A single holiday was the turning point of the COVID-19 policy of Israel

Characteristics and Motivational Factors of Whole Blood and Convalescent Plasma Donors during the SARS-CoV-2 Pandemic in Israel

Demands for whole blood (WB) and COVID-19 convalescent plasma (CCP) donations during the SARS-CoV-2 (COVID-19) pandemic presented unprecedented challenges for blood services throughout the world. This study aims to understand the motivating factors that drive WB and CCP donations in the context of the pandemic. This cross-sectional study is based on data extracted from surveys of the two volunteer donor cohorts. The findings reveal that when compared to CCP donors, WB donors were more likely to view donation as a form of social engagement (97.7% vs. 87.1%, p < 0.01), advantageous in the workplace (46.4% vs. 28.6%, p < 0.01), advantageous in their social network (58.6% vs. 47.0%, p = 0.01), and view their donation in the context of positive self-satisfaction (99% vs. 95.1%, p = 0.01). The average age of CCP donors was 7.1 years younger than those who donated WB (p < 0.01). Motivational factors were also analyzed by sex and religiosity. In conclusion, whereas both donor groups showed a high motivation to partake in these life-saving commitments, WB donors were more likely to be motivated by factors that, when better-understood and implemented in policies concerning plasma donations, may help to increase these donations.

Public holidays increased the transmission of COVID-19 in Japan, 2020-2021: a mathematical modelling study

OBJECTIVES

Although the role of specific holidays in modifying transmission dynamics of infectious diseases has received some research attention, the epidemiological impact of public holidays on the transmission of coronavirus disease 2019 (COVID-19) remains unclear.

METHODS

To assess the extent of increased transmission frequency during public holidays, we collected COVID-19 incidence and mobility data in Hokkaido, Tokyo, Aichi, and Osaka from February 15, 2020 to September 30, 2021. Models linking the estimated effective reproduction number (Rt) with raw or adjusted mobility, public holidays, and the state of emergency declaration were developed. The best-fit model included public holidays as an essential input variable, and was used to calculate counterfactuals of Rt in the absence of holidays.

RESULTS

During public holidays, on average, Rt increased by 5.71%, 3.19%, 4.84%, and 24.82% in Hokkaido, Tokyo, Aichi, and Osaka, respectively, resulting in a total increase of 580 (95% confidence interval [CI], 213 to 954), 2,209 (95% CI, 1,230 to 3,201), 1,086 (95% CI, 478 to 1,686), and 5,211 (95% CI, 4,554 to 5,867) cases that were attributable to the impact of public holidays.

CONCLUSIONS

Public holidays intensified the transmission of COVID-19, highlighting the importance of considering public holidays in designing appropriate public health and social measures in the future.

Unravelling the effect of New Year's Eve celebrations on SARS-CoV-2 transmission

Public holidays have been associated with SARS-CoV-2 incidence surges, although a firm link remains to be established. This association is sometimes attributed to events where transmissions occur at a disproportionately high rate, known as superspreading events. Here, we describe a sudden surge in new cases with the Omicron BA.1 strain amongst higher education students in Belgium. Contact tracers classed most of these cases as likely or possibly infected on New Year's Eve, indicating a direct trigger by New Year celebrations. Using a combination of contact tracing and phylogenetic data, we show the limited role of superspreading events in this surge. Finally, the numerous simultaneous transmissions allowed a unique opportunity to determine the distribution of incubation periods of the Omicron strain. Overall, our results indicate that, even under social restrictions, a surge in transmissibility of SARS-CoV-2 can occur when holiday celebrations result in small social gatherings attended simultaneously and communitywide.

Timing, extent and outcomes of public health measures in the first wave of the COVID-19 pandemic in Israel and a comparative analysis by socioeconomic indices

BACKGROUND

Early in the coronavirus disease 2019 (COVID-19) pandemic, governments implemented exceptional public health measures (PHMs) in the face of uncertainty. This study aimed to compare mitigation policies implemented by Israel and their timing in the first wave of the pandemic to those of other countries, and to assess whether country characteristics such as democracy, trust, education, economic strength and healthcare reserve were associated with decision-making.

METHODS

PHMs and pre-pandemic characteristics, using internationally accepted indices, of 50 countries were collected from 1/1/2020-30/06/2020; and associations between them were assessed. Time to implementation of these measures was compared among the Organisation for Economic Co-operation (OECD) nations. Log-rank test was used for univariate analysis. Cox regression was performed to assess the independent contribution of pre-pandemic characteristics to time-to-implementation of measures. Correlations between timing of specific measures and COVID-19 mortality at 60 days were assessed.

