International epidemic intelligence at the Institut de Veille Sanitaire, France.
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ABSTRACT:
SUBMITTER: Rotureau B
PROVIDER: S-EPMC2851537 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundMore than half of the global population is under strict forms of social distancing. Estimating the expected impact of lockdown and exit strategies is critical to inform decision makers on the management of the COVID-19 health crisis.MethodsWe use a stochastic age-structured transmission model integrating data on age profile and social contacts in Île-de-France to (i) assess the epidemic in the region, (ii) evaluate the impact of lockdown, and (iii) propose possible exit strategies and estimate their effectiveness. The model is calibrated to hospital admission data before lockdown. Interventions are modeled by reconstructing the associated changes in the contact matrices and informed by mobility reductions during lockdown evaluated from mobile phone data. Different types and durations of social distancing are simulated, including progressive and targeted strategies, with large-scale testing.ResultsWe estimate the reproductive number at 3.18 [3.09, 3.24] (95% confidence interval) prior to lockdown and at 0.68 [0.66, 0.69] during lockdown, thanks to an 81% reduction of the average number of contacts. Model predictions capture the disease dynamics during lockdown, showing the epidemic curve reaching ICU system capacity, largely strengthened during the emergency, and slowly decreasing. Results suggest that physical contacts outside households were largely avoided during lockdown. Lifting the lockdown with no exit strategy would lead to a second wave overwhelming the healthcare system, if conditions return to normal. Extensive case finding and isolation are required for social distancing strategies to gradually relax lockdown constraints.ConclusionsAs France experiences the first wave of COVID-19 pandemic in lockdown, intensive forms of social distancing are required in the upcoming months due to the currently low population immunity. Extensive case finding and isolation would allow the partial release of the socio-economic pressure caused by extreme measures, while avoiding healthcare demand exceeding capacity. Response planning needs to urgently prioritize the logistics and capacity for these interventions.
| S-EPMC7391016 | biostudies-literature
Project description:The aim of our retrospective study was to evaluate the earliest COVID19-related signal to anticipate requirements of intensive care unit (ICU) beds. Although the number of ICU beds is crucial during the COVID-19 epidemic, there is no recognized early indicator to anticipate it. In the Ile-de-France region, from February 20 to May 5, 2020, emergency medical service (EMS) calls and the response provided (ambulances) together the percentage of positive reverse transcriptase polymerase chain reaction (RT-PCR) tests, general practitioner (GP) and emergency department (ED) visits, and hospital admissions of COVID-19 patients were recorded daily and compared to the number of ICU patients. Correlation curve analysis was performed to determine the best correlation coefficient, depending on the number of days the indicator has been shifted. Primary endpoint was the number of ICU patients. EMS calls, percentage of positive RT-PCR tests, ambulances used, ED and GP visits of COVID-19 patients were strongly associated (R2 ranging between 0.79 to 0.99, all P<0.001) with COVID-19 ICU patients with an anticipation delay of 23, 15, 14, 13, and 12 days respectively. Hospitalization did not anticipate ICU bed requirement. A qualitative analysis of the onset of the second wave period of the epidemic (August 1 to September 15, 2020) in the same region provided similar results. The daily number of COVID19-related telephone calls received by the EMS and corresponding dispatch ambulances, and the proportion of positive RT-PCR tests were the earliest indicators of the number of COVID19 patients requiring ICU care during the epidemic crisis, rapidly followed by ED and GP visits. This information may help health authorities to anticipate a future epidemic, including a second wave of COVID19, or decide additional social measures.
| S-EPMC7673527 | biostudies-literature
Project description:UNLABELLED: We present a novel public health database (GENI-DB) in which news events on the topic of over 176 infectious diseases and chemicals affecting human and animal health are compiled from surveillance of the global online news media in 10 languages. News event frequency data were gathered systematically through the BioCaster public health surveillance system from July 2009 to the present and is available to download by the research community for purposes of analyzing trends in the global burden of infectious diseases. Database search can be conducted by year, country, disease and language. AVAILABILITY: The GENI-DB is freely available via a web portal at http://born.nii.ac.jp/.
