❤❤❤ Chae Chan Pang V. United States Case Study

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Chae Chan Pang V. United States Case Study on tumor biopsies taken about Chae Chan Pang V. United States Case Study weeks before, and then after surgery, women in the flaxseed group showed decreased tumor proliferation, increased cancer Chae Chan Pang V. United States Case Study death rate, and lower c-erB2 scores which is a marker of Chae Chan Pang V. United States Case Study aggressiveness. Interestingly, Chae Chan Pang V. United States Case Study Frank Costello Research Paper, obtained via an Chae Chan Pang V. United States Case Study Advantages of application forms model, suggest that the epidemiological markers of COVID are consistent with those observed in other countries and that the observed pattern is compatible with a low case detection, late Personal Narrative: Native American Colonies importation, and effective NPIs. JAMA Chae Chan Pang V. United States Case Study The second Womens Suffrage Thesis was conducted in 21 oncological care institutions in 10 countries. From the Mayo Clinic Executive Summary thus far, it is clear that Chae Chan Pang V. United States Case Study and elderly are at high risk for zinc deficiency, which is associated with the impaired immune function contributing Chae Chan Pang V. United States Case Study the increased morbidity and mortality from infections in these populations. In addition, sometimes altered cytokine levels may not necessarily tell the situation in their synthesis. Rev Med Pyotr Tchaikovsky Research Paper.

Lockhart v. United States Case Brief Summary - Law Case Explained

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Home Articles Article. Open Access Review. Views: Downloads: Cited: Mariah Madigan 1 , Elisa Karhu 2. Views Downloads Cited: 12 Comments:0 : 3. Abstract Plant-based nutrition has been shown to protect against the 15 leading causes of death in the world, including many cancers, and may offer benefits as a disease modifying tool to improve the management and treatment of these conditions. Plant-based nutrition and breast cancer Next to skin cancer, the most common cancer among American women is breast cancer. Heterocyclic amines and breast cancer Another substance besides IGF-1 that is found in animal products and contributes to cancer risk is heterocyclic amines HCAs.

Soy and breast cancer One way researchers discovered the effects of soy on breast cancer risk, is through population studies. Plant-based nutrition and prostate cancer It is estimated that in , approximately 1,, new cases of prostate cancer will be diagnosed, , will die from the disease [ 83 ]. Diet vs. Prostate cancer regression via nutritional intervention In Dr. Plant-based nutrition and colorectal cancer Colorectal cancer CRC is the third most common cancer in men and the second most common cancer in women worldwide with more than half of cases occurring in developed countries. Plant-based nutrition and other cancers Plant-based diets have also been shown to offer protection against a myriad of other GI and non-GI cancers.

Conclusion Diet is one of the main causes of premature death and disability in developed countries and contributes to the burden of cancers commonly encountered in Western society. Financial support and sponsorship None. Conflicts of interest All authors declared that there are no conflicts of interest. Ethical approval and consent to participate Not applicable.

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Regulatory activity of polyunsaturated fatty acids in T-cell signaling. Prog Lipid Res. Shaikh SR, Edidin M. Polyunsaturated fatty acids, membrane organization, T cells, and antigen presentation. N-3 polyunsaturated fatty acids modulate B cell activity in pre-clinical models: implications for the immune response to infections. Eur J Pharmacol. The model considers as subpopulation the municipalities of the capital of Chile and adopts data from mobile phones to estimate the mobility flows as well as their changes induced by NPIs.

The model suggests that only the compound effects of subsequent measures was enough to suppress the epidemic. Furthermore, the results confirm how even in this country individuals from municipalities characterized by low Human Development Index HDI were not able to reduce their mobility as those living in high HDI locations. As result of these socio-economic factors poor areas registered higher cases and deaths. In doing so, they adopt the radiation model to estimate the mobility between subpopulations [] before and during the pandemic. They investigate different scenarios considering moderate to strong physical distancing. The results indicate that the scenario closer to the observation is the one with moderated physical distancing of people younger than 60, very strong distancing of those older than 60 as well as a general awareness and compliance to home isolation if symptomatic.

Hence, this confirms how despite the lack of strict top-down NPIs respect to many other countries the Swedish population did change behavior. Unfortunately the health outcome was still much worse than other nordic countries which took a suppression rather than a mitigation approach. The authors consider the state divided in small cells m x m which are the nodes of the metapopulation system. Mobility is modeled considering a density function. While typically metapopulation models consider mobility at the aggregated level of compartment e. In doing so, they are able to study the role of super-spreaders events.

