Since the outbreak of the COVID-19 epidemic, it has posed a great crisis to the health and economy of the world. The objective is to provide a simple deep-learning approach for predicting, modelling, and evaluating the time evolutions of the COVID-19 epidemic. The Dove Swarm Search (DSS) algorithm is integrated with the echo state network (ESN) to optimize the weight. The ESN-DSS model is constructed to predict the evolution of the COVID-19 time series. Specifically, the self-driven ESN-DSS is created to form a closed feedback loop by replacing the input with the output. The prediction results, which involve COVID-19 temporal evolutions of multiple countries worldwide, indicate the excellent prediction performances of our model compared with several artificial intelligence prediction methods from the literature (e.g., recurrent neural network, long short-term memory, gated recurrent units, variational auto encoder) at the same time scale. Moreover, the model parameters of the self-driven ESN-DSS are determined which acts as a significant impact on the prediction performance. As a result, the network parameters are adjusted to improve the prediction accuracy. The prediction results can be used as proposals to help governments and medical institutions formulate pertinent precautionary measures to prevent further spread. In addition, this study is not only limited to COVID-19 time series forecasting but also applicable to other nonlinear time series prediction problems.

While prior studies have barely explored social interaction for COVID-19 across Asia, this study highlights how people interact with each other for the COVID-19 pandemic among India, Japan, and South Korea based on social network analysis by employing NodeXL for Twitter between July 27 and July 28, 2020. This study finds that the Ministry of Health and Prime Minister of India, news media of Japan, and the president of South Korea play the most essential role in social networks in their country, respectively. Second, governmental key players play the most crucial role in South Korea, whereas they play the least role in India. Third, the Indian are interested in COVID-19 deaths, the Japanese care about the information of COVID-19 patients, and the South Korean focus on COVID-19 vaccines. Therefore, governments and disease experts should explore their social interaction based on the characteristics of social networks to release important news and information in a timely manner.

This prospective observational study examined changing trends of excess self-protective behavior (EPB), and their association with perceived risk, perceived severity, and irrational beliefs about prevention during the Chinese COVID-19 epidemic. Participants were recruited for an online panel survey. There are 150 participants for the baseline and 102 for the final survey. There were 5 waves of interviews. Perceptions of risk and disease severity were measured by single items. Irrational beliefs about prevention and EPB comprised 5 common prevention misconceptions. Descriptive statistics and the CATMOD program were used for data analysis. The prevalence of participants perceiving personal risk of contracting COVID-19 and severe consequences of the disease was 18.6% and 25.5%, respectively, at baseline, and declining to 4.9% and 17.6% at final observation. The 5 selected EPB also showed a diminishing trend. Belief in COVID-19 prevention myths trended upwards. Perceived risk was positively associated with each EPB, and perceived severity with disinfection of clothes and hoarding of products. Myth adherence was positively associated with disinfection of clothes and both hand washing and sanitization. This study yields new information about EPB among the Chinese public. Policy modifications and public education interventions are essential for minimizing the adverse health effects of subscribing to irrational beliefs.

SARS-CoV-2 transmission dynamics within households involving children are complex. We examined the association between paediatric index case (PIC) age and subsequent household SARS-CoV-2 transmission among cases reported to the Minnesota Department of Health between March 2021 and February 2022. In our primary analysis, we used logistic regression to estimate odds ratios adjusted for race/ethnicity, sex, geographic region, and disease severity among households with an unvaccinated PIC. We performed a secondary analysis among households where the PIC was eligible for vaccination adjusting for the same covariates plus time since the last vaccination. Both analyses were stratified by variant wave. During the Alpha wave, PICs of all age groups had similar odds of subsequent transmission. During Delta and Omicron waves, PICs aged 16–17 had higher odds of subsequent transmission than PICs aged 0–4 (Delta OR, 1.32; [95% CI, 1.16–1.51], Omicron OR, 4.21; [95% CI, 3.25–5.45]). In the secondary analysis, unvaccinated PICs had higher odds of subsequent transmission than vaccinated PICs (Delta OR 2.89 [95% CI, 2.18–3.84], Omicron OR 1.35 [95% CI, 1.21–1.50]). Enhanced preventative measures, especially for 12–17-year-olds, may limit SARS-CoV-2 transmission within households involving children.

