Longitudinal menstrual cycle studies allow to investigate the effects of ovarian hormones on brain organization. Here, we use spectral dynamic causal modelling (spDCM) in a triple network model to assess effective connectivity changes along the menstrual cycle within and between the default mode, salience and executive control networks . Sixty healthy young women were scanned three times along their menstrual cycle, during early follicular, pre-ovulatory and mid-luteal phase. Related to estradiol, right before ovulation the left insula recruits the ECN, while the right middle frontal gyrus decreases its connectivity to the precuneus and the DMN decouples into anterior/posterior parts. Related to progesterone during the mid-luteal phase, the insulae (SN) engage to each other, while decreasing their connectivity to parietal ECN, which in turn engages the posterior DMN. When including the most confident connections in a leave-one out cross-validation, we find an above-chance prediction of the left-out subjects’ cycle phase. These findings corroborate the plasticity of the female brain in response to acute hormone fluctuations and may help to further understand the neuroendocrine interactions underlying cognitive changes along the menstrual cycle. Hidalgo-Lopez et al. use dynamic causal modelling to investigate changes in effective connectivity related to menstrual phase and hormonal levels in healthy women. Their results provide further insight into how the brain responds to hormone fluctuations throughout the menstrual cycle. Animal research has broadly evidenced the rapid changes exerted by estradiol and progesterone on the neuronal excitatory/inhibitory balance2, synaptogenesis3, myelination and re-myelination4. These effects result in synaptic connectivity changes and therefore neural function6, and in rodents high levels of both hormones have been shown to improve cognition8. In ovariectomized rats, both estradiol and progesterone treatment enhances novel object recognition, mechanistically linked to increased long-term potentiation and N-methyl-D-aspartic acid receptors at hippocampal synapses for estradiol7, and to an increased density of the basal dendrites of hippocampal neurons for progesterone8. More importantly, as evidenced in hormonal replacement studies in rodents9 and non-human primates12 at least some of the reported neuroactive effects are dependent on a cyclic variation of hormone levels, as opposed to a continuous schedule of treatment. Although in humans such multilevel relationships between molecular mechanisms and neural functions are more difficult to determine, new results hint that neural reorganization attributed to the hormones also appears abolished when the endogenous fluctuation of ovarian hormones is disrupted15. This emphasizes the importance of studying menstrual cycle-related neural changes in healthy subjects, which still remains underinvestigated. Although sparse, acute structural changes related to hormonal fluctuations have already been reported for both grey17 and white matter18. Accordingly, connectivity patterns vary in women depending on the hormonal status, as shown by resting-state functional MRI (fMRI)21.Physiological fluctuations of ovarian hormones  affect the nervous system at multiple levels23 and are consistent across healthy subjects25. Three large-scale systems derived by independent component analyses (ICA) arise as ‘core’ neurocognitive networks, essential for cognitive functions26. First, the default mode network (DMN), which includes the precuneus/posterior cingulate cortex (PCC), medial prefrontal cortex (mPFC) and bilateral angular gyrus (AG), is characterized by increased activity during the resting state and decreased activity during goal-directed tasks28. Second, the salience network (SN), which comprises bilateral anterior insula (AI) and dorsal anterior cingulate cortex (ACC), is specialized in identifying and mapping relevant inputs, such as emotional stimuli30. Third, the executive control network (ECN), is composed of bilateral middle frontal gyri (MFG) and bilateral supramarginal gyri (SMG)30. This fronto-parietal system is usually lateralized24 and responsible for higher cognitive control functions, such as working memory or directed attention, once the relevant stimuli are detected30.Amongst the most common approaches to resting-state functional MRI is the assessment of intrinsic connectivity networks (ICNs). These sets of brain networks with temporally correlated activity at rest relate to task-based BOLD activation patterns32, all of these ICNs are susceptible to modulation by ovarian hormones. Specifically, within the DMN, intrinsic resting-state connectivity has been shown to increase before ovulation33 and decrease during the luteal phase to both left and right AG34. More recently, a single-subject study showed that the peak in estradiol right before ovulation had a key role in temporarily reorganizing the functional coupling of ICNs, especially within-network connectivity of DMN and dorsal attention network14. Further analyses in this dataset showed that during this time window several brain nodes increased their flexibility, defined as a measure of how often each node changes its affiliation among different networks or functional modules. Specifically, limbic and subcortical nodes were more flexible around ovulation and the mid-luteal phase, while the posterior DMN (PCC) was most flexible around ovulation, followed by an increased stability after the estradiol’s peak13. Within the SN, higher activity and connectivity have been consistently reported during the luteal cycle phase and related to higher progesterone levels, both at rest and during tasks36. Finally, for the ECN, increased task-based activation with higher levels of estradiol and progesterone have been shown for frontal areas. Specifically, increased right dorsolateral PFC activation has been reported during the luteal phase, over a range of tasks including spatial and verbal working memory and verbal fluency40. Relatedly, during resting state, increased eigenvector centrality in bilateral dorsolateral PFC has been found in the presence of higher progesterone levels41.Although some studies have reported no menstrual cycle-related effects on resting-state functional connectivity33). Specifically, ACC and amygdala (nodes of the SN) increased their connectivity with the precuneus (posterior DMN) during the luteal phase compared to early follicular42. Likewise, when treated with progesterone, increased connectivity between several nodes of the SN-DMN has been reported35. This enhanced inter-connectivity between SN and DMN, alongside the increased intrinsic connectivity in the SN and decreased intrinsic connectivity in the DMN, sets a very unique scenario for the luteal phase. Considering that both networks involved  are also implicated in self-referential43 and affective experience44, this distinctive connectivity pattern could elicit the misattribution of salient stimuli and dysfunctional appraisal, leading to anxiety and depressive symptoms26. Consequently, the coupling dynamics between and within the SN and DMN have been proposed to underlie the window of vulnerability for cycle-related affective disorders during the luteal phase45. More importantly, the precise role of the ECN, responsible for the regulation of the SN and the DMN, has not yet been defined. Weis et al.46 observed decreased connectivity during the pre-ovulatory phase between the DMN and the left MFG (part of the ECN), while Petersen et al.34 observed decreased connectivity during the luteal phase between the ECN and the ACC (part of the SN), both compared to early follicular. These changes could imply a difference in functional integration of cognitive and affective processes, but up to now a cohesive model for understanding the global mechanisms in which the healthy female brain adapts to hormonal changes remains elusive.Regarding inter-network connectivity, previous findings mainly report changes in the DMN-SN connectivity, pointing out an increase during the luteal phase  estimates hidden neural states from the observed Blood Oxygen Level Dependent (BOLD) signal—specifically, the cross-spectral density of BOLD signals from different brain regions. It assumes that spontaneous fluctuations in the signal during resting state reflect the endogenous neural activity48. By parameterising the hidden coupling among the neuronal populations, one can generate (complex) cross spectra among observed responses51. In addition, spDCM is especially efficient to invert large DCMs of resting-state fMRI51, which makes it feasible to assess large-scale between and within networks’ organization.Despite being a useful resource to address brain organization, the assessment of resting-state functional connectivity52. For example, it is yet not defined whether the enhanced inter-connectivity of the SN and DMN during the luteal cycle phase42 originates from the SN or the DMN. Likewise, it is unclear whether the downregulation of the SN during the luteal phase is related to an increase in the directed connectivity from the ECN as proposed by the triple network model26. In addition, it also remains unexplored how the increased activation of the right MFG relates to increased afferent connectivity, given that the BOLD-response rather reflects the input to a neuronal population53. As several psychiatric and neurological disorders share an aberrant intrinsic organization of the aforementioned three core networks26, we consider it of the utmost importance to characterize their non-pathological directed organization in healthy women. In order to do so, we applied state-of-the-art effective connectivity analyses to a previously published longitudinal resting state-fMRI data set acquired during early follicular, pre-ovulatory and mid-luteal cycle phase in a large sample of healthy young women21. Finally, we aimed to identify, whether changes in specific directed connections were able to predict which cycle phase a woman was in.To the best of our knowledge, no study has yet investigated the directed connectivity across the different menstrual cycle phases and related to ovarian hormonal levels. In this work, we aim to delineate the menstrual cycle-related changes in effective connectivity within and between DMN, SN and ECN, and identify the specific direction of previously reported effectsp < 0.001; F2, 114 = 33.49, p < 0.001, for estradiol and progesterone respectively)  and mid-luteal phase , as well as during the mid-luteal phase compared to early follicular . Progesterone levels were significantly lower during early follicular compared to the pre-ovulatory and the mid-luteal phase , and higher during the mid-luteal