The Deepening of Disciplinary Content: Public Health in Post-Covid India

We are amid the COVID-19 pandemic, the biggest public health event in a century that has caused illness in almost 180 million persons and loss of over 4 million lives worldwide, and disrupted the social and economic life of all societies. More such crises are predicted to occur in the coming decades, and there are massive pre-existing unaddressed public health needs in all countries. It is to be anticipated that in the post-COVID world there will be greater attention to the often neglected discipline of public health.

Adapting to change: Clalit's response to the COVID-19 pandemic

The COVID-19 pandemic is the most significant global health event of the past century. The profound and unexpected changes that it brought about have forced healthcare organizations to make far-reaching adjustments to accommodate the new reality. With the outbreak of the pandemic in Israel and the understanding of its consequences, Clalit Health Services (Clalit), the largest healthcare organization in Israel, rapidly mobilized in order to provide the best response possible from the perspective of both its patients and its employees. In the short term, four designated workgroups were established just days into the pandemic. Their task was to prepare operational work plans to achieve the following goals: providing the best possible treatment for COVID patients; maintaining the level of care for non-COVID patients; protecting healthcare personnel without compromising their competence and level of functioning; and beginning the process of post-crisis planning. In the context of the long term, and with the understanding that the changes in healthcare brought about by the COVID-19 pandemic would be long-lasting and irreversible, and would act as a catalyst in Clalit’s preparations for the future, Clalit has carried out the called-for modifications in its organizational strategy. This was based on the need to shift service and treatment foci from the hospitals to the community and the patient’s home and his cellular device, by means of strengthening Clalit’s strategic abilities to become more proactive, more digital and more home-based. In this article, we present a survey of Clalit’s preparations for the new reality in the short and medium terms, as well as the leveraging of insights gained during the first wave of the pandemic, with goal of revising Clalit’s long-term strategic plan. We conclude and point out the organizational abilities required for optimal response to future large-scale emergencies: The ability to quickly identify the need for change, respond quickly while harnessing the various parts of the organization in order to provide an agile and adaptive response, and facilitate long-term planning activity in parallel to providing an operational response in the short and medium terms.

Incidence of Mental Health Events and Its Association with Survival Among Patients with Diffuse Large B-Cell Lymphoma: A Population-Based Cohort Study

Introduction While prior studies suggest that mental health complications are underdiagnosed and undertreated in patients with cancer, a paucity of data exists for patients with diffuse large B-cell lymphoma (DLBCL). Indeed, mental illness can impact the success of potentially curative treatment for DLBCL including delays in treatment initiation, poor chemotherapy compliance, and suboptimal rates of completion. Accordingly, we aimed to examine the risk of incident mental health events following DLBCL diagnosis, and the association of mental health conditions with overall survival (OS). Methods We conducted a population-based observational study using linked administrative healthcare databases from Ontario, Canada. All Ontario residents aged ≥18 years with DLBCL treated with rituximab-based chemotherapy for curative intent between January 2005 and December 2017 were identified and followed from the date of first rituximab until March 1, 2020. The primary outcome was any incident mental health event (emergency department visit, hospitalization, or outpatient visit for mood disturbance including depression and anxiety, psychotic disorder, or substance-related disorder). Patients with a DLBCL diagnosis without pre-existing mental health comorbidity in the 2-years prior to start of rituximab were matched to mental health condition- and cancer-free controls in a 1:4 ratio based on birth year and sex. The cumulative incidence function was used to estimate incidence of mental health events while accounting for the competing risk of death, and differences were compared using Gray's K-sample test. A cause-specific Cox regression model was used to estimate mental health events up to two-years following rituximab initiation, while controlling for relevant covariates (sex, age modeled in 10-year interval increments, rural vs. urban residence, income quintile, and quartile of sum of aggregated diagnosis groups (ADGs) as a measure of comorbid disease burden (mental health and cancer diagnoses excluded). The secondary outcome was the association of mental health conditions on OS for all identified DLBCL patients, evaluated using Cox regression (with mental health event as time-varying variable). Results We identified 10,299 patients diagnosed with DLBCL and treated with a rituximab-containing regimen in Ontario, with median age 67 years (IQR 56-76), 45.9% female, median ADG score of 9 (IQR 6-11), and median of 6 cycles of rituximab received (IQR 4-6). For patients with available stage data (49.2% of cohort), 34.6% had stage IV at diagnosis. When compared to birth year- and sex-matched controls (n=29,620), DLBCL cases (n=7,405) had a greater comorbidity burden (p<0.001). During a median follow-up of 5.16 years (SD+4.13), 28.8% of DLBCL patients without pre-existing mental health conditions developed an incident mental health event. With adjustment of potential confounders, patients with DLBCL still had significantly higher risk of an incident mental health event compared to controls (adjusted hazard ratio [aHR] 1.29, 95% confidence interval [CI] 1.21-1.39, p<0.0001) (Figure 1, Table 1). Younger age, female sex and higher comorbidity burden were associated with an increased risk of an incident mental health event (Table 1). In addition, having a mental health condition (either pre-existing or after start of rituximab) was associated with a significantly worse one-year OS (aHR 1.11, 95% CI 1.01-1.22, p<0.0001) and at end of follow-up (aHR 1.24, 95% CI 1.16-1.32, p<0.0001; Table 2). Additional factors independently associated with worse overall OS included older age, increased comorbidity, and male sex (Table 2). Conclusions In this large population-based study, patients with DLBCL were found to have a significantly higher risk of incident mental health events compared to controls. Moreover, the presence of a mental health condition was associated with worse survival outcomes. These data suggest that patients with DLBCL, particularly those with pre-existing mental health condition(s), would benefit from routine mental health assessment and management during follow-up, not only for mental health itself but also potentially to improve survival. Figure 1 Figure 1. Disclosures Prica: Astra-Zeneca: Honoraria; Kite Gilead: Honoraria.

Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcare

Accurate and explainable health event predictions are becoming crucial for healthcare providers to develop care plans for patients. The availability of electronic health records (EHR) has enabled machine learning advances in providing these predictions. However, many deep-learning-based methods are not satisfactory in solving several key challenges: 1) effectively utilizing disease domain knowledge; 2) collaboratively learning representations of patients and diseases; and 3) incorporating unstructured features. To address these issues, we propose a collaborative graph learning model to explore patient-disease interactions and medical domain knowledge. Our solution is able to capture structural features of both patients and diseases. The proposed model also utilizes unstructured text data by employing an attention manipulating strategy and then integrates attentive text features into a sequential learning process. We conduct extensive experiments on two important healthcare problems to show the competitive prediction performance of the proposed method compared with various state-of-the-art models. We also confirm the effectiveness of learned representations and model interpretability by a set of ablation and case studies.

Structural Basis for SARS-CoV-2 Nucleocapsid Protein Recognition by Single-Domain Antibodies

The COVID-19 pandemic, caused by the coronavirus SARS-CoV-2, is the most severe public health event of the twenty-first century. While effective vaccines against SARS-CoV-2 have been developed, there remains an urgent need for diagnostics to quickly and accurately detect infections. Antigen tests, particularly those that detect the abundant SARS-CoV-2 Nucleocapsid protein, are a proven method for detecting active SARS-CoV-2 infections. Here we report high-resolution crystal structures of three llama-derived single-domain antibodies that bind the SARS-CoV-2 Nucleocapsid protein with high affinity. Each antibody recognizes a specific folded domain of the protein, with two antibodies recognizing the N-terminal RNA binding domain and one recognizing the C-terminal dimerization domain. The two antibodies that recognize the RNA binding domain affect both RNA binding affinity and RNA-mediated phase separation of the Nucleocapsid protein. All three antibodies recognize highly conserved surfaces on the Nucleocapsid protein, suggesting that they could be used to develop affordable diagnostic tests to detect all circulating SARS-CoV-2 variants.

Structural basis for SARS-CoV-2 Nucleocapsid protein recognition by single-domain antibodies

The COVID-19 pandemic, caused by the coronavirus SARS-CoV-2, is the most severe public health event of the twenty-first century. While effective vaccines against SARS-CoV-2 have been developed, there remains an urgent need for diagnostics to quickly and accurately detect infections. Antigen tests, particularly those that detect the abundant SARS-CoV-2 Nucleocapsid protein, are a proven method for detecting active SARS-CoV-2 infections. Here we report high-resolution crystal structures of three llama-derived single-domain antibodies that bind the SARS-CoV-2 Nucleocapsid protein with high affinity. Each antibody recognizes a specific folded domain of the protein, with two antibodies recognizing the N-terminal RNA binding domain and one recognizing the C-terminal dimerization domain. The two antibodies that recognize the RNA binding domain affect both RNA binding affinity and RNA-mediated phase separation of the Nucleocapsid protein. All three antibodies recognize highly-conserved surfaces on the Nucleocapsid protein, suggesting that they could be used to develop affordable diagnostic tests to detect all circulating SARS-CoV-2 variants.

Using social media data to assess the impact of COVID-19 on mental health in China

Background. The outbreak and rapid spread of COVID-19 not only caused an adverse impact on physical health but also brought about mental health problems among the public.Methods. To assess the causal impact of COVID-19 on psychological changes in China, we constructed a city-level panel data set based on the expressed sentiment in the contents of 13 million geotagged tweets on Sina Weibo, the Chinese largest microblog platform.Results. Applying a difference-in-differences approach, we found a significant deterioration in mental health status after the occurrence of COVID-19. We also observed that this psychological effect faded out over time during our study period and was more pronounced among women, teenagers and older adults. The mental health impact was more likely to be observed in cities with low levels of initial mental health status, economic development, medical resources, and social security.Conclusions. Our findings may assist the understanding of COVID-19’s mental health impact and yield useful insights on how to make effective psychological interventions in this kind of sudden public health event.