Anticipating the Need for Healthcare Resources Following the Escalation of the COVID-19 Outbreak in the Republic of Kazakhstan

Historical evolution of healthcare systems of post-soviet Russia, Belarus, Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, Uzbekistan, Armenia, and Azerbaijan: A scoping review

This scoping review addresses the transformation and development of new healthcare systems in nine countries -Armenia, Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Russia, Tajikistan, Turkmenistan, and Uzbekistan over the period following the collapse of the Soviet Union from 1991 to the present. This assessment focuses on maternal and child health, mental health, communicable diseases, and non-communicable diseases in an effort to highlight the changes in the healthcare status of these nine countries under scrutiny. Considering that all the post-Soviet nations are officially recognized members of the World Health Organization (WHO) and have demonstrated their commitment to attaining the WHO's objectives, the evaluation of healthcare system progress and improvement was carried out utilizing indicators provided by the WHO. This review reveals that the evolution of healthcare systems could be considered sustainable, given that average life expectancy has returned to the level it was in 1991- the year of the USSR's breakup, and people's health has improved since the turn of the twenty-first century. To enhance the potential success of future healthcare reforms, however, governments must monitor implementation of the reform process, evaluate the achievement of objectives, and make necessary adjustments. The success of future healthcare changes will depend on the active involvement of the government, medical community, and patient community, as well as obtaining the support of local health authorities. This study may help identify successful and failed strategies, guiding future healthcare changes and investments.

Evaluating the Demand for Nucleic Acid Testing in Different Scenarios of COVID-19 Transmission: A Simulation Study

INTRODUCTION

The 2019 novel coronavirus (COVID-19) has been recognized as the most severe human infectious disease pandemic in the past century. To enhance our ability to control potential infectious diseases in the future, this study simulated the influence of nucleic acid testing on the transmission of COVID-19 across varied scenarios. Additionally, it assessed the demand for nucleic acid testing under different circumstances, aiming to furnish a decision-making foundation for the implementation of nucleic acid screening measures, the provision of emergency materials, and the allocation of human resources.

METHODS

Considering the transmission dynamics of COVID-19 and the preventive measures implemented by countries, we explored three distinct levels of epidemic intensity: community transmission, outbreak, and sporadic cases. Integrating the theory of scenario analysis, we formulated six hypothetical epidemic scenarios, each corresponding to possible occurrences during different phases of the pandemic. We developed an improved SEIR model, validated its accuracy using real-world data, and conducted a comprehensive analysis and prediction of COVID-19 infections under these six scenarios. Simultaneously, we assessed the testing resource requirements associated with each scenario.

RESULTS

We compared the predicted number of infections simulated by the modified SEIR model with the actual reported cases in Israel to validate the model. The root mean square error (RMSE) was 350.09, and the R-squared (R2) was 0.99, indicating a well-fitted model. Scenario 4 demonstrated the most effective prevention and control outcomes. Strengthening non-pharmaceutical interventions and increasing nucleic acid testing frequency, even under low testing capacity, resulted in a delayed epidemic peak by 78 days. The proportion of undetected cases decreased from 77.83% to 31.21%, and the overall testing demand significantly decreased, meeting maximum demand even with low testing capacity. The initiation of testing influenced case detection probability. Under high testing capacity, increasing testing frequency elevated the detection rate from 36.40% to 77.83%. Nucleic acid screening proved effective in reducing the demand for testing resources under diverse epidemic prevention and control strategies. While effective interventions and nucleic acid screening measures substantially diminished the demand for testing-related resources, varying degrees of insufficient testing capacity may still persist.

CONCLUSIONS

The nucleic acid detection strategy proves effective in promptly identifying and isolating infected individuals, thereby mitigating the infection peak and extending the time to peak. In situations with constrained testing capacity, implementing more stringent measures can notably decrease the number of infections and alleviate resource demands. The improved SEIR model demonstrates proficiency in predicting both reported and unreported cases, offering valuable insights for future infection risk assessments. Rapid evaluations of testing requirements across diverse scenarios can aptly address resource limitations in specific regions, offering substantial evidence for the formulation of future infectious disease testing strategies.

The Role of Traditional Chinese Medicine and Chinese Pharmacopoeia in the Evaluation and Treatment of COVID-19

The epidemic prompted by COVID-19 continues to spread, causing a great risk to the general population's safety and health. There are still no drugs capable of curing it. Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) are the two other diseases caused by coronaviruses. Traditional Chinese Medicine (TCM) showed benefits in treating SARS and MERS by preventing the disease early, substantially mitigating symptoms, shortening the treatment period, and minimizing risks and adverse reactions caused by hormone therapy. Although several vaccines have been developed and are being used for the treatment of COVID-19, existing vaccines cannot provide complete protection against the virus due to the rapid evolution and mutation of the virus, as mutated viral epitopes evade the vaccine's target and decrease the efficacy of vaccines. Thus, there is a need to develop alternative options. TCM has demonstrated positive effects in the treatment of COVID-19. Previous research studies on TCM showed broad-spectrum antiviral activity, offering a range of possibilities for their potential use against COVID-19. This study shed some light on common TCM used for SARS and MERS outbreaks and their effective use for COVID-19 management. This study provides new insights into COVID-19 drug discovery.

