Clinical and epidemiological features of the 2019 West Nile fever outbreak in the city of Krasnodar

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Background

West Nile fever (WNF) is a natural-focal arboviral vector-borne infection caused by an enveloped virus of the genus Flavivirus (the West Nile virus), first isolated in Uganda in 1937 [1]. The main vectors of West Nile virus (WNV) are mosquitoes of the Culex and Aedes genera [2]. The WNV has been identified in 30 mammalian species, 60 mosquito species, and some reptiles, including snakes; however, it is most widespread among birds inhabiting aquatic and wetland ecosystems, which serve as the primary reservoir and amplifying host of the virus [3, 4]. WNV mosquito vectors are widely distributed across the globe, and the known geographic range of WNV transmission has steadily expanded over the past 30 years. Humans, like other mammals, are considered incidental hosts and do not contribute to further transmission, serving as a “dead-end” in the infection cycle. In most cases, WNF is asymptomatic or presents as a mild, influenza-like illness and often remains undiagnosed. Severe forms involving the central nervous system are rare but may result in long-term sequelae or death [5].

In the Krasnodar Territory, WNF is considered an emerging infectious disease, having appeared in a previously unaffected geographic area. WNV was first isolated from mosquitoes in the region in 1988 during arbovirus circulation research. However, human cases were first diagnosed in the region during the first documented outbreak of WNF in the Russian Federation (RF) in 1999 [6, 7]. That year, Russia experienced record-breaking summer temperatures [8], although average summer temperatures in Krasnodar remained within the typical historical range. A dramatic increase in WNF incidence occurred in 2010 (527 cases) and spread to seven regions of the RF, most notably the Volgograd Region (413 cases) [9]. This period also coincided with the occurrence of extreme summer heat [8]. Between 2010 and 2018, only sporadic WNF cases were reported in the Krasnodar Territory [10]. In 2019, WNF incidence rose again across the RF, reaching 2.14 cases per 100,000 population in the Krasnodar Territory compared with 0.02–0.05 per 100,000 between 2016 and 2018 [11].

WNV may be introduced into the RF from countries in Africa, Southwest Asia, and Southeast Asia. The virus is introduced from Africa by migratory birds such as black-headed gulls, quails, swallows, ducks, sandpipers, rooks, starlings, and other species following southern and southwestern flyways. In Western Siberia, species posing a potential risk include geese, ducks, sandpipers, gulls, and passerines that follow similar migratory routes. In Russia, the primary endemic focus is maintained by Eurasian coots and several duck species inhabiting the Kuban and Terek River deltas [12]. In the Krasnodar Territory, WNV antibodies have been detected in 34 bird species [10]. Global climate change has altered migratory patterns of birds and contributed to increased population densities of synanthropic and ornithophilic mosquitoes [6]. In the Krasnodar Territory, rising ambient temperatures contribute to WNV transmission by facilitating the accumulation of effective temperature sums required for viral replication and persistence within mosquitoes [9]. Elevated temperatures accelerate mosquito population growth, shorten the incubation period, and enhance the efficiency of viral transmission to birds [13]. A strong correlation has been documented between extreme heat events and the intensity of human outbreaks [14].

When analyzing the factors contributing to the rise in WNF incidence, particular attention is given to the formation of transmission foci within large urban centers [9]. In Krasnodar, areas at risk for WNV transmission remain underrecognized.

Aim

The work aimed to characterize the main clinical and epidemiological manifestations of WNF and identify potential foci locations within Krasnodar, using the 2019 outbreak as an example.

Methods

Study Design

It was an observational, cross-sectional, single-center, non-controlled study of the clinical and epidemiological characteristics of WNF.

Medical records of 78 inpatients diagnosed with WNF were selected for the study. All patients received care at the State Budgetary Healthcare Institution “Specialized Clinical Infectious Diseases Hospital” of the Ministry of Health of the Krasnodar Territory. The diagnosis was established in accordance with Sanitary Regulations 3.1.7.3107-13, Prevention of West Nile Fever, based on the detection of WNF-specific IgM and IgG antibodies via enzyme-linked immunosorbent assay (ELISA) and by polymerase chain reaction (PCR). Using the online mapping service Yandex.Maps, a visualization was created to reflect the actual residential addresses of individuals diagnosed with WNF. This mapping aimed to identify potential areas for the formation of WNF transmission foci within the urban territory of Krasnodar.

