Total Number Of Infections Research Articles

Substantial impact of post-vaccination contacts on cumulative infections during viral epidemics

Background: The start of 2021 was marked by the initiation of a global vaccination campaign against the novel coronavirus SARS-CoV-2. Formulating an optimal distribution strategy under social and economic constraints is challenging. Optimal distribution is additionally constrained by the potential emergence of vaccine resistance. Analogous to chronic low-dose antibiotic exposure, recently inoculated individuals who are not yet immune play an outsized role in the emergence of resistance. Classical epidemiological modelling is well suited to explore how the behavior of the inoculated population impacts the total number of infections over the entirety of an epidemic. Methods: A deterministic model of epidemic evolution is analyzed, with seven compartments defined by their relationship to the emergence of vaccine-resistant mutants and representing three susceptible populations, three infected populations, and one recovered population. This minimally computationally intensive design enables simulation of epidemics across a broad parameter space. The results are used to identify conditions minimizing the cumulative number of infections. Results: When an escape variant is only modestly less infectious than the originating strain within a naïve population, there exists an optimal rate of vaccine distribution. Exceeding this rate increases the cumulative number of infections due to vaccine escape. Analysis of the model also demonstrates that inoculated individuals play a major role in the mitigation or exacerbation of vaccine-resistant outbreaks. Modulating the rate of host–host contact for the inoculated population by less than an order of magnitude can alter the cumulative number of infections by more than 20%. Conclusions: Mathematical modeling shows that optimization of the vaccination rate and limiting post-vaccination contacts can perceptibly affect the course of an epidemic. The consideration of limitations on post-vaccination contacts remains relevant for the entire duration of any vaccination campaign including the current status of SARS-CoV-2 vaccination.

Massive Burns: Retrospective Analysis of Changes in Outcomes Indicators Across 18 Years.

The treatment and management of massive burns, defined as burns affecting at least 50% of total body surface area (TBSA), have considerably changed since the 1990s. This study aimed at analyzing if the length of intensive care unit (ICU) stay, the success of skin grafting operations, and the mortality changed in the past 18 years. Between 2000 and 2018, 77 patients were admitted for massive burns to the ICU of a university hospital. Transfers and early care withdrawal precluded inclusion for 38 patients, leaving 39 for analysis. Study variables were year of admission, demographics, burn characteristics, critical care treatment (fluid resuscitation, ventilation, and nutrition), and surgical therapy. Association between outcomes and year of admission was assessed through correlation and logistic regression analysis. Potential confounders were assessed through stepwise linear regression. Patients’ characteristics were stable over time with a median age of 36 (25.0–48.0) years, burns 65% (55.0–83.0) TBSA, and deep burns 55% (50.0–68.0) TBSA. Length of ICU stay remained stable at 0.97 (0.6–1.5) days/%TBSA. Mortality was stable as well. Energy and carbohydrate delivery decreased in parallel with the number of infectious episodes per patient. The number of operations was stable, but the take rate of skin grafts increased significantly. The multivariate analysis retained year of admission, weight, the total number of infections, daily lipid intakes, and fluid resuscitation as independent predicting variables.

Facemask and social distancing, pillars of opening up economies.

The COVID-19 pandemic has caused severe health and economic impacts globally. Strategies to safely reopen economies, travel and trade are a high priority. Until a reliable vaccine is available, non-pharmaceutical techniques are the only available means of disease control. In this paper, we aim to evaluate the extent to which social distancing (SD) and facemask (FM) use can mitigate the transmission of COVID-19 when restrictions are lifted. We used a microsimulation activity-based model for Sydney Greater Metropolitan Area, to evaluate the power of SD and FM in controlling the pandemic under numerous scenarios. The hypothetical scenarios are designed to picture feasible futures under different assumptions. Assuming that the isolation of infected cases and the quarantining of close contacts are in place, different numerical tests are conducted and a full factorial two-way MANOVA test is used to evaluate the effectiveness of the FM and SD control strategies. The main and interactive effects of the containment strategies are evaluated by the total number of infections, percentage of infections reduction, the time it takes to get the pandemic under control, and the intensity of active cases.

