Spread of the SARS-CoV-2 UK-variant in the South East of France: impact on COVID-19 patients age, comorbidity profiles and clinical presentation, week 50 2020 to week 8 2021

ObjectivesThe variant 20I/501Y.V1, associated to a higher risk of transmissibility, emerged in Nice city (South East of France, French Riviera) during January 2021. The pandemic has resumed late December 2020 in this aera. A high incidence rate together with a fast turn-over of the main circulating variants, provided us the opportunity to analyze modifications in clinical profile and outcome traits. MethodsObservational study in the University hospital of Nice from December 2020 to February 2021. We analyzed data of sequencing of SARS-CoV-2 from the sewage collector and PCR screening from all positive samples at the hospital. Then, we described the characteristics of all COVID-19 patients admitted in the emergency department (ED) (n=1247) and those hospitalized in the infectious diseases ward or ICU (n=232). Demographic data, clinical signs and severity were recorded by the NEWS-2, SAPS-2 and SOFA scores were recorded and analyzed. Resultsthe UK-variant was absent in the area in December, then increasingly spread in January representing 59% of the PCR screening performed mid-February. The rate of patients over 65 years admitted to the ED decreased from 63% to 50% (p=0.001). The mean age of hospitalized patients in the infectious diseases ward decreased from 70.7 to 59.2 (p<0.001) while the proportion of patients without comorbidity increased from 16% to 42% (p=0.007). Neither the NEWS-2 score nor the main signs of clinical severity have changed over time. ConclusionSpread of the UK-variant in the South East of France affects younger and healthier patients.

Clinical performance of oral sponge sampling for detection by RT-PCR of SARS-CoV-2

BackgroundThe current standard for coronavirus 2019 disease (COVID-19) diagnosis is reverse transcriptase-polymerase chain reaction (RT-PCR) testing of naso-pharyngeal swabs (NPS), Sampling with NPS is invasive and requires specialized and trained personnel, which limits rapid and repeated screening for the disease. A less invasive and possibly self-administered sampling method may increase the capacity for testing and be more effective in identifying, isolating, and filtering out currently infected persons. MethodsOver a period of three months, we included volunteers presenting with recent symptoms suggestive of a SARS-CoV-2 infection at a free COVID-19 screening center in the city of Nice, France. NPS as well as nasal and oral sponges were collected in parallel and analyzed by RT-PCR for SARS-CoV-2. ResultsOne hundred and forty-seven subjects were included, of whom, 41.5% were diagnosed with COVID-19 using NPS RT-PCR. RT-PCR on nasal and oral sponges showed a sensitivity of 87 to 98% and 72 to 87%, respectively for diagnosis of COVID-19 in symptomatic subjects, depending on the type of RT-PCR technique used. The specificity was 100% whatever the RT-PCR test. The viral load determined with the oral samples was significantly lower than with NPS. ConclusionTaken together, these results demonstrated that the oral sponge sampling method can be standardized, is easy to use and cheap. The acceptability makes it a repeatable test, notably for elderly people or children. It may become a high-frequency - low analytical sensitive testing strategy. Summary of the "take home" messageOral sponge sampling for SARS-CoV2 RT-PCR, is easy to use, can be self-administered with a sensitivity of up to 87 % in symptomatic patients.

Model of a Testing-and-Quarantine Strategy to Slow-Down the COVID-19 Outbreak in Guadeloupe

Using a stochastic epidemic model explicitly considering the entire population of Guadeloupe (1), we explore the domain of solutions presenting an efficient slowing down of the COVID-19 epidemic spread during the post-containment period. The considered model parameters are the basic reproduction number R0 to simulate the effects of social distancing, the time delay{delta} TO_SCPLOWQC_SCPLOW elapsed between the detection of a symptomatic person and her/his placement in quarantine to suppress her/his contagiousness, and the number Na of asymptomatic people tested positively and isolated. We show that acceptable solutions are obtained for a wide range of parameter values. Thanks to a good control of the initial epidemic spread resulting from an early containment and efficient communication by the sanitary and administrative authorities, the present situation corresponds to a pre-epidemic state. The most safe solutions are a combinations of social distancing, numerous testing to perform a systematic isolation of symptomatic patients and guided detection of asymptomatic people in the entourage of localised symptomatic patients.