Eligibility Criteria

Inclusion criteria: a confirmed diagnosis of West Nile fever; age over 18 years; residence within Krasnodar or its suburbs within one month prior to symptom onset.

Exclusion criteria: Given the clinical polymorphism of WNF, differential diagnoses were ruled out using PCR testing of cerebrospinal fluid for conditions with similar symptoms, including: enteroviral infection, Ixodes tick-borne borreliosis, tuberculosis, parvovirus infection, pneumococcal infection, influenza, toxoplasmosis, and herpesvirus infections caused by herpes simplex virus types 1 and 2, human herpesvirus 6, Epstein–Barr virus, cytomegalovirus, and varicella-zoster virus. ELISA testing was used to exclude the presence of specific IgM antibodies to measles, HIV, and rubella.

Non-inclusion criteria: absence of IgG and IgM antibodies to WNV in blood samples; residence outside the Krasnodar Territory.

Study Setting

The study included data from medical records of patients hospitalized in 2019 at the State Budgetary Healthcare Institution “Specialized Clinical Infectious Diseases Hospital” of the Ministry of Health of the Krasnodar Territory.

Study Duration

Medical documentation was analyzed from 2023 to 2024.

Intervention

Patient selection was based on a confirmed diagnosis of WNF, established by ELISA detecting serum IgM and IgG antibodies to WNV in rising titers or via seroconversion, and/or by the presence of WNV RNA identified using PCR in cerebrospinal fluid or blood.

Examination and treatment of patients were performed in accordance with Decree of the Chief State Sanitary Physician of the RF dated January 28, 2021, No. 4, “Approval of Sanitary Rules and Regulations SanPiN 3.3686-21 ‘Sanitary and Epidemiological Requirements for the Prevention of Infectious Diseases,’” Methodological Guidelines MU 3.1.3.2600-10 “Measures to Combat West Nile Fever in the Russian Federation” (approved by the Chief State Sanitary Physician of the RF on April 19, 2010), and the clinical management protocol for patients with West Nile fever at the State Budgetary Healthcare Institution “Specialized Clinical Infectious Diseases Hospital,” which includes performing lumbar puncture with cerebrospinal fluid analysis by PCR.

The primary indicators assessed upon hospital admission included: actual residential address, age, complete blood count and urinalysis, liver enzymes [alanine aminotransferase (ALT), aspartate aminotransferase (AST)], creatine phosphokinase (CPK), lactate dehydrogenase (LDH), C-reactive protein (CRP), urea, creatinine, and bilirubin levels.

Potential zones of anthropurgic transmission risk in Krasnodar were determined using the Yandex.Maps digital platform.

Main Study Outcome

Identification of diagnostically significant manifestations of WNF based on clinical symptoms, complete blood count, biochemistry, urinalysis, and cerebrospinal fluid analysis.

Identification of WNF transmission foci within Krasnodar based on the geographic distribution of diagnosed cases.

Subgroup Analysis

Patients were stratified into two groups according to the clinically diagnosed form of the disease. Group 1 (n = 58) included patients with meningeal or meningoencephalitic manifestations of WNF; group 2 (n = 20) included patients with an influenza-like form of WNF. Each patient’s actual residential address was used to determine the administrative district and the presence of nearby water bodies.

Statistical Analysis

Principles of sample size calculation. The sample size was not pre-calculated.

Statistical methods. Statistical analysis was used for comparisons of quantitative variables. Means (M), standard deviations (SD), 95% confidence intervals, and standard error of the mean (m) were calculated. Distribution normality was assessed using the Shapiro–Wilk test. The significance of differences was assessed using Student’s t-test; differences were considered statistically significant at p < 0.05. Nonparametric statistical methods were used to analyze the results, employing Microsoft Excel 10 (Microsoft, USA) and Statistica 6.0 software package (StatSoft, USA), which were also used for graphical data presentation.

Ethics Approval

The study protocol was approved by the independent ethics committee of the Federal State Budgetary Educational Institution of Higher Education “Kuban State Medical University” of the Ministry of Health of Russia, Krasnodar (Protocol No. 89, dated June 26, 2020).

