Impact of international travel and border control measures on the global spread of the novel 2019 coronavirus outbreak

SARS-CoV-2 Testing of Aircraft Wastewater Shows That Mandatory Tests and Vaccination Pass before Boarding Did Not Prevent Massive Importation of Omicron Variant into Europe

BACKGROUND

Most new SARS-CoV-2 epidemics in France occurred following the importation from abroad of emerging viral variants. Currently, the risk of new variants being imported is controlled based on a negative screening test (PCR or antigenic) and proof of up-to-date vaccine status, such as the International Air Transport Association travel pass.

METHODS

The wastewater from two planes arriving in Marseille (France) from Addis Ababa (Ethiopia) in December 2021 was tested by RT-PCR to detect SARS-CoV2 and screen for variants. These tests were carried out between landing and customs clearance and were then sequenced by MiSeq Illumina. Antigenic tests and sequencing by NovaSeq were carried out on respiratory samples collected from the 56 passengers on the second flight.

RESULTS

SARS-CoV-2 RNA suspected of being from the Omicron BA.1 variant was detected in the aircraft's wastewater. SARS-CoV2 RNA was detected in 11 [20%) passengers and the Omicron BA.1 variant was identified.

CONCLUSION

Our work shows the efficiency of aircraft wastewater testing to detect SARS-CoV-2 cases among travellers and to identify the viral genotype. It also highlights the low efficacy of the current control strategy for flights entering France from outside Europe, which combines a requirement to produce a vaccine pass and proof of a negative test before boarding.

Technological Advancements and Economics in Plant Production Systems: How to Retrofit?

Plant production systems such as plant factories and greenhouses can help promote resilience in food production. These systems could be used for plant protection and aid in controlling the micro- and macro- environments needed for optimal plant growth irrespective of natural disasters and changing climate conditions. However, to ensure optimal environmental controls and efficient production, several technologies such as sensors and robots have been developed and are at different stages of implementation. New and improved systems are continuously being investigated and developed with technological advances such as robotics, sensing, and artificial intelligence to mitigate hazards to humans working in these systems from poor ventilation and harsh weather while improving productivity. These technological advances necessitate frequent retrofits considering local contexts such as present and projected labor costs. The type of agricultural products also affects measures to be implemented to maximize returns on investment. Consequently, we formulated the retrofitting problem for plant production systems considering two objectives; minimizing the total cost for retrofitting and maximizing the yearly net profit. Additionally, we considered the following: (a) cost of new technologies; (b) present and projected cost for human labor and robotics; (c) size and service life of the plant production system; (d) productivity before and after retrofit, (e) interest on loans for retrofitting, (f) energy consumption before and after retrofit and, (g) replacement and maintenance cost of systems. We solved this problem using a multi-objective evolutionary algorithm that results in a set of compromised solutions and performed several simulations to demonstrate the applicability and robustness of the method. Results showed up to a 250% increase in annual net profits in an investigated case, indicating that the availability of all the possible retrofitting combinations would improve decision making. A user-friendly system was developed to provide all the feasible retrofitting combinations and total costs with the yearly return on investment in agricultural production systems in a single run.

Intentions to use ride-sourcing services in Vietnam: What happens after three months without COVID-19 infections?

The COVID-19 pandemic has brought new risks and stress for paid transport users worldwide. COVID-19 has changed mobility dynamics worldwide, including low- and middle-income countries (e.g., Vietnam). The present study aims to provide an in-depth understanding of ride-sourcing passengers' behavioural intentions when COVID-19 pandemic management successfully prevented community transmission by extending the TPB with two constructs: perceived virus infection risk and problem-focused coping. Using self-administered questionnaires, data were collected from ride-sourcing customers in Ho Chi Minh City (Vietnam). A total of 540 responses were used for validating the proposed theorethical model. The structural equation model results indicate that problem-focused coping is a multi-faceted construct with two dimensions: problem-solving and self-protection. Also, problem-focused coping has the highest total effect on the intention to use ride-sourcing services following a period of COVID-19 suppression (3 months without identified cases). The findings also reveal that attitude partially mediates the link between problem-focused coping and behavioural intention. The results of this study could be used to develop strategies to promote ride-sourcing services in the aftermath of the COVID-19 pandemic.

Community-Level Health Interventions are Crucial in the Post-COVID-19 Era: Lessons from Africa’s Proactive Public Health Policy Interventions

Measured against the gloomy pre-COVID-19 predictions, Africa has fared far better than most regions in managing the pandemic. This much, however, has received less attention. This paper answers the question: how have the new rituals of self determination in public health affected the successful management of COVID-19 in Africa, and how can the continent and the rest of the world build on such models/lessons in the post-pandemic era? I employ emancipatory theorising in reviewing literature on approaches to governance of COVID-19. The rationale is to empower the grassroots and to accentuate the urgency for a decolonized local ownership of the governance of all public health crises. I argue that while traditional international cooperation is necessary for additional resource and expertise from the global North for sustainable health, the political will of Southern governments remains fundamental for any extraordinary success due to its grassroots/community orientation towards non-pharmaceutical interventions and initial pre-emptive rituals. The novelty in this paper is that it lays bare the ignored African responses and lessons and reveals how to harness protective communitarian ethos in solving future crises. The paper further provides population health as an ‘immune system’ policy framework for explaining and predicting how a scientific and human-centrered grassroots leadership can yield optimal outcomes in any future crisis.

Was the Reduction in Seasonal Influenza Transmission during 2020 Attributable to Non-Pharmaceutical Interventions to Contain Coronavirus Disease 2019 (COVID-19) in Japan?

We quantified the effects of adherence to various non-pharmaceutical interventions (NPIs) on the seasonal influenza epidemic dynamics in Japan during 2020. The total monthly number of seasonal influenza cases per sentinel site (seasonal influenza activity) reported to the National Epidemiological Surveillance of Infectious Diseases and alternative NPI indicators (retail sales of hand hygiene products and number of airline passenger arrivals) from 2014−2020 were collected. The average number of monthly seasonal influenza cases in 2020 had decreased by approximately 66.0% (p < 0.001) compared to those in the preceding six years. An increase in retail sales of hand hygiene products of ¥1 billion over a 3-month period led to a 15.5% (95% confidence interval [CI]: 10.9−20.0%; p < 0.001) reduction in seasonal influenza activity. An increase in the average of one million domestic and international airline passenger arrivals had a significant association with seasonal influenza activity by 11.6% at lag 0−2 months (95% CI: 6.70−16.5%; p < 0.001) and 30.9% at lag 0−2 months (95% CI: 20.9−40.9%; p < 0.001). NPI adherence was associated with decreased seasonal influenza activity during the COVID-19 pandemic in Japan, which has crucial implications for planning public health interventions to minimize the health consequences of adverse seasonal influenza epidemics.

The impact of geo-environmental factors on global COVID-19 transmission: A review of evidence and methodology

Studies on Coronavirus Disease 2019 (COVID-19) transmission indicate that geo-environmental factors have played a significant role in the global pandemic. However, there has not been a systematic review on the impact of geo-environmental factors on global COVID-19 transmission in the context of geography. As such, we reviewed 49 well-chosen studies to reveal the impact of geo-environmental factors (including the natural environment and human activity) on global COVID-19 transmission, and to inform critical intervention strategies that could mitigate the worldwide effects of the pandemic. Existing studies frequently mention the impact of climate factors (e.g., temperature and humidity); in contrast, a more decisive influence can be achieved by human activity, including human mobility, health factors, and non-pharmaceutical interventions (NPIs). The above results exhibit distinct spatiotemporal heterogeneity. The related analytical methodology consists of sensitivity analysis, mathematical modeling, and risk analysis. For future studies, we recommend highlighting geo-environmental interactions, developing geographically statistical models for multiple waves of the pandemic, and investigating NPIs and care patterns. We also propose four implications for practice to combat global COVID-19 transmission.

