Epidemiological and clinical risk factors related to severe COVID-19 in Iran: a multi-center study.

BACKGROUND: Iran was one of the first countries to be affected by COVID-19. Identifying factors associated with the severity of COVID-19 is effective in disease management. This study investigated the epidemiological and clinical features and factors related to the severity of COVID-19 in one of the less privileged areas in Iran. METHODS: In a multi-center study, all patients admitted to Zahedan University of Medical Sciences hospitals in southeastern Iran were investigated from February 29 to April 31, 2020. Demographic, epidemiological, and clinical data of patients were extracted from medical records. Bivariate and multivariate logistic regression models were used to explore the risk factors associated with the severity of COVID-19. RESULTS: Among the 413 patients, 55.5% were male, and 145 (35.10%) were in a severe condition at admission time. Multivariate analysis showed that the adjusted odds of the disease severity increased in patients with older age (OR 2.27; 95% CI 1.41-3.65), substance abuse (OR 2.49; 95% CI 1.14-5.43), having one underlying disease (OR 1.52; 95% CI 0.90-2.55), having two underlying disease (OR 2.31; 95% CI 1.19-4.50), and having three or more underlying disease (OR 2.60; 95% CI 1.19-5.66). CONCLUSIONS: COVID-19 was more severe in older patients, patients with a history of substance abuse, and patients with the underlying disease. Understanding the factors affecting the disease severity can help the clinical management of COVID-19, especially in less privileged areas where fewer resources are available.

Predicting the Potential Distribution of Major Malaria Vectors Based on Climate Changes in Sistan and Baluchistan Province, Southeastern Iran.

Background: Given the significance of climate change and its substantial effects on mosquitoes' habitats, this study was aimed to model the spatial distribution of the main malaria vectors in the south east of Iran. Methods: Several scientific databases between 1980 and 2019 were reviewed to find mosquito species and their spatial information in this area. The archived folders in the center for diseases control and prevention were used to exploit essential data on malaria cases and foci. Three representative concentration pathways (RCP2.6, RCP4.5 and RCP8.5) were chosen to stand for three possible climate scenarios. Finally the potential species distribution of Anopheles stephensi and An. culicifacies s.l. in the 2030s and 2050s horizons were estimated by the Maximum Entropy Model. Results: So far, a total of 39 mosquito species belonging to the family Culicidae have been reported from the study area. In 2019, the total malaria cases have increased by 91% compared to 2015, as well as a sharp rise than 2018 (249%). In that year, 91% of cases were imported from other countries, which caused 40% increase in the new potential foci than in 2018. The Jackknife test demonstrated the annual mean temperature and precipitation of the coldest quarter with the greatest impact on the environmental suitability of the mentioned two species. Conclusion: The effect of climate change on the appearance and recurrence of mosquito-borne diseases has been demonstrated in various studies. Collecting further data and conducting investigation on this issue will improve control management, especially for the malaria vectors.