| S-EPMC3324518 | biostudies-other
Project description: Not available
| S-EPMC8175101 | biostudies-literature
Project description:BackgroundAlthough recent work has described the spatiotemporal diffusion of influenza viruses worldwide, comprehensive data on spatiotemporal patterns of influenza from the African continent and Madagascar are still lacking.MethodsNational Influenza Centers from 5 countries-Cameroon, Côte d'Ivoire, Madagascar, Niger, and Senegal--collected specimens from patients presenting with influenza-like illness who visited sentinel surveillance clinics during a 2-year period (2008-2009). Isolates were genetically and antigenically characterized.ResultsOverall, 8312 specimens were tested. Seasonal influenza A virus subtypes H1N1 and H3N2 and influenza B viruses were detected in 329, 689, and 148 specimens, respectively. In 2009, pandemic influenza A virus subtype H1N1 was detected in Madagascar most commonly (98.5% of cases). Influenza activity was either significant year-round or occurred during a specific period of the year in the African countries we evaluated.ConclusionsOur results demonstrate that, from Madagascar to Senegal, the epidemiologic and virologic characteristics of influenza viruses are diverse in terms of spatiotemporal circulation of the different virus types, subtypes, and strains. Our data highlight the importance of country-specific surveillance and of data and virus sharing, and they provide a rational basis to aid policy makers to develop strategies, such as vaccination at the right moment and with the right formulation, aimed at reducing the disease burden in Africa and Madagascar.
| S-EPMC8250070 | biostudies-literature
Project description:Data Access Committee EGAC00001000178
| EGAC00001000178 | EGA
Project description:In France, an epidemic peak of acute diarrhea is observed each winter. Previous results suggested a viral etiology for these winter epidemics. We investigated the role of enteric viruses in acute diarrhea and their molecular diversity. One hundred sixty-one patients with acute diarrhea and 45 healthy patients (controls) from the general population were given a standardized questionnaire between December 1998 and May 1999. Stool specimens were screened for group A and C rotaviruses, human caliciviruses, astroviruses, and adenovirus types 40 and 41 by reverse transcription-PCR and/or enzyme immunoassay. Virologic analysis was positive for 63 cases (39%). Caliciviruses and group A rotaviruses were the most frequent (19 and 17% of cases, respectively). Two control stool specimens were found positive for group A rotavirus, and one was found positive for astrovirus. Molecular characterization of the strains disclosed a cocirculation of P[8],G1, P[8],G4, and P[4],G2 rotaviruses; type 1, 2, 3, 4, and 8 astroviruses; and Sapporo-like and Norwalk-like human caliciviruses. These four types of viruses accounted for an attributable risk of acute diarrhea of 34.7% for the general population, under the assumption of a causal role of these viruses.
| S-EPMC139722 | biostudies-literature
Project description:We report 11 cases of schistosomiasis in international travelers who had bathed in rivers in Corsica, France, during 2012-2014. The infections were diagnosed in 2014 and reported to the GeoSentinel Surveillance Network and European Travel Medicine Network. Travelers can be sentinels for emerging infections; thus, this situation warrants a concerted human and veterinary epidemiologic response.
| S-EPMC4593456 | biostudies-literature
Project description:SARS-Cov2 Haut-de-France sequenced positive samples
| PRJEB43269 | ENA
Project description:Background: Artificial intelligence (AI) has recently surfaced as a research topic in dermatology and dermatopathology. In a recent survey, dermatologists were overall positive toward a development with an increased use of AI, but little is known about the corresponding attitudes among pathologists working with dermatopathology. The objective of this investigation was to make an inventory of these attitudes. Participants and Methods: An anonymous and voluntary online survey was prepared and distributed to pathologists who regularly analyzed dermatopathology slides/images. The survey consisted of 39 question divided in five sections; (1) AI as a topic in pathology; (2) previous exposure to AI as a topic in general; (3) applications for AI in dermatopathology; (4) feelings and attitudes toward AI and (5) self-reported tech-savviness and demographics. The survey opened on March 13, 2020 and closed on May 5, 2020. Results: Overall, 718 responders (64.1% females) representing 91 countries were analyzed. While 81.5% of responders were aware of AI as an emerging topic in pathology, only 18.8% had either good or excellent knowledge about AI. In terms of diagnosis classification, 42.6% saw strong or very strong potential for automated suggestion of skin tumor diagnoses. The corresponding figure for inflammatory skin diseases was 23.0% (Padj < 0.0001). For specific applications, the highest potential was considered for automated detection of mitosis (79.2%), automated suggestion of tumor margins (62.1%) and immunostaining evaluation (62.7%). The potential for automated suggestion of immunostaining (37.6%) and genetic panels (48.3%) were lower. Age did not impact the overall attitudes toward AI. Only 6.0% of the responders agreed or strongly agreed that the human pathologist will be replaced by AI in the foreseeable future. For the entire group, 72.3% agreed or strongly agreed that AI will improve dermatopathology and 84.1% thought that AI should be a part of medical training. Conclusions: Pathologists are generally optimistic about the impact and potential benefit of AI in dermatopathology. The highest potential is expected for narrow specified tasks rather than a global automated suggestion of diagnoses. There is a strong need for education about AI and its use within dermatopathology.
| S-EPMC7606983 | biostudies-literature