Despite notable scientific and medical advances, broader political, socioeconomic and behavioural factors continue to undercut the response to the COVID-19 pandemic1,2. Here we convened, as part of this Delphi study, a diverse, multidisciplinary panel of 386 academic, health, non-governmental organization, government and other experts in COVID-19 response from 112 countries and territories to recommend specific actions to end this persistent global threat to public health. The panel developed a set of 41 consensus statements and 57 recommendations to governments, health systems, industry and other key stakeholders across six domains: communication; health systems; vaccination; prevention; treatment and care; and inequities. In the wake of nearly three years of fragmented global and national responses, it is instructive to note that three of the highest-ranked recommendations call for the adoption of whole-of-society and whole-of-government approaches1, while maintaining proven prevention measures using a vaccines-plus approach2 that employs a range of public health and financial support measures to complement vaccination. Other recommendations with at least 99% combined agreement advise governments and other stakeholders to improve communication, rebuild public trust and engage communities3 in the management of pandemic responses. The findings of the study, which have been further endorsed by 184 organizations globally, include points of unanimous agreement, as well as six recommendations with >5% disagreement, that provide health and social policy actions to address inadequacies in the pandemic response and help to bring this public health threat to an end.

We describe the early spread of the novel coronavirus (COVID-19) and the first human-to-human transmission networks, in Romania. We profiled the first 147 cases referring to sex, age, place of residence, probable country of infection, return day to Romania, COVID-19 confirmation date and the probable modes of COVID-19 transmissions. Also, we analysed human-to-human transmission networks and explored their structural features and time dynamics. In Romania, local cycles of transmission were preceded by imported cases, predominantly from Italy. We observed an average of 4.8 days (s.d. = 4.0) between the arrival to a Romanian county and COVID-19 confirmation. Furthermore, among the first 147 COVID-19 patients, 88 were imported cases (64 carriers from Italy), 54 were domestic cases, while for five cases the source of infection was unknown. The early human-to-human transmission networks illustrated a limited geographical dispersion, the presence of super-spreaders and the risk of COVID-19 nosocomial infections. COVID-19 occurred in Romania through case importation from Italy. The largest share of the Romanian diaspora is concentrated especially in the northern parts of Italy, heavily affected by COVID-19. Human mobility (including migration) accounts for the COVID-19 transmission and it should be given consideration while tailoring prevention measures.

We study to what degree and how homophily and network properties affect individual citation counts of researchers in the sociology departments of three East European countries, namely Poland, Romania, and Slovenia. We built first-order personal coauthorship networks out of the Web of Science publication records. Each sociologist is assigned as a focal node or ego, while her coauthors are alters. We analyze the data using structural measurements methods, hierarchical regression models, and we make visualizations based on the clustered graph technique. For all three populations, our results indicate that the mean score of the citations of alters substantially predicts the citation counts of egos. In particular, citation similarity increases the chances for coauthorship ties. Evidence for the impact of network properties on the citation levels of egos is mixed. For Poland, normalized ego-betweenness shows a negative effect on citation counts, while network density displays a positive one. For Romania and Slovenia, network characteristics have only a minor impact. Even if the visual summarization of the personal networks uncovers a wide palette of coauthorship patterns, homophily appears to be pervasive. These results are relevant for domestic policy makers who aim to improve the aggregated research performance in East European countries.

The current pandemic has disproportionally affected the workforce. To improve our understanding of the role that occupations play in the transmission of COVID-19, we analyse real-world network data that were collected in Bucharest between August 1st and October 31st 2020. The data record sex, age, and occupation of 6895 patients and the 13,272 people they have interacted with, thus providing a social network from an urban setting through which COVID-19 has spread. Quite remarkably, we find that medical occupations have no significant effect on the spread of the virus. Instead, we find common transmission chains to start with infected individuals who hold jobs in the private sector and are connected with non-active alters, such as spouses, siblings, or elderly relatives. We use relational hyperevent models to assess the most likely homophily and network effects in the community transmission. We detect homophily with respect to age and anti-homophily with respect to sex and employability. We note that, although additional data would be welcomed to perform more in-depth network analyses, our findings may help public authorities better target under-performing vaccination campaigns.

Experts worldwide have constantly been calling for high-quality open-access epidemiological data, given the fast-evolving nature of the COVID-19 pandemic. Disaggregated high-level granularity records are still scant despite being essential to corroborate the effectiveness of virus containment measures and even vaccination strategies. We provide a complete dataset containing disaggregated epidemiological information about all the COVID-19 patients officially reported during the first 250 days of the COVID-19 pandemic in Bucharest (Romania). We give the sex, age, and the COVID-19 infection confirmation date for 46,440 individual cases, between March 7th and November 11th, 2020. Additionally, we provide context-wise information such as the stringency levels of the measures taken by the Romanian authorities. We procured the data from the local public health authorities and systemized it to respond to the urgent international need of comparing observational data collected from various populations. Our dataset may help understand COVID-19 transmission in highly dense urban communities, perform virus spreading simulations, ascertain the effects of non-pharmaceutical interventions, and craft better vaccination strategies.