Spread Of COVID-19 Disease Research Articles

Research on blood donation and supply of red blood cell products to medical institutions under the spread of COVID-19 disease in Japan

Research on blood donation and supply of red blood cell products to medical institutions under the spread of COVID-19 disease in Japan

Post-migration infection with SARS-CoV-2 in Venezuelan migrants: A laboratory-based epidemiological observational study

BackgroundSince 2015, over 6 million Venezuelans migrated to Colombia and neighboring countries. While most people adhered to lockdown measures, migrants kept moving during the COVID-19 pandemic. MethodTo investigate the extent of migration-associated SARS-CoV-2 infections, we interviewed 1209 adult Venezuelan migrants upon arrival to Bucaramanga, Colombia, 200 km from the Colombian-Venezuelan border along the main migration route during April–September 2021, collected individual-level socio-economic and clinical data, sampled blood and saliva, and assessed SARS-CoV-2 infection by serological, molecular and phylogenetic tools. ResultsSARS-CoV-2 RT-PCR positivity was 1.9 % (95 % Confidence Interval (CI), 1.2–2.9) without varying significantly over the study period (chi-square, p = 0.922) and significantly associated with stay in Colombia >14 days (p = 0.018; prevalence ratio 3.3, 95 % CI, 1.2–8.7). Pre-existing SARS-CoV-2-specific antibodies were neither significantly associated with preventing infection (Chi-square, p = 0.188), nor symptom development (Fisher, p = 0.246). Predominance and time of detection of SARS-CoV-2 Mu and Gamma variants in migrants in comparison to available genomic data suggested infection predominantly in Colombia. SARS-CoV-2 IgG-based seroprevalence was 34.2 % (95 % CI, 31.5–36.9). Detection of SARS-CoV-2-specific antibodies was significantly associated with previous contact with infected individuals (p = 0.002). ConclusionsSARS-CoV-2 infection occurred predominantly after immigration, potentially facilitated by densely populated border camps. Improved infrastructure and health care will prevent migration-associated spread of COVID-19 and other infectious diseases.

ANALYSIS OF DETERMINANTS OF COVID-19 VACCINATION BEHAVIOR IN THE ACEH BESAR COMMUNITY

The COVID-19 vaccination program is one of the Government's policies to prevent the spread of COVID-19 disease. Some people in Aceh Besar receive and participate in vaccinations voluntarily. However, there are some people who take vaccinations because they are forced to and there are also those who refuse vaccination. This community behavior has greatly influenced the achievement of COVID-19 vaccination in Aceh Besar. In mid-February 2022, the achievement of the first dose of COVID-19 vaccination in Aceh Besar reached 90.5% and the achievement of the second dose was still low at only 47%. Objective : analyze the relationship between Perceived Behavioral Control and behavior, analyze the relationship between Actual Behavioral Control and behavior and analyze the relationship between Actual Behavioral Control and Perceived Behavioral Control. Method : This research is a quantitative research with a cross sectional research design. Sampling using cluster sampling. The respondents were determined to be 384 people. Data analysis with Spearman Correlation using the SPSS application. Results : There is a significant relationship between Perceived Behavioral Control and behavior, between Actual Behavioral Control and behavior, and between Actual Behavioral Control and Perceived Behavioral Control (p-value 0.000). There is a fairly strong relationship between Perceived Behavioral Control and behavior (r = 0.433). There is a fairly strong relationship between Actual Behavioral Control and behavior (r = 0.502). There is a strong relationship between Actual Behavioral Control and Perceived Behavioral Control (r = 0.725). Conclusion : Actual Behavioral Control influences COVID-19 vaccination behavior in the people of Aceh Besar more than Perceived Behavioral Control.

Optimization of testing protocols to screen for COVID-19: a multi-objective model.