RESULTS

Israel ranked in the upper third of the OECD in swiftness to implementation of eight of the ten measures compared. In univariate survival analysis, countries with an education level below the OECD median were more likely to implement a lockdown (p-value = 0.043) and to close restaurants and entertainment venues (p-value = 0.007) when compared to countries above the OECD median. In Cox regression models, controlling for geographic location, democracy level above the OECD median was associated with a longer time-to-implementation of a lockdown (HR=0.35, 95% CI=0.14-0.88, p-value=0.025). Similarly, a high level of GDP per capita was inversely associated with closing schools; and a high level of education inversely associated with closure of restaurants and entertainment venues. Earlier initiation of all PHMs was associated with lower mortality at 60 days, controlling for geographic location.

CONCLUSIONS

Israel's initial response to the pandemic was relatively quick, and may have been facilitated by its geographic isolation. Countries with lower pre-pandemic socio-economic indices were quicker to initiate forced social distancing. Early initiation of PHMs was associated with reduced mortality in the short run. Timing of initiation of measures relative to the country-specific spread of disease is a significant factor contributing to short-term early local pandemic control, perhaps more than the exact measures implemented. It is important to note that this study is limited to the initial pandemic response. Furthermore, it does not take into account the broader long-term effects of certain PHMs, which should be a focus of further research.

Modeling post-holiday surge in COVID-19 cases in Pennsylvania counties

COVID-19 arrived in the United States in early 2020, with cases quickly being reported in many states including Pennsylvania. Many statistical models have been proposed to understand the trends of the COVID-19 pandemic and factors associated with increasing cases. While Poisson regression is a natural choice to model case counts, this approach fails to account for correlation due to spatial locations. Being a contagious disease and often spreading through community infections, the number of COVID-19 cases are inevitably spatially correlated as locations neighboring counties with a high COVID-19 case count are more likely to have a high case count. In this analysis, we combine generalized estimating equations (GEEs) for Poisson regression, a popular method for analyzing correlated data, with a semivariogram to model daily COVID-19 case counts in 67 Pennsylvania counties between March 20, 2020 to January 23, 2021 in order to study infection dynamics during the beginning of the pandemic. We use a semivariogram that describes the spatial correlation as a function of the distance between two counties as the working correlation. We further incorporate a zero-inflated model in our spatial GEE to accommodate excess zeros in reported cases due to logistical challenges associated with disease monitoring. By modeling time-varying holiday covariates, we estimated the effect of holiday timing on case count. Our analysis showed that the incidence rate ratio was significantly greater than one, 6-8 days after a holiday suggesting a surge in COVID-19 cases approximately one week after a holiday.

Preschool Teachers' Psychological Distress and Work Engagement during COVID-19 Outbreak: The Protective Role of Mindfulness and Emotion Regulation

COVID-19 has dramatically affected the mental health and work environment of the educational sector. Our primary aim was to investigate preschool teachers’ psychological distress and work engagement during the COVID-19 outbreak, while examining the possible protective role of participating in a mindfulness-based intervention geared to foster compassion (Call2Care-Israel for Teachers; C2C-IT) and emotion regulation. The prevalence of emotional distress, work engagement, and COVID-19 concerns were evaluated in 165 preschool teachers in the early stages of the COVID-19 outbreak in Israel through questionnaires. The findings showed that preschool teachers experienced increased emotional distress. Teachers who had participated in the C2C-IT intervention six months before the pandemic outbreak (N = 41) reported lower emotional distress, higher use of adaptive emotion regulation strategies, and higher work engagement, compared to their counterparts that had not participated in the intervention (N = 124). Emotion regulation strategies mediated the link between participating in CTC-IT intervention and emotional distress and work engagement. Teaching is a highly demanding occupation, especially during a pandemic, thus making it important to invest resources in empowering this population. The findings here suggest that the implementation of a mindfulness-based intervention during the school year can enhance teachers’ well-being, even during stressful events such as the COVID-19 pandemic.

