Prevalence of Mood Disorders and Associated Factors at the Time of the COVID-19 Pandemic: Potocol for a Community Survey in La Manouba Governorate, Tunisia

Aims: The present survey aims to assess the overall mood disorder prevalence and identify associated socio-demographic and clinical factors in a Tunisian community sample, with special attention to the COVID-19 pandemic. Background: Mood disorders are one of the leading causes of all non-fatal burdens of disease, with depression being at the top of the list. The COVID-19 pandemic may have increased the prevalence of mood disorders, especially in Low and Middle-income countries (LMICs) and in vulnerable populations. Objective: 1/ Assess point and lifetime prevalence of depressive and bipolar disorders as well as subthreshold bipolarity in a representative population sample of La Manouba governorate and assess treatment patterns for these disorders; 2/Study socio-demographic and clinical correlates of mood disorders 3/ Assess the association between mood disorders and quality of life 4/ Study the impact of the COVID-pandemic on the prevalence of mood disorders 5/ Assess coping mechanisms to the COVID-pandemic and whether these mechanisms moderate the appearance of mood disorders or symptoms since the beginning of the pandemic Methods: This is a household cross-sectional observational survey to be conducted in La Manouba Governorate in a sample of 4540 randomly selected individuals aged ≥ 15 years. Data collection will be carried out by trained interviewers with clinical experience, through face-to-face interviews and the use of the computer assisted personal interviewing approach (CAPI). The following assessment tools are administered: Results: Structured clinical Interview for DSM IV-TR (Mood disorder section and Screening questions on Anxiety), Mood Disorder Questionnaire (MDQ), Suicide Behaviors Questionnaire-Revised (SBQ), 12-item Short Form Survey (SF-12), the Brief-COPE, and a questionnaire about a headache. In addition, socio-demographic and clinical data will be collected. Conclusion: This will be one of the very few household surveys in a general population sample to assess mental health problems and COVID-19-related variables since the beginning of the pandemic. Through this research, we aim to obtain an epidemiological profile of mood disorders in Tunisia and an estimation of the impact of the COVID-19 pandemic on their prevalence. Results should contribute to improving mental health care in Tunisia

Order-of-magnitude speedup for steady states and traveling waves via Stokes preconditioning in Channelflow and Openpipeflow

Steady states and traveling waves play a fundamental role in understanding hydrodynamic problems. Even when unstable, these states provide the bifurcation-theoretic explanation for the origin of the observed states. In turbulent wall-bounded shear flows, these states have been hypothesized to be saddle points organizing the trajectories within a chaotic attractor. These states must be computed with Newton's method or one of its generalizations, since time-integration cannot converge to unstable equilibria. The bottleneck is the solution of linear systems involving the Jacobian of the Navier-Stokes or Boussinesq equations. Originally such computations were carried out by constructing and directly inverting the Jacobian, but this is unfeasible for the matrices arising from three-dimensional hydrodynamic configurations in large domains. A popular method is to seek states that are invariant under numerical time integration. Surprisingly, equilibria may also be found by seeking flows that are invariant under a single very large Backwards-Euler Forwards-Euler timestep. We show that this method, called Stokes preconditioning, is 10 to 50 times faster at computing steady states in plane Couette flow and traveling waves in pipe flow. Moreover, it can be carried out using Channelflow (by Gibson) and Openpipeflow (by Willis) without any changes to these popular spectral codes. We explain the convergence rate as a function of the integration period and Reynolds number by computing the full spectra of the operators corresponding to the Jacobians of both methods.Comment: in Computational Modelling of Bifurcations and Instabilities in Fluid Dynamics, ed. Alexander Gelfgat (Springer, 2018