Rethinking Lockdown Policies in the Pre-Vaccine Era of COVID-19: A Configurational Perspective

The significance of lockdown policies for controlling the COVID-19 pandemic is widely recognized. However, most studies have focused on individual lockdown measures. The effectiveness of lockdown policy combinations has not been examined from a configurational perspective. This research applies fuzzy-set qualitative comparative analysis (fsQCA) to examine different lockdown policy combinations associated with high-epidemic situations in 84 countries. A high-epidemic situation can occur through three different “weak-confined” patterns of lockdown policy combinations. The findings demonstrate that a combination of lockdown policies is more successful than any single lockdown policy, whereas the absence of several key measures in policy combinations can lead to a high-epidemic situation. The importance of international travel controls can become obscured when they are the only measures adopted, and a high-epidemic situation can still arise where restrictions are placed on international travel but not on public transport or when workplaces are closed but schools remain open.

A measure to estimate the risk of imported COVID-19 cases and its application for evaluating travel-related control measures

High connectivity between nations facilitates the spread of infectious diseases. We introduce an improved measure to estimate the risk of COVID-19 importation. The measure was applied to identify the effectiveness of travel-related control measures. We estimated the risk of importation, using the product of air-travel volume and COVID-19 prevalence in the area-of-origin. Travel volumes were acquired through real-time mobile data, and prevalence was calculated considering the time-varying strength of the COVID-19 testing policy. With the measure, the number of expected-imported cases was calculated, and compared with the reported-imported COVID-19 cases before and after post-entry quarantine for all entrants. The expected and reported-imported cases were well fitted (R² = 0.8). A maximum of 35 undetected-imported cases was estimated to have entered Seoul, before the first imported COVID-19 case was confirmed. With the travel-related control measures, at most, 48 (73%) imported cases could be isolated from the local community. Our measure predicted trends in imported COVID-19 cases well. The method used to develop the measure can be applied to future emerging infectious diseases. Our results provide a ‘real-world’ evidence that travel-related control measures are effective at curbing further COVID-19 transmission.

Clinical Characteristics in Patients with Redetected Positive RNA Test After Recovery from Foreign-Imported COVID-19 Cases in Xi’an, China

Purpose

At present, it has been found that managing patients with a redetected positive RNA test after recovery from foreign-imported coronavirus disease 2019 (COVID-19) cases in China is challenging. The purpose of the current study was to describe the clinical characteristics of these patients.

Methods

This retrospective cohort study included 137 COVID-19 patients who were discharged from the Xi’an Public Health Center from 28 July 2020 to 31 December 2021. We compared the clinical characteristics between positive retest patients and non-positive retest patients.

Results

137 COVID-19 patients entered our study, 27 (19.7%) cases of COVID-19 with a redetected positive RNA test by the end of the follow-up period. Fever [(n = 31 (22.6%)], cough [n = 26 (18.9%)] and sore throat [n = 20 (14.5%)] were the most common initial symptoms among the foreign-imported COVID-19 patients, and there were almost no significant differences in initial symptoms between positive retest patients and non-positive retest patients. The positive retest patients had a higher lymphocyte count (p = 0.031) and lymphocyte percentage (p = 0.007) during readmission. There were generally no significant differences in other routine blood test findings, IgG and IgM antibody responses, between positive retest patients and non-positive retest patients, or in positive retest patients over time (before, during, or after positive patient detection). After readmission, positive retest patients displayed fewer symptoms or no obvious disease progression and more sustained remission by CT imaging.

Conclusion

Our findings revealed that the clinical characteristics at the time of initial diagnosis were not closely related to redetected positive RNA tests after recovery from foreign-imported COVID-19 cases. Positive retest patients had virtually no symptoms and displayed no obvious disease progression during readmission. These findings provide important information and clinical evidence for the effective management of foreign-imported COVID-19 patients during their convalescent phase.

There exists the "smartest" movement rate to control the epidemic rather than "city lockdown"

The emergency outbreak and spread of coronavirus disease 2019 (COVID-19) has left great damage to individuals over most of the world. Population mobility is the primary reason for the spread of the epidemic. A delayed stochastic epidemic susceptible-infected-recovered (SIR) model with Gaussian white noise is introduced. Compared with traditional models,this model is characterized by time delay, environmental noise and population mobility among municipalities with the convenient transportation network. The stochastic dynamic behavior of the SIR model is analyzed and the existence of the stochastic bifurcation of the system is proved. The effect of time delay and movement rate are investigated. Numerical simulations are performed to support the theoretical results. It is worth mentioning that the movement rate is not as low as possible and appropriate population mobility is conducive to alleviating the epidemic. Through simulation, we demonstrate the existence of the best movement rate named the "smartest" κ , which is helpful to control the epidemic. This model is also useful to prevent other infectious diseases.

Mobility during the pandemic: how did our movements shape the course of COVID-19?

In this manuscript, we critically assess the evidence around various methods of reducing mobility, and how these have impacted the course of the coronavirus disease 2019 (COVID-19) pandemic. We further highlight the difficulty in assessing the effectiveness of such measures before giving directions for future research.

Prevalence and Dynamics of SARS-CoV-2 Antibodies in the Population of St. Petersburg, Russia

Background

The aim of the study was to assess the prevalence of seropositive status for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-IgA, -IgM, and -IgG; its dynamics in connection with restrictive measures during the coronavirus disease (COVID-19) pandemic; and the quantitative dynamics of antibody levels in the population of St. Petersburg, Russia.

Methods

From May to November 2020, a retrospective analysis of Saint Petersburg State University Hospital laboratory database was performed. The database included 158,283 test results of 87,067 patients for SARS-CoV-2 detection by polymerase chain reaction (PCR) and antibody detection of SARS-CoV-2-IgA, -IgM, and -IgG. The dynamics of antibody level was assessed using R v.3.6.3.

Results

The introduction of a universal lockdown was effective in containing the spread of COVID-19. The proportion of seropositive patients gradually decreased; approximately 50% of these patients remained seropositive for IgM after 3–4 weeks; for IgG, by follow-up week 22; and for IgA, by week 12. The maximum decrease in IgG and IgA was observed 3–4 months and 2 months after the detection of the seropositive status, respectively.

Conclusions

The epidemiological study of post-infection immunity to COVID-19 demonstrates significant differences in the dynamics of IgA, IgM, and IgG seropositivity and in PCR test results over time, which is linked to the introduction of restrictive measures. Both the proportion of seropositive patients and the level of all antibodies decreased in terms of the dynamics, and only approximately half of these patients remained IgG-positive 6 months post-infection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s44197-022-00041-9.

Global research production pertaining to gastrointestinal involvement in COVID-19: A bibliometric and visualised study

BACKGROUND

Coronavirus disease 2019 (COVID-19) is a global pandemic that can cause diarrhoea, nausea/vomiting, and abdominal pain, among other gastrointestinal (GI) symptoms.