The COVID-19 pandemic in 2020 significantly impacted Australia’s resources sector, particularly mining, oil, and gas industries, posing challenges for operational leaders. This study applied Adaptive Crisis Management Theory (ACMT) to understand how these leaders adapted during the crisis. Through interviews with 32 operational leaders, it was found that their roles evolved as crisis demands changed. Initially, they addressed immediate needs, then shifted focus to remote work facilitation and digital transformation, and finally emphasised recovery, trust, and resilience. These adaptations influenced leaders’ behaviours, highlighting the importance of flexibility in supporting employee wellbeing and organisational continuity during crises.

Predicting epidemic trends of coronavirus disease 2019 (COVID-19) remains a key public health concern globally today. However, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinfection rate in previous studies of the transmission dynamics model was mostly a fixed value. Therefore, we proposed a meta-Susceptible-Exposed-Infectious-Recovered-Susceptible (SEIRS) model by adding a time-varying SARS-CoV-2 reinfection rate to the transmission dynamics model to more accurately characterize the changes in the number of infected persons. The time-varying reinfection rate was estimated using random-effect multivariate meta-regression based on published literature reports of SARS-CoV-2 reinfection rates. The meta-SEIRS model was constructed to predict the epidemic trend of COVID-19 from February to December 2023 in Sichuan province. Finally, according to the online questionnaire survey, the SARS-CoV-2 infection rate at the end of December 2022 in Sichuan province was 82.45%. The time-varying effective reproduction number in Sichuan province had two peaks from July to December 2022, with a maximum peak value of about 15. The prediction results based on the meta-SEIRS model showed that the highest peak of the second wave of COVID-19 in Sichuan province would be in late May 2023. The number of new infections per day at the peak would be up to 2.6 million. We constructed a meta-SEIRS model to predict the epidemic trend of COVID-19 in Sichuan province, which was consistent with the trend of SARS-CoV-2 positivity in China. Therefore, a meta-SEIRS model parameterized based on evidence-based data can be more relevant to the actual situation and thus more accurately predict future trends in the number of infections.

During the second wave of COVID-19 pandemic, an increasing number of patients experienced breathlessness, which progressed to acute respiratory distress syndrome, leading to the need for supplemental oxygen therapy and mechanical ventilation. With each passing day, the need for medical oxygen increased and simultaneously medical oxygen reserves in the country were getting depleted. Government agencies deployed multipronged strategies to ensure that the hospitals had an adequate supply of medical oxygen. Mechanisms and formulae were devised for the rational allocation of medical oxygen to various regions in the country; the production of medical oxygen was boosted along with the curtailment of oxygen usage in industries; and efficient supply chain management, which included “Oxygen Express”— special trains for transporting oxygen, aircrafts for transporting medical oxygen, creating green corridors and real-time monitoring of oxygen levels using information technology. The usage and promotion of indigenous PSA oxygen technology augmented the medical oxygen generation capacity at the health care facility level. This emergency situation demonstrated a need for strengthening established intersectoral coordination mechanisms for swift and effective responses to similar situations in future. Various strategies adopted by the Central Government and other government agencies to a large extent helped in addressing the medical oxygen emergencies.

Since the beginning of mass vaccination campaign for COVID-19 in Italy (December 2020) and following the rapidly increasing vaccine administration, sex differences have been emphasized. Nevertheless, incomplete and frequently incoherent sex-disaggregated data for COVID-19 vaccinations are currently available, and vaccines clinical studies generally do not include sex-specific analyses for safety and efficacy. We looked at sex variations in the COVID-19 vaccine’s effectiveness against infection and severe disease outcomes. We conducted a nationwide retrospective cohort study on Italian population, linking information on COVID-19 vaccine administrations obtained through the Italian National Vaccination Registry, with the COVID-19 integrated surveillance system, held by the Istituto Superiore di Sanità. The results showed that, in all age groups, vaccine effectiveness (VE) was higher in the time-interval ≤120 days post-vaccination. In terms of the sex difference in vaccination effectiveness, men and women were protected against serious illness by vaccination in a comparable way, while men were protected against infection to a somewhat greater extent than women. To fully understand the mechanisms underlying the sex difference in vaccine response and its consequences for vaccine effectiveness and development, further research is required. The sex-related analysis of vaccine response may contribute to adjust vaccination strategies, improving overall public health programmes.