In the Greater Mekong Subregion (GMS), forest-going populations are considered high-risk populations for malaria and are increasingly targeted by national control programmes’ elimination efforts. A better understanding of forest-going populations’ mobility patterns and risk associated with specific types of forest-going trips is necessary for countries in the GMS to achieve their objective of eliminating malaria by 2030.Between March and November 2018, as part of a focal test and treat intervention (FTAT), 2,904 forest-goers were recruited in southern Lao PDR. A subset of forest-goers carried an “i-Got-U” GPS logger for roughly 2 months, configured to collect GPS coordinates every 15 to 30 min. The utilization distribution (UD) surface around each GPS trajectory was used to extract trips to the forest and forest-fringes. Trips with shared mobility characteristics in terms of duration, timing and forest penetration were identified by a hierarchical clustering algorithm. Then, clusters of trips with increased exposure to dominant malaria vectors in the region were further classified as high-risk. Finally, gradient boosting trees were used to assess which of the forest-goers’ socio-demographic and behavioural characteristics best predicted their likelihood to engage in such high-risk trips.A total of 122 forest-goers accepted carrying a GPS logger resulting in the collection of 803 trips to the forest or forest-fringes. Six clusters of trips emerged, helping to classify 385 (48%) trips with increased exposure to malaria vectors based on high forest penetration and whether the trip happened overnight. Age, outdoor sleeping structures and number of children were the best predictors of forest-goers’ probability of engaging in high-risk trips. The probability of engaging in high-risk trips was high (~ 33%) in all strata of the forest-going population.This study characterized the heterogeneity within the mobility patterns of forest-goers and attempted to further segment their role in malaria transmission in southern Lao People’s Democratic Republic (PDR). National control programmes across the region can leverage these results to tailor their interventions and messaging to high-risk populations and accelerate malaria elimination.The online version contains supplementary material available at 10.1186/s12936-023-04468-8. Anopheles dirus and Anopheles minimus  p p37] pacResults are presented using SHAP (SHapley Additive exPlanations) values , an innoOver the course of 8 months, 2904 forest-goers were recruited into the FTAT intervention and 122 carried a GPS logger. In terms of acceptability, the field team reported informally that most forest-goers accepted to carry a GPS logger when offered, with only a few refusals. Using answers in the FTAT survey, Table Two (1.6%) GPS loggers were not returned and data downloading from 5 (4.2%) others failed, resulting in a total of 472,751 GPS points collected from 115 (94.2%) GPS loggers. Figure Data visualization exposed a few GPS points obviously logged incorrectly and the filtering algorithm discarded 1973 (0.4%) data points. Most of the time, these errors occurred while the GPS logger was sitting at forest-goers’ house location, most likely beneath some type of roof that disabled connection with the GPS satellites.Plotting the GPS trajectories also highlighted that forest-goers did not always carry their GPS logger with them. Indeed, some GPS loggers obviously were left at home for weeks at a time. The incentive to give the GPS logger back to the study team after two months may have discouraged forest-goers to take the risk to carry them all the time. Importantly, the study’s instructions insisted primarily on the importance of accurately recording trips to the forest, forest-fringes and rice fields. That is why the analysis focused on outdoor trips rather than on the whole mobility patterns over the two-month study period. In the process, the analysis discarded 95% of the GPS points to focus on the 21,668 (5%) collected along 803 outdoor trips from 96 (79%) forest-goers. The out of the bag error rate of the terrain classification algorithm used to identify outdoor trips was 8.6%.Table The first seven PCs accounted for 96% of the variability in the data and were therefore extracted to summarize the outdoor trips data. The dendogram tree  of the outdoor trips collected were classified as forest trips and just over 10% of outdoor trips happened overnight. Overnight trips are also the longest both in duration and distance covered.Overnight forest trips as well as forest trips and short forest trips that happened around twilight and/or dawn hours (6 pm and/or 6 am) further defined 385 (48%) high-risk trips because of their presumed higher exposure to malaria vectors. Figure Together, these results have identified age, lack of outdoor sleeping structure and number of children as the best predictors of high-risk outdoor trips for malaria. Specifically, being 30 to 45 years old, using no structure when sleeping outside and having more than two children all increase the probability for a forest-goer to engage in high-risk trips in terms of their exposure to malaria vectors. All the other features impact forest-goers’ probability to engage in high-risk trips by less than 5% on average. As a summary, Fig. Using GPS loggers to capture fine-scale mobility patterns of 122 forest-goers in southern Lao PDR over two-month periods, data on 803 trips to the forest, forest-fringes or rice fields were extracted. A hierarchical clustering algorithm was used to describe the heterogeneity within these mobility patterns and highlight six major types of outdoor trips. Using gradient boosting trees, forest-goers’ age, lack of outside sleeping structures and number of children were identified as the best predictors of their likelihood to engage in trips at higher risk for malaria, in terms of an increased exposure to mosquito vectors. Together, these three risk factors defined strata of forest-goers with probability as high as 75% and as low as 33% to engage in such high-risk trips.An. dirus and An. minimus13,14, which thrive in a forested environment and bite during the night and around twilight and dawn hours. This heterogeneity in forest-goers’ outdoor trips and exposure to the surrounding mosquito vectors echoes the result from a recent systematic review that focused on qualitative studies on forest-goers in the GMS [A key finding from this study is the diversity in forest-goers’ mobility patterns highlighted in the cluster analysis. The 803 outdoor trips collected were highly heterogeneous. Some trips lasted no more than 3 h while others lasted up to a week. Distance covered ranged from 1 to 100 km. Most trips were day trips, with only around 10% happening overnight. The average tree crown cover along the trip ranged from 75% down to around 5%, even for long trips. Six clusters of outdoor trips were identified with major differences in terms of forest penetration, distance covered, duration and whether the trip happened overnight. These differences likely translate into different exposures to the dominant malaria vectors in the GMS,  the GMS  and callThis study attempted to leverage this heterogeneity in mobility patterns to segment the population of forest-goers and identify sub-groups at potentially higher risk for malaria because of their increased likelihood to engage in high-risk trips. This study was able to rank individual level characteristics of forest-goers collected in the FTAT survey in terms of their ability to predict their probability to engage in high-risk trips. The top three individual predictors, number of children, lack of outside sleeping structure and age, would impact, on average, forest-goers’ probability to engage in high-risk trips by, 5%, 7% and 17% on the additive scale respectively and together defined strata of forest-goers with probability as high as 75%. In combination, these predictors separated the forest-going population into two subgroups with respective probabilities of engaging in such high-risk trips of 54% across the seven non-reference strata and 33% in the reference strata. This difference in risk could be leveraged to focus resources and efforts on the most high-risk forest-goers but the results also suggest that some level of risk is ubiquitous among forest-goers. In particular, this study failed to identify a very low-risk subgroup and malaria programmes across the GMS would miss some high-risk forest-goers if they were to further segment this population.This study also demonstrated how GPS loggers can be used to measure fine-scale mobility patterns of rural and hard to access forest-going populations in the GMS. Thanks to PNs, we were able to recruit forest-goers in the study and train them on all aspects of the GPS loggers. Acceptability among forest-goers was high and this study proved its feasibility with very few data gaps thanks to the external charging device and additional batteries that were provided with the GPS loggers. GPS coordinates every 15 to 30 min along forest-going trips represent an incredibly rich dataset about forest-goers’ mobility patterns and interaction with their surrounding environment that could not be collected otherwise via surveys or mobile phone data.However, data visualization highlighted that forest-goers did not carry the GPS loggers at all times, likely because the instructions insisted too much on the importance of carrying them during forest-going trips. As a result, the analysis was restricted to the 5% of GPS points that were collected during the 803 outdoor trips. This was a necessary step to ensure high-quality input data in our analyses but limits the effectiveness of using such GPS loggers. In addition, these data required substantial processing time and simple steps such as directly collecting the GPS coordinates of forest-goers’ house and the exact timing when the GPS logger was handed out would have significantly improved our experience.1.This study has additional limitations. First, the definition of high-risk trips is subjective and based on a simplified version of the malaria ecosystem in the GMS where what matters is exposure to places with suspected higher exposure to mosquito vectors. Having prospective data on malaria infection among this cohort would be extremely valuable. Forest-goers recruited in FTAT were tested for malaria before being given GPS loggers, but reverse causality would have undermined the results from any association analysis and statistical power was low with only six forest-goers in the GPS component of the study testing positive for malaria cases by PCR (polymerase chain reaction). Additional information about the actual activities forest-goers engaged in during their outdoors trips would also have been valuable for a more comprehensive definition of risk. Second, the small sample size of 96 forest-goers in the regression analysis lacked sufficient variation in some individual level features to evaluate their association with high-risk trips. For instance, 95% of forest-goers who carried a GPS logger were male. Third and related, the forest-goers participating in the GPS logger component of the study were somewhat different from those that did not. This may be due to chance or bias in PNs’ recruitment of forest-goers or recruitment of PNs themselves. Ultimately, the quality of the data sample relies heavily of the aptitude of PNs to navigate their communities of forest-goers and recruit representative participants. As a consequence, the results may not generalize well to the whole 2,904 forest goers recruited in FTAT or even the 20,000 forest-goers or so estimated to reside in the study areaIn conclusion, this study illustrated how GPS loggers can be leveraged to measure and characterize fine-scale mobility patterns of forest-going populations in southern Lao PDR. The results highlighted the diversity within forest-going trips but could not clearly segment the role of forest-goers in malaria transmission in the GMS any further. These results shall be informative to malaria programmes across the region to tailor their interventions and messaging to high-risk populations and meet the objective of eliminating malaria by 2030 in the GMS , 16.Additional file 1: S1. GPS filtering algorithm.Additional file 2: Figure S2. Dendogram from the hierarchical clustering algorithm. Starting from the bottom, every data point, i.e outdoor trip, is regrouped one a time into “leaves” (=cluster) until they are all in one big and uninformative cluster. The length of the “branches” quantifies the dissimilarity between the leaves. The red horizontal line represents our subjective decision to cut the tree in 6 clusters. We felt selecting 5 clusters would have failed to cut lengthy branches whereas selecting 7 clusters would have started to cut short branches.


