greater than 1. However, R0 estimates based on disease cluster sizes were lower than 1, suggesting that cluster identification leads to application of successful control measures. Using data on MERS-infected travellers returning from the Middle East, the investigators estimated MERS incidence, and back-calculated the likely extent of case underreporting; they estimated that most cases have been undetected.

These findings suggest that mildly symptomatic cases are common, with implications for the effectiveness of infection control measures. They also show us that the MERS outbreak represents a dynamic process, with human incidence possibly portraying transmission from animal to man occurring in the context of an as yet unconfirmed epizootic.

The distance between the raw, publicly available, epidemiological and virological data obtained by the authors, and the insights provided by them in their report can represent the distance between abundant information and actionable knowledge. The quality of data available to these authors is poor, but should that have prevented them from proceeding with analysis until better data were available? We do not think so: inferences based on the best available data, even if those data are imperfect, allow decision makers to follow optimum courses of action based on what is known at a given point in time. Could the estimates presented here be refined if more complete data were to become available? Undoubtedly, and it seems likely that these investigators and others will continue to do so as this disease is further studied.

The widespread, transparent, and trans-jurisdictional sharing of epidemiological data in the context of public health emergencies could improve the accuracy of early efforts at epidemiological synthesis, such as those presented here by Cauchemez and colleagues.5 However, many disincentives for such sharing by jurisdictions experiencing outbreaks remain, including lost travel and tourism, concerns about data security, and interest in scientific publication. Creative epidemiologists and computer scientists have shown various means to infer levels of disease activity with indirect Internet data mining techniques.9—11 The ability to draw inferences about diseases from non-traditional data sources will hopefully both provide alternate means of characterising epidemics, and diminish the temptation towards non-transparency in traditional public health authorities. The resultant improvements in rapid epidemiological risk estimates would benefit all of us.

We declare that we have no conflicts of interest.


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8. ProMED Mail, PRO/AH/EDR> MERS-CoV - Eastern Mediterranean (11): Saudi Arabia, new death. [4] Transmissibility and cluster sizes. ProMED-mail 2013; May 27: 20130527.1738597. http://www.promedmail.org. (accessed Sept 7, 2013).
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a Dalla Lana School of Public Health, University of Toronto, 155 College Street, Room 586, Toronto, ON M5T 3M7, Canada


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