Computer Vision for Parkinson's Disease Evaluation: A Survey on Finger Tapping.

Parkinson's disease (PD) is a progressive neurodegenerative disorder whose prevalence has steadily been rising over the years. Specialist neurologists across the world assess and diagnose patients with PD, although the diagnostic process is time-consuming and various symptoms take years to appear, which means that the diagnosis is prone to human error. The partial automatization of PD assessment and diagnosis through computational processes has therefore been considered for some time. One well-known tool for PD assessment is finger tapping (FT), which can now be assessed through computer vision (CV). Artificial intelligence and related advances over recent decades, more specifically in the area of CV, have made it possible to develop computer systems that can help specialists assess and diagnose PD. The aim of this study is to review some advances related to CV techniques and FT so as to offer insight into future research lines that technological advances are now opening up.

[Retrospective estimation of initial COVID-19 infections in the Santiago Metropolitan Region in Chile]. / Estimación retrospectiva de los casos iniciales de COVID-19 en Santiago Región Metropolitana en Chile.

OBJECTIVE: Estimate daily infections of COVID-19 during the first year of the pandemic in the Santiago Metropolitan Region (SRM) in Chile and Chile that are more realistic than those officially registered. METHOD: Retrospective estimate of daily infections from daily data on COVID-19 deaths, a seroprevalence study, and the REMEDID (Retrospective Methodology to Estimate Daily Infections from Deaths) algorithm. RESULTS: In SRM, it is observed that: 1) the maximum peak of infections was more than double that registered in the official statistics; 2) such peak was reached on May 22 (95% CI: 20-24 May), 2022, that is, 24 days before the official date of the peak of infections; and 3) the first estimated contagion took place on January 28, 2020 (95% CI: January 21 to February 16), that is, 36 days before the official date. In Chile, the situation is similar. During the first wave SRM accounted for 70%-76% of those infected in Chile, while from August 2020 onwards it accounted for 36%-39%. CONCLUSIONS: The official records of COVID-19 infections in SRM and Chile underestimated the real number of positives and showed a delay of about a month in the dynamics of infections. This is not an isolated situation, as it is known to have been the case in other countries as well. However, it is important to have reliable estimates for a correct modeling of the spread of the virus.

Estimación retrospectiva de los casos iniciales de COVID-19 en Santiago Región Metropolitana en Chile / Retrospective estimation of initial COVID-19 infections in the Santiago Metropolitan Region in Chile

Objetivo: Estimar los casos diarios de COVID-19 durante el primer año de pandemia en Santiago Región Metropolitana (SRM) y en Chile con cifras más realistas que las registradas oficialmente. Método: Estimación retrospectiva de los casos diarios a partir de los datos diarios de fallecimientos por COVID-19, un estudio de seroprevalencia y el algoritmo REMEDID (Retrospective Methodology to Estimate Daily Infections from Deaths). Resultados: En SRM se observa que: 1) el pico máximo de contagios fue superior al doble del registrado en las estadísticas oficiales; 2) dicho pico se alcanzó el 22 de mayo de 2020 (IC95%: 20 a 24 de mayo), esto es, 24 días antes de la fecha oficial del pico de contagios; y 3) el primer contagio estimado tuvo lugar el 28 de enero de 2020 (IC95%: 21 de enero a 16 de febrero), esto es, 36 días antes de la fecha oficial. En Chile, la situación es similar. Durante la primera ola, SRM concentró el 70-76% de los infectados de Chile, mientras que a partir de agosto de 2020 solo concentró el 36-39%. Conclusiones: Los registros oficiales de casos de COVID-19 en SRM y Chile infravaloraron el número real de positivos y mostraron un retraso de alrededor de un mes en la dinámica de contagios. Esta no es una situación aislada, ya que se sabe que también ha sido así en otros países. No obstante, es importante disponer de estimaciones fidedignas para una correcta modelización de la expansión del virus.(AU)

