Mixing Individual and Collective Behaviours to Predict Out-of-Routine Mobility (preprint)

Predicting human displacements is crucial for addressing various societal challenges, including urban design, traffic congestion, epidemic management, and migration dynamics. While predictive models like deep learning and Markov models offer insights into individual mobility, they often struggle with out-of-routine behaviours. Our study introduces an approach that dynamically integrates individual and collective mobility behaviours, leveraging collective intelligence to enhance prediction accuracy. Evaluating the model on millions of privacy-preserving trajectories across three US cities, we demonstrate its superior performance in predicting out-of-routine mobility, surpassing even advanced deep learning methods. Spatial analysis highlights the model's effectiveness near urban areas with a high density of points of interest, where collective behaviours strongly influence mobility. During disruptive events like the COVID-19 pandemic, our model retains predictive capabilities, unlike individual-based models. By bridging the gap between individual and collective behaviours, our approach offers transparent and accurate predictions, crucial for addressing contemporary mobility challenges.

Two-year Follow-up of Internet-based Parent Training with Telephone Coaching Aimed at Treating Child Disruptive Behaviors in a Clinical Setting during the COVID-19 Pandemic (preprint)

Background: There is a lack of studies examining the long-term outcomes of internet-based parent training programs implemented in clinical settings during the COVID-19 pandemic.Objective: To study two-year outcomes of families with 3–8-year-old children referred from family counseling centers to the Finnish Strongest Families Smart Website (SFSW), which provides digital parent training with telephone coaching aimed at treating child disruptive behaviors.Methods Counseling centers in Helsinki identified 50 3–8-year-old children with high levels of disruptive behavioral problems. Child psychopathology and functioning as well as parenting styles and parental mental health were reported by parents at baseline, posttreatment and at 6-, 12- and 24-month follow-ups.Results The SFSW program had positive long-term effects on child psychopathology and parenting skills. Improvements in child psychopathology, including Strengths and Difficulties Questionnaire (SDQ) total score (Cohen’s d = 0.47, p < .001), SDQ conduct scores (Cohen’s d = 0.65; p < .001) and Affective Reactivity Index (ARI) irritability scores (Cohen’s d = 0.52; p < .001) were maintained until the 24-month follow-up. Similarly, treatment effects of parenting skills measured with the Parenting Scale, including overreactivity (Cohen’s d = 0.41; p = .001) and laxness (Cohen’s d = 0.26; p = .021), were maintained until the 24-month follow-up. Parent training did not have a long-term effect on parental hostility (Cohen’s d = − 0.04; p = .70).Conclusions: The study shows that the SFSW parent training program can yield significant long-term benefits. Findings indicate that the benefits of the treatment may vary between different parenting profiles, which is important to consider when developing more personalized parenting interventions.

Values Clarity, Action, and Posttraumatic Growth Arising from the COVID-19 Pandemic (preprint)

In the midst of the COVID-19 pandemic’s peak, many individuals faced unprecedented levels of perceived threat. That being said, it has been reported that many individuals also reported positive psychological outcomes and engagement in altruistic or prosocial behaviour. This quasi-experimental study delves into the interplay of sample types (students versus community members) and sample timing (pre- and post-vaccine availability) on psychological disruption variables tied to positive psychological outcomes. Through a comprehensive questionnaire comprising seven measures, administered online to participants from distinct populations at two crucial time points, our findings unravel a compelling narrative. Notably, the community and Time 1 sample consistently exhibit heightened levels of psychological disruption, posttraumatic growth, and positive psychological outcomes. As anticipated, mediation analysis underscores the pivotal role of a disruption in core beliefs in mediating the relationship between threatening events and posttraumatic growth. This study not only sheds light on these intricate dynamics but also holds implications for researchers navigating the multifaceted landscape of psychological outcomes in the face of unprecedented global challenges.