compared to the pre-ovulatory phase .For the final sample and as expected, both estradiol and progesterone levels significantly changed within subject across the menstrual cycle  are reported. Those connections surviving a 95% threshold are further indicated in the figures and results section alongside each parameter’s estimated mean (Ep) and posterior probability (Pp). Given that all parameters contributed to the model, figures including all parameters regardless of threshold can be found in the supplementary material . Most of the changes in cycle phase were backed up by hormonal correlations (compare Supplementary Data file 1), but only those surviving a 95% threshold are reported in the text.Results are displayed in Fig. DMN: In general, effective connectivity within anterior and posterior nodes in the DMN was highest during early follicular and lowest during the pre-ovulatory phase , and mid-luteal phases , and positively related to estradiol levels  (Supplementary Data file 1). Likewise, effective connectivity from the left AI to the left MFG also increased from the early follicular to the pre-ovulatory phase . During the mid-luteal phase, effective connectivity from the left AI to frontal ECN decreased again . Accordingly, both connections were negatively correlated to progesterone levels . Likewise, higher estradiol levels had a negative impact on the connectivity from the left AI to the left MFG , while the combinatory effect with progesterone was positive . From the left AI to the right MFG, connectivity was further negatively affected by the combinatory effect of estradiol and progesterone (Supplementary Data file 1).On the other hand, from the right AI, effective connectivity to posterior ECN decreased right before ovulation , and during the mid-luteal phase  and was related to higher estradiol , lower progesterone  and their combinatory effect  , except from the left MFG to the ACC, which decreased from the pre-ovulatory to the mid-luteal phase , and was negatively related to progesterone levels , and positively to estradiol  , and related negatively to estradiol levels . The negative impact of higher estradiol levels was reversed by progesterone’s positive impact , as indicated by a significant interaction effect  (Supplementary Data file 1). During the mid-luteal phase, only those connections originating in the right hemisphere increased again in connectivity strength, while connections originating from the left hemisphere stayed decreased  and were negatively related to progesterone levels . The latter effect was partially reversed in the presence of high estradiol, as indicated by a significant interaction effect   in the previous analyses. Those directed connections were from left AI and right SMG to left SMG, from left SMG to left MFG, and from right MFG to PCC. The Pearson’s correlation coefficient between the actual cycle phase in the left-out-subject’s design matrix  and the predicted cycle phase based on the left-out-subject’s connectivity was rdf:172 = 0.21, p = 0.003 42. Furthermore, the over recruitment of the ACC into the DMN and enhanced connectivity with the mPFC has been characterized as unique for major depression symptoms and could reflect an inability to attend salient relevant external stimuli26. Conversely, in our model we observed a reduced connectivity from mPFC to ACC during the mid-luteal phase, related to higher progesterone levels, while increased mPFC-PCC coupling to parietal areas, involved in external information processing . Although the bilateral AI are involved in the response to all emotional stimuli, a left-hemisphere dominance for positive stimuli67 and empathy68 has been suggested, relating the lateralized pattern of insula coupling and decoupling to the ECN to menstrual cycle-dependent changes in emotion processing69. During the mid-luteal phase both insulae decoupled from the PCC as they increased the connectivity to each other. In addition, the left insula maintained the connectivity with parietal ECN while the right insula replaced its counterpart recruiting again the frontal ECN. Accordingly, these findings support the idea that the enhanced salience detection during the mid-luteal phase could be buffered by coupling with frontal ECN. In fact, the increased connectivity between ACC and right MFG during the mid-luteal phase may reflect an enhanced top-downregulation in healthy women.The present results not only corroborate these previous findings in causal networks’ dynamics5). In women, frontal areas such as the IFG and MFG have shown enhanced activity during the pre-ovulatory phase and related to increased estradiol levels for implicit memory70 and verbal encoding71. We recently found increased right frontrostriatal functional connectivity during resting state, related to higher estradiol levels during the pre-ovulatory phase21. The increased afferent connectivity we observed from the left hemisphere to bilateral MFG right before ovulation could reflect underlying structural changes, but in humans, the relationship between molecular mechanisms and neural functions are difficult to determine. Nevertheless, evidence from animal studies strongly suggests the involvement of oestrogen-dependent synaptogenesis in the PFC (in non-human primates3 and rodents72).Third, the ECN showed both a lateralized and anterior-posterior hormonal modulation, in line with previous neuroendocrine research. Converging evidence from animal and human research relates estradiol to improved prefrontal-dependent functions, especially in verbal tasks . Specifically, in patients, the left insula was found less active than in healthy controls before ovulation, while more active during the mid-luteal phase compared to both controls and pre-ovulatory patients73. If, as our results suggest, the balanced bottom-up/top-downregulation entails a shift in the lateralization of the dorsolateral PFC afferent connections from the SN, its absence or deregulation could underlie some symptomatology.Our model shows a shift of lateralization across the cycle phases with the most evident change being the recruitment of bilateral MFG from the left insula versus the right insula during early follicular and the mid-luteal phase. In turn, the increased top-down engagement to SN from frontal ECN was maintained during the high-hormone phases, and positively related to both estradiol and progesterone levels. As expected, the right MFG increased its afferent connectivity during the mid-luteal phase, including from left MFG, which could explain the increased executive-dependent activation previously observed74. In addition, the right SMG is particularly involved in shifting attention to salient stimuli75. The shift in connectivity between the right insula and posterior ECN to anterior ECN after ovulation may reflect the dynamic integration of bottom-up/top-down processes, not only lateralized but also according to an anterior/posterior specialization. Noteworthy, all four connections with the most confident effects included in the cross-validation analysis, involved at least one node from the ECN, reflecting the key role of this network in menstrual cycle-related changes and SN/DMN coupling dynamics.After ovulation, parietal areas coupled to the posterior DMN and to each other. Related to higher progesterone levels (Supplementary Data file 1), the right SMG increased the efferent connectivity to every node of the other networks but to right insula, which similarly decreased its connectivity to right SMG. A rightward asymmetry in SMG-insula connectivity has been found to be stronger in females than in males, and related to susceptibility to chronic pain disorders76, transcranial magnetic stimulation77 and fMRI studies78 and suggested to reflect a reduced transcallosal inhibition81. On the other hand, a more symmetrical pattern during early follicular and pre-ovulatory phase while right lateralized during the mid-luteal phase is observed for the connectivity from ECN to the SN, in which the anterior-posterior modulation makes the scenario more complex. Furthermore, and as discussed previously, the right MFG also constitutes an exception to the lateralization observed across the menstrual cycle: its connectivity to the SN was the lowest during early follicular and increased as the hormone levels increased. These differential patterns could explain why the findings involving hemispheric asymmetries are sometime controversial and depend on the specific task and cognitive system involved82.Fourth, across the menstrual cycle, two distinctive patterns regarding changes in lateralization could be distinguished. On the one hand, a right-lateralized pattern during early follicular, which changes to the left hemisphere during pre-ovulatory, and recruiting the right hemisphere again during the mid-luteal phase. This is the case for connectivity from SMG to posterior DMN, AG to SN, or the connectivity from the insula (broadly speaking). In addition, we observed an increased connectivity between homotopic regions of the SN and ECN during the mid-luteal phase. Therefore, in most cases, this time window was characterized by a decreased asymmetry, which has been previously reported for different methods including behavioural14 does not come as a surprise, since the neuroendocrine feedback loops triggered by it are quite unique in the human physiology, and the biological relevance of ovulation is undeniable. Structural changes between the early follicular and the pre-ovulatory phase have been previously shown to accurately classify cycle phase using a machine learning approach, and related to estradiol levels (BrainAGE83). A more detailed discussion of the functional role of each of the connections included in the LOOCV can be found in the Supplementary Note 1.In summary, this triple network dynamic model corroborates the plasticity of the brain in response to the acute ovarian hormone fluctuations along the natural menstrual cycle. We have shown how both lateralization and anterior-posterior effective connectivity patterns within and between networks depend on the endogenous hormonal status in healthy young women. Furthermore, when using those parameters with the largest posterior probability, we found an above-chance prediction of the left-out subjects’ cycle phase, although this should be interpreted with caution, given the small effect size and therefore low percentage of the variance explained. Remarkably, all these connections reflect and summarize the effects that have been already discussed: increased engagement of the DMN with the ECN during the early follicular phase, enhanced left frontoparietal connectivity right before ovulation, increased frontoparietal recruitment by the left insula