This study set out to identify and analyse trends and seasonal variations of monthly global reported cases of the Middle East respiratory syndrome coronavirus (MERS-CoV). It also made a prediction based on the reported and extrapolated into the future by forecasting the trend. Finally, the study assessed contributions of various risk factors in the reported cases. The motivation for this study is that MERS-CoV remains among the list of blueprint priority and potential pandemic diseases globally. Yet, there is a paucity of empirical literature examining trends and seasonality as the available evidence is generally descriptive and anecdotal. The study is a time series analysis using monthly global reported cases of MERS-CoV by the World Health Organisation between January 2015 and January 2018. We decomposed the series into seasonal, irregular and trend components and identified patterns, smoothened series, generated predictions and employed forecasting techniques based on linear regression. We assessed contributions of various risk factors in MERS-CoV cases over time. Successive months of the MERS-CoV cases suggest a significant decreasing trend (P = 0.026 for monthly series and P = 0.047 for Quarterly series). The MERS-CoV cases are forecast to wane by end 2018. Seasonality component of the cases oscillated below or above the baseline (the centred moving average), but no association with the series over time was noted. The results revealed contributions of risk factors such as camel contact, male, old age and being from Saudi Arabia and Middle East regions to the overall reported cases of MERS-CoV. The trend component and several risk factors for global MERS-CoV cases, including camel contact, male, age and geography/region significantly affected the series. Our statistical models appear to suggest significant predictive capacity and the findings may well inform healthcare practitioners and policymakers about the underlying dynamics that produced the globally reported MERS-CoV cases.

Our objective was to identify predictors of severe acute respiratory infection in hospitalised patients and understand the impact of vaccination and neuraminidase inhibitor administration on severe influenza. We analysed data from a study evaluating influenza vaccine effectiveness in two Michigan hospitals during the 2014–2015 and 2015–2016 influenza seasons. Adults admitted to the hospital with an acute respiratory infection were eligible. Through patient interview and medical record review, we evaluated potential risk factors for severe disease, defined as ICU admission, 30-day readmission, and hospital length of stay (LOS). Two hundred sixteen of 1119 participants had PCR-confirmed influenza. Frailty score, Charlson score and tertile of prior-year healthcare visits were associated with LOS. Charlson score >2 (OR 1.5 (1.0–2.3)) was associated with ICU admission. Highest tertile of prior-year visits (OR 0.3 (0.2–0.7)) was associated with decreased ICU admission. Increasing tertile of visits (OR 1.5 (1.2–1.8)) was associated with 30-day readmission. Frailty and prior-year healthcare visits were associated with 30-day readmission among influenza-positive participants. Neuraminidase inhibitors were associated with decreased LOS among vaccinated participants with influenza A (HR 1.6 (1.0–2.4)). Overall, frailty and lack of prior-year healthcare visits were predictors of disease severity. Neuraminidase inhibitors were associated with reduced severity among vaccine recipients.

The Arizona Department of Health Services identified unusually high levels of influenza activity and severe complications during the 2015–2016 influenza season leading to concerns about potential increased disease severity compared with prior seasons. We estimated state-level burden and severity to compare across three seasons using multiple data sources for community-level illness, hospitalisation and death. Severity ratios were calculated as the number of hospitalisations or deaths per community case. Community influenza-like illness rates, hospitalisation rates and mortality rates in 2015–2016 were higher than the previous two seasons. However, ratios of severe disease to community illness were similar. Arizona experienced overall increased disease burden in 2015–2016, but not increased severity compared with prior seasons. Timely estimates of state-specific burden and severity are potentially feasible and may provide important information during seemingly unusual influenza seasons or pandemic situations.

