Cases Of Infectious Diseases Research Articles

Public Health and Political Governance

Abstract In the light of the Covid-19 pandemic, its mutations, concealment by people and the resistance to vaccines against it, it is relevant to examine the outbreak of bubonic plague in colonial Lagos during the early twentieth century and the response by the British colonial authorities. The methodology applied to this study is historical, drawing information from medical, sanitary, land use and physical planning documents accessed from various archives as well as some secondary sources. It is clear that the colonial government’s housing and public health regulations, which allowed authorities to inspect people’s homes for cases of infectious disease, drove people to escape into the hinterland, increasing the spread of the plague. Consequently, the colonial authorities carried out a massive structural and physical reorganisation of towns and villages. They also embarked on large-scale land reclamation, decongested overcrowded houses and introduced sanitary measures to make the environment more habitable. This paper argues that through effective political governance structures the colonial government strategically eliminated the bubonic plague in Lagos.

Family physicians overestimate diagnosis probabilities regardless of the test results.

As useful tools for clinical decision-making, diagnostic tests require careful interpretation in order to prevent underdiagnosis, overdiagnosis or misdiagnosis. The aim of this study was to explore primary care practitioners' understanding and interpretation of the probability of disease before and after test results for six common clinical scenarios. This cross-sectional study was conducted with 414 family physicians who were working at primary care in Istanbul via face-to-face interviews held between November 2021 and March 2022. The participants were asked to estimate the probability of diagnosis in six clinical scenarios provided to them. Clinical scenarios were about three cancer screening cases (breast, cervical and colorectal), and three infectious disease cases (pneumonia, urinary tract infection, and COVID-19). For each scenario participants estimated the probability of the diagnosis before application of a diagnostic test, after a positive test result, and after a negative test result. Their estimates were compared with the true answers derived from relevant guidelines. For all scenarios, physicians' estimates were significantly higher than the scientific evidence range. The minimum overestimation was positive test result for COVID-19 and maximum was pre-test case for cervical cancer. In the hypothetical control question for prevalence and test accuracy, physicians estimated disease probability as 95.0% for a positive test result and 5.0% for a negative test result while the correct answers were 2.0 and 0%, respectively (p < 0.001). Comparing the scientific evidence, overestimation in all diagnostic scenarios, regardless of if the disease is an acute infection or a cancer, may indicate that the probabilistic approach is not conducted by the family physicians. To prevent inaccurate interpretation of the tests that may lead to incorrect or unnecessary treatments with adverse consequences, evidence-based decision-making capacity must be strengthened.

HIV/AIDS, SARS, and COVID-19: the trajectory of China's pandemic responses and its changing politics in a contested world.

The COVID-19 pandemic has revealed the contested politics of global health governance, though we still don't know enough about the dynamics of domestic pandemic responses, or about the relationship between the politics of those responses and the politics of global health governance, both of which have changed significantly in recent decades. Focusing on three cases (HIV/AIDS, SARS, and COVID-19) of cross-border infectious diseases, this article explores the trajectory of China's pandemic responses in the context of globalization. Attending to changing politics at domestic, international, and global levels, I argue that those responses have been a complex combination of China's domestic politics (e.g., priorities, institutions, leadership, and timing), its international relations (especially with the US), and its engagements with global health governance. It is concluded that the increasing divergence of pandemic responses in a time of ubiquitous global health crisis demands urgent attention to the connections (including contestations) between domestic pandemic responses and the evolvement of global health governance from a broader perspective that considers changes in geopolitics.

