Characterizing the role of human behavior in the effectiveness of contact-tracing applications

IntroductionAlthough numerous countries relied on contact-tracing (CT) applications as an epidemic control measure against the COVID-19 pandemic, the debate around their effectiveness is still open. Most studies indicate that very high levels of adoption are required to stop disease progression, placing the main interest of policymakers in promoting app adherence. However, other factors of human behavior, like delays in adherence or heterogeneous compliance, are often disregarded.MethodsTo characterize the impact of human behavior on the effectiveness of CT apps we propose a multilayer network model reflecting the co-evolution of an epidemic outbreak and the app adoption dynamics over a synthetic population generated from survey data. The model was initialized to produce epidemic outbreaks resembling the first wave of the COVID-19 pandemic and was used to explore the impact of different changes in behavioral features in peak incidence and maximal prevalence.ResultsThe results corroborate the relevance of the number of users for the effectiveness of CT apps but also highlight the need for early adoption and, at least, moderate levels of compliance, which are factors often not considered by most policymakers.DiscussionThe insight obtained was used to identify a bottleneck in the implementation of several apps, such as the Spanish CT app, where we hypothesize that a simplification of the reporting system could result in increased effectiveness through a rise in the levels of compliance

Characterising the role of human behaviour in the effectiveness of contact-tracing applications

Albeit numerous countries relied on contact-tracing (CT) applications as an epidemic control measure against the COVID-19 pandemic, the debate around their effectiveness is still open. Most studies indicate that very high levels of adoption are required to stop disease progression, placing the main interest of policymakers in promoting app adherence. However, other factors of human behaviour, like delays in adherence or heterogeneous compliance, are often disregarded. To characterise the impact of human behaviour on the effectiveness of CT apps we propose a multilayer network model reflecting the co-evolution of an epidemic outbreak and the app adoption dynamics over a synthetic population generated from survey data. The model was initialised to produce epidemic outbreaks resembling the first wave of the COVID-19 pandemic and was used to explore the impact of different changes in behavioural features in peak incidence and maximal prevalence. The results corroborate the relevance of the number of users for the effectiveness of CT apps but also highlight the need for early adoption and, at least, moderate levels of compliance, which are factors often not considered by most policymakers. The insight obtained was used to identify a bottleneck in the implementation of several apps, such as the Spanish CT app, where we hypothesise that a simplification of the reporting system could result in increased effectiveness through a rise in the levels of compliance.Comment: 25 pages including all figures and S

Characterizing the role of human behavior in the effectiveness of contact-tracing applications

Introduction: Although numerous countries relied on contact-tracing (CT) applications as an epidemic control measure against the COVID-19 pandemic, the debate around their effectiveness is still open. Most studies indicate that very high levels of adoption are required to stop disease progression, placing the main interest of policymakers in promoting app adherence. However, other factors of human behavior, like delays in adherence or heterogeneous compliance, are often disregarded. Methods: To characterize the impact of human behavior on the effectiveness of CT apps we propose a multilayer network model reflecting the co-evolution of an epidemic outbreak and the app adoption dynamics over a synthetic population generated from survey data. The model was initialized to produce epidemic outbreaks resembling the first wave of the COVID-19 pandemic and was used to explore the impact of different changes in behavioral features in peak incidence and maximal prevalence. Results: The results corroborate the relevance of the number of users for the effectiveness of CT apps but also highlight the need for early adoption and, at least, moderate levels of compliance, which are factors often not considered by most policymakers. Discussion: The insight obtained was used to identify a bottleneck in the implementation of several apps, such as the Spanish CT app, where we hypothesize that a simplification of the reporting system could result in increased effectiveness through a rise in the levels of compliance

Warfare as a case of mating behavior

Mating is a vital activity that is characterized for its complexity. In humans, there are two sexes with different interests: women are choosier because of their bigger investment on reproduction, and men are more protective because of the uncertainty of their paternity due to internal fertilization. This leads to the development of different mating strategies that both men and women perform, such as sexual deception, sexual exploitation, stalking, etc. and its corresponding developed defenses. The result is a co-evolutionary arms race, similar to that between predators and preys, or between different states to achieve better military force

