West Nile Virus (WNV) infection has been reported in over 300 species of birds and mammals. Raptors such as eagles, hawks and falcons are remarkably susceptible, but reports of WNV infection in Bald Eagles (Haliaeetus leucocephalus) are rare and reports of WNV infection in grebes (Podicipediformes) even rarer. We report an unusually large wild bird mortality event involving between 15,000-20,000 Eared Grebes (Podiceps nigricollis) and over 40 Bald Eagles around the Great Salt Lake, Utah, in November-December 2013. Mortality in grebes was first reported in early November during a period when the area was unseasonably warm and the grebes were beginning to gather and stage prior to migration. Ten out of ten Eared Grebes collected during this period were WNV RT-PCR and/or isolation positive. This is the first report of WNV infection in Eared Grebes and the associated mortality event is matched in scale only by the combined outbreaks in American White Pelican (Pelecanus erythrorhynchos) colonies in the north central states in 2002-2003. We cannot be sure that all of the grebes were infected by mosquito transmission; some may have become infected through contact with WNV shed orally or cloacally from other infected grebes. Beginning in early December, Bald Eagles in the Great Salt Lake area were observed to display neurological signs such as body tremors, limb paralysis and lethargy. At least 43 Bald Eagles had died by the end of the month. Nine of nine Bald Eagles examined were infected with WNV. To the best of our knowledge, this is the largest single raptor mortality event since WNV became endemic in the USA. Because the majority of the eagles affected were found after onset of below-freezing temperatures, we suggest at least some of the Bald Eagles were infected with WNV via consumption of infected Eared Grebes or horizontal transmission at roost sites.
The key challenge during food-borne disease outbreaks, e.g. the 2011 EHEC/HUS outbreak in Germany, is the design of efficient mitigation strategies based on a timely identification of the outbreak’s spatial origin. Standard public health procedures typically use case-control studies and tracings along food shipping chains. These methods are time-consuming and suffer from biased data collected slowly in patient interviews. Here we apply a recently developed, network-theoretical method to identify the spatial origin of food-borne disease outbreaks. Thereby, the network captures the transportation routes of contaminated foods. The technique only requires spatial information on case reports regularly collected by public health institutions and a model for the underlying food distribution network. The approach is based on the idea of replacing the conventional geographic distance with an effective distance that is derived from the topological structure of the underlying food distribution network. We show that this approach can efficiently identify most probable epicenters of food-borne disease outbreaks. We assess and discuss the method in the context of the 2011 EHEC epidemic. Based on plausible assumptions on the structure of the national food distribution network, the approach can correctly localize the origin of the 2011 German EHEC/HUS outbreak.
A recrudescent wave of pandemic influenza A/H1N1 is underway in Mexico in winter 2013-14, following a mild 2012-13 A/H3N2 influenza season. Mexico previously experienced several waves of pandemic A/H1N1 activity in spring, summer and fall 2009 and winter 2011-2012, with a gradual shift of influenza-related hospitalizations and deaths towards older ages. Here we describe changes in the epidemiology of the 2013-14 A/H1N1 influenza outbreak, relative to previous seasons dominated by the A/H1N1 pandemic virus. The analysis is intended to guide public health intervention strategies in near real time.
We analyzed demographic and geographic data on hospitalizations with severe acute respiratory infection (SARI), laboratory-confirmed A/H1N1 influenza hospitalizations, and inpatient deaths, from a large prospective surveillance system maintained by the Mexican Social Security medical system during 01-October 2013 to 31-Jan 2014. We characterized the age and regional patterns of influenza activity relative to the preceding 2011-2012 A/H1N1 influenza epidemic. We also estimated the reproduction number (R) based on the growth rate of daily case incidence by date of symptoms onset.
A total of 7,886 SARI hospitalizations and 529 inpatient-deaths (3.2%) were reported between 01-October 2013 and 31-January 2014 (resulting in 3.2 laboratory-confirmed A/H1N1 hospitalizations per 100,00 and 0.52 laboratory-confirmed A/H1N1-positive deaths per 100,000). The progression of daily SARI hospitalizations in 2013-14 exceeded that observed during the 2011-2012 A/H1N1 epidemic. The mean age of laboratory-confirmed A/H1N1 patients in 2013-14 was 41.1 y (SD=20.3) for hospitalizations and 49.2 y (SD=16.7) for deaths. Rates of laboratory-confirmed A/H1N1 hospitalizations and deaths were significantly higher among individuals aged 30-59 y and lower among younger age groups for the ongoing 2013-2014 epidemic, compared to the 2011-12 A/H1N1 epidemic (Chi-square test, P<0.001). The reproduction number of the winter 2013-14 wave in central Mexico was estimated at 1.3-1.4 which is slightly higher than that reported for the 2011-2012 A/H1N1 epidemic.