In this paper we develop a new multi-objective simulated annealing (MOSA) algorithm to generate optimal testing protocols for infectious diseases, using the COVID-19 pandemic as our context. A SEIR (susceptible-exposed-infected-recovered) epidemiological model is embedded as the computational platform for our MOSA algorithm to optimize testing protocols for screening across three joint objectives: minimum cost of test materials, minimum total infections over the testing horizon, and minimum number of false negatives over the horizon. We demonstrate the application of this optimization tool to recommend screening protocols for K-12 school districts in the U.S.State of North Carolina. Our approach is scalable by population coverage and can be employed at the level of individual school districts or regional collections of districts, individual schools or collections of schools across a district, business sites, or nursing homes, among other congregate settings where individuals may be screened prior to gaining entry to the site. The algorithm can be solved two ways, generating either independent optimal protocols across individual testing locations, or a common protocol covering all locations in the collection of testing sites. Our findings can be used to inform policy decisions to guide the development of effective testing strategies for controlling the spread of COVID-19 or other pandemic diseases in a wide range of congregate settings across various geographic regions.

A Modified SIVR Mathematical Model of Covid-19 Post-vaccination Stability Analysis in Kenya

In this paper, the study focused on carrying out a stability analysis on a modified SIR model for the COVID-19 pandemic for the period after vaccination in Kenya. The purpose of the work was to show that whereas the rate and the extent of disease spread amongst the Kenyan people was not as wide spread as happened in other parts of the world, it was necessary for government and policy makers to roll out a robust civic education to convince the majority of the Kenyan population to embrace vaccination as a major containment measure in curbing the spread of COVID-19 and other infectious diseases since the study revealed that the infections drastically reduced to near zero after vaccination except for a few isolated cases that were and still continue to exhibit mild symptoms to none at all. This was attributed to the development of the vaccine which upon a massive campaign by the Kenyan government, led into a significant portion of the population being vaccinated. It is believed this vaccination drive enhanced herd immunity amongst the population. This development has had a significant effect in the control of more recent COVID-19 variants like JN-1 that have remained largely mild and undetected in the country. Both local and global post vaccination stabilities were analyzed for the system using the Lyapunov function. The main objective of the study was therefore to carry out a post vaccination stability analysis by estimating key parameters such as the basic reproduction number, ( R0) and herd immunity threshold (HIT) for infectious diseases by fitting data into the model to enable predictions of future dynamics of the disease. The study used the Next Generation matrix and the least square method besides the Python software to solve generated differential equations of the model for and HIT parameters. Results obtained showed that, there was a significant reduction in infections due to enhanced herd immunity attributed largely to the roll out of vaccination.

Spatial scales of COVID-19 transmission in Mexico.

During outbreaks of emerging infectious diseases, internationally connected cities often experience large and early outbreaks, while rural regions follow after some delay. This hierarchical structure of disease spread is influenced primarily by the multiscale structure of human mobility. However, during the COVID-19 epidemic, public health responses typically did not take into consideration the explicit spatial structure of human mobility when designing nonpharmaceutical interventions (NPIs). NPIs were applied primarily at national or regional scales. Here, we use weekly anonymized and aggregated human mobility data and spatially highly resolved data on COVID-19 cases at the municipality level in Mexico to investigate how behavioral changes in response to the pandemic have altered the spatial scales of transmission and interventions during its first wave (March-June 2020). We find that the epidemic dynamics in Mexico were initially driven by exports of COVID-19 cases from Mexico State and Mexico City, where early outbreaks occurred. The mobility network shifted after the implementation of interventions in late March 2020, and the mobility network communities became more disjointed while epidemics in these communities became increasingly synchronized. Our results provide dynamic insights into how to use network science and epidemiological modeling to inform the spatial scale at which interventions are most impactful in mitigating the spread of COVID-19 and infectious diseases in general.

