Epidemiology - Science topic

The creation and approval of local clinical guidelines in developing countries, where international guidelines are inadequate, involve several essential steps and criteria. These countries often face challenges such as resource limitations, epidemiological, cultural, and social differences, and lack of infrastructure, requiring an adapted process to their specific realities. The following are the main steps and criteria involved:

1. Identifying Needs and Local Context Analysis

2. Formation of the Development Committee

3. Review of Scientific Evidence and Contextual Adaptation

4. Development of Recommendations

5. Public Consultation and Peer Review

6. Pilot Testing and Evaluation

7. Formal Approval

8. Dissemination and Training

9. Monitoring and Continuous Review

Necessary Criteria for Development and Approval

The creation of local clinical guidelines in developing countries is a complex process that requires a collaborative approach adapted to the specific context of each country. Considering cultural differences, resource limitations, and the reality of the health system is essential to ensure that the guidelines are effective and contribute to improving the health indicators of the population.

4o

Here are brief definitions for key epidemiology terms:

These measures help understand the frequency, severity, and impact of health conditions.

I agree with you

Limitation in recall refers to the general inability of individuals to remember past events accurately or completely. This can be due to a variety of factors, including the passage of time, the complexity of the information, the individual’s cognitive abilities, or the context in which the information was encoded and stored.

Recall bias is a type of systematic error that occurs when there is a differential accuracy of recall between study groups. It typically arises in retrospective studies when participants with a particular outcome or exposure remember past events differently than those without the outcome or exposure.

A p-value of less than .001 (p < .001) indicates that the observed differences in hypertension prevalence among the three levels of poverty are unlikely to have occurred by random chance alone. In other words, the results are statistically significant.

Interpretation: Since the p-value is less than .001, it suggests that there is strong evidence to reject the null hypothesis, which typically assumes no difference between groups. In this case, it would imply that there are indeed differences in the prevalence of hypertension across the three levels of poverty.

It would be beneficial to conduct additional tests to explore the nature and magnitude of these differences further. This could involve pairwise comparisons between specific poverty levels to identify which groups differ significantly from each other in terms of hypertension prevalence.

The graph you uploaded, and the code to produce it can be found on this page:

sysuse auto, clear

quietly regress price mpg trunk length turn if foreign==0

estimates store D

quietly regress price mpg trunk length turn if foreign==1

estimates store F

quietly regress weight mpg trunk length turn if foreign==0

estimates store D_weight

quietly regress weight mpg trunk length turn if foreign==1

estimates store F_weight

coefplot (D, label(Domestic)) (F, label(Foreign)), bylabel(Price) ///

|| (D_weight) (F_weight), bylabel(Weight) ///

||, drop(_cons) xline(0) byopts(xrescale) // scheme(s2color)

To get the same graphics scheme shown on the web page, remove the // before scheme(s2color). If you use the default graphics scheme for Stata 18 (the current version), the graph will look like the one I attached.

With kindness, this request is unlikely to help you get onto a PhD programme. Staff in university departments receive direct requests like this daily and do not have capacity to provide information they would expect the candidate to source for themselves.

I hope the following tips help you apply successfully.

1. Search for different Public Health departments that are undertaking research you're interested in. You can do that either department websites, or through literature searching on topics that would interest you and note where key scholars in public health are - they may be able to supervise you or know who might be open to supervision.

2. Using the questions you've asked (Program details, research areas, and deadlines; Scholarships and financial aid availability; Application process and link; Admissions requirements and deadlines; Current projects and faculty research; Any recent program advertisements) search university websites and also academic job websites like jobs.ac.uk. You can narrow down by topic (public health) and level of work/funding (PhD/postgraduate). The information you want to know will be included in funding calls, adverts for PhD candidates, or university web pages aimed at doctoral students.

3. Having found a potential funder/supervisor you can either apply directly if there is a specific opportunity advertised. Or you can approach a potential supervisor and ask them if they have spaces to supervise you. You should also include a brief abstract outlining what you'd like to study and a link to your CV. Do not include the list of questions you've put here and ask them to do that work for you as sadly it won't count in your favour. They will prioritise candidates who have sourced these answers themselves and know what they want to do and can demonstrate their proposed PhD would align with the supervisor/department goals and that the candidate is of a standard to fit with the university doctoral programme's requirements.

