Abstracts by keywords: Vaccination
In the simplest case, so-called SIR models are used for the mathematical modeling of epidemics. The three capital letters describe the states of the individuals or the population that are relevant to the infection process: S means being susceptible to the infection, I means being infected and infectious, and R stands for resistance (immunity). As elsewhere, SIR models are mainly used at the Robert Koch Institute (an der Heiden 2020; Maier 2022). Without further modifications, SIR models are used for modeling infectious diseases that leave lifelong immunity after recovery, as is the case with many “childhood diseases”. But this does not seem to apply to an infection with SARS-CoV-2. There is evidence that both infection with the coronavirus and vaccination against the coronavirus produce only temporary immunity (Baraniuk 2021). In addition, the virus can circumvent an existing immunity with new virus variants (so-called escape variants), against which cross-immunity from previous infections is not available or insufficient (Starr 2021; Weisblum 2020). This article neither describes the incidence of the disease in society nor the burden on the healthcare system. Instead, modeling will be used to examine how various factors could influence the transmission of the infection. In this case, infections must not be equated with diseases that are influenced by many other factors (age, previous illnesses, etc.); infections that occur after previous vaccinations or after previous infections are also associated with a different probability of illness, which is very likely lower. The article presented here focuses on the parameters relevant to infection epidemiology, in particular concerning prevalence and immunity.
23.03.2022
According to estimates from individual doctors, the vaccination status of around 40 percent of patients does not correspond to the current recommendations of the Standing Vaccination Commission. However, reliable data on the vaccination protection of outpatient primary care patients is sparse. Methods: In this study, standardized vaccination-related data were collected from patients from 118 primary care practices. Results: The results of the survey (n=557) suggest that vaccination gaps exist among older general practitioner patients and that factors influencing vaccination rates in the general practitioner sector in Germany have both patient and, in some cases, practice-specific characteristics. Conclusion: Relevant data on vaccination protection could be collected using a representative cross-sectional survey. As part of applied family medicine research, the present study contributes to improving the data situation on vaccinations in older adults.