Monitoring the post-containment COVID-19 crisis in Guadeloupe: Early-warning signals of destabilisation through bootstrapped probability density functions

We propose a method to detect early-warning information in relation with subtle changes occurring in the trend of evolution in data time series of the COVID-19 epidemic spread (e.g. daily new cases). The method is simple and easy to implement on laptop computers. It is designed to be able to provide reliable results even with very small amounts of data (i.e. {approx} 10 - 20). The results are given as compact graphics easy to interpret. The data are separated into two subsets: the old data used as control points to statistically define a "trend" and the recent data that are tested to evaluate their conformity with this trend. The trend is characterised by bootstrapping in order to obtain probability density functions of the expected misfit of each data point. The probability densities are used to compute distance matrices where data clusters and outliers are easily visually recognised. In addition to be able to detect very subtle changes in trend, the method is also able to detect outliers. A simulated case is analysed where R0 is slowly augmented (i.e. from 1.5 to 2.0 in 20 days) to pass from a stable damped control of the epidemic spread to an exponentially diverging situation. The method is able to give an early warning signal as soon as the very beginning of the R0 variation. Application to the data of Guadeloupe shows that a small destabilising event occurred in the data near April 30, 2020. This may be due to an increase of R0 0.7 around April 13-15, 2020.

Prediction of the time evolution of the COVID-19 disease in Guadeloupe with a stochastic evolutionary model

Predictions on the time-evolution of the number of severe and critical cases of COVID-19 patients in Guadeloupe are presented. A stochastic model is purposely developed to explicitly account for the entire population ([~=]400000 inhabitants) of Guadeloupe. The available data for Guadeloupe are analysed and combined with general characteristics of the COVID-19 to constrain the parameters of the model. The time-evolution of the number of cases follows the well-known exponential-like model observed at the very beginning of a pandemic outbreak. The exponential growth of the number of infected individuals is controlled by the so-called basic reproductive number, R0, defined as the likely number of additional cases generated by a single infectious case during its infectious period TI. Because of the rather long duration of infectious period ([~=]14 days) a high rate of contamination is sustained during several weeks after the beginning of the containment period. This may constitute a source of discouragement for people restrained to respect strict containment rules. It is then unlikely that, during the containment period, R0 falls to zero. Fortunately, our models shows that the containment effects are not much sensitive to the exact value of R0 provided we have R0 < 0.6. For such conditions, we show that the number of severe and critical cases is highly tempered about 4 to 6 weeks after the beginning of the containment. Also, the maximum number of critical cases (i.e. the cases that may exceed the hospitals intensive care capacity) remains near 30 when R0 < 0.6. For a larger R0 = 0.8 a slower decrease of the number of critical cases occurs, leading to a larger number of deceased patients. This last example illustrates the great importance to maintain an as low as possible R0 during and after the containment period. The rather long delay between the beginning of the containment and the appearance of the slowing-down of the rate of contamination puts a particular strength on the communication and sanitary education of people. To be mostly efficient, this communication must be done by a locally recognised medical staff. We believe that this point is a crucial matter of success. Appendix Posterior model assessment with data acquired after April 11, 2020 added in a second version of the paper compares the model predictions with the data acquired from April 12 to May 25 2020, after the construction of the model discussed in the present study. The remarkable agreement between the model predictions and the data may be explained by the good quality of first-hand data used to constrain the model, the ability of the stochastic approach to integrate new information and stability of the sanitary situation due to the respect of the recommendations emitted by medical and administrative authorities by the guadeloupean population.