Interactions between four species in a complex wildlife: livestock disease community : implications for Mycobacterium bovis maintenance and transmission

Livestock diseases such as bovine tuberculosis can have considerable negative effects on human health and economic activity. Wildlife reservoirs often hinder disease eradication in sympatric livestock populations. Therefore, quantifying interactions between wildlife and livestock is an important aspect of understanding disease persistence. This study was conducted on an extensive cattle farm in southwest Spain, where cattle, domestic pigs, wild boar and red deer are considered to be part of a tuberculosis host community. We tested the hypothesis that the frequency of both types of interactions would be greater at food and water sites, due to the aggregation of individuals from multiple species at these locations. We measured direct and indirect interactions between individuals using GPS and proximity loggers. Over 57,000 direct interactions were recorded over a 2-year period, of which 875 (1.5 %) occurred between different species and 216 (0.38 %) occurred between wildlife and livestock. Most direct and indirect interactions occurred at water sites. Over 90 % of indirect interactions between wildlife and livestock took place within the estimated 3-day environmental survival time of Mycobacterium bovis in this habitat. Red deer home ranges and daily activity patterns revealed significant spatial and temporal overlaps with cattle, particularly in autumn. Suids and red deer also cross the farm boundary regularly, introducing a between-farm interaction risk. The infrequent occurrence of direct interactions between individuals from different species suggests that they are unlikely to be the sole mode of disease transmission and that indirect interactions may play an important role

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution-individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.Published versio

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multi-national data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar was found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-negligible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic