The longitudinal association between internet addiction and depressive and anxiety symptoms among Chinese adolescents before and during the COVID-19 pandemic.

Background: The COVID-19 pandemic and related prevention policies, such as home quarantine or online courses, could increase the risks of experiencing internet addiction and mental health problems among Chinese adolescents. There is a lack of longitudinal evidence to show the association between internet addiction symptoms and psychological consequences (e.g., depressive and anxiety symptoms). Objective: This study aimed to explore the association between internet addiction and depressive and anxiety symptoms before and during the coronavirus disease 2019 (COVID-19) pandemic. Methods: An effective sample of 7,958 Chinese adolescents was recruited for this two-wave longitudinal survey conducted over a six-month interval. All participants completed two-wave surveys before and during the COVID-19 pandemic. A longitudinal cross-lagged path model was used to analyze the associations between internet addiction and depressive and anxiety symptoms after controlling for four covariates (i.e., age, sex, minority, and COVID-19 influence). Results: Higher depressive and anxiety symptoms before COVID-19 significantly predicted severe internet addiction during COVID-19. Results showed a significant bidirectional relationship between internet addiction and depressive symptoms. Furthermore, the prevalence of internet addiction displayed an increasing trend over the two waves. Conversely, a reduced prevalence of anxiety and depressive symptoms was observed over the two waves. Conclusion: This current study provided valuable evidence that psychological problems and internet addiction significantly influenced each other before and during the COVID-19 outbreak. Consequently, the presence of psychological problems before and during the COVID-19 outbreak could indicate internet addiction. Thus, depression- and anxiety-related psychotherapies should be developed to prevent internet addiction among Chinese adolescents.

Using simulation modelling and systems science to help contain COVID-19: A systematic review.

This study systematically reviews applications of three simulation approaches, that is, system dynamics model (SDM), agent-based model (ABM) and discrete event simulation (DES), and their hybrids in COVID-19 research and identifies theoretical and application innovations in public health. Among the 372 eligible papers, 72 focused on COVID-19 transmission dynamics, 204 evaluated both pharmaceutical and non-pharmaceutical interventions, 29 focused on the prediction of the pandemic and 67 investigated the impacts of COVID-19. ABM was used in 275 papers, followed by 54 SDM papers, 32 DES papers and 11 hybrid model papers. Evaluation and design of intervention scenarios are the most widely addressed area accounting for 55% of the four main categories, that is, the transmission of COVID-19, prediction of the pandemic, evaluation and design of intervention scenarios and societal impact assessment. The complexities in impact evaluation and intervention design demand hybrid simulation models that can simultaneously capture micro and macro aspects of the socio-economic systems involved.

Risk assessment of imported COVID-19 in China: A modelling study in Sichuan Province.

The importation of COVID-19 cases in China is due to the returning of Chinese citizens abroad, where the majority of cases stand. This study aimed to evaluate the risk of importing COVID-19 into the Sichuan Province of China and conduct a short-term risk prediction assessment and analysis. Data on COVID-19 cases in each country and Sichuan were collected, as well as visitors to Sichuan, population, area, and medical resources in each city in Sichuan province. According to different control strategies of entry aviation and quarantine control, we built models of epidemic transmission to estimate the risk for imported COVID-19 cases in 21 cities of Sichuan. Within 140 days of the policy change's implementation, the number of susceptible, infected, and recovered people in all cities followed the same pattern over time: (1) the number of susceptible people declined slowly at first, then accelerated to reach a stable value; (2) the number of infections gradually increased to a peak, then decreased; and (3) the number of recovered patients gradually increased to a stable value. Under the four different scenarios, there were no significant differences between the risk peaks because the social distance did not change. However, the peak time would be delayed due to the implementation of flight control and nucleic acid detection measures. The improvement of foreign epidemics (reduction of attenuation factors) all delayed the arrival of the peak risk value in Chengdu by about 20 days; however, the size of the peak value did not change significantly. The improvement of nucleic acid detection accuracy delayed the arrival of the peak risk value in Chengdu, but the size of the peak value did not change significantly. Therefore, flight control and the improvement of nucleic acid detection accuracy and overseas epidemic situations have positively affected the prevention and control of the epidemic in Sichuan.

Innovations in Public Health Surveillance for Emerging Infections.

