Food insecurity, body mass index, socio-economic status, and food intake in lactating and non-lactating mothers with children under two years.

BACKGROUND: food insecurity (FI) is considered as an essential public health problem which may have detrimental effects on people's health. The aim of present study was to evaluate FI, body mass index, quantity and quality of food intake in lactating and non-lactating mothers with children under two years. METHODS: in this cross-sectional study 307 mothers (237 lactating and 70 non-lactating) were participated. Socio-economic and demographic information were gathered by questionnaires. FI of families was evaluated by the questionnaire of the United States Department of Agriculture (USDA) Household Food Security. For assessing quality and quantity of food intake of mothers, dietary diversity score (DDS), diet quality index-international (DQI-I) and nutrient adequacy ratio (NAR) were calculated. Weight and height of participants were measured and body mass index (BMI) was calculated. Finally, Chi-squared test, analysis of variance (ANOVA) and linear regression were used for statistical analysis. RESULTS: in this study the rate of underweight, normal weight, overweight, and obesity in mothers was 0.3%, 39.2%, 42.3%, and 18.2%, respectively. Among the determinants of BMI, household food security status had the greatest effect (Beta=-1.584, P < 0.001) and mother age had the least effect (Beta = 0.101, P = 0.013). Mother's occupational and educational status, having facilities, physiological status of mother, and house size had significant correlation with NAR. Mother's occupational and educational status, and having facilities had significant relationship with DDS, too. Also, the significant correlation of Mother's education, having facilities, and physiological status of mother with DQI-I were found. CONCLUSIONS: we found that Household food security status had the most effect on BMI of mothers. In this study, the best nutrient adequacy and dietary diversity were found in the obese group and the most diet quality was found in the normal weight group.

The Effect of Tang Forte (Royal Jelly) Capsule on Hypoglycemia and Clinical Course in COVID-19 Patients Under Corticosteroid Therapy.

Corticosteroids improve the complications of Covid-19 but may cause some side effects such as hyperglycemia. Royal jelly is one of the bee products that exert anti-inflammatory, insulin-like, and hypoglycemic activities. The present study was conducted to investigate the effect of royal jelly capsules on blood sugar and the clinical course of Covid-19 in the patients receiving corticosteroid therapy. In this clinical trial, 72 Covid-19 patients with positive reverse transcription polymerase chain reaction (RT-PCR) test and pulmonary involvement hospitalized in Shahrekord Hajar Hospital were enrolled and randomized into two groups: treatment (receiving corticosteroids and Royal Jelly 1000 mg capsules daily for 7 days) and placebo (given corticosteroids and placebo). Laboratory tests, blood sugar, and clinical courses were determined and compared. Data was analyzed using SPSS version 16. On day 7 after the onset of the intervention, the dosage and frequency of insulin, FBS level, and required corticosteroid showed a decrease in both groups but the inter-group difference was not significant (P > .05). As well, the Spo2 level indicated a non-significant increase and hospital stay length indicated a non-significant decrease in the intervention group (P > .05). Among the symptoms, only headache, cough, and dyspnea indicated an improvement in the intervention group (P < .05). Overall, the results indicated the short-term consumption of royal jelly could not significantly improve blood sugar and the clinical course of Covid-19; however, it could significantly improve headache, cough, and dyspnea in the patients.

Safety and immunogenicity of a recombinant receptor-binding domain-based protein subunit vaccine (Noora vaccine™) against COVID-19 in adults: A randomized, double-blind, placebo-controlled, Phase 1 trial.