Results

Participants

The process of sample formation is presented in the study design flowchart (Fig. 1). Initially, medical records of 180 patients with a preliminary diagnosis of “meningitis, fever of unknown origin, WNF?” were screened. A total of 78 inpatient records with a clinical diagnosis of WNF were selected. A total of 102 patients were excluded from the study due to the absence of a confirmed final diagnosis of WNF and residence outside the Krasnodar Territory or recent travel outside the territory within the past month.

 

Fig. 1. Study design flowchart. Flowchart developed by the authors (in accordance with STROBE guidelines). WNF, West Nile fever.

 

Based on the clinical presentation, developed complications, and changes in laboratory parameters, patients were divided into groups according to the clinical form of the disease as established by the final diagnosis: group 1 included meningeal or meningoencephalitic forms; group 2 included influenza-like form.

Primary Results

All patients were admitted to the hospital as emergency cases on average on day 5.9 ± 0.32 of the disease. In terms of sex distribution, among the 78 patients included in the study, 48.7% (38 patients) were male and 51.3% (40 patients) were female. The mean age of the patients was 44.7 ± 0.51 years (18–78 years), individuals under 50 years of age accounted for 57.7% of all cases, with the most affected age group being those aged 29–38 years (29.5%).

The age distribution of patients with WNF is presented in Fig. 2.

 

Fig. 2. Age distribution of patients with West Nile fever.

 

The majority of patients were unemployed (44.9%, 35 patients), 34.6% (27 patients) were employed, 17.9% (14 patients) were retirees, and 2.6% (2 patients) were students. The average hospital stay was 14.2 ± 6.71 bed-days.

The most prevalent comorbidities (Fig. 3) included cardiovascular diseases in 36 patients (46.1%), of whom 17 (21.8% of the total) had hypertension. Respiratory disorders were reported in 21 patients (26.9%); genitourinary and gastrointestinal pathologies were reported in 28 patients each (35.9%); nervous system diseases were reported in 25 patients (32.0%); and hematologic conditions were reported in 21 patients (26.9%), including 20 cases of anemia. Cardiovascular pathology was observed in patients over 48 years of age. In group 1, 84.5% of patients had comorbidities of varying severity, most often in combination. Diabetes mellitus, hypertension, immunosuppression, chronic kidney disease, and liver disease were associated with a more severe clinical course, complicated diagnosis and prolonged recovery. In group 2, isolated cases of comorbid pathology were observed in only 35.0% of patients.

 

Fig. 3. Comorbidity profile in patients with West Nile fever.

 

WNF cases were recorded from July through September, with a peak in August 2019 (see Fig. 4). The month preceding the increase in incidence—June 2019—was characterized by a moderate rise in precipitation levels (35 mm) compared with 2018 (11 mm), although it did not exceed the levels recorded over the past 10 years. At the same time, precipitation level in July 2019 reached 132 mm, surpassing the highest level for that month over the past 20 years. A higher precipitation level was recorded only in July 1997, which was 171 mm. August and September, precipitation levels decreased to 38 mm and 41 mm, respectively. The average monthly temperatures in the summer of 2019 remained within 25.3–23.7°C, not exceeding the average values for the decade [15].

 

Fig. 4. Seasonal characteristics of West Nile fever in 2019.

 

Of all examined patients, only 11 (14.1%) associated deterioration in their health with a mosquito bite as a potential risk factor for WNF (see Fig. 5). Meanwhile, 47 patients were unable to precisely identify or speculate on the cause of their disease, reflecting low awareness of possible transmission routes of WNF. The majority of affected individuals were unaware of the existence of the disease.

 

Fig. 5. Results of patient survey on possible sources of West Nile fever infection.

 

Based on patients’ actual residential addresses, a distribution map of registered WNF cases was constructed and analyzed by territorial districts (see Fig. 6). The highest number of cases was found in the Prikubansky District—50.0% (39 patients)—with a predominance of cases near Rossiyskaya Street and Rostovskoe Highway (see Table 1). This district includes the Shapsug Reservoir, Kopanka Lake, Tsaritsyna Lake, and several small water bodies near Kruglikovsky Boulevard, Ekaterininskaya Estate, and the Yuzhny settlement area. Numerous unnamed water bodies and shallow stagnant water ditches were also observed in this district. In the Karasunsky District, 23.1% of cases (18 patients) were registered. This district borders the Krasnodar Reservoir, with foci concentrated along the Karasun Lakes and Kotlovan Lake. In the Central District, 14.1% of cases (11 patients) were identified near the Kuban River, Staraya Kuban Lake, and Verkhnee Pokrovskoe Lake. The Western District accounted for 3.8% of cases (3 patients), and adjacent suburban areas along the Kuban River or its tributaries accounted for 9.0% (7 patients).

