This is a draft version of a short comic on the vaccine research that I am planning. It focuses on Whooping Cough, but many other pathogens could be studied in a similar way.
The following is a draft research proposal to investigate the scientific perception and reality of the efficacy and efficiency of B. pertussis vaccines and the prevalence of asymptomatic infections. I have written extensively, both on The Spiritual Anthropologist, and over at Politicoid, on the topics of vaccine efficacy and science, especially concerning issues with the way vaccine efficacy is researched and on the potential threat of asymptomatic infections, and have been striving to publish new research, rather than just summarizing existing research.
Although vaccines against B. pertussis have been around for decades, it has only been in the last decade or so that concerns about the ability for the vaccine to prevent infection have arisen. A small clinical trial involving human primates suggests that the acellular B. pertussis vaccine prevents against clinical symptoms, but may not protect against colonization and transmission of the pathogen. Furthermore, in an observational study, B. pertussis infection was confirmed in Israeli children vaccinated with the whole cell B. pertussis vaccine. Both of these findings bring into question whether or not there is a significant ability for these vaccines to prevent colonization and transmission, or if they can only prevent clinical symptoms. Why did it take so long for the medical community to identify weaknesses in these vaccines? Phase I and II clinical trials should have been able to identify how well the vaccine could prevent the spread of infection. Did B. pertussis evolve to become less affected by the vaccines? Did the researchers fail to consider whether or not the vaccines could prevent infection? Or were the methods that they used incorrect?
One indication that the final situation is actually involved is that at least some studies, which claim that the vaccines are effective at preventing infection, actually can only measure the ability to prevent clinical symptoms. These studies look at case reports or gather their data from patients who have gone to seek medical attention for symptoms. An asymptomatic infection is unlikely to result in a visit to a doctor or hospital, and therefore studies which choose their sample from patients seeking medical attention, rather than from the community as a whole, or which look at symptom prevalence, rather than identifying infection using culture or PCR tests, will only be able to identify how well the vaccine does its job of preventing disease.
A systematic review of available studies on B. pertussis vaccines can help answer the question of whether or not study methodology is at fault. The proposed systematic review will start by searching for all studies which investigate the efficacy and efficiency of B. pertussis vaccines, either whole cell or acellular, whether currently in use or not. Duplicates will be removed, and the studies will be sorted into categories. The categories will be as follows: investigates efficacy, investigates efficiency, sample drawn from general population, sample drawn from those seeking medical attention, identifies symptoms only, identifies infection, comments on ability to prevent infection, and comments on ability to prevent disease. In this way, the study can investigate what fraction of studies have conflated ability to prevent disease with the ability to prevent colonization and transmission. While it is not crucial to the question at hand, a quality analysis will also be conducted to see if there is a relationship between study quality and tendency to conflate these concepts.
The full systematic review will involve two readers. I will not be involved in the review process as the amount of material I have written and read on this specific topic may skew my analysis of the papers.
Model Construction & Parameter Estimation
The basic SVIR model is a useful tool for estimating the dynamics of how infections spread, under various vaccination regimes. However, the model does not take into account how asymptomatic infections, either due to natural partial immunity, or due to partial immunity derived from vaccination, affects epidemics. Parameters that will need to be studied or assumed, before the model becomes viable, include how likely an unvaccinated person is to become asymptomatic upon infection, how likely a vaccinated person is to become asymptomatic upon infection, and how symptoms affect contact rates between healthy and unhealthy individuals.
A key assumption of the model that will be constructed is that appearance of symptoms influences how likely a healthy and infected person are to come into contact with one another. This assumption is based on theories about disease avoidance. Kouznetsova et al. 2011 indicate that such behavior is not limited to actual contagious diseases, but that people will avoid anyone who even appears to be contagious Kouznetsova, Daria, Richard J. Stevenson, Megan J. Oaten, and Trevor I. Case. “Disease-avoidant behaviour and its consequences.” Psychology & Health 27, no. 4 (2012): 491-506. doi:10.1080/08870446.2011.603424.. Risk aversion also occurs in sick individuals. Even though many Americans go to work sick, a significant fraction do stay home or take additional precautionary measures. According to a survey conducted by nsf.org, at least 26% of workers admit to going to work sick. 17% of women and 33% of men admit to always going to work sick. However, those numbers still indicate that a significant number of individuals do stay home, especially if a doctor tells the person to do so.
These results indicate that the rate of contact between healthy and sick individuals is a function of how obvious it is that the person is sick and potentially contagious. Asymptomatic carriers and those with minor symptoms do not appear to be contagious, and might not know that they are sick, and therefore there may be little to no risk avoidance behavior. Ideally, this concept would be modeled using a system of partial differential equations, but ordinary differential equations are much easier to manipulate.
Once parameter estimates are made and the model constructed and evaluated, it will be time to obtain empirical justification of the model. If the model is a reasonable one, it should be able to give us an estimate of the current rate of B. pertussis infection. Even if the model itself fails, the results from obtaining actual estimates for the incidence rates of infection, within the general population, and certain at risk sub-populations, will be useful, both for adjusting the model and for updating public health policy.
The basis of the observational study is a similar study conducted in China. The cross-sectional study attempted to identify the prevalence of asymptomatic infections among school aged students (aged 7 – 15) in four different counties in China. Both culture and PCR testing was used, and sampled were collected between July and September of 2011.
- Kouznetsova, Daria, Richard J. Stevenson, Megan J. Oaten, and Trevor I. Case. “Disease-avoidant behaviour and its consequences.” Psychology & Health27, no. 4 (2012): 491-506. doi:10.1080/08870446.2011.603424.
- Kurzban, Robert, and Mark R. Leary. “Evolutionary origins of stigmatization: The functions of social exclusion.” Psychological Bulletin 127, no. 2 (2001): 187-208. doi:10.1037/0033-2909.127.2.187.