This study aims to investigate across subgroups of healthcare workers (1) the changes in psychosocial working conditions and emotional exhaustion during the pandemic compared with the situation before, and (2) the impact of different stages of the COVID-19 pandemic in terms of hospital pressure on psychosocial working conditions and emotional exhaustion.Five questionnaire measurements during 2 years from 1915 healthcare workers in the longitudinal study ‘the Netherlands Working Conditions Survey-COVID-19’ were used. At each measurement, three subgroups were defined: working with patients with COVID-19, working with other patients and not working with patients. For each measurement, hospital pressure was determined by number of hospitalisations per day. Linear mixed models were fitted to analyse differences across subgroups of healthcare workers.During COVID-19, psychosocial working conditions deteriorated among healthcare workers working with patients, in particular with patients with COVID-19, compared with healthcare workers not working with patients after correcting for the situation before COVID-19. No changes were observed for emotional exhaustion in any of the subgroups. An increasing hospital pressure improved job autonomy and reduced emotional demands among healthcare workers in COVID-19 wards, but had no influence on other psychosocial working conditions and emotional exhaustion.Psychosocial working conditions deteriorated for healthcare workers working with (COVID-19) patients during the pandemic, while emotional exhaustion did not change among all groups of healthcare workers. There is a high prevalence of mental health problems among healthcare workers, before and during the COVID-19 pandemic.No consistent evidence exists on mental health among different types of healthcare workers during the COVID-19 pandemic.Unfavourable working conditions contribute to poor mental health outcomes among healthcare workers.During the COVID-19 pandemic, healthcare workers working with patients with COVID-19 or other patients experienced more unfavourable psychosocial working conditions compared with healthcare workers not working with patients.After adjustment for the pre-COVID-19 period, healthcare workers working with patients with COVID-19 or other patients experienced a larger deterioration in psychosocial working conditions compared with healthcare workers not working with patients, but no changes were observed for emotional exhaustion.An increasing hospital pressure due to more hospitalisations of patients with COVID-19 resulted in an improvement of job autonomy and emotional demands among healthcare workers in COVID-19 wards compared with healthcare workers not working with patients. It was not associated with other psychosocial working conditions and emotional exhaustion.Unfavourable psychosocial working conditions were already apparent among healthcare workers before the COVID-19 pandemic, and these conditions deteriorated during the pandemic. No effects were found for emotional exhaustion. Policy should focus on developing and implementing effective interventions to improve psychosocial working conditions of healthcare workers.Healthcare workers are considered as a high-risk group to acquire COVID-19,Unfavourable working conditions may contribute to poor mental health among healthcare workers.Based on the job demands-resources (JD-R) model, working conditions can be categorised into job demands  and job resources . An imbalance between demands and resources could result in job strain and therefore occupational stress. The JD-R model provides strong evidence that job demands are primarily related to the emotional exhaustion component of burnout.The current study will contribute to the existing literature in three ways. First, the current literature among healthcare workers lacks longitudinal studies comparing the effects of the COVID-19 pandemic on changes in psychosocial working conditions and mental health before and during the pandemic at the individual level. As unfavourable working conditions and mental health problems were already present among healthcare workers before the COVID-19 pandemic, it is important to compare the associations of unfavourable working conditions and mental health problems during the pandemic with the pre-COVID-19 situation. Second, the COVID-19 pandemic is not a fixed stage, meaning that infection rates, hospitalisations and governmental measures differed over time. Therefore, it is relevant to gain insight in the effects of different stages of the COVID-19 pandemic on psychosocial working conditions and mental health. Thereby, differentiation across groups of healthcare workers is needed as hospital pressure is higher for COVID-19 wards than other departments. The aim of the current study is to investigate (1) changes in psychosocial working conditions and emotional exhaustion during the pandemic compared with the situation before across subgroups of healthcare workers, and (2) the impact of different stages of the COVID-19 pandemic in terms of hospital pressure on psychosocial working conditions and emotional exhaustion across these subgroups.The current study is embedded within the longitudinal study ‘the Netherlands Working Conditions Survey COVID-19’ (NWCS-COVID-19), which is a cohort study that consists of one measurement before (baseline measurement) and four measurements during the COVID-19 pandemic.The target population of this study were Dutch workers in the healthcare sector between the ages of 18 and 65 years who participated in the baseline measurement and at least one follow-up measurement. The study population consists of healthcare workers working—among others—in hospitals, nursing homes and in home care. When workers became unemployed or changed their job at (one of) the follow-up measurements, this observation and the following observations were excluded. The final analytical sample included 6282 observations from 1915 respondents .Based on questions about whether the healthcare workers worked with patients and if they did, whether they worked with patients with COVID-19, healthcare workers were divided into three subgroups: (1) working with patients with COVID-19, (2) working with other patients and (3) not working with patients. Since workers could change their group status over time, the number of workers per group is not fixed across the measurements .Emotional exhaustion was measured with the emotional exhaustion scale of the validated Utrecht Burnout Scale.Job autonomy was based on five items of the Job Content Questionnaire (JCQ) with questions on decision-making at the job, deciding on the order and speed of conducting tasks, having to find solutions for problems and being able to take time off from work.Another three items of the JCQ were used to measure psychological job demands. The items assess the speed, amount of work and difficulty level of the job,To measure emotional demands of the job, three items of the Copenhagen Psychosocial Questionnaire were used.Social support from colleagues was based on two items of the JCQ.Social support from the supervisor was based on two items of the JCQ.The average scores of all outcome measures were used as continuous variables, because no clear cut-offs exist.Hospital pressure was determined as a daily number of patients with COVID-19 hospitalised in the Netherlands.Age, sex, household composition, level of education and working hours at baseline were included as covariates. Age was divided into four categories, namely 19–34, 35–44, 45–54 and 55–64. Gender was a dichotomous variable . Household composition was categorised into: single (with or without children), having a partner and no children, or having a partner and children. Level of education was divided into three categories: low, intermediate or high. The number of working hours at baseline was included as continuous variable.Linear mixed models were fitted for the five psychosocial working conditions and emotional exhaustion as dependent variables. The models contained random intercepts for the within-person variation. Time-dependent fixed effects were hospital pressure and subgroup status. Time-independent fixed effects were sex, age, household composition, level of education and working hours. First, differences over time across subgroups were estimated, adjusted for individual characteristics with adjustments for baseline scores of the dependent variables. Second, the impact of different stages of the COVID-19 pandemic across subgroups was estimated using interaction terms between subgroups and hospital pressure. Hospital pressure was used as time-varying variable since the aim of the study is to measure the impact of different stages of the COVID-19 pandemic. Time of measurement was not included in the models to prevent overadjustment. All linear mixed model analyses were also performed with stratification by sex. For descriptive purposes, the differences across subgroups were estimated without adjusting for baseline scores of the dependent variables. Additionally, fixed effects analyses were performed to investigate the effect of a change from working with other patients to working with patients with COVID-19 on the change in psychosocial working conditions and emotional exhaustion. All analyses were performed using IBM SPSS software V.28 with the unstructured repeated covariance type and the restricted maximum likelihood method in the linear mixed models procedure. The supplementary fixed effects models were performed as linear regression analyses, both with and without adjusting for hospital pressure. Hedge’s d effect sizes, expressing the observed difference relative to the pooled SD, were calculated to compare the three groups of healthcare workers for differences in psychosocial working conditions and exhaustion. Logistic regression analyses were used to evaluate non-response bias due to selective dropout during the follow-up measurements.Regarding the non-response analyses, respondents in measurement 3 had a higher job autonomy and more social support from the supervisor at measurement 2 than those who dropped out after measurement 2 . No diff10.1136/oemed-2022-108478.supp1Supplementary dataAn increase in hospital pressure resulted in a larger increase in job autonomy and a larger decrease in emotional demands among healthcare workers in COVID-19 wards compared with healthcare workers not working with patients . InteracRegarding the effects for sex, no or small differences were found between males and females  on a scale from 1 to 3. No differences in emotional exhaustion were found between subgroups of healthcare workers. Unexpectedly, an increase in hospital pressure resulted in improvements of job autonomy and emotional demands among healthcare workers in COVID-19 wards.Our study is in line with a previous study that showed an association between the COVID-19 pandemic and adverse psychosocial working conditions such as high emotional demands and high workload.No differences in emotional exhaustion over time were found between subgroups of healthcare workers, even though the results show that healthcare workers working with patients, especially those working with patients with COVID-19, experienced adverse psychosocial working conditions. While the JD-R model states that more job demands lead to more emotional exhaustion,Surprisingly, an increase in hospital pressure resulted in a more favourable change in job autonomy and emotional demands among healthcare workers working with patients with COVID-19. A reason for the increase in autonomy could be that during higher hospital pressure, healthcare workers are expected to be more self-reliant due to the hectic and new situations at the workplace. An explanation for the decrease in emotional demands could be related to the JD-R model. Research shows that high social support at work may moderate the adverse impact of jobs with high job demands.A major strength of this study is the longitudinal data with measurements before and during COVID-19, which made it possible to study psychosocial working conditions and emotional exhaustion during the pandemic and compare them to the period before the pandemic in 2019. Another strength is the possibility to divide the healthcare workers into three different groups to further disentangle the impact of COVID-19 on psychosocial working conditions and emotional exhaustion.However, the study also goes with limitations. First, only the respondents who gave permission in 2019 were contacted to participate in the NWCS-COVID-19 follow-up study, possibly leading to selection bias. Second, we considered a mediation analysis to further disentangle the relationship between psychosocial working conditions and emotional exhaustion. However, this was not feasible due to changes in subgroup status across the measurement periods. Third, the timing of the follow-up measurements was before or after a COVID-19 peak, which means during periods of less hospitalisations. This could have had an effect on the experienced psychosocial working conditions at the time the measurements took place, whereas the results could have been different when measured during peaks of hospitalisations. Fourth, only emotional exhaustion has been assessed as a measure of burnout. However, other factors could also be related to burnout, such as workplace justice, reward and job insecurity.Healthcare workers working with patients with COVID-19 experience the most unfavourable psychosocial working conditions, and these working conditions deteriorated during COVID-19 compared with the period before the pandemic. However, an increase in hospital pressure has no further deteriorating effects on psychosocial working conditions; job autonomy and emotional demands even improved. Unfavourable psychosocial working conditions were already apparent among healthcare workers before the COVID-19 pandemic, and the current results show that these conditions deteriorated during the pandemic. Policy should focus on developing and implementing effective interventions to improve the psychosocial working conditions of healthcare workers.


