Repositorio Académico UPC

 This paper examines whether compliance with COVID-19 mitigation measures is motivated by wanting to save lives or save the economy (or both), and which implications this carries to fight the pandemic. National representative samples were collected from 24 countries (N = 25,435). The main predictors were (1) perceived risk to contract coronavirus, (2) perceived risk to suffer economic losses due to coronavirus, and (3) their interaction effect. Individual and country-level variables were added as covariates in multilevel regression models. We examined compliance with various preventive health behaviors and support for strict containment policies. Results show that perceived economic risk consistently predicted mitigation behavior and policy support—and its effects were positive. Perceived health risk had mixed effects. Only two significant interactions between health and economic risk were identified—both positive.

The COVID-19 pandemic presents threats, such as severe disease and economic hardship, to people of different ages. These threats can also be experienced asymmetrically across age groups, which could lead to generational differences in behavioral responses to reduce the spread of the disease. We report a survey conducted across 56 societies (N = 58,641), and tested pre-registered hypotheses about how age relates to (a) perceived personal costs during the pandemic, (b) prosocial COVID-19 responses (e.g., social distancing), and (c) support for behavioral regulations (e.g., mandatory quarantine, vaccination). We further tested whether the relation between age and prosocial COVID-19 responses can be explained by perceived personal costs during the pandemic. Overall, we found that older people perceived more costs of contracting the virus, but less costs in daily life due to the pandemic. However, age displayed no clear, robust associations with prosocial COVID-19 responses and support for ...

Self-medication impacts both negatively and positively the health of people, which has become evident during the COVID-19 pandemic. The study aimed to assess the prevalence of self-medicated drugs used for respiratory symptoms, as COVID-19 preventive, for its symptoms or once tested positive. To determine the perception of symptom relief and demographic variables that promote self-medication in Peru. We performed a cross-sectional, analytical, multicenter study in 3792 study respondents on the use, the reason for use, and perception of relief after the use of six drugs during the quarantine period. An online questionnaire was developed, pretested and submitted to the general public. Multivariable logistic regression was used to ascertain factors that influence an individual's desire to self-medicate, associations were considered significant at p < 0.05 and using region (coast, mountain and jungle) as cluster group. The majority of respondents self-medicated with acetaminophen fo...

Open Access / Acceso abierto Otros títulos: Análisis de la distribución de macronutrientes en canastas alimentarias entregadas por las municipalidades durante la pandemia de Covid-19 en Perú Editorial: Instituto Nacional de Salud Journal: Revista Peruana de Medicina Experimental y Salud Publica URI: http://hdl.handle.net/10757/659815 DOI: 10.17843/rpmesp.2022.391.9742 Enlaces adicionales: https://rpmesp.ins.gob.pe/index.php/rpmesp/article/view/9742

Open Access / Acceso abierto URI: http://hdl.handle.net/10757/659813 DOI: 10.1016/j.patter.2022.100482 Enlaces adicionales: https://www.cell.com/patterns/fulltext/S2666-3899(22)00067-8 Before vaccines for coronavirus disease 2019 (COVID-19) became available, a set of infection-prevention behaviors constituted the primary means to mitigate the virus spread. Our study aimed to identify important predictors of this set of behaviors. Whereas social and health psychological theories suggest a limited set of predictors, machine-learning analyses can identify correlates from a larger pool of candidate predictors. We used random forests to rank 115 candidate correlates of infection-prevention behavior in 56,072 participants across 28 countries, administered in March to May 2020. The machine-learning model predicted 52% of the variance in infection-prevention behavior in a separate test sample—exceeding the performance of psychological models of health behavior. Results indicated the two most i...

Open Access / Acceso abierto URI: http://hdl.handle.net/10757/659814 DOI: 10.1371/journal.pone.0265820 Enlaces adicionales: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0265820 Introduction The rapid expansion of the novel SARS-CoV-2 virus has raised serious public health concerns due to the possibility of misdiagnosis in regions where arboviral diseases are endemic. We performed the first study in northern Peru to describe the detection of SARSCoV-2 IgM antibodies in febrile patients with a suspected diagnosis of dengue and chikungunya fever. Materials and methods A consecutive cross-sectional study was performed in febrile patients attending primary healthcare centers from April 2020 through March 2021. Patients enrolled underwent serum sample collection for the molecular and serological detection of DENV and CHIKV. Also, serological detection of IgM antibodies against SARS-CoV-2 was performed. Results 464 patients were included during the study period, of which ...