Epidemiological Investigation Of Outbreak Research Articles

Antimicrobial resistance and genomic characterization of Salmonella enterica isolates from chicken meat.

This study investigated genotypic and phenotypic antimicrobial resistance profiles, phylogenic relatedness, plasmid and virulence composition of 39 Salmonella enterica strains isolated from chicken meat samples using whole genome sequencing (WGS) technology. Four distinct serotypes were identified; Salmonella Minnesota (16/39, 41%), Salmonella Infantis (13/39, 33.3%), Salmonella Enteritidis (9/39, 23.1%), and one isolate was detected for Salmonella Kentucky (1/39, 2.6%), with sequence types (STs) as followed: ST548, ST32, ST11, and ST198, respectively. Phenotypic resistance to tetracycline (91.2%), ampicillin (82.4%), sulfisoxazole (64.7%), and nalidixic acid (61.6%) was the most observed. Resistome analysis revealed the presence of resistance genes to aminoglycosides, β-lactamase, sulfonamides, trimethoprim, phenicol, lincosamide, macrolides, and tetracyclines. Plasmidome showed the presence of eight incompatibility groups, including IncA/C2, IncFIB(K)_1_Kpn3, Col440I_1, IncR, IncX1, IncI1_1_Alpha, IncFIB(S)/IncFII(S), IncHI2/IncHI2A, IncX2 and ColpVC plasmids across the 39 genomes. Three resistance genes, sul2, tetA and blaCMY-2, were predicted to be located on IncA/C2 plasmid in S. Minnesota isolates, whereas all S. Infantis isolates were positive to IncFIB(K)_1_Kpn3 plasmid that carries bla CTX-M-65 gene. Eleven Salmonella pathogenicity islands and up to 131 stress and/or virulence genes were identified in the evaluated genomes. Phylogenetic analysis showed four phylogroups that were consistent with the identified ST profiles with a high level of inter-diversity between isolates. This is the first genomic characterization of Salmonella isolates from retail chicken meat in Saudi Arabia using WGS technology. The availability of Salmonella genomes from multiple geographic locations, including Saudi Arabia, would be highly beneficial in future source-tracking, especially during epidemiological surveillance and outbreak investigations.

An outbreak of acute neurological illness associated with drinking water source following a cyclone in Eluru, West Godavari district, Andhra Pradesh, India, December 2020

BackgroundIn December 2020, over 500 residents of Eluru City were hospitalised with seizures and sudden loss of consciousness (LOC) resembling the neurotoxic effects of organochlorine poisoning after a flooding event during the last week of November 2020. We described the epidemiological investigation of outbreak and identified risk factors. MethodsWe performed descriptive analysis followed by 1:1 unmatched case-control study. Cases were identified through house-to-house search and review of medical records at district hospital. A case defined as sudden onset LOC or new-onset seizures in an Eluru resident aged ≥1 year, December 1–15, 2020 and a control as absence of neurological symptoms in a person aged ≥1 year selected randomly from same administrative division of the case. We compared cases and controls for possible risk factors and calculated adjusted odds ratio (aOR) with 95% confidence interval (CI). Biological and environmental samples were tested for contaminants. ResultsWe identified 545 cases (56% males), including one death. Seizures were reported in 491 (90%) cases. Median age was 27 years (interquartile range: 17–37 years) and 480 (88%) cases resided in urban area. Cases were clustered in administrative divisions supplied by municipal water reservoirs. Cases were more likely than controls to use municipal water as primary source of drinking water (aOR = 4.6, 95% CI = 1.6–13.0). High levels (average: 14.6 mg/l) of organochlorine compounds were detected in all municipal water samples (acceptable limit: <0.001 mg/l). ConclusionThis investigation highlights water ingestion as an exposure pathway for environmental contaminants (organochlorines) in the community after largescale flooding. We recommended strengthening safe water surveillance in natural disaster response contingency plans in Eluru.

Optimizing hierarchical tree dissection parameters using historic epidemiologic data as 'ground truth'.

