Spatio-temporal analysis of COVID-19 incidence rate using GIS: a case study-Tehran metropolitan, Iran.

COVID-19 has been distinguished as a zoonotic coronavirus, like SARS coronavirus and MERS coronavirus. Tehran metropolis, as the capital of Iran, has a high density of residents that experienced a high incidence and mortality rates which daily increase the number of death and cases. In this study, the IDW (Inverse Distance Weight), Hotspots, and GWR (Geography Weighted Regression) Model are used as methods for analyzing big data COVID-19 in Tehran. The results showed that the majority of patients and deaths were men, but the death rate was higher in women than in men; also was observed a direct relationship between the area of the houses, and the infected rate, to COVID-19. Also, the results showed a disproportionate distribution of patients in Tehran, although in the eastern regions the number of infected people is higher than in other districts; the eastern areas have a high population density as well as residential land use, and there is a high relationship between population density in residential districts and administrative-commercial and the number of COVID-19 cases in all regions. The outputs of local R2 were interesting among patients and underlying disorders; the local R2 between hypertension and neurological diseases was 0.91 and 0.79, respectively, which was higher than other disorders. The highest rates of local R2 for diabetes and heart disease were 0.67 and 0.55, respectively. From this study, it can be concluded the restrictions must be considered especially, in areas densely populated for all people.

Assessment of the belief and attitudes of Iranian healthcare personnel's toward the influenza infection and influenza vaccination.

INTRODUCTION: Influenza is one of the main public health problems and health care personnels (HCPs) are one of the at-risk groups for this infection. The goal of the current study was to identify the beliefs and attitudes of the Iranian HCPs about influenza and the influenza vaccine. METHODS: This cross-sectional study was performed in a general hospital in Tehran, Iran from January to June 2016. A total of 418 questionnaires were distributed among the HCPs. The Chi2 test, linear regression and one-way ANOVA were used for data analysis, α: 0.05 was considered as a statistically significant level. All analyses were performed using the SPSS19 software. RESULTS: The influenza vaccination coverage was 57.7%; the highest vaccine rate belongs to the allied health professionals (68.2%). Two main causes for avoiding the influenza vaccination were; the "fear of vaccine adverse effects" and the "uncertainty about the vaccine effectiveness". The linear regression analysis identified that the physicians had the highest belief score, followed by the nurses and the allied health professionals (p < 0.001). CONCLUSIONS: Educational planning on influenza and influenza vaccination is necessary to improve the vaccination coverage and to reduce the influenza mortality and morbidity in susceptible patients.

Different combinations of glucose tolerance and blood pressure status and incident cardiovascular disease and all-cause mortality events.

The purpose of this study was to evaluate the effect of combinations of blood pressure and glucose tolerance status on cardiovascular and all-cause mortality. A total of 7619 participants aged ⩾30 years old were stratified to nine categories as follows: (1) normotension (NTN) and normal glucose tolerance (NGT) (reference group), (2) NTN and pre-diabetes mellitus (pre-DM), (3) NTN and DM, (4) pre-hypertension (pre-HTN) and NGT, (5) pre-HTN and pre-DM, (6) pre-HTN and DM, (7) HTN and NGT, (8) HTN and pre-DM and (9) HTN and DM. Cox proportional hazards were applied to calculate the multivariate hazard ratios (HRs) of different groups for outcomes. For all-cause mortality outcomes, prevalent cardiovascular disease (CVD) was also adjusted. In a median follow-up of 11.3 years, 696 CVD and 412 all-cause mortality events occurred. Among the population free from CVD at baseline (n=7249), presence of HTN was associated with increased risk of CVD, regardless of glucose tolerance status with HRs of 1.97 (95% confidence interval (CI), 1.49-2.61), 2.25 (1.68-3.02) and 3.16 (2.28-4.37) for phenotypes of HTN and NGT, HTN and pre-DM and HTN and DM for CVD, respectively; corresponding HRs for all-cause mortality were 1.65 (95% CI, 1.15-2.37), 1.69 (1.15-2.49) and 2.73 (1.80-4.14), respectively. Phenotypes of NTN and pre-DM (1.48; 1.03-2.14) and NTN and DM (2.04; 1.06-3.92) were also associated with CVD and all-cause mortality, respectively. HTN was significantly associated with CVD/mortality events, regardless of glucose tolerance status. Blood pressure <120/80 mm Hg among pre-diabetic/diabetic population, not on antihypertensive medications, was generally associated with worse outcomes.