Community Pharmacists’ Perceptions and Experiences of Medicine Shortages in Disruptive Situations: A Qualitative Study (preprint)

Background: Medicine shortages are a challenge in upper, lower and middle-income countries, including South Africa. In recent years, community pharmacists in Durban, South Africa, have experienced disruptions such as the COVID-19 pandemic, flooding, civil unrest and electricity disruptions. Little is known about the impact of these disruptive situations on medicine shortages in community pharmacies. Aim: Exploring the perceptions of community pharmacists and their experiences with medicine shortages during the COVID-19 pandemic and other disruptive situations. Method: Convenience and snowball sampling were used to recruit community pharmacists in Durban, South Africa. Semi-structured interviews were conducted in person or via an online video conferencing platform. All interviews were audio-recorded and transcribed verbatim. The transcripts were analysed thematically on NVivo 14 software, using the Framework Method. Results:A total of 15 community pharmacists were interviewed. Five major themes emerged from thematic analysis, viz. the perceptions of medicine shortages, the impact of disruptive situations, the consequences of medicine shortages, mitigation strategies; and further suggestions and resources. Perceptions were that shortages were exacerbated by the disruptive situations. Participants perceived a negative financial impact on patients and pharmacies, with out-of-pocket costs affecting the former and loss of income affecting the latter. The mitigation strategies used were contacting stakeholders, medicine substitution and stock management. Conclusion: Community pharmacists felt that medicine shortages required improved communication, collaboration, policies, notification systems and guidelines to mitigate the problem further.

Immune Correlates of Hyperglycemia and Vaccination in a Non-human Primate Model of Long-COVID (preprint)

Hyperglycemia, and exacerbation of pre-existing deficits in glucose metabolism, are major manifestations of the post-acute sequelae of SARS-CoV-2 (PASC). Our understanding of lasting glucometabolic disruptions after acute COVID-19 remains unclear due to the lack of animal models for metabolic PASC. Here, we report a non-human primate model of metabolic PASC using SARS-CoV-2 infected African green monkeys (AGMs). Using this model, we have identified a dysregulated chemokine signature and hypersensitive T cell population during acute COVID-19 that correlates with elevated and persistent hyperglycemia four months post-infection. This persistent hyperglycemia correlates with elevated hepatic glycogen, but there was no evidence of long-term SARS-CoV-2 replication in the liver and pancreas. Finally, we report a favorable glycemic effect of the SARS-CoV-2 mRNA vaccine, administered on day 4 post-infection. Together, these data suggest that the AGM metabolic PASC model exhibits important similarities to human metabolic PASC and can be utilized to assess therapeutic candidates to combat this syndrome.

Predictive Systems Biology Modeling: Unraveling Host Metabolic Disruptions and Potential Drug Targets in SARS-CoV-2 and Its Variants (preprint)

Background: Host response is critical to the onset, progression, and outcome of viral infections. Since viruses hijack the host cellular metabolism for their replications, we hypothesized that restoring host cell metabolism can efficiently reduce viral production. Here, we present a viral-host Metabolic Modeling (vhMM) method to systematically evaluate the disturbances in host metabolism in viral infection and computationally identify targets for modulation by integrating genome-wide precision metabolic modeling and cheminformatics. Results: In SARS-CoV-2 infections, we identified consistent changes in host metabolism and gene and endogenous metabolite targets between the original SARS-COV-2 and different variants (Alpha, Delta, and Omicron). Among six compounds predicted for repurposing, methotrexate, cinnamaldehyde, and deferiprone were tested in vitro and effective in inhibiting viral production with IC50 less than 4uM. Further, an analysis of real-world patient data showed that cinnamon usage significantly reduced the SARS-CoV-2 infection rate with an odds ratio of 0.65 [95%CI: 0.55~0.75]. Conclusions: These results demonstrated that vhMM is an efficient method for predicting targets and drugs for viral infections.

Short-Term Impact of "Amaka Amasanyufu" Multiple Family Group Intervention on Mental Health Functioning of Children With Disruptive Behavior Disorders in Uganda.