The Epidemiological and Economic Impact of COVID-19 in Kazakhstan: An Agent-Based Modeling

BACKGROUND

Our study aimed to assess how effective the preventative measures taken by the state authorities during the pandemic were in terms of public health protection and the rational use of material and human resources.

MATERIALS AND METHODS

We utilized a stochastic agent-based model for COVID-19's spread combined with the WHO-recommended COVID-ESFT version 2.0 tool for material and labor cost estimation.

RESULTS

Our long-term forecasts (up to 50 days) showed satisfactory results with a steady trend in the total cases. However, the short-term forecasts (up to 10 days) were more accurate during periods of relative stability interrupted by sudden outbreaks. The simulations indicated that the infection's spread was highest within families, with most COVID-19 cases occurring in the 26-59 age group. Government interventions resulted in 3.2 times fewer cases in Karaganda than predicted under a "no intervention" scenario, yielding an estimated economic benefit of 40%.

CONCLUSION

The combined tool we propose can accurately forecast the progression of the infection, enabling health organizations to allocate specialists and material resources in a timely manner.

Factors Influencing Antibiotic Consumption in Adult Population of Kazakhstan

Poor or suboptimal knowledge of appropriate antibiotic use is a cause for global concern and little is known about Central Asian countries. Therefore, this survey is aimed at evaluating awareness about antibiotic use and resistance among the adult population of Kazakhstan. A cross-sectional study of a random sample was conducted between October 2021 and February 2022 among 727 individuals without medical education and followed the methodology described in the WHO report “Antibiotic Resistance: Multi-country public awareness survey”. Half of the respondents (50.4%) received antibiotic therapy within the last 12 months, 40.1% had no prescription for this and 40.4% received no advice from a medical professional. Nearly two-thirds of respondents (65.3%) never heard about antibiotic resistance and 57.2% believed that it is worth requesting the same antibiotic if it helped to treat a similar condition previously. In general, knowledge about antibiotic use proved to be low in 82.1% of respondents and 91.9% agreed with the statement that a common cold requires antibiotics. There is a need for awareness-raising campaigns to improve the knowledge about antibiotic use and resistance in the population of Kazakhstan.

Is It Possible to Predict COVID-19? Stochastic System Dynamic Model of Infection Spread in Kazakhstan

BACKGROUND

Since the start of the COVID-19 pandemic, scientists have begun to actively use models to determine the epidemiological characteristics of the pathogen. The transmission rate, recovery rate and loss of immunity to the COVID-19 virus change over time and depend on many factors, such as the seasonality of pneumonia, mobility, testing frequency, the use of masks, the weather, social behavior, stress, public health measures, etc. Therefore, the aim of our study was to predict COVID-19 using a stochastic model based on the system dynamics approach.

METHOD

We developed a modified SIR model in AnyLogic software. The key stochastic component of the model is the transmission rate, which we consider as an implementation of Gaussian random walks with unknown variance, which was learned from real data.

RESULTS

The real data of total cases turned out to be outside the predicted minimum-maximum interval. The minimum predicted values of total cases were closest to the real data. Thus, the stochastic model we propose gives satisfactory results for predicting COVID-19 from 25 to 100 days. The information we currently have about this infection does not allow us to make predictions with high accuracy in the medium and long term.

CONCLUSIONS

In our opinion, the problem of the long-term forecasting of COVID-19 is associated with the absence of any educated guess regarding the dynamics of β(t) in the future. The proposed model requires improvement with the elimination of limitations and the inclusion of more stochastic parameters.

Restenosis of Coronary Arteries in Patients with Coronavirus Infection: Case Series

Introduction

Coronavirus infection is a risk factor for vascular thrombosis. This is of particular importance for patients undergoing myocardial revascularization since this infection can be a trigger for the formation of restenosis in the area of a previously implanted coronary stent. Understanding the risk factors for stent thrombosis and restenosis is of particular importance in individuals at risk for adverse outcomes. The rarity of such situations makes the present study unique.

Objective

Studying the peculiarities of restenosis and thrombosis of the coronary arteries in patients after coronavirus infection.

Methods

The study was performed in the Department of Cardiovascular Surgery of Emergency Hospital, Semey City, in 2021. We have examined the medical records of 10 consecutive patients with restenosis of coronary arteries after coronavirus infection and 10 matched-by-age patients with similar restenosis of coronary arteries who did not have coronavirus infection as a comparison group. To determine statistically significant differences between independent samples, we calculated the Mann-Whitney U test.