Epidemiological situation regarding the new type of coronavirus infection (COVID-19) among healthcare workers in the Republic of Moldova

Introduction. The emergence of the new coronavirus (SARS-CoV-2) has led to a rapid spread of the novel infection (COVID-19) worldwide. Since February 1, 2021, to date, more than 103,989,900 cases and more than 2 million deaths have been reported globally. The infection incidence and death rate among medical staff worldwide, as well as in the Republic of Moldova continues to be very high, whereas the preventive measures to prevent infections among medical staff remains imperative.
 Material and methods. Data on morbidity, incidence, prevalence and mortality of COVID-19 were analyzed and evaluated among healthcare workers, based on the selection of data from the digital information-epidemiological surveillance system of COVID-19 infection with SARS CoV-2 virus. The epidemiological methods (retrospective, prospective) recommended by WHO, CDC, ECDC were used.
 Results. Until 01.02.2021, the Republic of Moldova registered 153,371 cases of SARS-CoV-2 infection among healthcare workers, of which 4,103 were doctors, 6,406 were nurses, 4,435 were auxiliary staff, and over 70 employees of medical institutions died.
 Conclusions. The share of infection cases among medical staff accounts for 9.45% out of the total number of infections and about 39.08% of infections were registered in Chisinau. Most cases were registered among nurses (41.7%), whereas female health workers are more frequently affected (80.4%), the ratio of female to male being of 4:1.

Estimating the Cumulative Incidence of SARS-CoV-2 Infection and the Infection Fatality Ratio in Light of Waning Antibodies.

Serology tests can identify previous infections and facilitate estimation of the number of total infections. However, immunoglobulins targeting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been reported to wane below the detectable level of serologic assays (which is not necessarily equivalent to the duration of protective immunity). We estimate the cumulative incidence of SARS-CoV-2 infection from serology studies, accounting for expected levels of antibody acquisition (seroconversion) and waning (seroreversion), and apply this framework using data from New York City and Connecticut. We estimated time from seroconversion to seroreversion and infection fatality ratio (IFR) using mortality data from March to October 2020 and population-level cross-sectional seroprevalence data from April to August 2020 in New York City and Connecticut. We then estimated the daily seroprevalence and cumulative incidence of SARS-CoV-2 infection. The estimated average time from seroconversion to seroreversion was 3-4 months. The estimated IFR was 1.1% (95% credible interval, 1.0%, 1.2%) in New York City and 1.4% (1.1, 1.7%) in Connecticut. The estimated daily seroprevalence declined after a peak in the spring. The estimated cumulative incidence reached 26.8% (24.2%, 29.7%) at the end of September in New York City and 8.8% (7.1%, 11.3%) in Connecticut, higher than maximum seroprevalence measures (22.1% and 6.1%), respectively. The cumulative incidence of SARS-CoV-2 infection is underestimated using cross-sectional serology data without adjustment for waning antibodies. Our approach can help quantify the magnitude of underestimation and adjust estimates for waning antibodies.

Cross-sectional Study on Sero-Prevalence of SARS-CoV-2 Infection in Jabalpur, Madhya Pradesh, India

Introduction: In India, laboratory diagnosis of SARS - CoV-2 infection has been mostly based on real-time reverse transcriptase polymerase chain reaction (RT-PCR). Studies have shown that Viral titres peak within the first week of symptoms, but may decline post this time frame, thereby hampering RT-PCR based diagnostic strategies. These reasons have prompted the call for adoption of antibody testing as a potential source of data to address the gap in data and inform public health and governance policies oriented towards COVID-19. Materials and Methods: A Cross-sectional study with a sample size of 9000 was conducted for 11 days (Dec 11-21, 2020) including all the 79 wards under Jabalpur Municipal Corporation. Serum samples were tested for the presence of specific antibodies to COVID19 using ICMR-Kavach IgG ELISA kits. The data collected was compiled on Microsoft Excel and data analysis was carried out using STATA 15E statistical software. Result: Overall seroprevalence of the study population was found to be 28.70% (weighted). Wards of the city of Jabalpur were classified into three categories based on the case prevalence - High (27 wards), Medium (26 wards) and Low (26 wards). Based on the overall seroprevalence, the estimated number of total infections were calculated to be 3, 54,870 for the study population. Overall Case Infection Ratio was 31.41. Conclusion: The current seroprevalence study rightly provides information on proportion of the population exposed, however, the correlation between presence and absence of antibodies is not a marker of total or partial immunity. Hence, the golden rule of Social distancing, sanitization, personal protective equipment and public health measures have to be continued.

