Dromedary camels have been shown to be the main reservoir for human Middle East respiratory syndrome (MERS) infections. This systematic review aims to compile and analyse all published data on MERS-coronavirus (CoV) in the global camel population to provide an overview of current knowledge on the distribution, spread and risk factors of infections in dromedary camels. We included original research articles containing laboratory evidence of MERS-CoV infections in dromedary camels in the field from 2013 to April 2018. In general, camels only show minor clinical signs of disease after being infected with MERS-CoV. Serological evidence of MERS-CoV in camels has been found in 20 countries, with molecular evidence for virus circulation in 13 countries. The seroprevalence of MERS-CoV antibodies increases with age in camels, while the prevalence of viral shedding as determined by MERS-CoV RNA detection in nasal swabs decreases. In several studies, camels that were sampled at animal markets or quarantine facilities were seropositive more often than camels at farms as well as imported camels vs. locally bred camels. Some studies show a relatively higher seroprevalence and viral detection during the cooler winter months. Knowledge of the animal reservoir of MERS-CoV is essential to develop intervention and control measures to prevent human infections.

Coronaviruses (CoVs) produce a wide spectrum of disease syndromes in different mammalian and avian host species. These viruses are well-recognized for their ability to change tissue tropism, to hurdle the interspecies barriers and to adapt ecological variations. It is predicted that the inherent genetic diversity of CoVs caused by accumulation of point mutations and high frequency of homologous recombination is the principal determinant of these competences. Several CoVs (e.g. Severe acute respiratory syndrome-CoV, Middle East respiratory syndrome-CoV) have been recorded to cross the interspecies barrier, inducing different disease conditions in variable animal hosts. Bovine CoV (BCoV) is a primary cause of gastroenteritis and respiratory disease in cattle calves, winter dysentery in lactating cows and shipping fever pneumonia in feedlot cattle. Although it has long been known as a restrictive cattle pathogen, CoVs that are closely related to BCoV have been recognized in dogs, humans and in other ruminant species. Biologic, antigenic and genetic analyses of the so-called ‘bovine-like CoVs’ proposed classification of these viruses as host-range variants rather than distinct virus species. In this review, the different bovine-like CoVs that have been identified in domesticated ruminants (water buffalo, sheep, goat, dromedary camel, llama and alpaca) and wild ruminants (deer, wild cattle, antelopes, giraffes and wild goats) are discussed in terms of epidemiology, transmission and virus characteristics. The presented data denote the importance of these viruses in the persistence of BCoV in nature, spread to new geographical zones, and continuous emergence of disease epidemics in cattle farms.

The Middle East respiratory syndrome coronavirus (MERS-CoV) is a life-threatening respiratory disease with a high case fatality rate; however, its risk factors remain unclear. We aimed to explore the influence of demographic factors, clinical manifestations and underlying comorbidities on mortality in MERS-CoV patients. Retrospective chart reviews were performed to identify all laboratory-confirmed cases of MERS-COV infection in Saudi Arabia that were reported to the Ministry of Health of Saudi Arabia between 23 April 2014 and 7 June 2016. Statistical analyses were conducted to assess the effect of sex, age, clinical presentation and comorbidities on mortality from MERS-CoV. A total of 281 confirmed MERS-CoV cases were identified: 167 (59.4%) patients were male and 55 (20%) died. Mortality predominantly occurred among Saudi nationals and older patients and was significantly associated with respiratory failure and shortness of breath. Of the 281 confirmed cases, 160 (56.9%) involved comorbidities, wherein diabetes mellitus, hypertension, ischemic heart disease, congestive heart failure, end-stage renal disease and chronic kidney disease were significantly associated with mortality from MERS-CoV and two or three comorbidities significantly affected the fatality rates from MERS-CoV. The findings of this study show that old age and the existence of underlying comorbidities significantly increase mortality from MERS-CoV.