Objective: Estimate daily infections of COVID-19 during the first year of the pandemic in the Santiago Metropolitan Region (SRM) in Chile and Chile that are more realistic than those officially registered. Method: Retrospective estimate of daily infections from daily data on COVID-19 deaths, a seroprevalence study, and the REMEDID (Retrospective Methodology to Estimate Daily Infections from Deaths) algorithm. Results: In SRM, it is observed that: 1) the maximum peak of infections was more than double that registered in the official statistics; 2) such peak was reached on May 22 (95% CI: 20–24 May), 2022, that is, 24 days before the official date of the peak of infections; and 3) the first estimated contagion took place on January 28, 2020 (95% CI: January 21 to February 16), that is, 36 days before the official date. In Chile, the situation is similar. During the first wave SRM accounted for 70%–76% of those infected in Chile, while from August 2020 onwards it accounted for 36%–39%. Conclusions: The official records of COVID-19 infections in SRM and Chile underestimated the real number of positives and showed a delay of about a month in the dynamics of infections. This is not an isolated situation, as it is known to have been the case in other countries as well. However, it is important to have reliable estimates for a correct modeling of the spread of the virus.(AU)

Correlation between Health and eHealth Literacy and a Healthy Lifestyle: A Cross-Sectional Study of Spanish Primary Healthcare Patients.

BACKGROUND: Health literacy and eHealth literacy play a crucial role in improving a community's ability to take care of themselves, ultimately leading to a reduction in disparities in health. Embracing a healthy way of living is vital in lessening the impact of illnesses and extending one's lifespan. This research delves into the link between the health and eHealth literacy levels of individuals accessing primary healthcare services and investigates how this relates to adopting a health-conscious lifestyle. METHODS: The approach involves a cross-sectional examination carried out at a healthcare facility in the Madrid region of Spain, focusing on adult patients who are in need of primary care nursing services. Health and eHealth literacy and a healthy lifestyle were measured using the Health Literacy Questionnaire (HLQ), the eHealth Literacy Questionnaire (eHLQ), and the "PA100" questionnaire, respectively. RESULTS: Only some of the dimensions of the HLQ and eHLQ were significantly related to a healthy lifestyle, predominantly with a very low or low relationship. Dimension three of the HLQ and dimension five of the eHLQ acquired more importance and were positioned as positive predictors of a healthy lifestyle. CONCLUSIONS: This study helps comprehend the relationship between health and eHealth literacy and a healthy lifestyle, which provides information that contributes to understanding the factors that might have a higher impact on lifestyles.

Latitude and longitude as drivers of COVID-19 waves' behavior in Europe: A time-space perspective of the pandemic.

BACKGROUND: Social restrictions and vaccination seem to have shaped the pandemic development in Europe, but the influence of geographical position is still debated. This study aims to verify whether the pandemic spread through Europe following a particular direction, during the period between the start of the pandemic and November 2021. The existence of a spatial gradient for epidemic intensity is also hypothesized. METHODS: Daily COVID-19 epidemiological data were extracted from Our World in Data COVID-19 database, which also included vaccination and non-pharmacological interventions data. Latitude and longitude of each country's centroid were used as geographic variables. Epidemic periods were delimited from epidemic surge data. Multivariable linear and Cox's regression models were performed for each epidemic period to test if geographical variables influenced surge dates. Generalized additive models (GAM) were used to test the spatial gradient hypothesis with three epidemic intensity measures. RESULTS: Linear models suggest a possible west-east shift in the first epidemic period and features a significant association of NPIs with epidemic surge delay. Neither latitude nor longitude had significant associations with epidemic surge timing in both second and third periods. Latitude displays strong negative associations with all epidemic intensity measures in GAM models. Vaccination was also negatively associated with intensity. CONCLUSIONS: A longitudinal spread of the pandemic in Europe seems plausible, particularly concerning the first wave. However, a recurrent trend was not observed. Southern Europe countries may have experienced increased transmissibility and incidence, despite climatic conditions apparently unfavourable to the virus.

Design and Content Validation using Expert Opinions of an Instrument Assessing the Lifestyle of Adults: The 'PONTE A 100' Questionnaire.