AIM

To perform a bibliometric analysis of the global research production pertaining to GI involvement in COVID-19.

METHODS

The Scopus database was used to search the global literature on GI involvement in COVID-19 during 2020. A bibliometric review of these publications was also performed using VOSviewer.

RESULTS

Scopus had published 95615 documents on COVID-19 in all areas of research at the time of data collection. In total, 1267 publications on the topic of GI and COVID-19 were identified. Research articles (n = 606; 47.83%), letters (293; 23.13%), and reviews (186; 14.68%) were the most popular types of documents. The most productive countries and institutions in this field were the United States and Huazhong University of Science and Technology. The most cited paper was Xiao et al, which was published in Gastroenterology as a brief communication, with 798 citations. This paper provides evidence for GI infection of COVID-19 and its possible faecal–oral transmission route. In the term cluster analysis, there were two frontiers in this field: GI manifestations among COVID-19 patients and the implications of COVID-19 for the gastroenterologist.

CONCLUSION

GI manifestations among COVID-19 patients and implications of COVID-19 for gastroenterologists were of interest, especially in the early stages of the pandemic.

A longitudinal study of the impact of university student return to campus on the SARS-CoV-2 seroprevalence among the community members

Returning university students represent large-scale, transient demographic shifts and a potential source of transmission to adjacent communities during the COVID-19 pandemic. In this prospective longitudinal cohort study, we tested for IgG antibodies against SARS-CoV-2 in a non-random cohort of residents living in Centre County prior to the Fall 2020 term at the Pennsylvania State University and following the conclusion of the Fall 2020 term. We also report the seroprevalence in a non-random cohort of students collected at the end of the Fall 2020 term. Of 1313 community participants, 42 (3.2%) were positive for SARS-CoV-2 IgG antibodies at their first visit between 07 August and 02 October 2020. Of 684 student participants who returned to campus for fall instruction, 208 (30.4%) were positive for SARS-CoV-2 antibodies between 26 October and 21 December. 96 (7.3%) community participants returned a positive IgG antibody result by 19 February. Only contact with known SARS-CoV-2-positive individuals and attendance at small gatherings (20-50 individuals) were significant predictors of detecting IgG antibodies among returning students (aOR, 95% CI 3.1, 2.07-4.64; 1.52, 1.03-2.24; respectively). Despite high seroprevalence observed within the student population, seroprevalence in a longitudinal cohort of community residents was low and stable from before student arrival for the Fall 2020 term to after student departure. The study implies that heterogeneity in SARS-CoV-2 transmission can occur in geographically coincident populations.

Forecasting COVID-19 Pandemic Using Prophet, ARIMA, and Hybrid Stacked LSTM-GRU Models in India

Due to the proliferation of COVID-19, the world is in a terrible condition and human life is at risk. The SARS-CoV-2 virus had a significant impact on public health, social issues, and financial issues. Thousands of individuals are infected on a regular basis in India, which is one of the populations most seriously impacted by the pandemic. Despite modern medical and technical technology, predicting the spread of the virus has been extremely difficult. Predictive models have been used by health systems such as hospitals, to get insight into the influence of COVID-19 on outbreaks and possible resources, by minimizing the dangers of transmission. As a result, the main focus of this research is on building a COVID-19 predictive analytic technique. In the Indian dataset, Prophet, ARIMA, and stacked LSTM-GRU models were employed to forecast the number of confirmed and active cases. State-of-the-art models such as the recurrent neural network (RNN), gated recurrent unit (GRU), long short-term memory (LSTM), linear regression, polynomial regression, autoregressive integrated moving average (ARIMA), and Prophet were used to compare the outcomes of the prediction. After predictive research, the stacked LSTM-GRU model forecast was found to be more consistent than existing models, with better prediction results. Although the stacked model necessitates a large dataset for training, it aids in creating a higher level of abstraction in the final results and the maximization of the model's memory size. The GRU, on the other hand, assists in vanishing gradient resolution. The study findings reveal that the proposed stacked LSTM and GRU model outperforms all other models in terms of R square and RMSE and that the coupled stacked LSTM and GRU model outperforms all other models in terms of R square and RMSE. This forecasting aids in determining the future transmission paths of the virus.

COVID-19 transmission risk factors

We analyze risk factors correlated with the initial transmission growth rate of the recent COVID-19 pandemic in different countries. The number of cases follows in its early stages an almost exponential expansion; we chose as a starting point in each country the first day di with 30 cases and we fitted for 12 days, capturing thus the early exponential growth. We looked then for linear correlations of the exponents α with other variables, for a sample of 126 countries. We find a positive correlation, i.e. faster spread of COVID-19, with high confidence level with the following variables, with respective p-value: low Temperature (4⋅10-7), high ratio of old vs. working-age people (3⋅10-6), life expectancy (8⋅10-6), number of international tourists (1⋅10-5), earlier epidemic starting date di (2⋅10-5), high level of physical contact in greeting habits (6⋅10-5), lung cancer prevalence (6⋅10-5), obesity in males (1⋅10-4), share of population in urban areas (2⋅10-4), cancer prevalence (3⋅10-4), alcohol consumption (0.0019), daily smoking prevalence (0.0036), and UV index (0.004, 73 countries). We also find a correlation with low Vitamin D serum levels (0.002-0.006), but on a smaller sample, ∼50 countries, to be confirmed on a larger sample. There is highly significant correlation also with blood types: positive correlation with types RH- (3⋅10-5) and A+ (3⋅10-3), negative correlation with B+ (2⋅10-4). We also find positive correlation with moderate confidence level (p-value of 0.02∼0.03) with: CO₂/SO emissions, type-1 diabetes in children, low vaccination coverage for Tuberculosis (BCG). Several of the above variables are correlated with each other, and so they are likely to have common interpretations. We thus performed a Principal Component Analysis, to find the significant independent linear combinations of such variables. The variables with loadings of at least 0.3 on the significant PCA are: greeting habits, urbanization, epidemic starting date, number of international tourists, temperature, lung cancer, smoking, and obesity in males. We also analyzed the possible existence of a bias: countries with low GDP-per capita might have less intense testing, and we discuss correlation with the above variables.

COVID-19 transmission risk factors

We analyze risk factors correlated with the initial transmission growth rate of the recent COVID-19 pandemic in different countries. The number of cases follows in its early stages an almost exponential expansion; we chose as a starting point in each country the first day d i with 30 cases and we fitted for 12 days, capturing thus the early exponential growth. We looked then for linear correlations of the exponents α with other variables, for a sample of 126 countries. We find a positive correlation, i.e. faster spread of COVID-19, with high confidence level with the following variables, with respective p -value: low Temperature (4 ⋅ 10 - 7 ), high ratio of old vs. working-age people (3 ⋅ 10 - 6 ), life expectancy (8 ⋅ 10 - 6 ), number of international tourists (1 ⋅ 10 - 5 ), earlier epidemic starting date d i (2 ⋅ 10 - 5 ), high level of physical contact in greeting habits (6 ⋅ 10 - 5 ), lung cancer prevalence (6 ⋅ 10 - 5 ), obesity in males (1 ⋅ 10 - 4 ), share of population in urban areas (2 ⋅ 10 - 4 ), cancer prevalence (3 ⋅ 10 - 4 ), alcohol consumption (0.0019 ), daily smoking prevalence (0.0036 ), and UV index (0.004 , 73 countries). We also find a correlation with low Vitamin D serum levels (0.002 - 0.006 ), but on a smaller sample, ∼ 50 countries, to be confirmed on a larger sample. There is highly significant correlation also with blood types: positive correlation with types RH- (3 ⋅ 10 - 5 ) and A+ (3 ⋅ 10 - 3 ), negative correlation with B+ (2 ⋅ 10 - 4 ). We also find positive correlation with moderate confidence level (p -value of 0.02 ∼ 0.03 ) with: CO2/SO emissions, type-1 diabetes in children, low vaccination coverage for Tuberculosis (BCG). Several of the above variables are correlated with each other, and so they are likely to have common interpretations. We thus performed a Principal Component Analysis, to find the significant independent linear combinations of such variables. The variables with loadings of at least 0.3 on the significant PCA are: greeting habits, urbanization, epidemic starting date, number of international tourists, temperature, lung cancer, smoking, and obesity in males. We also analyzed the possible existence of a bias: countries with low GDP-per capita might have less intense testing, and we discuss correlation with the above variables.

