Critical Care Requirements Under Uncontrolled Transmission of SARS-CoV-2

Invited Commentary: Modern Epidemiology Confronts COVID-19-Reflections From Psychiatric Epidemiology

Dimitris et al. (Am J Epidemiol. 2022;191(6):980-986) outline how the coronavirus disease 2019 (COVID-19) pandemic has, with mixed results, put epidemiology under the spotlight. While epidemiologic theory and methods have been critical in many successes, the ongoing global death toll from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the sometimes chaotic public messaging underscore that epidemiology as a field has room for improvement. Here, we use examples from psychiatric epidemiologic studies conducted during the COVID-19 era to reflect on errors driven by overlooking specific major methodological advances of modern epidemiology. We focus on: 1) use of nonrepresentative sampling in online surveys, which limits the potential knowledge to be gained from descriptive studies and amplifies collider stratification bias in causal studies; and 2) failure to acknowledge multiple versions of exposures (e.g., lockdown, school closure) and differences in prevalence of effect measure modifiers across contexts, which causes violations of the consistency assumption and lack of effect transportability. We finish by highlighting: 1) the heterogeneity of psychiatric epidemiologic results during the pandemic across place and sociodemographic groups and over time; 2) the importance of following the foundational advancements of modern epidemiology even in emergency settings; and 3) the need to limit the role of political agendas in cherry-picking and reporting epidemiologic evidence.

The impact of the COVID-19 pandemic on suicide mortality in Spain: Differences by sex and age

BACKGROUND

Variations in suicide following the initial COVID-19 pandemic outbreak were heterogeneous across space, over time, and across population subgroup. Whether suicide has increased during the pandemic in Spain, a major initial COVID-19 hotspot, remains unclear, and no study has examined differences by sociodemographic group.

METHODS

We used 2016-2020 data on monthly suicide deaths from Spain's National Institute of Statistics. We implemented Seasonal Autoregressive Integrated Moving Average (SARIMA) models to control seasonality, non-stationarity, and autocorrelation. Using January 2016-March 2020 data, we predicted monthly suicide counts (95 % prediction intervals) between April and December 2020, and then compared observed and predicted monthly suicide counts. All calculations were conducted for the overall study population and by sex and age group.

RESULTS

Between April and December 2020, the number of suicides in Spain was 11 % higher-than-predicted. Monthly suicide counts were lower-than-expected in April 2020 and peaked in August 2020 with 396 observed suicides. Excess suicide counts were particularly salient during the summer of 2020 - largely driven by over 50 % higher-than-expected suicide counts among males aged 65 years and older in June, July, and August 2020.

DISCUSSION

The number of suicides increased in Spain during the months following the initial COVID-19 pandemic outbreak in Spain, largely driven by increases in suicides among older adults. Potential explanations underlying this phenomenon remain elusive. Important factors to understand these findings may include fear of contagion, isolation, and loss and bereavement - in the context of the particularly high mortality rates of older adults during the initial phases of the pandemic in Spain.

SARS-CoV-2 Infection During the First and Second Pandemic Waves in Spain: the ENE-COVID Study

Objectives. To describe participant characteristics associated with severe acute respiratory syndrome coronavirus 2 infection in Spain's first 2 COVID-19 waves per the Spanish National Seroepidemiological Survey of SARS-CoV-2 Infection (ENE-COVID). Methods. A representative cohort of the noninstitutionalized Spanish population, selected through stratified 2-stage sampling, answered a questionnaire and received point-of-care testing April to June 2020 (first wave: n = 68 287); previously seronegative participants repeated the questionnaire and test November 2020 (second wave: n = 44 451). We estimated seropositivity by wave and participant characteristics, accounting for sampling weights, nonresponse, and design effects. Results. We found that 6.0% (95% confidence interval [CI] = 5.7%, 6.4%) of Spain's population was infected by June and 3.8% (95% CI = 3.5%, 4.1%) more by November 2020. Both genders were equally affected. Seroprevalence decreased with age in adults 20 years and older in the second wave; socioeconomic differences increased. Health care workers were affected at 11.1% (95% CI = 9.0%, 13.6%) and 6.1% (95% CI = 4.4%, 8.5%) in the first and second waves, respectively. Living with an infected person increased infection risk to 22.1% (95% CI = 18.9%, 25.6%) in the first and 35.0% (95% CI = 30.8%, 39.4%) in the second wave. Conclusions. ENE-COVID characterized the first 2 pandemic waves, when information from surveillance systems was incomplete. (Am J Public Health. 2023;113(5):533-544. https://doi.org/10.2105/AJPH.2023.307233).

