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Objective: A year after the emergence of a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as a new crisis in respiratory infections, there remain many uncertainties and unknowns about SARS-CoV-2 and the disease it causes, called coronavirus disease (COVID-19). Although COVID-19 is known as a respiratory disease, some atypical manifestations have been seen, different from those seen in other types of viral respiratory infections. This paper aims to describe designing, launching, and implementing a data collection system for all respiratory diseases, with a focus on SARS-CoV-2 from the onset of this pandemic. Method: The current registry is designed in compliance with the standard Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines, along with the declaration of Helsinki principles. Results: A respiratory disease registry, with an emphasis on COVID-19 and other co-infections, was developed. Data consisted of demographic, clinical, and supporting information about SARS-CoV-2 and other respiratory viral diseases. Conclusion: It is hoped that the current data registry will facilitate patient evaluation and improve the outcomes of cases of respiratory infection defined by a particular condition, disease, or exposure. Moreover, the registry can harmonize data about the treatment, outcomes, and well-being of patients who receive care over time, and identify best practices. [ABSTRACT FROM AUTHOR]

A life-threatening respiratory disease, coronavirus 2019 (COVID-19), has spread across the globe since December 2019. Many prognostic factors have already been put forward to predict the risk of death and other outcomes. The current study is evaluating the survival rate between hypertensive and non-hypertensive infected patients. Patients who were included in this study were admitted between 20 February to 1 March 2020 in Fars (southwest of Iran) province hospitals. Data were collected from the electronic base registry which contained demographic information, medical symptoms, and signs, underlying diseases, CT scan results, and final outcome. Of all 1239 positive cases, 159 (12.83%) had known with hypertension ant this group was significantly older than non-hypertensive patients (66.1 years Vs 48.95 years, p <.001). According to Kaplan–Meier survival curve and log-rank test, it was seen hypertensive patients deteriorated more rapidly than non-hypertensive group (p =.032). Moreover, HIV, cardiovascular, and kidney disease were diagnosed as factors that increase the risk of death in hypertensive patients. The current study about the survival rate of COVID-19 patients had shown hypertensive patents are in danger of disease severity, although it may be related to their age. Moreover, the probability of other complications like diabetes, smoking, asthma, kidney, and cardiovascular diseases, and either some other infections such as HIV can make the condition complicated and need more consideration to prevent noxious outcomes. [ABSTRACT FROM AUTHOR]

Emergence of a new coronavirus causes a serious concern whether this can be stopped at all. The ongoing coronavirus disease created a substantial variation in the fatality rate over the world. The current report brought an explore about the epidemiological characteristics of deceased patients and the fatality rate after the first peak in Fars province which is the fourth most populous and large province in Iran. Of the 3702 confirmed cases with coVID-19, 87 patients passed away and so the fatality rate estimated 2.35. Also, it was derived that male sex, old age and underlying diseases especially diabetes were common characteristics of these victims. [ABSTRACT FROM AUTHOR]

Sustainable management of orchard fields requires detailed information about the tree types, which is a main component of precision agriculture programs. To this end, hyperspectral imagery can play a major role in orchard tree species mapping. Efficient use of hyperspectral data in combination with field measurements requires the development of optimized band selection strategies to separate tree species. In this study, field spectroscopy (350 to 2500 nm) was performed through scanning 165 spectral leaf samples of dominant orchard tree species (almond, walnut, and grape) in Chaharmahal va Bakhtiyari province, Iran. Two multivariable methods were employed to identify the optimum wavelengths: the first includes three-step approach ANOVA, random forest classifier (RFC) and principal component analysis (PCA), and the second employs partial least squares (PLS). For both methods we determined whether tree species can be spectrally separated using discriminant analysis (DA) and then the optimal wavelengths were identified for this purpose. Results indicate that all species express distinct spectral behaviors at the beginning of the visible range (from 350 to 439 nm), the red edge and the near infrared wavelengths (from 701 to 1405 nm). The ANOVA test was able to reduce primary wavelengths (2151) to 792, which had a significant difference (99% confidence level), then the RFC further reduced the wavelengths to 118. By removing the overlapping wavelengths, the PCA represented five components (99.87% of variance) which extracted optimal wavelengths were: 363, 423, 721, 1064, and 1388 nm. The optimal wavelengths for the species discrimination using the best PLS-DA model (100% accuracy) were at 397, 515, 647, 1386, and 1919 nm. [ABSTRACT FROM AUTHOR]

Background: Influenza is one of the most important viral diseases with high mortality and morbidity that can have a great impact on public health and economy. Objective: To investigate the clinical and epidemiological features of influenza virus A/H1N1, A/H3N2, and B infection in Fars province, southern Iran, in 2015-2019. Methods: In this retrospective cross-sectional study, we assessed the archived data of Syndromic Surveillance System of Iran's Health Ministry, allowed access by Communicable Diseases' Unit of Health chancellor of Shiraz University of Medical Sciences, from December 22, 2015 to September 22, 2019. The participants included all patients whose data were recorded as influenza-like illness (ILI) and severe acute respiratory infections/illness (SARI). Influenza viral infection was confirmed by reverse-transcriptase polymerase chain reaction (RT-PCR). Results: Totally, 1269 patients suspected of influenza were sampled. The mean ± SD of age was 29.40 ± 26.91 years. Fever was the most common symptom (68.6%). The highest incidence was in winter (55.9%). Of 928/1269 laboratory's results which were recorded in the registry, 204 (16.08%) samples were positive and 724 (57.05%) were negative. Among 204 positive results, 191 (15.05%) were influenza type A, and 8 (0.63%) influenza type B. Among patients with definite influenza type A, 34 (2.68%) had H1N1/p subtype, 58 (4.57%) H3N2, and one (0.08%) had other subtypes; however, subtypes were not identified in 7.72% of patients. Six (3.0%) patients with confirmed influenza expired. Conclusion: The incidence of influenza, especially type A, in Fars province, southern Iran is considerable and requires more attention for prevention in health policy programs. [ABSTRACT FROM AUTHOR]