Retrospective data evaluated increases in advanced medical support for children with medically attended acute respiratory illness (MAARI) during influenza outbreak periods (IOP). Advanced support included hospitalisation, intensive care unit admission, or mechanical ventilation, for children aged 0–17 years hospitalised in Maryland's 50 acute-care hospitals over 12 influenza seasons. Weekly numbers of positive influenza tests in the Maryland area defined IOP for each season as the fewest consecutive weeks, including the peak week containing at least 85% of positive tests with a 2-week buffer on either side of the IOP. Peak IOP (PIOP) was defined as four consecutive weeks containing the peak week with the most number of positive influenza tests. Off-PIOP was defined as the ‘shoulder’ weeks during each IOP. Non-influenza season (NIS) was the remaining weeks of that study season. Rate ratios of mean daily MAARI-related admissions resulting in advanced medical support outcomes during PIOP or Off-PIOP were compared with the NIS and were significantly elevated for all 12 study seasons combined. The results suggest that influenza outbreaks are associated with increased advanced medical support utilisation by children with MAARI. We feel that this data may help preparedness for severe influenza epidemics or pandemic.

Previously we reported on the HPIV2 genotype distribution in Croatia 2011–2014. Here we expand this period up to 2017 and confirm that G1a genotype has replaced G3 genotype from the period 2011–2014. Our hypothesis was that the G1a-to-G3 genotype replacement is an antibody-driven event. A cross-neutralisation with anti-HPIV2 sera specific for either G1a or G3 genotype revealed the presence of genotype-specific antigenic determinants. By the profound, in silico analyses three potential B cell epitopic regions were identified in the hemagglutinin neuraminidase (regions 314–361 and 474–490) and fusion protein (region 440–484). The region identified in the fusion protein does not show any unique site between the G1a and G3 isolates, five differentially glycosylated sites in the G1a and G3 genotype isolates were identified in epitopic regions of hemagglutinin neuraminidase. All positively selected codons were found to be located either in the region 314–316 or in the region 474–490 what indicates a strong positive selection in this region and reveals that these regions are susceptible to evolutionary pressure possibly caused by antibodies what gives a strong verification to our hypothesis that neutralising antibodies are a key determinant in the inherently complex adaptive evolution of HPIV2 in the region.

To investigate the impact of viral and bacterial co-infection in hospitalised children with Mycoplasma pneumoniae pneumonia (RMPP). Retrospective analysis of 396 children with RMPP in our hospital admitted between 1 January 2011 and 31 December 2016 was performed. Nasal aspirate samples were collected for pathogen detection and clinical data were collected. We analysed clinical characteristics, lung imaging characteristics and pathogenic species among these children. Of the 396 RMPP cases, 107 (27.02%) had co-infection with other pathogen, with Streptococcus pneumoniae, Haemophilus influenzae and Staphylococcus aureus being the most common bacteria of infection and human bocavirus (HBoV), human rhinovirus, respiratory syncytial virus being the most common viruses of infection. Children with co-infection were younger than that with single infection (P = 0.010). Children with both virus and bacteria co-infection had been the youngest (P = 0.040). Children with co-infection had a longer fever process, higher leukocyte count, higher C-reactive protein compared with single infection (P < 0.05). Children with co-infection had a higher percentage of pnemothorax and diffuse large area of inflammation in chest X-ray manifestation compared with children with single infection (P < 0.05). S. pneumonia and HBoV was the leading cause of co-infection in RMPP. Co-infections led to more disease severity in children with RMPP compared with single infections.

Understanding the burden of respiratory pathogens on health care is key to improving public health emergency response and interventions. In temperate regions, there is a large seasonal rise in influenza and other respiratory pathogens. We have examined the associations between individual pathogens and reported respiratory tract infections to estimate attributable burden. We used multiple linear regression to model the relationship between doctor consultation data and laboratory samples from week 3 2011 until week 37 2015. We fitted separate models for consultation data with in-hours and out-of-hours doctor services, stratified by different age bands. The best fitting all ages models (R2 > 80%) for consultation data resulted in the greatest burden being associated with influenza followed by respiratory syncytial virus (RSV). For models of adult age bands, there were significant associations between consultation data and invasive Streptococcus pneumoniae. There were also smaller numbers of consultations significantly associated with rhinovirus, parainfluenza, and human metapneumovirus. We estimate that a general practice with 10 000 patients would have seen an additional 18 respiratory tract infection consultations per winter week of which six had influenza and four had RSV. Our results are important for the planning of health care services to minimise the impact of winter pressures.