Replanting unproductive palm oil with smallholder plantations can help achieve Sustainable Development Goals in Sumatra, Indonesia

Oil palm (Elaeis guinensis) is a controversial crop. To assess its sustainability, we analysed the contribution of different types of plantations (smallholder, industrial and unproductive) towards meeting six Sustainable Development Goals. Using spatial econometric methods and data from 25,067 villages in Sumatra, Indonesia, we revealed that unproductive plantations are associated with more cases of malnutrition, worsened school access, more air pollution and increased criminality. We also proposed a strategy for sustainable palm oil expansion based on replanting unproductive plantations with either industrial or smallholder palm oil. Smallholder replanting was beneficial for five Goals (Zero poverty, Good health, Quality Education, Environmental preservation and Crime reduction), while the same intervention only improved two Goals in the industrial case (Zero poverty and Quality Education). Our appraisal is relevant to policymakers aiming towards the 2030 Agenda, organisations planning oil palm expansion, and retailers or consumers concerned about the sustainability of oil consumption

Barriers to linkage to care in hepatitis C patients with substance use disorders and dual diagnoses, despite centralized management

Hepatitis C virus; Dual diagnosis; Substance use disorderVirus de l'Hepatitis C; Diagnòstic dual; Trastorn per consum de substànciesVirus de la Hepatitis C; Diagnóstico dual; Trastorno por consumo de sustanciasBackground: Hepatitis C virus (HCV) management is a challenge in patients with substance use disorder (SUD). This study aimed to describe an HCV screening and linkage to care program in SUD patients, and analyze the characteristics of this population in relation to HCV infection, particularly the impact of psychiatric comorbidities (dual diagnosis). Methods: This study was a prospective clinical cohort study using a collaborative, multidisciplinary model to offer HCV care (screening, diagnosis, and therapy) to individuals with SUD attending a dedicated hospital clinic. The characteristics of the participants, prevalence of HCV infection, percentage who started therapy, and adherence to treatment were compared according to the patients’ consumption characteristics and presence of dual diagnosis. HCV screening, diagnosis, treatment initiation, and sustained virologic response were analyzed. Results: 528 individuals attended the center (November 2018–June 2019) and 401 (76%) accepted screening. In total, 112 (28%) were anti-HCV-positive and 42 (10%) had detectable HCV RNA, but only 20 of the latter started HCV therapy. Among the 253 (63%) patients with a dual diagnosis, there were no differences in HCV infection prevalence versus patients with SUD alone (p = 0.28). Dual diagnosis did not lead to a higher risk of HCV infection or interfere with linkage to care or treatment. Conclusion: This study found a high prevalence of dual diagnosis and HCV infection in SUD patients, but dual diagnosis was not associated with an increased risk of acquiring HCV or more complex access to care. Despite use of a multidisciplinary management approach, considerable barriers to HCV care remain in this population that would need more specific focus.This work was supported by AbbVie

EVE: A liquid handling robot based on LEGO Mindstorms

Treball de fi de grau en BiomèdicaTutors: Jordi García-Ojalvo, Letícia GaleraHigh throughput screening (HTS) has lead to a revolution in research laboratories due to the possibility of performing millions of tests very quickly. The rise of HTS was accompanied by the appearance of the market of liquid handling robots (LHRs), which intend to automatize the handling of samples in HTS procedures. However, commercial LHRs are a noticeable investment for many small biology laboratories. The objective of this project is to create, using LEGO Mindstorm, a low-cost LHR that is able to fill 96-well plates automatically. The robot, which we have called EVE, uses a single channel micropipette and avoids cross-contamination between wells by changing pipette tips during the plate-filling procedure. EVE’s design was created combining computational design with the physical assembly of the different robot parts. Additionally, two 3D printed bases were created to sustain all the different required elements for the robot function. Finally, EVE was coded to perform routines like copying a 96-well plate or performing a dilution. The software also includes a menu to calibrate the robot and select the desired routine to perform