4. You ask "I would appreciate any updates or resources that you may have regarding the program's current status, faculty, and research activities". This is for you to find out, perhaps via this site, but also other academic groups, societies, literature searches and social media. They will prioritise candidates who are informed and aren't asking for updates that busy academics unfortunately don't have time to deliver individually. Follow academics on social media and most will be sharing this kind of update for you to appreciate.

5. If you're sending a request like this via email and are not getting a reply it'll be because you're asking them to help you apply, whereas they want to see what you can offer and where they might align. They won't answer requests like the one you've posted here because they are overwhelmed and don't have capacity. They may also perceive you as sending the same messages to many places, indicating there's nothing special about them but you're expecting free work. To avoid this, focus your requests and demonstrate why you'd be a good person for them to work alongside and support in your studies. Avoid ending messages with "Reply to this discussion" as it will appear demanding and rude (although I know that isn't what you intended).

6. Ensure things like funding, visas etc are either possible, sorted, or in the pipeline. It may be they can assist with a PhD place/supervision but the funding and visa aspect will be for you to sort. They may have funding, but they may not. Don't rely on them sorting that, again it's for you to find out about, or ideally apply for funded PhDs in Public Health. You can try places like Find a Phd for this https://www.findaphd.com

If you're based in a low or middle income country you can join Author Aid who have free training for scholars and can also give advice if you can't find answers to questions that need researching as part of your PhD application process. It's a nice friendly community too. https://www.authoraid.info/en/

Hope that helps and feel free to ask if anything isn't clear. TL;DR do the majority of this research yourself to present your ideas as an outstanding candidate. Get help with friends/colleagues along the way if you find some of those tasks challenging. Good luck!

Both "among" and "in" can be appropriate in titles when discussing a group within a larger category, but the choice depends on the specific context and emphasis of the title. Here's a brief overview of the optimal usage for each term:

Among:

Use "among" when you want to emphasize the idea of being part of a larger group or set, but not necessarily confined to it. This term suggests that the group you're referring to is integrated or exists within a broader context.

Example title: "Patterns of Communication Among Adolescents in Urban Schools"

In:

Use "in" when you want to emphasize the idea of being contained or located within a specific category or context. This term suggests a more specific or bounded relationship between the group and the larger category.

Example title: "Factors Affecting Academic Achievement in Students with Disabilities"

In summary, consider the nuances of meaning and emphasis you want to convey in your title when choosing between "among" and "in." If you want to highlight the group's integration within a larger context, use "among." If you want to emphasize their specific location or relationship within a category, use "in."

Bruce Weaver I'm sorry, I forgot to include the other indirect effects (which were negative, significant). Yes, the sum of these effects + direct effect is the total effect.

Total Effect: Negative (-0.42)

Indirect Effect 1: Positive (0.03)

Indirect Effect 2: negative (-0.22)

Indirect Effect 3: positive (0.06) - Not significant

Direct Effect: Negative (-0.29)

Now, can you tell me how I could interpret this positive indirect effect in the face of the total and direct positive effects?

The interpretations depends on all aspects either positive nor negative.simply advantages and disadvantages .

Liverpool School of Tropical Medicine , Global Health Trials Unit can offer this service

Holistic healing approach is the most beneficial for all health issues.

A new study has found that no cases of cervical cancer have been detected in young women who have been fully-vaccinated as part of the HPV immunisation programme.

The Public Health Scotland (PHS) research said the HPV (human papillomavirus virus) vaccine was "highly effective" in preventing the development of the cancer...

It is possible to conduct a meta-analysis of the studies which examine the association of millet consumption and diabetes mellitus, if the studies that have been retrieved by a comprehensive searching process is not too heterogeneous. If, however, there is insufficient number of studies which can possibly be retrieved by a comprehensive searching process, then it is possible to conduct other epidemiological studies which aims to examine the level of association.

Some of the key challenges gathered:

1. Infection Control: Infectious diseases can be highly contagious, and strict infection control measures are crucial to prevent the spread of the disease among patients, healthcare workers, and the broader community. Critical care and anesthesia units need to have robust infection controlprotocols in place, including appropriate isolation procedures, personal protective equipment (PPE) usage, and disinfection practices. Balancing the need for effective infection control with the provision of necessary care can be challenging.