The first nine months from conception to birth involves greater changes than at any other time in life, affecting organogenesis, endocrine, metabolic and immune programming. It has led to the concept that the “first 1000 days” from conception to the second birthday are critical in establishing long term health or susceptibility to disease. Immune ontogeny is predominantly complete within that time and is influenced by the maternal genome, health, diet and environment pre-conception and during pregnancy and lactation. Components of the immunological protection of the pregnancy is the generation of Th-2 and T-regulatory cytokines with the consequence that neonatal adaptive responses are also biased towards Th-2  and T-regulatory (tolerance promoting) responses. Normally after birth Th-1 activity increases while Th-2 down-regulates and the evolving normal human microbiome likely plays a key role. This in turn will have been affected by maternal health, diet, exposure to antibiotics, mode of delivery, and breast or cow milk formula feeding. Complex gene/environment interactions affect outcomes. Many individual nutrients affect immune mechanisms and variations in levels have been associated with susceptibility to allergic disease. However, intervention trials employing single nutrient supplementation to prevent allergic disease have not achieved the expected outcomes suggested by observational studies. Investigation of overall dietary practices including fresh fruit and vegetables, fish, olive oil, lower meat intake and home cooked foods as seen in the Mediterranean and other healthy diets have been associated with reduced prevalence of allergic disease. This suggests that the “soup” of overall nutrition is more important than individual nutrients and requires further investigation both during pregnancy and after the infant has been weaned. Amongst all the potential factors affecting allergy outcomes, modification of maternal and infant nutrition and the microbiome are easier to employ than changing other aspects of the environment but require large controlled trials before recommending changes to current practice. During delivery the neonate leaves the controlled and sterile environment of the uterus to be exposed to potentially overwhelming physical challenges. Development through pregnancy can be viewed as a preparation for extra-uterine existence with maternal gene/environment interactions influencing organ development and the programming of foetal immune, metabolic and endocrine responses. This concept arises from the hypothesis that the origins of health or risks of most diseases are a consequence of minor perturbations during organogenesis and periods of rapid cell division. It has evolved into the science known as “The Developmental Origins of Health And Disease (DOHAD)” or in common parlance the first 1000 days from conception to the second birthday  Figure . StudiesThe immunological mechanisms underlying allergic disease are the expression of T-lymphocyte-mediated responses to common environmental allergens that are biased towards T lymphocytes with helper-2 (Th-2) activity. Th-2 lymphocytes release peptide regulatory factors (cytokines) such as interleukins (IL) 4, IL-5, IL-9 and IL-13, which trigger the production of immunoglobulin-E (IgE), the allergy promoting antibody, and activate inflammatory cells such as eosinophils. Counter regulation is achieved by T-helper-1 (Th-1) lymphocytes generating cytokines such as interferon-gamma (IFN-gamma) which down-regulates Th-2 activity, while IL-4 suppresses Th-1 function. A group of T-lymphocyte regulators (T-regs) suppress both Th-1 and Th-2 activity by either cell–cell contact or the generation of IL-10 and transforming growth factor (TGF) beta ,7.The pattern of response of T-lymphocytes is dictated by the nature of the signaling from antigen presenting cells (APCs). They, in turn are affected by the nature of the antigen exposure and the presence or absence of co-stimulatory signals. Mucosal epithelial cells are the usual first contact points with antigens, which if recognised as conferring potential danger, by, for instance, having enzymic activity, cytokines known as alarmins  are released by epithelial cells. The alarmins stimulate innate lymphocytic cells with a type-2 phenotype, which amongst a range of cytokines, release IL-4 and 5. This creates the environment to bias the adaptive response to increased Th-2 activity thereby promoting IgE production and eosinophil activation. This is the normal immune response to parasite infestation but is also characteristic of allergy . APCs geThis review focusses on events during foetal life that influence susceptibility to allergic sensitisation and/or allergic disease. In evaluating the outputs from observational and interventional studies it is important to discriminate between immunological processes leading to allergic sensitisation from those that evolve into the diseases associated with allergy such as eczema, asthma, rhinitis and food allergy. As the modification of maternal and infant diets is easier to achieve than changing other aspects of the early-life environment, the final section focuses on nutrition.The neonatal immune system should be able to recognise diverse antigens to identify and destroy pathogens while maintaining tolerance to self, to food, and other harmless environmental exposures. Pregnancy is immunologically equivalent to an organ transplant because the foetus expresses both paternal and maternal antigens to which maternal Th-1 tissue rejecting responses would be expected. Where this occurs, it causes intra-uterine growth retardation or early miscarriage in both murine models and human pregnancies. Counter-balancing this response is in part due to a Th-2 and T-regulatory cytokine profile produced by decidual tissues which down-regulate maternal Th-1 responses  10]. Wh. Wh10]. Newborn infants have allergen reactive T-cells which are characterised by greater production of Th-2 rather than Th-1 cytokines. Normally, the post-natal environment modulates responses with an increase in Th-1 and reduction in Th-2 activity. Infants destined to develop allergic disease have a different pattern with sustained Th-2 activity. There are differences in allergen induced cytokine production at birth in infants who have subsequently developed allergic disease. There is a generally reduced capacity in such infants to generate both IFN-gamma the archetypal Th-1 cytokine and IL-13 a characteristic Th-2 cytokine ,15. IL-1The neonate has a relatively immature innate immune response to pathogen challenge as a consequence of low circulating complement levels, impaired neutrophil function, natural killer cell function and macrophage activation ,18. AdapAmniotic fluid contains antigens/allergens to which the mother has been exposed together with desidual tissue derived Th-2 cytokines, which are swallowed by the foetus. This is a potential route toTh-2 biased sensitisation in the small intestine ,21. A reAmniotic fluid also contains IgE antibodies at 10% of maternal circulating levels by 16 weeks’ gestation. IgE receptors are present on cells within the lamina propria of the foetal gut. Therefore, there is the potential for the high-affinity pick-up of antigens by APCs. This is a phenomenon known as antigen focusing. With IgE on low and high affinity IgE receptors, sensitization occurs to 100–1000-fold lower concentrations of allergens than would occur without IgE . While tSingle nucleotide gene polymorphisms (SNPs) have variously been associated with allergy and/or asthma, and/or eczema, and/or rhinitis, but account for only a small proportion of variability in the phenotype. It has been suggested that it will be more fruitful to focus on gene/environment interactions, epigenetics, and pharmaco-genetics . Twin anHowever, genetic influences on outcomes contribute relatively small effects because the impact of the polymorphisms will only be apparent at critical stages during development and/or the presence of environmental stressors. For example, ADAM-33 is expressed during airway branching morpho-genesis and SNPs may have their greatest impact very early in foetal life because airway formation is complete by the middle of the second trimester of pregnancy . The metThe other way in which environment impacts on gene expression is through modification of molecules attached to DNA sequences or the histones around which chromosomes wind. This is the relatively new discipline of epigenetics which not only directly affects phenotype but is also hereditable. Cigarette smoking induces many epigenetic changes and grand-maternal smoking increases risks of asthma in grand-children independent of maternal smoking . Levels The maternal diet will affect the mother’s gut microbiome and therefore the infant’s inoculum during delivery. However, the maternal microbiome and other confounders have hitherto not been comprehensively analyzed in relation to studies of the impact of pregnancy nutriention on allergy outcomes. This means that outcomes must be interpreted with caution.Foetal growth and nutrition have an impact on the ontogeny of immune responses. There is an unexpected association between large head circumference at birth and levels of total IgE at birth in childhood and adulthood . It has The key question is whether there are any specific nutrients of importance in promoting appropriate immune responsiveness. Reduced intake of fresh fruit and vegetables has been associated with a higher rate of allergic sensitisation in many studies . A high Maternal obesity has been associated with higher risks of wheezing illnesses and asthma but not other allergic disorders in children. There are credible mechanistic explanations because mediators, known as adipokines, that are released by adipocytes are pro-inflammatory. They will have effects at the materno-foetal interface leading to foetal immune and neuro-endocrine dysregulation. Obesity also likely has epigenetic effects with enhanced pro-inflammatory gene expression . There aSeveral studies have focused on lipids as being important in immune ontogeny. Indeed, fatty acids have a crucial role as a source of energy, as the principle component of cell membranes, and as precursors for the synthesis of prostaglandins and leukotrienes. Minor variations in levels could have a profound effect on immune responses. Fish oils have a high level of omega-3 polyunsaturated fatty acids (n-3 PUFAs) and Western diets have a diminished intake of n-3 PUFAs with corresponding increases in n-6 PUFAs. This change has been associated with increasing rates of allergic disease and asthma . Low corVitamin D receptors (VDR) have been identified on many immune active cells and vitamin D has important immunoregulatory functions. Most notable are effects on T-regs through TGF-beta expression and signaling. Polymorphisms in the VDR have been linked to an increased risk of asthma . While sMost studies of maternal dietary factors affecting allergic disease outcomes in off-spring have attempted to identify beneficial influences. There are a few recent studies suggesting adverse effects of some nutrients such as refined sugar and pro-inflammatory factors ,57. A hiAssociations between omega-3 PUFAs, vitamins D, E and zinc at best show only weak beneficial effects, while intervention trials have produced conflicting results with variable outcomes, phenotyping and confounding being critical issues. As is apparent from all pregnancy gene/environment interactions, the relationships are complex, being influenced by timing, dose, and combinations of exposures which are not normally analysed in observational or intervention studies. Some studies of the so-called Mediterranean diet (Med-Diet) with its high intake of fish, olive oil, fresh vegetables and fruits with low intake of chicken and red-meat  have suggested reductions in some but not all allergic phenotypes. A systematic review indicated that maternal adherence to the Med-Diet reduced offspring wheeze/asthma in the first year of life but not thereafter, and had minor effects on allergy but none on eczema . A more Complex interactions at the materno-placental-foetal interface have a profound influence on the infants’ immune maturation and the likelihood of developing allergic sensitisation and disease. Gene/environment interactions and timing of exposures through pregnancy add further degrees of complexity. Understanding the early life origins of allergy will only be possible by embracing this complexity. Studies will now need to investigate combinations of dietary, pollutant, medication and microbial exposures during pregnancy in relation to genomics, epigenomics, metagenomics and metabolomics in relation to infant/child outcomes. Controlled trials of a “healthy diet” during pregnancy are likely to yield better outcomes than focusing on single nutrients which hitherto have produced disappointing results. The manipulation of the neonates’ evolving microbiome is suggested as another focus for controlled prevention trials.


