First outbreak of norovirus in Albania

Aims: Noroviruses (NoVs) represent the most important enteric viruses responsible for acute gastroenteritis world‐wide. This study objective is to characterize the first outbreak of NoV that occurred in Ballsh, a small city in Albania. Methods and Results: Stool specimens were collected from people attending to the hospital. Samples were also collected from the aqueduct for bacteriological and virological tests. Overall 33 stools and five drinking water samples were collected, respectively, from the hospital in Ballsh and from the municipal aqueduct. No water samples were scored positive whereas ten stool samples (30·3%) were scored GGII NoV positive. All the GGII isolates were identified as GGII·4 genotype, and no GGI was identified. The alignment and protein analysis were performed using, respectively, Clustal V and the mega 4 software. Conclusions: This is the first report of NoV GGII·4 in Albania causing an outbreak. The genetic analysis showed several point mutations and amino acid substitutions with respect to the international strains. Significance and Impact of Study: Over the last decades, Albania has suffered from different outbreaks as cholera, poliomyelitis, hepatitis A and now, for the first time, it has been documented an outbreak of NoV.     

Spatiotemporal modeling of first and second wave outbreak dynamics of COVID-19 in Germany

The COVID-19 pandemic has kept the world in suspense for the past year. In most federal countries such as Germany, locally varying conditions demand for state- or county-level decisions to adapt to the disease dynamics. However, this requires a deep understanding of the mesoscale outbreak dynamics between microscale agent models and macroscale global models. Here, we use a reparameterized SIQRD network model that accounts for local political decisions to predict the spatiotemporal evolution of the pandemic in Germany at county resolution. Our optimized model reproduces state-wise cumulative infections and deaths as reported by the Robert Koch Institute and predicts the development for individual counties at convincing accuracy during both waves in spring and fall of 2020. We demonstrate the dominating effect of local infection seeds and identify effective measures to attenuate the rapid spread. Our model has great potential to support decision makers on a state and community politics level to individually strategize their best way forward during the months to come.

     

Molecular epidemiology for the detection of outbreaks of nosocomial aspergillosis

The most important molecular techniques used in the diagnosis of Aspergillus spp. and typing of the most pathogen species of this genus are described and discussed. The former, are mainly based in PCR amplification of a concrete DNA fragment and posterior confirmation with Southern-blot; RAPD techniques and less frequently microsatellite markers analysis and DNA-DNA hybridization to a moderately repeated, inactive, retrotransposon-like DNA Afut1 are used in typing clinical isolates.     

Cryptosporidium: from laboratory diagnosis to surveillance and outbreaks

The burden of disease caused by the protozoan parasite Cyptosporidium is unknown. However, routine laboratory diagnosis and surveillance enables the basic epidemiology to be described, changes to be monitored and under-ascertainment to be measured. Although the two main species involved in human disease in developed countries, Cryptosporidium parvum and Cryptosporidium hominis, have differing epidemiologies and risk factors, national surveillance is generally from isolates identified to the genus level only. Enhancing the data by typing, at least to identify the isolates to the species level, removes some of the noise generated and better identifies the risks than when reports are not species-specific. This level of identification is also valuable for outbreak investigations, but further investigation of the population genetics of C. parvum and C. hominis is required for the development of more readily applied subtyping tools.     

GHOST: global hepatitis outbreak and surveillance technology

Background

Hepatitis C is a major public health problem in the United States and worldwide. Outbreaks of hepatitis C virus (HCV) infections associated with unsafe injection practices, drug diversion, and other exposures to blood are difficult to detect and investigate. Effective HCV outbreak investigation requires comprehensive surveillance and robust case investigation. We previously developed and validated a methodology for the rapid and cost-effective identification of HCV transmission clusters. Global Hepatitis Outbreak and Surveillance Technology (GHOST) is a cloud-based system enabling users, regardless of computational expertise, to analyze and visualize transmission clusters in an independent, accurate and reproducible way.

Results

We present and explore performance of several GHOST implemented algorithms using next-generation sequencing data experimentally obtained from hypervariable region 1 of genetically related and unrelated HCV strains. GHOST processes data from an entire MiSeq run in approximately 3 h. A panel of seven specimens was used for preparation of six repeats of MiSeq libraries. Testing sequence data from these libraries by GHOST showed a consistent transmission linkage detection, testifying to high reproducibility of the system. Lack of linkage among genetically unrelated HCV strains and constant detection of genetic linkage between HCV strains from known transmission pairs and from follow-up specimens at different levels of MiSeq-read sampling indicate high specificity and sensitivity of GHOST in accurate detection of HCV transmission.