2. Transmission Risk: Healthcare workers, including critical care and anesthesia providers, are at an increased risk of exposure to infectious diseases due to close contact with infected patients, aerosol-generating procedures, and potential exposure to bodily fluids. Adequate training, adherence to infection control protocols, and availability of appropriate PPE are essential to minimize the risk of transmission to healthcare professionals.

3. Resource Allocation: Infectious disease outbreaks can strain healthcare resources, including critical care beds, ventilators, medications, and specialized equipment. The increased demand for these resources during outbreaks may require careful allocation and prioritization of resources to ensure optimal care for critically ill patients. Ethical considerations, such as fair distribution and maximizing the overall benefit, may come into play when making resource allocation decisions.

4. Diagnostic Challenges: Prompt and accurate diagnosis of infectious diseases is crucial for appropriate patient management. However, some infectious diseases may present with nonspecific symptoms or have overlapping clinical features, making diagnosis challenging. Access to rapid and reliable diagnostic tests is essential to facilitate timely and accurate diagnosis, which can impact treatment decisions and infection control measures.

5. Staffing and Workforce Management: Infectious disease outbreaks can lead to increased patient loads and workforce demands, potentially straining the healthcare system. Adequate staffing levels, including trained critical care and anesthesia providers, are essential to meet the increased demand for services without compromising patient care. Ensuring the physical and mental well-being of healthcare providers is crucial to sustain the workforce during challenging times.

6. Evolving Knowledge and Guidelines: Infectious diseases often present new challenges and require healthcare providers to stay updated on the latest knowledge, guidelines, and best practices. Rapidly evolving evidence and changing recommendations can pose challenges in providing consistent and evidence-based care. Continuous education and training are essential to ensure healthcare providers are equipped with the most current information and can adapt their practices accordingly.

These challenges highlight the importance of preparedness, infection control measures, collaboration across healthcare teams, and ongoing education and training to effectively provide critical care and anesthesia services in the context of infectious diseases.

Hope it helps

infectious disease outbreaks have a huge impact on health systems and the well-being of the people affected in addition to responders themselves.

- First of all, they cause disruption to other health services provided. For example, during COVID-19, a lot of services for chronic diseases were disrupted and the focus was on more acute cases of the infectious disease.

- additionally, the public health measures taken, such as quarantine and physical distancing can have an impact on mental health.

That is why other aspects of health and well-being such as mental health should be considered during infectious disease outbreaks.

I published a paper about how mental health interventions could be integrated into outbreak response.

Share of informal workers is an indicator of "not enough" for defining a separate welfare state model. As, for example, the share of unemployed, the share of high-tech employees, etc.

Thanks for clarifying. Why do you think you need to carve g/day into tertiles? Carving quantitative variables into categories can cause many problems. See this page for more info:

So basically you're discussing the use of observational data to answer causal questions (which are often best answered using randomized trials). In that case, the most important thing will be bias (selection bias, measurement error, and confounding bias). I will specifically look for the detail of study design and statistical analyses on this part, i.e., how the authors came up with measures to mitigate bias when they recruit and follow up participants, or if this is a retrospective study, how they can confirm the validity of the measurements.

Confounding is often seen as the most important problem in answering causal questions, so of course I'll look for the methods used to control for confounding. As you said in your comment, it may be multiple regression where the potential confounders are selected based on a DAG (or DAGs), some causal inference method such as propensity score or instrumental variable, or the confounders are controlled by design (restriction, matching, etc). However, I believe the use of one method is not sufficient; I'll read the description, too, to make sure that their actual implementation is valid. Unfortunately, you'll see that not all papers described their DAG in detail (e.g., how they came up with the variables and the relationships between variables); some didn't even publish their DAG. Or for propensity score methods, they didn't show the diagnostic results (SMDs, Love plot, histogram of weights).

It's hard to summarize everything I'll look for in a few keywords, but yeah, probably "did they handle bias properly?".

@athanasios paraskevopoulus reach me at Doris.Nyamwaya@mrcuganda.org

Hello Sherif Hammad , it is very interesting to read your question and feel your enthusiasm to start your academic journey. This question reminded me of myself back in 2018. I will provide you with some tips that helped me to be involved in the research community until now:

With pleasure, I can support you in your journey and I believe you have more capabilities than what you think.

Best wishes for you

the nature of variable, maybe... you can to try do this in JAMOVI, "medmod" pack.

It is probably too late for the original poster, but blog post on how to create a havest plot in R using ggplot (which I contributed to) is available at https://medium.com/@cxiao94/creating-harvest-plots-in-r-75fb45c8f393 Hopefully the code used there can be adapted to your needs.