Hierarchical clustering of pathogen genotypes is widely used to complement epidemiologic investigations of outbreaks. Investigators must dissect trees to obtain genetic partitions that provide epidemiologists with meaningful information. Statistical approaches to tree dissection often require a user-defined parameter to predict the optimal partition number and augmenting this parameter can drastically impact resultant partition memberships. Here, we demonstrate how to optimize a given tree dissection parameter to maximize accuracy irrespective of the tree dissection method used. We hierarchically clustered 1,873 genotypes of the foodborne pathogen Cyclospora spp., including 587 possessing links to historic outbreaks. We dissected the resulting tree using a statistical method requiring users to select the value of a 'stringency parameter' (s), with a recommended value of 95% to 99.5%. We dissected this hierarchical tree across s-values from 94% to 99.5% (at increments of 0.25%), to identify a value that maximized partitioning accuracy, defined as the degree to which genetic partitions conform to known epidemiologic groupings. We show that s-values of 96.5% and 96.75% yield the highest accuracy (> 99.9%) when clustering Cyclospora sp. isolates with known epidemiologic linkages. In practice, the optimized s-value will generate robust genetic partitions comprising isolates likely derived from a common food source, even when the epidemiologic grouping is not known prior to genetic clustering. While the s-value is specific to the tree dissection method used here, the optimization approach described could be applied to any parameter/method used to dissect hierarchical trees.

Deployment of whole genome next-generation sequencing of SARS-CoV-2 in a military maritime setting

BackgroundSARS-CoV-2 can spread rapidly on maritime platforms. Several outbreaks of SARS-CoV-2 have been reported on warships at sea, where transmission is facilitated by living and working in close quarters. Core...

Clinical Manifestation of Ralstonia mannitolilytica Infection in Pediatric Patients and Epidemiological Investigation of Outbreaks.

Ralstonia mannitolilytica is a causative organism of nosocomial infections, particularly associated with contaminated water, and resistant to various antibiotics, including carbapenems. Several clusters of R. mannitolilytica infections appeared in children at our institute from August 2018 to November 2019. From March 2009 to March 2023, all patients admitted to Asan Medical Center Children's Hospital in Seoul, Korea, with culture-confirmed R. mannitolilytica and corresponding clinical signs of infection were identified. Epidemiological and environmental investigations were conducted. Polymerase chain reaction (PCR) was performed for the genes of OXA-443 and OXA-444 on R. mannitolilytica isolates. A total of 18 patients with R. mannitolilytica infection were included in this study, with 94.4% (17/18) and 5.6% (1/18) being diagnosed with pneumonia and central line-associated bloodstream infection, respectively. All-cause 30-day mortality rate was 61.1% (11/18), and seven of the fatal cases were caused by R. mannitolilytica infection itself. The resistance rates to meropenem and imipenem werew 94.4% (17/18) and 5.6% (1/18), respectively. Although four out of nine meropenem-resistant R. mannitolilytica isolates had positive PCR results for OXA-443 and OXA-444 genes, there were no significant differences in antimicrobial susceptibility patterns. Environmental sampling identified R. mannitolylica at two sites: a cold-water tap of a water purifier and an exhalation circuit of a patient mechanical ventilator. After implementing and improving adherence to infection control policies, no additional R. mannitolilytica infection cases have been reported since December 2019. R. mannitolilytica can cause life-threatening infections with high mortality in fragile pediatric populations. To prevent outbreaks, healthcare workers should be aware of R. mannitolilytica infections and strive to comply with infection control policies.

Management and analysis of high-throughput sequence data for infectious animal diseases.

Advances in technology and decreasing costs have accelerated the use of high-throughput sequencing (HTS) for both diagnosis and characterisation of infectious animal diseases. High-throughput sequencing offers several advantages over previous techniques, including rapid turnaround times and the ability to resolve single nucleotide changes among samples, both of which are important for epidemiological investigations of outbreaks. However, due to the plethora of genetic data being routinely generated, the storage and analysis of these data are proving challenging in their own right. In this article, the authors provide insight into the aspects of data management and analysis that should be considered before adopting HTS for routine animal health diagnostics. These elements fall largely into three interrelated categories: data storage, data analysis and quality assurance. Each has numerous complexities and may need to be adapted as HTS evolves. Making appropriate strategic decisions about bioinformatic sequence analysis early on in project development will help to avert major issues in the long term.