The development of a safe and effective vaccine is essential to protect populations against coronavirus disease 2019 (COVID-19). There are several vaccine candidates under investigation with different mechanisms of action. In the present study, we have evaluated the safety and immunogenicity of a recombinant receptor-binding domain (RBD)-based protein subunit vaccine (Noora vaccine) against COVID-19 in adults. This Phase 1 trial is a randomized, double-blind, placebo-controlled study to evaluate the safety and immunogenicity of the recombinant RBD-based protein subunit vaccine (Noora vaccine) against COVID-19 in healthy adults volunteers. Eligible participants were included in this study after evaluating their health status and considering the exclusion criteria. They were then randomized into three groups and received three doses of vaccine (80 µg, 120 µg, and placebo) on Days 0, 21, and 35. Primary outcomes including solicited, unsolicited, and medically attended adverse events were recorded during this study. Secondary outcomes including the humoral and cellular immunity (including anti-RBD IgG antibody and neutralizing antibody) were measured on Days 0, 21, 28, 35, 42, and 49 by using the ELISA kit and the Virus Neutralization Test (VNT) was performed on day 49. Totally 70 cases were included in this Phase 1 trial and 60 of them completed the study. Safety assessments showed no severe adverse events. Local pain at the vaccine injection site occurred in 80% of the vaccinated volunteers. Induration and redness at the injection site were the other adverse reactions of this vaccine. There was no significant difference between the studied groups regarding adverse reactions. Anti-RBD IgG antibody and neutralizing antibody assessment showed significant seroconversion in comparison to the placebo group (80%, and 100% respectively, p < 0.001). The cellular immunity panel also showed mild to moderate induction of TH1 responses and the VNT showed 78% of seroprotection. The results of this Phase 1 trial showed acceptable safety without serious adverse events and significant seroconversions in the humoral and cellular immunity panel. The dose of 80 µg is an appropriate dose for injection in the next phases of the trial.

Systematic Risk in Iran's Medical Tourism Industry: A Narrative Review

Medical tourism is a new form of tourism grown significantly in recent years across the world and in Iran. The flow of medical tourism today is from developed countries to developing countries. Yet, demand volatility due to systematic risks can hurt industry players. The occurrence of systematic risks in the tourism industry, especially medical tourism, is common. The latest case of systemic risk is the COVID19 pandemic. The present study aimed to detect and study the factors that can help companies to be more resilient in the occurrence of systematic risks in the medical tourism industry. The Delphi method was used to summarize and analyze the industry managers' perception of the above factors. The results of analyzing the perceptions of managers of companies operating in the medical tourism industry show that debt advantage, liquidity and profitability, and operational efficiency are the determinants that play the most important role in the resilience of companies against systematic risks. The role of advertising is also relatively agreed upon by the managers.

Public sentiments toward COVID-19 vaccines in South African cities: An analysis of Twitter posts.

Amidst the COVID-19 vaccination, Twitter is one of the most popular platforms for discussions about the COVID-19 vaccination. These types of discussions most times lead to a compromise of public confidence toward the vaccine. The text-based data generated by these discussions are used by researchers to extract topics and perform sentiment analysis at the provincial, country, or continent level without considering the local communities. The aim of this study is to use clustered geo-tagged Twitter posts to inform city-level variations in sentiments toward COVID-19 vaccine-related topics in the three largest South African cities (Cape Town, Durban, and Johannesburg). VADER, an NLP pre-trained model was used to label the Twitter posts according to their sentiments with their associated intensity scores. The outputs were validated using NB (0.68), LR (0.75), SVMs (0.70), DT (0.62), and KNN (0.56) machine learning classification algorithms. The number of new COVID-19 cases significantly positively correlated with the number of Tweets in South Africa (Corr = 0.462, P < 0.001). Out of the 10 topics identified from the tweets using the LDA model, two were about the COVID-19 vaccines: uptake and supply, respectively. The intensity of the sentiment score for the two topics was associated with the total number of vaccines administered in South Africa (P < 0.001). Discussions regarding the two topics showed higher intensity scores for the neutral sentiment class (P = 0.015) than for other sentiment classes. Additionally, the intensity of the discussions on the two topics was associated with the total number of vaccines administered, new cases, deaths, and recoveries across the three cities (P < 0.001). The sentiment score for the most discussed topic, vaccine uptake, differed across the three cities, with (P = 0.003), (P = 0.002), and (P < 0.001) for positive, negative, and neutral sentiments classes, respectively. The outcome of this research showed that clustered geo-tagged Twitter posts can be used to better analyse the dynamics in sentiments toward community-based infectious diseases-related discussions, such as COVID-19, Malaria, or Monkeypox. This can provide additional city-level information to health policy in planning and decision-making regarding vaccine hesitancy for future outbreaks.