Comparison in safety of chemotherapy protocols for blood cancers: toxicity of H-CVAD versus GELA/BURKIMAB/PETHEMA LAL

Background and objectiveThe Hyper-CVAD/Methotrexate-Cytarabine (H-CVAD/MTX-AraC) chemotherapy protocol has been one of the standard treatments for blood cancers, such as Mantle cell lymphoma (MCL), Burkitt’s lymphoma (BL) and B-cell and T-cell acute lymphoblastic leukaemia (ALL). Due to high toxicity, it has been progressively replaced with new specific regimens with a better safety profile (GELA protocol for MCL, BURKIMAB for BL and PETHEMA for B-cell and T-cell ALL). The objective of this study is to analyse the toxicity and infectious complications of these therapeutic regimens, as well as the event free survival (EFS).Patients and methodsThis is a retrospective and descriptive observational study of 81 patients, comparing 42 patients treated with H-CVAD/MTX-AraC (group A) versus 39 patients treated with GELA/BURKIMAB/PETHEMA (group B).ResultsAll patients in group A developed pancytopenia, but in group B 74.4% neutropenia, 51.3% thrombocytopenia and 69.2% anaemia. The total number of infections in group A was higher than in group B: 154 versus 48, 3.67 versus 1.23 per patient and 0.59 versus 0.25 per cycle. Likewise, febrile neutropenia happened: 106 versus 21 cases, 2.52 versus 0.52 per patient and 0.41 versus 0.11 per cycle. EVS is higher in group B: 33% versus 79% (2-year), and 24% versus 69% (5-year).ConclusionsCurrent therapeutic protocols have shown higher EFS due to better safety profile, with less haematological, neurological and haemorrhagic toxicity, as well as lower rates of infectious complications.

Assessing the Risk of Salmonellosis from Consumption of Conventionally and Alternatively Produced Broiler Meat Prepared In-Home in the United States

Salmonella has long presented a major problem for the food safety of broiler meat. As the popularity of alternatively produced (e.g. organic) broiler meat increases, an understanding of the food safety risks associated with these types of products is needed. The purpose of this study was to develop a retail-to-consumption quantitative microbial risk assessment model that could be used to estimate the differences in risk of salmonellosis acquired from the consumption of conventionally and alternatively produced broiler meat in the United States annually. Data were extracted and used to define distributions that could be used to estimate Salmonella growth during retail storage, transportation, and home storage, as well as concentration changes during preparation and due to cross-contamination. A Monte Carlo simulation with 100,000 iterations was performed to estimate the risk of infection per serving and total number of infections in the United States annually from both meat types. Sensitivity analyses were performed to determine the factors that were highly correlated with increased risk of salmonellosis. Conventionally produced chicken meat was estimated to have a median risk of infection per serving of 6.4 × 10−8 and cause an average of approximately 3,880,000 infections annually compared with a median risk of infection per serving of 7.7 × 10−8 and average of approximately 641,000 estimated infections for alternatively produced chicken. The sensitivity analysis identified cross-contamination of hands during meal preparation as the most important factor linked to risk. The ‘what-if’ scenario analysis estimated that using antimicrobial soap during hand washing after handling raw chicken can reduce the risk considerably. The developed risk assessment model provides information on the public health risk of conventionally and alternatively produced broiler meat. These results will be useful in determining the key intervention strategies to mitigate the food safety risks associated with the consumption of contaminated chicken products.

Comment on “Poorly known aspects of flattening the curve of COVID-19″

This short research note describes and summarizes several recent peer-reviewed and non-peer-reviewed studies on the concept of flattening-the-curve (FTC) in the context of the COVID-19 pandemic. This note also highlights contradictory findings of these studies in terms of the effect of FTC on the total number of infections (the final epidemic size), and poses a research problem for future studies.

Estimated seroprevalence of SARS-CoV-2 antibodies among adults in Orange County, California

Clinic-based estimates of SARS-CoV-2 may considerably underestimate the total number of infections. Access to testing in the US has been heterogeneous and symptoms vary widely in infected persons. Public health surveillance efforts and metrics are therefore hampered by underreporting. We set out to provide a minimally biased estimate of SARS-CoV-2 seroprevalence among adults for a large and diverse county (Orange County, CA, population 3.2 million). We implemented a surveillance study that minimizes response bias by recruiting adults to answer a survey without knowledge of later being offered SARS-CoV-2 test. Several methodologies were used to retrieve a population-representative sample. Participants (n = 2979) visited one of 11 drive-thru test sites from July 10th to August 16th, 2020 (or received an in-home visit) to provide a finger pin-prick sample. We applied a robust SARS-CoV-2 Antigen Microarray technology, which has superior measurement validity relative to FDA-approved tests. Participants include a broad age, gender, racial/ethnic, and income representation. Adjusted seroprevalence of SARS-CoV-2 infection was 11.5% (95% CI: 10.5–12.4%). Formal bias analyses produced similar results. Prevalence was elevated among Hispanics (vs. other non-Hispanic: prevalence ratio [PR] = 1.47, 95% CI 1.22–1.78) and household income < $50,000 (vs. > $100,000: PR = 1.42, 95% CI: 1.14 to 1.79). Results from a diverse population using a highly specific and sensitive microarray indicate a SARS-CoV-2 seroprevalence of ~ 12 percent. This population-based seroprevalence is seven-fold greater than that using official County statistics. In this region, SARS-CoV-2 also disproportionately affects Hispanic and low-income adults.

