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Article: Food composition databases in the era of Big Data: Vegetable oils as a case study.

Ferraz de Arruda, Henrique / Aleta, Alberto / Moreno, Yamir

2023 Volume 9, Page(s) 1052934

Abstract: Understanding the population's dietary patterns and their impacts on health requires many different sources of information. The development of reliable food composition databases is a key step in this pursuit. With them, nutrition and health care ... ...

Abstract	Understanding the population's dietary patterns and their impacts on health requires many different sources of information. The development of reliable food composition databases is a key step in this pursuit. With them, nutrition and health care professionals can provide better public health advice and guide society toward achieving a better and healthier life. Unfortunately, these databases are full of caveats. Focusing on the specific case of vegetable oils, we analyzed the possible obsolescence of the information and the differences or inconsistencies among databases. We show that in many cases, the information is limited, incompletely documented, old or unreliable. More importantly, despite the many efforts carried out in the last decades, there is still much work to be done. As such, institutions should develop long-standing programs that can ensure the quality of the information on what we eat in the long term. In the face of climate change and complex societal challenges in an interconnected world, the full diversity of the food system needs to be recognized and more efforts should be put toward achieving a data-driven food system.
Language	English
Publishing date	2023-01-05
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2776676-7
ISSN	2296-861X
ISSN	2296-861X
DOI	10.3389/fnut.2022.1052934
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Article ; Online: Digital cities and the spread of COVID-19: Characterizing the impact of non-pharmaceutical interventions in five cities in Spain.

Rodríguez, Jorge P / Aleta, Alberto / Moreno, Yamir

Frontiers in public health

2023 Volume 11, Page(s) 1122230

Abstract: Mathematical modeling has been fundamental to achieving near real-time accurate forecasts of the spread of COVID-19. Similarly, the design of non-pharmaceutical interventions has played a key role in the application of policies to contain the spread. ... ...

Abstract	Mathematical modeling has been fundamental to achieving near real-time accurate forecasts of the spread of COVID-19. Similarly, the design of non-pharmaceutical interventions has played a key role in the application of policies to contain the spread. However, there is less work done regarding quantitative approaches to characterize the impact of each intervention, which can greatly vary depending on the culture, region, and specific circumstances of the population under consideration. In this work, we develop a high-resolution, data-driven agent-based model of the spread of COVID-19 among the population in five Spanish cities. These populations synthesize multiple data sources that summarize the main interaction environments leading to potential contacts. We simulate the spreading of COVID-19 in these cities and study the effect of several non-pharmaceutical interventions. We illustrate the potential of our approach through a case study and derive the impact of the most relevant interventions through scenarios where they are suppressed. Our framework constitutes a first tool to simulate different intervention scenarios for decision-making.
MeSH term(s)	Humans ; COVID-19/epidemiology ; COVID-19/prevention & control ; SARS-CoV-2 ; Cities ; Spain/epidemiology ; Models, Theoretical
Language	English
Publishing date	2023-03-23
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2711781-9
ISSN	2296-2565 ; 2296-2565
ISSN (online)	2296-2565
ISSN	2296-2565
DOI	10.3389/fpubh.2023.1122230
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Article ; Online: Assessing the effectiveness of perimeter lockdowns as a response to epidemics at the urban scale.

de Miguel Arribas, Alfonso / Aleta, Alberto / Moreno, Yamir

Scientific reports

2023 Volume 13, Issue 1, Page(s) 4474

Abstract: From September 2020 to May 2021 Madrid region (Spain) followed a rather unique non-pharmaceutical intervention (NPI) by establishing a strategy of perimeter lockdowns (PLs) that banned travels to and from areas satisfying certain epidemiological risk ... ...