We have documented a substantial and ongoing increase in the number of A/H1N1-related hospitalizations and deaths during the period October 2013-January 2014 and a proportionate shift of severe disease to middle aged adults, relative to the preceding A/H1N1 2011-2012 epidemic in Mexico. In the absence of clear antigenic drift in globally circulating A/H1N1 viruses in the post-pandemic period, the gradual change in the age distribution of A/H1N1 infections observed in Mexico suggests a slow build-up of immunity among younger populations, reminiscent of the age profile of past pandemics.
Pathogens such as MERS-CoV, influenza A/H5N1 and influenza A/H7N9 are currently generating sporadic clusters of spillover human cases from animal reservoirs. The lack of a clear human epidemic suggests that the basic reproductive number R0 is below or very close to one for all three infections. However, robust cluster-based estimates for low R0 values are still desirable so as to help prioritise scarce resources between different emerging infections and to detect significant changes between clusters and over time. We developed an inferential transmission model capable of distinguishing the signal of human-to-human transmission from the background noise of direct spillover transmission (e.g. from markets or farms). By simulation, we showed that our approach could obtain unbiased estimates of R0, even when the temporal trend in spillover exposure was not fully known, so long as the serial interval of the infection and the timing of a sudden drop in spillover exposure were known (e.g. day of market closure). Applying our method to data from the three largest outbreaks of influenza A/H7N9 outbreak in China in 2013, we found evidence that human-to-human transmission accounted for 13% (95% credible interval 1%–32%) of cases overall. We estimated R0 for the three clusters to be: 0.19 in Shanghai (0.01-0.49), 0.29 in Jiangsu (0.03-0.73); and 0.03 in Zhejiang (0.00-0.22). If a reliable temporal trend for the spillover hazard could be estimated, for example by implementing widespread routine sampling in sentinel markets, it should be possible to estimate sub-critical values of R0 even more accurately. Should a similar strain emerge with R0>1, these methods could give a real-time indication that sustained transmission is occurring with well-characterised uncertainty.
An outbreak of PVL-positive MSSA skin and soft tissue-infections (SSTIs) was suspected in May 2010 when recurrent SSTI was diagnosed in an inmate of a large prison in Nantes, France.
Methods and findings.
Retrospective and prospective investigations were performed. Microbiological characterisation was by DNA microarray testing (S. aureus genotyping – Identibac, Alere). We identified 14 inmates meeting our clinical and microbiological case definition for PVL-MSSA SSTI between March 2010 and April 2011. The SSTIs developed in tattooed areas in 4 patients and in areas shaved daily with a mechanical razor in 4 other patients. All case isolates exhibited a similar SmaI pulsed-field gel electrophoresis pattern. Microarray analysis showed that all 14 isolates harboured genes encoding PVL and enterotoxins (A, H, K, and Q) and belonged to clonal complex 1 (CC1). Individual and collective hygiene measures, education delivered to inmates and prison employees, and antibiotic treatment of SSTIs were successful in controlling the outbreak. No new cases were identified after April 2011. Routine screening for PVL-positive MSSA carriage was not feasible.
Our data suggest that tattooing and shaving with mechanical razors may constitute risk factors for SSTIs among previously colonised inmates and contribute to the PVL-MSSA outbreak in the prison. Allowing inmates access to professional tattooists and to the hygiene and safety conditions available to people in the community would help to prevent tattoo-related infections.
We have identified environmental and demographic variables, available in January, that predict the relative magnitude and spatial distribution of West Nile virus (WNV) for the following summer. The yearly magnitude and spatial distribution for WNV incidence in humans in the United States (US) have varied wildly in the past decade. Mosquito control measures are expensive and having better estimates of the expected relative size of a future WNV outbreak can help in planning for the mitigation efforts and costs. West Nile virus is spread primarily between mosquitoes and birds; humans are an incidental host. Previous efforts have demonstrated a strong correlation between environmental factors and the incidence of WNV. A predictive model for human cases must include both the environmental factors for the mosquito-bird epidemic and an anthropological model for the risk of humans being bitten by a mosquito. Using weather data and demographic data available in January for every county in the US, we use logistic regression analysis to predict the probability that the county will have at least one WNV case the following summer. We validate our approach and the spatial and temporal WNV incidence in the US from 2005 to 2013. The methodology was applied to forecast the 2014 WNV incidence in late January 2014. We find the most significant predictors for a county to have a case of WNV to be the mean minimum temperature in January, the deviation of this minimum temperature from the expected minimum temperature, the total population of the county, publicly available samples of local bird populations, and if the county had a case of WNV the previous year.
