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Introduction: SARS-CoV-2 cause pneumonia can spread across the lung and lead to acute respiratory distress syndrome (ARDS) in severe cases. Post-exposure prophylaxis has shown great potential to prevent the transmission of some viral infections; however, such results for COVID-19 are still inconclusive. Methods: Therefore, the aim of this study was to systematically review the resources that utilized postexposure prophylaxis (PEP) for COVID-19 and the possible clinical benefits of such drugs. An organized search of relevant literature was done using the keywords and search queries on public databases of Cochrane, PubMed, Web of Science and Scopus from December 2019 to August 23, 2021. Original resources that had the inclusion criteria were included after two-phase title/abstract and full-text screenings. This review adhered to the Preferred Reporting Items for Systematic Reviews and MetaAnalysis (PRISMA) statement. Results: Out of 841 retrieved records 17 resources were appropriate to include in the systematic review. Hydroxychloroquine with a daily dose of 400-800 mg and a duration of 5-14 days was the most frequently used agent for PEP. Chloroquine was recommended to use to control treatment in patients with mild to severe COVID-19 pneumonia. Other agents like Lopinavir-ritonavir (LPV/r), angiotensinconverting enzyme inhibitors (ACEIs), Angiotensin receptor blockers (ARBs), Vitamin D, arbidol, thymosin drugs, and Xin guan no.1 (XG.1, a Chinese formula medicine) have also been applied in some studies. Conclusion: Current evidence demonstrated no established clinical benefits of any drug as PEP in individuals with COVID-19. However, scarce indication occurs for the beneficial effects of some agents, but more studies are needed to explore such effects.

Introduction: The accurate number of COVID-19 cases is essential knowledge to control an epidemic. Currently, one of the most important obstacles in estimating the exact number of COVID-19 patients is the absence of typical clinical symptoms in a large number of people, called asymptomatic infections. In this systematic review, we included and evaluated the studies mainly focusing on the prediction of undetected COVID-19 incidence and mortality rates as well as the reproduction numbers, utilizing various mathematical models. Methods: This systematic review aims to investigate the estimating methods of undetected infections in the COVID-19 outbreak. Databases of PubMed, Web of Science, Scopus, Cochrane, and Embase, were searched for a combination of keywords. Applying the inclusion/ exclusion criteria, all retrieved English literature by April 7, 2022, were reviewed for data extraction through a two-step screening process; first, titles/ abstracts, and then full-text. This study is consistent with the PRISMA checklist. Results: In this study, 61 documents were retrieved using a systematic search strategy. After an initial review of retrieved articles, 6 articles were excluded and the remaining 55 articles met the inclusion criteria and were included in the final review. Most of the studies used mathematical models to estimate the number of underreported asymptomatic infected cases, assessing incidence and prevalence rates more precisely. The spread of COVID-19 has been investigated using various mathematical models. The output statistics were compared with official statistics obtained from different countries. Although the number of reported patients was lower than the estimated numbers, it appeared that the mathematical calculations could be a useful measure to predict pandemics and proper planning. Conclusion: In conclusion, our study demonstrates the effectiveness of mathematical models in unraveling the true burden of the COVID-19 pandemic in terms of more precise, and accurate infection and mortality rates, and reproduction numbers, thus, statistical mathematical modeling could be an effective tool for measuring the detrimental global burden of pandemic infections. Additionally, they could be a really useful method for future pandemics and would assist the healthcare and public health systems with more accurate and valid information.