Rapid and ecofriendly ultra performance liquid chromatographic analytical methodology for the simultaneous determination of four drugs included in COVID-19 treatment protocol

The global spread of COVID-19 disease has increased the demand for new therapeutic approaches. The clinical studies revealed that remdesivir and molnupiravir have been effective against COVID-19. Remdesivir (REM) is the first FDA-approved antiviral drug for COVID-19, while molnupiravir is the first oral antiviral drug for SARS-CoV-2 infections. In addition to antivirals, anticoagulants such as apixaban (APX) and antibiotics such as levofloxacin (LVF) are also included in the treatment protocols. This study suggests and validates a rapid and selective method for the determination of the four drugs involved in the COVID-19 treatment protocol. The simultaneous separation and determination of REM, MLP, LVF, and APX in human plasma were achieved using UPLC with a fluorophenyl column and a mobile phase composed of acetonitrile and water acidified with formic acid (pH = 3) in the ratio of 45: 55, v/v, at a flow rate of 0.1 mL/min. The PDA detector was adjusted at 254 nm. The method could simultaneously determine the four drugs in a single run in less than 6 min. The method exhibited linearity over the concentration ranges of 1.0–15.0 µg/mL, 0.1–5.0 µg/mL, 0.1–2.0 µg /mL, and 0.1–5.0 µg/mL, for LVF, MLP, APX and REM, respectively. The proposed method was validated following the International Council on Harmonization Q2(R1) guidelines and the findings were compared statistically to previously reported methods. The recovery rates of the drugs from spiked human plasma were satisfactory. The greenness of the suggested method was evaluated using three metrics, namely, Analytical Eco-scale, Green Analytical Procedure Index (GAPI) metric, and the Analytical GREEnness measure approach (AGREE).

Impact of COVID-19 on Manila City Jail: Perspectives of Persons Deprived of Liberty and Jail Officers

This study aimed to assess the implementation of COVID-19 health protocols by the Bureau of Jail Management and Penology (BJMP) at Manila City Jail and to determine the impact of the pandemic on Persons Deprived of Liberty (PDLs) and jail officers in terms of family, psychological, physical, and infrastructure factors. The study involved 50 PDLs and 50 jail officers, and used a quantitative research approach. The findings revealed that the BJMP had strictly implemented COVID-19 health protocols within the jail, such as mandatory mask-wearing, temperature checks, social distancing, and sanitization measures. However, the COVID-19 outbreak still significantly impacted the PDLs and jail officers. In terms of family, the pandemic caused high levels of fear for the safety of family members, affected family relationships, and limited visitation and communication. Psychologically, the respondents experienced high levels of worry about the virus spreading due to overcrowding, and feeling scared of potential COVID-19 symptoms. Regarding physical and infrastructure factors, the jail had insufficient hygiene supplies and poor environmental conditions that increased virus transmission. While there were substantial differences between PDLs and jail officers in their assessments of the pandemic's impact on family, no significant differences were found in their psychological and physical/infrastructure assessments. The study recommends that the BJMP continue implementing strict health protocols, provide peer support networks and counseling services to address mental health, and organize regular sanitization campaigns to mitigate the spread of COVID-19 and other infectious diseases within the jail. Overall, the findings highlight the significant challenges faced by PDLs and jail officers during the pandemic, underscoring the need for comprehensive strategies to protect the health and well-being of these vulnerable groups.

The impact of vaccination and social distancing on COVID-19: A compartmental model and an evolutionary game theory approach

The spread of COVID-19 disease is a worldwide issue that has impacted many countries. Mathematical modeling can help us better understand this disease and predict how different interventions and behavioral changes will affect disease progression. This study presents a compartmental model that corresponds to the COVID-19 trend in some countries. The compartments are: susceptible–exposed–unvaccinated infectious-partially vaccinated infectious–hospitalized–recovered–death–vaccinated (with at least three doses of vaccine). In this model, we have compartments such as individuals who have recovered but may re-infect if they come into contact with infection after completing the post-recovery immunity course, and individuals who have received one or two doses of vaccine are assumed to be partially immune and may infect. Individuals who have received at least three doses of vaccine are considered fully immune and will no longer be infected. The results show this model fits the data from the World Health Organization (WHO) for Finland, Denmark, the Netherlands, the United Kingdom, Italy, and Canada. Furthermore, the basic reproduction number of the proposed model is calculated, and we can compare it to the one released by the WHO to analyze the relative risk of infection based on the amount of investment in social distancing. People in Denmark, according to the study’s findings, invested less in social distancing than people in the other five countries. Finally, we use evolutionary game theory to examine the impact of changing strategy from not-vaccinated to partially vaccinated (with one or two doses of vaccine) in a population that is not fully immune.