OBJECTIVE: We evaluate the mid-intervention (8 weeks) and short-term (16 weeks) impact of a culturally adapted multiple family group (MFG) intervention, "Amaka Amasanyufu," on the mental health of children with disruptive behavior disorders (DBDs) and primary caregivers in Uganda. METHOD: We analyzed data from the Strengthening mental health and research training in Sub-Saharan Africa (SMART) Africa-Uganda study. Schools were randomized to the following: a control group; an MFG facilitated by parent peers (MFG-PP); or an MFG facilitated by community health workers (MFG:CHW). All participants were blinded to interventions provided to other participants and study hypotheses. At 8 weeks and 16 weeks, we evaluated differences in depressive symptoms and self-concept among children and in mental health and caregiving-related stress among caregivers. Three-level linear mixed-effects models were fitted. Pairwise comparisons of post-baseline group means were performed using the Sidak adjustment for multiple comparisons and standardized mean differences. Data from 636 children with DBDs and caregivers (controls: n = 243, n = 10 schools; MFG-PP: n = 194, n = 8 schools; MFG-CHW: n = 199, n = 8 schools) were analyzed. RESULTS: There were significant group-by-time interactions for all outcomes, and differences were observed mid-intervention, with short-term effects at 16 weeks (end-intervention). MFG-PP and MFG-CHW children had significantly lower depressive symptoms and higher self-concept, whereas caregivers had significantly lower caregiving-related stress and fewer mental health problems, than controls. There was no difference between intervention groups. CONCLUSION: Amaka Amasanyufu MFG intervention is effective for reducing depressive symptoms and improving self-concept among children with DBDs while reducing parental stress and mental health problems among caregivers. Given the paucity of culturally adapted mental health interventions, this provides support for adaptation and scale-up in Uganda and other low-resource settings. CLINICAL TRIAL REGISTRATION INFORMATION: SMART Africa (Strengthening Mental Health Research and Training); https://clinicaltrials.gov/: NCT03081195.

Response toward Public Health Policy Ambiguity and Insurance Decisions (preprint)

Adjustments to public health policy are common. This paper investigates the impact of COVID-19 policy ambiguity on specific groups' insurance consumption. The results show that sensitive groups' willingness to pay (WTP) for insurance is 12.2% above the benchmark. Groups that have experienced income disruptions are more likely to suffer this. This paper offers fresh perspectives on the effects of pandemic control shifts.

COVID-19-related disruption and resiliency in immunisation activities in LMICs: a rapid review (preprint)

Objectives Rapid review to determine the extent that immunisation services in LMICs were disrupted by the COVID-19 pandemic and what factors can be considered to build resilience in future. Setting We searched PubMed on 28th Feb 2023 for studies published after 1st December 2019 in English that focused on LMICs. Participants Screening and data extraction were conducted by two experienced reviewers with one reviewer vote minimum per study per stage. Of 3801 identified studies, 66 met the eligibility criteria. Outcomes Routine vaccine coverage achieved; Supplementary immunisation activity timing; Vaccine doses given; Timing of vaccination; Supply chain changes; factors contributing to disruption or resilience. Results Included studies showed evidence of notable declines in immunisation activities across LMICs related to the COVID-19 pandemic. These have included reductions in achieved routine coverage, cancellation or postponement of campaigns, and underimmunised cohorts. Immunisation was most disrupted in the early months of the pandemic, particularly March to May 2020; however, the amount of recovery seen varied by country, age-group, and vaccine. Though many countries observed partial recovery beginning after lockdown policies were lifted in 2020, disruption in many countries has also continued into 2021. It has also been noted that clinician staff shortages and vaccine stock outs caused by supply chain disruptions contributed to immunisation delays but that concern over COVID transmission was a leading factor. Key resiliency factors included community outreach and healthcare worker support. Finally, whilst our search took place in February 2023, the latest dataset used across all studies was from November 2022 and many focused on 2020; as a result some of the study conclusions do not take recovery into account. Conclusions There is limited information on whether reductions in vaccination coverage or delays have persisted beyond 2021. Further research is needed to assess ongoing disruptions and identify missed vaccine cohorts.

