MODELS AND STATISTICAL ANALYSIS IN EPIDEMIOLOGY OF INFECTIOUS DISEASES
https://doi.org/10.17238/PmJ1609-1175.2019.3.80-83
Abstract
The use of mathematical model based on assumption of heterogeneity of population in epidemiological studies of infectious diseases cause grave mistakes in assessment of transmission rate of infection and average incidence rate. For an accurate assessment of morbidity, we need models that take into account the structure of risk groups. In this case, the duration of cycles of multi-year oscillations for homogeneous and heterogeneous models is close, so it can be used to estimate the value of the contact number. In addition, models that do not take into account the finiteness of the population give an incorrect description of the dynamics of the incidence – in such models the incidence tends to a constant value. The reason for this lies in the fact that even for multimillion populations the dynamics of the number of infected people has a strong stochasticity, and to reproduce the actual dynamics of the epidemic process, it is necessary to use not deterministic but stochastic models.
About the Author
A. N. Gerasimov
I.M. Sechenov First Moscow State Medical University
Russian Federation
Russian Federation
8/2 Trubetskaya St. Moscow 119991 Russian Federation
References
1. Razzhevajkin V.N. Рopulation dynamics of model. Мoscow: Russian Academy of Sciences, A.A. Dorodnitsyn Computing Center, 2006. 87 р.
2. Brazhnikov A.Yu., Gerasimov A.N. Experience in applying correlation analysis to explore the synchronicity of infectious morbidity level fluctuations in individual Territories // Journal of Microbiology, Epidemiology and Immunobiology. 1999. No. 4. Р. 1–5.
3. Demetris A., Séverine A., Vasieva O., Vasiev B. On the heterogeneity of human populations as reflected by mortality dynamics // Aging (Albany NY). 2016. Vol. 8, No. 11. Р. 3045–3064.
4. Gerasimov A.N., Razzhevajkin V.N. Dynamics of epidemic process in heterogeneous is not completely isolated populations, taking into account the seasonal fluctuations in activity transport mechanism // Journal of Computational Mathematics and Mathematical Physics. 2008. Vol. 48, No. 8. Р. 1488–1499.
5. Eaton J.W., Johnson L.F., Salomon J.A. [et al.]. HIV treatment as prevention: Systematic comparison of mathematical models of the potential impact of antiretroviral therapy on HIV incidence in South Africa // PLoS Med. 2012. Vol. 9, No. 7. P. e1001245. doi: 10.1371/journal.pmed.1001245
6. Gerasimov A.N, Shpitonkov M.I. Score random fluctuations in the number of people infected with HIV in the model “parasite–host” with the continuing overall strength // Operations Research (model systems). 2014. No. 9. P. 17–30.
7. Platonova T.A., Golubkov A.A., Obabkov V.N. [et al.]. Multifactorial simulation in the prediction of measles for immediate and longer-range // Еpidemiology and Infectious Disease. 2018. Vol. 23, No. 5. Р. 225–233.
8. Munday J.D., van Hoek A.J., Edmunds W.J., Atkins K.E. Quantifying the impact of social groups and vaccination on inequalities in infectious diseases using a mathematical model // BioMed Central Medicine. 2018. Vol. 16, No. 1. Р. 162. doi: 10.1186/s12916-018-1152-1
9. Razzhevajkin V.N. Рopulation dynamics of model. Мoscow: Russian Academy of Sciences, A.A. Dorodnitsyn Computing Center, 2006. 87 р.
10. Demetris A., Séverine A., Vasieva O., Vasiev B. On the heterogeneity of human populations as reflected by mortality dynamics // Aging (Albany NY). 2016. Vol. 8, No. 11. Р. 3045–3064.
11. Eaton J.W., Johnson L.F., Salomon J.A. [et al.]. HIV treatment as prevention: Systematic comparison of mathematical models of the potential impact of antiretroviral therapy on HIV incidence in South Africa // PLoS Med. 2012. Vol. 9, No. 7. P. e1001245. doi: 10.1371/journal.pmed.1001245
12. Munday J.D., van Hoek A.J., Edmunds W.J., Atkins K.E. Quantifying the impact of social groups and vaccination on inequalities in infectious diseases using a mathematical model // BioMed Central Medicine. 2018. Vol. 16, No. 1. Р. 162. doi: 10.1186/s12916-018-1152-1
Review
For citations:
Gerasimov A.N. MODELS AND STATISTICAL ANALYSIS IN EPIDEMIOLOGY OF INFECTIOUS DISEASES. Pacific Medical Journal. 2019;(3):80-83. (In Russ.) https://doi.org/10.17238/PmJ1609-1175.2019.3.80-83
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