Explaining the impact of mutations on quantification of SARS-CoV-2 in wastewater

Wastewater surveillance is an effective tool for monitoring community spread of COVID-19 and other diseases. Quantitative PCR (qPCR) analysis for wastewater surveillance is more susceptible to mutations in target genome regions than binary PCR analysis for clinical surveillance. The SARS-CoV-2 concentrations in wastewater estimated by N1 and N2 qPCR assays started to diverge around July 2022 in data from different sampling sites, analytical methods, and analytical laboratories in Japan. On the basis of clinical genomic surveillance data and experimental data, we demonstrate that the divergence is due to two mutations in the N1 probe region, which can cause underestimation of viral concentrations. We further show that this inaccuracy can be alleviated if the qPCR data are analyzed with the second derivative method or the Cy0 method instead of the crossing point method.

Does urban particulate matter hinder COVID-19 transmission rate?

The COVID-19 pandemic has had a significant impact on global health, with millions of people affected by the disease. Recent studies have shown that environmental factors such as air quality, temperature, and humidity can impact the survival and transmission of the virus, leading to differences in the rate of spread and severity of the disease in different regions. In this global cross-sectional study, we analyzed the relationship between environmental factors and the transmission and survival of the virus in 167 cities distributed all over the world. We used a dataset containing daily COVID-19 data for 167 cities from 01/05/2020 to 01/01/2022, along with variables related to atmospheric and environmental conditions. We found an expected positive relationship between increases in atmospheric NO2 concentration and increases in the infective rate of COVID-19. We also found an unexpected negative relationship between PM10 and COVID-19 spread, which was stronger in unpolluted cities, and indicating a likely stronger and faster deactivation of the viruses by the absorption to the larger than to the smaller particles, to PM10 more than to PM2.5. Although a complete analysis would require taking into account the restrictions in the city and the immunization status of the population, and the variance of COVID-19 spread explained by PM10 was small, only up to approx. 2%, these results contribute to a better understanding of the impact of particles on the spread of COVID-19 and other respiratory viral diseases thus informing public health policies and interventions aimed at mitigating the impact of these pandemics.

Wastewater Surveillance of US Coast Guard Installations and Seagoing Military Vessels to Mitigate the Risk of COVID-19 Outbreaks, March 2021-August 2022.

Military training centers and seagoing vessels are often environments at high risk for the spread of COVID-19 and other contagious diseases, because military trainees and personnel arrive after traveling from many parts of the country and live in congregate settings. We examined whether levels of SARS-CoV-2 genetic material in wastewater correlated with SARS-CoV-2 infections among military personnel living in communal barracks and vessels at US Coast Guard training centers in the United States. The Coast Guard developed and established 3 laboratories with wastewater testing capability at Coast Guard training centers from March 2021 through August 2022. We analyzed wastewater from barracks housing trainees and from 4 Coast Guard vessels for the presence of SARS-CoV-2 genes N and E and quantified the results relative to levels of a fecal indicator virus, pepper mild mottle virus. We compared quantified data with the timing of medically diagnosed COVID-19 infection among (1) military personnel who had presented with symptoms or had been discovered through contact tracing and had medical tests and (2) military personnel who had been discovered through routine surveillance by positive SARS-CoV-2 antigen or polymerase chain reaction test results. Levels of viral genes in wastewater at Coast Guard locations were best correlated with diagnosed COVID-19 cases when wastewater testing was performed twice weekly with passive samplers deployed for the entire week; such testing detected ≥1 COVID-19 case 69.8% of the time and ≥3 cases 88.3% of the time. Wastewater assessment in vessels did not continue because of logistical constraints. Wastewater testing is an effective tool for measuring the presence and patterns of SARS-CoV-2 infections among military populations. Success with wastewater testing for SARS-CoV-2 infections suggests that other diseases may be assessed with similar approaches.