An Optimal Nucleic Acid Testing Strategy for COVID-19 during the Spring Festival Travel Rush in Mainland China: A Modelling Study.

Western countries are experiencing surges in COVID-19 cases and deaths due to increasing public transportation during holiday seasons. This study aimed to explore whether mainland China will face an epidemic rebound during the Spring Festival holiday, when millions of Chinese people travel across the country, and investigate which nucleic acid testing (NAT) strategy is optimal to contain the epidemic. A microsimulation model was used to simulate SARS-CoV-2 transmission among railway travelers and evaluated the effects of various NAT strategies. An extended susceptible-exposed-infectious-recovered (SEIR) model was built to forecast local transmission during the Spring Festival period under different scenarios of testing strategies. The total number of infections, testing burden, and medical expenditure were calculated to devise an optimal strategy during the Spring Festival travel rush. Assuming the daily incidence of 20 per 10 million persons, our model simulated that there would be 97 active infections on the day of travel among 10 million railway passengers without NAT and symptom screening. Pre-travel testing could reduce the number of active infections. Compared with no NAT, testing passengers from risk tier 2–4 regions 3 days before travelling could significantly reduce the risk of transmission, and it is more economical and efficient than testing for all passengers.

Associations of exposure to perfluoroalkyl substances individually and in mixtures with persistent infections: Recent findings from NHANES 1999-2016.

Certain viruses and parasites can cause persistent infections that often co-occur and have been associated with substantial morbidity and mortality. Separate lines of research indicate exposures to per- and polyfluoroalkyl substances (PFAS) suppress the immune system. We hypothesized that PFAS exposures might systematically increase susceptibility to persistent infections resulting in a higher pathogen burden. We used data from 8778 individuals (3189 adolescents, 5589 adults) in the nationally-representative U.S. National Health and Nutrition Examination Survey (NHANES) 1999-2016 to examine cross-sectional associations between serum concentrations of four highly detected PFAS (PFOS, PFOA, PFHxS, PFNA) with the presence of antibodies to cytomegalovirus, Epstein Barr virus, hepatitis C and E, herpes simplex 1 and 2, HIV, T.gondii, and Toxocara spp. Seropositivity was summed to calculate a pathogen burden score reflecting the total number of infections. Separate survey-weighted multivariable regression models were fitted to analyze PFAS individually and quantile g-computation was used to analyze PFAS mixtures. Among adolescents, 38.7% had at least one persistent infection while 14.9% had two or more; among adults, these percentages were 48.0% and 19.7%. Each PFAS was individually associated with significantly higher pathogen burdens and the most pronounced associations were observed in adolescents [e.g., among adolescents, a doubling of PFOS was associated with 30% (95% CI: 25-36%) higher pathogen burden]. Quantile g-computation revealed PFAS mixtures as a whole were also associated with higher pathogen burdens. Taken together, these results suggest PFAS exposure may increase susceptibility to and foster the clustering of persistent infections, particularly among adolescents. Since persistent infections are important contributors to long-term health, prospective data are needed to confirm these findings.

Mobility Restrictions and the Control of COVID-19

A recent study on the impact of mobility controls on the final size of epidemics by Espinoza, Castillo-Chavez, and Perrings (2020) found that mobility restrictions between areas experiencing different levels of disease risk and with different public health infrastructures do not always reduce the final epidemic size. Indeed, restrictions on the mobility of people from high-risk to low-risk areas can increase, not reduce, the total number of infections. Since the first response of many countries to the COVID-19 pandemic was to implement mobility restrictions, it is worth bearing in mind the implications of the Espinoza result when considering the effectiveness of such restrictions.