Rapid antigen testing as a reactive response to surges in nosocomial SARS-CoV-2 outbreak risk

Healthcare facilities are vulnerable to SARS-CoV-2 introductions and subsequent nosocomial outbreaks. Antigen rapid diagnostic testing (Ag-RDT) is widely used for population screening, but its health and economic benefits as a reactive response to local surges in outbreak risk are unclear. We simulate SARS-CoV-2 transmission in a long-term care hospital with varying COVID-19 containment measures in place (social distancing, face masks, vaccination). Across scenarios, nosocomial incidence is reduced by up to 40-47% (range of means) with routine symptomatic RT-PCR testing, 59-63% with the addition of a timely round of Ag-RDT screening, and 69-75% with well-timed two-round screening. For the latter, a delay of 4-5 days between the two screening rounds is optimal for transmission prevention. Screening efficacy varies depending on test sensitivity, test type, subpopulations targeted, and community incidence. Efficiency, however, varies primarily depending on underlying outbreak risk, with health-economic benefits scaling by orders of magnitude depending on the COVID-19 containment measures in place.

Superspreading and heterogeneity in transmission of SARS, MERS, and COVID-19: A systematic review

BACKGROUND

Severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and coronavirus disease 2019 (COVID-19) have caused substantial public health burdens and global health threats. Understanding the superspreading potentials of these viruses are important for characterizing transmission patterns and informing strategic decision-making in disease control. This systematic review aimed to summarize the existing evidence on superspreading features and to compare the heterogeneity in transmission within and among various betacoronavirus epidemics of SARS, MERS and COVID-19.

METHODS

PubMed, MEDLINE, and Embase databases were extensively searched for original studies on the transmission heterogeneity of SARS, MERS, and COVID-19 published in English between January 1, 2003, and February 10, 2021. After screening the articles, we extracted data pertaining to the estimated dispersion parameter (k) which has been a commonly-used measurement for superspreading potential.

FINDINGS

We included a total of 60 estimates of transmission heterogeneity from 26 studies on outbreaks in 22 regions. The majority (90%) of the k estimates were small, with values less than 1, indicating an over-dispersed transmission pattern. The point estimates of k for SARS and MERS ranged from 0.12 to 0.20 and from 0.06 to 2.94, respectively. Among 45 estimates of individual-level transmission heterogeneity for COVID-19 from 17 articles, 91% were derived from Asian regions. The point estimates of k for COVID-19 ranged between 0.1 and 5.0.

CONCLUSIONS

We detected a substantial over-dispersed transmission pattern in all three coronaviruses, while the k estimates varied by differences in study design and public health capacity. Our findings suggested that even with a reduced R value, the epidemic still has a high resurgence potential due to transmission heterogeneity.

A nationwide analysis of population group differences in the COVID-19 epidemic in Israel, February 2020-February 2021

BACKGROUND

Social inequalities affect the COVID-19 burden and vaccine uptake. The aim of this study was to explore inequalities in the incidence and mortality rate of SARS-CoV-2 infection and vaccine uptake in various sociodemographic and population group strata in Israel.

METHODS

We analysed nationwide publicly available, aggregated data on PCR-confirmed SARS-CoV-2 infections and COVID-19 deaths between March 2020 and February 2021, as well as the first three months of COVID-19 immunisation according to sociodemographics, including population group and residential socioeconomic status (SES). We computed incidence and mortality rates of COVID-19. Comparisons between towns with predominantly Arab, ultra-Orthodox Jewish (the minorities), general Jewish populations, and according to SES, were conducted using generalised linear models with negative binomial distribution.

FINDINGS

Overall, 774,030 individuals had SARS-CoV-2 infection (cumulative incidence 84•5 per 1,000 persons) and 5687 COVID-19 patients had died (mortality rate 62•8 per 100,000 persons). The highest mortality rate was found amongst the elderly. Most (>75%) individuals aged 60 years or above have been vaccinated with BNT162b2 vaccine. The risk of SARS-CoV-2 infection was higher in towns with predominantly Arab and ultra-Orthodox Jewish populations than in the general Jewish population, and in low SES communities. COVID-19 mortality rate was highest amongst Arabs. Conversely, vaccine uptake was lower amongst Arab and ultra-Orthodox Jewish populations and low SES communities.

INTERPRETATION

Ethnic and religious minorities and low SES communities experience substantial COVID-19 burden, and have lower vaccine uptake, even in a society with universal accessibility to healthcare. Quantifying these inequalities is fundamental towards reducing these gaps, which imposes a designated apportion of resources to adequately control the pandemic.

FUNDING

No external funding was available for this study.

Impact of the COVID-19 pandemic on stress and emotional reactions in Israel: a mixed-methods study

BACKGROUND

The COVID-19 pandemic has had a profound impact worldwide. This study sought to assess the pandemic's psychological impact on the Israeli public.

METHODS

Using mixed methods we assessed Israeli adults during the COVID-19 outbreak. In the quantitative study, participants (N=1407) completed an online battery of measures assessing psychological variables and perceived threat related to COVID-19. Statistical analyses included tests for between-group differences and Pearson correlations. The qualitative study entailed in-depth, semistructured interviews conducted by telephone (N=38).