Framework for assessing and easing global COVID-19 travel restrictions

During the COVID-19 pandemic, many countries implemented international travel restrictions that aimed to contain viral spread while still allowing necessary cross-border travel for social and economic reasons. The relative effectiveness of these approaches for controlling the pandemic has gone largely unstudied. Here we developed a flexible network meta-population model to compare the effectiveness of international travel policies, with a focus on evaluating the benefit of policy coordination. Because country-level epidemiological parameters are unknown, they need to be estimated from data; we accomplished this using approximate Bayesian computation, given the nature of our complex stochastic disease transmission model. Based on simulation and theoretical insights we find that, under our proposed policy, international airline travel may resume up to 58% of the pre-pandemic level with pandemic control comparable to that of a complete shutdown of all airline travel. Our results demonstrate that global coordination is necessary to allow for maximum travel with minimum effect on viral spread.

Health, Economic and Social Development Challenges of the COVID-19 Pandemic: Strategies for Multiple and Interconnected Issues

The COVID-19-pandemic-related economic and social crises are leading to huge challenges for all spheres of human life across the globe. Various challenges highlighted by this pandemic include, but are not limited to, the need for global health cooperation and security, better crisis management, coordinated funding in public health emergencies, and access to measures related to prevention, treatment and control. This systematic review explores health, economic and social development issues in a COVID-19 pandemic context and aftermath. Accordingly, a methodology that focuses on identifying relevant literature with a focus on meta-analysis is used. A protocol with inclusion and exclusion criteria was developed, with articles from 15 December 2019 to 15 March 2022 included in the study. This was followed by a review and data analysis. The research results reveal that non-pharmaceutical measures like social distancing, lockdown and quarantine have created long-term impacts on issues such as changes in production and consumption patterns, market crashes resulting in the closure of business operations, and the slowing down of the economy. COVID-19 has exposed huge health inequalities across most countries due to social stratification and unequal distribution of wealth and/or resources. People from lower socio-economic backgrounds lack access to essential healthcare services during this critical time for both COVID-19 and other non-COVID ailments. The review shows that there is minimal literature available with evidence and empirical backup; similarly, data/studies from all countries/regions are not available. We propose that there is a need to conduct empirical research employing a trans-disciplinary approach to develop the most effective and efficient strategies to combat the pandemic and its aftermath. There is a need to explore the social and ecological determinants of this contagious infection and develop strategies for the prevention and control of COVID-19 or similar infections in future.

An in-depth statistical analysis of the COVID-19 pandemic's initial spread in the WHO African region

During the first wave of the COVID-19 pandemic, sub-Saharan African countries experienced comparatively lower rates of SARS-CoV-2 infections and related deaths than in other parts of the world, the reasons for which remain unclear. Yet, there was also considerable variation between countries. Here, we explored potential drivers of this variation among 46 of the 47 WHO African region Member States in a cross-sectional study. We described five indicators of early COVID-19 spread and severity for each country as of 29 November 2020: delay in detection of the first case, length of the early epidemic growth period, cumulative and peak attack rates and crude case fatality ratio (CFR). We tested the influence of 13 pre-pandemic and pandemic response predictor variables on the country-level variation in the spread and severity indicators using multivariate statistics and regression analysis. We found that wealthier African countries, with larger tourism industries and older populations, had higher peak (p<0.001) and cumulative (p<0.001) attack rates, and lower CFRs (p=0.021). More urbanised countries also had higher attack rates (p<0.001 for both indicators). Countries applying more stringent early control policies experienced greater delay in detection of the first case (p<0.001), but the initial propagation of the virus was slower in relatively wealthy, touristic African countries (p=0.023). Careful and early implementation of strict government policies were likely pivotal to delaying the initial phase of the pandemic, but did not have much impact on other indicators of spread and severity. An over-reliance on disruptive containment measures in more resource-limited contexts is neither effective nor sustainable. We thus urge decision-makers to prioritise the reduction of resource-based health disparities, and surveillance and response capacities in particular, to ensure global resilience against future threats to public health and economic stability.

Should routine risk reduction procedures for the prevention and control of pandemics become a standard in all oncological outpatient clinics? The prospective COVID-19 cohort study: protect-CoV

Limited knowledge exists on the effectiveness of preventive preparedness plans for the care of outpatient cancer patients during epidemics or pandemics. To ensure adequate, timely and continuous clinical care for this highly vulnerable population, we propose the establishment of preventive standard safety protocols providing effective early phase identification of outbreaks at outpatient cancer facilities and communicating adapted standards of care. The prospective cohort study Protect-CoV conducted at the LMU Klinikum from mid-March to June 2020 investigated the effectiveness of a rapid, proactive and methodical response to protect patients and interrupt SARS-CoV-2 transmission chains during the first pandemic wave. The implemented measures reduced the risk of infection of individual cancer patients and ensured safe adjunctive infusion therapy in an outpatient setting during the early COVID-19 pandemic. In addition to the immediate implementation of standard hygiene procedures, our results underscore the importance of routine PCR testing for the identification of asymptomatic or pre-symptomatic COVID-19 cases and immediate tracing of positive cases and their contacts. While more prospective controlled studies are needed to confirm these results, our study illustrates the importance of including preventative testing and tracing measures in the standard risk reduction procedures at all out patient cancer centers.

Causal inference for the impact of economic policy on financial and labour markets amid the COVID-19 pandemic

The COVID-19 pandemic has turned the world upside down since the beginning of 2020, leaving most nations worldwide in both health crises and economic recession. Governments have been continually responding with multiple support policies to help people and businesses overcoming the current situation, from “Containment”, “Health” to “Economic” policies, and from local and national supports to international aids. Although the pandemic damage is still not under control, it is essential to have an early investigation to analyze whether these measures have taken effects on the early economic recovery in each nation, and which kinds of measures have made bigger impacts on reducing such negative downturn. Therefore, we conducted a time series based causal inference analysis to measure the effectiveness of these policies, specifically focusing on the “Economic support” policy on the financial markets for 80 countries and on the United States and Australia labour markets. Our results identified initial positive causal relationships between these policies and the market, providing a perspective for policymakers and other stakeholders.