Two-Age-Structured COVID-19 Epidemic Model: Estimation of Virulence Parameters through New Data Incorporation

The COVID-19 epidemic has required countries to implement different containment strategies to limit its spread, like strict or weakened national lockdown rules and the application of age-stratified vaccine prioritization strategies. These interventions have in turn modified the age-dependent patterns of social contacts. In our recent paper, starting from the available age-structured real data at the national level, we identified, for the Italian case, specific virulence parameters for a two-age-structured COVID-19 epidemic compartmental model (under 60, and 60 years and over) in six different diseases transmission scenarios under concurrently adopted feedback interventions. An interpretation of how each external scenario modifies the age-dependent patterns of social contacts and the spread of COVID-19 disease has been accordingly provided. In this paper, which can be viewed as a sequel to the previous one, we mainly apply the same general methodology therein (involving the same dynamic model) to new data covering the three subsequent additional scenarios: (i) a mitigated coordinated intermittent regional action in conjunction with the II vaccination phase; (ii) a super-attenuated coordinated intermittent regional action in conjunction with the II vaccination phase; and (iii) a last step towards normality in conjunction with the start of the III vaccination phase. As a new contribution, we show how meaningful updated information can be drawn out, once the identification of virulence parameters, characterizing the two age groups within the latest three different phases, is successfully carried out. Nevertheless, differently from our previous paper, the global optimization procedure is carried out here with the number of susceptible individuals in each scenario being left free to change, to account for reinfection and immunity due to vaccination. Not only do the slightly different estimates we obtain for the previous scenarios not impact any of the previous considerations (and thus illustrate the robustness of the procedure), but also, and mainly, the new results provide a meaningful picture of the evolution of social behaviors, along with the goodness of strategic interventions.

Visualization of Covid-19 Data in Indonesia in 2022 through the Google Data Studio Dashboard

The COVID-19 pandemic has presented significant challenges to governments, researchers and the general public in understanding and monitoring the spread of this disease. In an effort to analyse the spread of COVID-19 disease in Indonesia effectively, this study uses Google Data Studio as a tool for data visualization and better understanding. This review is based on collecting data on the spread of COVID-19 disease in Indonesia which has been collected from various reliable sources. , including the World Health Organization (WHO) and national health agencies. This data is then processed and processed using Google Data Studio to produce informative visualizations. The results of the study show that Google Data Studio can be used effectively to analyse the spread of the COVID-19 disease in Indonesia. Through the use of available features, such as interactive graphs, maps, and tables, researchers can easily describe patterns of disease spread, infection rates, and recovery rates from an area or country. The quality of data collected from different sources may vary, and this can affect the accuracy and reliability of the resulting visualizations. Elements of the Scorecard that displays some important information related to the Covid-19 pandemic from 1 January 2019 to 31 January 2022. Information regarding the Covid-19 displayed on the Scorecard is as follows. The total survivors of the Covid-19 disease are 3,234,336,858 people. This indicates the number of people who have successfully recovered and recovered from infection with the Covid-19 virus during the period in question. The total number of deaths due to Covid-19 is 89,398,496 people. This reflects the number of people who died due to complications caused by the Covid-19 virus in that period.