Real-time PCR assays to detect 10 Shiga toxin subtype (Stx1a, Stx1c, Stx1d, Stx2a, Stx2b, Stx2c, Stx2d, Stx2e, Stx2f, and Stx2g) genes

To develop subtyping methods for Shiga toxin (Stx)1a, Stx1c, Stx1d, Stx2a, Stx2b, Stx2c, Stx2d, Stx2e, Stx2f, and Stx2g genes for epidemiological analyses of Shiga toxin-producing Escherichia coli (STEC), we developed 10 simplex real-time polymerase chain reaction (PCR) assays with reference to 284 valid stx sequences and evaluated their specificity and quantitative accuracy using STEC and non-STEC isolates and recombinant plasmids, respectively. Three stx1 and 5 stx2 subtype genes, except for stx2c and stx2d, were detected with high specificity using STEC isolates. However, some stx2a sequences potentially being close to both Stx2a and Stx2d cluster in neighbor-joining cluster analysis were positive for stx2a and stx2d by real-time PCR. For the stx2c assay, the number of real-time PCR cycles was reduced to avoid unnecessary false-positive results. Based on these considerations, the real-time PCR assays developed here might aid epidemiological investigations of infections or outbreaks caused by STEC harboring any of the stx subtype genes.

Epidemiological, Entomological, and Climatological Investigation of the 2019 Dengue Fever Outbreak in Gewane District, Afar Region, North-East Ethiopia.

Dengue Fever (DF) is an important arthropod-borne viral infection that has repeatedly occurred as outbreaks in eastern and northeastern Ethiopia since 2013. A cross-sectional epidemiological outbreak investigation was carried out from September to November 2019 on febrile patients (confirmed malaria negative) who presented with suspected and confirmed DF at both public and private health facilities in Gewane District, Afar Region, northeastern Ethiopia. Entomological investigation of containers found in randomly selected houses belonging to DF-positive patients was undertaken to survey for the presence of Aedes larvae/pupae. A total of 1185 DF cases were recorded from six health facilities during the 3-month study period. The mean age of DF cases was 27.2 years, and 42.7% of cases were female. The most affected age group was 15-49 years old (78.98%). The total case proportions differed significantly across age groups when compared to the population distribution; there were approximately 15% and 5% higher case proportions among those aged 15-49 years and 49+ years, respectively. A total of 162 artificial containers were inspected from 62 houses, with 49.4% found positive for Aedes&amp;nbsp;aegypti larva/pupae. Aedes mosquitoes were most commonly observed breeding in plastic tanks, tires, and plastic or metal buckets/bowls. World Health Organization entomological indices classified the study site as high risk for dengue virus outbreaks (House Index = 45.2%, Container Index = 49.4%, and Breteau Index = 129). Time series climate data, specifically rainfall, were found to be significantly predictive of AR (p = 0.035). Study findings highlight the importance of vector control to prevent future DF outbreaks in the region. The scarcity of drinking water and microclimatic conditions may have also contributed to the occurrence of this outbreak.

Outbreak investigation including molecular characterization of community associated methicillin-resistant Staphylococcus aureus in a primary and secondary school in Eastern Switzerland

At our tertiary children’s hospital, infections with newly detected methicillin-resistant Staphylococcus aureus (MRSA) among children attending primary (age 6–12 years) and secondary school (age 13–16 years) nearly doubled in 2018 compared to previous years. This observation initiated an epidemiological outbreak investigation including phenotypic (susceptibility testing) and genotypic (whole genome sequencing) characterization of the isolates. In addition, a cross-sectional study was conducted to determine source of the outbreak, colonization frequency and to identify risk factors for transmission using a questionnaire. As a result, 49 individuals were detected with 57 corresponding isolates. Based on the case definition combined with whole genome sequencing, a core cluster was identified that shared common genetic features and a similar antimicrobial susceptibility pattern (efflux-mediated macrolide resistance, tetracycline susceptibility along with presence of Panton-Valentine leukocidin). Epidemiologic evaluation identified a distinct school as a common risk factor. However, the source of the clustered infections within that school could not be further specified. No further cases could be detected after decolonization of infected and colonized children.

