Epidemiological analysis of fractional order COVID-19 model with Mittag-Leffler kernel

<abstract> <p>This paper derived fractional derivatives with Atangana-Baleanu, Atangana-Toufik scheme and fractal fractional Atangana-Baleanu sense for the COVID-19 model. These are advanced techniques that provide effective results to analyze the COVID-19 outbreak. Fixed point theory is used to derive the existence and uniqueness of the fractional-order model COVID-19 model. We also proved the property of boundedness and positivity for the fractional-order model. The Atangana-Baleanu technique and Fractal fractional operator are used with the Sumudu transform to find reliable results for fractional order COVID-19 Model. The generalized Mittag-Leffler law is also used to construct the solution with the different fractional operators. Numerical simulations are performed for the developed scheme in the range of fractional order values to explain the effects of COVID-19 at different fractional values and justify the theoretical outcomes, which will be helpful to understand the outbreak of COVID-19 and for control strategies.</p> </abstract>

Spatial and epidemiological analysis of Covid-19 in Ardabil province,North West of Iran

Background: Coronavirus disease highly contagious, is prevalent in all age and sex groups infecting the respiratory system. The aim of this study are spatial analysis and geographical distribution of Covid-19 in different time periods in Ardabil province. Methods: In this cross-sectional study, official statistics recorded in the health centers of Counties and hospitals of Ardabil province were used from 20/03/2020 to 20/03/2021. For data analysis was used to Chi-square to investigate the relationship between disease peaks. In order to perform spatial analysis, were used to ArcGIS10.4.8 software and IDW interpolation analysis and Moran index was used to determine the pattern of disease spread in the study area. Results: The duration of the three peaks in Ardabil province was about 10 months and 11,761 people were referred to hospitals. The longest peak was the third peak, which lasted 72 days. Bilehsavar County with the highest incidence of 1334 and Kowsar County with 226/100000 has the lowest incidence of the disease. Covid-19 distribution pattern based on Moran's index shows that the incidence of disease in high-risk areas in all three peaks was significantly clustered (P <0.05) Conclusions: Covid-19 process during the three peaks in Ardabil province has been increasing in terms of incidence and duration of the peak. Take action in all Counties and to implement health protocols.

Comparison of Radiation Risk of Cancer Incidence among PA Mayak Workers Hired at Different Calendar Periods

Purpose: comparative epidemiological analysis of cancer incidence rates among PA Mayak workers hired at different calendar periods. Material and Methods: The cohort of PA Mayak workers hired at reactors, radiochemical, plutonium, water preparing and repair plants in 1948-1982 was selected for analysis of solid cancer (except lung, liver and bone) incidence. The cohort was divided into two subcohorts 1948-1958 and 1959-1982 years of hire. Regression models of relative risk included the description of background rates and excess radiation risk was used. Results: The radiation relative risk per 1 Gy was (ERR/Gy: 0.11; 95 % CI: 0.02; 0.21) in the subcohort of workers hired in 1948–1958 and was close to the estimates from previous studies for the whole cohort. In the subcohort of workers hired in 1959–1982 the point estimate of ERR/Gy was 3 times higher than in the subcohort 1948–1958 years of hire, but it was not statistically significant in the whole dose range. Restriction of doses up to 2 Gy allowed to get significant estimate of ERR/Gy (0.45; 95 % CI: 0.04; 0.95), which 4 times higher the estimate in the first subcohort calculated with the same restriction (0.11; 95 % CI: -0.01; 0.25). All subcohorts differences were not statistically significant and we can say about point distinctions only.

Epidemiological analysis of hospitalized cases of COVID-19 in in-digenous people in an Amazonian region: cross-sectional study with data from the surveillance of acute and severe respiratory syn-dromes in Brazil

Indigenous people are considered more vulnerable to new infectious agents. In view of the novel coronavirus causing COVID-19, health authorities are concerned about the possible impact of the pandemic on reaching vulnerable populations, such as the in-digenous people of the Brazilian Amazon. Thus, we aimed to carry out an epidemiological analysis of serious cases and deaths from COVID-19 in indigenous population in the state of Para, Brazil. The data was obtained from the public Ministry of Health platform. Data analysis was performed using the Statistical Package for the Social Sciences 20, Chi-square of adherence, the independence test and G test. For spatial distribution was used ArcGIS. We observed 123 COVID-19 cases: 46 deaths (37.40%), male gender (76-61.79%), age above 60 years (61- 49.6%), the most frequent risk factor was chronic cardiovascular disease (18- 14.63%). The predictors of death were: invasive ventilation has (10.73) more chances for the outcome death, those not vaccinated against influenza have (3.41) and age (1.4). COVID-19 occurrence was higher in municipalities that have villages with health care or commerce, or with migrants from the Warao ethnic group. Notifications should take into consideration the specific issues of in-digenous people so that effective control measures can be defined.

Divergent evolution of Corynebacterium diphtheriae in India: An update from National Diphtheria Surveillance network

Diphtheria is caused by a toxigenic bacterium Corynebacterium diphtheria which is being an emerging pathogen in India. Since diphtheria morbidity and mortality continues to be high in the country, the present study aimed to study the molecular epidemiology of C. diphtheriae strains from India. A total of 441 diphtheria suspected specimens collected as part of the surveillance programme between 2015 and 2020 were studied. All the isolates were confirmed as C. diphtheriae with standard biochemical tests, ELEK’s test, and real-time PCR. Antimicrobial susceptibility testing for the subset of isolates showed intermediate susceptibility to penicillin and complete susceptible to erythromycin and cefotaxime. Isolates were characterized using multi locus sequence typing method. MLST analysis for the 216 C. diphtheriae isolates revealed major diversity among the sequence types. A total of 34 STs were assigned with majority of the isolates belonged to ST466 (30%). The second most common ST identified was ST405 that was present in 14% of the isolates. The international clone ST50 was also seen. The identified STs were grouped into 8 different clonal complexes (CC). The majority belongs to CC5 followed by CC466, CC574 and CC209, however a single non-toxigenic strain belongs to CC42. This epidemiological analysis revealed the emergence of novel STs and the clones with better dissemination properties. This study has also provided information on the circulating strains of C. diphtheriae among the different regions of India. The molecular data generated through surveillance system can be utilized for further actions in concern.