For the primary prevention of coronavirus disease 2019 (COVID-19), there are currently four different vaccines available in the USA. These are Pfizer (messenger RNA [mRNA]), Moderna (mRNA), Novavax (recombinant protein), and Jansen/Johnson & Johnson . All individuals should get vaccinated, and the Centers for Disease Control and Prevention (CDC) has provided comprehensive guidelines on recommended doses, their frequency by age group, and vaccine types, all discussed in detail in this article. Vaccines are a critical and cost-effective tool for preventing the disease. Prior to receiving a vaccine, patients should get adequate counseling regarding any potential adverse effects post vaccination. Appropriate safety precautions must be taken for those more likely to experience adverse consequences. Healthcare professionals should be aware of the symptoms, indicators, and treatment of any adverse event post-vaccination. We have provided a comprehensive review of the different characteristics of COVID-19 vaccines available in the United States, including their effectiveness against various variants, adverse effects, and precautions necessary for healthcare professionals and the general population. This article also briefly covers COVID-19 vaccines available worldwide, specifically their mode of action and effectiveness. After being discovered in Wuhan, China, in November 2019, the novel coronavirus pandemic expanded quickly, causing significant morbidity, mortality, and financial burden worldwide .The Food and Drug Administration (FDA) first issued emergency use authorization of the COVID-19 vaccine on December 11, 2020, in the United States. Since then, the number of COVID-19 vaccines approved for use has significantly increased worldwide. Along with the development of multiple COVID-19 vaccines, concerns about their side effects and contraindications have also increased. The development of COVID-19 vaccines is regulated by data safety and monitoring committees (DSMCs) composed of vaccine specialists and study sponsors. Before sanctioning the progression of a specific vaccine to the next phase, these groups evaluate the adverse events identified in each clinical study. This review article aims to provide a thorough analysis of COVID-19 vaccines approved for use in the USA, their characteristics, and their adverse effects profile.MethodologyA complete review of the medical literature was performed systematically with the keywords "COVID-19," "COVID-19 variants", "COVID-19 vaccine", and "COVID vaccine adverse effects" in PubMed, Google Scholar, and ScienceDirect databases. We also reviewed information from regulatory drug agencies and pharmaceutical companies' websites till September 4, 2022. To gather relevant content, all articles, which included literature reviews, meta-analyses, case reports, case-control cohort studies, and randomized controlled trials of vaccines, were screened and used to complete this article. Data from the Centers for Disease Control and Prevention (CDC) was also used and included in this article. We summarized and organized pertinent information for ease of understanding.DiscussionGeneral Principles for COVID-19 VaccineThe COVID-19 virus and its variants have surface spike protein (S-protein) which bind to the angiotensin-converting enzyme 2 (ACE2) receptors on the target cells resulting in membrane fusion. This enables the virus to penetrate the host cell and begin to replicate. The S-protein is the primary antigenic target site of COVID-19 vaccines. The antibodies produced by COVID-19 vaccines bind to the receptor binding domain of the S-protein, preventing the virus from binding to the host . Based oCOVID-19 Vaccines Available in the United StatesPresently, four COVID-19 vaccines are approved for use in the United States by the FDA. They include two mRNA vaccines, an adjuvant recombinant vaccine and an adenoviral vaccine as seen in Table Why vaccinate? Who to vaccinate? Which vaccine to choose? The COVID-19 vaccines effectively reduce individuals' risk of contracting the virus. In addition, research has established that individuals receiving COVID-19 vaccines have a reduced risk of COVID-19-associated morbidity and mortality ,14. Based on currently available data and CDC guidelines, COVID-19 vaccinations are recommended for all people aged six months and older ,16. mRNAStudies have also shown that two doses of mRNA vaccine are more effective than a single dose of Janssen . For insCOVID-19 vaccines: doses and intervals, monovalent and bivalent booster dosesThe following is the description of the old COVID-19 immunization schedule approved by the CDC before August 31, 2022. This has been discussed below in detail and can also be seen in Figure The guidelines for the COVID-19 vaccines have not yet been granted FDA approval or authorization for use in children under six months. These guidelines are frequently updated by the CDC.Pfizer-BioNTech COVID-19 (BNT162b2)Pfizer-BioNTech COVID-19 (BNT162b2) vaccine is an mRNA-based vaccine that was developed by BioNTech and Pfizer in close collaboration . This vaAdults 18 years and older: In a healthy individual, the first two doses of the Pfizer-BioNTech vaccine are considered primary series, which can be given three to eight weeks apart. The individual is considered fully vaccinated two weeks after receiving the final dose in the primary series . An immuChildren and teenagers age 12 to 17 years: In a healthy individual, the first two doses of Pfizer-BioNTech are considered primary series, which can be given three to eight weeks apart. The individual is considered fully vaccinated two weeks after receiving the final dose in the primary series . HoweverChildren age five to 11 years: In a healthy individual, the first two doses of Pfizer-BioNTech are considered primary series, which can be given three to eight weeks apart. The individual is considered fully vaccinated two weeks after receiving the final dose in the primary series. However, in an immunocompromised individual, three doses of the primary series need to be given three to four weeks apart . In a heChildren age six months to four years: In healthy children, a total of three primary doses are given. The first two doses of Pfizer-BioNTech can be given three weeks apart, and the third can be given eight weeks from the last dose. The individual is considered fully vaccinated two weeks after receiving the final dose in the primary series. The immunocompromised individuals also receive the same three doses with the same duration in the primary series as healthy individuals . No boosModerna COVID-19 Vaccine (mRNA-1273)Moderna COVID-19 vaccine (mRNA-1273) is also an mRNA-based vaccine developed by the company Moderna . This vaAdults 18 years and older: In a healthy individual, for the age group 18 to 49 years, the primary series consists of two doses, and for individuals aged 50 years and older, three doses are given at least four to eight weeks apart. The individual is considered fully vaccinated two weeks after receiving the final dose in the primary series. However, in an immunocompromised individual, the three doses of the primary series need to be given at four-week intervals . One booChildren and adolescents age six months to 17 years: In these healthy individuals, two doses of Moderna vaccine are considered primary series, should be given four to eight weeks apart. The individual is considered fully vaccinated two weeks after receiving the final dose in the primary series . HoweverNovavax COVID-19 Vaccine (NVX-CoV2373)Novavax COVID-19 vaccine (NVX-CoV2373) is an adjuvanted recombinant protein vaccine developed by the company Novavax . This vaJanssen COVID-19 Vaccine (Ad26.COV2.S)Janssen COVID-19 vaccine (Ad26.COV2.S) is an adenoviral vector vaccine  that, liNew COVID-19 vaccine schedule with bivalent mRNA vaccine recommendationsAs of August 31, 2022, the FDA has authorized and approved the bivalent COVID-19 vaccine booster dose. The CDC has also updated its COVID-19 vaccine schedule and guidelines, especially focusing on booster doses, as seen in Figure This recommendation extends to both healthy and moderately or severely immunocompromised individuals over the age of 12. The two bivalent mRNA vaccines currently available are Pfizer and Moderna. To determine which bivalent vaccine is most appropriate, healthcare providers should refer to the individual's age group and primary vaccine series type. The current recommendations are as follows:In healthy, moderately, or severely immunocompromised individuals, the primary vaccination series has remained the same in all individuals (in the same age group). The only change is with the booster dose only. Instead of receiving multiple booster doses, CDC now recommends individuals ages 12 years and above receive only "one bivalent mRNA booster dose" after completing the primary series or any monovalent booster doses received in the past ,20. This new recommendation of receiving one bivalent booster dose replaces all prior monovalent mRNA booster vaccination for individuals ages 12 and above. The monovalent mRNA vaccine is not authorized as a booster dose for individuals ages 12 years and older.Individuals ages five through 11 who received the Pfizer-BioNTech vaccine will still receive only the monovalent booster after completing the primary dose . Also, all individuals who have received Novavax as a primary vaccine should receive a bivalent booster dose of either Pfizer or Moderna vaccine ,20.Can we mix different vaccines along with booster dose?Unless otherwise noted, the CDC advises that the primary series of mRNA vaccinations be completed with the same type. For example, if a particular mRNA vaccine is in short supply or unavailable, CDC recommends delaying the second dose until the same vaccine can be obtained . HoweverPer CDC recommendations, an alternative vaccine to the one given as part of the primary series can be administered as a booster. This is particularly relevant when an mRNA vaccination is administered as a booster to people who had Janssen as their primary series. Studies have demonstrated that this strengthens vaccine effectiveness against COVID-19 viral infection . The intCan you administer non-COVID-19 vaccines with the COVID-19 vaccines?Per CDC guidelines, non-COVID-19 vaccines can be administered simultaneously with the COVID-19 vaccine. However, both vaccines should be injected at least in different limbs  or at least 1 inch apart .Adverse reactions, contraindications, and precautionsThe safety of COVID-19 vaccinations has been the subject of numerous misconceptions and myths, but in reality, most of them are relatively safe. Table Severe allergic reaction to COVID-19 