A set of training materials for professionals working in intervention epidemiology, public health microbiology and infection control and hospital hygiene.
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From the page on applied immunology we have understood that our immune system plays a vital role in determining whether or not we are susceptible to infections. Yet other factors can play a role too, either by directly influencing susceptibility, or by influencing the immune system.
An often described fact is how a genetic disorder called sickle cell anemia enhances susceptibility against malaria infections. This disorder is caused by a single mutation in the gene that produces hemoglobin, the protein in our red blood cells that transports oxygen. At a specific location in the hemoglobin gene, only one single change is made. Since we have two copies of each of our genes (one from our mother and one from our father), it could happen that only one of these genes have this mutation, while the other gene is still 'healthy'. When that occurs, this is called a heterozygous gene. When the mutation happens in both genes this is called homozygous. People who are homozygous for the sickle cell trait, cannot produce normal hemoglobin, which leads to a form of anemia where the red blood cells lose their round shape and turn to curved 'sickles'. People who are heterozygous have a high resistance to malaria infections (though not 100%).
Similarly, resistance against norovirus occurs when in the FUT2 gene a single nucleotide is mutated, where an amino acid guanine (G) is changed for adenine (A). In this case, you need to have the mutation on both copies of the gene (homozygous) in order to be resistant to norovirus. People who are heterozygous for this mutation, are not resistant to norovirus. The down side is that homozygous FUT2 mutations in this specific example probably lead to a higher susceptibility to influenza virus.
The huge amount of microbes that live with us in and on our body affects our ability to deal with infectious diseases. Recently the intensity of infection and the success of certain parasite strains have found to be influenced by the microbiome.
Since a long time we know that vitamin A affects our suscebtibility to infections. Vitamin A deficiency impairs innate immunity by impeding normal regeneration of mucosal barriers damaged by infection, and by diminishing the function of neutrophils, macrophages, and natural killer cells. Vitamin A is also required for adaptive immunity and plays a role in the development of T both-helper (Th) cells and B-cells. In particular, vitamin A deficiency diminishes antibody-mediated responses directed by Th2 cells, although some aspects of Th1-mediated immunity are also diminished.
Recent studies suggest that social networks (family ties, friends, colleagues) have a positive effect on our susceptibility to infections. This is notwithstanding the fact that the proximity of many people (also in our networks) increase the chance to be exposed to pathogenic microbes. In addition, social support has a positive effect too, on our ability to deal with infections. Social support includes instrumental support, which is task-related help that we may receive, such as information and tangible resources to deal with problems or challenging situations. The other part of social support is emotional support; which refers to helping people to manage their feelings, including making someone feel loved or valued. These types of support have been found to enhance immune functions.
Stress is found to be associated with poor immune function. Stress reduces our immune functions through enhancing detrimental behavior such as smoking, excessive alcohol use and lack of sleep.
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aLambrou posted on 9/30/2015 4:31:20 PM:Some proposed changes in the following sentences in the text:
1. “Adding a p-value to the description of our study results is useful since it suggests how high or low the probability is that the difference that we observed between the groups was due to chance.” to “Adding a p-value to the description of our study results is useful since it suggests how high or low the probability is that the observed difference between the groups or a more extreme one was due to chance”
2. “Please note that again it is a common convention to chose 95% as a confidence interval, but this might as well have been 90%, 99% or even 93.37%: it is a matter of choice” to “Please note that again it is a common convention to choose 95% as a confidence level, but this might as well have been 90%, 99% or even 93.37%; it is a matter of choice.”
3. “The deviation comprises the Standard Error”…Actually, the deviation is expressed as “critical value (of a distribution) plus or minus the standard error”. Some more elaboration here would be beneficial...
4. “If the Null Hypothesis is included within the CI, then we should consider it non-significant. For example, in case of a relative risk, the null hypothesis is that RR=1.0 (and the same goes for Odds Ratio).” What about writing this “If the null value is included within the CI, we will consider that the result is not statistically significant. For example, in case of a relative risk, the null value is 1.0 (RR=1.0) based on the null hypothesis that the exposure under study is not associated with the outcome under study (and the same goes for Odds Ratio).”?
5. “Most analytical software will give the confidence intervals automatically, together with the point estimates and p-value.” to “Most analytical software will provide the confidence intervals automatically, together with the point estimates and p-values.”
6. “This can be interpreted that the true relative risk for olive eating and botulism is with 95% probability between 1.17 and 11.07.” can maybe be rephrased to “The true relative risk lies between 1.17 and 11.07 with 95% confidence. That is, the data are also consistent with hypotheses of a relative risk between 1.17 and 11.07.”
7. “A confidence interval represents the range of effects that are compatible with the data. The CI provides
• the magnitude of the measured effect
• the the range in which the effect of our interest is most likely to be
• the direction of the effect (risk factor or protective factor)”
“A confidence interval represents the range of hypotheses that are compatible with the data.
The CI provides information on:
• the magnitude of the measured effect or else the strength of the association
• the range in which the effect of our interest is most likely to be
• the direction of the effect (risk factor or protective factor)
A separate part on the interpretation of the confidence intervals (as a headline) can also be useful. One may also include the results from the botulism outbreak example in this part.
It might also be preferable to use the terms wide and narrow instead of large and small when commenting on the width of confidence intervals. For example, “In principle, high data variability will lead to wide confidence intervals. The larger the sample size, the narrower the confidence interval. And finally, the higher the confidence level chosen, the wider the interval will be.”
There are some typos in the following sentences:
- “If we want to answer to this question, we can calculate the confidence interval around or estimated effect” to “If we want to answer to this question, we can calculate the confidence interval around our estimated effect”
- “Please note that again it is a common convention to chose 95% as a confidence interval, but this might as well have been 90%, 99% or even 93.37%: it is a matter of choice.” to “Please note that again it is a common convention to choose 95% as a confidence interval, but this might as well have been 90%, 99% or even 93.37%: it is a matter of choice.”
Arnold Bosman replied on 9/30/2015 5:30:55 PM: These are very good comments !
Thanks for this. I would like to suggest to modify the article accordingly (please feel free to use the 'edit' button on top of this article.
Alternatively I would also be happy to do so, if you experience technical obstacles to modifying the article.
Thanks again, this is highly valuable.
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