in response to enhanced estradiol levels as well as interhemispheric decoupling in executive parietal areas, partially reversed after ovulation. The impact of the surge of estradiol levels around ovulation in brain connectivity and nodes flexibility84 and human research85. Therefore, results on healthy naturally cycling women may have further implications for those menstrual cycle-related disorders where this pattern of brain coupling dynamics has been suggested to be impaired, such as premenstrual syndrome (PMS), PMDD or dysmenorrhoea86. Moreover, some factors in other neurological and psychiatric disorders, where the triple model network is impaired26, have been previously related to hormonal levels, like the incidence of epileptic seizures87 addiction patterns and drug sensitivity88, as well as the sensitivity and risk to develop affective disorders90, Alzheimer’s disease91 or Schizophrenia93. Therefore, some of the key findings here described, correspondent to healthy mechanisms, may be targeted in future clinical neuroendocrine studies.The present work also corroborates a differential effect of each hormone depending on the brain region and network dynamics, which remarks the relevance of widening the focus to large-scale systems interaction, rather than the activity of localized brain areas. In fact, the cycle-related effects on connectivity from different nodes of a network to other networks suggest that ICA, the most used approach up to now, might be too coarse to capture the hormonal effects since the time-courses of various areas are averaged together and the results depend on the areas included in the ICN. Although we are still far away to comprehend the full scope of the ovarian hormones effects on the human brain coupling dynamics, this proposed causal model of menstrual cycle-related changes may improve our understanding of the underlying neuroendocrine interactions. At least to some extent, the neural substrate needs the cyclic ovarian hormones fluctuation to undergo this brain reorganization, as evidenced by animal21. Main inclusion criteria were an age range of 18–35 years, and a regular menstrual cycle (MC) of 21–35 days with a variability between cycles of <7 days94. Exclusion criteria included use of hormonal contraceptives within the previous 6 months, neurological, psychiatric or endocrine disorders, including PMDD and PMS and any medication intake. Due to inconsistencies between self-reported cycle phase and hormone levels, 18 women were excluded, and 2 participants were further excluded during the fMRI analysis due to insufficient signal in some of the regions of interest, resulting in a total sample of 58 healthy young women  and were approved by the University of Salzburg’s ethics committee.Seventy-eight healthy young women participated in 1 of 2 functional imaging studiesCycle duration was calculated based on participants’ self-reports of the dates of onset of their last three periods, and three appointments were scheduled once during the early follicular phase ; once in the pre-ovulatory phase , and once during the mid-luteal phase , order counter-balanced. Pre-ovulatory sessions were confirmed by commercially available urinary ovulation tests (Pregnafix®). Participants had to confirm the onset of next menses in retrospect.21. Estradiol and progesterone were assessed using the Salimetrics High Sensitivity salivary Estradiol assay (sensitivity of 1 pg/ml) and the DeMediTec Progesterone free in saliva ELISAs (a sensitivity of 10 pg/ml), respectively. All samples were assessed in duplicates and samples with more than 25% variation between duplicates were reanalyzed. In order to corroborate hormonal changes along the menstrual cycle, statistical analyses were performed in R 3.6.2 (https://www.R-project.org/)96 using nlme97. To explore the menstrual cycle effects on estradiol and progesterone levels within-subject, a linear mixed model was fitted to the data, using estradiol and progesterone as dependent variables, cycle phase as fixed effects, and participant number (PNr) as random effect, respectively. We accounted for multiple testing by using the package multcomp98 for conducting all-pairwise comparisons between cycle phases. P values were adjusted for multiple comparisons.Saliva samples were collected from participants, stored and processed as described in ref. Functional images, fieldmaps and an MPRAGE sequence were acquired on a Siemens Magnetom TIM Trio 3T scanner. For the resting state we used a T2*-weighted gradient echo planar (EPI) sequence with 36 transversal slices oriented parallel to the AC–PC line . Participants were instructed to close their eyes, relax and let their mind flow. For the structural images we acquired a T1-weighted 3D MPRAGE sequence of 5 min 58 sec .www.fil.ion.ucl.ac.uk/spm) including segmentation of the structural images using CAT12. The resulting images were subjected to the ICA-AROMA algorithm implemented in FSL and non-aggressive removal of artefactual components99.For the preprocessing, the first six images of each session were discarded, and functional images were despiked using 3d-despiking as implemented in AFNI (afni.nimh.nih.gov). The despiked images were then pre-processed using SPM12 standard procedures and templates SPM12 101, and already described in Hidalgo-Lopez et al.21. After extracting20 components, we selected those four corresponding to the posterior DMN , posterior SN (IC 17), left ECN (IC 10) and right ECN (IC 11) via spatial correlation to pre-existing templates23 . Both the DMN and the SN lacked of sufficient signal in anterior regions, and therefore, the anterior nodes of the DMN (mPFC) and SN (ACC) were identified through seed-based functional connectivity analysis from the posterior nodes  using the CONN toolbox102. The resulting areas were masked with BA10 & BA11 and ACC as implemented in the Wake Forest University (WFU) Pickatlas toolbox . Subject-specific coordinates were selected as local maximum within 8 mm of the group-level coordinates within the region-specific mask WFUpickatlas. For each of the 11 ROIs the principal eigenvariate from an 8 mm sphere around the subject-specific coordinates and within the ROI mask was extracted and corrected for CSF and WM . These time series were then used in subsequent DCM analyses . We modelled our data using a (Bayesian) hierarchical random effects model. At the first level of analysis, for each individual subject, interactions between brain regions were captured by inverting dynamic causal models (DCMs). These provided a  probability density over the connectivity parameters for each subject. For each participant and session, a fully connected model , with no exogenous inputs, was specified to estimate the intrinsic effective connectivity  within and between networks. The estimation fits the complex cross-spectral density taking into account the effects of neurovascular fluctuations as well as noise49 and the default priors implemented in SPM were used at this level. The percentage of variance explained by the model for our subjects and sessions ranged from 91.60 to 99.27, which reflect good data fits for each model we estimated104.Spectral DCM for resting state was specified and inverted using DCM12 as implemented in SPM12  to capture effects of interest and a covariance component model to capture random effects .For the second-level analyses, the parameters (effective connectivity strengths) were estimated in a Parametric Empirical Bayes (PEB) framework as described in Zeidman et al.An advantage of this fully Bayesian approach is that models with different regressors in their group-level design matrix can be compared in terms of their log model evidence or marginal likelihood (thereby identifying the model that offers the best trade-off between accuracy and complexity). In a preliminary analysis, we evaluated whether including dummy regressors for each subject in addition to regressors for each phase of the menstrual cycle (thereby forming a within-subject repeated measures ANOVA) would increase the model evidence, relative to a model that only included regressors for each phase of the menstrual cycle. We found that the evidence decreased when including subject-specific regressors . Therefore, we did not include subject-specific regressors in the final regression model.54, by thresholding our effects at 75% posterior probability , there is a strong dilution-of-evidence effect, where parameters with small effect sizes can markedly reduce predictive accuracy. It is important, therefore, to first perform feature selection, retaining only the largest or most probable parameters. Therefore, we only assessed the predictive accuracy of those parameters with 99% probability of being non-zero. In order to do so we used a leave-one-out scheme (spm_dcm_loo.m) as described in Friston et al.Further information on research design is available in the Supplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Reporting Summary


The mental health burden of COVID-19 has been examined in different settings. Existing research has relied on the latent variable model in assessing COVID-19-related distress. Network theory provides an alternative framework wherein symptoms are conceptualised as causal, interconnected constituents rather than outcomes of mental disorders.To assess networks of self-reported anxiety and depressive symptoms among quarantined individuals.Consenting individuals in different quarantine centres in Qatar completed the Patient Health Questionnaire Anxiety and Depression Scale. We used partial correlation network methods to illustrate interactions of self-reported psychopathology.Participants with COVID-19 were significantly older and had a significantly higher proportion of males. The most central node was COVID-19, followed by thoughts of self-harm. COVID-19 status was strongly positively connected to thoughts of self-harm, which was positively connected to psychomotor changes, which were connected to decreased concentration. COVID-19 status was also positively connected to feeling anxious, which was strongly connected to inability to concentrate, which was connected to feeling afraid.COVID-19 was the most influential factor, with the highest number and strength of connections to psychopathology in a network of anxiety and depressive symptoms in a quarantine setting. Beyond the resolution of the infection, therapeutic interventions targeting psychomotor changes might prove beneficial in reducing suicidality among quarantined individuals with COVID-19. Follow-up with mental health services after COVID-19 infection is needed to restore psychological well-being. Further research is needed to understand the short- and long-term psychological effects of