Long COVID and financial outcomes: Evidence from four longitudinal population surveys (preprint)

Background: Long-term sequelae of COVID-19 (long COVID) include muscle weakness, fatigue, breathing difficulties and sleep disturbance over weeks or months. Using UK longitudinal data, we assessed the relationship between long COVID and financial disruption. Methods: We estimated associations between long COVID (derived using self-reported length of COVID-19 symptoms) and measures of financial disruption (subjective financial well-being, new benefit claims, changes in household income) by analysing data from four longitudinal population studies, gathered during the first year of the pandemic. We employed modified Poisson regression in a pooled analysis of the four cohorts adjusting for a range of potential confounders, including pre-pandemic (pre-long COVID) factors. Results: Among 20,112 observations across four population surveys, 13% reported having COVID-19 with symptoms that impeded their ability to function normally - 10.7% had such symptoms for <4 weeks (acute COVID-19), 1.2% had such symptoms for 4-12 weeks (ongoing symptomatic COVID-19) and 0.6% had such symptoms for >12 weeks (post-COVID-19 syndrome). We found that post-COVID-19 syndrome was associated with worse subjective financial well-being (adjusted relative risk ratios (aRRR)=1.57, 95% confidence interval (CI)=1.25, 1.96) and new benefit claims (aRRR=1.79, CI=1.27, 2.53). Associations were broadly similar across sexes and education levels. These results were not meaningfully altered when scaled to represent the population by age. Conclusions: Long COVID was associated with financial disruption in the UK. If our findings reflect causal effects, extending employment protection and financial support to people with long COVID may be warranted.

Disrupted seasonality and association of COVID-19 with medically attended respiratory syncytial virus infections among young children in the US: January 2010-January 2023 (preprint)

Respiratory syncytial virus (RSV) infections and hospitalizations surged sharply in 2022 among young children. To assess whether COVID-19 contributed to this surge, we leveraged a real-time nation-wide US database of electronic health records (EHRs) using time series analysis from January 1, 2010 through January 31, 2023, and propensity-score matched cohort comparisons for children aged 0-5 years with or without prior COVID-19 infection. Seasonal patterns of medically attended RSV infections were significantly disrupted during the COVID-19 pandemic. The monthly incidence rate for first-time medically attended cases, most of which were severe RSV-associated diseases, reached a historical high rate of 2,182 cases per 1,0000,000 person-days in November 2022, corresponding to a related increase of 143% compared to expected peak rate (rate ratio: 2.43, 95% CI: 2.25-2.63). Among 228,940 children aged 0-5 years, the risk for first-time medically attended RSV during 10/2022-12/2022 was 6.40% for children with prior COVID-19 infection, higher than 4.30% for the matched children without COVID-19 (risk ratio or RR: 1.40, 95% CI: 1.27-1.55); and among 99,105 children aged 0-1 year, the overall risk was 7.90% for those with prior COVID-19 infection, higher than 5.64% for matched children without (RR: 1.40, 95% CI: 1.21-1.62). These data provide evidence that COVID-19 contributed to the 2022 surge of severe pediatric RSV cases.

Real-time assessment of positive and negative affective fluctuations and mood lability in a transdiagnostic sample of youth.

BACKGROUND: Emotional lability, defined as rapid and/or intense affect fluctuations, is associated with pediatric psychopathology. Although numerous studies have examined labile mood in clinical groups, few studies have used real-time assessments in a well-characterized transdiagnostic sample, and no prior study has included participants with disruptive mood dysregulation disorder (DMDD). The present study leverages ecological momentary assessment (EMA) to assess emotional lability in a transdiagnostic pediatric sample. METHODS: One hundred thirty participants ages 8-18 with primary diagnoses of DMDD, attention-deficit/hyperactivity disorder (ADHD), an anxiety disorder (ANX), or healthy volunteers completed a previously validated 1-week EMA protocol. Clinicians determined diagnoses based on semi-structured interviews and assessed levels of functional impairment. Participants reported momentary affective states and mood change. Composite scores of fluctuations in positive and negative affect were generated. Affect fluctuations were compared between diagnostic groups and tested for their association with functional impairment. RESULTS: Diagnostic groups differed in levels of negative and positive emotional lability. DMDD patients demonstrated the highest level of labile mood compared with other groups. Emotional lability was associated with global impairment in the whole sample. CONCLUSIONS: Both positive and negative emotional lability is salient in pediatric psychopathology and is associated with functional impairment, particularly in DMDD youth.