COVID-19 in low-tolerance border quarantine systems: Impact of the Delta variant of SARS-CoV-2

In controlling transmission of coronavirus disease 2019 (COVID-19), the effectiveness of border quarantine strategies is a key concern for jurisdictions in which the local prevalence of disease and immunity is low. In settings like this such as China, Australia, and New Zealand, rare outbreak events can lead to escalating epidemics and trigger the imposition of large-scale lockdown policies. Here, we develop and apply an individual-based model of COVID-19 to simulate case importation from managed quarantine under various vaccination scenarios. We then use the output of the individual-based model as input to a branching process model to assess community transmission risk. For parameters corresponding to the Delta variant, our results demonstrate that vaccination effectively counteracts the pathogen's increased infectiousness. To prevent outbreaks, heightened vaccination in border quarantine systems must be combined with mass vaccination. The ultimate success of these programs will depend sensitively on the efficacy of vaccines against viral transmission.

An epidemic model for COVID-19 transmission in Argentina: Exploration of the alternating quarantine and massive testing strategies

The COVID-19 pandemic has challenged authorities at different levels of government administration around the globe. When faced with diseases of this severity, it is useful for the authorities to have prediction tools to estimate in advance the impact on the health system as well as the human, material, and economic resources that will be necessary. In this paper, we construct an extended Susceptible-Exposed-Infected-Recovered model that incorporates the social structure of Mar del Plata, the 4°most inhabited city in Argentina and head of the Municipality of General Pueyrredón. Moreover, we consider detailed partitions of infected individuals according to the illness severity, as well as data of local health resources, to bring predictions closer to the local reality. Tuning the corresponding epidemic parameters for COVID-19, we study an alternating quarantine strategy: a part of the population can circulate without restrictions at any time, while the rest is equally divided into two groups and goes on successive periods of normal activity and lockdown, each one with a duration of τ days. We also implement a random testing strategy with a threshold over the population. We found that τ=7 is a good choice for the quarantine strategy since it reduces the infected population and, conveniently, it suits a weekly schedule. Focusing on the health system, projecting from the situation as of September 30, we foresee a difficulty to avoid saturation of the available ICU, given the extremely low levels of mobility that would be required. In the worst case, our model estimates that four thousand deaths would occur, of which 30% could be avoided with proper medical attention. Nonetheless, we found that aggressive testing would allow an increase in the percentage of people that can circulate without restrictions, and the medical facilities to deal with the additional critical patients would be relatively low.

COVID-19 pandemic in Africa’s island nations during the first 9 months: a descriptive study of variation in patterns of infection, severe disease, and response measures

The geographic and economic characteristics unique to island nations create a different set of conditions for, and responses to, the spread of a pandemic compared with those of mainland countries. Here, we aimed to describe the initial period of the COVID-19 pandemic, along with the potential conditions and responses affecting variation in the burden of infections and severe disease burden, across the six island nations of the WHO’s Africa region: Cabo Verde, Comoros, Madagascar, Mauritius, São Tomé e Príncipe and Seychelles. We analysed the publicly available COVID-19 data on confirmed cases and deaths from the beginning of the pandemic through 29 November 2020. To understand variation in the course of the pandemic in these nations, we explored differences in their economic statuses, healthcare expenditures and facilities, age and sex distributions, leading health risk factors, densities of the overall and urban populations and the main industries in these countries. We also reviewed the non-pharmaceutical response measures implemented nationally. We found that the burden of SARS-CoV-2 infection was reduced by strict early limitations on movement and biased towards nations where detection capacity was higher, while the burden of severe COVID-19 was skewed towards countries that invested less in healthcare and those that had older populations and greater prevalence of key underlying health risk factors. These findings highlight the need for Africa’s island nations to invest more in healthcare and in local testing capacity to reduce the need for reliance on border closures that have dire consequences for their economies.

Epidemiological characteristics of imported respiratory infectious diseases in China, 2014‒2018

Background

With the progress of globalization, international mobility increases, greatly facilitating cross-border transmission of respiratory infectious diseases (RIDs). This study aimed to analyze the epidemiological characteristics and factors influencing imported RIDs, with the goal of providing evidence to support adoption of high-tech, intelligent methods to early find imported RIDs and prevent their spread in China.

Methods

We obtained data of imported RIDs cases from 2014 to 2018 from the Inbound Sentinel Network of Customs and the National Notifiable Diseases Reporting System in China. We analyzed spatial, temporal, and population distribution characteristics of the imported RIDs. We developed an index to describe seasonality. Pearson correlation coefficients were used to examine associations between independent variables and imported cases. Data analyses and visualizations were conducted with R software.

Results

From a total of 1 409 265 253 inbound travelers, 31 732 (2.25/100 000) imported RIDs cases were reported. RIDs cases were imported from 142 countries and five continents. The incidence of imported RIDs was nearly 5 times higher in 2018 (2.81/100 000) than in 2014 (0.58/100 000). Among foreigners, incidence rates were higher among males (5.32/100 000), 0–14-year-olds (15.15/100 000), and cases originating in Oceania (11.10/100 000). The vast majority (90.3%) of imported RIDs were influenza, with seasonality consistent with annual seasonality of influenza. The spatial distribution of imported RIDs was different between Chinese citizens and foreigners. Increases in inbound travel volume and the number of influenza cases in source countries were associated with the number of imported RIDs.

Conclusions

Our study documented importation of RIDs into China from 142 countries. Inbound travel poses a significant risks bringing important RIDs to China. It is urgent to strengthen surveillance at customs of inbound travelers and establish an intelligent surveillance and early warning system to prevent importation of RIDs to China for preventing further spread within China.

Graphical Abstract

Prevention and Control Measures for Imported SARS-CoV-2 Transmission During the Postpandemic Period in Shenzhen, China

In China, most cities have gradually controlled the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and brought coronavirus disease 2019 (COVID-19) under control locally. This means that crucial work has shifted from internal management of the pandemic to external prevention and control, especially management of international travelers and imported goods. There is much uncertainty about variants of concern for SARS-CoV-2, which pose challenges to the steady resumption of social and economic life once the mutant strains begin to spread. The sporadic outbreaks of COVID-19 in different provinces of China caused by these mutant strains emphasizes the need for both prevention and control measures. Therefore, we introduce China's experience with preventing and controlling COVID-19 in the postpandemic period, which may serve as a reference in various settings.

SARS-CoV-2 detection among international air travellers to Ghana during mandatory quarantine

Objectives

To determine the prevalence of SARS-CoV-2 detection among international travellers to Ghana during mandatory quarantine.

Design

A retrospective cross-sectional study.

Setting

Air travellers to Ghana on 21^st and 22^nd March 2020.

Participants

On 21^st and 22^nd March 2020, a total of 1,030 returning international travellers were mandatorily quarantined in 15 different hotels in Accra and tested for SARS-CoV-2. All of these persons were included in the study.

Main outcome measure

Positivity for SARS-CoV-2 by polymerase chain reaction.

Results

The initial testing at the beginning of quarantine found 79 (7.7%) individuals to be positive for SARS-CoV-2. In the exit screening after 12 to 13 days of quarantine, it was discovered that 26 of those who tested negative for SARS-CoV-2 in the initial screening subsequently tested positive.

Conclusions

Ghana likely averted an early community spread of COVID-19 through the proactive approach to quarantine international travellers during the early phase of the pandemic.

Funding

None

SARS-CoV-2 screening strategies for returning international travellers: Evaluation of a rapid antigen test approach

Background

International travel poses the risk of importing SARS-CoV-2 infections and introducing new viral variants into the country of destination. Established measures include mandatory quarantine with the opportunity to abbreviate it with a negative rapid antigen test (RAT).