Phytonutrient Screening and In vitro Antibacterial and Antifungal Properties of Polar and Nonpolar Extracts of Albizia gummifera, Prunus africana, and Combretum molle from Mount Elgon Region, Kenya

Background: Globally, and particularly in less-developed countries, one of the principal factors associated with morbidity and mortality is infectious diseases. Over the years, the abuse and misuse of pharmaceutical products have caused an increase in resistant microbes, and consequently, today, the rate of infectious disease cases continues to increase to dangerously high levels as most medications have lost their efficacy. This indicates that there’s a need for new effective medications and calls for active research in drug discovery to curb this dangerous trend.&#x0D; Results: Obtained data demonstrated the presence of different bioactive compounds in the tested plant extracts such as glycosides, alkaloids, tannins, terpenoids, saponins, and phenols. Using the Kirby-Bauer disc diffusion method, P. africana methanol and ethyl acetate extracts showed significantly bigger inhibition zones compared to the rest against S. aureus (excluding controls). None of the tested extracts, however, were able to inhibit C. albicans and E. coli. The P. africana methanolic extract and the A. gummifera hexane, ethyl acetate, and methanolic extracts all inhibited the growth of S. aureus at the same minimum concentration of 31.25 mg/ml. The methanolic extract of C. molle exhibited the least activity against S. aureus, with an MIC of 250 mg/ml and mean zones of inhibition of 9.33±0.33 mm.&#x0D; Conclusions: This study revealed the presence of various phytoconstituents in crude extracts of the selected medicinal plants, but also highlighted the resistance of E. coli and C. albicans to these phytochemicals. The P. africana methanolic extract showed strongest inhibitory effect against S. aureus compared to the other plant extracts. The highest susceptibility was demonstrated by S. aureus, while E. coli and C. albicans were resistant to all the extracts. These findings support the usage of A. gummifera, P. africana, and C. molle in folk medicine against infections caused by S. aureus and highlight them as potential sources of phytonutrients for the development of new drugs.

Modeling Infectious Disease Trend using Sobolev Polynomials

Trend analysis plays an important role in infectious disease control. An analysis of the underlying trend in the number of cases or the mortality of a particular disease allows one to characterize its growth. Trend analysis may also be used to evaluate the effectiveness of an intervention to control the spread of an infectious disease. However, trends are often not readily observable because of noise in data that is commonly caused by random factors, short-term repeated patterns, or measurement error. In this paper, a smoothing technique that generalizes the Whittaker-Henderson method to infinite dimension and whose solution is represented by a polynomial is applied to extract the underlying trend in infectious disease data. The solution is obtained by projecting the problem to a finite-dimensional space using an orthonormal Sobolev polynomial basis obtained from Gram-Schmidt orthogonalization procedure and a smoothing parameter computed using the Philippine Eagle Optimization Algorithm, which is more efficient and consistent than a hybrid model used in earlier work. Because the trend is represented by the polynomial solution, extreme points, concavity, and periods when infectious disease cases are increasing or decreasing can be easily determined. Moreover, one can easily generate forecast of cases using the polynomial solution. This approach is applied in the analysis of trends, and in forecasting cases of different infectious diseases.

The antimicrobial study of white turmeric (Curcuma zedoaria) extracted using deep euthectic solvent (DES) and ultrasonication

This research is prompted by the emergence of various cases of infectious diseases and antibiotic resistance that often occur and the development of the latest research methods in the field of medicinal plants. One of the medicinal plants that is often used is Curcuma zedoaria which is generally extracted using conventional solvents. This research aims to find new innovations in the extraction process of medicinal plants. This research is a laboratory experiment carried out in vitro. This research uses the latest solvent, called DES (Deep Eutectic Solvent) with the help of ultrasonication to extract active compounds from C. zedoaria as a natural anti-bacterial. DES is known as an environmentally friendly solvent, cheap, easy to make, and is still relatively new in Indonesia. The C. zedoaria extraction process uses two types of DES solvent composition assisted by a ultrasonicator. The research results show that: White turmeric extract (C. zedoaria) obtained by extraction using DES solvent and ultrasonication. Ultrasonication results using 30%, 70% and 100% DES solvent showed antimicrobial properties against Escherichia coli with a lower zone of inhibition compared to the antibiotic ciprofloxacin. Ultrasonication results using 30%, 70% and 100% DES solvent showed antimicrobial properties against Staphylococcus aureus with a lower zone of inhibition compared to ciprofloxacin. TLC data shows that the white turmeric extract obtanined contains various antimicrobial substances which allows to inhibit each other to such an extent that their activity is lower than ciprofloxacin.