Public health surveillance is defined as the ongoing, systematic collection, analysis, and interpretation of health data and is closely integrated with the timely dissemination of information that the public needs to know and upon which the public should act. Public health surveillance is central to modern public health practice by contributing data and information usually through a national notifiable disease reporting system (NNDRS). Although early identification and prediction of future disease trends may be technically feasible, more work is needed to improve accuracy so that policy makers can use these predictions to guide prevention and control efforts. In this article, we review the advantages and limitations of the current NNDRS in most countries, discuss some lessons learned about prevention and control from the first wave of COVID-19, and describe some technological innovations in public health surveillance, including geographic information systems (GIS), spatial modeling, artificial intelligence, information technology, data science, and the digital twin method. We conclude that the technology-driven innovative public health surveillance systems are expected to further improve the timeliness, completeness, and accuracy of case reporting during outbreaks and also enhance feedback and transparency, whereby all stakeholders should receive actionable information on control and be able to limit disease risk earlier than ever before.

Children and adolescents' positive youth development qualities and internet addiction during the COVID-19 pandemic: A longitudinal study in China.

Backgrounds: Recent studies have shown that the qualities of children and adolescents' positive youth development (PYD) enable them to cope with developmental challenges in an adaptive manner and maintain healthy functioning. During the COVID-19 pandemic, there is still a lack of reporting on changes in children and adolescents' PYD qualities and Internet addiction and their relationship. This study investigated the association between PYD qualities and Internet addiction among the children and adolescents who have experienced the COVID-19 lockdown. Methods: A school-based cohort survey was launched in December 2019 (Wave 1, before COVID-19 lockdown) and followed up in June 2020 (Wave 2, after COVID-19 lockdown). The Chinese PYD scale (80 items, scoring 80-480) and Young's Internet addiction test (20 items, scoring 20-100) were used to evaluate the children and adolescents' PYD qualities and the degree of their Internet addiction, respectively. Cross-sectional regressions, longitudinal regressions, and cross-lagged panel model were used to examine the association between PYD qualities and Internet addiction. Results: 7,985 children and adolescents completed both waves of surveys. Compared with children and adolescents before lockdown (Wave 1), their total PYD quality dropped from 4.99 to 4.96 after COVID-19 lockdown (Wave 2), and the mean score for Internet addiction rose from 35.56 to 36.16. Cross-sectional analysis showed that after controlling for basic characteristics such as age and gender, the total PYD quality of children and adolescents in two waves was negatively correlated with the degree of Internet addiction during the same period, with ß of -6.10 and -6.95, respectively. Longitudinal analysis showed that after controlling for basic characteristics, children and adolescents' total PYD quality in Wave 1 was negatively correlated with the Wave 2 of Internet addiction and the change between the two waves of Internet addiction, with ß of -3.35 and -0.26, respectively. Cross-lagged panel models showed a negative bilateral relationship between total PYD quality and Internet addiction. Conclusion: During the COVID-19 pandemic, the qualities of children and adolescents' PYD declined, which makes children and adolescents more vulnerable to Internet addiction. Therefore, it is necessary to widely implement programs in China that can comprehensively improve the qualities of children and adolescents' positive development to prevent Internet addiction, especially after the blockade due to public health emergencies.

Chinese adolescents' depression, anxiety, and family mutuality before and after COVID-19 lockdowns: Longitudinal cross-lagged relations.

Objective: This study aimed to investigate the longitudinal cross-lagged association between family mutuality, depression, and anxiety among Chinese adolescents before and after the COVID-19 lockdown in 2020. Background: Limited attention has been paid to the longitudinal links between family mutuality, depression, and anxiety in the context of the COVID-19 pandemic. Method: We used self-administered questionnaires to collect data from three high schools and two middle schools in Chengdu City at two time points: Time 1 (T1), December 23, 2019-January 13, 2020; Time 2 (T2), June 16-July 8, 2020. The sample consisted of 7,958 participants who completed two wave surveys before and after the COVID-19 lockdown. We analyzed the data using cross-lagged structural equation modeling. Results: The longitudinal cross-lagged model showed family mutuality at T1 significantly predicted depression, anxiety, and family mutuality at T2. We observed a decreasing prevalence of depression and anxiety after the COVID-19 lockdown. Conclusion: Family mutuality plays an important role in mitigating long-term mental health disorders, such as depression and anxiety. More family-centered psychological interventions could be developed to alleviate mental health disorders during lockdowns. Implications: Improving family mutuality (e.g., mutual support, interaction, and caring among family members) could be beneficial for reducing mental health disorders among Chinese adolescents during the COVID-19 pandemic.