COVID-19, and the outcomes of different therapeutic interventions. Using the Patient Health Questionnaire (PHQ-9) and seven-item Generalized Anxiety Scale (GAD-7), with a cut-off score of 10 or above for both scales, the prevalence of depression among individuals with COVID-19 was found to be 29.2%, significantly higher than other groups (P = 0.016). Rates of anxiety or depression comorbid with anxiety did not reach statistical significance.7 However, analysing survey outcomes by using similar diagnostic thresholds and summary scores might hinder scientific progress in understanding and treating psychopathology.8Most studies focused on the indirect psychological impact of the pandemic on non-infected individuals, with a few addressing psychiatric manifestations in patients testing positive for SARS-CoV-2.9 heralding the National Institute of Mental Health (NIMH)'s decision to halt funding for research predicated on DSM diagnosis in favour of the more scientifically based Research Domain Criteria.10 Furthermore, the constellation of symptoms defining a mental disorder is amassed irrespective of potential stressors or comorbid conditions, with no reference to differential weight or significance of set components. For instance, excessive anxiety and worry that is difficult to control, and the presence of low mood, loss of interest or pleasure, are contextually blind prerequisites for the diagnoses of generalised anxiety disorder and major depressive disorder, respectively.11 Said core symptoms might not consistently represent the most central or relevant sources of distress for the population of interest. Cramer et al intriguingly tackled this limitation by assessing patterns of depressive symptoms following four stressful life events: stress , romantic loss, health problems and interpersonal conflict. Decreased appetite was found to be highly central in the conflict group compared with loss of interest in those who experienced romantic loss. Additionally, correlation patterns between depressive symptoms differed among groups, as the association between depressed mood and thoughts of death was stronger in cohorts experiencing health problems and interpersonal conflicts. In contrast, strong connections between worthlessness and thoughts of death was more pronounced in groups experiencing stress or romantic loss.12 More recently, McWilliams et al analysed self-reported depressive symptoms in patients seeking treatment for chronic pain, and found difficulty concentrating, loss of interest or pleasure, depressed mood and fatigue to be the most central symptoms.13Statistical manuals and classification systems interpret psychopathology by using the disease model, whereby clinical symptoms represent manifestations of a latent variable  and share a causal background. Psychometrics aggregate outcomes in a total score that presumably reflects the severity of the latent variable. The DSM-5 has been criticised for its selective reliance on expert opinion in defining mental illness notwithstanding existing clinical research,14 Further exploration is needed to comprehend the psychological ramifications of the current pandemic, and applying network theory offers a more extensive appreciation of presenting symptoms. We have previously assessed the psychological outcome of COVID-19 in quarantine settings, and found that quarantined participants who were positive for COVID-19 reported significantly higher anxiety and depressive symptoms compared with controls (quarantined participants without COVID-19).15 In this study, we aim to perform an exploratory network analysis of data from our previous study, with the goal of providing a deeper understanding of psychopathology and generating foci for therapeutic intervention and future research.Such conceptualisation of psychopathology is possible through the application of network theory, wherein mental disorders are conceived as systems of interconnected variables. This statistical framework allows for in-depth analysis of centrality and connectivity among different components of mental disorders, without assuming a common underlying biological aetiology or equivalent diagnostic weight for clinical symptoms. Psychopathology is therefore construed as a constituent of mental disorders rather than its outcome or reflection.15 Inclusion criteria comprised all adults aged 18 or above who were located in quarantine cites. Those unable to consent to participation because of illiteracy, health conditions or other factors were deemed ineligible to take part in the study. Participant selection was randomised based on room number allocation: alternate room numbers in smaller facilities and every fifth room in larger facilities. We performed a network analysis on depressive and anxiety symptoms in participants with COVID-19 (positive COVID-19 polymerase chain reaction (PCR) test). Quarantined participants with a negative COVID-19 PCR test served as controls. All individuals with pending or inconclusive COVID-19 PCR test results were excluded. This study is not a trial and has not been registered under any registry. It only received approval from IRB at Hamad Medical Corporation (MRC-05-086) and is in accordance with the World Medical Association's Declaration of Helsinki. All participants provided written informed consent to enrol in the study and approved the use of collected data for research purposes.We carried out a network analysis using data from our nationwide study examining the prevalence of depressive and anxiety symptoms in individuals quarantined for COVID-19 in Qatar.16 It was chosen as our screening tool given the availability of validated Arabic versions of both the PHQ-9 and GAD-7.17Demographic information and COVID-19 status were collected in the first part of the study questionnaire. The second part comprised the Patient Health Questionnaire Anxiety and Depression Scale, a reliable tool for the composite measure of depressive and anxiety symptoms in different settings, including both the PHQ-9 and GAD-7.EstimateNetwork feature of the R package ‘bootnet’ . JASP software  was used to produce plots. The nodes of each network corresponded to the list of depressive and anxiety symptoms as per the PHQ-9 and GAD-7, respectively. To examine the links between COVID-19 and depressive and anxiety symptoms, we also chose to add COVID-19 status (as per the PCR result) as a node in the network. We chose this approach previously followed by Fried et al18 instead of establishing two different networks for COVID-19-positive and COVID-19-negative groups, to avoid Berkson's bias. We used the Extended Bayesian Information Criterion Graphical Least Absolute Shrinkage and Selection Operator (EBICglasso) regularised partial correlation estimator. We calculated the matrix of partial correlations between symptoms in each study group and proceeded with the graphical representation of the symptom network in each of the groups. To plot the network, we chose the following options: tuning parameter (γ) = 0.5, cut-off of 0.1, minimum value of 0 and maximum value of 1.We performed a partial correlation network study by using the 19 and Eigenvector centrality . Other centrality indices such as betweenness and closeness were not used because of their poor stability.20We also calculated the following centrality indices for the two networks estimated jointly: strength of the node ,21 First, we determined the 95% confidence intervals for each edge, using 1000 bootstraps. We also estimated the edge stability coefficient, which represents the maximum proportion of the sample that can be dropped to retain a correlation of at least 0.7 between the original edge weights and the edge weights in the bootstrapped data-sets, with 95% probability. Second, we calculated the centrality stability coefficient, which corresponds to the maximum proportion of the sample that can be dropped to retain a correlation of at least 0.7 between the original edge weights and the edge weights in the bootstrapped data-sets, with 95% probability.22We examined the stability of the network by assessing the stability of edge weights and the stability of centrality indices.v. 35.2 ± 10.5 years; P < 0.001) and had a significantly higher percentage of males .A total of 748 individuals participated in the study. Individuals with an inconclusive COVID-19 PCR test or those for whom the test result was not available at the time of survey distribution were excluded. Our sample comprised 394 participants with a positive COVID-19 PCR and 269 controls (with a negative COVID-19 PCR) . COVID-1The network analysis is illustrated in 22. In addition, 22The edge stability coefficient was 0.594, which can be interpreted as very good The most central node was COVID-19 status, followed by thoughts of self-harm (TSH). COVID-19 status was strongly positively connected to TSH, which in turn was positively connected to psychomotor changes (PMCs). PMCs were connected to decreased concentration. COVID-19 status was also positively connected to feeling anxious, which was strongly connected to inability to concentrate, which in turn was connected to feeling afraid. In addition, COVID-19 status was negatively associated with irritability, worries and decreased concentration .Table 123 The accuracy of centrality indices in our network is acceptable , as values above 0.25 are suggested to reflect accuracy, with a preference for values above 0.5.24 The edge stability coefficient indicates a very good accuracy level of depicted connections. However, because of large, overlapping bootstrapped 95% confidence intervals, the order of the edge weights needs to be interpreted with caution. Based on these findings, the elucidated network represents a relatively valid tool in interpreting the covariance and connections of psychopathology in quarantine settings.We analysed our data with a γ of 0.5 to balance revealing a true network structure and excluding spurious relationships. The choice of tuning parameter setting was based on the work by Epskamp, who found the adoption of a γ of 0.75 or 1.00 to be non-superior to γ = 0.5 in an established data-set.27 Despite warnings of a concurrent suicide pandemic, subsequent analyses of national and regional statistics revealed either no significant change or a reduction in suicide rates during the COVID-19 period. No evidence of increase in suicide rates was found in a time-series analysis of data from 21 countries.28 Compared with the same period in the preceding 14 years, Deisenhammer and Kemmler found a significant decrease in suicide numbers between April and September of 2020 in the state of Tyrol, Austria.29 In New York, no significant change was observed in suicidal ideation, self-injurious behaviour and suicide