Also, infected non-elderly might be about three times more infectious than elderly thus driving the super-spreading events. By using an Markov chain approach the authors are able to derive analytical expressions for the reproductive number as function of different types of NPIs. Furthermore, they show how the model can be calibrated to reproduce the observed evolution of the pandemic in the country. The approaches described above model the spreading of infectious diseases mechanistically. Real epidemiological data is then used to constrain the phase space of parameters.

Statistical inference approaches are then used to determine the parameters modulating such relationships. Let us dive into some details. The authors assume that the number of infections in a country m at time t can be written as:. Hence, the new number of infected individuals is function of how many have been infected in the past modulated by the generation distribution and the average number of infections each of these is able to produce. The authors consider six types of NPIs: school closures, self-isolation of symptomatic, banning of public events, partial or complete lockdown, social distancing, and any other government intervention.

They then assume the effect of such interventions to be multiplicative and such that:. The parameters are fitted for all 11 countries in a single hierarchical model. The results show that the portfolio of measures put in place was enough to suppress the epidemic. Lockdowns are found to be the most significant NPIs in terms of variations to the R t.

The same model, extended to consider more data such as hospitalizations and ICU patients, has been proposed for Slovenia []. The results suggest that the country has the smallest attack rate in Europe 0. A similar model has been also applied to the case of Brazil []. The estimation of the R t points to the fact that the measures put in place were not enough to suppress the spreading, but were able to mitigate it. The authors consider also genomic data to shed light on the start of the local epidemic. The results point to the fact that the majority of importations in the genomic sample are linked to Europe and the local spreading was in place before the implementation of travels bans.

A model with the same approach has been also proposed in Ref. Interestingly the results show how across the board reduction of gatherings to ten or less, school closure and remote working had the largest impact on the reproductive number. A model based on a renewal process has been also proposed in Ref. Authors define the reproductive number at time t for country m as:. The model is applied to 11 European countries and confirms the importance of NPIs in the mitigation and suppression efforts. Interestingly, the model suggests that most significant variations in mobility are linked to groceries and pharmacies.

However, variations of mobility to all categories of place are shown to be highly correlated with disease burden measured in terms of deaths with a delay of one month. Authors in Refs. This method is readily available in Python and R and is called EpiEstim. Without going to the details, the approach assumes that the number of case is extracted from a Poisson distribution providing an expression linking the probability of observing a number of cases in a time window given the R t.

This allows to apply Bayesian inference from data having as target R t. Interestingly they found social distancing to be the most efficient in reducing the reproductive number followed by mandatory masks. Furthermore, they confirm that a portfolio of measures is required to suppress the spreading. Similar results have been reported in Ref. Beside estimating the effects of NPIs the authors report also the result of three surveys which show high level of awareness and adoption of NPIs such as face mask and avoid crowded places. The results highlight the effectiveness of the aggressive NPIs strategy put in place and point to a very different confirmed case fatality ratio in Hubei and outside.

In the epicenter of the pandemic it appears to be five times higher than outside. Hence, this model could be classified as a compartmental model. However as it does not match directly any archetype I opted to add it to this category. The model is fitted to data from China, Iran, Italy and South Korea with the aim to characterize the impact of NPIs in those countries and project possible attack rates. Agent-based models push the mechanistic approach to its limit. In fact, they simulate the spreading of disease reproducing, to different extents, key aspects of the society where the disease is spreading.

In particular, classic epidemiological agent-based models are based on a synthetic population that is built considering empirical socio-demographic features such as households sizes and compositions. A key aspect for the spreading of diseases are social contacts which are built accounting for socio-economic activities such as school, work places, and other types of activities. The nature of agent-based models requires a much wider range of data necessary to build the synthetic population and its interactions.

The computational costs associated are also much more significative. A large body of literature has been devoted to study the effects of considering real social contact networks on the spreading of infectious diseases [] , []. These agent-based models do not typically account for all societal details such as households, schools and work places. As such they are not typically used to make accurate predictions but rather to develop a better understanding of how the features of real contact networks might affect the unfolding of a virus. They have been used to quantify the effects of contact tracing, isolation, vaccination campaigns among other things.

In the sample of papers under review here, we find full fledged agent-based models used to model the COVID and the effects of NPIs at the levels of countries, regions, or cities [63] , [66] , [] , [] , [] , []. We also find more theoretical approaches modeling particular aspects of NPIs such as different strategies for isolation [] , [] , []. This is a text book example of this category of models. The first important point to mention is the complexity of the approach which is exemplified by the number of parameters: in total.