A Novel Multiplex LAMP Assay for the Rapid and Accurate Diagnosis of Visceral Leishmaniasis Caused by Leishmania infantum from Iran.

Visceral leishmaniosis (VL) is one of the neglected tropical diseases despite being responsible for serious clinical symptoms, some of which lead to fatal outcomes. Thus, there is a need to apply accurate, rapid, and specific diagnostic measurements in order to control the disease and reduce the mortality rate. We aimed to develop and validate a multiplex LAMP assay for the diagnosis of VL caused by Leishmania infantum (L. infantum). Moreover, a thorough assessment was conducted to determine the effectiveness of multiplex LAMP in identifying various Leishmania species, such as Leishmania tropica (L. tropica) and Leishmania major (L. major) in comparison to Leishmania infantum (L. infantum). The diagnostic performance of the multiplex LAMP method for VL was compared to each LAMP assay, real-time polymerase chain reaction (RT-qPCR), and nested PCR technique. Two separated primers were set and used in a multiplex LAMP assay which was designed based on the ITS2 (internal transcribed spacer II) and were selected on the basis of conserved and high copy number region. Multiplex LAMP primers were designed using an online tool available at https://www.primerexplorer.jp/e. The alignment was performed using MEGA5, and the primers were further adjusted utilizing GENE Runner software. All molecular methods were tested on the serial dilution of cloned plasmid containing ITS region from standard strains of L. infantum, L. tropica, and L. major. Moreover, multiplex LAMP assay was evaluated and compared based on both standard strains and 55 clinical samples from humans as well as dogs. Various approaches were applied to interpret the multiplex LAMP reaction which deciphered a higher sensitivity when compared to the RT-qPCR for L. infantum (one copy number of plasmid, equal to 0.85 femtograms (fg) of plasmid concentration, and 0.004 parasite DNA per μL) detection while these three standard strains of Leishmania were confirmed to contain 40 DNA copies using RT-qPCR. Additionally, the multiplex LAMP detection limit was approximately equivalent to RT-qPCR for L. major and L. tropica, which included 0.342 picograms (pg) and 342 femtograms (fg) of plasmid concentration, 4 × 103 and 4 × 102 copy number of plasmid, and 17.1 and 1.71 parasite DNA per μL for L. major and L. tropica, respectively. Nested PCR exhibited a lower detection limit for L. infantum of 4 × 106 plasmid copy number compared to multiplex LAMP and RT-qPCR. Multiplex LAMP has the potential for accurate and rapid detection of infectious disease, successful treatment, and finding and monitoring asymptomatic cases, especially in low-income countries.

A Formal Approach to Model the Expansion of Natural Events: The Case of Infectious Diseases

A formal approach to modeling the expansion of natural events is presented in this paper. Since the mathematical, statistical or computational methods used are not relevant for development, a modular framework is carried out that guides from the external observation down to the innermost level of the variables that have to appear in the future mathematical-computational formalization. As an example we analyze the expansion of Covid-19. We perform a qualitative estimation of the impact of the causes on the delays of the spread and an analysis of the parameters.

Modeling and clinical data exchange in registration of infectious disease cases

Modeling and clinical data exchange in registration of infectious disease cases

Oriented transformer for infectious disease case prediction

Oriented transformer for infectious disease case prediction

Impact of Preventive Measures Against Covid-19 on the Prevalence of Infectious Diseases Among the Population of The Republic of Kazakhstan