Lifestyle, a major determinant of health status, comprises a number of habits and behaviours that form a part of daily life. People with healthy lifestyles have a better quality of life, suffer less disease, and have a longer life expectancy. This work reports the design and content validation of a questionnaire-the 'PONTE A 100' questionnaire-assessing the lifestyle of adults. This collects information across five dimensions-'Eating Habits', 'Physical Activity', 'Smoking and use of Alcohol and other Drugs', 'Emotional Wellbeing', and 'Safety and Non-intentional Injuries'-via the answering of a total 33 items. Psychometric validation of the instrument's content was obtained via expert opinions. This was performed by two rounds of assessment and involved 34 experts representing different health science disciplines (mean experience, 27.4 ± 9.4 years). At the end of each round, adjustments were made according to their recommendations. Agreement between the experts was examined using the Aiken V test. A final V value of 0.95 (95% CI, 0.90-1.00) was obtained for the questionnaire as a whole, highlighting the validity of its content. The questionnaire would therefore appear to be an appropriate instrument for assessing the lifestyle of adults.

Epidemic thresholds and human mobility.

A comprehensive view of disease epidemics demands a deep understanding of the complex interplay between human behaviour and infectious diseases. Here, we propose a flexible modelling framework that brings conclusions about the influence of human mobility and disease transmission on early epidemic growth, with applicability in outbreak preparedness. We use random matrix theory to compute an epidemic threshold, equivalent to the basic reproduction number [Formula: see text], for a SIR metapopulation model. The model includes both systematic and random features of human mobility. Variations in disease transmission rates, mobility modes (i.e. commuting and migration), and connectivity strengths determine the threshold value and whether or not a disease may potentially establish in the population, as well as the local incidence distribution.

Estimates of mpox effective reproduction number in Spain, April-August 2022.

We analysed the transmission of the human mpox virus in Spain by estimating the effective reproduction number of the disease from official surveillance data. Our computations show that this decreased steadily after an initial burst phase, dropping below 1 on July 12, and thus the outbreak was expected to reduce in the following weeks. Differences in trends were found across geographical regions of the country and across MSM and heterosexual populations.

Epidemic Diffusion Network of Spain: A Mobility Model to Characterize the Transmission Routes of Disease.

Human mobility drives the geographical diffusion of infectious diseases at different scales, but few studies focus on mobility itself. Using publicly available data from Spain, we define a Mobility Matrix that captures constant flows between provinces by using a distance-like measure of effective distance to build a network model with the 52 provinces and 135 relevant edges. Madrid, Valladolid and Araba/Álaba are the most relevant nodes in terms of degree and strength. The shortest routes (most likely path between two points) between all provinces are calculated. A total of 7 mobility communities were found with a modularity of 63%, and a relationship was established with a cumulative incidence of COVID-19 in 14 days (CI14) during the study period. In conclusion, mobility patterns in Spain are governed by a small number of high-flow connections that remain constant in time and seem unaffected by seasonality or restrictions. Most of the travels happen within communities that do not completely represent political borders, and a wave-like spreading pattern with occasional long-distance jumps (small-world properties) can be identified. This information can be incorporated into preparedness and response plans targeting locations that are at risk of contagion preventively, underscoring the importance of coordination between administrations when addressing health emergencies.

Factors Influencing eHealth Literacy among Spanish Primary Healthcare Users: Cross-Sectional Study.

BACKGROUND: Adequate eHealth literacy levels empower people to make informed decisions, enhancing their autonomy. The current study assessed a group using primary care services for their eHealth literacy and examined its relationship with sociodemographic characteristics. METHODS: Adult patients in need of primary care nursing services participated in this cross-sectional study, which was carried out in a healthcare center in the Madrid region of Spain. Through systematic random sampling, 166 participants were chosen for the study. The eHealth Literacy Questionnaire was used to assess eHealth literacy (eHLQ). RESULTS: The studied population showed higher eHealth literacy scores in dimensions 2 ("understanding of health concepts and language") and 4 ("feel safe and in control"); the lowest scores were recorded for dimensions 1 ("using technology to process health information"), 3 ("ability to actively engage with digital services"), and 7 ("digital services that suit individual needs"). People with completed secondary education and a better-perceived health status who were younger and employed showed a higher level of eHealth literacy. CONCLUSIONS: The findings advance our knowledge of the variables affecting eHealth literacy. We may be able to understand patients' needs and provide them with greater support if we can pinpoint the areas where they demonstrate the lowest eHealth literacy.