Analysis of Rice Blast Outbreaks in Korea through Text Mining

Rice blast is a major plant disease that occurs worldwide and significantly reduces rice yields. Rice blast disease occurs periodically in Korea, causing significant socio-economic damage due to the unique status of rice as a major staple crop. A disease outbreak prediction system is required for preventing rice blast disease. Epidemiological investigations of disease outbreaks can aid in decision-making for plant disease management. Currently, plant disease prediction and epidemiological investigations are mainly based on quantitatively measurable, structured data such as crop growth and damage, weather, and other environmental factors. On the other hand, text data related to the occurrence of plant diseases are accumulated along with the structured data. However, epidemiological investigations using these unstructured data have not been conducted. The useful information extracted using unstructured data can be used for more effective plant disease management. This study analyzed news articles related to the rice blast disease through text mining to investigate the years and provinces where rice blast disease occurred most in Korea. Moreover, the average temperature, total precipitation, sunshine hours, and supplied rice varieties in the regions were also analyzed. Through these data, it was estimated that the primary causes of the nationwide outbreak in 2020 and the major outbreak in Jeonbuk region in 2021 were meteorological factors. These results obtained through text mining can be combined with deep learning technology to be used as a tool to investigate the epidemiology of rice blast disease in the future.

Using genetic markers for detection and subtyping of the emerging Salmonella enterica subspecies enterica serotype Muenchen

Non-typhoidal Salmonella (NTS) poses a global threat to public health. Poultry, one of the main reservoirs of NTS, is usually not clinically affected by most NTS, yet the economic losses to the poultry industry due to control and mitigation efforts, and due to negative publicity can be tremendous.NTS strains are routinely characterized into serotypes in a time-consuming, labor-intensive multistep process that requires skilled personnel. Moreover, the discriminatory power of serotyping is limited compared to other subtyping methods. Whole-genome sequence data enable the identification of genetic variation within serotypes. However, sequencing is often limited by available resources, and analyzing and interpreting the genetic data may be time-consuming. Source tracing during epidemiological outbreak investigations requires rapid and efficient characterization of strains to control pathogen spread. Here we designed a multiplex polymerase chain reaction (PCR) assay for the detection of genetic variants of Salmonella Muenchen, a serotype that has emerged in Israel in the last 3 yr in both clinical human cases and different hosts. Test sensitivity of 99.21% and specificity of 94 to 100% were determined using in-silico PCR with a dataset of 18,282 NTS assemblies from 37 NTS serotypes. Similarly, test sensitivity of 100% and specificity of 96.2 to 100% were determined in-vitro with 120 NTS isolates of 52 serotypes. Moreover, the test enabled differentiation between the common sequence types of serotype Muenchen using both approaches. As opposed to traditional serotyping and other subtyping methods, the designed test allows for rapid and cost-efficient detection of the emerging S. Muenchen serotype and its variants in a single step. Future development of similar assays for other dominant serotypes may help reduce the time and cost required for detection and initial characterization of dominant NTS strains. Overall, these tests will be beneficial to both public health and for reducing of the economic losses to the poultry industry due to NTS infections.

Epidemiological investigation of lumpy skin disease outbreaks in Bangladeshi cattle during 2019-2020.

