Epidemiological and microbiological investigation of the large increase of vibriosis in northern Europe in 2018

Northern European countries and countries bordering the Baltic Sea have witnessed an increase of vibriosis cases during recent heatwaves. Here, we described the epidemiology of vibriosis cases and the genetic diversity of Vibrio isolates from Norway, Sweden, Denmark, Finland, Poland, Estonia, and Latvia in 2018, a year with an exceptionally warm summer. We conducted a retrospective study and analysed demographics, geographic distribution, seasonality, causative species, and severity of non-travel related vibriosis cases in 2018. Data sources included surveillance systems, national laboratory notification databases and/or nationwide surveys to public health microbiology laboratories. Moreover, we performed whole genome sequencing and multilocus sequence typing of available isolates from 2014-2018 to map their genetic diversity. In 2018, we identified 445 non-travel related vibriosis cases in the study countries, which was considerably higher than the median of 126 cases between 2014-2017 (range: 87-272). The main reported mode of transmission was exposure to seawater. We observed a species-specific geographic disparity of vibriosis cases across the Nordic-Baltic region. Developing severe vibriosis was associated with infections caused by Vibrio vulnificus (adjOR: 17.2; 95% CI: 3.3-90.5) or Vibrio parahaemolyticus (adjOR: 2.1; 95% CI: 1.0-4.5), being ≥65 years of age (65-79 years, adjOR: 3.9; 95% CI: 1.7-8.7; 80+ years, adjOR: 15.5; 95% CI: 4.4-54.3) or acquiring infections during summer (adjOR: 5.1; 95% CI: 2.4-10.9). Although phylogenetic analysis revealed diversity between Vibrio isolates, two V. vulnificus clusters (<10 SNPs) were identified. Study countries could benefit from establishing a shared sentinel surveillance system for vibriosis to address this emerging public health issue.

Validation of a rapid and sensitive SARS-CoV-2 screening system developed for pandemic-scale infection surveillance

Without any realistic prospect of comprehensive global vaccine coverage and lasting immunity, control of pandemics such as COVID-19 will require implementation of large scale, rapid identification and isolation of infectious individuals to limit further transmission. Here, we describe an automated, high-throughput testing instrument, designed for population-scale testing for SARS-CoV-2 RNA within 25 minutes from inactivated saliva to result, and capable of reporting 3,840 results per hour. This integrated screening platform incorporates continuous flow loading of samples at random intervals to cost-effectively adjust for fluctuations in testing demand. Protecting vulnerable populations during global pandemics requires rapid and sensitive infection surveillance of asymptomatic carriers. This Sentinel surveillance system offers a feasible and scalable approach to complement vaccination, to curb the spread of COVID-19 variants and future pandemics to save lives.

Enhanced Sentinel Surveillance System for COVID-19 Outbreak Prediction in a Large European Dialysis Clinics Network

Accurate predictions of COVID-19 epidemic dynamics may enable timely organizational interventions in high-risk regions. We exploited the interconnection of the Fresenius Medical Care (FMC) European dialysis clinic network to develop a sentinel surveillance system for outbreak prediction. We developed an artificial intelligence-based model considering the information related to all clinics belonging to the European Nephrocare Network. The prediction tool provides risk scores of the occurrence of a COVID-19 outbreak in each dialysis center within a 2-week forecasting horizon. The model input variables include information related to the epidemic status and trends in clinical practice patterns of the target clinic, regional epidemic metrics, and the distance-weighted risk estimates of adjacent dialysis units. On the validation dates, there were 30 (5.09%), 39 (6.52%), and 218 (36.03%) clinics with two or more patients with COVID-19 infection during the 2-week prediction window. The performance of the model was suitable in all testing windows: AUC = 0.77, 0.80, and 0.81, respectively. The occurrence of new cases in a clinic propagates distance-weighted risk estimates to proximal dialysis units. Our machine learning sentinel surveillance system may allow for a prompt risk assessment and timely response to COVID-19 surges throughout networked European clinics.