The longitudinal association between internet addiction and depressive and anxiety symptoms among Chinese adolescents before and during the COVID-19 pandemic

Background The COVID-19 pandemic and related prevention policies, such as home quarantine or online courses, could increase the risks of experiencing internet addiction and mental health problems among Chinese adolescents. There is a lack of longitudinal evidence to show the association between internet addiction symptoms and psychological consequences (e.g., depressive and anxiety symptoms). Objective This study aimed to explore the association between internet addiction and depressive and anxiety symptoms before and during the coronavirus disease 2019 (COVID-19) pandemic. Methods An effective sample of 7,958 Chinese adolescents was recruited for this two-wave longitudinal survey conducted over a six-month interval. All participants completed two-wave surveys before and during the COVID-19 pandemic. A longitudinal cross-lagged path model was used to analyze the associations between internet addiction and depressive and anxiety symptoms after controlling for four covariates (i.e., age, sex, minority, and COVID-19 influence). Results Higher depressive and anxiety symptoms before COVID-19 significantly predicted severe internet addiction during COVID-19. Results showed a significant bidirectional relationship between internet addiction and depressive symptoms. Furthermore, the prevalence of internet addiction displayed an increasing trend over the two waves. Conversely, a reduced prevalence of anxiety and depressive symptoms was observed over the two waves. Conclusion This current study provided valuable evidence that psychological problems and internet addiction significantly influenced each other before and during the COVID-19 outbreak. Consequently, the presence of psychological problems before and during the COVID-19 outbreak could indicate internet addiction. Thus, depression- and anxiety-related psychotherapies should be developed to prevent internet addiction among Chinese adolescents.

Impact of Implementing and Lifting COVID-19 Lockdown on Study and Physical Activity Patterns Among Youths in China.

OBJECTIVE: The youths' study and physical activity (PA) patterns may have been affected by lockdown measures due to COVID-19. This study aimed to reveal how youths' study and PA patterns had changed after implementing and lifting COVID-19 lockdown in China. METHODS: The COVID-19 Impact on Lifestyle Change Survey (COINLICS) was used, where 10082 youth participants voluntarily reported their study and PA patterns in the 3 periods before, during, and after COVID-19 lockdown. PA was measured as the weekly frequency of engaging in active transport for commuting/errands, leisure-time walking, leisure-time moderate-/vigorous-intensity physical activity (MVPA), and moderate-/vigorous-intensity housework (MVH); study patterns were measured as the daily average study time and the major study modes. We assessed differences of these variables across educational levels, sex, and periods. RESULTS: The significant decreases were generally observed during lockdown in the frequency of active transport for commuting/ errands (1.3 to 0.2 days/ week), leisure-time walking (1.0 to 0.2 days/ week), leisure-time MVPA (0.7 to 0.3 days/ week), and MVH (2.3 to 2.0 days/ week), with heterogeneities existing between sexes and across educational levels, except for the increase in MVH engagement among graduate students, especially female (1.5 to 2.4 days/ week). Rebounds were observed in the frequency of all activities except MVH after lifting lockdown (2.0 to 1.9 days/ week). The average study time generally increased during lockdown, with more youths studying for 1 - 4 hours/ day and less studying for < 1 hour/ day, and further increased after lockdown. A main shift of study modes has been from in-class to online study after implementing lockdown. CONCLUSIONS: The youths' PA level have generally decreased, and study patterns significantly changed during and after lockdown in China. Our results would inform policymakers and educational administrators of the declined PA levels and changed study patterns among youths during COVID-19 lockdown for better policy making. In - class and/ or extracurricular PA programs could be designed to counteract those effects under cooperation of youths' parents.

Assessing the dynamic impacts of non-pharmaceutical and pharmaceutical intervention measures on the containment results against COVID-19 in Ethiopia.