Lumpy skin disease (LSD) is an acute infectious viral disease of cattle with a wide distribution that emerged in Bangladesh in 2019, causing huge economic losses. This study was undertaken to investigate the epidemiological features of LSD emergence in nine districts of Bangladesh between December 2019 and December 2020. A total of 8215 cattle from 603 herds were investigated and LSD was diagnosed based on the characteristic clinical findings. A standard questionnaire was administered to collect herd-level data including location, herd size, number of LSD-infected cattle, number died due to LSD, farm type, season, house type, vector presence, sanitation and fly repellent use. Similarly, data on clinical signs, sex, age, animal class and breed of the LSD-infected cattle were also recorded. The herd-level attack risk (%) and mortality risk (%) were calculated based on the number of infected and dead cattle, respectively, as a proportion of total cattle. The herd-level risk factors for LSD were identified using a multivariable Poisson regression model. The most common clinical signs were skin nodules (100%), fever (97.9%) and depression with anorexia and weight loss (97.9%). Crossbred (84.9%) and female (72.2%) cattle were mostly affected by LSD. The overall LSD attack risk, mortality risk and case fatality were 26.5%, 0.26% and 0.97%, respectively. The LSD attack risk was significantly higher in small herds (risk ratio: [RR] 1.39; 95% CI: 1.27; 1.53) than large herds. In addition, significantly higher LSD attack risk was observed in semi-intensive management systems (RR=1.29; 95% CI: 1.01; 1.64) than intensive management systems. Moreover, it was also significantly higher in hut (RR=1.81; 95% CI: 1.12; 2.92), temporary (RR=1.62; 95% CI: 1.21; 2.17) and tin-shed houses (RR=1.29; 95% CI: 1.11; 1.51) than in semi-building houses. To the best of our knowledge, this is the first detailed epidemiological study of LSD emergence in South Asia. Female crossbred cattle in small herds under semi-intensive management should be prioritized for LSD surveillance and vaccination to prevent further outbreaks and control the impact of the disease in Bangladesh.

Whole-Genome Sequencing and Epidemiological Investigation of Tuberculosis Outbreaks in High Schools in Hunan, China.

BackgroundTuberculosis (TB) seriously threatens individual and public health. Recently, TB outbreaks in schools have been reported more frequently in China and have attracted widespread attention. We reported three TB outbreaks in high schools in Hunan Province, China.MethodsWhen a tuberculosis patient was reported in a school, we carried out field epidemiological investigations, including tuberculin skin testing (TST), chest X-ray (CXR) and laboratory test for all close contacts, and whole-genome sequencing (WGS) analyses to understand the transmission patterns, the causes and the risk factors for the outbreaks, thereby providing a foundation for the control of TB epidemics in schools.ResultsA total of 49 students with TB patients were identified in the three schools where TB outbreaks occurred, including nine patients in School A, 14 patients in School B, and 26 patients in School C. In Schools A, B and C, the putative attack rates in the classes of the index case were 13.8% (8/58), 7.6% (5/66), and 40.4% (21/52), while the putative attack rates of expanding screening in the school were 0.3% (1/361), 0.2% (9/3955), and 0.2% (5/2080), respectively. Thirteen patients had patient delay, with a median delay interval of 69 days (IQR 30.5–113 days). Twelve patients had a healthcare diagnostic delay with a median delay interval of 32 days (IQR 24–82 days). Phylogenetic analysis of culture-positive patients revealed that most of them shared a small genetic distance (≤12 SNPs), with three separate genetic clusters (including one MDR-TB genomic cluster), indicating the recent transmission of Mycobacterium tuberculosis strains.ConclusionThis combination of field investigation and WGS analysis revealed the transmission of three TB outbreaks in schools. Reinforced implementation is needed to improve timely case finding and reduce diagnosis delay in routine TB control in the school population.

Connect to Protect: Dynamics and Genetic Connections of Highly Pathogenic Avian Influenza Outbreaks in Poultry from 2016 to 2021 in Germany.