Abstract	From September 2020 to May 2021 Madrid region (Spain) followed a rather unique non-pharmaceutical intervention (NPI) by establishing a strategy of perimeter lockdowns (PLs) that banned travels to and from areas satisfying certain epidemiological risk criteria. PLs were pursued to avoid harsher restrictions, but some studies have found that the particular implementation by Madrid authorities was rather ineffective. Based on Madrid's case, we devise a general, minimal framework to investigate the PLs effectiveness by using a data-driven metapopulation epidemiological model of a city, and explore under which circumstances the PLs could be a good NPI. The model is informed with real mobility data from Madrid to contextualize its results, but it can be generalized elsewhere. The lowest lockdown activation threshold [Formula: see text] considered (14-day cumulative incidence rate of 20 cases per every [Formula: see text] inhabitants) shows a prevalence reduction [Formula: see text] with respect to the scenario [Formula: see text], more akin to the case of Madrid, and assuming no further mitigation. Only the combination of [Formula: see text] and mobility reduction [Formula: see text] can avoid PLs for more than [Formula: see text] of the system. The combination of low [Formula: see text] and strong local transmissibility reduction is key to minimize the impact, but the latter is harder to achieve given that we assume a situation with highly mitigated transmission, resembling the one observed during the second wave of COVID-19 in Madrid. Thus, we conclude that a generalized lockdown is hard to avoid under any realistic setting if only this strategy is applied.
MeSH term(s)	Humans ; COVID-19/epidemiology ; COVID-19/prevention & control ; Communicable Disease Control ; Epidemics/prevention & control ; Spain/epidemiology
Language	English
Publishing date	2023-03-18
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-31614-8
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Article ; Online: Characterizing the role of human behavior in the effectiveness of contact-tracing applications.

Fosch, Ariadna / Aleta, Alberto / Moreno, Yamir

Frontiers in public health

2023 Volume 11, Page(s) 1266989

Abstract: 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 ... ...

Abstract	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.
MeSH term(s)	Humans ; Contact Tracing ; Pandemics ; Mobile Applications ; COVID-19/epidemiology ; COVID-19/prevention & control ; COVID-19 Testing
Language	English
Publishing date	2023-11-03
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2711781-9
ISSN	2296-2565 ; 2296-2565
ISSN (online)	2296-2565
ISSN	2296-2565
DOI	10.3389/fpubh.2023.1266989
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Article ; Online: Characterizing the role of human behavior in the effectiveness of contact-tracing applications

Ariadna Fosch / Alberto Aleta / Yamir Moreno

Frontiers in Public Health, Vol

2023 Volume 11

Abstract: 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 ...

Abstract	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.
Keywords	digital contact-tracing ; contact-tracing apps ; COVID-19 ; epidemic modeling ; human behavior ; multilayer networks ; Public aspects of medicine ; RA1-1270
Subject code	612
Language	English
Publishing date	2023-11-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
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Article ; Online: Modeling the impact of COVID-19 on future tuberculosis burden.

Tovar, Mario / Aleta, Alberto / Sanz, Joaquín / Moreno, Yamir

Communications medicine

2022 Volume 2, Page(s) 77

Abstract: Background: The ongoing COVID-19 pandemic has greatly disrupted our everyday life, forcing the adoption of non-pharmaceutical interventions in many countries and putting public health services and healthcare systems worldwide under stress. These ... ...

Abstract	Background: The ongoing COVID-19 pandemic has greatly disrupted our everyday life, forcing the adoption of non-pharmaceutical interventions in many countries and putting public health services and healthcare systems worldwide under stress. These circumstances are leading to unintended effects such as the increase in the burden of other diseases. Methods: Here, using a data-driven epidemiological model for tuberculosis (TB) spreading, we describe the expected rise in TB incidence and mortality if COVID-associated changes in TB notification are sustained and attributable entirely to disrupted diagnosis and treatment adherence. Results: Our calculations show that the reduction in diagnosis of new TB cases due to the COVID-19 pandemic could result in 228k (CI 187-276) excess deaths in India, 111k (CI 93-134) in Indonesia, 27k (CI 21-33) in Pakistan, and 12k (CI 9-18) in Kenya. Conclusions: We show that it is possible to reverse these excess deaths by increasing the pre-covid diagnosis capabilities from 15 to 50% for 2 to 4 years. This would prevent almost all TB-related excess mortality that could be caused by the COVID-19 pandemic if no additional preventative measures are introduced. Our work therefore provides guidelines for mitigating the impact of COVID-19 on tuberculosis epidemic in the years to come.
Language	English
Publishing date	2022-06-29
Publishing country	England
Document type	Journal Article
ISSN	2730-664X
ISSN (online)	2730-664X
DOI	10.1038/s43856-022-00145-0
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Article ; Online: Impact of vaccine hesitancy on secondary COVID-19 outbreaks in the US: an age-structured SIR model.

