Contact Tracing over Uncertain Indoor Positioning Data

Pandemics often cause dramatic losses of human lives and impact our societies in many aspects such as public health, tourism, and economy. To contain the spread of an epidemic like COVID-19, efficient and effective contact tracing is important, especially in indoor venues where the risk of infection is higher. In this work, we formulate and study a novel query called Indoor Contact Query (<sc>ICQ</sc>) over raw, uncertain indoor positioning data that digitalizes people's movements indoors. Given a query object <inline-formula><tex-math notation="LaTeX">$o$</tex-math></inline-formula>, e.g., a person confirmed to be a virus carrier, an <sc>ICQ</sc> analyzes uncertain indoor positioning data to find objects that most likely had close contact with <inline-formula><tex-math notation="LaTeX">$o$</tex-math></inline-formula> for a long period of time. To process <sc>ICQ</sc>, we propose a set of techniques. First, we design an enhanced indoor graph model to organize different types of data necessary for <sc>ICQ</sc>. Second, for indoor moving objects, we devise methods to determine uncertain regions and to derive positioning samples missing in the raw data. Third, we propose a query processing framework with a close contact determination method, a search algorithm, and the acceleration strategies. We conduct extensive experiments on synthetic and real datasets to evaluate our proposals. The results demonstrate the efficiency and effectiveness of our proposals. IEEE

The Public's COVID-19 Fatigue and Mental Health Towards COVID-19 Public Health and Social Measures (PHSMS) and Mental Health in China: A Discrete Choice Experiment

Objectives: The public's stated preference for public health and social measures (PHSMs), and levels of pandemic fatigue are insufficiently fixed. We aim to quantify the public's preferences for varied PHSMs, and measure population's pandemic fatigue. Method(s): We conducted a cross-sectional, nationwide sampling, survey-based experiment to assess public preference for and attitudes towards PHSMs. A set of psychometric scales, specifically, the COVID-19 pandemic fatigue scale (CPFS), was used to screen fatigue levels in the respondents. The multinomial logit model (MNL) and latent class model (LCM) were utilized for choice tasks analysis, and Mann-Whitney tests were used for CPFS statistical analysis. Result(s): There were 689 respondents, who completed the survey, and were included in the study after quality control. The discrete choice experiments revealed that respondents attached the greatest importance to the risk of COVID-19 infection within three months (45.53%), followed by loss of income within three months (30.69%). Vulnerable populations (lower-income and older respondents) are more sensitive to the risk of infection, and younger respondents are more sensitive to income loss and prefer non-suspension of socialization and transportation. Migrants, and respondents with a higher level of fatigue, have less acceptance of the mandatory booster vaccination and suspension of transportation. Additionally, a higher fatigue level was observed in females, younger respondents, migrants, and relatively lower-income respondents. Conclusion(s): Fatigue and fear of COVID-19 infection contributed to the public's mental health problem. Hence, at the late-stage pandemic, policymakers should consider reducing people's mental burden via relieving people's fear of infection when PHSMs are being relaxed. And this also provides insights for the outbreaks' PHSMs implementation in the future.Copyright © 2023

Coronavirus murine hepatitis virus strain 3 induces intestinal injury via caspase 3 dependent apoptosis

Background: Diarrhea was typical symptoms of the coronavirus disease 2019 (COVID-19). However, the underlying mechanism had not been fully understood. Aim(s): The study aimed to explore the mechanism of intestinal injury during COVID-19 in a coronavirus murine hepatitis virus strain 3 (MHV-3) induced acute mouse model. Method(s): MHV-3 induced acute infection Balb/cJ mice model was established. Intestine samples were collected at indicated time points as 0 h, 24 h, 48 h and 60 h post infection. The mRNA and protein expression of IL1b, TNFalpha, IL6, caspase 3 and cleaved caspase 3 were examined by real-time quantitative PCR (qPCR) and western blot respectively. The intestine injury and apoptosis were measured by HE staining and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL). Moreover, Z-DEVD-FMK (caspase 3 inhibitor) pre-treated MHV-3 infection mice model were established, in which the apoptosis of intestine was evaluated as well. Meanwhile, the murine intestinal cell MODE-K was infected by MHV-3 in vitro for evaluation of virus induced apoptosis. Result(s): Post MHV-3 infection, the histopathology of intestine tissue showed extraordinary injury with time dependence, as well as high level of TUNEL positivity. The mRNA levels of inflammatory cytokine IL1b, TNFalpha and IL6 were significantly increased. The protein expressions of caspase 3 and cleaved caspase 3 in the intestine was found significantly elevated from 24 to 48 h post MHV-3 infection. Z-DEVD-FMK pretreatment inhibited caspase 3 and cleaved caspase 3 expression and decreased TUNEL positivity. Meanwhile, alleviated gut injury and inhibited TNFalpha expression were observed. In vitro treated by MHV-3, intestinal cell line MODE-K showed nine-fold increase of apoptosis by comparison with saline treated ones. The expressions of apoptosis crucial protein caspase3 and cleaved caspase3 significantly elevated, as well as TNFalpha. Conclusion(s): Coronavirus murine hepatitis virus strain 3 induces intestinal injury via caspase 3 dependent apoptosis, which might shed light on the treatment of intestinal complications in COVID-19.