attempts among patients requiring emergent psychiatric evaluation. A significant decline was also noted in suicide attempts among children and adolescents during the pandemic compared with the pre-COVID period . Furthermore, patients with COVID-19 were less likely to be depressed or report suicidal ideation compared with those without COVID-19.30In accordance with centrality indices, COVID-19 status had the highest degree and strength of connectivity to anxiety and depressive symptoms. Although our network does not reveal the direction of connections, it still emphasises the central role of COVID-19 in propagating psychopathology. The strongest connection to COVID-19 status was TSH (weighted matrix of 0.471). In 2020, several reports shed light on suicide cases during the pandemic.v. 2.8; P < 0.001) and anxiety scores  compared with controls.15 In addition, our participants comprised quarantined individuals. Social isolation and loneliness in the context of quarantine can lead to symptoms of depression, anxiety and post-traumatic stress disorders.31Based on our previous study, the majority of our participants were migrant workers, and participants with COVID-19 had higher depressive . However, this difference was non-significant after controlling for psychotic features.38 Conversely, Ballard et al showed that psychomotor agitation was not significantly elevated before suicidal behaviour.39 Among our participants, COVID-19 status and quarantine might have affected psychomotor activity and strengthened the relationship between TSH and PMCs.Our network revealed a strong connection between TSH and PMCs, and therapeutic interventions targeting PMCs might be beneficial in reducing suicidality among quarantined individuals with COVID-19. Indic et al found an inverse relationship between participant motility and suicidal thinking in patients diagnosed with bipolar disorder and unipolar depression.40 A recent scoping review also found persistent physical and mental health problems and an overall lower quality of life up to 3 months after COVID-19 infection.41 Our findings, in accordance with existing literature, highlight the need for post-infection follow-up with mental health services in addressing psychological distress and restoring quality of life.PMCs was strongly connected to decreased concentration. COVID-19 status was also strongly connected with feeling anxious, which was in turn strongly connected to decreased concentration. On the periphery of the network, strong connections are additionally seen between difficulty sleeping, low energy and loss of appetite. The strong branching connections outside the direct impact of the most central node indicate the existence of a potentially reinforcing and self-sustaining relationship between anxiety and depressive symptoms beyond the effect of COVID-19. Hence, the resolution of infection might not be sufficient to ameliorate psychological distress. Li et al found that symptoms of insomnia, anxiety and depression significantly decreased after patients with COVID-19 were discharged to home isolation from quarantine facilities in Wuhan, China. However, out of 782 cases, 188 patients reported insomnia, 78 patients had anxiety symptoms and 84 patients reported depressive symptoms that persisted after discharge.In quarantine settings, we found COVID-19 to be the most influential factor, with the highest number and strength of connections to psychopathology in a network of anxiety and depressive symptoms. Beyond the resolution of the infection, therapeutic interventions targeting PMCs might prove beneficial in reducing suicidality among quarantined individuals with COVID-19. The branching connections of psychopathology and relationships among anxiety and depressive symptoms beyond the direct effect of COVID-19 suggest the possibility of psychological distress propagation after COVID-19 infection, and emphasise the importance of follow-up with mental health services in restoring psychological well-being. Further research is needed to understand the short- and long-term psychological manifestations of COVID-19, and the outcomes of different management strategies in ameliorating psychopathology.. In addition, the order of the edge weights in our model could only be interpreted with caution because of large, overlapping bootstrapped 95% confidence intervals. Moreover, we did not include past psychiatric history in our analysis, which could have confounded our results. We were also unable to illustrate the directionality and possible causal relationship between symptoms, as our data was cross-sectional rather than longitudinal. Finally, it would have been ideal to evaluate anxiety and depressive symptoms by objective observation rather than self-reporting.We performed a network analysis of data obtained from a nationwide study involving randomly assigned participants in major quarantine cites in Qatar, stratified based on infection status. We were able to identify symptoms and factors of high centrality and explore the connections between anxiety and depressive symptoms. This approach is advantageous, offering a more detailed and comprehensive conceptualisation of mental distress compared with a proportional display of conjectured classification of psychopathology. However, our results could have been confounded by age and gender differences between cohorts. The lack of a third arm of controls, with and without COVID-19 outside quarantine facilities, obscured our ability to assess the impact of quarantine on mental health


The overwhelming coronavirus disease- 2019 (COVID-19) cases have called for inevitable home-based care for some cases and direct involvement in COVID-19 dead body burials by many families worldwide. However, data on the knowledge and readiness by families for these practices is still scarce, hence this study among residents of Wakiso district, Uganda.We conducted a cross-sectional study between 6th March and 4th April 2021. Household heads aged 15years and above in 5 sub counties of Wakiso district were interviewed using a pre-tested questionnaire. Multivariable logistic regression analysis was used to assess the association between COVID-19 related knowledge on home-based care and burials with demographics characteristics.We enrolled 205 participants, with a median age of 28 (range: 25–35) years. Majority  were female and had achieved at least secondary level of education . The mean knowledge score on home-based care for COVID-19 patient was 49.5 %, while that on COVID-19 dead body management was 36.5%. Seven (3.4%) respondents were ready to undertake home-based care and dead body management. For the remainder 198 (96.6%) unready respondents reported inadequate knowledge  and lack of personal protective equipment (PPE)  as major barriers for their readiness. There was no statistically significant difference in both the knowledge on home-based COVID-19 patient care and dead body management stratified by demographics characteristics.The knowledge and preparedness for home-based Covid-19 patient care and dead body management are suboptimal among Wakiso district residents. More public education programmes and PPE provision are recommended. The world is experiencing one of its ever-worst moments- the coronavirus disease-2019 (COVID-19) pandemic. The outbreak started in Wuhan City China in the late 2019, and was declared a global emergency on January 30th and a pandemic on 12th March 2020 , mental,With the everyday exponential increases in the number of new infections, countries globally especially the developing countries of Sub-Saharan Africa (SSA) and Asia have been overburdened with patients’ numbers beyond the carrying capacity of the existing hospitals –11. In sAs of 26th September 2021, a total of 232,360,218 COVID-19 cases and 4,758,748 deaths had been reported world-wide . In UganLittle is known of how much knowledgeable the public- “the now home nurses” is concerning the guidelines of managing COVID-19 patients and dead bodies through burial. Though many COVID-19 awareness campaigns in the country have focused on public transmissions, little efforts have been directed towards home based patient care and dead body management safety precautions. With the already existing high number of professional health care workers dying of COVID-19 globally –23 worseCurrently, there is minimal literature about the public’s knowledge stand regarding safe home-based COVID-19 patient care and dead body handling. This study therefore intended to assess the knowledge and preparedness for home-based COVID-19 patient care and family-centred dead body management among residents of Wakiso district which could unveil any existing gaps for appropriate evidence-based interventions that could help prevent avoidable COVID-19 transmissions, reduce new COVID-19 cases, and deaths.This was a cross-sectional study using quantitative techniques conducted between 6th March and 4th April 2021 in Wakiso district Uganda.Wakiso district lies in the central region of the country, bordering with Nakaseke and luweero districts to the north, Mukono district to the east, Kalangala district and Lake Victoria to the south, Mpigi district to the southwest and Mityana district to the northwest. Wakiso district head-quarters are located approximately 20 kilometres northwest of Kampala, the capital of Uganda. It is the second most populated district in the country and was selected as our study site because it ranked second after Kampala among districts reporting the highest number of COVID-19 patients and deaths in the country.The district consists of 17 sub counties, with a total population of 1,997,418 people and 501467 households .We conducted this study among male and female residents of Wakiso district Uganda, aged 15 years and above. We included participants below 18 years of age because there was a significant number of household heads in this district who were less than 18 years, hence their opinions too had to be equally considered. The target population were the household heads in Nangabo, Wakiso, Nsangi, Nabweru, and Wakiso town council sub counties of wakiso district Uganda.The sample size was calculated using Cochran’s equation for sample size estimation:We obtained 41 participants from each of the selected sub counties mentioned above using simple random sampling of the households.Household heads in the selected sub counties of wakiso district who were of sound mind and who consented to participate in the study were recruited. Household heads who were not available at their homes at the time of data collection and those who by the investigators’ judgement were severely ill to respond to the questions were excluded.Independent variables included sex, age, and