Suchergebnisse

BACKGROUND: Governments have implemented a range of measures to tackle COVID-19, primarily focusing on changing citizens' behaviours in order to lower the transmission of the virus. Few studies have looked at the patterns of compliance with different measures within individuals: whether people comply with all measures or selectively choose some but not others. Such research is important for designing interventions to increase compliance. METHODS: We used cross-sectional data from 20 947 UK adults in the COVID-19 Social Study collected from 17 November to 23 December 2020. Self-report compliance was assessed with six behaviours: mask wearing, hand washing, indoor household mixing, outdoor household mixing, social distancing and compliance with other guidelines. Patterns of compliance behaviour were identified using latent class analysis, and multinomial logistic regression was used to assess demographic, socioeconomic and personality predictors of behaviour patterns. RESULTS: We selected a four-latent class solution. Most individuals reported similar levels of compliance across the six behaviour measures. High level of compliance was the modal response. Lower self-reported compliance was related to young age, high risk-taking behaviour, low confidence in government and low empathy, among other factors. Looking at individual behaviours, mask wearing had the highest level of compliance while compliance with social distancing was relatively low. CONCLUSION: Results suggest that individuals choose to comply with all guidelines, rather than some but not others. Strategies to increase compliance should focus on increasing general motivations to comply alongside specifically encouraging social distancing.

INTRODUCTION: COVID-19 vaccines do not confer immediate immunity and vaccinated individuals may still be at risk of transmitting the virus. Governments have not exempted vaccinated individuals from behavioural measures to reduce the spread of COVID-19, such as practising social distancing. However, vaccinated individuals may have reduced compliance with these measures, given lower perceived risks. METHODS: We used monthly panel data from October 2020 to March 2021 in the UK COVID-19 Social Study to assess changes in compliance following vaccination. Compliance was measured with two items on compliance with guidelines in general and compliance with social distancing. We used matching to create comparable groups of individuals by month of vaccination (January, February or not vaccinated by February) and fixed effects regression to estimate changes in compliance over the study period. RESULTS: Compliance increased between October 2020 and March 2021, regardless of vaccination status or month of vaccination. There was no clear evidence that vaccinated individuals decreased compliance relative to those who were not yet vaccinated. CONCLUSION: There was little evidence that sample members vaccinated in January or February reduced compliance after receiving vaccination for COVID-19. Continued monitoring is required as younger individuals receive the vaccine, lockdown restrictions are lifted and individuals receive second doses of the vaccine.

The prediction of carbon uptake by forests across fertility gradients requires accurate characterisation of how biochemical limitations to photosynthesis respond to variation in key elements such as nitrogen (N) and phosphorus (P). Over the last decade, proxies for chlorophyll and photosynthetic activity have been extracted from hyperspectral imagery and used to predict important photosynthetic variables such as the maximal rate of carboxylation (Vcmax) and electron transport (Jmax). However, little research has investigated the generality of these relationships within the nitrogen (N) and phosphorus (P) limiting phases, which are characterised by mass based foliage ratios of N:P ≤ 10 for N limitations and N:P > 10 for P limitations. Using measurements obtained from one year old Pinus radiata D. Don grown under a factorial range of N and P treatments this research examined relationships between photosynthetic capacity (Vcmax, Jmax) and measured N, P and chlorophyll (Chla+b). Using functional traits quantified from hyperspectral imagery we then examined the strength and generality of relationships between photosynthetic variables and Photochemical Reflectance Index (PRI), Sun-Induced Chlorophyll Fluorescence (SIF) and chlorophyll a + b derived by radiative transfer model inversion. There were significant (P < .001) and strong relationships between photosynthetic variables and both N (R2 = 0.82 for Vcmax; R2 = 0.87 for Jmax) and Chla+b (R2 = 0.85 for Vcmax; R2 = 0.86 for Jmax) within the N limiting phase that were weak (R2 < 0.02) and insignificant within the P limiting phase. Similarly, there were significant (P < .05) positive relationships between P and photosynthetic variables (R2 = 0.50 for Vcmax; R2 = 0.58 for Jmax) within the P limiting phase that were insignificant and weak (R2 < 0.33) within the N limiting phase. Predictions of photosynthetic variables using Chla+b estimated by model inversion were significant (P < .001), positive and strong (R2 = 0.64 for Vcmax; R2 = 0.63 for Jmax) within the N limiting phase but insignificant and weak (R2 < 0.05) within the P limiting phase. In contrast, both SIF and PRI exhibited moderate to strong positive correlations with photosynthetic variables within both the N and P limiting phases. These results suggest that quantified SIF and PRI from hyperspectral images may have greater generality in predicting biochemical limitations to photosynthesis than proxies for N and chlorophyll a + b, particularly under high foliage N content, when P is limiting. ; Resilient Forests programme Scion SSIF Forest Grower's Levy Trust National Institute for Forest Products Innovation NIF073-1819 Australian Government CGIAR Australasian Forestry Companies South Australian State Government Tasmanian State Government