During autumn/winter in 2016–2017 and 2020–2021, highly pathogenic avian influenza viruses (HPAIV) caused severe outbreaks in Germany and Europe. Multiple clade 2.3.4.4b H5 HPAI subtypes were responsible for increased mortality in wild birds and high mortality and massive losses in the poultry sector. To clarify putative entry sources and delineate interconnections between outbreaks in poultry holdings and wild birds, we applied whole-genome sequencing and phylodynamic analyses combined with the results of epidemiological outbreak investigations. Varying outbreak dynamics of the distinct reassortants allowed for the identification of individual, putatively wild bird-mediated entries into backyard holdings, several clusters comprising poultry holdings, local virus circulation for several weeks, direct farm-to-farm transmission and potential reassortment within a turkey holding with subsequent spill-over of the novel reassorted virus into the wild bird population. Whole-genome sequencing allowed for a unique high-resolution molecular epidemiology analysis of HPAIV H5Nx outbreaks and is recommended to be used as a standard tool. The presented detailed account of the genetic, temporal, and geographical characteristics of the recent German HPAI H5Nx situation emphasizes the role of poultry holdings as an important source of novel genetic variants and reassortants.

Guidelines for reporting Whole Genome Sequencing‐based typing data through the EFSA One Health WGS System

In 2019, the European Food Safety Authority (EFSA) and the European Centre for Disease Prevention and Control (ECDC) received a mandate from the European Commission (EC) to implement and manage two interoperable systems for the collection and analysis of Whole Genome Sequence (WGS) data of Salmonella enterica, Listeria monocytogenes and Escherichia coli, including Shiga toxin-producing E. coli (STEC) from humans and from food, feed, animals and the related environment, to contribute to the epidemiological investigations of food-borne outbreaks and to the identification of emerging health threats. As response to this EC mandate, EFSA has developed the EFSA One Health WGS System that interoperates with the ECDC Molecular Typing system exchanging core genome Multi Locus Sequence Typing (cgMLST) profiles and minimum metadata. Interested European Union (EU) Member States (MS) and European Economic Area (EEA) countries can submit their typing data from food, feed and animal samples to the EFSA One Health WGS system either through an user-friendly interface or programmatically. This technical report describes the EFSA One Health WGS system, including his architecture, the users and their relative data visibility, as well as data ownership and intellectual property. This report provides also detailed information on the types and formats of data that can be submitted to the EFSA One Health WGS system. Moreover, these guidelines describe the individual steps of the reporting procedure in order to support the EU MSs and EEA countries in data submission and data management.

Genotyping Canadian Cyclospora cayetanensis Isolates to Supplement Cyclosporiasis Outbreak Investigations.

Cyclospora cayetanensis is an emerging foodborne parasite that causes cyclosporiasis, an enteric disease of humans. Domestically acquired outbreaks have been reported in Canada every spring or summer since 2013. To date, investigations into the potential sources of infection have relied solely on epidemiological data. To supplement the epidemiological data with genetic information, we genotyped 169 Canadian cyclosporiasis cases from stool specimens collected from 2010 to 2021 using an existing eight-marker targeted amplicon deep (TADS) scheme specific to C. cayetanensis as previously described by the US Centers for Disease Control and Prevention (CDC). This is the first study to genotype Canadian Cyclospora cayetanensis isolates, and it focuses on evaluating the genotyping performance and genetic clustering. Genotyping information was successfully collected with at least part of one of the markers in the TADS assay for 97.9% of specimens, and 81.1% of cyclosporiasis cases met the minimum requirements to genetically cluster into 20 groups. The performance of the scheme suggests that examining cyclosporiasis cases genetically will be a valuable tool for supplementing epidemiological outbreak investigations and to minimize further infections. Further research is required to expand the number of discriminatory markers to improve genetic clustering.

First report of nosocomial outbreak of vancomycin-resistant Enterococcus faecium infection among COVID-19 patients hospitalized in a non-intensive care unit ward in Slovakia.