RESULTS

The quantitative findings indicate that about 48% of the public had negative emotional reactions and 20% perceived they were liable to contract the virus. Moreover, a positive correlation was found between these feelings and the degree of perceived threat. Three major themes emerged from the qualitative study: 1) a sense of shock and chaos; 2) gradual adjustment to the new reality; and 3) fears and concerns for self and family members. The study's results revealed the following sources of participants' emotional responses and sense of threat: health concerns regarding themselves and their loved ones; employment concerns; problems with children and spouses caused by being together at home; and difficulties entailed in working at home.

CONCLUSIONS

The study reveals many of the psychological variables and perceived threats related to COVID-19 in Israel. While social distancing may make people feel safer, it can also increase their feelings of isolation, stress and frustration and cause difficulties in many life situations. The findings point to the necessity of addressing the public's perceived susceptibility and emotional reactions about COVID-19.

Population Mobility Trends, Deprivation Index and the Spatio-Temporal Spread of Coronavirus Disease 2019 in Ireland

Like most countries worldwide, the coronavirus disease (COVID-19) has adversely affected Ireland. The aim of this study was to (i) investigate the spatio-temporal trend of COVID-19 incidence; (ii) describe mobility trends as measured by aggregated mobile phone records; and (iii) investigate the association between deprivation index, population density and COVID-19 cases while accounting for spatial and temporal correlation. Standardised incidence ratios of cases were calculated and mapped at a high spatial resolution (electoral division level) over time. Trends in the percentage change in mobility compared to a pre-COVID-19 period were plotted to investigate the impact of lockdown restrictions. We implemented a hierarchical Bayesian spatio-temporal model (Besag, York and Mollié (BYM)), commonly used for disease mapping, to investigate the association between covariates and the number of cases. There have been three distinct "waves" of COVID-19 cases in Ireland to date. Lockdown restrictions led to a substantial reduction in human movement, particularly during the 1st and 3rd wave. Despite adjustment for population density (incidence ratio (IR) = 1.985 (1.915-2.058)) and the average number of persons per room (IR = 10.411 (5.264-22.533)), we found an association between deprivation index and COVID-19 incidence (IR = 1.210 (CI: 1.077-1.357) for the most deprived quintile compared to the least deprived). There is a large range of spatial heterogeneity in COVID-19 cases in Ireland. The methods presented can be used to explore locally intensive surveillance with the possibility of localised lockdown measures to curb the transmission of infection, while keeping other, low-incidence areas open. Our results suggest that prioritising densely populated deprived areas (that are at increased risk of comorbidities) during vaccination rollout may capture people that are at risk of infection and, potentially, also those at increased risk of hospitalisation.

Linked transmission chains of imported SARS-CoV-2 variant B.1.351 across mainland France, January 2021

Two cases of confirmed SARS-CoV-2 infection with the B.1.351 variant were reported in France in mid-January, 2020. These cases attended a gathering in Mozambique in mid-December 2020. Investigations led to the identification of five imported cases responsible for 14 transmission chains and a total 36 cases. Epidemiological characteristics seemed comparable to those described before the emergence of the South African variant B.1.351. The lack of tertiary transmission outside of the personal sphere suggests that distancing and barrier measures were effective.

Evidence of the effectiveness of travel-related measures during the early phase of the COVID-19 pandemic: a rapid systematic review

OBJECTIVE

To review the effectiveness of travel measures implemented during the early stages of the COVID-19 pandemic to inform changes on how evidence is incorporated in the International Health Regulations (2005) (IHR).

DESIGN

We used an abbreviated Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols to identify studies that investigated the effectiveness of travel-related measures preprinted or published by 1 June 2020.

RESULTS

We identified 29 studies, of which 26 were modelled. Thirteen studies investigated international measures, while 17 investigated domestic measures (one investigated both). There was a high level of agreement that the adoption of travel measures led to important changes in the dynamics of the early phases of the COVID-19 pandemic: the Wuhan measures reduced the number of cases exported internationally by 70%-80% and led to important reductions in transmission within Mainland China. Additional travel measures, including flight restrictions to and from China, may have led to additional reductions in the number of exported cases. Few studies investigated the effectiveness of measures implemented in other contexts. Early implementation was identified as a determinant of effectiveness. Most studies of international travel measures did not account for domestic travel measures thus likely leading to biased estimates.