Mental health problems and needs of frontline healthcare workers during the COVID-19 pandemic in Spain: A qualitative analysis

Background

Healthcare workers (HCWs) from COVID-19 hotspots worldwide have reported poor mental health outcomes since the pandemic's beginning. The virulence of the initial COVID-19 surge in Spain and the urgency for rapid evidence constrained early studies in their capacity to inform mental health programs accurately. Here, we used a qualitative research design to describe relevant mental health problems among frontline HCWs and explore their association with determinants and consequences and their implications for the design and implementation of mental health programs.

Materials and methods

Following the Programme Design, Implementation, Monitoring, and Evaluation (DIME) protocol, we used a two-step qualitative research design to interview frontline HCWs, mental health experts, administrators, and service planners in Spain. We used Free List (FL) interviews to identify problems experienced by frontline HCWs and Key informant (KI) interviews to describe them and explore their determinants and consequences, as well as the strategies considered useful to overcome these problems. We used a thematic analysis approach to analyze the interview outputs and framed our results into a five-level social-ecological model (intrapersonal, interpersonal, organizational, community, and public health).

Results

We recruited 75 FL and 22 KI interviewees, roughly balanced in age and gender. We detected 56 themes during the FL interviews and explored the following themes in the KI interviews: fear of infection, psychological distress, stress, moral distress, and interpersonal conflicts among coworkers. We found that interviewees reported perceived causes and consequences across problems at all levels (intrapersonal to public health). Although several mental health strategies were implemented (especially at an intrapersonal and interpersonal level), most mental health needs remained unmet, especially at the organizational, community, and public policy levels.

Conclusions

In keeping with available quantitative evidence, our findings show that mental health problems are still relevant for frontline HCWs 1 year after the COVID-19 pandemic and that many reported causes of these problems are modifiable. Based on this, we offer specific recommendations to design and implement mental health strategies and recommend using transdiagnostic, low-intensity, scalable psychological interventions contextually adapted and tailored for HCWs.

Role of medical comorbidity in the association between psychiatric disorders and mortality among patients with COVID-19

We examined whether excess chronic medical comorbidity mediated excess COVID-19 inpatient mortality among people with mental disorders in the early phase of the pandemic, a question with important implications for public health and clinical decision-making. Using records of 2599 COVID-19 hospitalized patients, we conducted a formal causal mediation analysis to estimate the extent to which chronic comorbidity mediates the association between mental disorders and COVID-19 mortality. The Odds Ratio (95% CI) for Natural Indirect Effect and Controlled Direct Effect were 1.07(1.02, 1.14) and 1.40 (1.00, 1.95), respectively, suggesting that a large proportion of excess COVID-19 mortality among people with mental disorders may be explained by factors other than comorbidity.

Prospective Analysis Between Neutrophil-to-Lymphocyte Ratio on Admission and Development of Delirium Among Older Hospitalized Patients With COVID-19

Objective: To examine any prospective association between neutrophil-to-lymphocyte ratio (NLR) at hospital admission and subsequent delirium in older COVID-19 hospitalized patients comparing by sex and age groups. Methods: The sample consisted of 1,785 COVID-19 adult inpatients (minimum sample size required of 635 participants) admitted to a public general hospital in Madrid (Spain) between March 16th and April 15th, 2020. Variables were obtained from electronic health records. Binary logistic regression models were performed between baseline NLR and delirium adjusting for age, sex, medical comorbidity, current illness severity, serious mental illness history and use of chloroquine and dexamethasone. An NLR cut-off was identified, and stratified analyses were performed by age and sex. Also, another biomarker was tested as an exposure (the systemic immune-inflammation index -SII). Results: 55.3% of the patients were men, with a mean age of 66.8 years. Roughly 13% of the patients had delirium during hospitalization. NLR on admission predicted subsequent delirium development (adjusted OR = 1.02, 95 percent CI: 1.00-1.04, p = 0.024). Patients between 69 and 80 years with NLR values > 6.3 presented a twofold increased risk for delirium (p = 0.004). There were no sex differences in the association between baseline NLR and delirium (p > 0.05) nor SII predicted delirium development (p = 0.341). Conclusion: NLR is a good predictor of delirium during hospitalization, especially among older adults, independently of medical comorbidity, illness severity, and other covariates. Routine blood tests on admission might provide valuable information to guide the decision-making process to be followed with these especially vulnerable patients.