Results

The average age of patients was 65.7 years. Only one case was classified as early restenosis (within 8 days of previous revascularization), two cases represented late restenosis, and seven cases were very late restenoses. In 70% of cases, restenosis was localized in the left anterior descending artery, in 30% of cases, it was in the right coronary artery, and in 40% of cases, it was in the left circumflex artery. In comparison with patients who did not have a coronavirus infection, there were statistically significant differences regarding IgG (P < 0.001) and fibrinogen (P=0.019).

Conclusion

Patients with myocardial revascularization in the past have a higher risk of stent restenosis against the background of coronavirus infection due to excessive neointimal hyperplasia, hypercoagulability, increased inflammatory response, and endothelial dysfunction.

Assessing the medical resources in COVID-19 based on evolutionary game

COVID-19 has brought a great challenge to the medical system. A key scientific question is how to make a balance between home quarantine and staying in the hospital. To this end, we propose a game-based susceptible-exposed-asymptomatic -symptomatic- hospitalized-recovery-dead model to reveal such a situation. In this new framework, time-varying cure rate and mortality are employed and a parameter m is introduced to regulate the probability that individuals are willing to go to the hospital. Through extensive simulations, we find that (1) for low transmission rates (β < 0.2), the high value of m (the willingness to stay in the hospital) indicates the full use of medical resources, and thus the pandemic can be easily contained; (2) for high transmission rates (β > 0.2), large values of m lead to breakdown of the healthcare system, which will further increase the cumulative number of confirmed cases and death cases. Finally, we conduct the empirical analysis using the data from Japan and other typical countries to illustrate the proposed model and to test how our model explains reality.

Impact of the SARS-CoV-2 Outbreak on the Epidemiology and Treatment Outcomes of Fractures of the Proximal Femur in Kazakhstan

The study aimed to assess the impact of isolation and quarantine on the frequency of registration and the treatment of fractures of the proximal femur in Kazakhstan in the context of the COVID-19 pandemic in 2020 (compared to the pre-pandemic period). This retrospective observational comparative study included all primary patients with injuries (the code S72) in the period 2019-2020 according to the national register.

In 2020, the number of S72 fractures was 6.6 % higher compared to 2019. In comparison with 2019, in 2020 the number of beddays of patients was reduced to 7.1±3.8 days (p≤0.001). Both in 2019 and in 2020, the number of women predominated among all patients (p ≤ 0.05). The frequency of conservative treatment in 2020 compared to 2019 was increased from 26.6% to 35.6%, while the surgical procedure for internal fixation was reduced to 34.2% in 2020. In 2020, the highest number of cases among women with S72 fractures cases were recorded in the age groups 60-74 years and 75-90 years. In 2019 in female patients (42%) with S72 cases were registered in the age group 75-90 years.

The incidence of fractures of the proximal femur did not change significantly in 2020 compared to 2019. However, the number of conservative treatment methods has increased along with the decrease in the frequency of surgical interventions. We observed the growth of the frequency of non-surgical treatment methods in 2020 that might impose the possible risks of mortality of these patients in the long term after conservative treatment.

Using simulation modelling and systems science to help contain COVID-19: A systematic review

This study systematically reviews applications of three simulation approaches, that is, system dynamics model (SDM), agent-based model (ABM) and discrete event simulation (DES), and their hybrids in COVID-19 research and identifies theoretical and application innovations in public health. Among the 372 eligible papers, 72 focused on COVID-19 transmission dynamics, 204 evaluated both pharmaceutical and non-pharmaceutical interventions, 29 focused on the prediction of the pandemic and 67 investigated the impacts of COVID-19. ABM was used in 275 papers, followed by 54 SDM papers, 32 DES papers and 11 hybrid model papers. Evaluation and design of intervention scenarios are the most widely addressed area accounting for 55% of the four main categories, that is, the transmission of COVID-19, prediction of the pandemic, evaluation and design of intervention scenarios and societal impact assessment. The complexities in impact evaluation and intervention design demand hybrid simulation models that can simultaneously capture micro and macro aspects of the socio-economic systems involved.