CONCLUSION

Travel measures played an important role in shaping the early transmission dynamics of the COVID-19 pandemic. There is an urgent need to address important evidence gaps and also a need to review how evidence is incorporated in the IHR in the early phases of a novel infectious disease outbreak.

Epidemiological model for the inhomogeneous spatial spreading of COVID-19 and other diseases

We suggest a novel mathematical framework for the in-homogeneous spatial spreading of an infectious disease in human population, with particular attention to COVID-19. Common epidemiological models, e.g., the well-known susceptible-exposed-infectious-recovered (SEIR) model, implicitly assume uniform (random) encounters between the infectious and susceptible sub-populations, resulting in homogeneous spatial distributions. However, in human population, especially under different levels of mobility restrictions, this assumption is likely to fail. Splitting the geographic region under study into areal nodes, and assuming infection kinetics within nodes and between nearest-neighbor nodes, we arrive into a continuous, "reaction-diffusion", spatial model. To account for COVID-19, the model includes five different sub-populations, in which the infectious sub-population is split into pre-symptomatic and symptomatic. Our model accounts for the spreading evolution of infectious population domains from initial epicenters, leading to different regimes of sub-exponential (e.g., power-law) growth. Importantly, we also account for the variable geographic density of the population, that can strongly enhance or suppress infection spreading. For instance, we show how weakly infected regions surrounding a densely populated area can cause rapid migration of the infection towards the populated area. Predicted infection "heat-maps" show remarkable similarity to publicly available heat-maps, e.g., from South Carolina. We further demonstrate how localized lockdown/quarantine conditions can slow down the spreading of disease from epicenters. Application of our model in different countries can provide a useful predictive tool for the authorities, in particular, for planning strong lockdown measures in localized areas-such as those underway in a few countries.

Risk and Protective Factors in the COVID-19 Pandemic: A Rapid Evidence Map

Background: Given the worldwide spread of the 2019 Novel Coronavirus (COVID-19), there is an urgent need to identify risk and protective factors and expose areas of insufficient understanding. Emerging tools, such as the Rapid Evidence Map (rEM), are being developed to systematically characterize large collections of scientific literature. We sought to generate an rEM of risk and protective factors to comprehensively inform areas that impact COVID-19 outcomes for different sub-populations in order to better protect the public. Methods: We developed a protocol that includes a study goal, study questions, a PECO statement, and a process for screening literature by combining semi-automated machine learning with the expertise of our review team. We applied this protocol to reports within the COVID-19 Open Research Dataset (CORD-19) that were published in early 2020. SWIFT-Active Screener was used to prioritize records according to pre-defined inclusion criteria. Relevant studies were categorized by risk and protective status; susceptibility category (Behavioral, Physiological, Demographic, and Environmental); and affected sub-populations. Using tagged studies, we created an rEM for COVID-19 susceptibility that reveals: (1) current lines of evidence; (2) knowledge gaps; and (3) areas that may benefit from systematic review. Results: We imported 4,330 titles and abstracts from CORD-19. After screening 3,521 of these to achieve 99% estimated recall, 217 relevant studies were identified. Most included studies concerned the impact of underlying comorbidities (Physiological); age and gender (Demographic); and social factors (Environmental) on COVID-19 outcomes. Among the relevant studies, older males with comorbidities were commonly reported to have the poorest outcomes. We noted a paucity of COVID-19 studies among children and susceptible sub-groups, including pregnant women, racial minorities, refugees/migrants, and healthcare workers, with few studies examining protective factors. Conclusion: Using rEM analysis, we synthesized the recent body of evidence related to COVID-19 risk and protective factors. The results provide a comprehensive tool for rapidly elucidating COVID-19 susceptibility patterns and identifying resource-rich/resource-poor areas of research that may benefit from future investigation as the pandemic evolves.

The basic reproduction number of SARS-CoV-2 in Wuhan is about to die out, how about the rest of the World?

The virologically confirmed cases of a new coronavirus disease (COVID-19) in the world are rapidly increasing, leading epidemiologists and mathematicians to construct transmission models that aim to predict the future course of the current pandemic. The transmissibility of a virus is measured by the basic reproduction number ( R0 ), which measures the average number of new cases generated per typical infectious case. This review highlights the articles reporting rigorous estimates and determinants of COVID-19 R0 for the most affected areas. Moreover, the mean of all estimated R0 with median and interquartile range is calculated. According to these articles, the basic reproduction number of the virus epicentre Wuhan has now declined below the important threshold value of 1.0 since the disease emerged. Ongoing modelling will inform the transmission rates seen in the new epicentres outside of China, including Italy, Iran and South Korea.