Health Promotion and Hydration: A Systematic Review About Hydration Care.

AIM: Hydration and well-being are highly correlated. However, practice tells us that the significance of hydration is often unrecognized and is not treated as a priority. This review focuses on how health education can improve hydration levels among the adult population. METHOD: The research question of the study is "Can health promotion improve hydration among adults?" A total of 934 papers were screened using search engines such as CINAHL, COCHRANE, PUBMED, EMBASE, and Google Scholar. Seventy-two articles were assessed for eligibility and 41 of them were selected for quality appraisal using the Critical Appraisal Skills Program (CASP) Systematic Review Checklist, which left the study with 16 articles to be fully reviewed and included in the study. RESULTS: The findings of the study show that water intervention programs help low-drinker participants to sustainably increase their water intake and maintain their habits through time. There was a sustainable impact on decreasing the number of falls, delirium, and the patient's dependence, with an improvement in their overall condition. CONCLUSION: Dehydration is associated with increased morbidity and mortality and is an easily preventable condition, but is often overlooked. Public awareness and hydration education is needed to promote healthy habits, a subject in which nurses play a role of paramount importance.

Health Literacy and Its Sociodemographic Predictors: A Cross-Sectional Study of a Population in Madrid (Spain).

BACKGROUND: Health literacy enhances a population's self-care capacity and helps to reduce health inequalities. This work examines the health literacy of a population attending primary care services and explores its relationship with sociodemographic factors. METHODS: This cross-sectional study, conducted at a healthcare center in the Madrid region (Spain), involved adult patients requiring primary care nursing services. One hundred and sixty-six participants were recruited via systematic random sampling. Health literacy was measured using the Health Literacy Questionnaire (HLQ). RESULTS: The studied population showed higher health literacy scores for literacy dimensions 1 (feeling understood and supported by healthcare providers) and 4 (social support for health); the lowest scores were recorded for dimensions 5 (appraisal of health information) and 8 (ability to find good health information). People with a better perceived health status showed a higher level of health literacy. People over 65 years of age, those with an incomplete secondary education, and those who were unemployed returned lower scores for several literacy dimensions. CONCLUSIONS: The results contribute to our understanding of the factors that influence health literacy. Identifying the areas in which patients show the poorest health literacy may help us comprehend their needs and better support them.

Identification of the first COVID-19 infections in the US using a retrospective analysis (REMEDID).

Accurate detection of early COVID-19 cases is crucial to reduce infections and deaths, however, it remains a challenge. Here, we used the results from a seroprevalence study in 50 US states to apply our Retrospective Methodology to Estimate Daily Infections from Deaths (REMEDID) with the aim of analyzing the initial spread of SARS-CoV-2 infections across the US. Our analysis revealed that the virus likely entered the country through California on December 28, 2019, which corresponds to 16 days prior to the officially recognized entry date established by the Centers of Disease Control and Prevention. Furthermore, the REMEDID algorithm provides evidence that SARS-CoV-2 entered, on average, a month earlier than previously reflected in official data for each US state. Collectively, our mathematical modeling provides more accurate estimates of the initial COVID-19 cases in the US, and has the ability to be extrapolated to other countries and used to retrospectively track the progress of the pandemic. The use of approaches such as REMEDID are highly recommended to better understand the early stages of an outbreak, which will enable health authorities to improve mitigation and preventive measures in the future.

Assessing the effect of non-pharmaceutical interventions on COVID-19 transmission in Spain, 30 August 2020 to 31 January 2021.