A comparative national-level analysis of government food system resilience activities in preparation for future food system disruptions. (preprint)

Background The COVID-19 pandemic, extreme weather events, and the Russian invasion of Ukraine have highlighted global food system vulnerabilities and a lack of preparedness and prospective planning for increasingly complex disruptions. This has spurred an interest in food system resilience. Despite the elevated interest in food system resilience, there is a lack of comparative analyses of national-level food system resilience efforts. An improved understanding of the food system resilience landscape can support and inform future policies, programs, and planning.Methods We conducted a cross-country comparison of national-level food system resilience activities from Australia, Aotearoa (New Zealand), Sweden, and the United States. We developed upon and adapted the resilience framework proposed by Harris and Spiegel to compare actions derived from thirteen national food system resilience documents. We coded the documents based on how the governments determined actions by food system resilience attribute utilized, part of the food supply chain, specific shocks or stressors, implementation level, the temporal focus of action, and the expected impact on food security. We analyzed and compared countries’ coded categories, subcategories, and category combinations.Results The results showed that countries are using multi-pronged policy actions to address food system resilience issues and are focused on both retrospective reviews and prospective models of disruptive events to inform their decisions. Some work has been done towards preparing for climate change and other natural disasters, but not as much for other shocks or stressors.Conclusions The analysis identified potential gaps, concentrations, and themes in national food systems resilience. The framework can be applied to augment existing policy, create new policy, as well as to supplement and complement other existing frameworks.

Food Insecurity amid COVID-19 Lockdowns: Assessing Sociodemographic Indicators of Vulnerability in Harar and Kersa, Ethiopia (preprint)

Objective The COVID-19 pandemic was associated with widespread social disruptions, as governments implemented lockdowns to quell disease spread. To advance knowledge of consequences for households in lower-income countries, we examine food insecurity during the pandemic period. Design Cross-sectional study using logistic regression to examine factors associated with food insecurity. Data were collected between August and September of 2021 through a Health and Demographic Surveillance System (HDSS) using a survey instrument focused on knowledge regarding the spread of COVID-19; food availability; COVID-19 related shocks/coping; under-five child healthcare services; and healthcare services for pregnant women. Setting The study is set in two communities in Eastern Ethiopia, one rural and one urban. Participants A random sample of 880 households residing in Kersa and Harar. Results Roughly 16% of households reported not having enough food to eat during the pandemic, an increase of 6% since before the pandemic. After adjusting for other variables, households were more likely to report food insecurity if they were living in an urban area, were a larger household, had a family member lose employment, reported an increase in food prices, or were food insecure before the pandemic. Households were less likely to report food insecurity if they were wealthier or had higher household income. Discussion After taking other characteristics into consideration, households in urban areas were at higher risk for food insecurity. These findings point to the need for expanding food assistance programs to more urban areas to help mitigate the impact of lockdowns on more vulnerable households.

Electricity price forecasting with Smoothing Quantile Regression Averaging: Quantifying economic benefits of probabilistic forecasts (preprint)

In the world of the complex power market, accurate electricity price forecasting is essential for strategic bidding and affects both daily operations and long-term investments. This article introduce a new method dubbed Smoothing Quantile Regression (SQR) Averaging, that improves on well-performing schemes for probabilistic forecasting. To showcase its utility, a comprehensive study is conducted across four power markets, including recent data encompassing the COVID-19 pandemic and the Russian invasion on Ukraine. The performance of SQR Averaging is evaluated and compared to state-of-the-art benchmark methods in terms of the reliability and sharpness measures. Additionally, an evaluation scheme is introduced to quantify the economic benefits derived from SQR Averaging predictions. This scheme can be applied in any day-ahead electricity market and is based on a trading strategy that leverages battery storage and sets limit orders using selected quantiles of the predictive distribution. The results reveal that, compared to the benchmark strategy, utilizing SQR Averaging leads to average profit increases of up to 14\%. These findings provide strong evidence for the effectiveness of SQR Averaging in improving forecast accuracy and the practical value of utilizing probabilistic forecasts in day-ahead electricity trading, even in the face of challenging events such as the COVID-19 pandemic and geopolitical disruptions.