Personalized exercise recommendation method based on causal deep learning: Experiments and implications

The COVID-19 pandemic has accelerated innovations for supporting learning and teaching online. However, online learning also means a reduction of opportunities in direct communication between teachers and students. Given the inevitable diversity in learning progress and achievements for individual online learners, it is difficult for teachers to give personalized guidance to a large number of students. The personalized guidance may cover many aspects, including recommending tailored exercises to a specific student according to the student's knowledge gaps on a subject. In this paper, we propose a personalized exercise recommendation method named causal deep learning (CDL) based on the combination of causal inference and deep learning. Deep learning is used to train and generate initial feature representations for the students and the exercises, and intervention algorithms based on causal inference are then applied to further tune these feature representations. Afterwards, deep learning is again used to predict individual students' score ratings on exercises, from which the Top-N ranked exercises are recommended to similar students who likely need enhancing of skills and understanding of the subject areas indicated by the chosen exercises. Experiments of CDL and four baseline methods on two real-world datasets demonstrate that CDL is superior to the existing methods in terms of capturing students' knowledge gaps in learning and more accurately recommending appropriate exercises to individual students to help bridge their knowledge gaps. © 2022 The Author(s).

Enhanced performance of algal-bacterial aerobic granular sludge in comparison to bacterial aerobic granular sludge for treating surfactant-containing wastewater

Increasing amounts of surfactants are used and emitted into the environment due to the COVID-19 pandemic, posing potential threats to ecological health. Algal-bacterial aerobic granular sludge (A-BAGS), with the advantages of compact structure, high-efficient nutrient uptake, and high tolerance to harsh conditions, was attempted in this study to treat surfactant-containing wastewater at relatively high concentrations. The treatment performance was also compared to bacterial AGS (BAGS). Results showed that A-BAGS is preferable for treating wastewater containing a high SDS concentration (30 mg/L), achieving nutrient removal efficiency of 86.3 % for organic carbon, 60.5 % for total nitrogen, and 58.7 % for total phosphorus within a short duration, compared to 70.1 %, 52.8 % and 42.3 % in BAGS reactor. Besides, the removal rate of ammonia nitrogen by A-BAGS was much faster than that of BAGS. The above results confirmed that A-BAGS is a promising technology for treating surfactant-containing wastewater with high nutrient removal efficiency being maintained.Copyright © 2023 Elsevier Ltd

Negative ageism and compassionate ageism in news coverage of older people under COVID-19: how did the pandemic progression and public health responses associate with different news themes?

Previous studies have found negative ageing narratives in the media during the COVID-19 pandemic. However, few have focused on compassionate ageism and how the news responded to the progression of the COVID-19 pandemic. We investigated (a) media themes of negative and compassionate ageism and (b) their relationships with COVID-19 parameters and the public health response. The sample included 1,197 articles relevant to COVID-19 and older people in Hong Kong published between January and December 2020. We used thematic analysis to identify themes from the news articles and structural equation modelling to explore these themes' relationship with the number of older people infected, effective reproduction number, number of COVID-19 deaths and public health response parallel in time. Pandemic-related variables were lagged for a day - the time needed to be reflected in the news. Two negative ageism themes portrayed older people as vulnerable to COVID-19 but counterproductive in combating the pandemic. Two compassionate ageism themes depicted older people as a homogenous group of passive assistance recipients. The theme blaming older people was associated with the number of confirmed infections (beta = 0.418, p = 0.002) but vulnerability of older people was not associated with pandemic-related variables. The theme helping older people was negatively associated with the percentage of older people in confirmed infections (beta = -0.155, p = 0.019). The theme resources available was negatively associated with confirmed infections (beta = -0.342, p < 0.001) but positively associated with the Containment and Health Index (beta = 0.217, p = 0.005). Findings suggested that negative and compassionate ageism were translated into narratives about older people in the media as the pandemic evolved but did not address the actual risk they faced. Media professionals should be aware of the potential negative and compassionate ageism prompted by the news agenda and promote adequate health behaviours and responses.