BackgroundAfter a national lockdown during the first wave of the COVID-19 pandemic in Spain, regional governments implemented different non-pharmaceutical interventions (NPIs) during the second wave.AimTo analyse which implemented NPIs significantly impacted effective reproduction number (Rt) in seven Spanish provinces during 30 August 2020-31 January 2021.MethodsWe coded each NPI and levels of stringency with a 'severity index' (SI) and computed a global SI (mean of SIs per six included interventions). We performed a Bayesian change point analysis on the Rt curve of each province to identify possible associations with global SI variations. We fitted and compared several generalised additive models using multimodel inference, to quantify the statistical effect on Rt of the global SI (stringency) and the individual SIs (separate effect of NPIs).ResultsThe global SI had a significant lowering effect on the Rt (mean: 0.16 ± 0.05 units for full stringency). Mandatory closing times for non-essential businesses, limited gatherings, and restricted outdoors seating capacities (negative) as well as curfews (positive) were the only NPIs with a significant effect. Regional mobility restrictions and limited indoors seating capacity showed no effect. Our results were consistent with a 1- to 3-week-delayed Rt as a response variable.ConclusionWhile response measures implemented during the second COVID-19 wave contributed substantially to a decreased reproduction number, the effectiveness of measures varied considerably. Our findings should be considered for future interventions, as social and economic consequences could be minimised by considering only measures proven effective.

Caveats on COVID-19 herd immunity threshold: the Spain case.

After a year of living with the COVID-19 pandemic and its associated consequences, hope looms on the horizon thanks to vaccines. The question is what percentage of the population needs to be immune to reach herd immunity, that is to avoid future outbreaks. The answer depends on the basic reproductive number, R0, a key epidemiological parameter measuring the transmission capacity of a disease. In addition to the virus itself, R0 also depends on the characteristics of the population and their environment. Additionally, the estimate of R0 depends on the methodology used, the accuracy of data and the generation time distribution. This study aims to reflect on the difficulties surrounding R0 estimation, and provides Spain with a threshold for herd immunity, for which we considered the different combinations of all the factors that affect the R0 of the Spanish population. Estimates of R0 range from 1.39 to 3.10 for the ancestral SARS-CoV-2 variant, with the largest differences produced by the method chosen to estimate R0. With these values, the herd immunity threshold (HIT) ranges from 28.1 to 67.7%, which would have made 70% a realistic upper bound for Spain. However, the imposition of the delta variant (B.1.617.2 lineage) in late summer 2021 may have expanded the range of R0 to 4.02-8.96 and pushed the upper bound of the HIT to 90%.

Weather Variables Associated with Spore Dispersal of Lecanosticta acicola Causing Pine Needle Blight in Northern Spain.

In the last decade, the impact of needle blight fungal pathogens on the health status of forests in northern Spain has marked a turning point in forest production systems based on Pinus radiata species. Dothistroma needle blight caused by Dothistroma septosporum and D. pini, and brown spot needle blight caused by Lecanosticta acicola, coexist in these ecosystems. There is a clear dominance of L. acicola with respect to the other two pathogens and evidence of sexual reproduction in the area. Understanding L. acicola spore dispersal dynamics within climatic determinants is necessary to establish more efficient management strategies to increase the sustainability of forest ecosystems. In this study, spore counts of 15 spore traps placed in Pinus ecosystems were recorded in 2019 and spore abundance dependency on weather data was analysed using generalised additive models. During the collection period, the model that best fit the number of trapped spores included the daily maximum temperature and daily cumulative precipitation, which was associated to higher spore counts. The presence of conidia was detected from January and maximum peaks of spore dispersal were generally observed from September to November.

Identification of the first COVID-19 infections in the US using a retrospective analysis.

Accurate detection of early COVID-19 cases is crucial to drastically reduce infection, hospitalization, and death rates. However, it remains a challenge and methods for identifying initial COVID-19 cases are urgently needed. Here, we used the results from a seroprevalence study in 50 US states to apply our Retrospective Methodology to Estimate Daily Infections from Deaths (REMEDID) with the aim of analyzing the initial stages and spread of SARS-CoV-2 infections across the United States (US). Our retrospective data analysis revealed that the virus likely entered the country through California on December 28, 2019, which corresponds to 16 days before the officially recognized entry date established by the CDC. Thus, REMEDID provides evidence that SARS-CoV-2 entered the U.S. earlier than previously reflected in official data. Collectively, our mathematical modeling more accurately estimates the initial COVID-19 cases in the US, may be extrapolated to other countries, and may be used to retrospectively track the progress of the pandemic. Approaches such as REMEDID may enable health authorities to accelerate preventative measures aimed at controlling pandemics within weeks of their onset.