Middle East respiratory syndrome coronavirus (MERS-CoV) remains a notable disease and poses a significant threat to global public health. The Arabian Peninsula is considered a major global epicentre for the disease and the virus has crossed regional and continental boundaries since 2012. In this study, we focused on exploring the temporal dynamics of MERS-CoV in human populations in the Arabian Peninsula between 2012 and 2017, using publicly available data on case counts and combining two analytical methods. Disease progression was assessed by quantifying the time-dependent reproductive number (TD-Rs), while case series temporal pattern was modelled using the AutoRegressive Integrated Moving Average (ARIMA). We accounted for geographical variability between three major affected regions in Saudi Arabia including Eastern Province, Riyadh and Makkah. In Saudi Arabia, the epidemic size was large with TD-Rs >1, indicating significant spread until 2017. In both Makkah and Riyadh regions, the epidemic progression reached its peak in April 2014 (TD-Rs > 7), during the highest incidence period of MERS-CoV cases. In Eastern Province, one unique super-spreading event (TD-R > 10) was identified in May 2013, which comprised of the most notable cases of human-to-human transmission. Best-fitting ARIMA model inferred statistically significant biannual seasonality in Riyadh region, a region characterised by heavy seasonal camel-related activities. However, no statistical evidence of seasonality was identified in Eastern Province and Makkah. Instead, both areas were marked by an endemic pattern of cases with sporadic outbreaks. Our study suggested new insights into the epidemiology of the virus, including inferences about epidemic progression and evidence for seasonality. Despite the inherent limitations of the available data, our conclusions provide further guidance to currently implement risk-based surveillance in high-risk populations and, subsequently, improve related interventions strategies against the epidemic at country and regional levels.

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.

This study analyzed and assessed publication trends in articles on “disaster medicine,” using scientometric analysis. Data were obtained from the Web of Science Core Collection (WoSCC) of Thomson Reuters on March 27, 2017. A total of 564 publications on disaster medicine were identified. There was a mild increase in the number of articles on disaster medicine from 2008 (n=55) to 2016 (n=83). Disaster Medicine and Public Health Preparedness published the most articles, the majority of articles were published in the United States, and the leading institute was Tohoku University. F. Della Corte, M. D. Christian, and P. L. Ingrassia were the top authors on the topic, and the field of public health generated the most publications. Terms analysis indicated that emergency medicine, public health, disaster preparedness, natural disasters, medicine, and management were the research hotspots, whereas Hurricane Katrina, mechanical ventilation, occupational medicine, intensive care, and European journals represented the frontiers of disaster medicine research. Overall, our analysis revealed that disaster medicine studies are closely related to other medical fields and provides researchers and policy-makers in this area with new insight into the hotspots and dynamic directions. (Disaster Med Public Health Preparedness. 2019;13:165–172)

Although Middle East respiratory syndrome coronavirus (MERS-CoV) has a recorded 5 years of circulation in 27 countries worldwide, there is no international study to assess whether there is variation in mortality by region. Neither has there been a comprehensive study detailing how the disease characteristics of MERS-CoV influence mortality in patients presenting symptoms. This study aimed to assess how region, patient and disease characteristics influence 14- and 45-day mortality in MERS patients. The author utilised publically available data on MERS-CoV. The study included 883 MERS patients reported between 5 January 2015 and 10 March 2017. Data on patient and disease characteristics were collected. The mean age at MERS-CoV diagnosis was 54.3 years: 69.1% were male, and 86.7% of the cases were reported from Saudi Arabia. About 40% of MERS patients studied were over the age of 60. The study estimated 14- and 45-day survival rates after initial onset of symptoms: 83.67% and 65.9%, respectively. Saudi Arabian MERS patients exhibited 4.1 and 5.0 times higher 14-day (adjusted hazard risk (aHR) = 4.1; 95% confidence interval (CI) 1.012–16.921) and 45-day (aHR = 5.0; 95% CI 1.856–13.581) mortality risk compared with MERS patients in the Republic of Korea or other countries. Similarly, Middle Eastern MERS patients showed 5.3 and 4.1 times higher 14-day (aHR = 5.3; 95% CI 1.070–25.902) and 45-day (aHR = 4.1; 95% CI 1.288–113.076) mortality risk compared with MERS patients in the Republic of Korea or other countries. The results demonstrated a link between mortality and geography, disease and patient factors such as regions, symptoms, source of infections, underlying medical conditions, modes of transmission, non-healthcare workers and those of older age. Educational programmes, access to healthcare and early diagnosis could be implemented as modifiable factors to reduce the higher mortality rates in MERS patients.

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.

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.

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.