de Miguel-Arribas, Alfonso / Aleta, Alberto / Moreno, Yamir

BMC infectious diseases

2022 Volume 22, Issue 1, Page(s) 511

Abstract: Background: The COVID-19 outbreak has become the worst pandemic in at least a century. To fight this disease, a global effort led to the development of several vaccines at an unprecedented rate. There have been, however, several logistic issues with its ...

Abstract	Background: The COVID-19 outbreak has become the worst pandemic in at least a century. To fight this disease, a global effort led to the development of several vaccines at an unprecedented rate. There have been, however, several logistic issues with its deployment, from their production and transport, to the hesitancy of the population to be vaccinated. For different reasons, an important amount of individuals is reluctant to get the vaccine, something that hinders our ability to control and-eventually-eradicate the disease. Materials and methods: Our aim is to explore the impact of vaccine hesitancy when highly transmissible SARS-CoV-2 variants of concern spread through a partially vaccinated population. To do so, we use age-stratified data from surveys on vaccination acceptance, together with age-contact matrices to inform an age-structured SIR model set in the US. Results: Our results show that per every one percent decrease in vaccine hesitancy up to 45 deaths per million inhabitants could be averted. A closer inspection of the stratified infection rates also reveals the important role played by the youngest groups. The model captures the general trends of the Delta wave spreading in the US (July-October 2021) with a correlation coefficient of [Formula: see text]. Conclusions: Our results shed light on the role that hesitancy plays on COVID-19 mortality and highlight the importance of increasing vaccine uptake in the population, specially among the eldest age groups.
MeSH term(s)	COVID-19/epidemiology ; COVID-19/prevention & control ; Disease Outbreaks/prevention & control ; Epidemiological Models ; Humans ; Patient Acceptance of Health Care ; SARS-CoV-2 ; Vaccination Hesitancy ; Vaccines
Chemical Substances	Vaccines
Language	English
Publishing date	2022-06-01
Publishing country	England
Document type	Journal Article
ZDB-ID	2041550-3
ISSN	1471-2334 ; 1471-2334
ISSN (online)	1471-2334
ISSN	1471-2334
DOI	10.1186/s12879-022-07486-0
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Article ; Online: Evaluation of the potential incidence of COVID-19 and effectiveness of containment measures in Spain: a data-driven approach.

Aleta, Alberto / Moreno, Yamir

BMC medicine

2020 Volume 18, Issue 1, Page(s) 157

Abstract: Background: We are currently experiencing an unprecedented challenge, managing and containing an outbreak of a new coronavirus disease known as COVID-19. While China-where the outbreak started-seems to have been able to contain the growth of the ... ...