vaccine: signs, symptoms, management, patient counseling and precautions to takeA history of severe allergic responses, including anaphylaxis, to a previous COVID-19 vaccine or a vaccine ingredient is an important contraindication to future COVID-19 vaccine doses . For exaAnaphylaxis has an acute onset from minutes to several hours and requires immediate intervention ,21. SympPer CDC, if a patient undergoes a severe allergic reaction after receiving a COVID-19 vaccine, they should not have any more doses of that same vaccine type and should be referred to an allergist for additional follow-up . For exaIn a multisite US study conducted from January 2021 to March 2021, the individuals who received the first dose of mRNA vaccine and experienced severe allergic reactions were able to successfully receive a second dose of Pfizer-BioNTech or Moderna vaccines . This stA general precaution prior to receiving a COVID-19 vaccine is evaluating for a history of an allergic reaction to a past COVID-19 or non-COVID-19 vaccine and other injected treatments . For indThrombosis with thrombocytopenia syndrome (TTS) from COVID-19 vaccineTTS is also known as vaccine-induced thrombotic thrombocytopenia (VITT). Studies show that the Janssen vaccination led to an estimated four cases per million and 0.6 deaths per million after the initial dose . Signs, Symptoms, and Management of TTSSymptoms of TTS usually develop between seven to 14 days after vaccination and include headache, vision changes, abdominal pain, shortness of breath, trouble with bleeding or bruising, and pain in the legs or back ,30. If tPatient Counseling After TTS OccursIf TTS is experienced after receiving a Janssen vaccine, a subsequent dose with it is contraindicated . Those wGuillain-Barre syndrome (GBS) from COVID-19 vaccineIf an individual develops GBS within six weeks of administration of a Janssen vaccine, it is not recommended to administer another dose of it . By JulySigns, Symptoms, and Management of GBSGBS is a peripheral disorder involving nerve damage caused by one’s immune system . SymptomPatient Counseling After GBS OccursFor those that develop GBS within six weeks after Janssen dose administration and wish to complete their vaccination series, an mRNA COVID-19 vaccine should be used for booster doses . For futGBS PrecautionsFor individuals with a history of GBS, the administration of Janssen should be approached with caution . Since uMyocarditis/pericarditis from COVID-19 vaccinemRNA COVID-19 vaccines and Novavax have been associated with developing myocarditis or pericarditis in young males 12 to 39 years of age post-vaccination ,33. HoweSigns, Symptoms, and Management of MyocarditisMyocarditis occurs when cardiac muscle is inflamed, while pericarditis occurs when the sac around the heart is inflamed . IndividPatient Counseling After Myocarditis OccursIf a patient experiences myocarditis, it is advised that subsequent doses of any mRNA or Novavax COVID-19 vaccines be avoided . If an iOther widely used COVID-19 vaccines worldwideThere are seven other COVID-19 vaccines available worldwide which are listed in Table ChAdOx1 nCoV-19/AZD1222 (AstraZeneca - the University of Oxford and the Serum Institute of India)The University of Oxford and AstraZeneca collaborated to create this vaccine. This vaccine utilizes DNA to create S-proteins as opposed to mRNA vaccines. The ChAdOx1 chimpanzee adenovirus serves as the vector for this vaccine. The genetic code for the COVID-19 S-protein will then be injected by the modified adenovirus into the nucleus of the recipient's cells, allowing it to be translated into mRNA. Later, this mRNA is translated into spike proteins that travel to the surface, where the immune system can detect them and eventually mount an immunological response. It is simple to use and store this vaccine. The vaccine does not have to remain frozen and can last long, even when refrigerated at 2°C to 8°C. The WHO recommends this vaccine be given in two doses IM eight to 12 weeks apart -37Ad5-Based COVID-19 Vaccine (CanSino Biologics)This vaccine was developed by CanSinoBio and the Beijing Institute of Biotechnology as a single-dose vaccine against COVID-19 in China. This single-dose vaccine is given IM and is based on the replication of an adenovirus type 5 vector that expresses the S-protein of SARS-CoV-2. This vaccine is available in China and other countries, including Pakistan and Mexico . The effGam-COVID-Vac/Sputnik V This vaccine was developed by the Gamaleya Research Institute of Russia. The vaccine's mechanism of action is similar to AZD1222 discussed above. Sputnik V uses double-stranded DNA for building COVID-19 spike proteins to induce an immune response. The vector used for this vaccine is also Adenovirus 26 (AD26) and Adenovirus 5 (AD5). This vaccine is given IM in two doses. The initial dose contains the AD26 vector followed by the AD5 vector given 21 days to three months apart ,40. The WIV04 and HB02 (Sinopharm)The Beijing Institute of Biological Products of Sinopharm was tasked with developing these two inactivated virus particle vaccines based on two different COVID-19 isolates found in patients in China. These two vaccines are given IM 28 days apart . The vacCoronaVac (Sinovac)This vaccine is based on an inactive COVID-19 virus within an aluminum hydroxide as an adjuvant. This is a two-dose vaccine given IM 28 days apart . This vaCovaxin This vaccine is based on an inactive COVID-19 virus developed by Bharat biotech and the Indian Council of Medical Research. This is a two-dose vaccine given IM 29 days apart . The vacZyCoV-D (Zydus Cadila)This vaccine is considered the world's first plasmid-based DNA vaccine developed by Zydus Cadila in India against the COVID-19 virus. This vaccine uses a plasmid that carries a coronavirus genome to generate S-proteins in the host cell, leading to an immune response. It is a three-dose vaccine with each dose given 28 days apart. The vaccine uses a needleless injector that delivers the vaccine with a high-pressure stream subcutaneously. The benefit of this vaccine is that it is needleless and, therefore, painless. Also, since this vaccine is plasmid-based, vector-based immunity concerns can be avoided . This vaCOVID-19 vaccine effectivenessIn the section, we have discussed the effectiveness of different COVID-19 vaccines against different SARS-CoV-2 variants -49. ThisDelta (B.1.617.2) VariantSeveral SARS-CoV-2 variants have surfaced since the COVID-19 pandemic erupted, despite vaccine efforts to confine it. Critical S-protein mutations  have been linked to the delta variant's increased transmissibility. Another major factor in the reduced vaccine efficacy against delta variants has been theorized to be its increased affinity of the S-protein and ACE2. The table highlights the vaccine effectiveness against the delta variant. The mRNA vaccines were over 94% effective two to four weeks after completing two doses. The effectiveness goes down to around 80% at 25 weeks or more after the completion of two doses of mRNA vaccines. The vaccine effectiveness increases to over 95% when boosted with either of the mRNA vaccines.After two doses, the AstraZeneca vaccine showed 82% effectiveness against the delta variant. This effectiveness goes down to around 43.5% at 25 weeks or more. The vaccine effectiveness increases to over 95% when boosted with either of the messenger RNA vaccines as shown in Table Omicron (B.1.1.529) VariantAccording to CDC data from August 2022, BA.5 sub-lineages of the omicron variety accounted for around 88% of infections in the United States. The effectiveness of vaccines was lower for the omicron variant for all mRNA vaccines compared to the delta variant. Patients who received two doses of Pfizer-BioNTech vaccine initially had vaccine effectiveness of 65.5% around two to four weeks after completing the second dose. This effectiveness goes down to 8.8% after 25 weeks. Similarly, with the Moderna vaccine, the two doses of vaccine were initially effective at 75.1% two to four weeks after completing the second dose. This effectiveness reduces to 14.9% after 25 weeks as shown in Table For the individuals who received Pfizer-BioNTech as a primary series (two doses) and as a booster dose, the vaccine effectiveness increased to around 67% two to four weeks post booster dose. This effectiveness declined to about 45% after 10 weeks of receiving the booster dose as shown in Table The individual who received Pfizer-BioNTech as a primary course (two-dose vaccine) and then received the Moderna vaccine as a third booster dose showed the effectiveness increased to around 74% two to four weeks after receiving the booster dose, which then declined to 64% around five to nine weeks as shown in Table The individuals who received Moderna as a primary course (two-dose vaccine) and then received Moderna vaccine as a third booster dose showed effectiveness increased to around 66% two to four weeks after receiving the booster dose as shown in Table The individuals who received Moderna as a primary series (two doses) and then received Pfizer-BioNTech vaccine as a third booster dose showed the effectiveness increase to around 65% at two to four weeks post booster dose as shown in Table AstraZeneca vaccine failed to provide any protection against this variant after 20 weeks. However, for individuals who have received AstraZeneca as a primary series (two doses) and then received the Pfizer-BioNTech vaccine as a third booster dose, the vaccine effectiveness increased to around 62% at two to four weeks post booster dose. This effectiveness declined to around 40% at 10 weeks. On the other hand, individuals who have received the Moderna vaccine as a booster dose had the vaccine effectiveness increased to 70% at two to four weeks post booster dose. This effectiveness declined to around 61% at five to nine weeks as shown in Table Limitations of this reviewWe have reviewed current literature regarding COVID-19 vaccines that have already been approved in the US as well as other nations like the UK, China, and India; some other countries may also have approved them. Not all vaccines licensed elsewhere in the globe could be reviewed in this article. Vaccine side effects discussed are from currently reported data as of September 9th, 2022, which may change in the future as new data emerges. The COVID-19 pandemic continues to perpetuate with the emergence of variants of concern like the delta and the omicron variants, making robust preventative measures for virus containment more crucial than ever. While these mutations may not necessarily make the COVID-19 virus more virulent, they certainly hinder pandemic containment measures. The essential primary prevention method is still vaccination, although this virus is constantly mutating, making it possible to escape vaccine protection and cause vaccine breakthrough infections. Immunizations among those who qualify can prevent disease transmission, hospitalizations, and fatalities from COVID-19. Vaccine manufacturers continue to update COVID-19 vaccines to combat the variants. Four vaccines are currently approved for use in the United States by the FDA, giving people a choice of which one is appropriate. While most adverse effects are mild and self-limiting, it is essential to inform vaccine recipients of any potential adverse effects.Additionally, compared to COVID-19 infection, the incidence of several potential side effects, such as myocarditis, is lower with COVID-19 immunization, as discussed previously in the article. Further, completing recommended doses (primary and booster) at the recommended interval is crucial to get the most benefit from the vaccination. People who have received the recommended number of vaccine doses fare substantially better than those with partial immunizations in the long term. In conclusion, the advantages of COVID-19 vaccination greatly outweigh the risks of adverse reactions. With COVID-19 vaccination reaching all parts of the world through global collaboration, prompt recognition of the adverse effects and appropriate screening of the population is essential for improving its acceptability and will be critical to containing this pandemic.