The rapid spread of COVID-19 in Ethiopia was attributed to joint effects of multiple factors such as low adherence to face mask-wearing, failure to comply with social distancing measures, many people attending religious worship activities and holiday events, extensive protests, country election rallies during the pandemic, and the war between the federal government and Tigray Region. This study built a system dynamics model to capture COVID-19 characteristics, major social events, stringencies of containment measures, and vaccination dynamics. This system dynamics model served as a framework for understanding the issues and gaps in the containment measures against COVID-19 in the past period (16 scenarios) and the spread dynamics of the infectious disease over the next year under a combination of different interventions (264 scenarios). In the counterfactual analysis, we found that keeping high mask-wearing adherence since the outbreak of COVID-19 in Ethiopia could have significantly reduced the infection under the condition of low vaccination level or unavailability of the vaccine supply. Reducing or canceling major social events could achieve a better outcome than imposing constraints on people's routine life activities. The trend analysis found that increasing mask-wearing adherence and enforcing more stringent social distancing were two major measures that can significantly reduce possible infections. Higher mask-wearing adherence had more significant impacts than enforcing social distancing measures in our settings. As the vaccination rate increases, reduced efficacy could cause more infections than shortened immunological periods. Offsetting effects of multiple interventions (strengthening one or more interventions while loosening others) could be applied when the levels or stringencies of one or more interventions need to be adjusted for catering to particular needs (e.g., less stringent social distancing measures to reboot the economy or cushion insufficient resources in some areas).

Ship carbon dioxide emission estimation in coastal domestic emission control areas using high spatial-temporal resolution data: A China case

It is necessary to accurately calculate ship carbon emissions for shipping suitability. The state-of-the-art approaches could arguably not be able to estimate ship carbon emissions accurately due to the uncertainties of Ship Technical Specification Database (STSD) and the geographical and temporal breakpoints in Automatic Identification System (AIS) data, hence requiring a new methodology to be developed to address such defects and further improve the accuracy of emission estimation. Firstly, a novel STSD iterative repair model is proposed based on the random forest algorithm by the incorporation of13 ship technical parameters. The repair model is scalable and can substantially improve the quality of STSD. Secondly, a new ship AIS trajectory segmentation algorithm based on ST-DBSCAN is developed, which effectively eliminates the impact of geographical and temporal AIS breakpoints on emission estimation. It can accurately identify the ships' berthing and anchoring trajectories and reasonably segment the trajectories. Finally, based on this proposed framework, the ship carbon dioxide emissions within the scope of domestic emission control areas (DECA) along the coast of China are estimated. The experiment results indicate that the proposed STSD repair model is highly credible due to the significant connections between ship technical parameters. In addition, the emission analysis shows that, within the scope of China's DECA, the berthing period of ships is longer owing to the joint effects of coastal operation features and the strict quarantine measures under the COVID-19 pandemic, which highlights the emissions produced by ship auxiliary engines and boilers. The carbon intensity of most coastal provinces in China is relatively high, reflecting the urgent demand for the transformation and updates of the economic development models. Based on the theoretical models and results, this study recommends a five-stage decarbonization scheme for China's DECA to advance its decarbonization process.

Using simulation modelling and systems science to help contain COVID‐19: A systematic review

This study systematically reviews applications of three simulation approaches, that is, system dynamics model (SDM), agent‐based model (ABM) and discrete event simulation (DES), and their hybrids in COVID‐19 research and identifies theoretical and application innovations in public health. Among the 372 eligible papers, 72 focused on COVID‐19 transmission dynamics, 204 evaluated both pharmaceutical and non‐pharmaceutical interventions, 29 focused on the prediction of the pandemic and 67 investigated the impacts of COVID‐19. ABM was used in 275 papers, followed by 54 SDM papers, 32 DES papers and 11 hybrid model papers. Evaluation and design of intervention scenarios are the most widely addressed area accounting for 55% of the four main categories, that is, the transmission of COVID‐19, prediction of the pandemic, evaluation and design of intervention scenarios and societal impact assessment. The complexities in impact evaluation and intervention design demand hybrid simulation models that can simultaneously capture micro and macro aspects of the socio‐economic systems involved.

COVID-19 is associated with the risk of cardiovascular disease death: A two-sample Mendelian randomization study

Objective This study aimed to estimate the causal effects of Coronavirus disease 2019 susceptibility and hospitalization on cardiovascular disease death using two-sample Mendelian randomization analysis. Methods We used statistics from a genome-wide association study. A total of 2,568,698 participants were assessed in this study, including 1,299,010 in Coronavirus disease 2019 susceptibility databases, 908,494 in Coronavirus disease 2019 hospitalization database, and 361,194 in a cardiovascular disease death database. We performed two-sample Mendelian randomization analysis using the inverse variance weighted method. As sensitivity analysis techniques, Mendelian randomization-Egger regression, heterogeneity analyses, and Leave-one-out analysis were employed. Reverse Mendelian randomization analysis was used to detect reverse causality. Statistical significance was defined as P < 0.05. Results Coronavirus disease 2019 susceptibility may be a causal factor for cardiovascular disease death (β = 2.188 × 10–3, P = 0.002), which involves five common single nucleotide polymorphisms. Similarly, Coronavirus disease 2019 hospitalization may also be a causal factor for cardiovascular disease death (β = 8.626 × 10–4, P = 0.010), which involves nine common single nucleotide polymorphisms. Furthermore, sensitivity and reverse Mendelian randomization analysis suggested that no heterogeneity, horizontal pleiotropy or reverse causality was found between Coronavirus disease 2019 and cardiovascular disease death. Conclusion Our bidirectional Mendelian randomization analysis showed a causal relationship between Coronavirus disease 2019 susceptibility and hospitalization associated with an increased risk of cardiovascular disease death.