• • Respiratory pathogen incidence explains over 80% of seasonal variation in respiratory consultation data.

• • Influenza and RSV are associated with the biggest seasonal rises in respiratory consultation counts.

• • A third of consultation counts associated with respiratory pathogens were due to influenza.

The US Food Safety Modernization Act (FSMA) gives food safety regulators increased authority to require implementation of safety measures to reduce the contamination of produce. To evaluate the future impact of FSMA on food safety, a better understanding is needed regarding outbreaks attributed to the consumption of raw produce. Data reported to the US Centers for Disease Control and Prevention's Foodborne Disease Outbreak Surveillance System during 1998–2013 were analysed. During 1998–2013, there were 972 raw produce outbreaks reported resulting in 34 674 outbreak-associated illnesses, 2315 hospitalisations, and 72 deaths. Overall, the total number of foodborne outbreaks reported decreased by 38% during the study period and the number of raw produce outbreaks decreased 19% during the same period; however, the percentage of outbreaks attributed to raw produce among outbreaks with a food reported increased from 8% during 1998–2001 to 16% during 2010–2013. Raw produce outbreaks were most commonly attributed to vegetable row crops (38% of outbreaks), fruits (35%) and seeded vegetables (11%). The most common aetiologic agents identified were norovirus (54% of outbreaks), Salmonella enterica (21%) and Shiga toxin-producing Escherichia coli (10%). Food-handling errors were reported in 39% of outbreaks. The proportion of all foodborne outbreaks attributable to raw produce has been increasing. Evaluation of safety measures to address the contamination on farms, during processing and food preparation, should take into account the trends occurring before FSMA implementation.

Since 2012–2016 an increased number of listeriosis cases, especially from one region of the Czech Republic, were observed. Most of them were caused by strains of serotype 1/2a, clonal complex 8, indistinguishable by pulsed-field gel electrophoresis. Twenty-six human cases were reported, including two neonatal cases in twins. Three cases were fatal. The typing of Listeria monocytogenes isolates from food enabled to confirm a turkey meat delicatessen as the vehicle of infection for this local outbreak in the Moravian-Silesian Region. The food strains belonging to identical pulsotype were isolated from ready-to-eat turkey meat products packaged by the same producer between 2012 and 2016. This fact confirms that the described L. monocytogenes outbreak strain probably persisted in the environment of the aforementioned food-processing plant over several years. Whole-genome sequencing confirmed a very close relationship (zero to seven different alleles) between isolates from humans, foods and swabs from the environment of the food-processing plant under investigation.

