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High work intensity (HWI) can occur in various occupational groups and induce health disorders, which means occu-pational health risk (OHR) assessment is necessary. This article describes methodical approaches to assessing OHR caused by HWI with a possibility to examine contributions made by its specific components and transition to personified risk assessment. The suggested approaches to assessing OHR caused by HWI include subjective assessment of the factor and health self-assessment. They allow identifying additional likelihood of health disorders and performing further risk assessment when exposure to HWI grows by one unit as per separate HWI indicators describing its specific components. Personified risk assessment involves using a template created for specific HWI components (intellectual, sensory, or emotional loads; work monotony; work regime). The approaches were tested on workers with mostly mental work (n = 137, respondents’ mean age was 43.9 ± 8.01 years; mean work records were 14.5 ± 3.7 years). Calculated data of personified levels of the integral health risk were used to rank likely health outcomes as per their priority. Mental disorders and diseases involving elevated blood pressure were established to correspond to ‘high’ health risk. Myopia, strained headache, atherosclerosis of peripheral vessels, and chronic laryngitis corresponded to ‘medium’ risk. Certain disorders involving the immune mechanism, tinnitus, ischemic heart disease, and atherosclerosis of coronary vessels as well as stomach and duodenum ulcer corresponded to ‘moderate’ risk. Detailed HWI assessment made it possible to identify its leading components; the shares of sensory and emotional loads in the integral health risk reached 29.0 ± 2.4 and 25.9 ± 3.9 % accordingly (р = 0.37). It is advisable to use these findings for creating personified activities aimed at OHR mitigation.

As we assess health risks caused by extremely dangerous infections, we can apply mathematical modeling to estimate a disease or a death case probability. This mathematical modeling describes epidemiological processes and allows to imitate their development without performing any anti-epidemic activities. Parameters which quantitatively assess morbidity and mortality cases obtained via this modeling together with actual data on losses which were not prevented even if anti-epidemic activities were in place, can be used as grounds for economic effects assessment. An economic effect of anti-epidemic activities was calculated in terms of indirect prevented losses which became possible due to decrease in mortality and morbidity; the effect was calculated in money units which were applied in the GDP calculation. The calculation is performed in full conformity with 'The Methodology for calculating economic losses caused by population mortality, morbidity, and disability" (Moscow, 2012) and envisages assessment of losses in the current year and over a period of survival (for death cases). The methodology was tested on the example of Ebola fever outbreak in Guinea in 2014-2016. The testing results revealed that if not for anti-epidemic activities which included substantial assistance rendered by other countries (the RF among them), a number of morbidity cases caused by Ebola virus would have reached 521,289, and a number of death cases, 56,345. The RF Rospotrebnadzor made a significant contribution into Ebola fever outbreak elimination in Guinea; it sent a special anti-epidemic team there in August 2014. The team participated in diagnostic procedures, staff training, and anti-epidemic activities organization. Risk prevented due to assistance rendered by other countries, including the RF, amounted to 517,485 morbidity cases, and 53,809 death cases. Economic effects for Guinea achieved due to anti-epidemic activities aimed at risk minimization with the help of other countries is estimated to be equal to 229.51 million USD; it amounts to approximately 3.5% of Guinea GDP.