Resilience and mental health: A longitudinal cohort study of Chinese adolescents before and during COVID-19.

Background: The COVID-19 outbreak has resulted in mental health issues, mainly depression and anxiety, prompted by stressors such as the need to maintain social distance, adapting to quarantine, and lockdown policies. Resilience may be vital in protecting individuals from mental disorders. However, few studies have examined the longitudinal relationships between resilience and mental disorders (i.e., depression and anxiety) among adolescents before and during the COVID-19 pandemic. Objective: This study aimed to examine the association between resilience, depression, and anxiety among Chinese adolescents before and during COVID-19 using a longitudinal cross-lagged model. Methods: A total of 7,958 Chinese adolescents completed a baseline survey in the month before COVID-19 and were followed up after the COVID-19 lockdown. Structural equation modeling analyses were applied to evaluate the associations between resilience, depression, and anxiety after controlling for three covariates (i.e., gender, age, and COVID-19 effect). Results: A higher level of resilience before COVID-19 significantly predicted decreased severity of depression and anxiety after the lockdown. Moreover, the mean level of resilience and prevalence of mental disorders (i.e., depression and anxiety) among Chinese adolescents decreased after the lockdown. These findings suggest resilience is a vital protective factor against depression and anxiety among adolescents. Furthermore, younger participants and those less affected by the pandemic could be more resilient. No significant link was found between gender and resilience in the second wave. Conclusions: Resilience is an essential protective factor for reducing mental disorders among Chinese adolescents exposed to COVID-19. Resilience-related interventions should be developed to efficiently promote mental health recovery among youth during pandemics.

Auxiliary Screening COVID-19 by Serology

Background The 2019 novel coronavirus (COVID-19) pandemic remains rampant in many countries/regions. Improving the positive detection rate of COVID-19 infection is an important measure for control and prevention of this pandemic. This meta-analysis aims to systematically summarize the current characteristics of the auxiliary screening methods by serology for COVID-19 infection in real world. Methods Web of Science, Cochrane Library, Embase, PubMed, CNKI, and Wangfang databases were searched for relevant articles published prior to May 1st, 2022. Data on specificity, sensitivity, positive/negative likelihood ratio, area under curve (AUC), and diagnostic odds ratio (dOR) were calculated purposefully. Results Sixty-two studies were included with 35,775 participants in the meta-analysis. Among these studies, the pooled estimates for area under the summary receiver operator characteristic of IgG and IgM to predicting COVID-19 diagnosis were 0.974 and 0.928, respectively. The IgG dOR was 209.78 (95% CI: 106.12 to 414.67). The IgM dOR was 78.17 (95% CI: 36.76 to 166.25). Conclusion Our findings support serum-specific antibody detection may be the main auxiliary screening methods for COVID-19 infection in real world.

Global spreading of Omicron variant of COVID-19.

Although two years have passed since the coronavirus disease 2019 (COVID-19) outbreak, various variants are still rampant across the globe. The Omicron variant, in particular, is rapidly gained dominance through its ability to spread. In this study, we elucidated the spatial distribution pattern of Omicron from a global perspective. We used the cumulative number of notified COVID-19 cases per country spanning four weeks up to February 10, 2022, and the proportion of the Omicron variant genomic sequences from the Global Initiative on Sharing Avian Influenza Data (GISAID). The global spatial distribution of Omicron was investigated by analyzing Global & Local Moran's I and Getis- Ord General G. The spatial weight matrix was defined by combining K-Nearest neighbour and flight connectivity between countries. The results showed that the epidemic is relatively severe in Europe, countries with a high number of Omicron cases and incidence tended to be clustered spatially. In contrast, there are relatively fewer Omicron cases in Asia and Africa, with few hotspots identified. Furthermore, some noted spatial outliers, such as a lowvalue area surrounded by high-value areas, deserve special attention. This study has improved our awareness of the global distribution of Omicron. The findings can provide helpful information for deploying targeted epidemic preparedness for the subsequent COVID-19 variant and future epidemics.