Coronary Heart Disease and Coronavirus Disease 2019: Pathogenesis, Epidemiology, Association with Myocardial Revascularization

BACKGROUND: Coronavirus disease 2019 (COVID-19) causes a hypercoagulable state with a high incidence of thrombotic complications. Patients with a history of myocardial revascularization have more severe complications due to COVID-19. Coronary stent thrombosis has become significantly more common during the COVID-19 pandemic. AIM: The aim of our study is to analyze scientific information on the risks of stent thrombosis in patients who underwent COVID-19. METHODS: A search was made for scientific publications in evidence-based medicine databases and web resources: PubMed, MEDLINE, UpToDate, TripDatabase, ResearchGate, and Google Scholar. Inclusion criteria were: (1) Observational studies or case series involving patients with a confirmed diagnosis of COVID-19 and myocardial infarction requiring myocardial revascularization; (2) the division of the population into survivors and non-survivors; and (3) data on the presence of the previous myocardial revascularization. Exclusion criteria: Case description and editorials/bulletins. In all articles selected for further analysis, 49 sources were considered that met the inclusion criteria and excluded duplication or repetition of information. RESULTS: Coronavirus infection has contributed to the change in the course of myocardial infarction in patients undergoing myocardial revascularization. The incidence of stent thrombosis has a positive correlation with the severity of the coronavirus infection. The previous myocardial revascularization procedures significantly increase the risk of mortality in patients with coronavirus infection. This is especially actual for elderly patients. CONCLUSION: One of the most vulnerable groups is elderly patients who have undergone myocardial revascularization after myocardial infarction in the past and have concomitant diseases. An analysis of scientific publications has shown that further larger-scale clinical studies are needed to confirm the hypothesis about the negative impact of coronavirus infection on stent thrombosis in patients who have undergone COVID-19.

Seropositivity of SARS-CoV-2 in the Population of Kazakhstan: A Nationwide Laboratory-Based Surveillance

The data on seroprevalence of anti-SARS-CoV-2 antibodies in Kazakhstani population are non-existent, but are needed for planning of public health interventions targeted to COVID-19 containment. The aim of the study was to estimate the seropositivity of SARS-CoV-2 infection in the Kazakhstani population from 2020 to 2021. We relied on the data obtained from the results from “IN VITRO” laboratories of enzyme-linked immunosorbent assays for class G immunoglobulins (IgG) and class M (IgM) to SARS-CoV-2. The association of COVID-19 seropositivity was assessed in relation to age, gender, and region of residence. Additionally, we related the monitoring of longitudinal seropositivity with COVID-19 statistics obtained from Our World in Data. The total numbers of tests were 68,732 for SARS-CoV-2 IgM and 85,346 for IgG, of which 22% and 63% were positive, respectively. The highest rates of positive anti-SARS-CoV-2 IgM results were seen during July/August 2020. The rate of IgM seropositivity was the lowest on 25 October 2020 (2%). The lowest daily rate of anti-SARS-CoV-2 IgG was 17% (13 December 2020), while the peak of IgG seropositivity was seen on 6 June 2021 (84%). A longitudinal serological study should be envisaged to facilitate understanding of the dynamics of the epidemiological situation and to forecast future scenarios.

Comparative Analysis Of Triage Systems At Emergency Departments Of Different Countries: Implementation In Kazakhstan

Medical sorting is aimed at assessment of disease severity and has to be carried out within a short time to determine the priorities for patient care and transportation to the most appropriate place for future treatment. The goal of this study was to provide an integrative review by analyzing the publications on the most common triage systems worldwide in order to select and implement the most reliable system at emergency departments. We searched for publications relevant to our comparative analysis in evidence-based medicine databases. A total of 1,740 literary sources were identified, of which 42 were selected for analysis. Comparative analysis of different triage systems may help implementing the most efficient system in Kazakhstan. The Emergency Severity Index is considered the most reliable and accurate tool used in international practice, and it could provide a basis for introduction of triage system at emergency departments in Kazakhstan.

Clinical characteristics and risk factors for disease severity and mortality of COVID-19 patients with diabetes mellitus in Kazakhstan: A nationwide study

BACKGROUND

Diabetes mellitus (DM) is associated with higher risk of developing infectious disease and COVID-19 is not the exception. There is a need to generate more data on clinical characteristics and risks of COVID19 patients presenting with DM. In this retrospective study we aimed to report on demographic features, clinical data, and outcomes of COVID-19 patients with DM in comparison with age- and sex-matched patients without DM.

METHODS

This was a retrospective study that relied on the nationwide data on all COVID-19 patients who were diagnosed from 14 March to 18 April, 2020. Overall, there were 31 cases with DM for which we randomly matched 4 patients without DM by age and sex.

RESULTS

COVID-19 patients with associated DM had less beneficial outcomes and more severe disease course both at hospital admission and final diagnosis, as compared with the age and sex-matched non-DM patients. Diabetics were more predisposed to impaired breathing (29.0 % versus 4.9 % in controls), nausea/vomiting (6.5 % versus 0 % in controls) and weakness/lethargy (45.2 % versus 26.0 % in controls). Finally, 48.4 % of diabetics showed the signs of pneumonia on CT scans versus 20.3 % of non-diabetics (p = 0.001), and 32.3 % of DM patients were admitted to intensive care units as compared with just 5.7 % of non-DM patients (p<0.001).

CONCLUSION

There is a need to envisage early status monitoring and supportive care in this vulnerable category of patients to enable better prognosis.