Cryptosporidium is a protozoan parasite that causes the diarrhoeal disease, cryptosporidiosis. Although many species have been identified, the majority of human disease worldwide is caused by two species; Cryptosporidium parvum and Cryptosporidium hominis. In Australia, data from the National Notifiable Diseases Surveillance System (NNDSS) show that cryptosporidiosis outbreaks occur every few years. To better understand the transmission, trends and nature of cryptosporidiosis outbreaks in Western Australia, epidemiological and genomic data from three cryptosporidiosis outbreaks in 2003, 2007 and 2011 were reviewed. The 2007 outbreak was the largest (n = 607) compared with the outbreaks in 2003 (n = 404) and 2011 (n = 355). All three outbreaks appeared to have occurred predominantly in the urban metropolitan area (Perth), which reported the highest number of case notifications; increases in case notifications were also observed in rural and remote areas. Children aged 0–4 years and non-Aboriginal people comprised the majority of notifications in all outbreaks. However, in the 2003 and 2007 outbreaks, a higher proportion of cases from Aboriginal people was observed in the remote areas. Molecular data were only available for the 2007 (n = 126) and 2011 (n = 42) outbreaks, with C. hominis the main species identified in both outbreaks. Subtyping at the glycoprotein 60 (gp60) locus identified subtype IbA10G2 in 46.3% and 89.5% of C. hominis isolates typed, respectively, in the 2007 and 2011 outbreaks, with the IdA15G1 subtype was identified in 33.3% of C. hominis isolates typed in the 2007 outbreak. The clustering of cases with the IdA15G1 subtype in the remote areas suggests the occurrence of a concurrent outbreak in remote areas during the 2007 outbreak, which primarily affected Aboriginal people. Both the C. hominis IbA10G2 and IdA15G1 subtypes have been implicated in cryptosporidiosis outbreaks worldwide; its occurrence indicates that the mode of transmission in both the 2007 and 2011 outbreaks was anthroponotic. To better understand the epidemiology, sources and transmission of cryptosporidiosis in Australia, genotyping data should routinely be incorporated into national surveillance programmes.

Salmonella Give is a rare serotype across Europe. In October 2016, a national outbreak of S. Give occurred in Malta. We describe the epidemiological, environmental, microbiological and veterinary investigations. Whole-genome sequencing (WGS) was performed on human, food, environmental and veterinary isolates. Thirty-six human cases were reported between October and November 2016, 10 (28%) of whom required hospitalisation. Twenty-six (72%) cases were linked to four restaurants. S. Give was isolated from ready-to-eat antipasti served by three restaurants which were all supplied by the same local food manufacturer. Food-trace-back investigations identified S. Give in packaged bean dips, ham, pork and an asymptomatic food handler at the manufacturer; inspections found inadequate separation between raw and ready-to-eat food during processing. WGS indicated two genetically distinguishable strains of S. Give with two distinct clusters identified; one cluster linked to the local food manufacturer and a second linked to veterinary samples. Epidemiological, environmental and WGS evidence pointed towards cross-contamination of raw and ready-to-eat foods at the local manufacturer as the likely source of one cluster. Severity of illness indicates a high virulence of this specific serotype. To prevent future cases and outbreaks, adherence to food safety practices at manufacturing level need to be reinforced.

As campylobacteriosis is one of the most important foodborne infections, a European Union (EU)-27 level cost-effectiveness model has been developed on the socio-economic costs and benefits of applying certain control measures for the reduction of Campylobacter in broiler meat. This is expected to be a gold standard for food safety policymakers in the EU; hence, the validity of its modelling assumptions is essential. The authors of the present paper conducted an independent review of model input parameters on health and economic burden and found that the model most probably overestimated the burden of human campylobacteriosis. A discounted, quality-adjusted life year (QALY)-based European estimate has been developed for human campylobacteriosis and resulted in 15.23 QALY loss per 1000 human gastroenteritis cases. Country-specific cost of illness estimates have been developed for various countries in the EU-27. Based on these model adaptations, a selected Campylobacter control strategy was re-assessed and its high cost-effectiveness was confirmed at the EU level, and also in all but three Member States. Bacteriocin treatment or vaccination of the animals, two alternative control measures were also re-evaluated, and these strategies seemed to be far less cost-effective than the investigated strategy. Putative barriers to the rapid implementation of the investigated Campylobacter control strategy are discussed, and potential solutions are proposed. Further research is required on stakeholder perspectives pertaining to the realistic barriers and implementation opportunities.