The majority are to describe the socio-demographic features of the french population, 33 are to model the contact networks, 21 to describe the features of the virus. The two remaining, which describe the contamination risk per minute per m 2 of contact and the fraction of undiagnosed cases, have been fitted to mortality data. In the model households are assigned to a square grid. These are built considering a stratification which include age and gender to reproduce the french population.

Furthermore, comorbidities e. The contact network is built taking into consideration several types of interactions taking place at home, in school, work, as well as during other locations such as groceries. The construction of such synthetic population allows to model with high resolution several NPIs such as reopening of particular activities or isolation approaches. The results, which where published in July, paint quite a grim picture which unfortunately has been later confirmed: measures in place after the strict lockdown is lifted are not enough to avoid the overwhelming of the healthcare system.

A similar approach has been proposed in Ref. The authors use high resolution data describing the movements and potential interactions of people in Boston. They build a multilayer synthetic population which models the socio-demographic features of Bostonians, their movements and possible interactions in different locations i. The authors use the model to investigate the impact of different reopening scenarios. The results suggest that aggressive testing and household isolation could allow to reopen economic activities while keeping the health care facilities protected from overflow of cases.

They model is informed with mobile phone data collected from about , users by Cuebiq. The authors, similar to what done for Boston, built a weighted layered network capturing interactions in the community, schools, work places, and households. Furthermore, they use foursquare data to identify POIs. The results show the impact of NPIs in the two cities, provide information about the risk of infection according to the type of locations visited and estimate the size of transmission chains.

Despite the big role played by large social event, the authors found that work places, restaurants, and grocery stores are the main drivers of the observed patterns. The model nicely show how the details can be adapted to the goal and data available. The authors built synthetic populations form by n individuals stratified for age, comorbidities and assigned to a household. Contacts are divided in two category: inside and outside households. Contacts in different contexts than home are modeled via contact matrices.

The free parameters are fitted to data using a Bayesian framework. The results show how the efficacy of NPIs aimed at limiting contacts across age brackets vary according to the location under study. This suggests how a one fit all strategy might not be optimal and measures should be tailored to the specific socio-demographic features of each populations. The authors model interactions within and across cities. These are modeled as clustered networks. Links inside each community are extracted from a configuration model.

Links across communities assume an homogenous random graph. Connections between cities are built considering real data from Baidu. Since the units of the model are individuals, the number of travelers from city i and j are assigned randomly to nodes in i. These form a number of connections, which is the average in the system, with random nodes in j. The population is scaled down to reduce the computational costs. This model does not consider explicitly the stratification of individuals in households, school or work locations.

The results obtained confirm the importance of NPIs in controlling the pandemic in China. Each type of agent is assigned with a set of features and enabled to take a set of actions. The framework allows for the implementation of a range of NPIs and measure the impact in terms of disease and economic burden. The seismic impact of COVID on our society has dramatically boosted the study of non-pharmaceutical interventions via explicit observations: surveys. This methodology allows to gather ground truth data by asking specific questions to a sample of the population rather than inferring answers from proxy data.

Hence, they are a powerful tool to understand and measure causal links. In the era of big-data surveys might look old fashion and surpassed. However they are still an invaluable approach to characterize complex processes. The sample size is typically an issue castings doubts about the external validity of the findings. However, modern technology and having a larger part of the population stuck at home in front of a screen due to lockdowns offered the opportunity to reach large numbers of participants quite easily. Before diving into the observations and results of this large body of research, let me spend few words to characterize the subset.

First of all, it is interesting to notice how the surveys have been answered by participants in 85 countries. While in the large majority of cases the survey targeted a specific country, four surveys were done in two countries, two in five, one was extended to participants in 59 countries. This top three is not surprising. China was the epicenter of the pandemic. Italy was the first country in Europe to be affected by the virus. USA is a powerhouse of scientific production and one of the most affected countries in the pandemic.

In Fig. All continents, except Antarctica, are represented. Third, 41 countries are found in the affiliations of this group of papers. Fourth, the research has been published in 65 different journals including 2 preprint in the medRxiv not yet published elsewhere. It is interesting to stress the diversity of the set of publication venues that ranges from Nature Human Behavior and Science to Journal of Medical Internet Research and Seizure. This, still limited sample, highlights the breadth of research on the subject. Finally, these papers have been written by more than authors and, as of December 19th they received citations. See Fig. Total number of articles, sub-categories, authors, and citations of the papers in this category on the left.

