Browsing by Subject "SARS-CoV-2"
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Item A Computational Modeling Study of COVID-19 in Bangladesh(The American Society of Tropical Medicine and Hygiene, 2020-11-02) Khan, Irtesam Mahmud; Haque, Ubydul; Kaisar, Samiha; Rahman, Mohammad SohelThe COVID-19 pandemic has spread globally. Only three cases in Bangladesh were reported on March 8, 2020. Here, we aim to predict the epidemic progression for 1 year under different scenarios in Bangladesh. We extracted the number of daily confirmed cases from March 8 to July 20, 2020. We considered the suspected-infected-removed (SIR) model and performed a maximum likelihood-based grid search to determine the removal rate (). The transmission was modeled as a stochastic random walk process, and sequential Monte Carlo simulation was run 100 times with bootstrap fits to infer the transmission rate (beta) and R t. According to the simulation, the (real) peak daily incidence of 3,600 would be followed by a steady decline, reaching below 1,000 in late January 2021. Thus, the model predicted that there would still be more than 300 cases/day even after a year. However, with proper interventions, a much steeper decline would be achieved following the peak. If we apply a combined (0.8beta, 1.2) intervention, there would be less than 100 cases by mid-October, only around five odd cases at the beginning of the year 2021, and zero cases in early March 2021. The predicted total number of deaths (in status quo) after 1 year would be 8,533 which would reduce to 3,577 if combined (0.8beta, 1.2) intervention is applied. We have also predicted the ideal number of tests that Bangladesh should perform and based on that redid the whole simulation. The outcome, though worse, would be manageable with interventions according to the simulation.Item Direct-to-Consumer Sexually Transmitted Infection Testing Services: A Position Statement from the American Sexually Transmitted Diseases Association(Wolters Kluwer Health, Inc., 2021-11-01) Exten, Cara; Pinto, Casey N.; Gaynor, Anne M.; Meyerson, Beth; Griner, Stacey B.; Van Der Pol, Barbara; Board of Directors of the American Sexually Transmitted Diseases, AssociationABSTRACT: Direct-to-consumer test services have gained popularity for sexually transmitted infections in recent years, with substantially increased use as a result of the SARS-CoV-2 (CoVID-19) global pandemic. This method of access has been variously known as "self-testing," "home testing," and "direct access testing." Although these online services may be offered through different mechanisms, here we focus on those that are consumer-driven and require self-collected samples, and sample shipment to a centralized laboratory without involvement of health care providers and/or local health departments. We provide the American Sexually Transmitted Diseases Association's position on utilization of these services and recommendations for both consumers and health care providers.Item Short-term forecasting of the COVID-19 outbreak in India(Oxford University Press, 2021-06-05) Mangla, Sherry; Pathak, Ashok Kumar; Arshad, Mohd; Haque, UbydulAs the outbreak of coronavirus disease 2019 (COVID-19) is rapidly spreading in different parts of India, a reliable forecast for the cumulative confirmed cases and the number of deaths can be helpful for policymakers in making the decisions for utilizing available resources in the country. Recently, various mathematical models have been used to predict the outbreak of COVID-19 worldwide and also in India. In this article we use exponential, logistic, Gompertz growth and autoregressive integrated moving average (ARIMA) models to predict the spread of COVID-19 in India after the announcement of various unlock phases. The mean absolute percentage error and root mean square error comparative measures were used to check the goodness-of-fit of the growth models and Akaike information criterion for ARIMA model selection. Using COVID-19 pandemic data up to 20 December 2020 from India and its five most affected states (Maharashtra, Karnataka, Andhra Pradesh, Tamil Nadu and Kerala), we report 15-days-ahead forecasts for cumulative confirmed cases and the number of deaths. Based on available data, we found that the ARIMA model is the best-fitting model for COVID-19 cases in India and its most affected states.Item The Disproportionate Impact of COVID-19 among Undocumented Immigrants and Racial Minorities in the US(MDPI, 2021-12-02) Hasan Bhuiyan, Mohammad Tawhidul; Mahmud Khan, Irtesam; Rahman Jony, Sheikh Saifur; Robinson, Renee; Nguyen, Uyen-Sa D.T.; Keellings, David; Rahman, M. Sohel; Haque, UbydulSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for coronavirus disease 2019 (COVID-19), has had an unprecedented effect, especially among under-resourced minority communities. Surveillance of those at high risk is critical for preventing and controlling the pandemic. We must better understand the relationships between COVID-19-related cases or deaths and characteristics in our most vulnerable population that put them at risk to target COVID-19 prevention