“I am scared, I do not want to lie”: Exploring the impacts of COVID-19 on engagement in care, perceived health, relationship dynamics, and parenting among postpartum women with HIV in South Africa (preprint)

Background COVID-19 and efforts to manage widespread infection may compromise HIV care engagement. The COVID-19-related factors linked to reduced HIV engagement have not been assessed among postpartum women with HIV, who are at heightened risk of attrition under non-pandemic circumstances. To mitigate the effects of the pandemic on care engagement and to prepare for future public health crises, it is critical to understand how COVID-19 has impacted (1) engagement in care and (2) factors that may act as barriers to care engagement.Methods A quantitative assessment of COVID-19-related experiences was added to a longitudinal cohort study assessing predictors of postpartum attrition from HIV care among women in South Africa. Participants (N = 266) completed the assessment at 6, 12, 18, or 24 months postpartum between June and November of 2020. Those who endorsed one or more challenge related to engagement in care (making or keeping HIV care appointments, procuring HIV medications, procuring contraception, and/or accessing immunization services for infants; n = 55) were invited to complete a brief qualitative interview, which explored the specific factors driving these challenges, as well as other impacts of COVID-19 on care engagement. Within this subset, 53 participants completed an interview; qualitative data were analyzed via rapid analysis.Results Participants described key challenges that reduced their engagement in HIV care and identified four other domains of COVID-19-related impacts: physical health, mental health, relationship with a partner or with the father of the baby, and motherhood/caring for the new baby. Within these domains, specific themes and subthemes emerged, with some positive impacts of COVID-19 also reported (e.g., increased quality time, improved communication with partner, HIV disclosure). Coping strategies for COVID-19-related challenges (e.g., acceptance, spirituality, distraction) were also discussed.Conclusions About one in five participants reported challenges accessing HIV care, medications, or services, and they faced complex, multilayered barriers to remaining engaged. Physical health, mental health, relationships with partners, and ability to care for their infant were also affected. Given the dynamic nature of the pandemic and general uncertainty about its course, ongoing assessment of pandemic-related challenges among postpartum women is needed to avoid HIV care disruptions and to support wellbeing.

Effects of the COVID-19 pandemic on general health and malaria control in Ghana: A qualitative study with mothers and health care professionals (preprint)

Background COVID-19 has severely impacted health systems and the management of non-COVID-19 diseases, including malaria, globally. The pandemic has hit sub-Saharan Africa less than expected; even considering large underreporting, the direct COVID-19 burden was minor compared to the Global North. However, the indirect effects of the pandemic, for example, on socio-economic inequality and health care systems, may have been more disruptive. Following a quantitative analysis of routine surveillance data of 2020 compared to 2015 to 2019 from northern Ghana, which showed significant reductions in overall outpatient department visits and malaria cases, this qualitative study aims to provide further explanations to those quantitative findings.Methods In the Northern Region of Ghana, 72 participants, consisting of 18 health care professionals (HCP) and 54 mothers of children under the age of five, were recruited in urban and rural districts. Data were collected using focus group discussions with women that were pregnant during the first phase of the pandemic, women that had already under five children by then, and through key informant interviews with HCP.Results Three main themes occurred. The first theme - general effects of the pandemic - includes impacts on finances, food security, health service provision as well as education and hygiene. Many women lost their jobs, which increased their dependance on males, children had to drop out of school, and families had to develop strategies to cope with food shortages and considering migration. HCPs had problems to reach the communities, suffered stigmatization and were often barely protected against the virus. The second theme - effects of the pandemic on health seeking - includes fear of infection, lack of COVID-19 testing capacities, changed behavior of HCPs, and reduced access to clinics and treatment due to reduced opening hours as well as patients’ and HCPs’ fear of getting infected with COVID-19. The third theme – effects of the pandemic on malaria – includes disruptions of malaria preventive measures and reduced access to and acceptance of chemoprophylaxis as the side effects mimic COVID-19 symptoms. Clinical discrimination between malaria and COVID-19 symptoms was difficult and HCPs observed increases in severe malaria cases in health facilities due to late reporting.Conclusion The COVID-19 pandemic has had large collateral impacts on mothers, children and HCPs. In addition to overall negative effects on families and communities, access to and quality of health services was severely impaired, including serious implications for malaria prevention and treatment.

