The chemical disinfection of virus-contaminated non-porous inanimate surfaces was investigated using coxsackievirus B3, adenovirus type 5, parainfluenzavirus type 3 and coronavirus 229E as representatives of important nosocomial viral pathogens. A 10 µl amount of the test virus, suspended in either faeces or mucin, was placed onto each stainless steel disk (about 1 cm in diameter) and the inoculum allowed to dry for 1 h under ambient conditions. Sixteen disinfectant formulations were selected for this study based on the findings of an earlier investigation with a human rotavirus.After 1 min exposure to 20 µl of the disinfectant, the virus from the disks was immediately eluted into tryptose phosphate broth and plaque assayed. Using an efficacy criterion of a 3 log10 or greater reduction in virus infectivity titre and irrespective of the virus suspending medium, only the following five disinfectants proved to be effective against all the four viruses tested: (1) 2% glutaraldehyde normally used as an instrument soak.(2) a strongly alkaline mixture of 0·5% sodium o-benzyl-p-chlorophenate and 0·6% sodium lauryl sulphate, generally used as a domestic disinfectant cleaner for hard surfaces, (3) a 0·04% solution of a quaternary ammonium compound containing 7% hydrochloric acid, which is the basis of many toilet bowl cleaners. (4) chloraminc T at a minimum free chlorine level of 3000 p.p.m. and (5) sodium hypochlorite at a minimum free chlorine concentration of 5000 p.p.m. Of those chemicals suitable for use as topical antiseptics, 70% ethanol alone or products containing at least 70% ethanol were ineffective only against coxsackievirus B3. These results emphasize the care needed in selecting chemical disinfectants for routine use in infection control.

The ability of three avian viruses to elicit antibody response in humans was surveyed for the purpose of identifying zoonotic diseases. Antibody levels in people associated with poultry were compared to those in people having limited poultry association. Antibody levels to three avian viruses: infectious bursal disease virus, a birnavirus; Newcastle disease virus, a paramyxovirus; and avian infectious bronchitis virus, a coronavirus were determined by enzyme–linked immunosorbent assays (ELISA). Differences between the two study groups were evident: people having a known association with poultry showed significantly higher levels of antibodies to Newcastle disease and avian infectious bronchitis virus. Antibodies detected may be due to virus exposure rather than zoonoses.

From 1985 to 1988, a total of 2496 swine sera from 60 farms in the Tohoku District of the Honshu Island of Japan were examined for antibodies to swine haemagglutinating encephalomyelitis virus (HEV), human coronavirus (HCV) and bovine coronavirus (BCV) by haemagglutination-inhibition (HI) test. Antibodies to HEV 67N strain and HCV OC43 strain were highly prevalent with positivity rates of 82·1 and 91·4%, respectively, while seropositivity rate to BCV Kakegawa strain was 44·2%. No clinical signs of HEV infection were noticed in any farms including farms with relatively high seropositivity. The results suggested that HCV or antigenitically related virus(es) as well as HEV might be perpetuated in swine in the Tohoku District.

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.

The hamadryas baboon (Papio hamadryas hamadryas) is the only indigenous species of non-human primates (NHP) found in the Kingdom of Saudi Arabia (KSA). There are no peer-reviewed publications on viral infections of the baboons of KSA. Apart from camels, other animals are likely sources of the novel Middle East Respiratory Syndrome coronavirus (MERSCoV) for humans. We investigated evidence of highly pathogenic coronavirus infections including MERSCoV in a large group of commensal baboons accompanied by feral dogs, on the outskirts of Ta'if city, KSA, in February 2013. Fifty baboons (16 juveniles and 34 adults) were screened for serum antibodies to human coronaviruses (HCoV-043/-NL63/-229) and canine coronaviruses (CCoV-1-3) using direct Enzyme-linked Immunosorbent Assay (ELISA) technique and for MERSCoV antibodies using Serum Neutralization Test (SNT). Of the 50 sampled baboons, 22% (n = 11) were seropositive to HCoVs, 10% (n = 5) were seropositive to CCoVs, while none had detectable MERSCoV antibodies. These findings bear potentially significant implications for public health, canine health and baboon conservation efforts, necessitating follow-up investigations and preventive measures at locations where baboons frequent human habitations, or are regarded as tourist attractions, in KSA.

Understanding viral transmission dynamics within populations of reservoir hosts can facilitate greater knowledge of the spillover of emerging infectious diseases. While bat-borne viruses are of concern to public health, investigations into their dynamics have been limited by a lack of longitudinal data from individual bats. Here, we examine capture–mark–recapture (CMR) data from a species of Australian bat (Myotis macropus) infected with a putative novel Alphacoronavirus within a Bayesian framework. Then, we developed epidemic models to estimate the effect of persistently infectious individuals (which shed viruses for extensive periods) on the probability of viral maintenance within the study population. We found that the CMR data analysis supported grouping of infectious bats into persistently and transiently infectious bats. Maintenance of coronavirus within the study population was more likely in an epidemic model that included both persistently and transiently infectious bats, compared with the epidemic model with non-grouping of bats. These findings, using rare CMR data from longitudinal samples of individual bats, increase our understanding of transmission dynamics of bat viral infectious diseases.