Prevention of major depressive disorder (MDD) is a public health priority. Strategies targeting individuals at elevated risk for MDD may guide effective preventive care. Insomnia is a reliable precursor to depression, preceding half of all incident and relapse cases. Thus, insomnia may serve as a useful entry point for preventing MDD. Cognitive-behavioral therapy for insomnia (CBT-I) is recommended as the first-line treatment for insomnia, but widespread implementation is limited by a shortage of trained specialists. Innovative stepped-care approaches rooted in primary care can increase access to CBT-I and reduce rates of MDD.We propose a large-scale stepped-care clinical trial in the primary care setting that utilizes a sequential, multiple assignment, randomized trial (SMART) design to determine the effectiveness of dCBT-I alone and in combination with clinician-led CBT-I for insomnia and the prevention of MDD incidence and relapse. Specifically, our care model uses digital CBT-I (dCBT-I) as a first-line intervention to increase care access and reduce the need for specialist resources. Our proposal also adds clinician-led CBT-I for patients who do not remit with first-line intervention and need a more personalized approach from specialty care. We will evaluate negative repetitive thinking as a potential treatment mechanism by which dCBT-I and CBT-I benefit insomnia and depression outcomes.This project will test a highly scalable model of sleep care in a large primary care system to determine the potential for wide dissemination and implementation to address the high volume of population need for safe and effective insomnia treatment and associated prevention of depression.ClinicalTrials.gov NCT03322774. Registered on October 26, 2017 Prevention of depression, as opposed to treatment, is exponentially more impactful in reducing disease burden and needs to be the prevailing public health strategy.Major depressive disorder (MDD) surpasses asthma, diabetes, and lung cancer as a “high impact” medical condition (Medicare) and is the second most costly illness in the USA . DespitePrevention efforts should target known at-risk populations based on potential mechanisms underlying risk . TraditiWhile sleep disturbance is a common symptom of depression, it often occurs independently and even precedes the development of depressive symptoms. Insomnia disorder is characterized by significant difficulties falling and/or staying asleep, which occur ≥ 3 nights a week for ≥ 3 months to warrant a diagnosis . SymptomA meta-analysis of > 20 studies identified insomnia as a reliable precursor of MDD such that people with insomnia are 3 times more likely to develop depression relative to good sleepers . As insoCognitive behavioral therapy for insomnia (CBT-I) is the guideline-recommended treatment of choice as it has advantages regarding long-term effectiveness and safety over pharmacotherapy , 23. As However, the benefits of CBT-I are not limited to sleep symptoms. CBT-I has been shown to alleviate comorbid depression in insomnia patients with comorbid depression –35. AddiDespite the possibility that treating insomnia may prevent depression, few trials have been undertaken, mostly due to the large sample sizes and long follow-up durations needed to achieve adequate power. For example, in one of the few studies to have tested depression prevention through insomnia treatment, no differences were detected, likely due to the low incidence of depression over the 6-month follow-up period . Two recThese results highlight the immense promise that insomnia therapeutics can have in MDD prevention. The next step is to examine whether insomnia treatment can reduce incidents and relapse of clinician-diagnosed MDD in a broader patient population, including young, middle, and older adults. Moreover, prevention strategies should be implemented in real-world settings where they will reach the most patients likely to benefit from this strategy.Despite its promise, CBT-I has limitations including an insufficient number of credentialed behavioral sleep medicine (BSM) clinicians to meet demand. Nearly 20% of US adults have insomnia , yet theFinally, and quite importantly, insomnia and depression cases are typically identified and treated in primary care where access to CBT-I specialists is often limited, thereby leaving first-line behavioral options underutilized. Thus, although CBT-I effectively decreases insomnia and depression and shows promise for preventing depression, the limited availability of BSM specialists and challenges to underserved populations represent critical barriers to the scalability of clinician-led CBT-I as a first-line treatment or preventative intervention.To improve access to CBT-I, web and mobile technology was utilized to develop digital CBT-I (dCBT-I). dCBT-I reduces cost and therapist time, is scalable, and empowers users to manage their own health and healthcare. dCBT-I also avoids the stigma of traditional therapy, most relevant for vulnerable populations  . Over a Even so, the field struggles with its implementation, particularly in relationship with primary care, where insomnia and depression are typically identified and treated. To maximize the implementation and reach of dCBT-I, we must (1) determine the effectiveness of treating insomnia with dCBT-I when integrated into primary care and (2) evaluate its effectiveness in preventing MDD. Without such information, the therapeutic potential of dCBT-I to prevent MDD will not be realized.Despite the success of dCBT-I, it has important limitations. Primarily, dCBT-I has limited capacity to promote treatment buy-in and to tailor specific treatment components to the needs of unique patients, potentially limiting efficacy for clinically complex cases. Thus, treatment strategies that enhance scalability while retaining the flexibility and personalization of specialty care are critically needed.Stepped-care approaches may be ideal for delivering insomnia treatments by capitalizing on the strengths of both digital and clinician-led CBT-I treatment modalities while minimizing their disadvantages , 47. SteIn a stepped-care approach for insomnia treatment, step 1 can leverage primary care and digital technology to maximize the reach of CBT-I to many patients who otherwise would have difficulty accessing care if only given the option to seek treatment in specialty clinics.Step 2 leverages the clinical expertise and flexibility of CBT-I specialists to treat treatment-resistant patients (did not remit in step 1) who may be more clinically complex and may benefit from the more individualized approach that clinician-led CBT-I provides. A sophisticated stepped-care model integrated into primary care that capitalizes on cutting edge eHealth technology and highly trained specialty care carries immense potential for population-level depression-prevention efforts and wide dissemination.Aim 1: Assess the effectiveness of stepped-care treatment for insomnia in primary care. Step 1 will involve randomization to dCBT-I or online sleep education control. dCBT-I patients who do not remit will then be re-randomized in step 2 to either clinician-led CBT-I or sleep education control.Aim 2: Determine the effectiveness of stepped-care insomnia treatment on the prevention of MDD. The effects of our stepped-care model on the 2-year rate of MDD incidence and relapse will be determined.Aim 3: Test rumination as a mediator of treatment response. Lastly, we aim to identify behaviors that facilitate treatment (mediators). Our hypothesis is that reducing rumination  will mediate the effects of dCBT-I/CBT-I on reduced insomnia symptoms and on the prevention of depression. A prior RCT showed that dCBT-I reduces ruminative thinking, which mediated nearly half of the preventive effects on developing new onset clinically significant depressive symptoms . In thisThe specific aims of the Sleep to Reduce Incident Depression Effectively (STRIDE) trial are as follows:The present study is a large-scale stepped-care clinical trial in the primary care setting that utilizes a sequential, multiple assignment, randomized trial (SMART) design to determine the effectiveness of dCBT-I alone and in combination with clinician-led CBT-I for insomnia and the prevention of MDD incidence and relapse. The study sponsor is the National Institute of Mental Health (NIMH), which had no role in the study protocol or study design. Any proposed protocol amendments will first be approved by NIMH and then the local IRB before being implemented. Protocol deviations will be documented using a breach report form.This is a RCT testing the effectiveness of a stepped-care model of insomnia treatment as implemented in primary care for the treatment of insomnia and prevention of MDD. As part of the Perfect Depression Care initiative, Henry Ford Health (HFH) routinely collects Patient Health Questionnaire (PHQ-9)  data froSTRIDE patients are primarily recruited from multiple sources. Primarily, this study uses data from the Perfect Depression Care initiative in HFH primary care. Specifically, we identify individuals with PHQ-9 total scores below the clinical cutoff of 10 , but whoEligibility information will be derived from