How to Prepare for the Next Pandemic -- Investigation of Correlation Between Food Prices and COVID-19 From Global and Local Perspectives (preprint)

The coronavirus disease (COVID-19) has caused enormous disruptions to not only the United States, but also the global economy. Due to the pandemic, issues in the supply chain and concerns about food shortage drove up the food prices. According to the U.S. Bureau of Labor Statistics, the prices for food increased 4.1% and 3.7% over the year ended in August 2020 and August 2021, respectively, while the amount of annual increase in the food prices prior to the COVID-19 pandemic is less than 2.0%. Previous studies show that such kinds of exogenous disasters, including the 2011 Tohoku Earthquake, 9/11 terrorist attacks, and major infectious diseases, and the resulted unusual food prices often led to subsequent changes in people's consumption behaviors. We hypothesize that the COVID-19 pandemic causes food price changes and the price changes alter people's grocery shopping behaviors as well. To thoroughly explore this, we formulate our analysis from two different perspectives, by collecting data both globally, from China, Japan, United Kingdom, and United States, and locally, from different groups of people inside the US. In particular, we analyze the trends between food prices and COVID-19 as well as between food prices and spending, aiming to find out their correlations and the lessons for preparing the next pandemic.

Ostracism in the era of COVID-19: Intrapersonal, interpersonal, and intergroup perspectives (preprint)

COVID-19 pandemic had a profound negative impact on people’s personal and social life. In this chapter, after some conceptual clarifications, we provide insights into the effects of ostracism on people’s well-being as individuals, partners, and group members. Specifically, we explore (a) individual- and personality-based risk factors of ostracism (intrapersonal level); (b) deprivation of social touch, disruption of empathy and social stigmatization in interpersonal relations (interpersonal level); and (c) disruption of social identity, social stigmatization and rise in prejudiced, discriminatory, and xenophobic tendencies withing groups (intergroup level). The contribution of this chapter lies in proposing an interplay among intrapersonal, interpersonal, and intergroup dimensions of identity, that is, a multi-level conceptualization of ostracism during the covidian era. By integrating theoretical arguments and research findings, we support the view that personal identity commitment and identification with social groups have similar roots, both based on the individual’s need to formulate meaningful connections to the world and, thus, cope with as well as prevent ostracism. The implications of the interplay between personal and social identity for the measurement of ostracism are also discussed. Next, strategies for tackling ostracism during the pandemic or similar widespread crises are proposed. Finally, avenues for future research are suggested.

A Comprehensive Benchmark for COVID-19 Predictive Modeling Using Electronic Health Records in Intensive Care (preprint)

The COVID-19 pandemic has posed a heavy burden to the healthcare system worldwide and caused huge social disruption and economic loss. Many deep learning models have been proposed to conduct clinical predictive tasks such as mortality prediction for COVID-19 patients in intensive care units using Electronic Health Record (EHR) data. Despite their initial success in certain clinical applications, there is currently a lack of benchmarking results to achieve a fair comparison so that we can select the optimal model for clinical use. Furthermore, there is a discrepancy between the formulation of traditional prediction tasks and real-world clinical practice in intensive care. To fill these gaps, we propose two clinical prediction tasks, Outcome-specific length-of-stay prediction and Early mortality prediction for COVID-19 patients in intensive care units. The two tasks are adapted from the naive length-of-stay and mortality prediction tasks to accommodate the clinical practice for COVID-19 patients. We propose fair, detailed, open-source data-preprocessing pipelines and evaluate 17 state-of-the-art predictive models on two tasks, including 5 machine learning models, 6 basic deep learning models and 6 deep learning predictive models specifically designed for EHR data. We provide benchmarking results using data from two real-world COVID-19 EHR datasets. One dataset is publicly available without needing any inquiry and another dataset can be accessed on request. We provide fair, reproducible benchmarking results for two tasks. We deploy all experiment results and models on an online platform. We also allow clinicians and researchers to upload their data to the platform and get quick prediction results using our trained models. We hope our efforts can further facilitate deep learning and machine learning research for COVID-19 predictive modeling.