A cross-country analysis of macroeconomic responses to COVID-19 pandemic using Twitter sentiments.

The COVID-19 pandemic has had a devastating impact on the global economy. In this paper, we use the Phillips curve to compare and analyze the macroeconomics of three different countries with distinct income levels, namely, lower-middle (Nigeria), upper-middle (South Africa), and high (Canada) income. We aim to (1) find macroeconomic changes in the three countries during the pandemic compared to pre-pandemic time, (2) compare the countries in terms of response to the COVID-19 economic crisis, and (3) compare their expected economic reaction to the COVID-19 pandemic in the near future. An advantage to our work is that we analyze macroeconomics on a monthly basis to capture the shocks and rapid changes caused by on and off rounds of lockdowns. We use the volume and social sentiments of the Twitter data to approximate the macroeconomic statistics. We apply four different machine learning algorithms to estimate the unemployment rate of South Africa and Nigeria on monthly basis. The results show that at the beginning of the pandemic the unemployment rate increased for all the three countries. However, Canada was able to control and reduce the unemployment rate during the COVID-19 pandemic. Nonetheless, in line with the Phillips curve short-run, the inflation rate of Canada increased to a level that has never occurred in more than fifteen years. Nigeria and South Africa have not been able to control the unemployment rate and did not return to the pre-COVID-19 level. Yet, the inflation rate has increased in both countries. The inflation rate is still comparable to the pre-COVID-19 level in South Africa, but based on the Phillips curve short-run, it will increase further, if the unemployment rate decreases. Unfortunately, Nigeria is experiencing a horrible stagflation and a wild increase in both unemployment and inflation rates. This shows how vulnerable lower-middle-income countries could be to lockdowns and economic restrictions. In the near future, the main concern for all the countries is the high inflation rate. This work can potentially lead to more targeted and publicly acceptable policies based on social media content.

Identification and molecular characterization of penicillin-nonsusceptible Streptococcus pneumoniae isolates recovered from invasive infections in a pre-pneumococcal vaccine era.

BACKGROUND: Given the significant role of penicillin-nonsusceptible Streptococcus pneumoniae in inducing severe infectious diseases, identifying serotypes and genotypes that can mediate antimicrobial resistance has become a pillar of treatment strategies. This study aims to determine the correlation between the minimum inhibitory concentration of antimicrobial agents and amino acid mutations in penicillin-binding proteins. Moreover, molecular serotyping and multiple-locus variable number tandem repeat analysis typing were first-ever performed to characterize the invasive penicillin-nonsusceptible S. pneumoniae isolates in Iran. METHODS: Of 149 isolates, antimicrobial susceptibility tests were performed against penicillin, ceftriaxone, and cefotaxime by the MIC Test Strip, and sequence analysis of the pbp genes was performed through PCR-sequencing method. All penicillin-nonsusceptible S. pneumoniae isolates were serotyped and genotyped by sequential multiplex PCR and multiple-locus variable-number tandem repeat analysis, respectively. RESULTS: Among pneumococcal isolates, 53 isolates were classified as penicillin-nonsusceptible S. pneumoniae, of which 38 (71.7%) and 15 (28.3%) were resistant and intermediate to penicillin, respectively. Furthermore, ceftriaxone- and cefotaxime-nonsusceptible pneumococci constituted 33 (62.2%) and 29 cases (54.7%), respectively. Of note, there were 8 and 41 different serotypes and multiple-locus variable-number tandem repeat analysis types, respectively. CONCLUSIONS: Due to the increasing resistance to antimicrobial agents, the most efficient approach to preventing pneumococcal infection mortality as vaccine-preventable diseases is focusing on wide-spectrum vaccination. Based on our findings, the 13-valent pneumococcal conjugate vaccine could considerably reduce the incidence of invasive pneumococcal diseases due to the high rate of serotype coverage.

Preclinical study of formulated recombinant nucleocapsid protein, the receptor binding domain of the spike protein, and truncated spike (S1) protein as vaccine candidates against COVID-19 in animal models.