Prevalence of Intestinal Helminthes with Respect to Age, Sex and Breeds of Chicken Slaughtered at Eke Awka Market, Awka, Anambra State, Nigeria

Aim: This research was designed to assess the prevalence of intestinal helminthes with respect to age, sex and breeds of chicken slaughtered at Eke-Awka Market, Awka, Anambra State, Nigeria.&#x0D; Methodology: Fecal specimen was obtained from 150 Chicken slaughtered at Eke-Awka, Market, Anambra State, Nigeria from August to October 2019. The Fecal specimen was processed following floatation and the formalin-ethyl acetate concentration techniques. The collected data was analyzed using descriptive statistics to get the percentage prevalence and chi-square to determine the association of prevalence in relation to age, sex and breeds of the chickens; level of significance was set at P &lt; 0.05.&#x0D; Results: Out of the 150 fecal specimens examined, 63 were found to be infected with intestinal helminthes parasites, giving a prevalence of 42%. The parasites found were Ascaridia galli, Heterakis gallinarum and Raillietina cesticillus. Raillietina cesticillus was observed to have the highest prevalence which is 16.7%. With respect to gender, a total of 38 males were found to be infected by helminthes parasites and the prevalence among males was 25.3%. Raillietina cesticillus infected the highest number of male chickens 17 (44.7%). A total of 25 female chickens were infected, with a prevalence of 16.7%, Ascaridia galli infected the highest number of female chickens 11 (44%). With respect to age groups, a total of 24 chickens aged (0 – 5) months were infected with a prevalence of 16%. Raillietina cesticillus had the highest infection rate 12 (50%). In the age group (6 – 10) months, a total of 21 chickens were infected giving a prevalence rate of 14%. Ascaridia galli recorded the highest infection rate 9 (49.9%). Among age group 11 months and above, the total number of infected chickens was 18, giving a prevalence rate of 12%. Heterakis gallinarum recorded the highest infection rate 8 (44.4%). With respect to breeds, a total of 28 old layer chickens were found to be infected by helminthes parasites and its prevalence was 18.7%, Raillietina cesticillus had the highest infection rate 13 (46.4%). The broiler had a total infection rate of 22 which gave a prevalence of 14.7%. Raillietina cesticillus had the highest infection rate of 9 (40.9%). Among the Native chickens, the total number of infections was 13 and its prevalence rate was 8.7%. Ascaridia galli recorded the highest infection rate which was 8 (61.5%).&#x0D; Conclusions: The overall prevalence of intestinal helminthes was 42%, the helminthes parasites found were Ascaridia galli, Heterakis gallinarum and Raillietina cesticillus. Raillietina cesticillus was observed to have the highest prevalence 16.7%. Government and poultry owners should ensure that good caging and management systems are adopted to prevent the spread of intestinal helminthes among chickens so as to ensure maximum output from poultry production.

COVID-19 Dynamics: A Heterogeneous Model.

The mathematical model reported here describes the dynamics of the ongoing coronavirus disease 2019 (COVID-19) epidemic, which is different in many aspects from the previous severe acute respiratory syndrome (SARS) epidemic. We developed this model when the COVID-19 epidemic was at its early phase. We reasoned that, with our model, the effects of different measures could be assessed for infection control. Unlike the homogeneous models, our model accounts for human population heterogeneity, where subpopulations (e.g., age groups) have different infection risks. The heterogeneous model estimates several characteristics of the epidemic more accurately compared to the homogeneous models. According to our analysis, the total number of infections and their peak number are lower compared to the assessment with the homogeneous models. Furthermore, the early-stage infection increase is little changed when population heterogeneity is considered, whereas the late-stage infection decrease slows. The model predicts that the anti-epidemic measures, like the ones undertaken in China and the rest of the world, decrease the basic reproductive number but do not result in the development of a sufficient collective immunity, which poses a risk of a second wave. More recent developments confirmed our conclusion that the epidemic has a high likelihood to restart after the quarantine measures are lifted.

Undetected infectives in the Covid-19 pandemic

ObjectivesEpidemiological investigations and mathematical models have revealed that the rapid diffusion of Covid-19 can mostly be attributed to undetected infective individuals who continue to circulate and spread the disease: finding their number would be of great importance in the control of the epidemic. MethodsThe dynamics of an infection can be described by the SIR model, which divides the population into susceptible (S), infective I, and removed R subjects. In particular, we exploited the Kermack-McKendrick epidemic model, which can be applied when the population is much larger than the fraction of infected subjects. ResultsWe proved that the fraction of undetected infectives, compared to the total number of infected subjects, is given by 1−1R0, where R0 is the basic reproduction number. The mean value R0=2.10 2.09-2.11 for the Covid-19 epidemic in three Italian regions yielded a percentage of undetected infectives of 52.4% (52.2%–52.6%) compared to the total number of infectives. ConclusionsOur results, straightforwardly obtained from the SIR model, highlight the role of undetected carriers in the transmission and spread of the SARS-CoV-2 infection. Such evidence strongly recommends careful monitoring of the infective population and ongoing adjustment of preventive measures for disease control until a vaccine becomes available for most of the population.