 

Fig. 6. Prevalence of West Nile fever in Krasnodar by patients’ actual residence in 2019: Prikubansky District, Karasunsky District, Zapadny District, and Central District are highlighted in purple, red, green, and blue.

 

Table 1. Distribution of West Nile Fever cases by territorial districts of Krasnodar

Territorial districts of Krasnodar	West Nile Fever cases
	absolute number	%
Prikubansky District	39	50.0
Central District	11	14.1
Karasunsky District	18	23.1
Zapadny District	3	3.8
Areas outside Krasnodar	7	9.0

 

Thus, all WNF cases occurred among individuals residing in close proximity to urban water bodies of both natural (lakes, ponds) and artificial origin (reservoirs, unnamed abandoned water bodies). Flowing waters of the Kuban River appeared to have considerably less significance.

In most cases, disease onset was acute with febrile temperatures recorded (55.1%); 11 cases (14.1%) presented with pyretic fever, and 2 cases (2.6%) exhibited hyperpyrexia (temperature > 40°C). Fever was accompanied by headache, marked weakness, and malaise. A subacute onset with subfebrile temperature was observed in 22 patients (28.2%).

The primary clinical manifestation was central nervous system involvement presenting as meningitis (56%–71.8%) and meningoencephalitis (2%–2.6%). These forms were observed in 58 patients (74.4%), constituting group 1. The disease onset with pyretic and hyperpyretic fever was observed only in this group. Fever and intoxication symptoms were accompanied by general cerebral symptoms, meningeal irritation signs, and loss of balance (ataxia). Hyperemia of the oropharyngeal mucosa was recorded in half of cases, while mucosal granularity, respiratory symptoms, and rash at disease onset were noted in only 10%–12% of cases (see Table 2).

 

Table 2. Frequency of clinical manifestations in patients with West Nile Fever by disease form

Clinical manifestation	Frequency of occurrence
	Group 1 (n = 58)		Group 2 (n = 20)
	absolute number	%	absolute number	%
Weakness	57	98.3	20	100.0
Headache	50	86.2	1	5.0
Dizziness	20	34.5	3	15.0
Malaise	56	96.5	19	95.0
Temperature: subfebrile	12	20.7	10	50.0
febrile	33	56.9	10	50.0
pyretic	11	19.0	-	-
hyperpyretic	2	3.4	-	-
Muscle pain	8	13.8	6	30.0
Nausea	37	63.8	6	30.0
Vomiting	24	41.4	4	20.0
Nasal congestion	2	3.4	1	5.0
Cough	6	10.3	6	30.0
Throat irritation	6	10.3	8	40.0
Sore throat	2	3.4	5	25.0
Sweating	8	13.8	1	5.0
Chills	8	13.8	5	25.0
Drowsiness	19	32.8	1	5.0
Ataxia	17	29.3	-	-
Exanthema	7	12.0	13	65.0
Cutaneous hyperesthesia	12	20.7	-	-
White coating on tongue	55	94.9	18	90.0
Lymphadenopathy	3	5.2	8	40.0
Pharyngeal hyperemia	28	48.3	15	75.0
Granularity of the pharynx	12	20.7	10	50.0
Harsh breathing	14	24.1	2	10.0
Positive Kernig sign	20	34.5	-	-
Positive occipital stiffness	39	67.2	-	-
Focal neurological symptoms	2	3.4	-	-
Hepatomegaly	3	5.2	-	-

 

Lumbar puncture was performed on admission in 59 patients (75.6%). It is noteworthy that in 15.4% (12 patients), despite intense headache, occipital stiffness and other meningeal signs were mild or absent, while cerebrospinal fluid showed pathological changes consistent with inflammation of the leptomeninges. Moderate lymphocytic pleocytosis was observed in most cases in cerebrospinal fluid, with an average of 81.3 ± 16.4 cells/µL, lymphocytes comprising 78.4% ± 3.02%, and protein concentration of 0.79 ± 0.082 g/L. Neutrophilic pleocytosis ranging from 31 to 633 cells/µL (mean 223.5 ± 88.07 cells/µL) was seen in 12 cases (15.4%), predominantly in older patients aged 48.1 ± 12.7 years (p > 0.05). Follow-up cerebrospinal fluid analysis after treatment showed improvement: cytosis decreased to 19.6 ± 0.86 cells/µL, lymphocytes increased to 88.1% ± 0.5%, and protein content decreased to 0.66 ± 0.113 g/L.

