Epidemiological Characteristics Of COVID-19 Research Articles

Clinical and Epidemiological Characteristics of COVID-19 in Persons Living with HIV Complicated by Tuberculosis

Relevance. At present, three infections – HIV infection, tuberculosis, and COVID-19 - are spreading simultaneously in the world. Of great practical importance is the assessment of clinical and epidemiological features of COVID-19 in HIV-infected patients with tuberculosis, COVID-19. Aim. To study the risk of COVID-19 disease and identify clinical and epidemiological features in and population of patients with HIV infection complicated by tuberculosis in comparison with patients with HIV infection and the population without these diseases.Materials and methods. Since 13.03.2020 by 31.12.2021 in the Kemerovo Region-Kuzbass, a continuous prospective analytical epidemiological study of the case-control type was performed. Of those with COVID-19, two observation groups were formed: group I (HIV +), group II (HIV/TB) and comparison group III (persons without either HIV or tuberculosis). All patients underwent: determination of SARS-CoV-2 RNA, standard examination methods in accordance with the temporary methodological recommendations «Prevention, diagnosis and treatment of a new coronavirus infection (COVID-19)», relevant at the time of treatment.Results. The incidence of COVID-19 among patients with HIV infection complicated by tuberculosis exceeded the incidence of COVID-19 among HIV-infected by 14%. There were no gender differences between patients I (HIV +) and II (HIV/TB) groups. In the comparison group, the incidence of COVID-19 was 1.26 times higher in women compared to men. COVID-19 disease in patients with co-infection (HIV/TB) was predominantly mild. Viral pneumonia developed 1.86 times less often, oxygenotherapy was required only in 18.75% of cases, which is 2.5 times lower than in group I (HIV +) and 2.47 times less than in the comparison group (III). In labeled pairs, clinical symptoms of COVID-19 in all groups occurred with the same frequency. Metabolic disorders were evident in all groups. Co-infected patients (HIV/TB) had higher levels of D-dimer, ESR, total bilirubin.Conclusion. Active tuberculosis in HIV-infected people is a factor that increases the risk of COVID-19 disease without affecting the severity of the infectious process.

Application of Autoregressive Moving Average Model in the Prediction of COVID-19 of China

Objective: To establish ARIMA model through time series analysis to understand the occurrence law of newly confirmed cases of novel coronavirus pneumonia and provide references for taking epidemic prevention and control measures.
 Methods: The cumulative confirmed and cured cases of COVID-19 are collected through the official website of the National Health Commission, and the number of newly confirmed and cured cases per week are sorted out. We analyze the time series of newly diagnosed and cured COVID-19 cases every week from April 12, 2020 to December 5, 2021 by IBM SPSS 25.0 software. The model is established through model identification, parameter estimation and model fitting.
 Results: The number of reported cases of COVID-19 has no obvious seasonal characteristics. The ARIMA(2,1,1) model well fitted the time series, R2 = 0.542/0.617. Through the residual white noise test, all parameters of the model have statistical significance, Ljung box q = 9.095/9.651, P > 0.05. We predict the cases and cures in the four weeks after December 5, 2021 by ARIMA(2,1,1). The measured values in the first week and the second week are within the predicted 95% CI range.
 Discussion and Conclusion: The epidemiological characteristics of COVID-19 need a longer time series for validation and analysis. ARIMA model can predict the incidence of COVID-19 in a short term, and the model should be constantly revised according to the actual situation.

Optimal vaccination strategies using a distributed model applied to COVID-19

Optimal distribution of vaccines to achieve high population immunity levels is a desirable aim in infectious disease epidemiology. A distributed optimal control epidemiological model that accounts for vaccination was developed and applied to the case of the COVID-19 pandemic. The model proposed here is nonstandard and takes into account the heterogeneity of the infected sub-population with respect to the time since infection, which is essential in the case of COVID-19. Based on the epidemiological characteristics of COVID-19 we analyze several vaccination scenarios and an optimal vaccination policy. In particular we consider random vaccination over the whole population and the prioritization of age groups such as the elderly and compare the effects with the optimal solution. Numerical results of the model show that random vaccination is efficient in reducing the overall number of infected individuals. Prioritization of the elderly leads to lower mortality though. The optimal strategy in terms of total deaths is early prioritization of those groups having the highest contact rates.