Aim: To study the impact of COVID-19 preventive measures on airborne and fecal-oral infectious diseases in Kazakhstan Materials and Research Methods: We used comparative data from the Study of Sanitary and Epidemiological Control of Infectious Morbidity in the Population of the Kazakhstan for 2019-2020. In this case, there are infectious diseases transmitted mainly by airborne droplets among the entire population (children, adolescents and adults) and diseases with fecal-oral transmission. Results: The total number of cases detected was 1,239,635. Thus, the percentage change in the total number of cases from 2019 to 2020 was - (+) 5.6%. In 2019, 596,216 cases of infectious diseases transmitted by airborne droplets were detected, and in 2020 - 631,407, i.e. 35,191 more were revealed (+5.9%). ARVI and influenza account for the largest proportion in this group, and the incidence has increased in these groups. At the same time, exacerbations of diseases transmitted by the fecal-oral route: from 2019 to 2020, diseases occurred in 1,716 (-38.8%) cases. Conclusion: This study demonstrated a useful effective COVID-19 prevention measure for several other infectious diseases in Kazakhstan during the pandemic. However, special attention should be paid to the increase in the incidence of ARVI and influenza in Kazakhstan. Possible exceptions, according to the authors, are ignoring the high incidence of influenza and ARVI in 2020 compared to 2019, since special attention was focused on COVID-19. The next hypothesis is the impact of COVID-19 on influenza immunization in the country - restrictive measures have reduced the number of influenza vaccinated.

Hysteresis effects of different levels of storm flooding on susceptible enteric infectious diseases in a central city of China

BackgroundRecently, attention has focused on the impact of global climate change on infectious diseases. Storm flooding is an extreme weather phenomenon that not only impacts the health of the environment but also worsens the spread of pathogens. This poses a significant challenge to public health security. However, there is still a lack of research on how different levels of storm flooding affect susceptible enteric infectious diseases over time.MethodsData on enteric infectious diseases, storm flooding events, and meteorology were collected for Changsha, Hunan Province, between 2016 and 2020. The Wilcoxon Rank Sum Test was used to identify the enteric infectious diseases that are susceptible to storm flooding. Then, the lagged effects of different levels of storm flooding on susceptible enteric infectious diseases were analyzed using a distributed lag nonlinear model.ResultsThere were eleven storm flooding events in Changsha from 2016 to 2020, concentrated in June and July. 37,882 cases of enteric infectious diseases were reported. During non-flooding days, the daily incidence rates of typhoid/paratyphoid and bacillary dysentery were 0.3/100,000 and 0.1/100,000, respectively. During flooding days, the corresponding rates increased to 2.0/100,000 and 0.8/100,000, respectively. The incidence rates of both diseases showed statistically significant differences between non-flooding and flooding days. Correlation analysis shows that the best lags for typhoid/paratyphoid and bacillary dysentery relative to storm flooding events may be 1 and 3 days. The results of the distributed lag nonlinear model showed that typhoid/paratyphoid had the highest cumulative RR values of 2.86 (95% CI: 1.71–4.76) and 8.16 (95% CI: 2.93–22.67) after 4 days of general flooding and heavy flooding, respectively; and bacillary dysentery had the highest cumulative RR values of 1.82 (95% CI: 1.40–2.35) and 3.31 (95% CI: 1.97–5.55) after 5 days of general flooding and heavy flooding, respectively.ConclusionsTyphoid/paratyphoid and bacillary dysentery are sensitive enteric infectious diseases related to storm flooding in Changsha. There is a lagging effect of storm flooding on the onset of typhoid/paratyphoid and bacillary dysentery, with the best lagging periods being days 1 and 3, respectively. The cumulative risk of typhoid/paratyphoid and bacillary dysentery was highest at 4/5 days lag, respectively. The higher of storm flooding, the higher the risk of disease, which suggests that the authorities should take appropriate preventive and control measures before and after storm flooding.

Mortality analysis of the Gomel region population from infectious and parasitic diseases in 2009-2019

According to the World Health Organization, infectious and parasitic diseases account for about a quarter of all deaths in the world. In Belarus, 2,0-2,5 million cases of infectious diseases are registered annually. An analysis of the levels and trends of mortality from infectious and parasitic diseases is important for improving the practice of anti-epidemic work.Aims: Conduct an analysis of mortality from infectious and parasitic diseases in the Gomel region for the period 2009-2019.For the study, official data of the National Statistical Committee of the Republic of Belarus on the number of deceased persons and estimated data (mortality rates) of the «Gomel Regional Clinical Hospital» organizational and methodological department on infectious and parasitic diseases for 2009-2019 were used. The mortality rates of the Gomel region population from infectious and parasitic diseases were analyzed. We used epidemiological and statistical methods of information processing. To assess the statistical significance of differences, Student’s t-test was used.During the analyzed period in the Gomel region, there was a statistically significant trend towards a decrease in the mortality rate of the population from infectious and parasitic dis -eases, both among urban and rural residents. A statistically significant downward trend in mortality rates was also noted among people of working age. In the dynamics of the analyzed years in the period from 2009 to 2015, there was a statistically significant decrease in the mortality rate of the population older than working age, from 2016 to 2019 a statistically significant increase was established.In order to further reduce mortality from infectious and parasitic diseases, the main emphasis should be placed on two aspects: the formation of the population’s commitment to preventive measures and the improvement of the quality of medical care for the population.