maximum level of education. Dependent variables included knowledge on covid-19 patient care, covid-19 dead body management, and family preparedness.Since we did not find any pre-validated questionaire used in previous studies about the same topic, we developed the questionnaire using the “WHO Home care for patients with suspected or confirmed Covid-19 and management of their contacts guidelines: interim guidance 12 August 2020” . It compThree questions on socio-demographic characteristics;Nine questions on knowledge about home-based Covid-19 patient care;Nine questions on knowledge about covid-19 dead body management;Two questions about the preparedness for home-based Covid-19 patient care and Covid-19 dead body management.The questions under each section were developed by the authors.The research assistants underwent an extensive training about the research study in order to minimise possible errors during data collection. The questionnaire was pre- tested on 10 household heads in two of the non-selected sub counties of Wakiso district and all the necessary corrections required were noticed and addressed before administering the tool to the final study participants. Each questionnaire used per participant was cross-checked for completeness at the end of the interview. At the end of the data collection period, all the collected data was entered into EpiCollect data forms and was always re-checked by the principal investigator for accurate entries.The study was conducted while following the MOH and the Uganda COVID-19 Task Force guidelines. We provided free medical face masks to all data collectors and the selected study subjects. Each data collector was in addition given a personal hand sanitiser. Prior to each interview conducted, both the interviewer and the interviewee were required to first wear the provided face mask, hand sanitise, and stand/sit at a distance of at least 1meter during the interview.Luganda- the local language in the district, for effective understanding and appropriate answering of the questions. By simple random sampling of households in each of the selected sub counties, a selected household head was approached through a home visit by the data collectors. While observing COVID-19 standard operating procedures (SOPs), a brief introduction about the study was given followed by obtaining informed consent, and answering the questionnaire. The data was collected during a period of 5 weeks, done on only Saturdays and Sundays to ensure maximum capturing of household heads when they were not at their respective work placesWe used an interviewer- administered questionnaire translated to Data was extracted from EpiCollect, cleaned and coded using Microsoft Excel 2016. Statistical analysis was performed using STATA 16 . At univariate analysis, all categorical variables were presented as frequency and percentages whereas numerical variables like age was presented as median and interquartile ratio (IQR) since it was non-parametric. The knowledge on home-based was assessed using 9 questions but each participant could score a maximum of 20 points. The individual scores were then converted to percentages. Knowledge on burial of COVID-19 deceased persons was calculated from nine questions but each participant could score a maximum of 12 points. Each correct response was awarded one point and thereafter individual scores calculated by totalling scores from the nine responses and presented as a percentage. A total score above 50% was considered good knowledge while that below 50% low knowledge. Linear regression was performed to assess the association between demographic variables and COVID-19 related knowledge on both home-based management and burial of the deceased. Results were presented as crude co-efficient, adjusted co-efficient, 95% confidence intervals and p-values. A p < 0.05 was considered statistically significant.The total number of participants enrolled in this study was 205 people. Their median age was 28 (interquartile range: 25–35) years. The majority  of the participants were between the age of 26 and 35 years, were female  and had secondary level of education . The mean knowledge score on home-based care of COVID-19 patients was 49.5%. Seventy-four (36.1 %) participants knew that a medical mask is the recommended facemask to be worn by COVID-19 patients’ caretakers . HoweverThe mean knowledge score on COVID-19 dead body management was 36.5%. Though majority  knew the right thing to be done by the first person to encounter a COVID-19 dead body, only 43 (21.0%) knew the most suitable equipment for protection against the dead body’s fluids splashes. One hundred sixty-six (81.0%) participants didn’t know the recommended number of people for active preparation of the dead body for burial while 137 (66.8%) believed that cultural practices such as bathing the dead body, trimming hair and cutting nails must not be done on COVID-19 dead bodies . OverallOf the 205 respondents, only 7 (3.4%) felt they were ready to participate in safe home-based care of COVID-19 patients and safe burial arrangements as a family. Three of these reported to have undertaken a special training in doing so. Of the 198 (96.6%) participants not ready to participate in home-based care,167(84%) reported inadequate knowledge as the reason. Lack of supplies like PPE , infectious nature of SARS-CoV-2  and insufficient space at home  were also stated. Similarly, insufficient knowledge  was still the most frequent reason for unreadiness to undertake COVID-19 dead body burial arrangements. Other reasons included fear of getting infected with SARS CoV-2 , lack of PPE required for burial  and lack of space .Both the knowledge on home-based care of COVID-19 patients and dead body management did not significantly differ by age, sex or level of education at both simple linear regression and multivariable logistic regression analyses after adjusting for all the three demographic variables . There wThe on-going COVID-19 pandemic is still a global puzzling jeopardy whose fate has remained unknown yet. The overwhelming patient numbers at most health facilities accompanied by the still much fear for stigma from the public among those infected –27 have To our knowledge, little data exists globally concerning the knowledge and readiness for COVID-19 home-based care and dead body management. In this study, we were able to reveal that the knowledge level about both home-based COVID-19 patient care and dead bodies’ management was below 50%, and that over 90% of the residents were not ready to undertake those two initiatives.This study found out that the mean knowledge about home-based covid-19 patient care among participants was at 49.5%, which is a low score. It could be because by the time the study was done, no awareness communications specifically about home-based Covid-19 patient care had been extended to communities in the country. This finding was congruent with that reported among patients at a public hospital in Uganda by Twinamasiko and others which showed a general knowledge about COVID-19 at only 50% . HoweverIn this study, the very low average knowledge (18.28%) expressed about the early warning signs of severe COVID-19 puts many home-cared covid-19 patients at a high risk of progressing from mild-moderate to severe and critical conditions without the care takers’ notice, hence delayed transfer to hospital for advanced management, increasing chances of dying from homes. This low knowledge could possibly be due to the COVID-19 public sensitization message in the country whose content is generally richer in mild to moderate COVID-19 symptoms such as cough, sneezing, body weakness, among others and less emphasis put on severe disease symptoms such as blue lips, confusion. In addition, the message is usually conveyed in English which may not be easily understood as effective as local languages and is via televisions and radios which may not be owned by all the people in communities. This score is however higher than the 5% reported on knowledge about signs of severe pneumonia among care takers in Ghana in 2011 but loweThe mean knowledge score concerning safe COVID-19 dead body management among study participants was 36.5%. Though the possibility of transmission of the virus from a covid-19 copse to living humans is still unclear –19, thisThis study also found out that 96.6% of the residents were not ready to undertake both home-based COVID-19 patient care as well as family-centred COVID-19 dead body burial arrangements. 84% of these reported insufficient knowledge regarding the proper conduction of such activities as the major block. This shows that despite the little knowledge they have so far, they are not confident enough to perform such activities as families alone. Of the 3.4% (n = 7) respondents who were ready to perform such activities, 3 were health care workers who reported to have undertaken a special training in doing so. This could imply that if such similar training is provided to the general public at large, the percentage of those ready to take on this proposed new involvement would increase, with reduced fear and chances of viral transmissions among people in homes. This is congruent with an observation by Sharma et al in India where family members of a covid-19 deceased refused to even have a look at the dead body due to fear .In this study, there was no association between the residents’ knowledge on home-based patient care, dead body management or preparedness with age, sex, or education level. This could possibly be due to the fact that COVID-19 is a new issue which came with almost uniform sensitization to the public regardless of one’s sex, age or education level hence uniform exposure to covid-19 information and roughly equal knowledge acquisition by all groups of people.This study has some limitations. Firstly, no standardised tool had been previously validated for assessment of knowledge on COVID-19 home-based care, dead body management or their preparedness. However, the questions have been formulated based on the WHO guidelines for home-based COVID-19 patient care and dead body management , 12. SecIn this study, knowledge on both home-based care of COVID-19 patient and handling of dead bodies of those who succumbed to the disease was suboptimal. Insufficient knowledge, inadequate PPE, small space at home, and fear of the infectious nature of the virus are the major barriers for the preparedness. Nation-wide public education programmes coupled with sensitization and awareness about home-based COVID-19 patient care and dead body management plus provision of basic PPE to homes by the concerned stakeholders are recommended to address these challenges even in case of future pandemics.