First Few Cases Study to Investigate Clinical and Epidemiological Characteristics of COVID-19 in the Early Phase of the Response, Sierra Leone 2020

Sierra Leone reported its first case of COVID-19 on March 30, 2020. This report describes the clinical characteristics and the epidemiological features of the first few cases and contacts of COVID-19 in Sierra Leone.

The COVID-19 Pandemic in South Asia: A Comprehensive Review of the Genomic Variations, Epidemiological Features, Diagnosis, Treatment and Preventive Schemes

Background: The purpose of the study was to outline the genomic and epidemiological characteristics of COVID-19 in South Asian countries as well as the diagnosis, treatments, and prevention approaches undertaken by these countries to tackle the COVID-19 pandemic.

One year of COVID-19 pandemic: Epidemiological characteristics of COVID-19 in the city of Uberaba, Minas Gerais, Brazil

One year of COVID-19 pandemic: Epidemiological characteristics of COVID-19 in the city of Uberaba, Minas Gerais, Brazil

Prevalence and epidemiological characteristics of COVID-19 after one year of pandemic in Jakarta and neighbouring areas, Indonesia: A single center study.

We determined the prevalence and epidemiological characteristics of COVID-19 in Jakarta and neighboring areas, Indonesia from March 2020 to February 2021, based on nasopharyngeal/oropharyngeal (NP/OP) swab specimens that were tested at the Eijkman Institute for Molecular Biology, Jakarta. NP/OP swab specimens were collected from COVID-19 suspects or individuals in contact tracing programs from primary healthcare centers (PHC) and hospitals. The specimens were screened for the SARS-CoV-2 by qRT-PCR. Demography data and clinical symptoms were collected using national standardized laboratory form. Of 64,364 specimens, 10,130 (15.7%) were confirmed positive for SARS-CoV-2, with the peak prevalence of infection in March 2020 (26.3%) follow by in January 2021 (23.9%) and February 2021 (21.8%). We found that the positivity rate of the specimens from Jakarta, West Java, and Banten was 16.3%, 13.3%, and 16.8%, respectively. Positivity rate was higher in specimens from hospitals (16.9%) than PHC (9.4%). Of the positive specimens, 29.6% were from individuals aged >60 years old, followed by individuals aged 41-60 years old (24.2%). Among symptomatic cases of SARS-CoV-2, the most common symptoms were cough, fever, and a combination of both cough & fever. In conclusion, this study illustrates the prevalence and epidemiological characteristics from one COVID-19 diagnostic center in Jakarta and neighbouring areas in Indonesia.

COVID-19 and the Beat-To-Beat Heart

Introduction Since December 2019, the coronavirus disease (COVID-19) has caused an exponential increase in acute respiratory syndrome cases and has rapidly spread to more than 210 regions, countries and territories, resulting in considerable morbidity and mortality in more than 100 countries worldwide. Over this period, several studies describing the clinical and epidemiological characteristics of COVID-19 have been published, allowing rapid dissemination of knowledge and helping health care professionals and policy makers to help patients with the disease. […] COVID-19 and [...]

Epidemiological Characteristics of COVID-19 among the Individuals from Nasik District, Maharashtra

Background: Coronavirus Disease 2019 (COVID 19) pandemic has created havoc around the world. All states of India, including Maharashtra, are severely affected by this viral infection. In Maharashtra, various regions including Mumbai, Pune and Nasik are largely affected due to this pandemic. Objectives: To study the epidemiological characteristic of COVID-19 Individuals from the Nasik district. Materials and Methods: A cross-sectional e-survey was conducted to study the epidemiological characteristics of COVID-19 individuals from and around Nasik. A random sampling method was adopted. Information from the individuals was collected in the form of a questionnaire, which was shared among 300 individuals, out of these 253 responses were received. Data analysis was done using Chi-square method. Results: Of 253 individuals, 90 (35.57%) were found to be COVID positive. Majority (50%) of them belonged to the age group 40–60 years. Among those tested positive, 83 (92.2%) individuals were symptomatic while, 7 (7.8%) were asymptomatic. Of 90 COVID positive individuals, 39 (43.3%) individuals with pre-COVID comorbidities showed severe symptoms and were hospitalized, while those without any comorbidity showed mild symptoms and were home quarantined, (Odds ratio = 15.88,95% confidence interval = 5.6–44.95, P < 0.0001). Post COVID symptoms, particularly diabetes and Mucormycosis, were developed among 8.8% and 1.1% individuals, respectively. Conclusion: Severity of illness was associated with comorbidity, among majority of the patients.