BACKGROUND: In this pre-clinical study, we designed a candidate vaccine based on severe acute respiratory syndrome-related -coronavirus 2 (SARS-CoV-2) antigens and evaluated its safety and immunogenicity. METHODS: SARS-CoV-2 recombinant protein antigens, including truncated spike protein (SS1, lacking the N-terminal domain of S1), receptor-binding domain (RBD), and nucleoprotein (N) were used. Immunization program was performed via injection of RBD, SS1 +RBD, and SS1 +N along with different adjuvants, Alum, AS03, and Montanide at doses of 0, 40, 80, and 120 µg at three-time points in mice, rabbits, and primates. The humoral and cellular immunity were analyzed by ELISA, VNT, splenocyte cytokine assay, and flow cytometry. RESULTS: The candidate vaccine produced strong IgG antibody titers at doses of 80 and 120 µg on days 35 and 42. Even though AS03 and Montanide produced high-titer antibodies compared to Alum adjuvant, these sera did not neutralize the virus. Strong virus neutralization was recorded during immunization with SS1 +RBD and RBD with Alum. AS03 and Montanide showed a strong humoral and cellular immunity; however, Alum showed mild to moderate cellular responses. Ultimately, no cytotoxicity and pathologic change were observed. CONCLUSION: These findings strongly suggest that RBD with Alum adjuvant is highly immunogenic as a potential vaccine.

Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life Years for 29 Cancer Groups From 2010 to 2019: A Systematic Analysis for the Global Burden of Disease Study 2019.

IMPORTANCE: The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. OBJECTIVE: To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. EVIDENCE REVIEW: The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs). FINDINGS: In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. CONCLUSIONS AND RELEVANCE: The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.

Description of Epidemiological Features, Symptoms and Mortality of the Patients with COVID-19 in Some Provinces of Iran.

BACKGROUND: Clinical manifestations of COVID-19 are different. There are some risk factors for COVID-19. This study aimed to describe the epidemiological features, symptoms and mortality of the patients with COVID-19 in Iran. METHODS: This were a cohort study performed on 103,179 patients with COVID-19. The demographic and clinical data were collected in selected provinces. The required data of all patients was extracted from the COVID registry system and analyzed using STATA version 14 and Excel 2016. RESULTS: The mean age was 52.40 years for men and 52.41 years for women. About 55.2% of the study population were male and 44.8% were female. Totally, 60.9% (5085) of deaths happened in men and 39.1% (3263) in women. The mean time from onset of symptoms to hospitalization in men and women were 3.47 and 3.48 days, respectively. The mean time from onset of symptoms to isolation was 2.81 days in men and was 2.87 days in women, from onset of symptoms to death was 9.29 and 9.54 days, respectively, from onset of symptoms to discharge was 7.47 and 7.39 days, and from hospitalization to death was 6.76 and 7.05 days. Cough and shortness of breath were the most common symptoms in the patients. CONCLUSION: According to the results, the overall mortality rate was higher in men than women. Women with cardiovascular disease and diabetes were more likely to die. The mean time from onset of symptoms to hospitalization, isolation, and discharge was similar in men and women.

Astaxanthin protective barrier and its ability to improve the health in patients with COVID-19.

Inflammation acts like a double-edged sword and can be harmful if not appropriately controlled. COVID-19 is created through a novel species of coronavirus SARS-CoV-2 (2019-nCoV). Elevated levels of inflammatory factors such as interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), etc. lead to Acute Respiratory Distress Syndrome (ARDS) and severe complications of infection in the lungs of coronavirus-infected patients. Astaxanthin is a natural and potent carotenoid with powerful antioxidant activity as well as an anti-inflammatory agent that supports good health. The effects of astaxanthin on the regulation of cyclooxygenase-2 (COX-2) pathways and the reduction and suppression of cytokines and other inflammatory agents such as IL-6 and TNF-α have already been identified. Therefore, these unique features can make this natural compound an excellent option to minimize inflammation and its consequences.

Association between dietary satisfaction and depression, anxiety and stress in obese and overweight patients during the coronavirus pandemic.