The influenza-like form was diagnosed in 20 patients (25.6%). The mean age in this group was 40.5 ± 3.71 years. Moderate intoxication syndrome with subfebrile (50%) or febrile (50%) temperatures was accompanied by myalgia (30%), dizziness (15%), and, in one third of cases, nausea and vomiting without positive Kernig or Brudzinski signs (see Table 2). Respiratory symptoms such as sore throat (65%) and cough (30%) predominated. Compared with group 1, rash (65%), lymphadenopathy (40%), and oropharyngeal mucosal hyperemia and granularity (75% and 50%, respectively) were significantly more frequent.

No statistically significant differences were found in age distribution between groups.

Complete blood count on admission showed no significant abnormalities (see Table 3). At discharge during early convalescence, elevated erythrocyte sedimentation rate of 20.1 ± 1.0 mm/h and lymphocytosis were recorded. Blood biochemistry revealed increased transaminase activity in some cases (11 patients, 14.1%) with normalization by convalescence, except 4 severe cases, where transaminases remained elevated. Severe cases were also characterized by marked elevation of CPK, LDH, and CRP, which significantly decreased by discharge.

 

Table 3. Changes in laboratory parameters in patients with West Nile fever

Parameter	At admission	At discharge	p-value
Leukocytes, 109/L	8.0 ± 0.43	6.7 ± 0.26	0.01
Erythrocytes, 1012/L	4.6 ± 0.07	4.5 ± 0.07	0.31
Hemoglobin, g/L	134.4 ± 1.9	128.5 ± 2.85	0.08
Lymphocytes, 109/L	4.3 ± 0.97	6.3 ± 1.46	0.25
Platelets, 109/L	221.0 ± 9.96	256.9 ± 9.38	0.0097
Erythrocyte sedimentation rate, mm/h	12.6 ± 0.51	20.1 ± 1.22	< 0.001
Alanine aminotransferase, U/L	29.5 ± 3.91	68.4 ± 32.91	0.24
Aspartate aminotransferase, U/L	35.0 ± 5.06	40.2 ± 13.38	0.71
Creatine phosphokinase, U/L	234.0 ± 36.39	79.6 ± 34.33	0.0024
Lactate dehydrogenase, U/L	418.8 ± 17.50	338.4 ± 15.27	< 0.001
C-reactive protein, mg/L	11.1 ± 3.20	3.0 ± 0.95	0.0168
Creatinine, µmol/L	81.0 ± 5.06	79.4 ± 11.68	0.90
Urea, mmol/L	5.2 ± 0.29	4.5 ± 0.47	0.20
Total bilirubin, mmol/L	14.8 ± 2.08	10.7 ± 3.77	0.34

 

Urinalysis on day 1 of hospitalization showed leukocyturia in 88.5% (69 patients), squamous epithelial cells in 83.3% (65 patients), microhematuria in 80.8% (63 patients), bacteria in 51.3% (40 patients), ketones in 47.4% (37 patients), and proteinuria in 37.2% (29 patients). By recovery, urinalysis normalized in almost all patients except one with acute kidney injury signs.

Additional investigations included electrocardiography in 88% (69 patients), chest X-ray in 68% (53 patients), and nasopharyngeal swab for meningococcus in 42% (33 patients). Neurologist, otolaryngologist and ophthalmologist consultations were performed in 70.5% (55), 51% (40), and 31% (24) of patients, respectively.

Due to lack of specific antiviral treatment, management of WNF was primarily focused on pathogenetic therapy and intensive rehabilitation. Considering the possibility of mixed viral-bacterial etiology in meningeal forms, empirical antibacterial therapy was initiated before laboratory confirmation. The majority of patients (92.5%) received antibiotics, either as monotherapy or in combination. After confirmation of WNF diagnosis, antibacterial therapy was discontinued unless other indications existed. The mean duration of therapy was 7.59 ± 3.91 days (see Table 4).