Conclusions

GHOST enables automatic extraction of timely and relevant public health information suitable for guiding effective intervention measures. It is designed as a virtual diagnostic system intended for use in molecular surveillance and outbreak investigations rather than in research. The system produces accurate and reproducible information on HCV transmission clusters for all users, irrespective of their level of bioinformatics expertise. Improvement in molecular detection capacity will contribute to increasing the rate of transmission detection, thus providing opportunity for rapid, accurate and effective response to outbreaks of hepatitis C. Although GHOST was originally developed for hepatitis C surveillance, its modular structure is readily applicable to other infectious diseases. Worldwide availability of GHOST for the detection of HCV transmissions will foster deeper involvement of public health researchers and practitioners in hepatitis C outbreak investigation.

     

Tracing of norovirus outbreak strains in mussels collected near sewage effluents

Noroviruses from mussels collected near sewage effluents were compared with local patient outbreak strains. Sequence analyses of RNA polymerase-capsid-poly(A)-3' (3.1-kilobase) regions confirmed the 99.9% similarity between genotype I.1 strains from mussels and patient strains from recreational-bathing outbreaks, indicating the potential usefulness of sentinel norovirus mussel studies in tracing human norovirus contamination of coastal waters.     

Phylogenetic analysis of norovirus isolates involved in some Canadian gastroenteritis outbreaks in 2004 and 2005

Noroviruses are recognized as the most common cause of nonbacterial gastroenteritis worldwide. In this study, we investigated the molecular epidemiology of noroviral isolates in Canada from 2004 to 2005 by sequencing the RNA polymerase gene and capsid N-terminal/shell (N/S) domain. Norovirus genogroups I and II were thus found to have co-circulated in Canada during the studied period, with a higher incidence of genogroup II (95.7%). The GII-4 or Lordsdale subgroup was the predominant genotype, suggesting that norovirus genogroup II is the major cause of viral gastroenteritis in Canada, as it is in many other countries. Phylogenetic analyses of the RNA polymerase gene and the capsid N/S domain indicated different genotypes for 2 strains, suggesting probable genetic recombination. Sequencing of the norovirus polymerase gene may reflect actual classification but should be supported by sequence information obtained from the capsid gene.     

Staphylococcus aureus nosocomial infections: the role of a rapid and low-cost characterization for the establishment of a surveillance system

Continuous surveillance on resistance patterns and characterization of Staphylococcus aureus represent simple and low-cost techniques to understand and evaluate the effectiveness of infection control and antimicrobial prescribing measures. In this study we analyzed the antibiotic susceptibility and trends for S. aureus strains collected from bacteraemia cases in a five year period. Between 2004 and 2008 we noted a progressive decrease in the number of S. aureus isolates compared to all pathogens from clinical specimens and S. aureus bloodstream infections (BSI) reflected a similar trend. In particular we analyzed 185 isolates from blood cultures: 89 isolates were MSSA and 96 isolates were MRSA. Molecular SCCmec typing of these strains showed an absolute prevalence of types I and II, whereas five spa types from 96 isolates were obtained. Resistance pattern analysis allowed us to place MRSA strains into 12 antibiotypes and the major antibiotype was resistant to penicillin, gentamicin, erythromycin, clindamycin and ciprofloxacin. The predominant antibiotype among the MSSA isolates was resistant only to penicillin. In addition, 19.1% of MSSA are susceptible to all antibiotics tested. We also found a close association between antibiotyping 1 and genotyping t002/SCCmecI of MRSA strains, suggesting a nosocomial scenario dominated by a few particular clones.     

Bayesian outbreak detection algorithm for monitoring reported cases of campylobacteriosis in Germany

In infectious disease epidemiology, statistical methods are an indispensable component for the automated detection of outbreaks in routinely collected surveillance data. So far, methodology in this area has been largely of frequentist nature and has increasingly been taking inspiration from statistical process control. The present work is concerned with strengthening Bayesian thinking in this field. We extend the widely used approach of Farrington et al. and Heisterkamp et al. to a modern Bayesian framework within a time series decomposition context. This approach facilitates a direct calculation of the decision‐making threshold while taking all sources of uncertainty in both prediction and estimation into account. More importantly, with the methodology it is now also possible to integrate covariate processes, e.g. weather influence, into the outbreak detection. Model inference is performed using fast and efficient integrated nested Laplace approximations, enabling the use of this method in routine surveillance at public health institutions. Performance of the algorithm was investigated by comparing simulations with existing methods as well as by analysing the time series of notified campylobacteriosis cases in Germany for the years 2002–2011, which include absolute humidity as a covariate process. Altogether, a flexible and modern surveillance algorithm is presented with an implementation available through the R package ‘surveillance’.     