electronic medical records (EMRs) and from patient reports on an online screening survey. The inclusion criteria are as follows: (1) Insomnia Severity Index (ISI)  score ofPatients are randomized 1:1 to CBT-I or control at each step using block randomization . Only the study coordinator accesses the allocation sequence and assigns patients to groups.Patients are blinded to the active therapy. Therapists are not blinded. Outcomes will be linked to a blinded group variable, which will be unblinded after primary analyses.See Fig. n = 500. The dCBT-I group receives treatment via the Sleepio platform (www.sleepio.com), which includes all six standard components of CBT-I delivered weekly through an automated online health program. The sleep education control group receives weekly electronically delivered information regarding sleep education and sleep hygiene. Patients then complete a study outcome assessment after step 1 treatment.After baseline assessment, participants are randomized into dCBT-I or online sleep education control, each with a group size of Patients who do not remit with dCBT-I  will be randomized to clinician-led CBT-I or sleep education control in step 2 of the SMART design. Treatment will be provided by personnel with CBT-I training (psychologists and nurses). Upon completing step 2, we will assess insomnia and depressive symptoms.At 1 and 2 years after the initial randomization, we will conduct follow-up assessments, which include measures of insomnia and depressive symptoms, as well as assessment of DSM-5 MDD incidence and relapse (via the SCID-5) occurring at any point in the previous 12-month period before the follow-up assessment. Rumination (aim 3) will be assessed at baseline, post-step 1, post-step 2, and at 1- and 2-year follow-ups.www.sleepio.com, Big Health Inc.). Sleepio is among several currently available digital CBT-I programs and was selected for this study because it is evidence-based, standardized, and fully automated. Patients are asked to complete six sessions; each session will be unlocked on a weekly basis, and patients are advised to complete one session per week. The intervention covers behavioral components , cognitive components , progressive muscle relaxation, and sleep hygiene. Sessions are directed by an animated “virtual therapist” who reviews and guides the progress of the patient based on the submitted sleep data. Patients complete daily sleep diaries to help monitor treatment progress and adherence to behavioral sleep strategies.Patients randomized to digital CBT-I in step 1 will complete the Sleepio program via the Internet  the Insomnia Severity Index (ISI) , (aim 2)Screening and baseline assessment occur at the same time point and are captured using online surveys. For screening purposes, patients first complete the ISI and the Quick Inventory of Depressive Symptomatology (QIDS) . PatientPost-step 1 assessment occurs 1 week after completing step 1 intervention (dCBT-I or control) and includes the ISI, QIDS, and PSASC among other clinical measures. The ISI serves as our primary end-point for insomnia symptoms as tested in aim 1. Patients who report insomnia remission  will no longer receive insomnia treatment and will enter the follow-up data collection phase of the study described below.On the other hand, patients who do not remit (ISI ≥ 8 at post-step 1) will then be elevated to step 2 treatment, which involves clinician-led CBT-I or sleep education control conducted via in-person or telemedicine video .Post-step 2 assessment occurs 1 week after completing step 2 intervention (CBT-I or control) and includes the ISI, QIDS, and PSASC among other clinical measures. All step 2 patients then enter the follow-up data collection phase of the study.Follow-up data collection will last for 2 years and consists of both online surveys and telemedicine video clinical interviews. Both the surveys and interviews are administered at 1 and 2 years after completing the final treatment. Surveys include the ISI, QIDS, and PSASC among other clinical symptom measures. The interviews include the SCID-5 module to diagnose major depression, which is oriented to assess over the preceding year; the MDD diagnosis serves as our primary end-point for MDD incidence and relapse for aim 2. In addition, we will assess new involvement in psychotherapy and/or pharmacotherapy for depression, which may reflect new-onset depression.All data will be collected using Qualtrics and will be downloaded from their servers for analysis. Downloaded data will be anonymized and stored on secured network folders that are encrypted and password-protected to preserve confidentiality.To maximize retention, participants will receive reminders for follow-ups via email, phone, and text using the patient portal already in use throughout our primary care networks. In addition, we will pay participants a stipend per assessment and follow up with them throughout the study to ensure participant retention, particularly during the 1- and 2-year follow-up periods. Our group has been successful in this regard (> 85% retention) in prior NIH and industry trials of > 1–2 years duration. Similar to previous long-term studies in our center, between post-treatment and each follow-up session, we will hold 2–3 raffles per year where a participant who updated their contact info during any given 4-month period wins a prize. In addition, we will send out “thank you” notes for each assessment and a regular newsletter of study progress and eventually results to those who have completed the trial.CBT-I is considered safe when delivered in clinician-led and digital formats; thus, the likelihood of serious adverse events occurring during this trial is low. Even so, we will record all occurrences of serious adverse events in patients, which are defined as deaths, suicide attempts, motor vehicle collisions, and complaints about the interventions. Although CBT-I is safe, we will discontinue treatment at patient request and/or if a therapist believes CBTI to be harmful to a patient.As insomnia increases the risk for depression and anxiety, it is possible that patients may contact the research team seeking additional mental health services. When this occurs, the research team will help guide patients to connecting with the appropriate mental health services.Insomnia is a risk factor for suicidal thoughts. Therefore, we will regularly assess suicidal thoughts and behaviors. For patients who express imminent suicidal intent, we will guide patients to seek an evaluation in their nearest hospital emergency services and/or contact their local emergency services to perform a wellness check.An independent data monitoring committee (DMC) consisting of independent scientists was appointed. The DMC met in the first study year to review study protocols and trial safety. The DMC will then meet on an as-needed basis to review safety and trial conduct.The steering committee is led by Drs. Drake (PI), Kalmbach (co-I), and Cheng. The steering committee, under the primary supervision of Dr. Drake, is responsible for facilitating patient recruitment, ensuring systems are in place to guarantee institutional compliance with US laws and NIH policies, reviewing trial conduct, translating the research proposal into operational plans and procedures, and overseeing the dissemination of study findings. The steering committee met weekly during the first 6 months, then biweekly thereafter to monitor the progress of the study objective, review interim analyses, and disseminate study findings. The remaining study team members, including the study coordinator and research assistants, support the study by conducting recruitment, consenting, and data collection at each site as well as data tracking in Qualtrics and reporting on progress.Aim 1: The immediate focus of the analysis will be on the post-treatment impact on sleep outcomes (ISI) of the Internet-based dCBT-I, followed by the clinician-led CBT-I group, compared to the sleep hygiene control group. A linear mixed model will be used to examine the post-treatment sleep values using the baseline values as covariates. The model is flexible and will allow the inclusion of other covariates as appropriate .Aim 2: MDD prevention will be assessed using a generalized mixed-effects logistic model that compares the incidence of MDD at year 1 and 2 follow-ups across treatment conditions. Covariates will also be tested, including baseline depression (QIDS), familial history of depression, and relevant demographics . The effectiveness of the stepped-care model will be assessed via two planned comparisons. The first will compare the rate of depression between those in the full stepped-care condition (dCBT-I to clinician-led CBT-I) and those in the step 2 control (dCBT-I to control). The second will assess the overall effectiveness of the stepped-care model by comparing MDD between those who were eligible to receive stepped-care  and those who received the sleep education control at step 1. A secondary analysis will also be conducted with QIDS scores using a linear mixed-effects model to examine the differences in depression severity.Aim 3 (test rumination as a mediator of CBT-I on depression): Mediation significance testing will involve three models: (1) the direct effect of treatment condition on the treatment outcome , (2) the effect of the treatment condition on the proposed mediator , and (3) the effect of the mediator (change in rumination) on the treatment outcome  while controlling for treatment condition (this is the β pathway). The indirect  effect of the predictor on the outcome variable will be tested using the product of the α and β parameter estimates. Significance testing of the indirect path will be conducted using confidence intervals estimated using the PRODCLIN method implemented in R using RMediation. Detailed descriptive analysis of all quantitative data will be performed. We will use information from this preliminary investigation to (1) describe univariate and bivariate sample distributions of the data, (2) identify the interrelationships among variables , and (3) check for violation of assumptions underlying identified statistical techniques . The study design involves comparing the study arms to evaluate their relative changes from pre-treatment to post-treatment. Consistent with appropriate clinical trial methodology, we will perform intent-to-treat analyses utilizing all data points with mixed modeling. We will use full information maximum likelihood estimation to handle data missingness in our mixed models. NIMH, the study sponsor, had no role in the analysis plan and will have no role in the data analysis or interpretation.Sample size justification