Associations between nighttime light and COVID-19 incidence and mortality in the United States.

COVID-19 has caused almost 770,000 deaths in the United States by November 2021. The nighttime light (NTL), representing the intensity of human activities, may reflect the degree of human contacts and therefore the intensity of COVID-19 transmission. This study intended to assess the associations between NTL differences and COVID-19 incidence and mortality among U.S. counties. The COVID-19 data of U.S. counties as of 31 December 2020 were collected. The average NTL values for each county in 2019 and 2020 were derived from satellite data. A negative binomial mixed model was adopted to assess the relationships between NTL intensity and COVID-19 incidence and mortality. Compared to the counties with the lowest NTL level (0.14-0.37 nW/cm2/sr), those with the highest NTL level (1.78-59.61 nW/cm2/sr) were related with 15% higher mortality rates (mortality rate ratio:1.15, 95 %CI: 1.02-1.30, p-value: 0.02) and 23% higher incidence rates (incidence rate ratio:1.23, 95 %CI: 1.13-1.34, p-value < 0.0001). Our study suggested that more intensive NTL was related with higher incidence and mortality rates of COVID-19, and NTL had a stronger correlation with the COVID-19 incidence rate than mortality rate. Our findings have contributed solid epidemiological evidence to the existing COVID-19 knowledge pool, and would help policymakers develop interventions when faced with the potential risk of the following outbreaks.

The relationship between family functioning and non-suicidal self-injury in adolescents: A structural equation modeling analysis.

BACKGROUND: Previous research has suggested that depressive symptoms, emotional competence, and posttraumatic stress symptoms (PTSS) may mediate the association between family functioning and non-suicidal self-injury (NSSI). Therefore, this study aimed to evaluate the mediation effects of depressive symptoms, emotional competence, and COVID-related PTSS on the relationship between family functioning and NSSI in adolescents. METHOD: A sample of 5854 adolescents was recruited from June 16 to July 8, 2020. The data for family functioning, depressive symptoms, emotional competence, COVID-related PTSS, and NSSI behavior of adolescents were collected via self-reported questionnaires. A structural equation model was constructed to examine the relationship, and a bootstrap analysis was conducted to evaluate the mediation effects. RESULTS: The reporting rate of adolescent NSSI was 30.2%. The poor family functioning was positively associated with adolescent NSSI (ß = 0.130, 95% CI = 0.093-0.182), which was mediated by depression with effect size of 0.231 (95% CI = 0.201-0.257). The pathway coefficients between emotional competence and NSSI, and depression, COVID-related PTSS and NSSI, though statistically significant were unlikely to be clinically meaning with values of 0.057 and 0.015. There was no mediating effect by COVID-related PTSS. The pathways initially constructed between family functioning and COVID-related PTSS, emotional capacity and COVID-related PTSS were not been verified. LIMITATIONS: It was unclear whether this mediational effect would be supported in a longitudinal design. The application and extension of this model toward other regions and countries, and different ages need to be further explored. CONCLUSION: The interventions of adolescent NSSI should focus on both the family level and individual levels. Improving family environment, screening depressive symptoms, enhancing emotional competence and lessening COVID-related PTSS may reduce NSSI.

Cultivating resilience during the COVID-19 pandemic: A socioecological perspective

The coronavirus disease 2019 (COVID-19) pandemic poses wide-ranging impacts on the physical and mental health of people around the world, increasing attention from both researchers and practitioners on the topic of resilience. In this article, we review previous research on resilience from the past several decades, focusing on how to cultivate resilience during emerging situations such as the COVID-19 pandemic at the individual, organizational, community, and national levels from a socioecological perspective. Although previous research has greatly enriched our understanding of the conceptualization, predicting factors, processes, and consequences of resilience from a variety of disciplines and levels, future research is needed to gain a deeper and comprehensive understanding of resilience, including developing an integrative and interdisciplinary framework for cultivating resilience, developing an understanding of resilience from a life span perspective, and developing scalable and cost-effective interventions for enhancing resilience and improving pandemic preparedness. (PsycInfo Database Record (c) 2022 APA, all rights reserved)