Methods

A total of 1,488 returnees were tested for SARS-CoV-2 with both PCR and RAT no earlier than 5 days after arrival. We assessed the sensitivity and specificity of the RAT. Positive samples were evaluated for infectivity in vitro in a cell culture outgrowth assay. We tracked if participants who tested negative were reported positive within 2 weeks of the initial test.

Results

Potential infectiousness was determined based on symptom onset analysis, resulting in a sensitivity of the antigen test of 89% in terms of infectivity. The specificity was 100%. All positive outgrowth assays were preceded by a positive RAT, indicating that all participants with proven in vitro infectivity were correctly identified. None of the negative participants tested positive during the follow-up.

Conclusions

RAT no earlier than the 5th day after arrival was a reliable method for detecting infectious travellers and can be recommended as an appropriate method for managing SARS-CoV-2 travel restrictions. Compliance to the regulations and a high standard of test quality must be ensured.

How social distancing, mobility, and preventive policies affect COVID-19 outcomes: Big data-driven evidence from the District of Columbia-Maryland-Virginia (DMV) megaregion

Many factors play a role in outcomes of an emerging highly contagious disease such as COVID-19. Identification and better understanding of these factors are critical in planning and implementation of effective response strategies during such public health crises. The objective of this study is to examine the impact of factors related to social distancing, human mobility, enforcement strategies, hospital capacity, and testing capacity on COVID-19 outcomes within counties located in District of Columbia as well as the states of Maryland and Virginia. Longitudinal data have been used in the analysis to model county-level COVID-19 infection and mortality rates. These data include big location-based service data, which were collected from anonymized mobile devices and characterize various social distancing and human mobility measures within the study area during the pandemic. The results provide empirical evidence that lower rates of COVID-19 infection and mortality are linked with increased levels of social distancing and reduced levels of travel—particularly by public transit modes. Other preventive strategies and polices also prove to be influential in COVID-19 outcomes. Most notably, lower COVID-19 infection and mortality rates are linked with stricter enforcement policies and more severe penalties for violating stay-at-home orders. Further, policies that allow gradual relaxation of social distancing measures and travel restrictions as well as those requiring usage of a face mask are related to lower rates of COVID-19 infections and deaths. Additionally, increased access to ventilators and Intensive Care Unit (ICU) beds, which represent hospital capacity, are linked with lower COVID-19 mortality rates. On the other hand, gaps in testing capacity are related to higher rates of COVID-19 infection. The results also provide empirical evidence for reports suggesting that certain minority groups such as African Americans and Hispanics are disproportionately affected by the COVID-19 pandemic.

Construct validation of the COVID-19 Cavalier Scale: Analysis of indirect effects with optimism on likelihood to travel

COVID-19 is a highly contagious disease that killed hundreds of thousands of people and crippled the tourism industry. Despite potential death, many people resumed life as if there was no pandemic. The obscure nature of diseases and overly optimistic beliefs about personal health fostered a unique COVID-19 cavalier phenomenon. These people professed, "It's just like the flu." Many engaged in passive (e.g., ignoring mask policies) and active (e.g., COVID parties) behaviors that risked exposure, believing it will generate safe immunity. The COVID-19 cavalier believe they are invulnerable to major adverse complications and communal exposure results in immunity. Identifying and understanding caviler individuals will help control the spread of diseases and reopen society for tourism. The design and validation of the 9-item COVID-19 cavalier scale (CCS) provided a tool for researchers to study these individuals. The economical measure demonstrated discriminant validity with practical public health traveling implications.

Quarantine and testing strategies to ameliorate transmission due to travel during the COVID-19 pandemic: a modelling study

BACKGROUND

Numerous countries have imposed strict travel restrictions during the COVID-19 pandemic, contributing to a large socioeconomic burden. The long quarantines that have been applied to contacts of cases may be excessive for travel policy.

METHODS

We developed an approach to evaluate imminent countrywide COVID-19 infections after 0-14-day quarantine and testing. We identified the minimum travel quarantine duration such that the infection rate within the destination country did not increase compared to a travel ban, defining this minimum quarantine as "sufficient."

FINDINGS

We present a generalised analytical framework and a specific case study of the epidemic situation on November 21, 2021, for application to 26 European countries. For most origin-destination country pairs, a three-day or shorter quarantine with RT-PCR or antigen testing on exit suffices. Adaptation to the European Union traffic-light risk stratification provided a simplified policy tool. Our analytical approach provides guidance for travel policy during all phases of pandemic diseases.

INTERPRETATION

For nearly half of origin-destination country pairs analysed, travel can be permitted in the absence of quarantine and testing. For the majority of pairs requiring controls, a short quarantine with testing could be as effective as a complete travel ban. The estimated travel quarantine durations are substantially shorter than those specified for traced contacts.

FUNDING

EasyJet (JPT and APG), the Elihu endowment (JPT), the Burnett and Stender families' endowment (APG), the Notsew Orm Sands Foundation (JPT and APG), the National Institutes of Health (MCF), Canadian Institutes of Health Research (SMM) and Natural Sciences and Engineering Research Council of Canada EIDM-MfPH (SMM).

The Impact of Quarantine and Medical Resources on the Control of COVID-19 in Wuhan based on a Household Model

In order to understand how Wuhan curbed the COVID-19 outbreak in 2020, we build a network transmission model of 123 dimensions incorporating the impact of quarantine and medical resources as well as household transmission. Using our new model, the final infection size of Wuhan is predicted to be 50,662 (95%CI: 46,234, 55,493), and the epidemic would last until April 25 (95%CI: April 23, April 29), which are consistent with the actual situation. It is shown that quarantining close contacts greatly reduces the final size and shorten the epidemic duration. The opening of Fangcang shelter hospitals reduces the final size by about 17,000. Had the number of hospital beds been sufficient when the lockdown started, the number of deaths would have been reduced by at least 54.26%. We also investigate the distribution of infectious individuals in unquarantined households of different sizes. The high-risk households are those with size from two to four before the peak time, while the households with only one member have the highest risk after the peak time. Our findings provide a reference for the prevention, mitigation and control of COVID-19 in other cities of the world.

Genomic assessment of quarantine measures to prevent SARS-CoV-2 importation and transmission

Mitigation of SARS-CoV-2 transmission from international travel is a priority. We evaluated the effectiveness of travellers being required to quarantine for 14-days on return to England in Summer 2020. We identified 4,207 travel-related SARS-CoV-2 cases and their contacts, and identified 827 associated SARS-CoV-2 genomes. Overall, quarantine was associated with a lower rate of contacts, and the impact of quarantine was greatest in the 16-20 age-group. 186 SARS-CoV-2 genomes were sufficiently unique to identify travel-related clusters. Fewer genomically-linked cases were observed for index cases who returned from countries with quarantine requirement compared to countries with no quarantine requirement. This difference was explained by fewer importation events per identified genome for these cases, as opposed to fewer onward contacts per case. Overall, our study demonstrates that a 14-day quarantine period reduces, but does not completely eliminate, the onward transmission of imported cases, mainly by dissuading travel to countries with a quarantine requirement.