The Positive Rate of Nucleic Acid Testing and the Epidemiological Characteristics of COVID-19 in Chongqing.

ObjectiveThe purpose of this study is to analyze the positive rate of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid testing (NAT), cases of and deaths due to SARS-CoV-2, and the epidemiological characteristics of SARS-CoV-2 to identify high-risk populations.MethodsA retrospective study in Jiulongpo district of Chongqing was conducted by performing continuous observations of the frequency of SARS-CoV-2 NAT, analyzing the data of close contacts of patients and asymptomatic carriers, and collecting epidemiological data. Data were collected from January 20, 2020, when the first case of SARS-CoV-2 infection was reported, to March 26, 2020. Descriptive statistical analysis and Cochrane–Mantel–Haenszel analysis were used to compare the positive detection rates and positive diagnostic rates of different exposure groups.ResultsA total of 7,118 people received 10,377 SARS-CoV-2 nucleic acid tests in one district, and the SARS-CoV-2 positive rates were 0.40% (18/4446) and 0.15% (4/2672) in people receiving one and ≥ two nucleic acid tests (p = 0.06), respectively. Those with suspected cases (12.35%) and close contacts (8%) had higher positive rates than people tested at fever clinics (0.39%) (p < 0.001). The median latency (range) of cases was 5 (2, 9) days, and the median time from diagnosis to recovery was 22 (14, 25) days. One recovered patient received a positive test result at 28 days after recovery when she attempted to donate blood. Six clustered cases, including one patient who died, indicated persistent human-to-human transmission. One patient who was diagnosed after death was found to have infected 13 close contacts. People working in catering and other public service departments (36.36%) and people who are unemployed and retirees (45.45%) have an increased risk of infection compared with technical staff (9.09%) and farmers (9.09%).ConclusionThe total positive rate was low in the tested population, and more effective detection ranges should be defined to improve precise and differentiated epidemic control strategies. Moreover, in asymptomatic carriers, SARS-CoV-2 tests were positive after recovery, and patients with suspected SARS-CoV-2 infection who die may pose serious potential transmission threats.

SARS-CoV-2 infections in pediatric patients: A comparison of three pandemic waves.

The pediatric population seems to be at a lower risk of developing severe clinical symptoms of COVID‐19. However, the clinical and epidemiological characteristics of COVID‐19 in children are yet to be fully clarified. This retrospective observational study aimed to evaluate the frequency of pediatric laboratory‐confirmed COVID‐19 patients from February 2020 to April 2021. A total of 740 (5.1% of total) pediatric COVID‐19 cases were observed during the study period. The peak of pediatric cases was observed in November 2020, with 239 cases. During the first wave of pandemics, the frequency of pediatric cases was 0.89% (49/5877 cases), ranging from 0.6% in February 2020 to 1.3% in April 2020. On the contrary, after the beginning of the second wave, the frequency of pediatric cases raised from 5.3% in September 2020 to 9.4%in February 2021, with an overall frequency of 8.2% (690/8416 cases). A different rate of SARS‐CoV‐2 circulation was observed among the pediatric population between the pandemic waves. During the second wave, two peaks of cases were observed. The last peak was associated with the spread of a more transmissive SARS‐CoV‐2 strain (VOC 202012/01).

Clinical and epidemiological characteristics of COVID-19 in children: experience in two hospitals.