Enterococcus species account for most of the human enterococcal HAI and multidrug-resistant infections andhave become a major threat to modern public health. We examine the risein the number of vancomycin resistantE. faeciumblood stream and urinary tractinfections in a COVID-19 department during an epidemiologic outbreak investigation to detect and eliminate nosocomial clusters of the bacteria. Strain identification was performed by classical isolation andbiochemical andcultivation methods. Antibiotic testing results were interpreted according to European committee on antimicrobial susceptibility testing (EUCAST) guidelines. Six isolatedsamples underwent the whole genome sequencing (WGS) during the outbreak investigation. Isolate relatedness was determined using the core genome multi-locus sequence typing. WGS revealed two genotypically distinct VRE clusters, one of which had genetically closely related patients and environmental isolates. The cluster was terminated by enhanced infection control strategies. This study provides the first description of an outbreak caused by vanB-ST117 and vanA-ST17E. faeciumstrains among COVID-19 patients in Slovakia. This study can help to raise the awareness about the need for strict adherence to infection control measures and the implementation of rational antimicrobial stewardship as a routine part of COVID-19 management (Tab. 3, Fig. 3, Ref. 27). Text in PDF www.elis.sk Keywords: vancomycin-resistantEnterococcus faecium, antibiotic resistant, COVID-19, SARS-CoV-2, bacterial outbreak, healthcare-associated infection.

Процедура розслідування захворювання на COVID-19 медичних працівників у контексті реалізації державної політики щодо безпеки праці

Розглянуто основні положення норм чинного законодавства щодо розслідування випадків захворювання на COVID-19 медичних працівників у контексті реалізації державної політики щодо безпеки праці, проаналізовано сучасний стан вітчизняного державного регулювання у цій сфері, досліджено його організаційно-правові механізми, а також запропоновано пріоритетні напрями удосконалення процедури розслідування гострих професійних захворювань.

Epidemiological investigation of a tularaemia outbreak after a hare hunt in Bavaria, Germany, 2018.

In November 2018, a tularaemia outbreak occurred in Bavaria, Germany, among participants of a hare hunt and butchery employees handling the hares. We conducted an epidemiological outbreak investigation, including a retrospective cohort study among hunting participants, to identify likely transmission routes and activities associated with infection. Twelve of 41 participants were antibody-positive for Francisella (F.) tularensis (attack rate: 29%). Cases reported influenza-like symptoms (n=11), lymphadenopathy (n=1) and conjunctivitis (n=1). Infection only occurred in those hunting participants present while hares were processed, while risk of infection was highest when directly involved (RR=10.0; 95%CI: 2.6-392). F.tularensis was isolated from 1/4 hares. Only two individuals reported using some of the recommended personal protective equipment (PPE). Occurrence of mainly non-specific symptoms, likely due to early treatment, was not indicative of a specific transmission route. Transmissions via direct (skin/mucosa) contact and by inhalation of contaminated aerosols seem plausible. Promoting and increasing appropriate use of PPE among people processing hares is crucial to prevent future outbreaks.

Clinical Presentation, Investigation and Control of an Outbreak of Adenoviral Conjunctivitis in a Neonatal Unit at a Tertiary Hospital.

Nosocomial spread of adenovirus infection has been reported in neonatal, pediatric and adult medical units. This nonenveloped and hardy virus is resistant to numerous disinfectants thus posing a challenge for control and prevention of adenovirus infections in health care settings. An epidemiologic outbreak investigation revealed an adenoviral outbreak in the neonatal nursery as well as in the neonatal screening outpatient department for Retinopathy of Prematurity (ROP). All suspected cases (94 neonates) underwent adenoviral conventional polymerase chain reaction (PCR) and representative samples underwent sequencing by Sanger's method. The clinical features and disease course were studied. Infected babies were started on tobramycin eye drops. Topical steroid eye drops were added for those who developed pseudomembranes. We found 58 cases of laboratory-confirmed neonatal adenovirus conjunctivitis (between July 10 and October 24, 2019). Redness (96%) was the most common presentation followed by discharge (68.9%) and lid edema (51.7%). Pseudomembrane were seen in 77.5% of the infected neonates. Prior ROP examination was carried out in 38 (65.5%) neonates. Respiratory symptoms were present in 7 (12.06%) neonates. Sequencing revealed serotype 8 as the cause of the outbreak. Control measures were strictly implemented. Standard Operating Procedures (SOPs) for ROP screening were revisited, revised and reinforced to prevent future outbreaks. We observed ROP screening as a risk factor for the development of adenoviral conjunctivitis in neonatal care units. Neonates present with different clinical manifestations as compared with adults. Prompt control measures were implemented to control the adenoviral outbreak.