Netflix's communication strategy on Twitter and Instagram during the unlock in Spain: humour, proximity and information

The Covid-19 pandemic and the arrival of Disney + marked the second quarter of 2020 in the Spanish audiovisual market. Thus, the period of home confinement among the Spanish population coincided with the irruption of the new streaming service of one of the best-known and most loved brands worldwide. However, Netflix was the most consumed SVoD during this period. The objective of this research is to find out what the Californian company has done in communicative terms as a market leader and in the face of the need to adapt to the new circumstances of its audiences. The results show how Netflix Spain has integrated COVID-19 in its social media strategy in the pass between the lockdown and maximum consumption to a progressive lessening of social restrictions. The content analysis of Twitter and Instagram found 121 messages regarding pandemic (from a total of 1380). Netflix employed Twitter to connect with its audiences with humor, proximity and information, using taboos in the hardest moments, and an increased frequency of publications as the health situation improved. On the contrary, on Instagram there was no specific strategy, but imitation of the practices on Twitter and scarce references to COVID. Besides, there has been an evolution of the messages more or less parallel to the public health changes, choosing a strategy of proximity with the users, and with a communication closer to an influencer rather than a company. Copyright © 2022 (Fernández-Gómez, Martín-Quevedo, Feijoo Fernández).

"Stay nearby or get checked": A Covid-19 control strategy.

This paper repurposes the classic insight from network theory that long-distance connections drive disease propagation into a strategy for controlling a second wave of Covid-19. We simulate a scenario in which a lockdown is first imposed on a population and then partly lifted while long-range transmission is kept at a minimum. Simulated spreading patterns resemble contemporary distributions of Covid- 19 across EU member states, German and Italian regions, and through New York City, providing some model validation. Results suggest that our proposed strategy may significantly reduce peak infection. We also find that post-lockdown flare-ups remain local longer, aiding geographical containment. These results suggest a tailored policy in which individuals who frequently travel to places where they interact with many people are offered greater protection, tracked more closely, and are regularly tested. This policy can be communicated to the general public as a simple and reasonable principle: Stay nearby or get checked.

A simple tool for comparing benefits and 'costs' of COVID-19 exit strategies.

BACKGROUND: Governments and health policymakers are now looking for strategies to lift the COVID-19 lockdown, while reducing risk to the public. METHODS: We propose the population attributable risk (PAR) as an established epidemiological tool that could support decision-making through quickly estimating the main benefits and costs of various exit strategies. RESULTS: We demonstrate the feasibility of use of PAR using pandemic data, that were publicly available in mid-May 2020 from Scotland and the US, to estimate the proportion of COVID-19 hospital admissions which might be avoided, and the proportion of adverse labour market effects - for various scenarios - based on maintaining the lockdown for those of certain ages with and without comorbidities. CONCLUSION: These calculations could be refined and applied in different countries to inform important COVID-19 policy decisions, using routinely collected data.

Health equity considerations in COVID-19: geospatial network analysis of the COVID-19 outbreak in the migrant population in Singapore.

BACKGROUND: Low-wage dormitory-dwelling migrant workers in Singapore were disproportionately affected by coronavirus disease 2019 (COVID-19) infection. This was attributed to communal living in high-density and unhygienic dormitory settings and a lack of inclusive protection systems. However, little is known about the roles of social and geospatial networks in COVID-19 transmission. The study examined the networks of non-work-related activities among migrant workers to inform the development of lockdown exit strategies and future pandemic preparedness. METHODS: A population-based survey was conducted with 509 migrant workers across the nation, and it assessed dormitory attributes, social ties, physical and mental health status, COVID-19-related variables and mobility patterns using a grid-based network questionnaire. Mobility paths from dormitories were presented based on purposes of visit. Two-mode social networks examined the structures and positions of networks between workers and visit areas with individual attributes. RESULTS: COVID-19 risk exposure was associated with the density of dormitory, social ties and visit areas. The migrant worker hub in the city centre was the most frequently visited for essential services of grocery shopping and remittance, followed by south central areas mainly for social gathering. The hub was positioned as the core with the highest degree of centrality with a cluster of workers exposed to COVID-19. CONCLUSIONS: Social and geospatial networks of migrant workers should be considered in the implementation of lockdown exit strategies while addressing the improvement of living conditions and monitoring systems. Essential services, like remittance and grocery shopping at affordable prices, need to be provided near to dormitories to minimize excess gatherings.

A quantitative framework for exploring exit strategies from the COVID-19 lockdown.

Following the highly restrictive measures adopted by many countries for combating the current pandemic, the number of individuals infected by SARS-CoV-2 and the associated number of deaths steadily decreased. This fact, together with the impossibility of maintaining the lockdown indefinitely, raises the crucial question of whether it is possible to design an exit strategy based on quantitative analysis. Guided by rigorous mathematical results, we show that this is indeed possible: we present a robust numerical algorithm which can compute the cumulative number of deaths that will occur as a result of increasing the number of contacts by a given multiple, using as input only the most reliable of all data available during the lockdown, namely the cumulative number of deaths.