Drivers and forecasts of multiple waves of the coronavirus disease 2019 pandemic: a systematic analysis based on an interpretable machine learning framework

Coronavirus disease 2019 (COVID-19) has become a global pandemic and continues to prevail with multiple rebound waves in many countries. The driving factors for the spread of COVID-19 and their quantitative contributions, especially to rebound waves, are not well studied. Multidimensional time-series data, including policy, travel, medical, socioeconomic, environmental, mutant and vaccine related data, were collected from 39 countries up to June 30, 2021, and an interpretable machine learning framework (XGBoost model with Shapley Additive explanation interpretation) was used to systematically analyze the effect of multiple factors on the spread of COVID-19, using the daily effective reproduction number as an indicator. Based on a model of the pre-vaccine era, policy-related factors were shown to be the main drivers of the spread of COVID-19, with a contribution of 60.81%. In the post-vaccine era, the contribution of policy-related factors decreased to 28.34%, accompanied with an increase in the contribution of travel-related factors, such as domestic flights, and contributions emerged for mutant-related (16.49%) and vaccine-related (7.06%) factors. For single-peak countries, the dominant ones were policy-related factors during both the rising and fading stages, with overall contributions of 33.7% and 37.7%, respectively. For double-peak countries, factors from the rebound stage contributed 45.8% and policy-related factors showed the greatest contribution in both the rebound (32.6%) and fading (25.0%) stages. For multiple-peak countries, the Delta variant, domestic flights (current month) and the daily vaccination population are the three greatest contributors (8.12%, 7.59% and 7.26%, respectively). Forecasting models to predict the rebound risk were built based on these findings, with accuracies of 0.78 and 0.81 for the pre- and post-vaccine eras, respectively. These findings quantitatively demonstrate the systematic drivers of the spread of COVID-19, and the framework proposed in this study will facilitate the targeted prevention and control of the ongoing COVID-19 pandemic. This article is protected by copyright. All rights reserved.

Optical imaging spectroscopy for rapid, primary screening of SARS-CoV-2: a proof of concept

Effective testing is essential to control the coronavirus disease 2019 (COVID-19) transmission. Here we report a-proof-of-concept study on hyperspectral image analysis in the visible and near-infrared range for primary screening at the point-of-care of SARS-CoV-2. We apply spectral feature descriptors, partial least square-discriminant analysis, and artificial intelligence to extract information from optical diffuse reflectance measurements from 5 µL fluid samples at pixel, droplet, and patient levels. We discern preparations of engineered lentiviral particles pseudotyped with the spike protein of the SARS-CoV-2 from those with the G protein of the vesicular stomatitis virus in saline solution and artificial saliva. We report a quantitative analysis of 72 samples of nasopharyngeal exudate in a range of SARS-CoV-2 viral loads, and a descriptive study of another 32 fresh human saliva samples. Sensitivity for classification of exudates was 100% with peak specificity of 87.5% for discernment from PCR-negative but symptomatic cases. Proposed technology is reagent-free, fast, and scalable, and could substantially reduce the number of molecular tests currently required for COVID-19 mass screening strategies even in resource-limited settings.

A combined model for COVID-19 pandemic control: The application of Haddon's matrix and community risk reduction tools combined

INTRODUCTION

To mitigate morbidity, mortality, and impacts of COVID-19 on health, it was essential to implement a comprehensive framework for COVID-19 control and prevention. A well-recognized tool from the field of injury prevention known as the Haddon matrix was utilized. The matrix states that any accident is affected by the host, agent, and environment. Another well-recognized tool used by the national fire protection association known as the Community risk reduction tool (CRR). The (CRR) tool utilizes the Five E's of Community Risk Reduction.

AIM OF THE STUDY

To describe the risk factors that increase the susceptibility and the severity of COVID-19 infection based on the Haddon matrix and the proposed prevention strategies by the CRR tool by using the combined model.

METHODOLOGY

We reviewed the literature to assess known factors contributing to COVID-19 susceptibility, infection, and severity of infection. We then used the Haddon matrix to structure, separating human factors from technical and environmental details and timing. We then used the community risk reduction (CRR) model to set all responses and control measures for each element obtained from the Haddon matrix tool. Subsequently, we incorporated both tools to develop the combined model.

CONCLUSION

we proposed and implemented a combined model that utilizes the CRR model as the systematic strategy for the more theoretical framework of Haddon's matrix. Combining both models was practical and helpful in planning the preparedness and control of the COVID-19 pandemic in Saudi Arabia that can be generalized to national and international levels.

Dealing with impact of COVID-19 on transportation in a developing country: Insights and policy recommendations

While developed nations have established policy frameworks for dealing with various macroeconomic shocks, developing countries respond to the influx of COVID-19 on heterogeneous scales, borne out of varying institutional bottlenecks. These inadequate transport facilities are not diversified enough to deal with an impending public health crisis. With the growing divergence in public transport management procedures and societal responses and willingness to adjust to a "new normal" transport procedures in time of COVID-19 and post-pandemic, it becomes expedient to learn evidence-based policy responses to transport service delivery. Qualitative data from semi-structured interviews with commuters and operators were thematically analysed to understand the impact of COVID-19 on transportation in Lagos Nigeria. The analysis revealed that increased cost of transportation, financial sustainability, changes in travel needs and loss of revenue were the significant impacts of the pandemic. This study contributes such that transport stakeholders can better understand how to navigate their transportation needs at this time of global uncertainty. The understanding of these impacts advances policy recommendations that are most inclined to the development objectives of developing nations in the time of COVID-19 and beyond. The limitations and suggestions for further research were discussed.

Combined anti-SARS-CoV-2 IgA, IgG, and IgM Detection as a Better Strategy to Prevent Second Infection Spreading Waves

Coronavirus disease (COVID-19) is challenging many health, economic, and social systems. RT-PCR assays are diagnosis gold standard; however, they can lead to false-negative results. Therefore, anti-SARS-CoV-2 IgG, IgM, and IgA investigation can play a complementary role in assessing the individuals immune status. Majority of serological tests focus on IgM and IgG although IgA are the main immunoglobulins involved in mucosal immunity. It has been reported that digestive symptoms may occur in the absence of any typical respiratory symptom. Thus, a complete screening, comprising IgA, IgM, and IgG detection could be more consistent and useful in patients with atypical symptoms or in paucisymptomatic cases. Current literature describes over 200 immunoassays available worldwide, pointing out a great results variability, depending on methodology or antigens' nature. In our study we evaluated anti-SARS-CoV-2 IgA, IgM, and IgG trend on a control group and on two COVID-19 patient groups (early and late infection time) with a lateral-flow combined immunoassay (LFIA) and an enzyme-linked immunosorbent assay (ELISA). Dissimilar antibodies time kinetics have been described in COVID-19 (decreasing IgM concentration with IgA/IgG persistence for a longer time; as well as persistent IgA, IgG, and IgM concentration); our results confirmed both of them depending on the methodology; therefore, it is difficult to compare different studies outcomes, suggesting the importance of a serological tests international standardization. Nevertheless, we propose a flowchart with combined anti-SARS-CoV-2 IgG/IgM/IgA detection as a screening on general population, where serological positivity should be considered as an "alert," to avoid and contain possible new outbreaks.

Balancing the Freedom-Security Trade-Off During Crises and Disasters

During crises and disasters, such as hurricanes, terrorist threats, or pandemics, policymakers must often increase security at the cost of freedom. Psychological science, however, has shown that the restriction of freedom may have strong negative consequences for behavior and health. We suggest that psychology can inform policy both by elucidating some negative consequences of lost freedom (e.g., depression or behavioral reactance) and by revealing strategies to address them. We propose four interlocking principles that can help policymakers restore the freedom-security balance. Careful consideration of the psychology of freedom can help policymakers develop policies that most effectively promote public health, safety, and well-being when crises and disasters strike.

