ABSTRACT
Background: Coronavirus is one of the major pathogens of the human respiratory system and a major threat to the human health. Objectives: This modeling study aimed to project the epidemics trend of coronavirus disease 2019 (COVID-19) in Qom, Iran Methods: This study projected the COVID-19 outbreak in Qom using a modified susceptible-exposed-infectious-recovered (SEIR) compartmental model by the end of December 2020. The model was calibrated based on COVID-19 epidemic trend in Qom from 1 January to 11 July. The number of infected, hospitalized, and death cases were projected by 31 December. A Monte Carlo uncertainty analysis was applied to obtain 95% uncertainty interval (UI) around the estimates. Results: According to the results, the reduced contact rate and increased isolation rate were effective in reducing the size of the epidemic in all scenarios. By reducing the contact rate from eight to six, the number of new cases on the peak day, as well as the total number of cases admitted to the hospital by the end of the period (31 December), decreased. For example, in Scenario A, compared to Scenario E, with a decrease in contact rate from eight to six, the number of new cases on peak days decreased from 15,700 to 1,100. The largest decrease in the number of new cases on peak days was related to Scenario F with 270 cases. Also, the total number of cases decreased from 948,000 to 222,000 between the scenarios, and the largest decrease in this regard was related to Scenario F, with 188,000 cases. Conclusions: The parameters of contact rate and isolation rate can reduce the number of infected cases and prevent the outbreak, or at least delay the onset of the peak. This can help health policymakers and community leaders to upgrade their health care
ABSTRACT
The present study is designed to predict the global adjusted values for mortality rate and case fatality rate of COVID-19 around the world. This study aims - to investigate some of the predictive factors which may affect the mortality rate and case fatality rate in 100 randomly chosen countries. Material and methods. This research was conducted at the ecological level using data from 100 countries which were chosen randomly. The adjusted values were predicted using beta regression considering predictive factors such as total expenditure on health per capita, expenditure on health as a percentage of GDP (gross domestic product), life expectancy and the percentage of the population aged over 65 years, hospital beds (per 1000 population), physicians (per 1000 population), nurses (per 1000 population), prevalence of smoking, prevalence of diabetes mellitus, and number of confirmed tests in each country. In the end, applying Monte Carlo simulation, the adjusted values of mortality rate and case fatality rate for the whole world were estimated. Results. The results of this study showed that two factors including percentage of population ages 65 and above (p=0.03) and Total expenditure on health as % of GDP (p=0.04) had a statistically significant relationship with the case fatality rate. Moreover, there was a statistically significant relationship between the mortality rate and life expectancy (p=0.02), total expenditure on health per capita (p<0.001), nurses (per 1000 population) (p=0.04), and the prevalence of diabetes mellitus (p=0.04). The mortality rate and case fatality rate for the whole world were estimated to be 0.000001 and 0.026, respectively. Conclusion. It seems that what can cause global concern is not the case fatality rate of the disease, but its mortality rate, which is directly related to the health status of a community. The worse the health status of a community, the greater the number of infected people likely to be there, that ultimately increases the mortality rate of the disease in the community. © 2022 by the authors.
ABSTRACT
Background: Higher mortality due to coronavirus disease 2019 (COVID-19) is reported among some immunocompromised patients;however, the relation between immunosuppression due to HIV infection and severity of COVID-19 infection remains unclear. We aimed to investigate the severity and mortality of COVID-19 infection in HIV-infected patients. Methods: This was a retrospective cohort study on all COVID-19 suspected and confirmed cases hospitlized in Iran between Febuary 19 (epidemic onset date) and April 8, 2020, whose data were recorded in the national database for Medical Care Monitoring Center. Hospitalized patients were followed from admittion to death/discharge. Patients’ HIV status was recorded based on their self report. Logistic and Cox regression models were used to evaluate the association between HIV infection and the severity (according to the Glascow-Coma Scale situation, need for intubation and hypoxemia) and mortality of COVID-19 infection, respectively. Analyses were performed separately for COVID-19 suspected and confirmed cases. Results: Out of 122 206 severe acute respiratory infection (SARI) cases, 90 were HIV-positive (0.07%), with a similar mean age (Pttest= 0.750) and distrubtion of gender (PChi-square= 0.887) and nationality (PChi-square= 0.202) as HIV-negative patients. A comparable proportion of HIV-positive and HIV-negative cases were tested for COVID-19 (p= 0.170);however, the frequency of positive results was lower among HIV-positives (p= 0.038). The frequency of COVID-19 and HIV coinfection was lower than expected among confirmed cases (adjusted OR= 0.54;95% CI: 0.29-1.02) and suspected cases (adjusted OR= 0.68;95% CI: 0.45- 1.02), which means that the frequency of COVID-19 infection was lower among HIV-positive cases. HIV infection decreased the risk of death among confirmed (adjusted HR= 0.33;95% CI: 0.05-2.32), suspected cases (adjusted HR= 0.81;95% CI: 0.33-1.94), and among SARI cases (adjusted HR= 0.73;95% CI: 0.35-1.54). Conclusion: Our findings support the concept that HIV infection was not a risk factor to increase the severity and risk of death among COVID-19 infected patients. Copyright© Iran University of Medical Sciences