Porous carbon tubes from recycling waste COVID-19 masks for optimization of 8 mol% Y2O3-doped tetragonal zirconia polycrystalline nanopowder.

Disposable polypropylene medical masks are widely used to protect people from injury caused by COVID-19 worldwide. However, disposable medical masks are non-biodegradable materials, and the accumulation of waste masks can pollute the environment and waste resources without a reasonable recycling method. The aims of this study are to transform waste masks into carbon materials and to use them as a dispersant in preparing high-quality 8 mol% Y2O3-doped tetragonal zirconia nanopowders. The waste masks were carbonized to get a carbon source in the first step, then KOH was used to etch the carbon source creating a micropores structure in the carbon material after the carbon-bed heat treatment method. The resulting carbon material is a porous tube structure with a high specific surface area (1220.34 m2/g) and adsorption capacity. The as-obtained porous carbon tubes were applied as a dispersant to produce 8 mol% Y2O3-doped tetragonal zirconia nanopowders, and the resulting nanopowders owned well-dispersed and had the smallest particle size than that prepared by activated carbon as a dispersant. Besides, the sintered 8 mol% Y2O3-doped tetragonal zirconia ceramic possessed high density, which resulted in higher ionic conductivity. These findings suggest that waste face masks can be recycled to prepare high-added-value carbon materials and provide a green and low-cost method to reuse polypropylene waste materials.

SMA-Net: Sobel Operator Combined with Multi-attention Networks for COVID-19 Lesion Segmentation

Coronavirus disease 2019 (COVID-19) has been spreading since late 2019, leading the world into a serious health crisis. To control the spread rate of infection, identifying patients accurately and quickly is the most crucial step. Computed tomography (CT) images of the chest are an important basis for diagnosing COVID-19. They also allow doctors to understand the details of the lung infection. However, manual segmentation of infected areas in CT images is time-consuming and laborious. With its excellent feature extraction capabilities, deep learning-based method has been widely used for automatic lesion segmentation of COVID-19 CT images. But, the segmentation accuracy of these methods is still limited. To effectively quantify the severity of lung infections, we propose a Sobel operator combined with Multi-Attention networks for COVID-19 lesion segmentation (SMA-Net). In our SMA-Net, an edge feature fusion module uses Sobel operator to add edge detail information to the input image. To guide the network to focus on key regions, the SMA-Net introduces a self-attentive channel attention mechanism and a spatial linear attention mechanism. In addition, Tversky loss function is adopted for the segmentation network for small size of lesions. Comparative experiments on COVID-19 public datasets show that the average Dice similarity coefficient (DSC) and joint intersection over Union (IOU) of proposed SMA-Net are 86.1% and 77.8%, respectively, which are better than most existing neural networks used for COVID-19 lesion segmentation. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

A Lightweight Segmentation Network Based on Weak Supervision for COVID-19 Detection

The Coronavirus Disease 2019 (COVID-19) outbreak in late 2019 threatens global health security. Computed tomography (CT) can provide richer information for the diagnosis and treatment of COVID-19. Unfortunately, labeling of COVID-19 lesion chest CT images is an expensive affair. We solved the challenge of chest CT labeling by simply marking point annotations to the lesion areas, i.e., by marking individual pixels for each lesion area in the chest CT scan. It takes only a few seconds to complete the labeling using this labeling strategy. We also designed a lightweight segmentation model with approximately 10% of the number of model parameters of the conventional model. So, the proposed model segmented the lesions of a single image in only 0.05 s. In order to obtain the shape and size of lesions from point labels, the convex-hull based segmentation (CHS) loss function is proposed in this paper, which enables the model to obtain an approximate fully supervised performance on point labels. The experiments were compared with the current state-of-the-art (SOTA) point label segmentation methods on the COVID-19-CT-Seg dataset, and our model showed a large improvement: IoU improved by 28.85%, DSC improved by 28.91%, Sens improved by 13.75%, Spes improved by 1.18%, and MAE decreased by 1.10%. Experiments on the dataset show that the proposed model combines the advantages of lightweight and weak supervision, resulting in more accurate COVID-19 lesion segmentation results while having only a 10% performance difference with the fully supervised approach. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Analyzing pure contagion between crude oil and agricultural futures markets