Association Among Sentinel Surveillance, Meteorological Factors, and Infectious Disease in Gwangju, Korea

Introduction: The outbreak of new infectious diseases is threatening human survival. Transmission of such diseases is determined by several factors, with climate being a very important factor. This study was conducted to assess the correlation between the occurrence of infectious diseases and climatic factors using data from the Sentinel Surveillance System and meteorological data from Gwangju, Jeollanam-do, Republic of Korea. Result The climate of Gwangju from June to September is humid, with this city having the highest average temperature, whereas that from December to February is cold and dry. Infection rates of Salmonella (Temperature: r = 0.710**; Relative humidity: r = 0.669**), E. coli (r = 0.617**; r = 0.626**), Rotavirus (r=-0.408**; r=-0.618**), Norovirus (r=-0.463**; r=-0.316**), Influenza virus (r=-0.726**; r=-0.672**), Coronavirus (r=-0.684**; r=-0.408**), and Coxsackievirus (r = 0.654**; r = 0.548**) have been shown to have a high correlation with seasonal changes, specifically in these meteorological factors. Discussion & Conclusions: Pathogens showing distinct seasonality in the occurrence of infection were observed, and there was a high correlation with the climate characteristics of Gwangju. In particular, viral diseases show strong seasonality, and further research on this matter is needed. Due to the current COVID-19 pandemic, quarantine and prevention have become important to block the spread of infectious diseases. For this purpose, studies that predicts infectivity through various types of data related to infection are important.

Substandard and Falsified Medicines: Proposed Methods for Case Finding and Sentinel Surveillance (Preprint)

UNSTRUCTURED The World Health Organization and others warn that substandard and falsified medicines harm health and waste money, especially in low- and middle-income countries. However, no country has measured the market-wide extent of the problem, and no standardized methods exist to estimate the prevalence of either substandard or falsified medicines. This is, in part, because the task seems overwhelming; medicine markets are huge and diverse, and testing medicines is expensive. Many countries do operate some form of postmarket surveillance of medicine, but their methods and goals differ. There is currently no clear guidance on which surveillance method is most appropriate to meet specific public health goals. In this viewpoint, we aimed to discuss the utility of both case finding and risk-based sentinel surveillance for substandard and falsified medicines, linking each to specific public health goals. We posit that choosing the system most appropriate to the goal, as well as implementing it with a clear understanding of the factors driving the production and sale of substandard and falsified medicines, will allow for surveillance resources to be concentrated most efficiently. We adapted principles used for disease outbreak responses to suggest a case-finding system that uses secondary data to flag poor-quality medicines, proposing risk-based indicators that differ for substandard and falsified medicines. This system potentially offers a cost-effective way of identifying “cases” for market withdrawal, enhanced oversight, or another immediate response. We further proposed a risk-based sentinel surveillance system that concentrates resources on measuring the prevalence of substandard and falsified medicines in the risk clusters where they are most likely to be found. The sentinel surveillance system provides base data for a transparent, spreadsheet-based model for estimating the national prevalence of substandard and falsified medicines. The methods we proposed are based on ongoing work in Indonesia, a large and diverse middle-income country currently aiming to achieve universal health coverage. Both the case finding and the sentinel surveillance system are designed to be adaptable to other resource-constrained settings.

Detection of SARS-CoV-2 virus using acute respiratory infections sentinel surveillance system (PIDIRAC) in Catalonia (Spain)

In the context of the Covid-19 pandemic in Catalonia (Spain), the first SARS-CoV-2 case confirmed was notified to the Catalonia Epidemiological Surveillance Network (RVEC) on 25 February 2020. The present study describes and analyses the respiratory samples obtained in primary care using PIDIRAC epidemiological sentinel surveillance system to complement the pandemic surveillance system activated, and describe whether SARS‑CoV-2 was circulating before the first case detected in Catalonia, between October 2019 and April 2020.During this period, 878 respiratory samples from patients with acute respiratory infection or influenza syndrome obtained by PIDIRAC epidemiological sentinel surveillance system were analysed. Of the total sample, 51.9% tested positive to influenza virus and 48.1% to other respiratory viruses, with SARS-CoV-2 being present in 6 samples. The first SARS‑CoV‑2 positive case showed the first symptoms on 2 March 2020. These were 3 men and 3 women aged between 25 and 50 years old (mean age 44.5 years old). Fever, general discomfort, coughing, chills, and arthromyalgia were the most frequent symptoms in the SARS-CoV-2 cases. Likewise, 44 samples that had tested positive for coronavirus during 2018-2019 were typed. They were all typed as one of the regular CoV, none of them being SARS-CoV-2.The acute respiratory infections sentinel surveillance system (PIDIRAC) reinforces the global epidemiological surveillance, allows to corroborate whether there is virus circulation or not, and helps confirm that generalised community transmission in Catalonia took place in mid-March.