Shigellosis causes significant morbidity and mortality in developing and developed countries, mostly among infants and young children. The World Health Organization estimates that more than one million people die from Shigellosis every year. In order to evaluate trends in Shigellosis in Israel in the years 2002–2015, we analysed national notifiable disease reporting data. Shigella sonnei was the most commonly identified Shigella species in Israel. Hospitalisation rates due to Shigella flexenri were higher in comparison with other Shigella species. Shigella morbidity was higher among infants and young children (age 0–5 years old). Incidence of Shigella species differed among various ethnic groups, with significantly high rates of S. flexenri among Muslims, in comparison with Jews, Druze and Christians. In order to improve the current Shigellosis clinical diagnosis, we developed machine learning algorithms to predict the Shigella species and whether a patient will be hospitalised or not, based on available demographic and clinical data. The algorithms’ performances yielded an accuracy of 93.2% (Shigella species) and 94.9% (hospitalisation) and may consequently improve the diagnosis and treatment of the disease.

Since April 2014 all presumptive Salmonella isolates received by Public Health England (PHE) have been characterised using whole genome sequencing (WGS) and the genomic data generated used to identify clusters of infection. To inform the implementation and development of a national gastrointestinal infection surveillance system based on WGS we have retrospectively identified genetically related clusters of Salmonella Enteritidis and Salmonella Typhimurium infection over a one year period and determined the distribution of these clusters by PHE operational levels. Using a constrained WGS cluster definition based on single nucleotide polymorphism distance, case frequency and temporal spread we demonstrate that the majority of clusters spread to multiple PHE operational levels. The greatest investigative burden is on national level staff investigating small, geographically dispersed clusters. We also demonstrate that WGS identifies long-running, slowly developing clusters that may previously have remained undetected. This analysis also indicates likely increased workload for local health protection teams and will require an operational strategy to balance limited human resources with the public health importance of investigating small, geographically contained clusters of highly related cases. While there are operational challenges to its implementation, integrated cluster detection based on WGS from local to international level will provide further improvements in the identification of, response to and control of clusters of Salmonella spp. with public health significance.

Foodborne non-typhoidal salmonellosis causes approximately 1 million illnesses annually in the USA. In April 2015, we investigated a multistate outbreak of 65 Salmonella Paratyphi B variant L(+) tartrate(+) infections associated with frozen raw tuna imported from Indonesia, which was consumed raw in sushi. Forty-six (92%) of 50 case-patients interviewed ate sushi during the week before illness onset, and 44 (98%) of 45 who specified ate sushi containing raw tuna. Two outbreak strains were isolated from the samples of frozen raw tuna. Traceback identified a single importer as a common source of tuna consumed by case-patients; this importer issued three voluntary recalls of tuna sourced from one Indonesian processor. Four Salmonella Weltevreden infections were also linked to this outbreak. Whole-genome sequencing was useful in establishing a link between Salmonella isolated from ill people and tuna. This outbreak highlights the continuing foodborne illness risk associated with raw seafood consumption, the importance of processing seafood in a manner that minimises contamination with pathogenic microorganisms and the continuing need to ensure imported foods are safe to eat. People at higher risk for foodborne illness should not consume undercooked animal products, such as raw seafood.

Detecting gastrointestinal (GI) infection transmission among men who have sex with men (MSM) in England is complicated by a lack of routine sexual behavioural data. We investigated whether gender distributions might generate signals for increased transmission of GI pathogens among MSM. We examined the percentage male of laboratory-confirmed patient-episodes for patients with no known travel history for 10 GI infections of public health interest in England between 2003 and 2013, stratified by age and region. An adult male excess was observed for Shigella spp. (annual maximum 71% male); most pronounced for those aged 25–49 years and living in London, Brighton and Manchester. An adult male excess was observed every year for Entamoeba histolytica (range 59.8–76.1% male), Giardia (53.1–57.6%) and Campylobacter (52.1–53.5%) and for a minority of years for hepatitis A (max. 69.8%) and typhoidal salmonella (max. 65.7%). This approach generated a signal for excess male episodes for six GI pathogens, including a characterised outbreak of Shigella among MSM. Stratified analyses by geography and age group were consistent with MSM transmission for Shigella. Optimisation and routine application of this technique by public health authorities elsewhere might help identify potential GI infection outbreaks due to sexual transmission among MSM, for further investigation.