Stochastic SIR Epidemiological Model With Two Levels of Severity

In this paper, we develop an epidemic model to analyze the spread of an infectious disease with two levels of severity within a population of varying size. Additionally, we examine the stability of the disease-free equilibrium.
 Such a model is suitable for the dynamics of COVID-19 disease spread. If the two types of infected individuals have different recovery rates, then there is no endemic equilibrium; only the disease-free equilibrium will be the subject of our study. We then study both the deterministic model and a stochastic version. The stochastic model is obtained by perturbing the contact rate using white noise. For the deterministic model, we have shown that if the basic reproduction number R_0 < 1, then the equilibrium state is globally asymptotically stable by using Lyapunov function. This implies that the disease will disappear, and the entire population will become susceptible. For the stochastic version, we demonstrate that the system admits a unique positive global solution that exists within a positively invariant domain. Under suitable conditions on the intensity of the white noise perturbations, we prove that the number of infectious individuals converge almost surely exponentially to zero and the disease-free equilibrium of system is stochastically asymptotically stable in the large provided. Finally, we give some numerical simulations to illustrate our theoretical results.

Governance Policy Evaluation in the United States during the Pandemic: Nonpharmaceutical Interventions or Else?

Scientific evidence suggests that nonpharmaceutical interventions (NPIs) effectively curb the spread of COVID-19 before a pharmaceutical solution. Implementing these interventions also significantly affects regular socioeconomic activities and practices of social, racial, and political justice. Local governments often face conflicting goals during policymaking. Striking a balance among competing goals during a global pandemic is a fine science of governance. How well state governments consume the scientific evidence and maintain such a balance remains less understood. This study employs a set of Bayesian hierarchical models to evaluate how state governments in the United States use scientific evidence to balance the fighting against the spread of COVID-19 disease and socioeconomic, racial, social justice, and other demands. We modeled the relationships between five NPI strategies and COVID-19 caseload information and used the modeled result to perform a balanced governance evaluation. The results suggest that governmental attitude and guidance effectively guide the public to fight back against a global pandemic. The more detailed spatiotemporally varying coefficient process model produces 612,000 spatiotemporally varying coefficients, suggesting all measures sometimes work somewhere. Summarized results indicate that states emphasizing NPIs fared well in curbing the spread of COVID-19. With over 1 million deaths due to COVID-19 in the United States, we feel the balance scale likely needs to tip toward preserving human lives. Our evaluation of governance policies is hence based on such an argument. This study aims to provide decision support for policymaking during a national emergency.

Examining the Role of Social Determinants of Health and COVID-19 Risk in 28 African Countries

While the impact of the pandemic has varied between and within countries, there are few published data on the relationship between social determinants of health (SDoH) and COVID-19 in Africa. This ecological cross-sectional study examines the relationship between COVID-19 risk and SDoH among 28 African countries. Included were countries with a recent demographic and health survey (years 2010 to 2018). The response variables were COVID-19 case rates and death rates (reported as of 15 August 2020); and the covariates comprised eight broad topics common to multiple SDoH frameworks aggregated to the country level: geography (urban residence), wealth index, education, employment, crowding, and access to information. A negative binomial regression was used to assess the association between aspects of SDoH and COVID-19 outcomes. Our analysis indicated that 1 in 4 (25.1%) households in study countries are without safe and clean water and a space for handwashing. The odds of COVID-19 morbidity and deaths were higher in countries with a high proportion of households without access to safe and clean water. Having a high proportional of educated women (1.003: 95% CI, 1.001–1.005) and living in a less crowded home (0.959: 95% CI, 0.920–1.000) were negatively associated with COVID-19 deaths, while being insured and owning a mobile phone predicted illness. Overall, aspects of SDoH contribute either negatively or positively to COVID-19 outcomes. Thus, addressing economic and environmental SDoH is critical for mitigating the spread of COVID-19 and re-emerging diseases on the African continent.

Analyzing Safe Epidemic Distancing in Public Transport Buses: A Simulation Study on Passenger Flow

During the COVID-19 pandemic, public transport played a crucial role in maintaining essential services while ensuring the safety of both passengers and staff. As the world gradually resumes operations, the impact of the pandemic is expected to persist for some time. Existing studies focus on virus transmission in vehicles, with limited knowledge about post-pandemic passenger flow, safety, and satisfaction. This paper presents a model of passenger movement in public transport, considering factors like boarding times, movement within stops, and the impact of crowding and delays. To reduce transmission at bus stops, we developed a simulation-based passenger flow model using PTV Vissim. The program was used to simulate passenger exchange scenarios, using data collected from real data. The goal was to create a model that minimizes the risk of infection. By understanding passenger flow and interactions with the public transport system, effective measures can be implemented to mitigate the spread of COVID-19 and other infectious diseases.