and management efforts. Population characteristics strongly related to United States (US) county-level data on COVID-19 cases and deaths during all stages of the pandemic were identified from the onset of the epidemic and included county-level socio-demographic and comorbidities data, as well as daily meteorological modeled observation data from the North American Regional Reanalysis (NARR), and the NARR high spatial resolution model to assess the environment. Advanced machine learning (ML) approaches were used to identify outbreaks (geographic clusters of COVID-19) and included spatiotemporal risk factors and COVID-19 vaccination efforts, especially among vulnerable and underserved communities. COVID-19 outcomes were found to be negatively associated with the number of people vaccinated and positively associated with age, the prevalence of cardiovascular disease, diabetes, and the minority population. There was also a strong positive correlation between unauthorized immigrants and the prevalence of COVID-19 cases and deaths. Meteorological variables were also investigated, but correlations with COVID-19 were relatively weak. Our findings suggest that COVID-19 has had a disproportionate impact across the US population among vulnerable and minority communities. Findings also emphasize the importance of vaccinations and tailored public health initiatives (e.g., mask mandates, vaccination) to reduce the spread of COVID-19 and the number of COVID-19 related deaths across all populations.Item The impact of COVID-19 on globalization(Elsevier Inc., 2020-10-13) Shrestha, Nistha; Shad, Muhammad Yousaf; Ulvi, Osman; Khan, Modasser Hossain; Karamehic-Muratovic, Ajlina; Nguyen, Uyen-Sa; Baghbanzadeh, Mahdi; Wardrup, Robert; Aghamohammadi, Nasrin; Cervantes, Diana; Nahiduzzaman, Kh Md; Zaki, Rafdzah Ahmad; Haque, UbydulGlobalization has altered the way we live and earn a livelihood. Consequently, trade and travel have been recognized as significant determinants of the spread of disease. Additionally, the rise in urbanization and the closer integration of the world economy have facilitated global interconnectedness. Therefore, globalization has emerged as an essential mechanism of disease transmission. This paper aims to examine the potential impact of COVID-19 on globalization and global health in terms of mobility, trade, travel, and countries most impacted. The effect of globalization were operationalized in terms of mobility, economy, and healthcare systems. The mobility of individuals and its magnitude was assessed using airline and seaport trade data and travel information. The economic impact was measured based on the workforce, event cancellations, food and agriculture, academic institutions, and supply chain. The healthcare capacity was assessed by considering healthcare system indicators and preparedness of countries. Utilizing a technique for order of preference by similarity to ideal solution (TOPSIS), we calculated a pandemic vulnerability index (PVI) by creating a quantitative measure of the potential global health. The pandemic has placed an unprecedented burden on the world economy, healthcare, and globalization through travel, events cancellation, employment workforce, food chain, academia, and healthcare capacity. Based on PVI results, certain countries were more vulnerable than others. In Africa, more vulnerable countries included South Africa and Egypt; in Europe, they were Russia, Germany, and Italy; in Asia and Oceania, they were India, Iran, Pakistan, Saudi Arabia, and Turkey; and for the Americas, they were Brazil, USA, Chile, Mexico, and Peru. The impact on mobility, economy, and healthcare systems has only started to manifest. The findings of this study may help in the planning and implementation of strategies at the country level to help ease this emerging burden.Item The Many Faces of Innate Immunity in SARS-CoV-2 Infection(MDPI, 2021-06-04) Hanan, Nicholas; Doud, Ronnie L., Jr.; Park, In-Woo; Jones, Harlan P.; Mathew, Stephen O.The innate immune system is important for initial antiviral response. SARS-CoV-2 can result in overactivity or suppression of the innate immune system. A dysregulated immune response is associated with poor outcomes; with patients having significant Neutrophil-to-Lymphocyte ratios (NLR) due to neutrophilia alongside lymphopenia. Elevated interleukin (IL)-6 and IL-8 leads to overactivity and is a prominent feature of severe COVID-19 patients. IL-6 can result in lymphopenia; where COVID-19 patients typically have significantly altered lymphocyte subsets. IL-8 attracts neutrophils; which may play a significant role in lung tissue damage with the formation of neutrophil extracellular traps leading to cytokine storm or acute respiratory distress syndrome. Several factors like pre-existing co-morbidities, genetic risks, viral pathogenicity, and therapeutic efficacy act as important modifiers of SARS-CoV-2 risks for disease through an interplay with innate host inflammatory responses. In this review, we discuss the role of the innate immune system at play with other important modifiers in SARS-CoV-2 infection.