The COVID-19 pandemic is the most significant current public health crisis. We conducted a retrospective case series, including patients under 18 years of age admitted to respiratory triage and hospitalized with COVID-19 infection in two hospital centers. Epidemiological, clinical, laboratory and radiological findings were documented. The diagnosis of COVID-19 was confirmed by real-time reverse transcription-polymerase chain reaction (RT-PCR). For the analysis, patients were classified into three groups: no comorbidities, immunocompromised, and with chronic disease. Fifty-four patients with COVID-19 were identified: 40 (74.1%) were admitted through respiratory triage. Of these, 28 (70%) were hospitalized, and 14 (25.9%) were already in the hospital. In addition, 26 (48.1%) presented comorbidities. A mild clinical course was observed in 14 cases (53.7%). The mean age was 6 years, with an interquartile range from 11 months to 13 years. The male sex was more frequent, representing 59.3%. Fever was the most common symptom in 74% of the patients. Lymphopenia was observed in 28.6%, and 69.3% had elevated C-reactive protein. Ground glass injuries were documented in 30.9% of COVID-19 cases; 11.1% of the patients required mechanical ventilation and vasopressor treatment. Fever was the main symptom, and mild infection was the principal presentation. In hospitalized patients with some comorbidity and COVID-19, the disease was more severe, with a high percentage of mortality.

Variation of Genomic Sites Associated with Severe Covid-19 Across Populations: Global and National Patterns.

BackgroundInformation about the distribution of clinically significant genetic markers in different populations may be helpful in elaborating personalized approaches to the clinical management of COVID-19 in the absence of consensus guidelines.AimAnalyze frequencies and distribution patterns of two markers associated with severe COVID-19 (rs11385942 and rs657152) and look for potential correlations between these markers and deaths from COVID-19 among populations in Russia and across the world.MethodsWe genotyped 1883 samples from 91 ethnic groups pooled into 28 populations representing Russia and its neighbor states. We also compiled a dataset on 32 populations from other regions using genotypes extracted or imputed from the available databases. Geographic maps showing the frequency distribution of the analyzed markers were constructed using the obtained data.ResultsThe cartographic analysis revealed that rs11385942 distribution follows the West Eurasian pattern: the marker is frequent among the populations of Europe, West Asia and South Asia but rare or absent in all other parts of the globe. Notably, the transition from high to low rs11385942 frequencies across Eurasia is not abrupt but follows the clinal variation pattern instead. The distribution of rs657152 is more homogeneous. The analysis of correlations between the frequencies of the studied markers and the epidemiological characteristics of COVID-19 in a population revealed that higher frequencies of both risk alleles correlated positively with mortality from this disease. For rs657152, the correlation was especially strong (r = 0.59, p = 0.02). These reasonable correlations were observed for the “Russian” dataset only: no such correlations were established for the “world” dataset. This could be attributed to the differences in methodology used to collect COVID-19 statistics in different countries.ConclusionOur findings suggest that genetic differences between populations make a small yet tangible contribution to the heterogeneity of the pandemic worldwide.

Role of Asymptomatic COVID-19 Cases in Viral Transmission: Findings From a Hierarchical Community Contact Network Model.

As part of ongoing efforts to contain the coronavirus disease (COVID-19) pandemic, understanding the role of asymptomatic patients in the transmission system is essential for infection control. However, the optimal approach to risk assessment and management of asymptomatic cases remains unclear. This study proposed a Susceptible, Exposed, Infectious, No symptoms, Hospitalized and reported, Recovered, Death (SEINRHD) epidemic propagation model. The model was constructed based on epidemiological characteristics of COVID-19 in China and accounting for the heterogeneity of social contact networks. The early community outbreaks in Wuhan were reconstructed and fitted with the actual data. We used this model to assess epidemic control measures for asymptomatic cases in three dimensions. The impact of asymptomatic cases on epidemic propagation was examined based on the effective reproduction number, abnormally high transmission events, and type and structure of transmission. Management of asymptomatic cases can help flatten the infection curve. Tracing 75% of the asymptomatic cases corresponds to a 32.5% overall reduction in new cases (compared with tracing no asymptomatic cases). Regardless of population-wide measures, household transmission is higher than other types of transmission, accounting for an estimated 50% of all cases. The magnitude of tracing of asymptomatic cases is more important than the timing; when all symptomatic patients were traced, tested, and isolated in a timely manner, the overall epidemic was not sensitive to the time of implementing the measures to trace asymptomatic patients. Disease control and prevention within families should be emphasized during an epidemic. Note to Practitioners—This article addresses the urgent need to assess the risk of another COVID-19 outbreak caused by asymptomatic cases and to find the optimal, most practical approach to asymptomatic case management. Previous studies mostly focused on the clinical and statistical characteristics of asymptomatic cases; few have evaluated the impact of asymptomatic case measures using mathematical modeling at the community scale. This study proposed a Susceptible, Exposed, Infectious, No symptoms, Hospitalized and reported, Recovered, Death (SEINRHD) propagation model based on local community structures and social contact networks, according to the development characteristics and trend of COVID-19 in a Chinese community. The conclusion provides theoretical support for emergency work of relevant departments in different periods of an epidemic. In the early stages of the epidemic, timely detection and isolation of symptomatic patients should be a priority. Where there are surplus resources for epidemic prevention, the authorities should consider increasing the proportion of asymptomatic patients being traced. Epidemic prevention measures among family members should be a primary focus of attention. This combination of strategies can help reduce the rate of viral transmission and result in extinguishing the epidemic.

