The SARS-CoV-2 pandemic has affected communities, populations, and countries throughout the world. As the SARS-CoV-2 pandemic developed, the extent to which the disease interacted with already existing endemic, non-communicable and infectious diseases became evident, hence deeply influencing health outcomes. Additionally, a synergistic effect has been demonstrated also with socio-economic, cultural, and contextual determinants of health which seem to contribute to poorer health and accumulating social disadvantages. In this essay, using as a starting point the syndemic theory that translates the cumulative and intertwined factors between different epidemics, we argue that the SARS-CoV-2 is a one health issue of a syndemic nature and that the failure to acknowledge this contributes to weakened policy-making processes and public health responses and ineffective health policies and programs.

Objectives Contact tracing and quarantine are common measures used in the management of infectious disease outbreaks. However, few studies have measured their impact on the control of the COVID-19 pandemic. This study aimed to assess the effectiveness of those measures on reducing transmission of SARS-CoV-2 in a community setting. Study Design Retrospective cohort study. Methods A retrospective cohort study of COVID-19 cases notified in Eastern Porto from March 1 st to April 30 th , 2020 was performed. Intervention and control cohorts were defined based on whether cases were subjected to contact tracing and quarantine measures before the laboratory confirmation of disease. The number of secondary cases per index case and the proportion of cases with subsequent secondary cases were the primary outcomes. Secondary outcomes included the time from symptom onset to specimen collection and the number of close contacts. The analysis was stratified according to whether national lockdown measures had already been implemented. Results The intervention and control cohorts comprised 98 and 453 cases, respectively. No differences were observed concerning primary outcomes. The intervention group had a shorter time between symptom onset and specimen collection (median: 3 days, IQR 1-6, vs. median: 5 days, IQR 2-7, p-value=0.004) and fewer close contacts (median: 0, IQR 0-2, vs. median: 2, IQR 1-4, p-value<0.001). The stratified analysis returned similar results. Conclusion Local public health measures were effective in reducing the time between symptom onset and laboratory diagnosis and the number of close contacts per case. No effect was apparent on secondary case figures, suggesting that further measures may be required.

The time and type of the States' responses to the COVID‐19 pandemic varied with the severity of the epidemiological situation, the perceived risk, the political organisation and the model of health system of the country. We discuss the response of Germany, Spain, France, Italy, Portugal and the United Kingdom during the first months of the COVID‐19 epidemic in 2020, considering the political organisation of the country and its health system model. We analyse public health measures implemented to contain or mitigate the pandemic, as well as those related to governance, resources and reorganisation of services, financing mechanisms, response of the health system itself and health outcomes. To measure the burden of COVID‐19, we use several indicators. The adoption of measures, to contain and mitigate epidemic varied in degree and time of adoption. All countries reorganised their governance structure and the provision of care, despite the differences in political models and health systems (ranging from a more unitary and centralised political organisational model—France and Portugal; to a decentralised matrix—Germany, Spain, Italy and the United Kingdom). Rather than the differences in political models and health systems, the explanation for the success in tackling the epidemic seems to lay in other social determinants of health.

Background Socioeconomic differences have been observed in the risk of acquiring infectious diseases, but evidence regarding SARS-CoV-2 remains sparse. Hence, this study aimed to investigate the association between SARS-CoV-2 infection risk and socioeconomic deprivation, exploring whether this association varied according to different phases of the national pandemic response. Methods A cross-sectional study was conducted. Data routinely collected for patients with a laboratorial result recorded in SINAVE®, between 2 March and 14 June 2020, were analysed. Socioeconomic deprivation was assessed using quintiles of the European Deprivation Index (Q1-least deprived to Q5-most deprived). Response phases were defined as before, during and after the national State of Emergency. Associations were estimated using multilevel analyses. Results The study included 223 333 individuals (14.7% were SARS-CoV-2 positive cases). SARS-CoV-2 infection prevalence ratio increased with deprivation [PR(Q1)=Ref; PR(Q2)=1.37 (95% CI 1.19–1.58), PR(Q3)=1.48 (95% CI 1.26–1.73), PR(Q4)=1.73 (95% CI 1.47–2.04), PR(Q5)=2.24 (95% CI 1.83–2.75)]. This was observed during the State of Emergency [PR(Q5)=2.09 (95% CI 1.67–2.62)] and more pronounced after the State of Emergency [PR(Q5)= 3.43 (95% CI 2.66–4.44)]. Conclusion The effect of socioeconomic deprivation in the SARS-CoV-2 infection risk emerged after the implementation of the first State of Emergency in Portugal, and became more pronounced as social distancing policies eased. Decision-makers should consider these results when deliberating future mitigation measures.

The interdependence of humans, animals, plants, and their social and abiotic environment is highlighted by past and recent pandemics. A good example to understand and tackle threats to ecosystems is the COVID-19 pandemic. A syndemic is a complex and multilevel phenomenon of epidemics interacting synergistically at individual, societal, and environmental levels. Understanding the syndemic nature of pandemics will facilitate the adoption of a One Health approach to improve planetary health. To address the eco-complexity underlying One Health issues, the development of intelligence management systems through a planetary perspective is of key importance. This requires the capacity to capture, process, and communicate data on human, animal, and plant health and well-being, and on their social and environmental determinants. The implementation of such systems will need political commitment at all levels of action, deployment of adequate resources and expertise, reliable and comprehensive data flowing pathways through interoperable, flexible, and secure data sharing systems.