Les mesures des variables doivent à mon avis tenir compte des conditions de la station où sont repérés les paramètres naturels (à décrire rigoureusement). Bonne chance!

With nature being exploited, global warming, threat of bioterrorism, Such Pandemics is not far from reality, one health approach is the solution. the article is attached

Samuel Oluwaseun Adeyemo Thank you for your explanation. Moreover, Sometimes we need to think about the confounding effect and effect modifiers. Most of the paper articles do not consider them. Is there any impact of these in the final model?

The parasite is diagnosed by the detection of Schistosoma eggs in the urine through stool and biopsy materials. The most appropriate method to detect the eggs in the urine is by examining the last part of the urine which passed in the afternoon after being centrifuged

I would be very careful and be sure of what Data is being released and in what form, be it sanitized, even low numbers with a small geographical area presents with potential identification of individuals. I can't stress enough, given the opaque closed source nature of the even supposedly "Open AI", which is far from.bring the open platform. It is increasingly attractive to be "early adopters" of potentially disruptive technologies and those which have enormous promise but the unbreakable rules regarding confidentially and the protection of the patients, must be given a absolute full review against the baseline ethical principles upon which our effectivness is alway being hit with data breaches and disclosures. This causes stress, ansgt, and distrust of doctors and the medical/pharmaceutical complex and encourages conspiracy theories and groups of people who have run from the people tryinf to help them (ground epidemiologist in the near recent and long Ebola Outbreak in Western Africa. A lot of care and trust management efforts should be out into place to restore the population's trust in caregivers. As a whole these caregivers, doctors, and scientists do have the public and individual patient's best interests and seek to achieve positive outcomes. But be remainded the Trust is earned. Is easy to lose, and though it can be regained, it is s very long and difficult path. After the mistakes, folly, and subsequent failure of the trusts relationship during the above epidemic. A team I was working with attempted to solve the inherent intrusive nature of contact tracing in a world of mass surveillance as potential contects, so afraid due to misinformation and conspiracy, in part due to lack of effective health emergency communications, were left with a void of reliable Informationen. This provides a door so big a train of conspiracy went driving through delivering a flood of outlandish claims (one bring them that vaccines contain aluminum preservtibe which was an "antenna" to communicate with Bill Gates. This came from the mount of a board certified pediatrician. The already present iron in you blood is a far better antenna. The point being as we seek to use technology, and new ones, careful attension must be paid to understanding exactly how it works and effectivly communicating thst to the public before people are left to make assumptions and suppositon. We envisioned an advanced contract tracing method using the tools of mass surveillance but wrapping the how, when, and where in a Blockchain encryption, where the system would only deliver "contacts" not the potentially private and and sources with high abuse potential concealed and not available for any other purpose, nor available for backward looking research, to rapidly increee the the Context trwcing, protecting vulnerable people, the vulnerable boots on the ground, and removing any potential for the tempting misuse of the data for anything other then that which exempts said data from the definition of "human research" while removing the potential for pressure to be applied by a local government, law enforcement, and other govermental uses outside the scope of the U.S..Common Rule exempting "forward looking only" epidemiological contact tracing from the definition of "research of human subjects" which allows the more rapid adoption of new technologies and surveillance without sacrificing speed, ground staff safety and equally important and often not well communicated the person's individual privacy concerns. The latter can and had shown to habe the most delirious effects on trust, opens the door for misinformation, and harms the whole effort increasing overall speed and efficacy. So, tred but tred carefully on there new tools especially where the functioning and data collection by the holders of sources code is being treated as a national security matter. This is counter productive and csnlewd to very serious loss of freut end confidece levels so well illuminated in the past and ongoing pandemic was vaccine roll out. It was shocking that the nation-states allowed the non-disclosure of the ingredients. Equally, the roll out of a human trial, which was a phase I (one) through 3 (three), multi-center clinical trials with seriously difficent state supported lack of "informed consent" without just bring honest with the population shows a serious communications failure and opened the door of the absurd commentary about aluminum antennas and the hundred other equally disturbing conspiracies which were in fact the failure of those running the otogrems to coordinate and communicate well with the public as one of the several ways to diffuse conspiracy and to bolster trust. Require the full disclosure by the ChatPT (and I hesitate strongly as a Philosophy graduate to use common anthropomorphisms thrown around without meaning or understandinf of A.I., M.L., Neural Networks, and Quantum anything). Be careful in your buzz word chocies as all of the above rest on shaky if not complete nonsensical foundations.

