Factors associated with hospitalization for seasonal influenza in Morocco.

Background: Morocco is actively working towards expanding its influenza vaccine policy to cover high-risk groups, as recommended by the World Health Organization (WHO).

Aims: We assessed the risk factors for influenza-associated hospitalization for severe acute respiratory infections (SARI) that occurred during the last 5 seasons.

Methods: We conducted a retrospective, analytical study among patients recruited in the ambulatory and hospital sites of the influenza sentinel surveillance system in Morocco between 2014 and 2019.

Explanatory predictive model for COVID-19 severity risk employing machine learning, shapley addition, and LIME.

The rapid spread of SARS-CoV-2 threatens global public health and impedes the operation of healthcare systems. Several studies have been conducted to confirm SARS-CoV-2 infection and examine its risk factors. To produce more effective treatment options and vaccines, it is still necessary to investigate biomarkers and immune responses in order to gain a deeper understanding of disease pathophysiology.

Physiological responses of three field-grown species (Ceratonia siliqua, Eucalyptus camaldulensis, and Moringa oleifera) to water deficits in a Mediterranean semi-arid climate.

Reforestation of degraded drylands calls for the selection of species with the capacity to withstand water scarcity. In this current study we have assessed, the physiological responses of three field-grown species (Ceratonia siliqua, Eucalyptus camaldulensis and Moringa oleifera) to water deficits in semi-arid regions in order to suggest a potential species for rehabilitation programs. The physiological behavior of the given species was studied in three irrigation schemes: subsurface drip irrigation (applied weekly), tank irrigation (applied monthly), and unirrigated plants.

Viral aetiology of influenza-like illnesses and severe acute respiratory illnesses in Morocco, September 2014 to December 2016.

Background: There is a scarcity of information on the viral aetiology of influenza-like illness (ILI) and severe acute respiratory infection (SARI) among patients in Morocco.

Methods: From September 2014 to December 2016, we prospectively enrolled inpatients and outpatients from all age groups meeting the World Health Organization (WHO) case definition for ILI and SARI from 59 sentinel sites. The specimens were tested using real-time monoplex reverse-transcription polymerase chain reaction method for detecting 16 relevant respiratory viruses.

Machine learning approaches in Covid-19 severity risk prediction in Morocco.

The purpose of this study is to develop and test machine learning-based models for COVID-19 severity prediction. COVID-19 test samples from 337 COVID-19 positive patients at Cheikh Zaid Hospital were grouped according to the severity of their illness. Ours is the first study to estimate illness severity by combining biological and non-biological data from patients with COVID-19.