Abstract	Background: We are currently experiencing an unprecedented challenge, managing and containing an outbreak of a new coronavirus disease known as COVID-19. While China-where the outbreak started-seems to have been able to contain the growth of the epidemic, different outbreaks are nowadays present in multiple countries. Nonetheless, authorities have taken action and implemented containment measures, even if not everything is known. Methods: To facilitate this task, we have studied the effect of different containment strategies that can be put into effect. Our work referred initially to the situation in Spain as of February 28, 2020, where a few dozens of cases had been detected, but has been updated to match the current situation as of 13 April. We implemented an SEIR metapopulation model that allows tracing explicitly the spatial spread of the disease through data-driven stochastic simulations. Results: Our results are in line with the most recent recommendations from the World Health Organization, namely, that the best strategy is the early detection and isolation of individuals with symptoms, followed by interventions and public recommendations aimed at reducing the transmissibility of the disease, which, although might not be sufficient for disease eradication, would produce as a second order effect a delay of several days in the raise of the number of infected cases. Conclusions: Many quantitative aspects of the natural history of the disease are still unknown, such as the amount of possible asymptomatic spreading or the role of age in both the susceptibility and mortality of the disease. However, preparedness plans and mitigation interventions should be ready for quick and efficacious deployment globally. The scenarios evaluated here through data-driven simulations indicate that measures aimed at reducing individuals' flow are much less effective than others intended for early case identification and isolation. Therefore, resources should be directed towards detecting as many and as fast as possible the new cases and isolate them.
MeSH term(s)	Betacoronavirus/pathogenicity ; COVID-19 ; Coronavirus Infections/prevention & control ; Coronavirus Infections/transmission ; Data Mining ; Disease Outbreaks/prevention & control ; Evaluation Studies as Topic ; Humans ; Incidence ; Pandemics/prevention & control ; Pneumonia, Viral/prevention & control ; Pneumonia, Viral/transmission ; Population Surveillance ; Quarantine/methods ; SARS-CoV-2 ; Spain/epidemiology
Keywords	covid19
Language	English
Publishing date	2020-05-27
Publishing country	England
Document type	Journal Article
ISSN	1741-7015
ISSN (online)	1741-7015
DOI	10.1186/s12916-020-01619-5
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Article ; Online: Modeling the impact of COVID-19 on future tuberculosis burden

Mario Tovar / Alberto Aleta / Joaquín Sanz / Yamir Moreno

Communications Medicine, Vol 2, Iss 1, Pp 1-

2022 Volume 10

Abstract: Tovar et al. use a data-driven epidemiological model for tuberculosis (TB) spreading to describe an expected rise in TB incidence and mortality due to COVID-associated disruption in TB diagnosis and treatment. Their calculations predict higher incidence ... ...

Abstract	Tovar et al. use a data-driven epidemiological model for tuberculosis (TB) spreading to describe an expected rise in TB incidence and mortality due to COVID-associated disruption in TB diagnosis and treatment. Their calculations predict higher incidence and mortality due to reduced diagnosis of new TB cases, however suggest increased diagnostic capacity could mitigate this situation.
Keywords	Medicine ; R
Language	English
Publishing date	2022-06-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
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Article ; Online: Modeling the effects of social distancing on the large-scale spreading of diseases.

Ventura, Paulo Cesar / Aleta, Alberto / Rodrigues, Francisco Aparecido / Moreno, Yamir

Epidemics

2022 Volume 38, Page(s) 100544

Abstract: To contain the propagation of emerging diseases that are transmissible from human to human, non-pharmaceutical interventions (NPIs) aimed at reducing the interactions between humans are usually implemented. One example of the latter kind of measures is ... ...

Abstract	To contain the propagation of emerging diseases that are transmissible from human to human, non-pharmaceutical interventions (NPIs) aimed at reducing the interactions between humans are usually implemented. One example of the latter kind of measures is social distancing, which can be either policy-driven or can arise endogenously in the population as a consequence of the fear of infection. However, if NPIs are lifted before the population reaches herd immunity, further re-introductions of the pathogen would lead to secondary infections. Here we study the effects of different social distancing schemes on the large scale spreading of diseases. Specifically, we generalize metapopulation models to include social distancing mechanisms at the subpopulation level and model short- and long-term strategies that are fed with local or global information about the epidemics. We show that different model ingredients might lead to very diverse outcomes in different subpopulations. Our results suggest that there is not a unique answer to the question of whether contention measures are more efficient if implemented and managed locally or globally and that model outcomes depends on how the full complexity of human interactions is taken into account.
MeSH term(s)	COVID-19/epidemiology ; Epidemics ; Humans ; Immunity, Herd ; Physical Distancing
Language	English
Publishing date	2022-02-21
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2467993-8
ISSN	1878-0067 ; 1755-4365
ISSN (online)	1878-0067
ISSN	1755-4365
DOI	10.1016/j.epidem.2022.100544
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