This work presents simulation results for different mitigation and confinement scenarios for the propagation of COVID-19 in the metropolitan area of Madrid. These scenarios were implemented and tested using EpiGraph, an epidemic simulator which has been extended to simulate COVID-19 propagation. EpiGraph implements a social interaction model, which realistically captures a large number of characteristics of individuals and groups, as well as their individual interconnections, which are extracted from connection patterns in social networks. Besides the epidemiological and social interaction components, it also models people's short and long-distance movements as part of a transportation model. These features, together with the capacity to simulate scenarios with millions of individuals and apply different contention and mitigation measures, gives EpiGraph the potential to reproduce the COVID-19 evolution and study medium-term effects of the virus when applying mitigation methods. EpiGraph, obtains closely aligned infected and death curves related to the first wave in the Madrid metropolitan area, achieving similar seroprevalence values. We also show that selective lockdown for people over 60 would reduce the number of deaths. In addition, evaluate the effect of the use of face masks after the first wave, which shows that the percentage of people that comply with mask use is a crucial factor for mitigating the infection's spread.
As long as critical levels of vaccination have not been reached to ensure heard immunity, and new SARS-CoV-2 strains are developing, the only realistic way to reduce the infection speed in a population is to track the infected individuals before they pass on the virus. Testing the population via sampling has shown good results in slowing the epidemic spread. Sampling can be implemented at different times during the epidemic and may be done either per individual or for combined groups of people at a time. The work we present here makes two main contributions. We first extend and refine our scalable agent-based COVID-19 simulator to incorporate an improved socio-demographic model which considers professions, as well as a more realistic population mixing model based on contact matrices per country. These extensions are necessary to develop and test various sampling strategies in a scenario including the 62 largest cities in Spain; this is our second contribution. As part of the evaluation, we also analyze the impact of different parameters, such as testing frequency, quarantine time, percentage of quarantine breakers, or group testing, on sampling efficacy. Our results show that the most effective strategies are pooling, rapid antigen test campaigns, and requiring negative testing for access to public areas. The effectiveness of all these strategies can be greatly increased by reducing the number of contacts for infected individual.
BackgroundThis work analyses the impact of different vaccination strategies on the propagation of COVID-19 within the Madrid metropolitan area starting the 27th of December 2020 and ending in the Summer of 2021. The predictions are based on simulation using EpiGraph, an agent-based COVID-19 simulator.MethodsWe briefly summarize the different interconnected models of EpiGraph and then we provide a comprehensive description of the vaccination model. We evaluate different vaccination strategies, and we validate the simulator by comparing the simulation results with real data from the metropolitan area of Madrid during the third wave.ResultsWe consider the different COVID-19 propagation scenarios on a social environment consisting of the ten largest cities in the Madrid metropolitan area, with 5 million individuals. The results show that the strategy that fares best is to vaccinate the elderly first with the two doses spaced 56 days apart; this approach reduces the final infection rate and the number of deaths by an additional 6% and 3% with respect to vaccinating the elderly first at the interval between doses recommended by the vaccine producer.ConclusionResults show that prioritizing the vaccination of young individuals would significantly increase the number of deaths. On the other hand, spacing out the first and second dose by 56 days would result in a slight reduction in the number of infections and deaths. The reason is the increase in the number of vaccinated individuals at any time during the simulation.
Introduction.-Une consultation dédiée aux professionnels de santé symptomatiques a été ouverte au début de l'épidémie de COVID-19, afin de répondre aux besoins spécifiques de cette population. L'objectif de ce travail était d'estimer la fréquence du portage nasopharyngé du SARS-Cov-2 chez les personnels de santé symptomatiques suspects de COVID-19, et de déterminer les facteurs associés à ce portage. Méthodes.-Étude descriptive des caractéristiques cliniques et épidémiologiques des consultants, conduite du 5 mars au 17 avril 2020. Le recueil des données cliniques et des résultats du test RT-PCR a été conduit à l'aide de formulaires standardisés. Résultats.-Des 522 consultants, 308 exerçaient à l'Hôpital et 214 à l'extérieur. Ils avaient des formes bénignes de COVID-19 et des signes cliniques non spécifiques à l'exception de l'agueusie/anosmie, significativement plus fréquente chez ceux avec RT-PCR positive. Le taux de positivité de la RT-PCR était globalement de 38 %, sans différence significative selon la profession, supérieur chez les consultants extérieurs (47 % versus 31 %). À l'hôpital, ce taux était significativement moindre pour les personnels symptomatiques des secteurs de soins, comparé aux personnels des plateaux techniques et laboratoires (24 %, versus 45 %, p = 0,006 et 54 %, p b 0,001, respectivement), mais ne différait pas entre personnels des unités COVID et des autres secteurs de soins (30 % versus 28 %). Parmi les consultants extérieurs, les taux de positivité des personnels des EHPAD et des libéraux (53 % et 55 % respectivement) étaient plus du double de celui du personnel soignant hospitalier (24 %, p b 0,001). Conclusions.-Ces données confirment l'impact fort du COVID-19 sur les professionnels de santé. Les taux de positivité plus élevés chez les professionnels symptomatiques exerçant en dehors de l'hôpital, comparativement à ceux exerçant à l'hôpital, pourraient s'expliquer en partie par une pénurie en équipements de protection et par des difficultés d'accès au diagnostic virologique, qui étaient plus importants en dehors de l'hôpital quand l'épidémie a commencé.
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