Our results indicate that delirium in COVID-19-related ARDS is more severe since its onset despite a relatively less severe systemic condition at the point of ICU admission and required higher dosages of antipsychotic and non-benzodiazepinic sedative therapy respect to non-COVID patients. Finally, the correlation analysis showed a direct association between the male gender and maximum dosage of anti-delirium medications needed within the COVID-19 group, which was taken as a surrogate of delirium severity. Overall, our results seem to indicate that pathogenetic factors specifically associated to severe COVID-19 are responsible for the high severity of delirium, paving the way for future research focused on the mechanisms of the cognitive alterations associated with COVID-19.The clinical outcome of the disease provoked by the SARS-CoV-2 infection, COVID-19, is largely due to the development of interstitial pneumonia accompanied by an Acute Respiratory Distress Syndrome (ARDS), often requiring ventilatory support therapy in Intensive Care Units (ICUs). Current epidemiologic evidence is demonstrating that the COVID-19 prognosis is significantly influenced by its acute complications. Among these, delirium figures as one of the most frequent and severe, especially in the emergency setting, where it shows a significantly negative prognostic impact. In this regard, the aim of our study is to identify clinical severity factors of delirium complicating COVID-19 related-ARDS. We performed a comparative and correlation analysis using demographics, comorbidities, multisystemic and delirium severity scores and anti-delirium therapy in two cohorts of ARDS patients with delirium, respectively, due to COVID-19 ( Coronavirus disease 19 (COVID-19) is an acute illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) , 4. In tSARS-CoV-2 belongs to the same family of Respiratory Syndrome Coronavirus 1 (SARS-CoV-1) and Middle East Respiratory Syndrome Coronavirus (MERS-CoV), which share similar mechanisms of invasion of the host tissues . NoteworAlso for SARS-CoV-2, a neuroinvasive potential has been suggested as a possible pathogenetic mechanism responsible for the neurological and psychiatric manifestations often occurring in COVID-19  is more frequent and/or severe in COVID-19 patients compared to non-COVID-19 patients in emergency settings and that premorbid and or disease-related risk factors may exist in delirium complicating COVID-19. To test this hypothesis, we used data from a pre-pandemic cohort of non-COVID-19 related ARDS patients from the same ICU as controls.We conducted a retrospective observational study on two samples of ICUs patients with delirium complicating an ARDS, respectively, due to COVID-19 (COV+/DEL+ group) or to other medical conditions (COV–/DEL+ group).Inclusion criteria were hospitalization in ICUs of the IRCSS Ca' Granda, Ospedale Maggiore Policlinico in Milan, Italy affected by COVID-19 (first group) and not affected by COVID-19 (second group).We retrospectively reviewed the electronic health records of a cohort of critically ill adult patients who developed delirium while admitted to the ICUs of the IRCSS Ca' Granda, Ospedale Maggiore Policlinico in Milan, Italy, which is a tertiary referral center for the treatment of patients with acute respiratory failure. The sample included two groups of delirium-complicated patients affected by ARDS due to COVID-19 (COV+/DEL+) or to other diseases (COV–DEL+). Both groups were expected to exhibit symptoms consistent with ARDS and delirium. For the second group (COVID – / DEL +), patients were evaluated before the first case of SARS-CoV-2 diagnosed in China (December 2019). The outline of the two groups is shown in In both groups, ARDS was diagnosed according to Berlin definition criteria  and the The presence of inclusion criteria and the adherence to diagnostic criteria for delirium and ARDS were confirmed by two expert medical researchers of the Psychiatry Unit and two expert intensivists of Ospedale Maggiore Policlinico. At the time of the study, all patients had not been vaccinated since the vaccine against the SARS-CoV-2 virus did not yet exist. The study was approved by the Ethics Committee “Milan Area 2” .- demographics, including age, sex and ethnicity- past medical history- history of psychiatric disorders- Sequential Organ Failure Assessment (SOFA) score, that describes the presence and severity of organ failures  and is used for the prognostic stratification of ICUs patients - severity of delirium, assessed using the short form of the Confusion Assessment Method—Severity (CAM-S) .- treatment of delirium For each patient, the following data were collected retrospectively from the digitalized data records of the Ospedale Maggiore Policlinico Intensive Care Unit:These data were reported in an electronic case report form with the Excel format, in compliance with current privacy regulations. Each participant, at the time of enrollment, was assigned a unique code and data were anonymized: only local investigators could trace the identity of enrolled subjects enrolled. The database was password-protected and accessible only to study personnel designated by the principal investigator.2 test for testing difference in co-occurrences for dichotomic and categorical variables. Since some anti-delirium drugs  were administered to less than the 50% of patients in each group  of the significant correlations was inferred from the Spearman's rho for the correlations between continuous variables or between monotonic categorical and binomial variables as well as from the comparison of medians in the correlations between continuous and binomial variables.A database was created specifically for the management and collection of data using Microsoft Excel, stored in anonymous digital form on the servers of the Policlinico Hospital of Milan. Julia language was used for data preprocessing, analysis, and implementation of the plots and R for basic statistical analyses. We proceeded with a primary consistency check in the data encoding, correcting any input errors with consequent uniformity of the data. Given the non-normal distribution of the variables collected, we performed averages comparisons between the “COVID +; Delirium +”; and “COVID –; Delirium +,” by means of non-parametric statistics. For the between-groups analysis, we selected Mann-Whitney U test for the median comparison of continuous variables and χch group , they haThe sample included two groups of patients, matched for age and sex: (a) the COV+/DEL+ group included patients hospitalized in the ICUs between February 21st 2020 and June 29th 2020 for ARDS due to COVID-19 who required invasive mechanical ventilation and developed delirium during the ICUs stay; (b) the COV-/DEL+ group included patients hospitalized between January 2014 and December 2019 in the same ICUs for ARDS related to different medical conditions requiring invasive mechanical ventilation support and complicated by delirium.The COV+/DEL+ group was made of 40 patients  with a mean age of 58.45 ± 8.78 years, whilst the COV–/DEL+ group included 38 patients , with a mean age of 56.76 ± 11.95 years. Descriptive and comparative analysis' results of the two study groups are reported in U = 516.5, p-value = 0.007) and significantly lower SOFA scores at ICUs admission  compared to COV-/DEL+ patients  and total bilirubin levels  in the COV+/DEL+ respect to the COV–/DEL+ group , showing a predominant administration of high-dose vasopressors (cardiovascular score = 4) in COV–/DEL+ patients (frequency 47.4%) in contrast to predominant normal arterial pressures (cardiovascular score = 0) in the COV+/DEL+ group (frequency 70.0%).In the comparative analysis, the COV+/DEL+ group presented significantly higher CAM-S scores at delirium onset  and hydroxyzine  than the COV–/DEL+ group   .U = 92.500, p-value = 0.035), quetiapine , hydroxyzine  and lorazepam  administered. Also, positive correlations have been found between the dose of lorazepam and SOFA scores  as well as between the quetiapine and hydroxyzine dose and the SOFA's cardiovascular component . On the contrary, a negative correlation between the dose of alprazolam and the PaO2 to FiO2 ratio was demonstrated   and between total bilirubin at ICU admission and lorazepam dose  as well as a negative correlation between midazolam administration and CAM-S at delirium onset   . None of= 0.038) .In this retrospective observational study involving two cohorts of patients with ARDS due to COVID-19 or to other medical conditions who developed delirium during ICUs stay, we primarily aimed at describing demographics, clinical features, and anti-delirium treatments. Furthermore, we performed a comparative analysis between the COV+/DEL+ and COV–/DEL+ groups as well as a set of within-group correlation analyses to explore the relationship between baseline variables, systemic involvement and delirium severity, as indicated by the CAM-S score at the onset and by the highest dose of anti-delirium therapies administered, used as surrogate markers of delirium course severity.2 to FiO2 ratio and alprazolam maximum dose, consistently with a limited use of benzodiazepine in worst respiratory conditions. Thus, the contrast between the lower systemic severity of ARDS and the higher severity of delirium in patients with COVID-19 observed in our analysis could be explained by the peculiar neuro-invasive capacity of SARS-CoV-2 and its association with cognitive impairment, frequently evoked by the most recent literature  at ICUs admission delirium complicating COVID-related ARDS was more severe since its onset. By comparing each single components forming the SOFA score, we observed that higher mean bilirubin levels and blood platelets count, both within normal limits, were found in the COVID-19 respect to the non-COVID-19 patients. On the contrary, a higher cardiovascular score was observed in the non-COVID-19 group, in which most patients required a treatment with high dose vasopressors (47% with cardiovascular score = 4), respect to most COVID-19 patients, which showed, instead, a Mean Arterial Pressure (MAP) ≥70 mmHg (70% with cardiovascular score = 0) at ICU admission. Notably, this latter result is in line with previous evidence having demonstrated a less extensive use of vasopressors at ICU admission and a later vasopressors commencement over the ICU stay in COVID-19 pneumonia respect to non-COVID community acquired pneumonia . Also, tterature , 27. MorFinally, current literature is increasingly focusing on the long-term effects of COVID-19 on patients recovered from the acute phase of the disease, leading to the definition of a “post-COVID syndrome,” characterized by long-term heterogenous and chronic symptoms. This