Crude oil and agricultural product prices are important factors affecting a country's economic and social stability. The pure contagion between these two markets may lead to excessive price linkage, increasing the fragility of the financial system. This paper uses the CEEMDAN method, fine-to-coarse reconstruction method, and TVP-VAR model to study the pure contagion between crude oil and agricultural futures markets. The empirical results show that there always is significant pure contagion between agricultural futures markets. However, pure contagion between crude oil and agricultural futures markets only exists in some specific periods. The crude oil futures market has obvious pure contagion to the agricultural futures markets in most periods. Only a few periods the agricultural futures have pure contagion to the crude oil futures. It is worth noting that the COVID-19 epidemic aggravates the pure contagion between crude oil and the agricultural futures markets. Based on the research conclusions, this paper puts forward corresponding policy recommendations, hoping to provide a reference and theoretical basis for the government to formulate corresponding policies. © 2023 Elsevier Ltd

VGG-FusionNet: A Feature Fusion Framework from CT scan and Chest X-ray Images based Deep Learning for COVID-19 Detection

COVID-19 has been rampant across the globe since it was discovered in 2020, but the method of virus detection still lacks efficiency and requires human resources. Given the slow delivery of the PCR test and the many possible false negatives of the rapid tests, medical imaging such as a chest computed tomography (CT) scan or chest X-ray (CXR) is an alternative and efficient way to detect the coronavirus accurately. For the past two years, many researchers have proposed different deep learning methods for COVID-19 detection using CT scans or CXR images. Due to the lack of available data, our study aims to propose a new deep learning framework VGG-FusionNet that takes advantage of integrating features from both CT scan and CXR images while avoiding some pitfalls from previous studies, including a high risk of bias due to lack of demographic information for the dataset, poor reproducibility, and no evaluation on different data sources to study the generalizability. Specifically, we use the convolutional layers of GoogLeNet, ResNet, and VGG to extract features from CT scan and CXR images and fuse them before training through fully connected layers. The result shows that using VGG's convolutional layers achieves the best overall performance with an accuracy of 0.93. Our proposed framework outperforms the deep learning models, using features from CT scans or CXR. © 2022 IEEE.

[Efficacy and safety of inactivated novel coronavirus vaccine inoculation in patients with chronic hepatitis B].

Objective: To explore the safety of inactivated novel coronavirus vaccine inoculation and the fluctuating neutralizing antibody in patients with chronic hepatitis B (CHB). Methods: Retrospective and prospective epidemiological research methods were employed. 153 CHB patients who visited the Department of Infectious Diseases at the First Hospital of Shanxi Medical University from September 2021 to February 2022 were selected as the research subjects. Information on vaccination-related adverse reactions was collected. Colloidal gold immunochromatography was used to identify neutralizing antibodies in the body after 3-6 months of vaccination. Statistical analysis was performed using the χ2-test or Fisher's exact test. Results: The positive rates of neutralizing antibodies after inactivated novel coronavirus vaccine inoculation in 153 patients with CHB were 45.50%, 44.70%, 40.00% and 16.20%, respectively, at 3, 4, 5, and 6 months. The neutralizing antibody concentrations were 10.00 (2.95, 30.01) U/ml, 6.08 (3.41, 24.50) U/ml, 5.90 (3.93, 14.68) U/ml, and 1.25 (0.92, 3.75) U/ml, respectively. The difference was not statistically significant (P>0.05) when the neutralizing antibody positivity rates in hepatitis B virus (HBV) DNA-negative and positive patients and HBeAg-negative and positive patients at different time points were compared. The overall incidence of adverse reactions following vaccination was 18.30%. Pain at the site of inoculation and fatigue were the main presentations, and no serious adverse reactions occurred. Conclusion: CHB patients, when inoculated with an inactivated novel coronavirus vaccine, can produce neutralizing antibodies, which can stay at certain levels for 3, 4, and 5 months. However, the neutralizing antibody level gradually decreases over time, and the decrease is remarkable at 6 months. So, it is recommended to boost vaccinations at an appropriate time. Additionally, the results of the study suggest that HBV replication status has little effect on the production of neutralizing antibodies in CHB patients with relatively stable liver function, which means the inactivated novel coronavirus vaccine has a good safety profile.