The Epidemiological and Spatiotemporal Characteristics of the 2019 Novel Coronavirus Disease (COVID-19) in Libya.

COVID-19 is a global pandemic that has affected all aspects of life. Understanding its geographical and epidemiological characteristics has become particularly important in controlling the spread of the pandemic. Such studies are lacking in North African countries, particularly in Libya, which has the second largest area of any country in Africa and the longest coast facing Europe. The objectives of this study are to determine the epidemiological parameters and spatiotemporal patterns of COVID-19 and outline strategies for containing the spread and consequences of the pandemic. This comprehensive study included all the confirmed cases of COVID-19 since its emergence in Libya on March 24, 2020 until July 31, 2020. The epidemiological characteristics of COVID-19 were analyzed and the spatial dynamic trends were explored. Regional counts of weekly reported cases were used to characterize the spatial dynamics of COVID-19. A total of 3,695 confirmed cases of COVID-19 were recorded: 2,515 men (68.1%) and 1,180 women (31.9%), with a male-to-female ratio of 2.1:1. Ages ranged between 2 and 78 years. Older patients infected with COVID-19 were at a risk of higher disease severity and mortality. Broad geographic variability and spatiotemporal spread variation of the COVID-19 pandemic in Libya was observed, indicating a significant increase of COVID-19 spread starting in the middle of July 2020, particularly in the western and southern regions, although it was consistently reported in the central and eastern regions as well. Assessing the spatiotemporal dynamics of COVID-19 in the early stages of the epidemic is particularly important in understanding the pandemic spread. Such assessments are essential for designing effective prevention and control programs aimed at reducing the impact of the COVID- 19 pandemic, particularly in countries with limited resources.

Clinical and epidemiological characteristics of COVID-19 during the early phase of the SARS-CoV-2 pandemic: a cross-sectional study among medical school physicians and residents employed in a regional reference teaching hospital in Northern Italy.

The aim of the study was to evaluate the clinical presentation and burden of SARS-CoV-2 infections among medical school physicians and residents, mainly young medical doctors. The awareness of COVID‑19 clinical manifestations can improve the early detection of mild cases, possibly reducing further transmission to colleagues and patients. The study was carried out in March-May 2020, involving medical school physicians in a teaching hospital in northern Italy, with a working population of 881 medical doctors. Data collection was performed using a structured form investigating clinical and epidemiological information. One hundred sixty-two medical doctors contacted the Occupational Health Service reporting acute respiratory symptoms or close contact exposure to a confirmed COVID‑19 case. Among the confirmed COVID‑19 cases, most were male doctors during residency, and 85% presented a mild clinical picture. Fever (70.3%) and cough (51.4%) represented the most prevalent symptoms of COVID‑19. As revealed by the univariate analysis, the prevalence of real-time reverse transcriptase-polymerase chain reaction (RT-PCR) positivity increased with age (OR = 1.08, 95% CI: 1.02-1.14, p = 0.012), working in a COVID‑19 ward (OR = 3.33, 95% CI: 1.09-10.21, p = 0.031), presenting alteration or loss of smell/taste (OR = 10.00, 95%CI: 2.80-35.69, p < 0.001) and myalgia (OR = 3.20, 95% CI: 1.00-10.26, p = 0.046), while being a resident (OR = 0.20, 95% CI: 0.05-0.80, p = 0.030) was associated with reduced odds of being infected, compared to staff physicians. Age and loss of smell/taste were the only factors independently associated with RT-PCR positivity. The majority of COVID‑19 cases showed a mild clinical syndrome, ranging from absence or paucity of symptoms to common cold or influenza-like symptoms. The findings of the present study increase the accuracy of the clinical diagnosis for the prompt identification and management of suspected COVID‑19 cases, being particularly useful during resurges of the SARS-CoV-2 pandemic. Int J Occup Med Environ Health. 2021;34(2):189-201.