Travel Bubbles in Air Transportation: Myth or Reality?

Aviation has been hit hard by COVID-19, with passengers stranded in remote destinations, airlines filing for bankruptcy, and uncertain demand scenarios for the future. Travel bubbles are discussed as one possible solution, meaning countries which have successfully constrained the spread of COVID-19 gradually increase their mutual international flights, returning to a degree of normality. This study aims to answer the question of whether travel bubbles are indeed observable in flight data for the year 2020. We take the year 2019 as reference and then search for anomalies in countries’ flight bans and recoveries, which could possibly be explained by having successfully implemented a travel bubble. To the best of our knowledge, this study is the first to try to address the identification of COVID-19 travel bubbles in real data. Our methodology and findings lead to several important insights regarding policy making, problems associated with the concept of travel bubbles, and raise interesting avenues for future research.

Using artificial intelligence technology to fight COVID-19: a review

In late December 2019, a new type of coronavirus was discovered, which was later named severe acute respiratory syndrome coronavirus 2(SARS-CoV-2). Since its discovery, the virus has spread globally, with 2,975,875 deaths as of 15 April 2021, and has had a huge impact on our health systems and economy. How to suppress the continued spread of new coronary pneumonia is the main task of many scientists and researchers. The introduction of artificial intelligence technology has provided a huge contribution to the suppression of the new coronavirus. This article discusses the main application of artificial intelligence technology in the suppression of coronavirus from three major aspects of identification, prediction, and development through a large amount of literature research, and puts forward the current main challenges and possible development directions. The results show that it is an effective measure to combine artificial intelligence technology with a variety of new technologies to predict and identify COVID-19 patients.

Associations between mobility and socio-economic indicators vary across the timeline of the Covid-19 pandemic

Covid-19 interventions are greatly affecting patterns of human mobility. Changes in mobility during Covid-19 have differed across socio-economic gradients during the first wave. We use fine-scale network mobility data in Ontario, Canada to study the association between three different mobility measures and four socio-economic indicators throughout the first and second wave of Covid-19 (January to December 2020). We find strong associations between mobility and the socio-economic indicators and that relationships between mobility and other socio-economic indicators vary over time. We further demonstrate that understanding how mobility has changed in response to Covid-19 varies considerably depending on how mobility is measured. Our findings have important implications for understanding how mobility data should be used to study interventions across space and time. Our results support that Covid-19 non-pharmaceutical interventions have resulted in geographically disparate responses to mobility and quantifying mobility changes at fine geographical scales is crucial to understanding the impacts of Covid-19.

Epidemic versus economic performances of the COVID-19 lockdown: A big data driven analysis

Lockdown measures have been a "panacea" for pandemic control but also a violent "poison" for economies. Lockdown policies strongly restrict human mobility but mobility reduce does harm to economics. Governments meet a thorny problem in balancing the pros and cons of lockdown policies, but lack comprehensive and quantified guides. Based on millions of financial transaction records, and billions of mobility data, we tracked spatio-temporal business networks and human daily mobility, then proposed a high-resolution two-sided framework to assess the epidemiological performance and economic damage of different lockdown policies. We found that the pandemic duration under the strictest lockdown is less about two months than that under the lightest lockdown, which makes the strictest lockdown characterize both epidemiologically and economically efficient. Moreover, based on the two-sided model, we explored the spatial lockdown strategy. We argue that cutting off intercity commuting is significant in both epidemiological and economical aspects, and finally helped governments figure out the Pareto optimal solution set of lockdown strategy.

JUE Insight: Understanding spatial variation in COVID-19 across the United States

What factors explain spatial variation in the severity of COVID-19 across the United States? To answer this question, we analyze the correlates of COVID-19 cases and deaths across US counties. We document four sets of facts. First, effective density is an important and persistent determinant of COVID-19 severity. Second, counties with more nursing home residents, lower income, higher poverty rates, and a greater presence of African Americans and Hispanics are disproportionately impacted, and these effects show no sign of disappearing over time. Third, the effect of certain characteristics, such as the distance to major international airports and the share of elderly individuals, dies out over time. Fourth, Trump-leaning counties are less severely affected early on, but later suffer from a large severity penalty.

International travel in times of the COVID-19 pandemic: The case of German school breaks

The COVID-19 pandemic has triggered severe global restrictions on international travel with the intention of limiting the spread of SARS-CoV-2 across countries. This paper studies the causal effect of the partial relaxation of these travel restrictions in Europe on the COVID-19 incidence in Germany during the summer months of 2020. It exploits the staggered start of the summer school breaks across German states as an exogenous shock to the travel opportunities of the population. While the school breaks also increased mobility within Germany, the event-study type regressions precisely control for domestic mobility and local COVID-19-related restrictions. The intention-to-treat effects of the relaxed travel restrictions show a significant and sizable increase of the COVID-19 incidence in German counties during the later weeks of the school breaks. Part of the increase can be attributed to a mandatory testing regime for travel returnees from high-incidence areas.

“Novel 2019 Coronavirus Outbreak” through the Eyes of GNSS Signal

Besides the global crisis of the novel COVID-19 outbreak, we have presented the other side towards an environmental perspective. Due to the economic shutdown of major cities, the novel COVID-19 outbreak has significantly influenced air quality in the atmosphere and also affected the tropospheric refraction on Global Navigation Satellite System GNSS signal propagation in the horizontally stratified column. We suggest that GNSS signal propagation and variation in Zenith Tropospheric Delay (ZTD) in the tropospheric column can be used as a proxy for the pollution-monitoring tool in the future. Although we have presented a case study from mainland China, the hypothesis can be tested globally.

Evaluation of Factors to Respond to the COVID-19 Pandemic Using DEMATEL and Fuzzy Rule-Based Techniques

Since social and environmental conditions have changed dramatically in recent years, the spectrum of diseases caused by infections is also evolving rapidly. The outspread of COVID-19 has resulted in an emergency situation across the globe with significant effects on the population’s lives, families, and societies, leading to concerns the World Health Organization. Accordingly, the virus has substantially threatened the Malaysians’ public health and contributed considerably to increased healthcare expenses. Since the novel coronavirus was found in China, Malaysia’s government has started its actions according to the World Health Organization procedures and concentrated on addressing and preventing the spread of the infection. The present paper aims to find and evaluate the factors to respond to the COVID-19 outbreak in Malaysia, limiting the outspread of the disease in this country. This study used the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Fuzzy Rule-Based techniques to evaluate the factors through a set of questionnaires completed by the health care professionals. According to the data analysis results, movement control order, international travel restrictions, and the mass gathering cancellations were of most importance in the prevention of COVID-19 infections transmission.

JUE Insight: Understanding spatial variation in COVID-19 across the United States

What factors explain spatial variation in the severity of COVID-19 across the United States? To answer this question, we analyze the correlates of COVID-19 cases and deaths across US counties. We document four sets of facts. First, effective density is an important and persistent determinant of COVID-19 severity. Second, counties with more nursing home residents, lower income, higher poverty rates, and a greater presence of African Americans and Hispanics are disproportionately impacted, and these effects show no sign of disappearing over time. Third, the effect of certain characteristics, such as the distance to major international airports and the share of elderly individuals, dies out over time. Fourth, Trump-leaning counties are less severely affected early on, but later suffer from a large severity penalty.