Forecasting New Tuberculosis Cases in Malaysia: A Time-Series Study Using the Autoregressive Integrated Moving Average (ARIMA) Model.

Background The application of the Box-Jenkins autoregressive integrated moving average (ARIMA) model has been widely employed in predicting cases of infectious diseases. It has shown a positive impact on public health early warning surveillance due to its capability in producing reliable forecasting values. This study aimed to develop a prediction model for new tuberculosis (TB) cases using time-series data from January 2013 to December 2018 in Malaysia and to forecast monthly new TB cases for 2019. Materials and methods The ARIMA model was executed using data gathered between January 2013 and December 2018 in Malaysia. Subsequently, the well-fitted model was employed to make projections for new TB cases in the year 2019. To assess the efficacy of the model, two key metrics were utilized: the mean absolute percentage error (MAPE) and stationary R-squared. Furthermore, the sufficiency of the model was validated via the Ljung-Box test. Results The results of this study revealed that the ARIMA (2,1,1)(0,1,0)12 model proved to be the most suitable choice, exhibiting the lowest MAPE value of 6.762. The new TB cases showed a clear seasonality with two peaks occurring in March and December. The proportion of variance explained by the model was 55.8%with a p-value (Ljung-Box test) of 0.356. Conclusions The application of the ARIMA model has developed a simple, precise, and low-costforecasting model that provides a warning six months in advancefor monitoring the TB epidemicin Malaysia, which exhibits a seasonal pattern.

POLA PENYEBARAN PENYAKIT MENULAR BERDASARKAN KABUPATEN/KOTA DI JAWA TIMUR MENGGUNAKAN ANALISIS KORESPONDENSI

Infectious diseases are a problem that is still a challenge and has not been resolved in Indonesia. The number of infectious disease cases continues to increase every year in Indonesia. Infectious diseases that are still a problem in Indonesia include tuberculosis (TB), pneumonia and leprosy (Leprosy). Identification of infectious disease endemic areas is an important issue in the health sector, the average rate of people with physical disabilities and deaths originating from infectious diseases. Indonesia, as a country consisting of 34 provinces, including East Java as one of the provinces that has a high rate of infectious disease cases. Therefore, research was conducted using correspondence analysis which aimed to determine the pattern of infectious disease trends and grouping districts / cities in East Java Province based on similarities between the spread of disease sufferers in each district / city. This type of research uses quantitative methods with secondary data obtained from the Central Bureau of Statistics of East Java Province. The results of correspondence analysis show that the spread of pneumonia and tuberculosis in East Java Province has a relative tendency to almost all regencies/cities in East Java, while the spread of leprosy is closer to Sampang Regency. From this research, it can be used to supervise and control infectious diseases in districts / cities in East Java Province, so that the government can adjust policy formulation and actions to prevent an increase in infectious disease cases in East Java

Комплексный подход к терапии острых респираторных вирусных инфекций

According to the World Health Organization, acute respiratory viral infections (ARVIs) account for 70–85% of all cases of infectious diseases in the world. High prevalence rates of ARVIs, influenza and COVID-19 require the search for new methods to prevent, treat, and control epidemics. Furthermore, there are significant economic losses due to high incidence and temporary disability rates. ARVIs constitute a heterogenous group of the infectious respiratory tract disorders caused by numerous viruses, such as influenza virus, parainfluenza virus, respiratory syncytial virus, adenovirus, coronavirus, and many other viruses. Symptoms of various ARVIs have much in common and include fever, cough, chest pain, headache, myalgia, asthenia, anosmia, etc. The paper discusses the features of diagnostic search and treatment tactics in seasonal ARVIs, as well as feasibility of preventive measures. The data of meta-analyses and systematic reviews are used to explore the role and potential of zinc, selenium, vitamin C, vitamin A, and vitamin E for prevention and treatment of bronchopulmonary diseases in adults.