Approaching or avoiding? Mechanisms of host-country language proficiency in affecting virtual work adaptivity during COVID-19

The COVID-19 pandemic has forced expatriates in many organizations to do virtual work, while virtual communication is becoming a critical skill, especially for second-language speakers. We explore how expatriates with high and low levels of host-country language (HCL) proficiency use different mechanisms to improve their virtual work adaptivity during the COVID-19 pandemic. Drawing upon the Job Demands-Resources (JD-R) theory, we argue that expatriates with high HCL proficiency tend to adopt approach crafting, whereas expatriates with low HCL proficiency tend to use avoidance crafting. We further examine the role of language-related human resource (HR) practices in reducing the tendency of expatriates with low HCL proficiency to choose avoidance crafting. We tested our predictions using data collected from 994 expatriates working in eight countries during the COVID-19 virtual work period, and the results generally supported our hypotheses. Our study sheds light on the importance of HCL skills in influencing expatriates' job-crafting behavior and adaptivity in virtual work, and the significant role of language-related HR practices. Last, we offer practical insights into improving virtual work during a crisis in relation to employees' HCL and organizational support. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

COVID-19 Severity, Cardiological Outcome, and Immunogenicity of mRNA Vaccine on Adult Patients With 22q11.2 DS

Ammonia-nitrogen, a grave environmental concern, is a typical pollutant in deliming process due to the inclusion of ammonium salts as deliming agents in leather manufacture. In order to reduce the emission of ammonianitrogen and improve the biological treatment of mixed tannery wastewater, an ammonium-free deliming method was designed and optimized based on the synergistic effects of aromatic sulfonic acids and sodium dihydrogen phosphate. The results indicated that, the penetrating and buffering performance of the mixtures of p-Hydroxybenzene sulfonic acid (pHBSA) and sodium dihydrogen phosphate (SDHP) at weight ratio of 2:1 was good enough to fulfill the requirement of deliming. The organoleptic and mechanical properties of the crust leather produced by pHBSA-SDHP mixtures deliming were similar with the conventional ammonium sulfate deliming, and the grain pattern was found to be protected against the damage caused by enzymes during bating. The concentrations of ammonia-nitrogen and total nitrogen in pHBSA-SDHP deliming effluent were dramatically cut down by 99% and 94%. It is anticipated that the mixed tannery wastewater could be disposed of more easily by means of adjusting the total organic ratios of C:N:P to their natural ratio by introducing an additional carbon and phosphorus source to the tannery wastewater. This investigation provides an improved method of leather making with significant reduction of ammonia nitrogen emission in deliming operation and fulfills the integral requirements of the modern sustainable leather industry.

Analyzing quantile spillover effects among international financial markets

This paper investigates the quantile-based spillover effects among 17 stock markets from January 1993 to January 2022, utilizing a quantile approach based on the variance decomposition of a quantile vector autoregression (QVAR) model. Compared with the traditional mean-based spill-over measures, this new quantile approach allows for a nuanced investigation of spillovers at every quantile and capture spillovers under extreme events. The results show that: (1) the total spillover is high and exhibits strong time-varying characteristics, and the tail spillover is higher and more complex in scale and direction;(2) the spillover at each quantile level shows an upward trend, especially during the 2008 crisis and the COVID-19 epidemic;(3) developed countries (or regions) are the net exporters of stock market spillovers, while the developing countries are the net importers;and (4) the 17 stock markets constitute different local financial networks, which may be related to economic conditions and geographical location.

Preparation of the Monoclonal Antibody against the African Swine Fever Virus p54 Protein and Identification of the Antigenic Epitope.

