Alireza Mirahmadizadeh; Fatemeh Rezaei; Kimia Jokari; Sepideh Mohseni; Sima Afrashteh; Seyed Sina Dehghani; Alireza Jafari; Mohsen Moghadami; Mousa Ghelichi-Ghojogh
Abstract
Background: HIV, Tuberculosis, and Malariaare neglected due to the high pressure imposed on healthcare systems by COVID-19; however, since these diseases afflict a large number of patients globally, their effect on COVID-19, as a world pandemic, should be assessed. We aimed to assess the relationship ...
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Background: HIV, Tuberculosis, and Malariaare neglected due to the high pressure imposed on healthcare systems by COVID-19; however, since these diseases afflict a large number of patients globally, their effect on COVID-19, as a world pandemic, should be assessed. We aimed to assess the relationship between the prevalence of these diseases and COVID-19 indices.Methods: In this ecological study, a data set was provided, which included the epidemiologic indices of COVID-19 for each country. The scatter plots of the social capital for the studied countries based on the epidemiologic indices of COVID-19 and HIV (human immunodeficiency virus), and Malaria were drawn.Results: The prevalence of HIV, Tuberculosis, and Malaria were inversely correlated with the cumulative incidence rate of cases, the cumulative incidence rate of death, and COVID-19 tests performed per million, and was directly correlated with the recovery rate. No correlation was seen between case fatality rate and the prevalence of these infectious diseases.Conclusion: However, the results of this study were in favor of people afflicted with HIV, and Further studies should be conducted on the concurrence of infectious events and their adverse consequences with future analytical protocols.
Alireza Mirahmadizadeh; Mousa Ghelichi-Ghojogh; Fatemeh Rezaei; Mehdi Nejat; Haleh Ghaem; Jafar Hassanzadeh; Mohammadreza Karimi; Zohre Khodamoradi; Kimia Jokari; Leila Jahangiry
Abstract
Background: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) can be transmitted through direct, indirect, or close contact with infected people by contaminated respiratory droplets or saliva. This study aimed to investigate the epidemiology of coronavirus disease 2019 (COVID-19) and the secondary ...
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Background: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) can be transmitted through direct, indirect, or close contact with infected people by contaminated respiratory droplets or saliva. This study aimed to investigate the epidemiology of coronavirus disease 2019 (COVID-19) and the secondary attack rate (SAR) in the cases’ close contact.Methods: A total of 431 confirmed COVID-19 patients were randomly selected using systematic random sampling from 15 May to 13 June 2020. The required data were extracted from the CORONALAB database of the Center for Disease Control and Prevention (CDC) at Shiraz University of Medical Sciences. Detection of COVID-19 was performed using Real- Time Polymerase Chain Reaction (RT-PCR) and nasopharyngeal swabs. SAR was also calculated for different groups.Results: Among the index cases, 64.27% were male, 24.80% were public sector employees, and 4.87% were admitted to the intensive care unit. In addition, most of them aged 30-39 years. The SAR was 11.56% (95% CI: 9.86% to 13.25%) in the close contacts. Accordingly, the highest SAR was observed among the friends, 19.05% (95% CI: 7.17% to 30.92%), followed by the spouses of COVID-19 cases, 16.67% (95% CI: 10.81% to 22.51%). Furthermore, diabetes (6.03%) and cardiovascular disease (5.1%) were the most common comorbidities among the index cases.Conclusion: The findings suggested that the SAR was relatively lower among the close contacts. Considering the familial and non-familial relationships between the index cases and their close contacts were the major causes of disease transmission. Therefore, it is crucial to conduct tracing for COVID-19 contacts in all cases with whom patients have had close contact.
Zahra Hemati; Mehrab Sayadi; Mehrzad Lotfi; Abdulrasool Hemmati; Fatemeh Azadian; Alireza Mirahmadizadeh; Fatemeh Rezaei; Babak Shirazi Yeganeh
Abstract
Background: The coronavirus disease 2019 (COVID-19) is rapidly spreading worldwide and becoming a pandemic. Since the diagnostic tests are relatively expensive, simple diagnostic tests are valuable for quarantining individuals suspicious of COVID- 19. This study is designed to predict the potential contributing ...
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Background: The coronavirus disease 2019 (COVID-19) is rapidly spreading worldwide and becoming a pandemic. Since the diagnostic tests are relatively expensive, simple diagnostic tests are valuable for quarantining individuals suspicious of COVID- 19. This study is designed to predict the potential contributing factors of COVID-19 diagnosis.Methods: It was a referral-based historical cohort study. 363358 individuals referred to the health centers from February to November 2020 in Fars province were entered in the study. The collected data before the lab test were symptoms, underlying diseases, some conditions, risk factors, and demographic information. The Reverse transcriptase polymerase chain reaction test was performed to identify the COVID-19 virus. Chi-square and T-tests were used to compare the variables. A logistic regression test was used to identify predictor variables.Results: Positive COVID-19 test was reported for 119,324 (% 34.9) participations. The positive group result was compared with that of the negative group (n=244,034). The studied symptoms were significant in positive patients. According to the odds ratio (OR), smell disorder (OR=3.80, P<0.001), taste disorder (OR=3.17, P<0.001), and fever (OR=2.65, P<0.001) were common. However, diarrhea, chest pain and dyspnea showed the lowest odds ratio. According to the results, DM (OR=1.46, P<0.001), HTN (OR=1.42, P<0.001), and CVD (OR=1.27, P<0.001) were common in patients with positive COVID-19 tests. Cases whose Body Mass Index (BMI) was more than 40 (excessive obesity) showed a higher odd (OR=1.45, P<0.001) for being positive.Conclusion: According to the results, the symptoms and underlying diseases are effective factors in predicting COVID- 19 disease. Identifying these factors for Covid-19 disease helps health policymakers to make quick decisions and take timely action.