Older Europeans' health perception and their adaptive behaviour during the COVID-19 pandemic.

BACKGROUND: Although older adults are more vulnerable to the COVID-19 virus, a significant proportion of them do not follow recommended guidelines concerning preventive actions during the ongoing pandemic. This article analyses the role of biased health beliefs for adaptive health behaviour such as reduced mobility, protection in public spaces and hygiene measures, for the population aged 50 and older in 13 European countries. METHODS: Health perception is measured based on the difference between self-reported health and physical performance tests for over 24 000 individuals included in the most recent Survey of Health, Ageing and Retirement in Europe. Logistic regressions are employed to explore how over- and underestimating health are related to preventive behaviours. RESULTS: Results suggest that older adults who underestimate their health are more likely to show adaptive behaviour related to mobility reductions. In particular, they are more likely to stay at home, shop less and go for walks less often. In contrast, overestimating health is not significantly associated with reduced mobility. Protective behaviour in public spaces and adopting hygiene measures do not vary systematically between health perception groups. CONCLUSION: As health beliefs appear relevant for the adoption of preventive health behaviours related to mobility, they have serious consequences for the health and well-being of older Europeans. Although adaptive behaviour helps to contain the virus, exaggerated mobility reduction in those who underestimate their health might be contributing to the already high social isolation and loneliness of older adults during the ongoing pandemic.

Impacts of introducing and lifting nonpharmaceutical interventions on COVID-19 daily growth rate and compliance in the United States

We evaluate the impacts of implementing and lifting non-pharmaceutical interventions (NPIs) in US counties on the daily growth rate of COVID-19 cases and compliance, measured through the percentage of devices staying home, and evaluate whether introducing and lifting NPIs protecting selective populations is an effective strategy. We use difference-in-differences methods, leveraging on daily county-level data and exploit the staggered introduction and lifting of policies across counties over time. We also assess heterogenous impacts due to counties' population characteristics, namely ethnicity and household income. Results show that introducing NPIs led to a reduction in cases through the percentage of devices staying home. When counties lifted NPIs, they benefited from reduced mobility outside of the home during the lockdown, but only for a short period. In the long term, counties experienced diminished health and mobility gains accrued from previously implemented policies. Notably, we find heterogenous impacts due to population characteristics implying that measures can mitigate the disproportionate burden of COVID-19 on marginalized populations and find that selectively targeting populations may not be effective. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

Measuring geographical disparities in England at the time of COVID-19: results using a composite indicator of population vulnerability.

OBJECTIVES: The growth of COVID-19 infections in England raises questions about system vulnerability. Several factors that vary across geographies, such as age, existing disease prevalence, medical resource availability and deprivation, can trigger adverse effects on the National Health System during a pandemic. In this paper, we present data on these factors and combine them to create an index to show which areas are more exposed. This technique can help policy makers to moderate the impact of similar pandemics. DESIGN: We combine several sources of data, which describe specific risk factors linked with the outbreak of a respiratory pathogen, that could leave local areas vulnerable to the harmful consequences of large-scale outbreaks of contagious diseases. We combine these measures to generate an index of community-level vulnerability. SETTING: 91 Clinical Commissioning Groups (CCGs) in England. MAIN OUTCOME MEASURES: We merge 15 measures spatially to generate an index of community-level vulnerability. These measures cover prevalence rates of high-risk diseases; proxies for the at-risk population density; availability of staff and quality of healthcare facilities. RESULTS: We find that 80% of CCGs that score in the highest quartile of vulnerability are located in the North of England (24 out of 30). Here, vulnerability stems from a faster rate of population ageing and from the widespread presence of underlying at-risk diseases. These same areas, especially the North-East Coast areas of Lancashire, also appear vulnerable to adverse shocks to healthcare supply due to tighter labour markets for healthcare personnel. Importantly, our index correlates with a measure of social deprivation, indicating that these communities suffer from long-standing lack of economic opportunities and are characterised by low public and private resource endowments. CONCLUSIONS: Evidence-based policy is crucial to mitigate the health impact of pandemics such as COVID-19. While current attention focuses on curbing rates of contagion, we introduce a vulnerability index combining data that can help policy makers identify the most vulnerable communities. We find that this index is positively correlated with COVID-19 deaths and it can thus be used to guide targeted capacity building. These results suggest that a stronger focus on deprived and vulnerable communities is needed to tackle future threats from emerging and re-emerging infectious disease.