Yes there's

I'm curious to know why you asked? Is there some reason that this might not be the right thing to do in your case, or did someone simply tell you that you shouldn't do it?^*

^*My attitude to people who tell you that you shouldn't do something is summed up by Terry Pratchett : Nothing is really worth doing unless there is somebody, somewhere, who would much rather you didn't.

Osinachi Ekeagwu

Dear Dr. Ekeagwu,

I am sorry for my delayed reply.

Thank you for spending your worth time on feedback, which not only assisted me in reaching acceptable answers but also made me look at the issue from a different perspective. However, I do not agree with your points 2 and 5 so much.

In general, I think it is true that due to significant heterogeneity, the pooled prevalence or incidence may not be considered too correct and logical; however, sometimes the policymaker wants to make a series of comparisons between countries on a broad level or make decisions supposedly for the provision of medicine based on the results from pooled means. Therefore, pooled prevalence or incidence can maybe be useful in this regard.

Best,

There are several statistical analyses that could be useful for a systematic review or meta-analysis of epidemiological and cost data. The specific analysis that is most appropriate will depend on the research question being addressed and the type and format of the data available.

Some common statistical analyses that may be useful in a systematic review or meta-analysis of epidemiological and cost data include:

It is important to carefully consider the statistical analysis that is most appropriate for your systematic review or meta-analysis, as the choice of analysis can greatly affect the results and conclusions of the study. It is also recommended to consult with a statistician or other expert in statistical analysis when planning and conducting your study.

I hope this helps.

If your main goal is to estimate values in the larger population, then the formula using the estimated variance makes the most sense. Alternatively, if your goal is to test specific hypotheses, then G*Power might be better suited to your objective.s

My openion about mRNA and vectorial AntiCovid vaccines that they play an important role in facing pandemic in the world so any withdrawal must be with more effective and cheaper one

Lin, H., Yu, W., A. Sabet, K. et al. Ferrobotic swarms enable accessible and adaptable automated viral testing. Nature 611, 570–577 (2022). https://doi.org/10.1038/s41586-022-05408-3

describes a palm sized printed circuit board-based programmable platform for viral testing.

Worldwide COVID-19 cases decline by 18% | Al Bawaba

Thermofisher Scientific has a virtual lab training option on cell culture. You can check here: https://www.thermofisher.com/bd/en/home/global/forms/cell-culture-basics.html

malignant mesothelioma in India is quite rare, according to Indian council of medical research, cancer registry the reported incidence is 0.05-0.08 and 0.05-0.1per 100,000 in men and women respectively

Zinc, copper, manganese, and selenium are main trace elements that have protective roles against radiation-induced DNA damages. Trace elements in the free salt forms have protective effect against cell toxicity induced by oxidative stress, metal-complex are more active in the attenuation of ROS particularly through superoxide dismutase mimetic activity. Manganese-complexes in protection of normal cell against radiation without any protective effect on cancer cells

i think acute fatal disease will have High YLL but low YLD, whereas NCDs will have high YLD with YLL may be high or low. Chronic diseases like Polio / Leprosy will have high YLD with low aYLL

Better to do a pooled prevalence, with some sampling weightings, or a population weighted meta prevalence . You can also do an inverse variance weighted prevalence

ie p = sigma (NiPi)/sigma (Ni) where p = meta prev, Ni = population in study i,

Pi = prevalence in study i.

or p = sigma (Pi/var Pi)/sigma (1/varPi)

for more details see attached papers.

Let's abolish ‘fold higher’ and ‘fold increase’ from our lexicon

Then there is this from Wiktionary [4]: “Some writers and speakers use misconstructions like ‘an increase by twofold’, which they believe to mean the same thing as ‘a twofold increase’. But these two things logically mean ‘an increase by 200% of the original amount’ and ‘an increase to 200% of the original amount’, respectively. This practice is not only ambiguous but grammatically poor; it misuses -fold by using it as a noun”.