The aim of this paper was to prepare specific monoclonal antibody (mAb) against African swine fever virus (ASFV) p54 protein. The p54 protein was expressed in Escherichia coli expression system and used as the antigen in mAb production. The spleen cells from the immunized BALB/c mice were fused with myeloma cells SP2/0. To screen the positive hybridoma cells, the purified p54 protein was used as envelope antigen for indirect ELISA. After four times' subcloning, the supernatant of hybridoma cells were used to identify mAb subtype, ascites were prepared via in vivo induction method in mice and then the mAb was purified. The titer of the mAb was detected by indirect ELISA, and the specificity of the mAb was identified by cross reactivity assay, IFA and Western blot. According to the predicted secondary structure of p54 protein, using the stepwise truncation method identified the epitope region of mAbs, and labeled the region in tertiary structure of p54 protein. Results were as follows: six hybridoma cells secreting p54 monoclonal antibody were successfully screened and named 28G12-1, 31G7-1, 31G7-2, 35F10-1, 35F10-2, 38D3-1, respectively. The heavy chains of 28G12-1, 31G7-1, and 31G7-2 were IgG2a type, the heavy chains of 35F10-1, 35F10-2, 38D3-1 were IgG1 type, light chains were all kappa chains. The lowest titer of mAb was 1:25 600, and having no cross reaction with PRRSV, PRV, PEDV, PPV, SADS-CoV, PCV2, the specificity was strong. All six monoclonal antibodies could recognize the 127-146 aa on carboxyl end. In this study, ASFV p54 protein and p54 monoclonal antibody were successfully obtained, and the epitopes of six mAbs were identified, these experimental data laid a foundation for the functional research of p54 protein and the study of ASFV epitope vaccine. Copyright © 2023 Editorial Board, Institute of Animal Science of the Chinese Academy of Agricultural Sciences. All rights reserved.

Molecular dynamics simulation of interaction between nanorod and phospholipid molecules bilayer

Natural and artificially prepared nanorods' surfaces have proved to have good bactericidal effect and self-cleaning property. In order to investigate whether nanorods can kill the enveloped virus, like destroying bacterial cell, we study the interaction between nanorods and virus envelope by establishing the models of nanorods with different sizes as well as the planar membrane and vesicle under the Dry Martini force field of molecular dynamics simulation. The results show that owing to the van der Waals attraction between nanorods and the tail hydrocarbon chain groups of phospholipid molecules, the phospholipid molecules on virus envelope are adsorbed to nanorods on a large scale. This process will increase the surface tension of lipid membrane and reduce the order of lipid molecules, resulting in irreparable damage to planar lipid membrane. Nanorods with different diameters have different effects on vesicle envelope, the larger the diameter of nanorod, the weaker the van der Waals effect on the unit cross-sectional area is and the smaller the degree of vesicle deformation. There is synergy between the nanorods in the nanorod array, which can enhance the speed and scale of lipid adsorption. The vesicle adsorbed in the array are difficult to desorb, and even if desorbed, vesicle will be seriously damaged. The deformation rate of the vesicle adsorbed in the nanorod array exceeds 100%, implying that the nanorod array has a strong destructive effect on the vesicle. This preliminarily proves the feasibility of nanorod array on a surface against enveloped virus, and provides a reference for the design of corresponding nanorods surface.

IMPACT OF COVID-19 PANDEMIC ON MENTAL HEALTH IN OLDER ADULTS: COMPARISON BETWEEN 2020 AND 2022

The COVID-19 pandemic had a major impact on older adults' mental health, but less is known about its longer-term effect. We examined changes in depressive and anxiety symptoms among older adults between the onset and two years into the pandemic. Data were drawn from two cross-sectional telephone surveys conducted with older adults aged ≥ 60 years in Hong Kong in 2020 and 2022. Respondents were screened for depression and anxiety using Patient Health Questionnaire-2 (PHQ-2) and General Anxiety Disorders-2 (GAD-2) and, if screened positive (i.e. scoring ≥ 3 in PHQ-2 or GAD-2), evaluated with PHQ-9 and GAD-7 for symptom severity. After case-control matching baseline age, gender, living districts, and pre-existing mental health conditions based on the respondent ratio between the two surveys (i.e. 2:1 ratio), 4095 and 2099 respondents from the 2020 and 2022 surveys were included in the analysis. Respondents' average baseline age was 75 years old, 77% were female, and 13% had a pre-existing mental health condition. There were significant increases in the proportion of older adults screened positive for depression (8.3% to 13.5%) and anxiety (6.9% to 11.4%) and a significant increase in depressive symptom severity (4.63 to 7.72) between 2020 and 2022 (p < .001). Logistic regression suggested that, over two years, older adults with pre-existing mental health conditions were 1.59 times more likely to screen positive for depression than those without such conditions. Linear regression suggested that males were associated with increased depressive (B=-2.42, p=.004) and anxiety (B=-2.49, p=.021) symptom severity than females over the years.