Retrospective methodology to estimate daily infections from deaths (REMEDID) in COVID-19: the Spain case study.

The number of new daily infections is one of the main parameters to understand the dynamics of an epidemic. During the COVID-19 pandemic in 2020, however, such information has been underestimated. Here, we propose a retrospective methodology to estimate daily infections from daily deaths, because those are usually more accurately documented. Given the incubation period, the time from illness onset to death, and the case fatality ratio, the date of death can be estimated from the date of infection. We apply this idea conversely to estimate infections from deaths. This methodology is applied to Spain and its 19 administrative regions. Our results showed that probable daily infections during the first wave were between 35 and 42 times more than those officially documented on 14 March, when the national government decreed a national lockdown and 9 times more than those documented by the updated version of the official data. The national lockdown had a strong effect on the growth rate of virus transmission, which began to decrease immediately. Finally, the first inferred infection in Spain is about 43 days before the official data were available during the first wave. The current official data show delays of 15-30 days in the first infection relative to the inferred infections in 63% of the regions. In summary, we propose a methodology that allows reinterpretation of official daily infections, improving data accuracy in infection magnitude and dates because it assimilates valuable information from the National Seroprevalence Studies.

Risperidone administered during adolescence induced metabolic, anatomical and inflammatory/oxidative changes in adult brain: A PET and MRI study in the maternal immune stimulation animal model.

Inflammation and oxidative stress (IOS) are considered key pathophysiological elements in the development of mental disorders. Recent studies demonstrated that the antipsychotic risperidone elicits an antiinflammatory effect in the brain. We administered risperidone for 2-weeks at adolescence to assess its role in preventing brain-related IOS changes in the maternal immune stimulation (MIS) model at adulthood. We also investigated the development of volumetric and neurotrophic abnormalities in areas related to the HPA-axis. Poly I:C (MIS) or saline (Sal) were injected into pregnant Wistar rats on GD15. Male offspring received risperidone or vehicle daily from PND35-PND49. We studied 4 groups (8-15 animals/group): Sal-vehicle, MIS-vehicle, Sal-risperidone and MIS-risperidone. [18F]FDG-PET and MRI studies were performed at adulthood and analyzed using SPM12 software. IOS and neurotrophic markers were measured using WB and ELISA assays in brain tissue. Risperidone elicited a protective function of schizophrenia-related IOS deficits. In particular, risperidone elicited the following effects: reduced volume in the ventricles and the pituitary gland; reduced glucose metabolism in the cerebellum, periaqueductal gray matter, and parietal cortex; higher FDG uptake in the cingulate cortex, hippocampus, thalamus, and brainstem; reduced NFκB activity and iNOS expression; and increased enzymatic activity of CAT and SOD in some brain areas. Our study suggests that some schizophrenia-related IOS changes can be prevented in the MIS model. It also stresses the need to search for novel strategies based on anti-inflammatory compounds in risk populations at early stages in order to alter the course of the disease.

Pregnancy and adolescence entail similar neuroanatomical adaptations: A comparative analysis of cerebral morphometric changes.

Mapping the impact of pregnancy on the human brain is essential for understanding the neurobiology of maternal caregiving. Recently, we found that pregnancy leads to a long-lasting reduction in cerebral gray matter volume. However, the morphometric features behind the volumetric reductions remain unexplored. Furthermore, the similarity between these reductions and those occurring during adolescence, another hormonally similar transitional period of life, still needs to be investigated. Here, we used surface-based methods to analyze the longitudinal magnetic resonance imaging data of a group of 25 first-time mothers (before and after pregnancy) and compare them to those of a group of 25 female adolescents (during 2 years of pubertal development). For both first-time mothers and adolescent girls, a monthly rate of volumetric reductions of 0.09 mm3 was observed. In both cases, these reductions were accompanied by decreases in cortical thickness, surface area, local gyrification index, sulcal depth, and sulcal length, as well as increases in sulcal width. In fact, the changes associated with pregnancy did not differ from those that characterize the transition during adolescence in any of these measures. Our findings are consistent with the notion that the brain morphometric changes associated with pregnancy and adolescence reflect similar hormonally primed biological processes.