Using Bandit Algorithms to Maximize SARS-CoV-2 Case-Finding: Evaluation and Feasibility Study.

The Flexible Adaptive Algorithmic Surveillance Testing (FAAST) program represents an innovative approach for improving the detection of new cases of infectious disease; it is deployed here to screen and diagnose SARS-CoV-2. With the advent of treatment for COVID-19, finding individuals infected with SARS-CoV-2 is an urgent clinical and public health priority. While these kinds of Bayesian search algorithms are used widely in other settings (eg, to find downed aircraft, in submarine recovery, and to aid in oil exploration), this is the first time that Bayesian adaptive approaches have been used for active disease surveillance in the field. This study's objective was to evaluate a Bayesian search algorithm to target hotspots of SARS-CoV-2 transmission in the community with the goal of detecting the most cases over time across multiple locations in Columbus, Ohio, from August to October 2021. The algorithm used to direct pop-up SARS-CoV-2 testing for this project is based on Thompson sampling, in which the aim is to maximize the average number of new cases of SARS-CoV-2 diagnosed among a set of testing locations based on sampling from prior probability distributions for each testing site. An academic-governmental partnership between Yale University, The Ohio State University, Wake Forest University, the Ohio Department of Health, the Ohio National Guard, and the Columbus Metropolitan Libraries conducted a study of bandit algorithms to maximize the detection of new cases of SARS-CoV-2 in this Ohio city in 2021. The initiative established pop-up COVID-19 testing sites at 13 Columbus locations, including library branches, recreational and community centers, movie theaters, homeless shelters, family services centers, and community event sites. Our team conducted between 0 and 56 tests at the 16 testing events, with an overall average of 25.3 tests conducted per event and a moving average that increased over time. Small incentives-including gift cards and take-home rapid antigen tests-were offered to those who approached the pop-up sites to encourage their participation. Over time, as expected, the Bayesian search algorithm directed testing efforts to locations with higher yields of new diagnoses. Surprisingly, the use of the algorithm also maximized the identification of cases among minority residents of underserved communities, particularly African Americans, with the pool of participants overrepresenting these people relative to the demographic profile of the local zip code in which testing sites were located. This study demonstrated that a pop-up testing strategy using a bandit algorithm can be feasibly deployed in an urban setting during a pandemic. It is the first real-world use of these kinds of algorithms for disease surveillance and represents a key step in evaluating the effectiveness of their use in maximizing the detection of undiagnosed cases of SARS-CoV-2 and other infections, such as HIV.

Construction and effectiveness evaluation of a knowledge-based infectious disease monitoring and decision support system

To improve the hospital's ability to proactively detect infectious diseases, a knowledge-based infectious disease monitoring and decision support system was established based on real medical records and knowledge rules. The effectiveness of the system was evaluated using interrupted time series analysis. In the system, a monitoring and alert rule library for infectious diseases was generated by combining infectious disease diagnosis guidelines with literature and a real medical record knowledge map. The system was integrated with the electronic medical record system, and doctors were provided with various types of real-time warning prompts when writing medical records. The effectiveness of the system's alerts was analyzed from the perspectives of false positive rates, rule accuracy, alert effectiveness, and missed case rates using interrupted time series analysis. Over a period of 12 months, the system analyzed 4,497,091 medical records, triggering a total of 12,027 monitoring alerts. Of these, 98.43% were clinically effective, while 1.56% were invalid alerts, mainly owing to the relatively rough rules generated by the guidelines leading to several false alarms. In addition, the effectiveness of the system's alerts, distribution of diagnosis times, and reporting efficiency of doctors were analyzed. 89.26% of infectious disease cases could be confirmed and reported by doctors within 5 min of receiving the alert, and 77.6% of doctors could complete the filling of 33 items of information within 2 min, which is a reduction in time compared to the past. The timely reminders from the system reduced the rate of missed cases by doctors; the analysis using interrupted time series method showed an average reduction of 4.4037% in the missed-case rate. This study proposed a knowledge-based infectious disease decision support system based on real medical records and knowledge rules, and its effectiveness was verified. The system improved the management of infectious diseases, increased the reliability of decision-making, and reduced the rate of underreporting.