On the right main panel histogram describing the number of countries subject of study in this category. On the right in-set most represented publication venues of the category. To improve visibility I am showing only countries featured at least in two studied and journals featuring at least two articles. After inspecting all the articles and considering their focus, I have assigned each survey to one of five categories.

Health and wellbeing indicators : surveys aimed at monitoring, measuring or access the impact of NPIs on health and wellbeing;. Adoption and awareness of NPI : surveys aimed characterizing the adoption of NPIs identifying the key factors influencing changes in behaviors;. Changes in medical practice : describes studies focused on accessing the impact of NPIs on patients and health care;. Contacts : surveys aimed at quantifying the effects of NPIs on human contacts. It is important to mention that similar topics will be found also in other types of study described in other sections. However, those do not rely on primary data collection methods but on data proxies.

In other words, they use data that have been collected for other uses as proxy for behavioral markers. In Table 3 I report the full list of references organized according the taxonomy I have created. Furthermore, I have grouped the research considering the sample size and the country or countries from where the participants where recruited.

Now, we are ready to dive into each subcategory. Summary of the surveys in the sample of papers. The first column describes the main topic of each survey, the second the subcategory, if any. The third the sample size. Note that for simplicity I have group them in brackets. This body of research aims to characterize the effects of NPIs on i mental health, ii health behaviors, and iii patients. These constitute three subcategories. Let us discuss them in order. It interesting to notice the variety of angles and aspects covered in the surveys on mental health. In fact, they consider loneliness [] , [] , [] , domestic abuse [] , psychological mindset [26] , [] , [] , [] , [] , [] , [] , [] , [] , as well as particular groups of the population studying the toll on frontline workers [] , students [] , [] , parents and children [] , [] , [] , [].

Several common themes as well as some conflicting results emerged from this research. When it comes to loneliness age, gender, and perceived concerns about the pandemic appear to be important factors. In particular, younger individuals, especially female, reported a larger increase in loneliness respect to adults []. Hence, loneliness appears not to be a monotone function of age. Very young and older age classes are more affected by it. Furthermore, loneliness increases more for those reporting greater concerns about the pandemic. However, it is important to notice that while two surveys found an increase of loneliness during the first wave [] , [] , another reported no significant variations from January to April [].

One survey focused on the effect of NPIs on domestic abuse []. The study considers a sample of women living in Jordan contacted via WhatsApp. Being unemployed and married were the most important features linked to abuse. In terms of psychological mindset of participants living under some type of NPIs country of residence, age, gender relationship status, living arrangements, income, and education are important factors [26] , [] , [] , [] , [] , [] , [] , []. In contrast, a survey conducted in Serbia found that worry, fear, boredom, anger, and annoyance decreased in time during the first wave []. Adherence to NPIs and exposure to media were linked to positive effects on worry and fear.

Similarly, a survey aimed at capturing the effect of NPIs on five factor personality traits found that during the crisis neuroticism went down []. The second subcategory describes surveys aimed at capturing the impact of NPIs on a range of health behaviors such as sleep, physical activity, sex, and substance use. Two studies on children noted how COVID restrictions led to less physical activity and sleep disturbances but to more screen and sleeping time [] , []. The findings hint to a complex picture with some positive and negative effects of home confinement.

Physical activity and changes in sleeping patterns have been reported also in the adult population [] , [] , [] , [] , []. A sample of more than participants in the UK provides some hints about the magnitude of physical activity variation before and during the lockdown []. Overall, the surveys on the subject highlight high BMI, depression, health conditions, gender being female , and high risk perception as features connected to larger decrease of physical activity [] , []. Being an essential worker negatively impacted lifestyle []. Social distancing and stay home orders affected also other health behaviors such as sex and substance use.

Two surveys done in Australia and USA show how NPIs have led to drastic reduction of sex with occasional partners and an increase of porn consumption [] , []. Alcohol consumption, above the drinking limits, has reported to increase during NPIs []. The tsunami of COVID cases that flooded health care facilities had a drastic impact also on patients affected by other conditions. Several surveys aimed at providing a better understanding of this unfortunate phenomenon.

They considered patients affected by diabetes, cancer, ALS, hypertension, mental or substance abuse disorders [] , [] , [] , [] , [] , [] , []. Admittedly, the research focused on short term effects and on the shift towards telemedicine i. A study conducted in Italy on diabetic patients revealed their good resilience and adaptation to technology []. However, a similar research done in Japan hints to a negative impact of reduced physical activity on glycemic control []. A cohort of patients affected by cancer in Germany showed levels of stress and anxiety similar to a control []. Drastic reduction of physical activity, with potentially detrimental effects, has been reported for adults with hypertension []. Several interesting themes emerge from the surveys aimed at understanding the factors driving the adoption of NPIs.