Year-round prevalence of norovirus in the environment of catering companies without a recently reported outbreak of gastroenteritis

Food handlers play an important role in the transmission of norovirus (NoV) in food-borne outbreaks of gastroenteritis (GE). In a year-round prevalence study, the prevalence of NoV in catering companies without recently reported outbreaks of GE was investigated and compared to the observed prevalence in catering companies with recently reported outbreaks. Swab samples were collected from surfaces in the kitchens and (staff) bathrooms in 832 randomly chosen companies and analyzed for the presence of NoV RNA. In total, 42 (1.7%) out of 2,496 environmental swabs from 35 (4.2%) catering companies tested positive. In contrast, NoV was detected in 147 (39.7%) of the 370 samples for 44 (61.1%) of the 72 establishments associated with outbreaks of gastroenteritis. NoV-positive swabs were more frequently found in winter, in specific types of companies (elderly homes and lunchrooms), and in establishments with separate bathrooms for staff. We found a borderline association with population density but no relation to the number of employees. Sequence analysis showed that environmental strains were interspersed with strains found in outbreaks of illness in humans. Thus, the presence of NoV in catering companies seemed to mirror the presence in the population but was strongly increased when associated with food-borne GE. Swabs may therefore serve as a valuable tool in outbreak investigations for the identification of the causative agent, although results should be interpreted with care, taking into account all other epidemiological data.     

Using models to identify routes of nosocomial infection: a large hospital outbreak of SARS in Hong Kong

Two factors dominated the epidemiology of severe acute respiratory syndrome (SARS) during the 2002-2003 global outbreak, namely super-spreading events (SSE) and hospital infections. Although both factors were important during the first and the largest hospital outbreak in Hong Kong, the relative importance of different routes of infection has not yet been quantified. We estimated the parameters of a novel mathematical model of hospital infection using SARS episode data. These estimates described levels of transmission between the index super-spreader, staff and patients, and were used to compare three plausible hypotheses. The broadest of the supported hypotheses ascribes the initial surge in cases to a single super-spreading individual and suggests that the per capita risk of infection to patients increased approximately one month after the start of the outbreak. Our estimate for the number of cases caused by the SSE is substantially lower than the previously reported values, which were mostly based on self-reported exposure information. This discrepancy suggests that the early identification of the index case as a super-spreader might have led to biased contact tracing, resulting in too few cases being attributed to staff-to-staff transmission. We propose that in future outbreaks of SARS or other directly transmissible respiratory pathogens, simple mathematical models could be used to validate preliminary conclusions concerning the relative importance of different routes of transmission with important implications for infection control.     

Communicable diseases prioritized for surveillance and epidemiological research: results of a standardized prioritization procedure in Germany, 2011

Introduction

To establish strategic priorities for the German national public health institute (RKI) and guide the institute''s mid-term strategic decisions, we prioritized infectious pathogens in accordance with their importance for national surveillance and epidemiological research.

Methods

We used the Delphi process with internal (RKI) and external experts and a metric-consensus approach to score pathogens according to ten three-tiered criteria. Additional experts were invited to weight each criterion, leading to the calculation of a median weight by which each score was multiplied. We ranked the pathogens according to the total weighted score and divided them into four priority groups.

Results

127 pathogens were scored. Eighty-six experts participated in the weighting; “Case fatality rate” was rated as the most important criterion. Twenty-six pathogens were ranked in the highest priority group; among those were pathogens with internationally recognised importance (e.g., Human Immunodeficiency Virus, Mycobacterium tuberculosis, Influenza virus, Hepatitis C virus, Neisseria meningitides), pathogens frequently causing large outbreaks (e.g., Campylobacter spp.), and nosocomial pathogens associated with antimicrobial resistance. Other pathogens in the highest priority group included Helicobacter pylori, Respiratory Syncytial Virus, Varicella zoster virus and Hantavirus.

Discussion

While several pathogens from the highest priority group already have a high profile in national and international health policy documents, high scores for other pathogens (e.g., Helicobacter pylori, Respiratory syncytial virus or Hantavirus) indicate a possible under-recognised importance within the current German public health framework. A process to strengthen respective surveillance systems and research has been started. The prioritization methodology has worked well; its modular structure makes it potentially useful for other settings.