and power: Using current recommendations for effectiveness trials, the current study is powered using clinically relevant effect sizes (moderate) for sleep and incident MDD . We hypoInsomnia often triggers MDD, precedes half of depression cases, and is an early behavioral indicator of MDD risk. Furthermore, insomnia is the most frequent residual symptom that persists following successful treatment of MDD, and insomnia is a predictor of relapse. Thus, occurrences of clinical insomnia represent critical periods throughout the trajectory of depression that not only have important predictive value for this debilitating disorder but may also serve as opportunities for intervention to prevent the onset and recurrence of depression.As insomnia is a modifiable risk factor for depression, treating insomnia to remission may prevent depression incidence and relapse. We are testing a stepped-care model of insomnia treatment wherein patients are first treated with digital CBT-I and then step up to clinician-led specialist care for insomnia as necessary. We believe that this highly accessible, efficient, and effective insomnia treatment program has immense potential to curb depression rates in this highly vulnerable patient population.The study results will be reported in accordance with the Standard Protocol Item: Recommendations for Interventional Trials (SPIRIT) guidelines and Consolidated Standards of Reporting Trials (CONSORT) 2010 statements. The results of this trial are expected to have an important positive impact because the demonstration of the effectiveness of a stepped-care approach to insomnia and MDD prevention will justify its wide dissemination as a scalable intervention to improve sleep and mental health outcomes in primary care settings. Importantly, this is where most insomnia treatment is initiated and where CBT-I can have the greatest impact on reducing exposure to high-risk sedative hypnotics.NCT03322774 version February 7, 2022. Recruitment began on March 7, 2018. Status: recruiting. Anticipated recruitment completion date: by the end of 2023.STRIDE World Health Organization Data Set.ClinicalTrials.gov NCT03322774.Registry: Date of registration: October 26, 2017.Sources of monetary support: National Institute of Mental Health (NIMH).Primary sponsor: NIMHContact for public or scientific queries: Christopher L. Drake PhD—cdrake1@hfhs.orgPublic and scientific title: Sleep To Reduce Incident Depression Effectively (STRIDE)Countries of recruitment: USAHealth condition(s) or problem(s) studies: insomnia, depressionKey inclusion and exclusion criteria: ages eligible for the study: ≥ 18 years; sexes eligible for the study: both. Inclusion: clinically significant insomnia symptoms and no clinically significant depression symptoms. Exclusion: current antidepressant use, bipolar disorder, seizure disorders, untreated sleep disorders other than insomnia, and major depression diagnosis at baseline.Study type:InterventionalAllocation: randomizedIntervention model: parallel assignmentMasking: single-blind (patient)Primary purpose: preventionDate of first enrollment: March 2018Target sample size: 1000Recruitment status: recruitingPrimary outcomes: prevention of major depressive disorder, insomnia remission, and mediation of depression prevention by reducing nocturnal rumination.


The world has been affected socioeconomically for the last two years due to the emergence of different variants of the COVID-19 virus. Vaccination is the major and most efficient way to prevent the widening of this pandemic. Those who are having comorbidities are more vulnerable to serious infections due to their immunocompromised state. Additionally, cancer patients could be at significant risk for COVID-19. In this pandemic era, the diagnosis and treatment of cancer were significantly affected. Clinical trials at the initial stage were performed on healthy or COVID-19 infected patients. This produces a greater level of hesitancy in cancer patients. This review article provide an update regarding the vaccination and treatment for COVID-19 in patients with cancer and future directions. The COVID-19 outbreak has caused catastrophe in health care systems, raising worries about its influence on non-COVID illnesses . Cancer This review aims to highlight the requirement for substantial clinical proof of the efficacy and safety profile of several COVID-19 vaccines in order to motivate patients to get immunized. To give the best care, the impact of SARS-CoV-2 on the different forms of cancer differs and has to be thoroughly researched. The review makes the claim that it will help readers comprehend how cancer and other co-occurring disorders are linked to COVID. It also focuses on the hesitancy, its cause, and the necessary precautions to be undertaken before receiving a vaccine.According to Allegra et al. , COVID-1Cancer patients are more likely to be hospitalized and die after contracting SARS-CoV-2 . As a reHuman tissues other than the lungs express TMPRSS2 and ACE2, including the testes, which are susceptible to SARS-CoV-2 infection. A very common alteration in prostate cancer is the fusion of TMPRSS2 with another androgen-responsive gene. In their study, Bhowmick NA et al. emphasized the evidence that TMPRSS2 and ACE2 are affected by androgens, as well as the implications of using androgen suppression to inhibit TMPRSS2 to target SARS-CoV-2 .Cancer treatment is primarily provided by pre-pandemic standards in regions with a low prevalence of viral infection. It is often advised that treatment be postponed until it is certain the patient will not get COVID-19 when a patient is known to have been infected with SARS-CoV-2, especially if he or she has not had a COVID-19 vaccination or if the vaccine is anticipated to have an unsatisfactory response. Patients undergoing low-risk cancer medicines, such as hormone medications, may be exempt from receiving therapy . For patCancer treatment in locations with strong viral transmission-the parts that follow will focus on the challenges associated with systemic anticancer medicines, radiation therapy, and surgery in regions with high rates of persistent viral transmission during the pandemic’s peak times of activity. In areas where the virus is less prevalent, all of these characteristics are less significant .Barrière et al. provide five suggestions to health authorities and healthcare professionals .Statement 1: All cancer patients should have a third vaccination dose three to four months after receiving the second dose (Dose 2), along with controls for any remaining anti-S serum antibodies, as cancer patients have a lower median anti-S antibody titer after two vaccine doses than the general population. The data currently available demonstrate quicker Omicron VOC immunity fading than the Delta strain, but enhanced protection following booster dosing (Dose 3) .Statement 2: Decide that if a patient’s serum anti-SARS-CoV-2 S (antiS) titer falls below 1000 BAU/mL, the fourth dose of vaccination should be suggested. This cut-off corresponds to titers seen in a group of individuals without comorbidities 3–4 months after Dose 2, for whom Dose 3 treatment is currently recommended in the majority of industrialized countries to give the best protection against the Omicron variant.Statement 3: Monoclonal antibody (mAB) tixagevimab/cilgavimab  is used for pre-exposure prophylaxis for cancer patients who do not have seroconversion after Dose 3 or 4. This combination of long-acting anti-S mAbs has a remarkable effect on in vitro efficacy of Delta VOC and is less affected by several Omicron S mutations ,35.Statement 4-A three-dose complete vaccination for the patient’s family should be suggested as soon as 4 months following Dose 2. Additionally, when in close, frequent contact with immune-compromised parents, the majority of Scientific Pediatric Societies, as well as the US (Food and Drug Administration) and European Medicines Agency (EMA) Health Agency advise the immunizing children between the ages of 5 and 11 .Statement 5: Patients should use a high-protection mask that filters at least 95% of particles(N95) and has a filtering facepiece type 2 (FFP2). Such masks should be required in crowded environments, whether on public or private transport (when shared with others). Recent comparative data demonstrates that these masks offer more effective personal protection than surgical masks .According to current prime-boost theories, patients with cancer can receive the COVID-19 vaccine in a safe and therapeutically effective way ,39,40. TNew observational research published by Sheeba Irshad et al. involved 151 cancer patients, including 95 with organ cancer and 56 patients with hematological cancer . There wAn international panel of oncology experts examined the long-term consequences of the pandemic on cancer clinical trials using new data on worldwide clinical trials gathered by IQVIA, and suggests remedies for clinical trial stakeholders . OncologPatients who have had malignant tumors may have diminished immunity as a result of immunosenescence, previous treatment, or comorbidities, which will affect the effectiveness of COVID-19 vaccines . People Vaccine hesitancy is more prevalent in malignant patients as compared to the normal individual. A study conducted on 429 patients concluded that 48% of the population was unsure regarding the vaccine consumption primarily due to safety concerns (32%) and about the complication it might cause (12%) . AccordiA cancer patient receives many treatments, the bulk of which target the immune system. According to a research, cancer patients have a greater fatality rate and need for intensive care than healthy people do. Immunosuppression in patients limits the use of live vaccines due to an increased risk of infection. However, immunization is necessary to guard against novel variations. If the patient is commencing chemotherapy, they should allow at least 14 days before the immunization. A patient with blood cancer who is receiving chemotherapy should not be vaccinated until the neutrophils achieve homeostasis. This circumstance has caused cancer therapy to be postponed or interrupted. This element may make the malignancy worse and, in extreme situations, may be lethal. According to clinical research on 18 cancer patients who had recently contracted COVID-19, the fatality rate for cancer patients had increased to 5.6% from 2.3%. This emphasizes that in order to offer proper care and maintain patient safety, a thorough investigation regarding the effects of real illness and vaccination must be conducted.The COVID-19 pandemic encourages us to develop viable strategies for dealing with subsequent health crises ,68,69,70