First of all, across several countries and in different studies gender appears to be a key factor. Similar trends are observed for individuals with high level of education [] , []. Age again does not appear to be a monotonic function: very young and old individuals share similar trends. In fact, young adults have reported a smaller decrease in mobility and old individuals less compliance to NPIs especially if male [] , []. It is important to mention that age was not a relevant factor in a survey conducted in Germany []. The research points also to a big urban—rural division and thus to the importance of socio-economic factors when it comes to compliance.

In fact, several barriers to NPIs have been reported in peri-urban and rural areas in India [] , [] , []. Individuals living in urban settings report a better knowledge about COVID and better opportunities to adopt hygienic behaviors. The country of residence also seems to play a role when it comes to the trust level towards media during the emergency which might influence adoption. A cohort in Jordan reported a positive influence, especially on the awareness levels []. However, a survey in Slovenia, done with 48 of the first confirmed case, points to low level of trust of the media and shows that perceived credibility of information linked to lower levels of negative emotional response and higher adherence to NPIs [].

Interestingly social distancing and practicing other transmission reducing behaviors increased significantly during the COVID pandemic. The subset of participants with a higher perception of risk was found to be more likely to adopt NPIs in both. Interestingly, several surveys confirm the expectation coming from the health belief model pointing to the fact that knowledge about the disease and perceived risks are predictors behavioral changes [] , [] , [] , [] , [] , [] , []. The adoption of face masks has been found to be negatively affected by perception of shortage in New Zealand [] , and positively influenced by national guidelines in the USA []. The app collects a range of demographic, symptoms, and behavioral data such as use of masks and social distancing practices.

Though the aim of the paper is to investigate whether the data collected can be used to estimate risk factors and exposure to the virus, it provides interesting insights about the behavior of the sample in terms of NPIs. Of this subset of people that left home the majority reported to practice social distancing and wearing face masks. Though still a significant fraction did not. A minority of users reported that, despite testing positive, they went to work sometime without wearing a mask. Healthcare and essential workers were more likely to go to work after testing positive. Though, people who tested positive, reported a clear reduction of contacts with respect to those that were untested or tested positive.

A very interesting subset of surveys provides some answers from both patients and doctors. I have identified three subcategories which refer to mental health, oncology and other medical specialties. A survey among psychotherapists in Austria revels that the decrease of face-to-face appointments was not necessarily linked to an increase of remote sessions []. Similarly, another in Italy reports the needs for more health care support [].

Even more concerning are the results of a survey that pooled participants in 29 countries []. These are the caregivers of individuals with intellectual and developmental disabilities. Across several surveys, telemedicine has been found to be useful [] , [] , []. Though, socio-economic disparities, linguistic disadvantage, and health issues have been reported as challenges of remote care. It is also interesting to notice the perception of telemedicine among practitioners [] , []. Rapid transitions towards it, reduce revenue and modification of communication linked to it have been reported as challenges []. Furthermore, the judgment of the transition appears to be function of the number of patients supported [].

In the second subcategory we have two surveys dealing with changes in oncology care. The first used WhatsApp to explore the topic covered in discussions between patients and doctors. The most common themes that emerged cover delays with care, queries about immunosuppression, and variation of lifestyle or activities []. The second survey was conducted in 21 oncological care institutions in 10 countries. Adoption of PPE was used across the board and only few clinical instrumental examination were performed. In the third and final subcategory we find surveys targeting both patients and practitioners in a variety of specializations. Overall the observations on patients point to the interim efficacy of telemedicine and to high level of awareness about the risk of infection.

The findings on medical practices highlight the drastic changes and adaption put in place to cope with the pandemic. Marked reduction of in person visits, stockpile of PPE and use of respiratory isolation units have been reported. This group of surveys captures the impact of NPIs of a range of human activities such as i leisure, ii education, iii mobility, and iv consumption.

Due to social distancing, travel limitation, and stay home orders the possibility for leisure has been dramatically reduced. A survey done in a cohort of around participants in 25 countries investigates the impact on bird watchers []. They reported also a significant change in social interactions. The increase of time spent inside has induced variations in the locations selected when going outside []. Walking paths have been changed to include urban gardens, tree lined streets and traveling by car in green areas. In others words, the confinement has boosted the interest and value of nature. The stop of many sport events and leagues has impacted also gambling [].