Viral respiratory infections continue to pose a major global healthcare burden. At the community level, the co-circulation of respiratory viruses is common and yet studies generally focus on single aetiologies. We conducted the first comprehensive epidemiological analysis to encompass all major respiratory viruses in a single population. Using extensive multiplex PCR diagnostic data generated by the largest NHS board in Scotland, we analysed 44230 patient episodes of respiratory illness that were simultaneously tested for 11 virus groups between 2005 and 2013, spanning the 2009 influenza A pandemic. We measured viral infection prevalence, described co-infections, and identified factors independently associated with viral infection using multivariable logistic regression. Our study provides baseline measures and reveals new insights that will direct future research into the epidemiological consequences of virus co-circulation. In particular, our study shows that (i) human coronavirus infections are more common during influenza seasons and in co-infections than previously recognized, (ii) factors associated with co-infection differ from those associated with viral infection overall, (iii) virus prevalence has increased over time especially in infants aged <1 year, and (iv) viral infection risk is greater in the post-2009 pandemic era, likely reflecting a widespread change in the viral population that warrants further investigation.

We conducted prospective, community-wide surveillance for acute respiratory illnesses (ARIs) in Rochester, NY and Marshfield, WI during a 3-month period in winter 2011. We estimated the incidence of ARIs in each community, tested for viruses, and determined the proportion of ARIs associated with healthcare visits. We used a rolling cross-sectional design to sample participants, conducted telephone interviews to assess ARI symptoms (defined as a current illness with feverishness or cough within the past 7 days), collected nasal/throat swabs to identify viruses, and extracted healthcare utilization from outpatient/inpatient records. Of 6492 individuals, 321 reported an ARI within 7 days (4·9% total, 5·7% in Rochester, 4·4% in Marshfield); swabs were collected from 208 subjects. The cumulative ARI incidence for the entire 3-month period was 52% in Rochester [95% confidence interval (CI) 42–63] and 35% in Marshfield (95% CI 28–42). A specific virus was identified in 39% of specimens: human coronavirus (13% of samples), rhinovirus (12%), RSV (7%), influenza virus (4%), human metapneumovirus (4%), and adenovirus (1%). Only 39/200 (20%) had a healthcare visit (2/9 individuals with influenza). ARI incidence was ~5% per week during winter.

Bovine calf scours reported to be caused by multiple aetiologies resulting in heavy mortality in unweaned calves and huge economic loss to the dairy farmers. Among these, cryptosporidiosis is an emerging waterborne zoonoses and one of the important causes of neonatal calf diarrhoea. Poor immune response coupled with primary cryptosporidial infections predispose neonatal calves to multiple secondary infections resulting in their deaths. In the present study, faecal samples from 100 diarrhoeic calves randomly picked up out of 17 outbreaks of bovine calf diarrhoea in periurban Ludhiana, Punjab in Northern India were subjected to conventional (microscopy, modified Zeihl–Neelsen (mZN) staining) and immunological and molecular techniques (faecal antigen capture ELISA and PCR) for detection of primary Cryptosporidium parvum infection as well as other frequently reported concurrent pathogens, viz. rotavirus and coronavirus, Salmonella spp., Escherichia coli, Clostridium perfringens and Eimeria spp. The faecal antigen capture ELISA and PCR revealed 35% prevalence of C. parvum in contrast to 25% by mZN staining with a relatively higher prevalence (66·7%) in younger (8–14-day-old) calves. The detection rate of the other enteropathogens associated with C. parvum was 45·71% for C. perfringens followed by Salmonella spp (40·0%), rotavirus (36·0%), coronavirus (16·0%), E. coli (12·0%) and Eimeria spp (4·0%) The sensitivity for detection of C. parvum by ELISA and mZN staining in comparison to PCR was 97·14% and 72·72%, respectively. An important finding of the study was that C. parvum alone was found in only 10% of the diarrhoeic faecal samples, whereas, majority of the samples (90%) showed mixed infections ranging from a combination of two to five agents. This is the first documentary proof of C. parvum and associated pathogens responsible for severe periurban outbreaks of bovine calf diarrhoea culminating in heavy mortality from Northern India.

System dynamics approach offers great potential for addressing how intervention policies can affect the spread of emerging infectious diseases in complex and highly networked systems. Here, we develop a model that explains the severe acute respiratory syndrome coronavirus (SARS-CoV) epidemic that occurred in Hong Kong in 2003. The dynamic model developed with system dynamics methodology included 23 variables (five states, four flows, eight auxiliary variables, six parameters), five differential equations and 12 algebraic equations. The parameters were optimized following an iterative process of simulation to fit the real data from the epidemics. Univariate and multivariate sensitivity analyses were performed to determine the reliability of the model. In addition, we discuss how further testing using this model can inform community interventions to reduce the risk in current and future outbreaks, such as the recently Middle East respiratory syndrome coronavirus (MERS-CoV) epidemic.

The Middle East respiratory syndrome coronavirus (MERS-CoV) is caused by a novel coronavirus discovered in 2012. Since then, 1806 cases, including 564 deaths, have been reported by the Kingdom of Saudi Arabia (KSA) and affected countries as of 1 June 2016. Previous literature attributed increases in MERS-CoV transmission to camel breeding season as camels are likely the reservoir for the virus. However, this literature review and subsequent analysis indicate a lack of seasonality. A retrospective, epidemiological cluster analysis was conducted to investigate increases in MERS-CoV transmission and reports of household and nosocomial clusters. Cases were verified and associations between cases were substantiated through an extensive literature review and the Armed Forces Health Surveillance Branch's Tiered Source Classification System. A total of 51 clusters were identified, primarily nosocomial (80·4%) and most occurred in KSA (45·1%). Clusters corresponded temporally with the majority of periods of greatest incidence, suggesting a strong correlation between nosocomial transmission and notable increases in cases.