How successful have the lockdowns been in controlling the (COVID-19/SARS-CoV-2) pandemic — A simulation-based analysis

The total number of infections (epidemic size), and the time needed for the infection to die out (epidemic duration), represent two of the main indicators for the measuring gravity of infectious disease epidemics in humans. A few attempts have been made to address the problem of controlling both the epidemic size and duration simultaneously from a theoretical point of view, by primarily using the Optimal control theory. In this study, a multi-objective optimal control problem has been simulated to gauge the success of the lockdowns in India. To accomplish this objective, a system dynamics modeling was used to simulate the Susceptible–Infected–Quarantined–Removed epidemic model. A set of sensitivity experiments for different scenarios allows illustrating the model’s behavior and its value for decision-makers regarding the lockdown intensity. The simulation of the model presents various scenarios, wherein the cost–benefit analysis of lockdown was done. Notably, the lockdown success intensity was defined, post which, the findings indicate that the states of Uttar Pradesh, Kerala, Panjab, Jammu, Kashmir, Haryana, and Bihar have achieved more than 90% lockdown success intensity. Further, it was observed that these states could effectively implement lockdowns by strictly enforcing social distancing measures during the early stages of the virus spread, which in turn resulted in the high success rate of lockdowns.

A simple transmission dynamics model for predicting the evolution of COVID-19 under control measures in China.

Epidemic forecasting provides an opportunity to predict geographic disease spread and counts when an outbreak occurs and plays a key role in preventing or controlling their adverse impact. However, conventional prediction models based on complex mathematical modelling rely on the estimation of model parameters, which yields unreliable and unsustainable results. Herein, we proposed a simple model for predicting the epidemic transmission dynamics based on nonlinear regression of the epidemic growth rate and iterative methods, which is applicable to the progression of the COVID-19 outbreak under the strict control measures of the Chinese government. Our model yields reliable and accurate results as confirmed by the available data: we predicted that the total number of infections in mainland China would be 91 253, and the maximum number of beds required for hospitalised patients would be 62 794. We inferred that the inflection point (when the growth rate turns from positive to negative) of the epidemic across China would be mid-February, and the end of the epidemic would be in late March. This model is expected to contribute to resource allocation and planning in the health sector while providing a theoretical basis for governments to respond to future global health crises or epidemics.

Mathematical modelling of the spread of COVID-19 on a university campus.

In this paper we present a deterministic transmission dynamic compartmental model for the spread of the novel coronavirus on a college campus for the purpose of analyzing strategies to mitigate an outbreak. The goal of this project is to determine and compare the utility of certain containment strategies including gateway testing, surveillance testing, and contact tracing as well as individual level control measures such as mask wearing and social distancing. We modify a standard SEIR-type model to reflect what is currently known about COVID-19. We also modify the model to reflect the population present on a college campus, separating it into students and faculty. This is done in order to capture the expected different contact rates between groups as well as the expected difference in outcomes based on age known for COVID-19. We aim to provide insight into which strategies are most effective, rather than predict exact numbers of infections. We analyze effectiveness by looking at relative changes in the total number of cases as well as the effect a measure has on the estimated basic reproductive number. We find that the total number of infections is most sensitive to parameters relating to student behaviors. We also find that contact tracing can be an effective control strategy when surveillance testing is unavailable. Lastly, we validate the model using data from Villanova University's online COVID-19 Dashboard from Fall 2020 and find good agreement between model and data when superspreader events are incorporated in the model as shocks to the number of infected individuals approximately two weeks after each superspreader event.

Upper gastrointestinal bleeding in COVID-19 patients: A case series and review of the literature

ABSTRACT The novel severe acute respiratory distress syndrome coronavirus 2 was declared a pandemic by the World Health Organization in 2019. The total number of infections and mortality continue to rise globally. The pandemic has changed the face of medicine in many regards. Upper gastrointestinal bleeding (UGIB) and the provision of endoscopy poses unique challenges in these patients. We present a case series of UGIB (variceal and non-variceal) in patients with SARS-CoV-2 and review the literature to provide guidance on management.