Crimean-Congo hemorrhagic fever in the North Caucasian Federal District: overview of the epidemiological situation and improvement of morbidity forecasting method

Abstract

This article is dedicated to analyzing epidemiological situation of Crimean-Congo hemorrhagic fever in the subjects of the North Caucasian Federal District (from 2005 to 2021) and developing a new approach to improve epidemiological forecasting by using an in-progress prognostic model. The study is comprehensive, using epidemiological methods and mathematical statistics. The epidemiological analysis was carried out based on information from the databases on the incidence rate for Crimean-Congo hemorrhagic fever presented as a project and maps of infectious disease focus epidemiological examination. The prognostic morbidity model is developed based on Bayes theorem and Walds sequential statistical analysis. The factors information calculation was carried out by using the Kullback method. The value of climatic factors was retrieved from the database of the Center for Collective Use IKI-monitoring of the Space Research Institute of the Russian Academy of Sciences. The data obtained indicate that the majority of patients with Crimean-Congo hemorrhagic fever within the studied long-term period in the Stavropol Territory (629) and the Republic of Dagestan (46) were revealed. Isolated cases in the Kabardino-Balkarian Republic (2), the Karachay-Cherkess Republic (3) and the Republic of Ingushetia (2) were noted. Infection by the Crimean-Congo hemorrhagic fever causative agent via the transmission mechanism occurred mainly during the care after farm animals in 59.4%. The prevalence of moderate forms of Crimean-Congo hemorrhagic fever (79%) was noted, with hemorrhagic manifestations (over the last five years) observed almost in half of the patients. The proportion of correct preliminary diagnoses during patient hospitalization was 49%. While testing the prognostic model in 2021 particularly in the Stavropol Territory, a complete exact coincidence for predicted and the actual data was obtained for 11 districts (42.3%). False positive (38.5%) and overestimated (11.5%) data at this stage of the study do not significantly reduce the predictive value of the model, since they often reflect registered infection case that occurred at the patients place of residence in another administrative region, underdiagnoses of mild forms of Crimean-Congo hemorrhagic fever in medical institutions or high efficiency of preventive measures against ticks measures carried out before the beginning of the epidemic season in individual municipal districts. False negative results were 7.7%. Thus, the results of the analysis evidence about a need to improve the training of medical personnel for the timely detection of patients with Crimean-Congo hemorrhagic fever and to enhance the effectiveness of preventive measures against ticks. The results of testing the prognostic model confirm the feasibility and hold promise to continue the study.