Clinical and Epidemiological Characteristics of COVID-19 in Mayan Pregnant Women of Yucatan, Mexico

In December 2019, the transmission of a new coronavirus called SARS-CoV-2 began in Wuhan, China and caused the COVID-19 disease; spreading rapidly to the world and producing the pandemic that is active until now.

Graph modelling for tracking the COVID-19 pandemic spread

The modelling is widely used in determining the best strategies for the mitigation of the impact of infectious diseases. Currently, the modelling of a complex system such as the spread of COVID-19 infection is among the topical issues. The aim of this article is graph-based modelling of the COVID-19 infection spread. The article investigates the studies related to the modelling of COVID-19 pandemic and analyses the factors affecting the spread of the disease and its main characteristics. We propose a conceptual model of COVID-19 epidemic by considering the social distance, the duration of contact with an infected person and their location-based demographic characteristics. Based on the hypothetical scenario of the spread of the virus, a graph model of the process are developed starting from the first confirmed infection case to human-to-human transmission of the virus and visualized by considering the epidemiological characteristics of COVID-19. The application of graph for the pandemic modelling allows for considering multiple factors affecting the epidemiological process and conducting numerical experiments. The advantage of this approach is justified with the fact that it enables the reverse analysis the spread as a result of the dynamic record of detected cases of the infection in the model. This approach allows for to determining undetected cases of infection based on the social distance and duration of contact and eliminating the uncertainty significantly. Note that social, economic, demographic factors, the population density, mental values and etc. affect the increase in number of cases of infection and hence, the research was not able to consider all factors. In future research will analyze multiple factors impacting the number of infections and their use in the models will be considered.

Graph modelling for tracking the COVID-19 pandemic spread

The modelling is widely used in determining the best strategies for the mitigation of the impact of infectious diseases. Currently, the modelling of a complex system such as the spread of COVID-19 infection is among the topical issues. The aim of this article is graph-based modelling of the COVID-19 infection spread. The article investigates the studies related to the modelling of COVID-19 pandemic and analyses the factors affecting the spread of the disease and its main characteristics. We propose a conceptual model of COVID-19 epidemic by considering the social distance, the duration of contact with an infected person and their location-based demographic characteristics. Based on the hypothetical scenario of the spread of the virus, a graph model of the process are developed starting from the first confirmed infection case to human-to-human transmission of the virus and visualized by considering the epidemiological characteristics of COVID-19. The application of graph for the pandemic modelling allows for considering multiple factors affecting the epidemiological process and conducting numerical experiments. The advantage of this approach is justified with the fact that it enables the reverse analysis the spread as a result of the dynamic record of detected cases of the infection in the model. This approach allows for to determining undetected cases of infection based on the social distance and duration of contact and eliminating the uncertainty significantly. Note that social, economic, demographic factors, the population density, mental values and etc. affect the increase in number of cases of infection and hence, the research was not able to consider all factors. In future research will analyze multiple factors impacting the number of infections and their use in the models will be considered.

An Evidence Base for School Health Policy during the COVID-19 Pandemic

Objective: Children represent a small fraction of confirmed COVID-19 cases, with a low case fatality rate (CFR). In this paper, we lay out an evidence-based policy for reopening schools. Methods: We gathered age-specific COVID-19 case counts and identified mortality data for 14 countries. Dose-response meta-analysis was used to examine the relationship of the incremental case fatality rate (CFR) to age. In addition, an evidence-to-decision framework (EtD) was used to correlate the dose-response data with other epidemiological characteristics of COVID-19 in childhood. Results: In the dose-response analysis, we found that there was an almost negligible fatality below age 18. CFR rose little between ages 5 to 50 years. The confidence intervals were narrow, suggesting relative homogeneity across countries. Further data suggested decreased childhood transmission from respiratory droplets and a low viral load among children. Conclusions: Opening up schools and kindergartens is unlikely to impact COVID-19 case or mortality rates in both the child and adult populations. We outline a robust plan for schools that recommends that general principles not be micromanaged, with authority left to schools and monitored by public health authorities.