syndrome seems to be more frequent in subjects that suffered from severe ARDS requiring invasive respiratory support during the acute phase . Interesp = 0.05). Considering that our cohort of patients had been hospitalized during the early phase of the pandemic, characterized by a scarcity of clinical guidelines for the treatment of the COVID-19-associated delirium, these data could reflect the tendency of the ICUs clinicians to privilege a therapy with lower doses of benzodiazepines, probably based mainly on clinical observation. Accordingly, a recent longitudinal study has demonstrated that treatment with benzodiazepines is one of the most important risk factors for delirium in ICUs-hospitalized COVID-19, discouraging the benzodiazepines treatment in these patients .The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The COVID-19 pandemic and relevant prevention and control measures may affect the mental health and induce depressive symptoms in fathers with concurrent partner delivery exposure. This study aims to investigate the prevalence of depression in fathers with simultaneous exposure to COVID-19 pandemic and the effects of family functions on paternal perinatal depression (PPD) risk.A cross-sectional study was conducted among the perinatal fathers recruited in a large tertiary hospital in Wuhan across the whole pandemic period from 31 December 2019 to 11 April 2020. Edinburgh Postnatal Depression Scale (EPDS) and APGAR family function scale were used to evaluate PPD and family function, respectively. Chi-square test and multivariable-adjusted logistic regression model were applied for data analysis.Among the 1187 participants, the prevalence of PPD was 13.82% throughout the COVID-19 pandemic. Compared with that in the time period before the announcement of human-to-human transmission on 19 January 2020, the depression risk was significantly lower during the traffic restriction  and public transportation reopening periods . Poor/fair family functions was associated with elevated depression risk . Individuals reporting a low family income and smoking had high depression risks.A declined risk of PPD was observed over the traffic restriction period of the COVID-19 pandemic. An improved family function may help alleviate the risk of PPD during the pandemic. Health authorities are recommended to formulate targeted prevention and control strategies to handle PPD.The online version contains supplementary material available at 10.1186/s12888-021-03325-9. Parent mental health status is important in offspring development , 2. Alththe Guidance Manual on the Prevention and Control of Novel Coronavirus-Infection Pneumonia in the Community issued by the national government in response to the COVID-19 pandemic [Coronavirus Disease 2019 (COVID-19) was first reported in December 2019 in Wuhan, Hubei province, China and has since spread worldwide. In addition to the direct physical health impairment caused by viral infections, the ongoing COVID-19 pandemic greatly threatens the mental health of pandemic-exposed individuals. The Chinese government promulgated Home quarantine is implemented as an important measure to reduce human-to-human transmission in the COVID-19 control; however, this policy may also increase the role of family function among home-staying residents. Family function is an important reflection of social support. Insufficient social support during pregnancy could result in an increased risk of joint postnatal depression in mothers and fathers . A systeTo date, the prevalence and influential factors of PPD during the COVID-19 pandemic have never been addressed. This study aims to investigate the prevalence of PPD among the fathers exposed to the COVID-19 pandemic and to determine relevant risk factors. The findings provide new knowledge for the global prevention and control of PPD in the COVID-19 pandemic.https://www.wjx.cn/) was provided to the participants and they could use their cellphone to fill in the survey in their spare time. Given that the nucleic acid detection method for COVID-19 was not fully developed in the early period of the pandemic, all participants were assumed to be not infected by COVID-19 when they had no clinical symptoms of COVID-19 including fever, respiratory symptoms and abnormal chest CT and had no history of direct contact with patients with COVID-19.This study adopted a cross-sectional design and was conducted at a maternity care hospital located in Wuhan city, a tertiary hospital that is the largest maternal and childcare centre in the Hubei province. Data on family function, demographics and health behaviour factors were collected. Participants included men whose partners were hospitalized in their perinatal period  for delivery. Trained doctors and nurses introduced this survey to eligible individuals and obtained their oral agreement of participation from 31 December 2019 to 11 April 2020. A two-dimensional barcode of Questionnaire star , which was compiled by Cox et al. in 1987 and is suitable for depression assessment because of its good reliability and validity . The ChiThe pandemic time was divided into the following four periods to evaluate the effects of the COVID-19 pandemic on participants’ depression: (i) 1st period before the official announcement of human-to-human transmission by the National Health Commission of China on 19 January 2020 (31 December 2019 to 18 January 2020); (ii) 2nd period of thereafter to the day when traffic restrictions started (19–23 January 2020); (iii) 3rd period of thereafter to the day of zero newly confirmed COVID-19 cases report (24 January to 27 March 2020); and (iv) 4th period of thereafter to the day when public traffic transportations reopened (28 March to 11 April 2020). Family function was regarded as an important independent variable in relation to PPD and was examined using the APGAR scale, which was developed by Smilkstein and determined family function from five dimensions  [Demographics used as covariates included age , ethnicity (Han and others), education , urban/rural, family income of last year , insurance (yes or no) and first-time father (yes or no). Other covariates of health behaviour factors, including smoking/passive smoking within 1 year (yes or no) and exercise within 1 year (yes or no), were also examined.p-value of less than 0.05 was considered as statistically significant.All statistical analyses were performed using SAS 9.4 for Windows. Chi-square test was used to analyse the between-group differences of depression prevalence stratified by factors as the COVID-19 pandemic periods, family function, demographics , and health behaviour factors (smoking and exercise). Multiple logistic regression modelling was applied to analyse the dependency of prevalent depression on the mentioned explanatory variables. Model 1 included the periods of the COVID-19 pandemic and family function as independent variables. Model 2 analysed the associations of the COVID-19 pandemic, family function and depression risk in the adjustment of demographics. Model 3 involved health behaviour factors for covariate adjustment in addition to those in model 2. Results from multiple logistic regression analyses were reported as adjusted odds ratios (OR) and 95% confidence intervals (CI). All tests were two-sided, and a n = 121) and patients with self-reported depression (n = 33), 1187 participants (88.52%) were finally included in the statistical analysis.A total of 1341 participants were found eligible for this study. After the removal of individuals with incomplete questionnaires (p < 0.01). Approximately 93.43% of fathers had insurance, and those without insurance had a relatively higher proportion of PPD . Almost two-thirds of the participants (67.31%) were first-time fathers and had significantly lower proportion of PPD than the others .The prevalence of PPD was 13.82% throughout the COVID-19 pandemic (Table p < 0.01). Approximately 64.94% of participants had a habit of exercise in the last year.Less than half of the participants (41.16%) reported smoking during the past year and had higher proportion of PPD than those who did not smoke .Table The participants had significantly lower PPD risk in the 3nd  and 4rd  periods of the COVID-19 pandemic than in the 1st period  was 3.00–30.50% . VariousCritically, our study revealed that the prevalence of PPD peaked to the highest before the human-to-human transmission announcement in the COVID-19 pandemic, and the traffic restriction led to a reduced depression risk. A similar result was observed among women who delivered at the Soroka University Medical Center . The higSimilar results were observed for the 10 items of EPDS. Specifically, fathers with thoughts of self-harm were at a high risk of self-harm behaviours and suicide. To the best of our knowledge, this study is the first to report the decreased prevalence of self-harm ideation in fathers during the quarantine period. A previous work concentrated on the depression of pregnant women who showed high risks of depression and self-harm ideation during the COVID-19 outbreak in China . AnotherFamily dysfunction is an important determinant of depression risks among adolescents , studentAs another determinant of paternal depression, low household income contributed to increased depression risk among new fathers. This finding was in line with previous studies , 32. TheMaternal depression is related to smoking before and within pregnancy –35. In tThis study has several limitations. Firstly, the cross-sectional design limited the causal relationship observation among factors. Secondly, data were self-reported, thereby possibly compromising the measurement accuracy of PPD and other related factors. Thirdly, the findings were only focused on targeted fathers in hospitals and cannot be generalized to those outside hospitals within the entire perinatal period. Fourthly, whether the women were in their prenatal or postnatal period when fathers participated in the survey has not been recorded. Moreover, this study drew conclusions based on findings from one hospital in Wuhan. Multi-centre studies are necessary to further address the issues related to PPD.Depression in perinatal mothers has been widely studied, but that in fathers is underestimated. The mental health of mothers and fathers must be promoted. This work presented a declined risk of PPD over the traffic restriction period. An improved family function may help alleviate the risk of PPD during the pandemic. Household income and smoking were also found to be associated with PPD risk. These findings provide evidence for health authorities to formulate targeted prevention and control strategies against PPD in relation to partner delivery during the COVID-19 pandemic.Additional file 1.