My opinion of the issue is reflected best by the blog and responding comments on John Petrie's LifeBlag [5]. The blog in part says the following: “As far as the word ‘fold’ goes, I thought its meaning seemed clear to me, but its meaning as used seems different, and I would typically avoid using it if I were writing a scientific paper and not just editing others’ papers. In my job as a scientific editor, I think every time I've ever seen the word fold, it has meant ‘entailing multiplication by a factor of [the number that comes before it]’. In other words, a 2.5-fold increase always is used to mean ‘multiplied by 2.5 times’. Therefore, people would say both that $250 is 2.5-fold greater than $100 and that $250 is 2.5-fold (of) $100. That makes no sense to me”. Comments to that posting express similar confusion.

Suraj Kapoor , thanks Mr Kapoor. It is very interesting paper. However, they only say: "that is better sutied" without explanation, but providing great practical examples.

Dear Mendiore

CDC guideline have 9 component of evaluation. Some.of these are quantitative like Sensitivity, PPV and data Quality. So these are easily calculated. However some of the indicator are qualitative. Which are to be ascertained through interview of related stake holders.

We have used CDC guideline these are easy and friendly to use. I will share you my evaluation report which have all these CDC guideline indicators of evaluation of public health programs.

Please mail me on drsandeepguriro@gmail.com

Thanks

Causality is something that is inferred on the basis of evidence. Bradford Hill's criteria are not a checklist. Rather, they constitute the categories of evidence that we may use to infer causality. We may not have evidence in all of the categories before we are obliged to make a decision.

And this is the other important point. Causality doesn't mean a philosophical certainty about the mechanism, it means that we believe that we have identified a causal pathway that is worth acting on. The decision to act has also to take into account the dangers of acting now versus waiting for more data, the costs involved and the potential consequences.

So Bradford Hill's list is a way of categorising evidence. Its use is in a decision making process. It's not epistemology, it's public health!

As in regression analysis, paths in path analysis (which are regression coefficients) can become smaller, insignificant and even change signs when you add additional predictors/paths to the model. This is often due to effects of redundancy (overlap/correlation/collinearity between independent variables). As you note, sulphur dioxide emissions and GDP are related and therefore partially redundant. Differences in sulphur dioxide emissions may not account for any variation in mortality above and beyond what can be explained by differences in GDP.

An alternative (or additional) explanation could be differences in the sample size when adding GDP due to missing data. A reduction in sample size may reduce your statistical power for showing that a coefficient is different from zero.

Epidemiology provides the data that is required to take policy decisions. Studying the distribution of diseases, which is one of the components of Epidemiology, helps us in identifying the health problems of public health importance & prioritizing them. This knowledge can help in drawing the attention of the policy makers to these priority health problems so that they can make wise policy decisions accordingly. In a resource-crunch setting, we would be able to make the best possible use of the available resources by diverting them towards the priority health problems. And evidence for this comes from epidemiology.

Policy, on the other hand, aims to achieve the goals put forward as regards any particular priority health problem that it targets & through its implementation, it has the potential to change the epidemiology of the same.

Thus, both influence each other.

OSDEA is easy and also free.

MATLAB

Robert Shour

Also have a look at this:

Thanks!

Yes, You can apply mixed model in epidemiological studies based on the design and your research objectives.

T-test (2 groups) and ANOVA (3 or more groups) are most common

Excellent book chapter: https://www.sciencedirect.com/science/article/pii/B9780123746023000286

Papers:

The incidence rate can be calculated retrospectively, Adil G. Fadil , as James Leigh explained.

You will need census estimates of the region's population over the time period. Of course, you won't have census data for every year, so the convention is to assume that the population changes linearly between census estimates.

The incidence is the number of cases over the number of person-years of exposure, so your exposure is the sum of all the annual population estimates.

In the very near of the BT bifurcation, we observe mainly four kinds of bifurcation (transcritical, saddle-node, Hopf and Homoclinic) and the character of the interior equilibrium point will show stable focus, stable limit cycle, Homoclinic loop, unstable focus, etc. So, I think to understand the biological significance of BT bifurcation in the epidemic model you need to specify the dimension of the model. Then we can clear it. Otherwise, it is difficult.

Yes certainly !!!, it is possible even in vaccinated people, as well as facing to the new varients

There are numerous examples of using SEIR model involving vaccination, see e.g. this google search:

https://scholar.google.com/scholar?q=seir+model+vaccination

and/or:

I can't say much about the other model you intend to include because I could not understand it well enough based on your description.

for sure it's 100% possible even with vaccine

Dear Mr. Hatami!