Severity and Clinical Outcome of COVID-19 Patients Admitted at a Provincial Infectious and Communicable Disease Hospital of Nepal: A Cross-Sectional Study

Background: This study provides information regarding severity and clinical outcome of people admitted with the diagnosis of COVID-19 infection during the global pandemic at a provincial infectious disease hospital in Gandaki Province in Nepal. The evidence from this study will be helpful to compare the clinical outcome of people admitted with COVID-19 during the outbreak. Methods: Cross-sectional study was conducted from March 2023 to August 2023 after approval from NHRC (ref. no. 1448) with sample size of 1366 at the hospital. Structured questionnaire was used to collect secondary data (electronic and paper records) retrospectively from hospital records with a diagnosis of COVID-19 infection. Total enumeration technique was used with enlisting of all cases of COVID-19 to the hospital. The collected data was analyzed using SPSS version 11.5. Results: The hospital admitted the highest number of cases between April to September 2021. Among the 1366 admitted cases, 791 (57.91%) were males and 575 (42.09%) were females, the most common age group affected was 31 to 40 years (22.99%); 1092 (79.94%) were from Kaski district. As per disease severity, 884 (64.71%) were moderate cases followed by 391 (28.62%) mild cases and 91 (6.67%) severe cases. A total of 1205 (88.21%) patients were discharged, 105(7.69%) patients were referred and 56 (4.10%) patients died of COVID -19.Conclusions: Almost 3/4th of the admitted cases came from same district, majority had moderate disease and the hospital cure rate was almost 8/9th. As the majority of cases are from active age group (21 years to 60 years old), public health measures can be targeted to these groups including surrounding population to stop transmission and spread of COVID-19 or similar infectious diseases. The information from this study can guide for the preparation and planning of in-patient and isolation departments of similar other provincial infectious disease hospitals.

The impact of Covid-19 on mortality and clinical characteristics in hospitalized patients with peripheral artery disease in the year 2020

Abstract Background The Covid-19 pandemic developed its full destructive capacity and caused over 6.6 million confirmed deaths worldwide in the year 2020. This retrospective study aimed to examine the effects of Covid-19 on the mortality and clinical characteristics of peripheral artery disease (PAD) patients because these chronically ill patients are at risk for arterial embolic vascular complications and a fatal outcome. Methods and results From a German nationwide registry of 2020 all patients hospitalized with PAD (n=173.075) were compared in four different groups. The first group had no additional diabetes mellitus type 2 or Covid-19 (n=110.531), the second diabetes mellitus but no Covid-19 (n=59.991), the third diabetes mellitus and Covid-19 (n=1497) and the fourth no diabetes mellitus but Covid-19 (n=1056). Mortality rates in all PAD patients without Covid-19 were low and ranging between 1.1-3.6%, depending on PAD classification. However, PAD patients with Covid-19 had significantly higher mortality rates of 11.1-12.6%. Clinical characteristics and the Charlson- comorbidity index surprisingly revealed that PAD patients with Covid-19 but without diabetes mellitus presented more complications such as higher rates of stroke (1.4%), cardiogenic shock (3.3%), chronic kidney failure with GFR < 15 ml/min (10.5%) and prolonged ventilation time >48 hours (4.4%). Conclusion Covid-19 massively increased death rates in PAD patients in the year 2020. Neither disease severity of different stages of PAD nor additional diabetes mellitus had an effect on in-hospital mortality. One explanation of this finding might be that the risk for arterial embolism increases after a Covid-19 infection and thus leads to higher mortality rates in PAD patients, who are in danger for vascular/embolic complications. Our study reveals the importance of preventing the spread of Covid-19 disease, especially in the case of patients with atherosclerotic diseases.