While sport gambling has dropped, the attention has been shifted towards other forms. The gambling habits of the majority of respondents to another survey reported did not report a change in gambling habit []. However, the minority that did was affected by gambling problems and reported an increase in alcohol consumption. The toll of NPIs on sport activities has been quite significant for elite athletes [] , []. Level of stress and anxiety have been observed, especially among women, and linked to worries about the future of the sport.

A survey conducted in South Korea links the tendencies towards keeping practicing sport with the perception of risk and worry about getting infected []. Age and the type of sport were found to play a modulating role. Educational activities have been also altered. Like in many other sectors the need for physical distancing required drastic shifts in the delivery of classes as well as on research production. A survey conducted in China extended to parents, students and teachers point to the fact that while online teaching was positively valued, parents and teachers were found to be more concerned about the possible side effects []. A survey delivered in a cohort of students in Jordan aimed to understand the impact of remote learning and in particular on online exams [].

Navigation of questions and technical issues were reported to be main drivers of stress. Furthermore, online exams appeared to affect negatively eating habits, sleep, physical activity and led to increase in smoking. A study conducted on principal investigators in USA and Europe, point how NPIs, despite the reduction of activities outside home, have reduced the time spent doing research especially for female scientists, those in experimental fields and with young children []. As we will see in more details later, one of the most explored aspect of non-pharmaceutical interventions is mobility. As result, we will speak about NPIs and mobility in several sections.

Though the aim will be the same, what changes is the methodology used to characterize changes in mobility. Here, we report two studies done with cohort of individuals in Germany [] and more than people in five European countries []. In both cases, smartphone apps were used to collected information about mobility distance traveled, steps count as well as other indicators heart rate, sleep duration, bedtime, social app use.

The reduction did not cease immediately after the end of lockdown. Age and gender groups behaved similarly, reporting a consistent relative variation respect to pre lockdown period. Reduction of steps and increase homestay have been reported also outside Germany []. Furthermore, use of phone and social media apps have increased. Consistently with what mentioned above, sleeping patterns have been altered.

More sleep and later bed time have been reported []. NPIs are designed to reduce transmission chains. Hence, several targeted directly or indirectly social contacts. Different surveys have been designed and deployed to capture the effect of NPIs on contacts and thus estimating the impact on the disease spreading. A survey conducted in Wuhan and Shanghai during the outbreak revealed a reduction of factor 7—8 of social contacts [25]. Using this data together with information about contact tracing the authors estimated, via an epidemic model, this reduction was enough to contain the spreading. A similar study conducted during the lockdown in the UK report consistent, though smaller, reduction contacts a factor 4 [27].

Nevertheless the change was enough to push the R 0 below the critical threshold of one. Here researchers reflect on future challenges, point out opportunities, summarize findings and approaches developed in the fight against COVID In doing so, they do not necessarily present new analysis or findings. Rather, the goal is to highlight key aspects, draw the attention to specific points, critically discuss evidence, questions assumptions as experts in the field.

Before summarizing this body of work, let me spend few words to provide a general description of it. While the large majority of articles provide a general outlook to a specific topic, some draw from a specific context. In fact, we find 6 comments focused from observations in USA [] , [] , [] , [] , [] , [] , 3 in Italy [] , [] , [] , 2 in Canada [] , [] and the UK [] , []. Comments and perspectives have been written by researchers with affiliations in 36 countries see Fig. Finally, this research has been published in 50 journals including one preprint in medrxiv.

Really a wide range of publication avenues ranging from journals focusing on pediatric psychology to interdisciplinary journals such as Science Advances. These papers have been written by more than authors and received more than citations. A median of 4 citations per article. The first column describes the category of each article in this group. The second, the topics and references. Change to medical practice : describe articles that analyze challenges and changes to medical procedures made necessary by NPIs;. We find articles focused on a range of medical specialties: mental health care [] , [] , [] , [] , [] , [] , emergency care [] , [] , substance abuse [] , [] , [] , [] , [] , oncological care [] , [] , health care practices [] , [] , [] , [] , [] , [] , pediatric care [] , [] , and other care [] , [] , [] , [] , [] , [].

The observations highlight how the changes in behaviors induced by NPIs shifted the sense of familiarity, predictability or daily activities towards the unknown and drastically limited social support. The variation of ordinary routine is linked to increase distress.

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