 

Table 4. Main types of therapy used in the treatment of patients with West Nile fever

Type of therapy	Patient category	Absolute number	%	95% confidence interval
Antibiotic therapy	Patients not receiving antibiotics	6	7.8	2.9–16.2
	Patients receiving III generation cephalosporins (ceftriaxone)	63	81.8	71.4–89.7
	Patients receiving fluoroquinolones (levofloxacin)	3	3.9	0.8–11.0
	Patients receiving combination therapy (ceftriaxone + levofloxacin)	5	6.5	2.1–14.5
Immunomodulatory therapy	Patients not receiving immunomodulatory therapy	63	81.8	71.4–89.7
	Patients receiving immunomodulatory therapy (meglumine acridone acetate)	14	18.2	10.3–28.6
Infusion therapy	Patients receiving infusion therapy in hospital	77	100.0	95.3–100.0
Glucocorticoid therapy	Patients without glucocorticoid therapy	60	77.9	67.0–86.6
	Patients receiving dexamethasone	15	19.5	11.3–30.1
	Patients receiving prednisolone	2	2.6	0.3–9.1

 

Pathogenetic treatment targeted correction of hemodynamic disturbances, hypoxemia, intracranial hypertension, seizure syndrome, electrolyte imbalance, and anemia. All patients received infusion therapy averaging 12.92 ± 7.19 days. Infusion regimens during the acute phase included 0.9% NaCl solution (250 mL) combined with 25% MgSO4 solution (5–10 mL), or 0.9% NaCl (250 mL) with 2.4% aminophylline solution (5–10 mL). Glucocorticoids (GC) were indicated for severe disease with neurological symptoms (meningoencephalitis, encephalitis, cerebral edema and swelling, focal symptoms, suspected demyelination). GC therapy was administered to 22.1% of patients, with a mean duration of 4.35 ± 2.03 days.

All patients were discharged with clinical improvement.

Secondary Results

No secondary results were reported.

Discussion

Since the 1990s, southern Russia has been considered a risk area for WNF transmission. In Krasnodar Territory, as in other southern regions, sporadic cases occur with periodic outbreaks. Outside epidemic peaks, diagnosis of sporadic WNF cases remains challenging. Due to the absence of pathognomonic symptoms and low clinical suspicion among physicians, cases without central nervous system involvement remain undiagnosed, preventing accurate assessment of the true disease burden in the region.

Environmental and socio-economic risk factors contributing to increased WNF incidence have been studied worldwide. Most researchers associate increases in incidence with weather conditions and the level of mosquito infection. Land use and socio-economic factors play a comparatively smaller role in predicting WNF cases, although occupational risk has been noted among agricultural and farm workers [16, 17]. When assessing the association between socioeconomic status and the risk of arboviral infection across different geographic regions, infection risk was shown to correlate with low levels of education and income, limited access to medical care, poor housing conditions, water supply disruptions, and migration status [18]. No such patterns were observed in our study; however, the highest incidence was recorded among unemployed individuals (44.9%) and retirees (17.9%).

Ambient temperature plays a significant role in the transmission of WNV, particularly in temperate climate regions [19]. Elevated temperatures in spring create favorable conditions for vector population growth, which can lead to an increase in human cases several weeks later. Awareness of such conditions early in spring can help public health authorities mitigate the risk before it becomes a tangible threat. An analysis of annual incidence trends in southern regions of Russia, correlated with detection of WNV in mosquitoes, has demonstrated the importance not only of ambient temperature, but also of road networks and proximity to water bodies [9]. In Krasnodar, average temperatures in the spring and summer of 2019 did not differ significantly from previous years, which precluded predicting the outbreak. Instead, an increase in monthly precipitation appeared to be more influential. July 2019 saw the highest rainfall in the past 20 years, coinciding with the onset of the WNV outbreak, which peaked in August.