I searched for YOU articles that deal with the problems of "depression and psychiatric problems before and after pandemic" so you can contact the authors who are interested in the same topics:

1) Kim, H., Rackoff, G.N., Fitzsimmons-Craft, E.E. et al. College Mental Health Before and During the COVID-19 Pandemic: Results From a Nationwide Survey. Cogn Ther Res (2021). https://doi.org/10.1007/s10608-021-10241-5 Free access:

2) Watkins-Martin, K., Orri, M., Pennestri, MH. et al. Depression and anxiety symptoms in young adults before and during the COVID-19 pandemic: evidence from a Canadian population-based cohort. Ann Gen Psychiatry 20, 42 (2021). https://doi.org/10.1186/s12991-021-00362-2 Open access:

3) Villarreal-Zegarra, D., Copez-Lonzoy, A., Vilela-Estrada, A.L. et al. Depression, post-traumatic stress, anxiety, and fear of COVID-19 in the general population and health-care workers: prevalence, relationship, and explicative model in Peru. BMC Psychiatry 21, 455 (2021). https://doi.org/10.1186/s12888-021-03456-z Open access:

4) Shaikh, A., Peprah, E., Mohamed, R.H. et al. COVID-19 and mental health: a multi-country study—the effects of lockdown on the mental health of young adults. Middle East Curr Psychiatry 28, 51 (2021). https://doi.org/10.1186/s43045-021-00116-6 Open access:

5) Panchal, U., Salazar de Pablo, G., Franco, M. et al. The impact of COVID-19 lockdown on child and adolescent mental health: systematic review. Eur Child Adolesc Psychiatry (2021). https://doi.org/10.1007/s00787-021-01856-w Open access:

6) Engin Burak Selçuk et al. (2021). Anxiety, depression and post-traumatic stress disorder symptoms in adolesce nts during the COVID-19 outbreak and associated factors, International Journal of Clinical Practice, Early View, 16 Sept. 2021 Free access:

7) Darren Hedley et al. (2021). The association between COVID-19, personal wellbeing, depression, and suicide risk factors in Australian autistic adults, Autism Research, Early View, 21 Sept. 2021, Open access:

8) Duncan Thomas et al. (2021). Prevalence, severity and distribution of depression and anxiety symptoms using observational data collected before and nine months into the COVID-19 pandemic, The Lancet Regional Health - Americas, Volume 1, September 2021, Free access:

Yours sincerely, Bulcsu Szekely

Covid

At a large hospital in Montreal (where my son works) many nurses have resigned and only a few doctors are remaining (most are taking a leave of absence, or a holiday, just to get out). The vaccine mandate (take vaccine or leave) has stripped this hospital of professionals rendering it useless. Who is going to treat patients?Maybe the administrators!

Please have a look at this useful link.

I hope the following is interesting to you

Dear Sunday,

I do not what facilities you have in your department to conduct research on molecular epidemiology of some emerging zoonotic diseases. If your laboratory is well equipped and your Adviser agrees, you may plan your research on some emerging pathogen , such as Nipah virus, Cryptosporidium parvum, Rift Valley fever virus, Burkholderia pseudomallei etc.

If you have some interest in mycotic infections, please upload my over 110 papers related to mycoses.

Stay safe and healthy.

With best wishes,

Prof.Dr.Mahendra Pal

Founder Director of Narayan Consultancy on Veterinary Public Health and Microbiology

No.

Please go through the following useful RG links.

The OPGD model and "GD" R software package were recommended to identify spatial determinants from a perspective of spatial heterogeneity. You can refer the guide to use the model https://cran.r-project.org/web/packages/GD/vignettes/GD.html. As a result, you can visualise contributions of determinants, and the interactive impacts of spatial variables.

Los más comunes son depresión, estrés, miedo, ansiedad, desesperación, tristeza etc

Prof. Charles Anukwonke: Before answering your valuable question, let us ask ourselves the following crucial question:

If COVID-19 is one of nature's secretions, we are part of "Nature" and we should realize that we have to always be in harmony with it. Anyhow, we must know how we know how to live with this pandemic while it lasts, indisputably. I hope that it was not fabricated inside the labs and it was not spread by a mistake. However, the coming days will prove if it is a nature-created or a man-made virus!

Now, let us ask another question:

If the COVID-19 pandemic is one of nature's secretions, do you think that the pandemic has its "cyclical apparition"?