Stemming from the 2010 cholera outbreak in Haiti, cholera transmission in Hispaniola continues with over 40,000 cases in 2013. The presence of an ongoing cholera outbreak in the region poses substantial risks to countries throughout the Americas, particularly in areas with poor infrastructure. Since September 9, 2013 nearly 200 cholera cases have been reported in Mexico, as a result of introductions from Hispaniola or Cuba. There appear to have been multiple introductions into Mexico resulting in outbreaks of 2 to over 150 people. Using publicly available data, we attempt to estimate the reproductive number (R) of cholera in Mexico, and thereby assess the potential of continued introductions to establish a sustained epidemic. We estimate R for cholera in Mexico to be between 0.8 to 1.1, depending on the number of introductions, with the confidence intervals for the most plausible estimates crossing 1. These results suggest that the efficiency of cholera transmission in some regions of Mexico is near that necessary for a large epidemic. Intensive surveillance, evaluation of water and sanitation infrastructure, and planning for rapid response are warranted steps to avoid potential large epidemics in the region.
The incidence of bovine tuberculosis (TB) in Great Britain has generally been increasing in recent decades. Routine ante-mortem testing of cattle herds is required for disease surveillance and control, due to the asymptomatic nature of the infection. The Department for Environment, Food and Rural Affairs (Defra) publishes TB incidence trends as the percentage of officially TB-free (OTF) herds tested per month with OTF status withdrawn due to post-mortem evidence of infection. This method can result in artefactual fluctuations. We have previously demonstrated an alternative method, that distributes incidents equally over the period of risk, provides a more accurate representation of underlying risk. However, this method is complex and it may not be sufficiently straightforward for use in the national statistics. Here we present a simple incidence-based method that adjusts for the time between tests and show it can provide a reasonable representation of the underlying risk without artefactual fluctuations.
The emergence of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) in the eastern Mediterranean and imported cases to Europe has alerted public health authorities. Currently, detection of MERS-CoV in patient samples is done by real-time RT-PCR. Samples collected from suspected cases are sent to highly-equipped centralized laboratories for screening. A rapid point-of-care test is needed to allow more widespread mobile detection of the virus directly from patient material. In this study, we describe the development of a reverse transcription isothermal Recombinase Polymerase Amplification (RT-RPA) assay for the identification of MERS-CoV. A partial nucleocapsid gene RNA molecular standard of MERS-coronavirus was used to determine the assay sensitivity. The isothermal (42°C) MERS-CoV RT-RPA was as sensitive as real-time RT-PCR (10 RNA molecules), rapid (3-7 minutes) and mobile (using tubescanner weighing 1kg). The MERS-CoV RT-RPA showed cross-detection neither of any of the RNAs of several coronaviruses and respiratory viruses affecting humans nor of the human genome. The developed isothermal real-time RT-RPA is ideal for rapid mobile molecular MERS-CoV monitoring in acute patients and may also facilitate the search for the animal reservoir of MERS-CoV.
A novel coronavirus, MERS-CoV (NCoV, HCoV-EMC/2012), originating from the Middle-East, has been discovered. Incoming data reveal that the virus is highly virulent to humans. A model that categorizes coronaviuses according to the hardness of their shells was developed before the discovery of MERS-CoV. Using protein intrinsic disorder prediction, coronaviruses were categorized into three groups that can be linked to the levels of oral-fecal and respiratory transmission regardless of genetic proximity. Using this model, MERS-CoV is placed into disorder group C, which consists of coronaviruses that have relatively hard inner and outer shells. The members of this group are likely to persist in the environment for a longer period of time and possess the highest oral-fecal components but relatively low respiratory transmission components. Oral-urine and saliva transmission are also highly possible since both require harder protective shells. Results show that disorder prediction can be used as a tool that suggests clues to look for in further epidemiological investigations.