BACKGROUND & AIM: The coronavirus disease-2019 (COVID-19) pandemic is a global health threat. The aim of this study was to evaluate the association between D-Sat and depression, anxiety and stress in obese patients during the coronavirus pandemic. METHODS: A cross-sectional study in 228 obese and overweight women on a weight loss diet was conducted through the use of two questionnaires. General characteristics, anthropometric indices, D-Sat and mental status were assessed in these patients. RESULTS: The greatest weight loss (WL) and waist circumference (WC) change was associated with the highest tertile of the D-Sat score in the first four months of the coronavirus pandemic (P < 0.05). Participants with the highest tertile of all D-sat score compared to those with the lowest had an 84% decrease in odds of depression. The highest tertile was also associated with decreased odds of anxiety (OR: 0.32 95%CI: 0.14; 0.68) The adjusted odds of stress score were negatively associated to the highest tertile of the D-Sat score (OR: 0.09, 95%CI (0.03, 0.23). WL was inversely related to stress (P < 0.05). Participants with higher WL and WC reduction had fewer depressive symptoms (P < 0.05). Sleep time and family income were associated with obesity. CONCLUSIONS: D-Sat and positive personal and family dynamics can improve the mental status of obese and overweight patients during quarantine.

Simultaneous monitoring of SARS-CoV-2, bacteria, and fungi in indoor air of hospital: a study on Hajar Hospital in Shahrekord, Iran.

The novel SARS-CoV-2 outbreak was declared as pandemic by the World Health Organization (WHO) on March 11, 2020. Understanding the airborne route of SARS-CoV-2 transmission is essential for infection prevention and control. In this study, a total of 107 indoor air samples (45 SARS-CoV-2, 62 bacteria, and fungi) were collected from different wards of the Hajar Hospital in Shahrekord, Iran. Simultaneously, bacterial and fungal samples were also collected from the ambient air of hospital yard. Overall, 6 positive air samples were detected in the infectious 1 and infectious 2 wards, intensive care unit (ICU), computed tomography (CT) scan, respiratory patients' clinic, and personal protective equipment (PPE) room. Also, airborne bacteria and fungi were simultaneously detected in the various wards of the hospital with concentrations ranging from 14 to 106 CFU m-3 and 18 to 141 CFU m-3, respectively. The highest mean concentrations of bacteria and fungi were observed in respiratory patients' clinics and ICU wards, respectively. Significant correlation (p < 0.05) was found between airborne bacterial concentration and the presence of SARS-CoV-2, while no significant correlation was found between fungi concentration and the virus presence. This study provided an additional evidence about the presence of SARS-CoV-2 in the indoor air of a hospital that admitted COVID-19 patients. Moreover, it was revealed that the monitoring of microbial quality of indoor air in such hospitals is very important, especially during the COVID-19 pandemic, for controlling the nosocomial infections.

Modeling and forecasting trend of COVID-19 epidemic in Iran until May 13, 2020.

Background: COVID-19 is a new disease and precise data are not available about this illness in Iran and in the world. Thus, this study aimed to determine the epidemic trend and prediction of COVID-19 in Iran. Methods: This was a secondary data analysis and modeling study. The daily reports of definitive COVID-19 patients released by Iran Ministry of Health and Medical Education were used in this study. Epidemic projection models of Gompertz, von Bertalanffy, and least squared error (LSE) with percentage error were used to predict the number of hospitalization cases from April 3, 2020 until May 13, 2020. Results: The prediction of the number of patients on April 3, 2020 by von Bertalanffy, Gompertz, and LSE, with 95% confidence interval (CI), were estimated at 44 200 (39 208-53 809), 47 500 (38 907-52 640), and 48 000 (40 000-57 560), respectively. The number of deceased COVID-19 patients was also estimated to be 3100 (2633-3717) individuals by the von Bertalanffy model, 3700 (2900-4310) by Gompertz's model, and 3850 (3200-4580) by LSE. Making predictions about the flat epidemic curve and number of patients based on Gompertz model, will project 67 000 (61 500-87 000) cases. Based on Gompertz and von models, 7900 (6200- 9300) and 4620 (3930- 5550) deaths will occur from May 13 to June 1, 2020, respectively, and then the curve will flatten. Conclusion: In this study, estimations were made based on severely ill patients who were in need of hospitalization. If enforcement and public behavior interventions continue with current trends, the COVID-19 epidemic will be flat from May 13 until July, 2020 in Iran.