Several studies have shown that urban environments significantly enhance the epidemic potential of a region and promote WNV circulation. Low-rise residential housing with private gardens located in suburban areas facilitates interaction between urban and rural transmission cycles [9]. Endemic transmission of WNV in urban settings has distinct features. WNV incidence within and around large cities is associated with the “urban heat island” effect, which results in additional warming of artificial and natural water bodies. Krasnodar is located in the Kuban River valley and contains several stagnant water bodies, including the Kuban Reservoir and the so-called Karasun Ponds—remnants of the 19th-century Karasun River—frequented by migratory birds. The city also has many small natural and artificial water bodies. As ambient temperatures rise, stagnant water bodies become enriched with organic material, facilitating mosquito breeding [19, 20]. Mapping of probable infection sites confirmed the epidemiologic importance of intra-urban aquatic habitats and served as the basis for identifying risk zones to guide targeted prevention efforts.

The broad clinical spectrum of WNV infection—ranging from asymptomatic or mild influenza-like illness to severe central nervous system involvement—necessitates identification of risk factors for disease severity. One avenue of investigation focuses on the roles of age and comorbidities. In several studies, age was the only consistent predictor of neuroinvasive disease and mortality [18]. High rates of chronic comorbidities have been reported in patients with severe flavivirus infections. The most common chronic diseases among patients with WNF were hypertension (mean 45.0%, 95% confidence interval 39.1% to 51.0%), diabetes mellitus (mean 24.7%, 95% confidence interval 20.2% to 29.8%), and cardiac disease (mean 25.6%, 95% confidence interval 19.5% to 32.7%). The odds ratio for severe flaviviral disease was 2 to 4 among infected individuals with diabetes mellitus, hypertension, or cardiac disease [21]. In another study, the risk factors for death from WNF included age, malignant neoplasms, coronary artery disease, quadriparesis, mechanical ventilation, and healthcare-associated infections [22]. In our cohort, cardiovascular disease (46.1%)—specifically, hypertension—was the most common comorbidity, recorded only in the group with meningeal forms. At the same time, a consistent association with patient age was observed: cardiovascular disorders were documented only in patients older than 48 years. The overall burden of comorbidity was higher in the group with meningeal forms of disease. Diabetes mellitus, hypertension, immunosuppression, chronic kidney disease, and liver disease in various combinations were noted in 84.5% of these patients.

During the 2019 outbreak, more than half of the affected individuals (57.7%) were under 50 years of age, and a new trend was noted: an increase in influenza-like cases and younger patients. Although older age is typically associated with more severe disease, we found no statistically significant difference in patient age between those with meningeal and influenza-like forms of disease.

A promising direction in the investigation of mechanisms underlying severe courses of infectious diseases is genetic research, which enables the identification of individual differences, including genetic predispositions and immune responses. Specific genetic mutations associated with WNV infection have been identified, including variations in OAS1 (meta-OR = 0.83; 95% CI, 0.69–1.00) and CCR5 (meta-OR = 1.29; 95% CI, 1.08–1.53) [5, 23]. These gene associations suggest that immune response mechanisms play a key role in susceptibility to severe disease. Another study of immune response profiles in patients with severe WNF during the acute phase showed elevated proinflammatory markers in innate immune cell types and reduced activity of regulatory T cells, whereas individuals with subclinical disease demonstrated increased expression of genes associated with anti-inflammatory CD16+ monocytes [24].

The absence of typical clinical manifestations, predominance of symptoms related to intoxication syndrome, low public awareness of the risk of mosquito-borne infection, and infrequent reporting of WNF cases over the past 20 years have contributed to both delayed medical consultation and untimely diagnosis, thereby increasing the risk of complicated disease progression. Most patients were admitted to the hospital due to the appearance of generalized or meningeal neurologic symptoms. Meningitis was confirmed by characteristic changes in the cerebrospinal fluid. Routine laboratory tests were nonspecific and mostly reflected the severity of the intoxication syndrome; in some cases, elevated ALT, AST, CPK, LDH, and CRP were noted.

To date, no approved etiologic therapy or vaccine exists for the prevention of WNF. Experimental vaccines based on insect-specific classical flaviviruses are under development for human use [25]. The main preventive measures for WNF remain those aimed at controlling the vector [26].