COVID-19 Testing Among Out-of-Hospital Cardiac Arrest Patients: Implications for Public Health

Objective The objective of this study was to compare COVID-19 test positivity among out-of-hospital cardiac arrest patients whose resuscitative efforts were terminated in the field with the surrounding community. Methods This was a retrospective cohort study of out-of-hospital cardiac arrest patients for whom unsuccessful resuscitative efforts were terminated in the field. Emergency medical services (EMS) personnel obtained postmortem COVID-19 nasal swab specimens from these patients between July 1, 2020 and February 28, 2022 to facilitate patient contact tracing and awareness of potential occupational exposure. A chi-square (n-1) was used to compare test result proportions between cardiac arrest patients and the community at large. A Pearson correlation was used to correlate test positivity among the two groups. Results EMS personnel obtained postmortem specimens from 648 cardiac arrest patients; 20 (3.1%) were inconclusive. Of the 628 specimens successfully tested, 69 (11.0%) were positive, and 559 (89.0%) were negative. Monthly positivity ranged from 0.0% to 34.0%. For the community at large, overall test positivity during the same period was 5.1%, with a monthly range from 0.4% to 15.2%. Overall, expired and tested cardiac arrest patients had 5.9% (95%CI 3.68 − 8.59) greater COVID-19 test positivity than the general community. There was significant correlation in monthly positivity rates between the groups (r = 0.778, p < .001, 95%CI0.51 − 0.91). Conclusions Compared to the general population, COVID-19 was over-represented among EMS cardiac arrest patients who died in the field. Postmortem testing by EMS personnel, not typical practice, identified infectious disease cases that would have otherwise gone undetected, indicating potential for future surveillance applications.

Assessment of the legal regulation of forensic medical bureau activities in the field of anti-epidemic measures

Introduction. The staff of the Bureau of Forensic Medicine (BFM) experience a high microbial load in the performance of their professional duties, which poses a serious health hazard. Cases of infectious diseases continue to be recorded among the medical personnel of the BFM, which requires the prevention of infection during professional activities. The process of legal regulation of BFM activities in terms of compliance with sanitary and hygienic measures ensuring the safety of BFM employees from infectious contamination and improving the quality of expertise is becoming highly relevant.The purpose of the study is to propose measures to improve the regulation of relevant procedures based on the analysis of the legal regulation of BFM activities in matters of infectious safety.Materials and methods. We studied laws and bylaws at the federal and departmental levels. The regulatory framework was evaluated at the following conditional stages of forensic medical examination: processing of the sectional table; processing of instruments used for autopsy; personnel hand hygiene; current and general cleaning in the sectional rooms of the BFM.Results It was noted that there are no recommendations for disinfection after each dissection when processing the sectional table, the disagreements in the documents regulating the processing and disinfection of sectional instruments were revealed, the necessity of processing the instruments by mechanized method with the help of ultrasonic washers was shown. The points requiring attention with respect to the use of personal protective equipment, treatment of experts’ hands and other antiepidemic measures in the light of the new regulatory documents that have come into force are listed: Sanitary Rules and Regulations 3.3686-21 and Sanitary Rules 2.1.3678-20.Discussion The identified contradictions in the issues determining the actions of the expert at each of the stages indicate that the sanitary and hygienic measures are covered insufficiently and require more detailed elaboration.Conclusion Changes are required at the legislative, subordinate, and regulatory levels. Standard operating procedures must be implemented for BSMSE staff, which must be carried out in compliance with the requirements of the legislation regulating the activities of BFM, as well as precautions to ensure the infectious safety of employees.