- Srugo, Isaac. “Pertussis Infection in Fully Vaccinated Children in Day-Care Centers, Israel.” Emerging Infectious Diseases6, no. 5 (2000): 526-29. doi:10.3201/eid0605.000512.
- Fulton, T. Roice, Varun K. Phadke, Walter A. Orenstein, Alan R. Hinman, Wayne D. Johnson, and Saad B. Omer. “Protective Effect of Contemporary Pertussis Vaccines: A Systematic Review and Meta-analysis.” Clinical Infectious Diseases 62, no. 9 (2016): 1100-110. doi:10.1093/cid/ciw051.
- Warfel, J. M., L. I. Zimmerman, and T. J. Merkel. “Acellular pertussis vaccines protect against disease but fail to prevent infection and transmission in a nonhuman primate model.” Proceedings of the National Academy of Sciences 111, no. 2 (2013): 787-92. doi:10.1073/pnas.1314688110.
- Zhang, Qi, Zundong Yin, Yixing Li, Huiming Luo, Zhujun Shao, Yuan Gao, Li Xu, Biao Kan, Shan Lu, Yan Zhang, Manshi Li, Meizhen Liu, Pingping Yao, Zhixian Zhao, and Qiushui He. “Prevalence of asymptomatic Bordetella pertussis and Bordetella parapertussis infections among school children in China as determined by pooled real-time PCR: A cross-sectional study.” Scandinavian Journal of Infectious Diseases 46, no. 4 (2014): 280-87. doi:10.3109/00365548.2013.878034.
References [ + ]
|1.||↑||Kouznetsova, Daria, Richard J. Stevenson, Megan J. Oaten, and Trevor I. Case. “Disease-avoidant behaviour and its consequences.” Psychology & Health 27, no. 4 (2012): 491-506. doi:10.1080/08870446.2011.603424.|
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Over the last couple of decades, we have learned a lot about the human gut microbiome. Rather than simply being a collection of commensal organisms, the gut microbiome (GMB) is now thought to be involved in a number of important metabolic roles, including nutrient extraction, immunity, and possibly even the regulation of sleep and mood. The degree with which negative health outcomes have been associated with a dysbiosis, or the dysfunctional GMB, and the degree with which different organ systems interact with the GMB, suggest that we should consider it to be as important as an organ, if not actually an organ itself. Dysbiosis is therefore not a minor inconvenience that may cause discomfort, but a syndrome or disease that must be treated to maintain proper health. Further research on gut microbiome dysbiosis should be undertaken, including research into new diagnostic tools. The first half of the paper will summarize part of the discoveries made in the field of research on the GMB. The second half of the paper will use those findings to suggest further research.
Overview of the Field
The human GMB is fairly diverse. On average, the human gut contains well over 1,000 species-level phylotypes (Lozupone et. al. 2012). But that is only on the individual level. According to Jandhyala et al. (2015), those species are from a pool of over 35,000 total species level phylotypes that have been identified as being found in human guts. But even with that diversity, there seems to be two main phyla present: Bacteroidetes and Firmicutes. Bacteroidetes are gram negative while Firmicutes are gram positive. Overall, these microbes are not just commensal but are responsible for a number of metabolic functions within the gut. Bacteroides, a genus in the phyla Bacteroidetes, “are the predominant organisms that participate in carbohydrate metabolism (Jandhyala et al. 2015).” A key species in this genus is B. thetaiotaomicron. These organisms process carbohydrates “by expressing enzymes such as glycosyl transferases, glycoside hydrolases and polysaccharide lyases (Ibid.).”
There are a number of useful byproducts generated by these industrious workers. “Fermentation of the carbohydrates that escaped proximal digestion and indigestible oligosaccharides by colonic organisms such as Bacteroides, Roseburia, Bifidobacterium, Faecalibacterium, and Enterobacteria result in the synthesis of short chain fatty acids (SCFA) such as butyrate, propionate and acetate, which are rich sources of energy for the host[35,36].” (Ibid) Additionally, vitamin K along with precursors to vitamin B are produced within the gut (Ibid). Furthermore, as indicated in Mahony et al. (2014), the GMB is associated with mood and sleep, through the gut-brain axis. This connection seems to be due, at least in part, to the production of serotonin from tryptophan in the gut (Mahony et al. 2014). However, as addressed in Carabotti et al. (2015), the interaction is not mono-directional. The brain influences numerous gut functions, including “motility, secretion of acid, bicarbonates and mucus, intestinal fluid handling and mucosal immune response” (Carabotti et al. 2015). Many of the bacteria in our gut also have receptors for neurotransmitters, such as GABA (Ibid.).
The importance of the many apparent functions of the GMB are consistent with the much narrower range found in functional diversity, as opposed to phylogenetic diversity, within the gut: “despite having highly divergent gut microbiota compositions, functional gene profiles are quite similar in different individuals” (Lozupone et al. 2012). The specific roles of our microbiota may also explain another interesting result. While Bacteroidetes and Firmicutes are the most common phyla of microbes present, the ratio of these organisms varies considerably depending on a number of factors, including diet. Looking at healthy individuals, Firmicutes were the most dominant phyla in vegetarians, while in non-vegetarians, Bacteroidetes were the most common phyla (Bamola et al. 2017). This variation is reasonable since different foods would require different microbes to process them.
So diet influences the human gut microbiome. But that microbiome needs to be established in the first place. Some of our GMB is colonized very early in our lives. Roughly 25% of infant gut bacteria come from breastmilk and microbes found on the breast of the mother (Pannaraj et al. 2017). Microbial composition then varies considerably for the first few years, increasing in overall diversity until the ecosystem finally stabilizes (Lozupone et al. 2012).