Conclusion

WNF outbreak in Krasnodar, with a peak incidence in August 2019, occurred in the context of increased precipitation in midsummer (July). Reported cases were territorially linked to urban water bodies. Both large reservoirs, such as the Krasnodar and Shapsug Reservoirs, the Karasun Lakes network, and small unnamed water bodies within the city, as well as the growth of the mosquito population and lack of appropriate anti-epidemic measures, had epidemiological significance. The abundance of water bodies makes Krasnodar a favorable environment for WNV spread, whereas the warm mild climate and high humidity create conditions for the formation of an urban endemic focus. Prevention of WNV circulation requires an integrated application of ecological and entomological approaches. The role of the urban habitat of migratory birds and mosquitoes in forming conditions for WNV circulation should not be underestimated. Effective prevention of WNF in urban areas requires development of comprehensive measures for monitoring natural and artificial water bodies, mosquito control as the main vector, and epidemiological surveillance of areas where migratory and nomadic birds—sources of infection—concentrate.

For timely diagnosis of WNF, detection of WNV RNA in cerebrospinal fluid by polymerase chain reaction and blood testing for WNV-specific IgM antibodies using enzyme-linked immunosorbent assay are necessary. These methods should be included in the comprehensive laboratory examination of patients presenting with clinical signs of meningitis and meningoencephalitis, as well as fever of unknown origin accompanied by catarrhal syndrome, rash, and lymphadenopathy during the summer-autumn period in the southern regions of the Russian Federation.

Additional information

Funding source. This study was not supported by any external sources of funding.

Competing interests. The authors declare that they have no competing interests.

Authors’ contribution. All authors made a substantial contribution to the conception of the work, acquisition, analysis, interpretation of data for the work, drafting and revising the work, final approval of the version to be published and agree to be accountable for all aspects of the work. M.G. Avdeeva, L.P. Blazhnaya: development of the concept and implementation of the study, preparation and editing of the text, approval of the final version of the article; M.I. Kulbuzheva: development of the concept and implementation of the study, preparation and editing of the text, conducting statistical analysis of data, approval of the final version of the article; V.A. Bakhtina, A.A. Vanyukov, A.V. Nezhurin: development of the concept and implementation of the study, preparation and editing of the text, approval of the final version of the article, resource support for the study; K.A. Arzumanyan, N.E. Mishchenko: development of the concept and implementation of the study, preparation and editing of the text, approval of the final version of the article, development of the methodology, preparation of graphic materials, conducting statistical analysis of the data.

作者简介

Marina Avdeeva

Kuban State Medical University

编辑信件的主要联系方式.
Email: avdeevam@mail.ru
ORCID iD: 0000-0002-4979-8768
SPIN 代码: 2066-2690

MD, Dr. Sci. (Medicine), Professor

俄罗斯联邦, Krasnodar

Makka Kulbuzheva

Kuban State Medical University

Email: kulbuzhevamakka@yandex.ru
ORCID iD: 0000-0003-1817-6664
SPIN 代码: 8090-3715

MD, Cand. Sci. (Medicine), Assistant Professor

俄罗斯联邦, Krasnodar

Lyudmila Blazhnyaya

Kuban State Medical University

Email: p-blazhnyaya@mail.ru
ORCID iD: 0000-0002-0055-1764
SPIN 代码: 1164-7038

MD, Cand. Sci. (Medicine), Associate Professor

俄罗斯联邦, Krasnodar

Viktoriya Bakhtina

Specialized Clinical Infectious Diseases Hospital

Email: kdlskib@mail.ru
ORCID iD: 0000-0001-6065-2922
SPIN 代码: 9446-5319

MD, Cand. Sci. (Medicine)

俄罗斯联邦, Krasnodar

Anatoly Vanyukov

Specialized Clinical Infectious Diseases Hospital

Email: kdlskib@mail.ru
ORCID iD: 0000-0002-5285-4222
SPIN 代码: 7310-4670

MD, Cand. Sci. (Medicine)

俄罗斯联邦, Krasnodar

Andrey Nezhurin

Kuban State Medical University; Specialized Clinical Infectious Diseases Hospital

Email: andrew_nezhurin@mail.ru
ORCID iD: 0000-0002-3138-8023
SPIN 代码: 3796-0539
俄罗斯联邦, Krasnodar; Krasnodar

Kamilla Arzumanyan

Kuban State Medical University

Email: arzumanyan.kamilla@mail.ru
ORCID iD: 0000-0001-8739-6340
SPIN 代码: 4987-1460
俄罗斯联邦, Krasnodar

Nika Mishchenko

Kuban State Medical University

Email: Nika.sportwomen.com@gmail.com
ORCID iD: 0009-0003-6748-5874
SPIN 代码: 4508-0814
俄罗斯联邦, Krasnodar

参考

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