Number Of COVID-19 Deaths Research Articles

Long-term exposure to fine particulate matter air pollution: An ecological study of its effect on COVID-19 cases and fatality in Germany

BackgroundCOVID-19 is a lung disease, and there is medical evidence that air pollution is one of the external causes of lung diseases. Fine particulate matter is one of the air pollutants that damages pulmonary tissue. The combination of the coronavirus and fine particulate matter air pollution may exacerbate the coronavirus’ effect on human health. Research questionThis paper considers whether the long-term concentration of fine particulate matter of different sizes changes the number of detected coronavirus infections and the number of COVID-19 fatalities in Germany. Study designData from 400 German counties for fine particulate air pollution from 2002 to 2020 are used to measure the long-term impact of air pollution. Kriging interpolation is applied to complement data gaps. With an ecological study, the correlation between average particulate matter air pollution and COVID-19 cases, as well as fatalities, are estimated with OLS regressions. Thereby, socioeconomic and demographic covariates are included. Main findingsAn increase in the average long-term air pollution of 1 μg/m3 particulate matter PM2.5 is correlated with 199.46 (SD = 29.66) more COVID-19 cases per 100,000 inhabitants in Germany. For PM10 the respective increase is 52.38 (SD = 12.99) more cases per 100,000 inhabitants. The number of COVID-19 deaths were also positively correlated with PM2.5 and PM10 (6.18, SD = 1.44, respectively 2.11, SD = 0.71, additional COVID-19 deaths per 100,000 inhabitants). ConclusionLong-term fine particulate air pollution is suspected as causing higher numbers of COVID-19 cases. Higher long-term air pollution may even increase COVID-19 death rates. We find that the results of the correlation analysis without controls are retained in a regression analysis with controls for relevant confounding factors. Nevertheless, additional epidemiological investigations are required to test the causality of particulate matter air pollution for COVID-19 cases and the severity.

The interplay between partisanship, forecasted COVID-19 deaths, and support for preventive policies

The COVID-19 pandemic is a global crisis that has forced governments around the world to implement large-scale interventions such as school closures and national lockdowns. Previous research has shown that partisanship plays a major role in explaining public attitudes towards these policies and beliefs about the intensity of the crisis. However, it remains unclear whether and how partisan differences in policy support relate to partisan gaps in beliefs about the number of deaths that the pandemic will cause. Do individuals who forecast fewer COVID-19 deaths show less agreement with preventive measures? How does partisanship correlate with people’s beliefs about the intensity of the crisis and their support for COVID-19 policies? Here, we sought to answer these questions by performing a behavioral experiment in Argentina (Experiment 1, N = 640) and three quasi-replication studies in Uruguay (Experiment 2, N = 372), Brazil (Experiment 3, N = 353) and the United States (Experiment 4, N = 630). In all settings, participants forecasted the number of COVID-19 deaths in their country after considering either a high or low number, and then rated their agreement with a series of interventions. This anchoring procedure, which experimentally induced a large variability in the forecasted number of deaths, did not modify policy preferences. Instead, each experiment provided evidence that partisanship was a key indicator of the optimism of forecasts and the degree of support for COVID-19 policies. Remarkably, we found that the number of forecasted deaths was robustly uncorrelated with participants’ agreement with preventive measures designed to prevent those deaths. We discuss these empirical observations in the light of recently proposed theories of tribal partisan behavior. Moreover, we argue that these results may inform policy making as they suggest that even the most effective communication strategy focused on alerting the public about the severity of the pandemic would probably not translate into greater support for COVID-19 preventive measures.

Estimating COVID-19 mortality in Italy early in the COVID-19 pandemic

Estimating rates of COVID-19 infection and associated mortality is challenging due to uncertainties in case ascertainment. We perform a counterfactual time series analysis on overall mortality data from towns in Italy, comparing the population mortality in 2020 with previous years, to estimate mortality from COVID-19. We find that the number of COVID-19 deaths in Italy in 2020 until September 9 was 59,000–62,000, compared to the official number of 36,000. The proportion of the population that died was 0.29% in the most affected region, Lombardia, and 0.57% in the most affected province, Bergamo. Combining reported test positive rates from Italy with estimates of infection fatality rates from the Diamond Princess cruise ship, we estimate the infection rate as 29% (95% confidence interval 15–52%) in Lombardy, and 72% (95% confidence interval 36–100%) in Bergamo.

Construction of a demand and capacity model for intensive care and hospital ward beds, and mortality from COVID-19

BackgroundThis paper describes a model for estimating COVID-19 related excess deaths that are a direct consequence of insufficient hospital ward bed and intensive care unit (ICU) capacity.MethodsCompartmental models were used to estimate deaths under different combinations of ICU and ward care required and received in England up to late April 2021. Model parameters were sourced from publicly available government information and organisations collating COVID-19 data. A sub-model was used to estimate the mortality scalars that represent increased mortality due to insufficient ICU or general ward bed capacity. Three illustrative scenarios for admissions numbers, ‘Optimistic’, ‘Middling’ and ‘Pessimistic’, were modelled and compared with the subsequent observations to the 3rd February.ResultsThe key output was the demand and capacity model described. There were no excess deaths from a lack of capacity in the ‘Optimistic’ scenario. Several of the ‘Middling’ scenario applications resulted in excess deaths—up to 597 deaths (0.6% increase) with a 20% reduction compared to best estimate ICU capacity. All the ‘Pessimistic’ scenario applications resulted in excess deaths, ranging from 49,178 (17.0% increase) for a 20% increase in ward bed availability, to 103,735 (35.8% increase) for a 20% shortfall in ward bed availability. These scenarios took no account of the emergence of the new, more transmissible, variant of concern (b.1.1.7).ConclusionsMortality is increased when hospital demand exceeds available capacity. No excess deaths from breaching capacity would be expected under the ‘Optimistic’ scenario. The ‘Middling’ scenario could result in some excess deaths—up to a 0.7% increase relative to the total number of deaths. The ‘Pessimistic’ scenario would have resulted in significant excess deaths. Our sensitivity analysis indicated a range between 49,178 (17% increase) and 103,735 (35.8% increase). Given the new variant, the pessimistic scenario appeared increasingly likely and could have resulted in a substantial increase in the number of COVID-19 deaths. In the event, it would appear that capacity was not breached at any stage at a national level with no excess deaths. it will remain unclear if minor local capacity breaches resulted in any small number of excess deaths.

Estimación del número de muertes evitables por COVID-19 en relación con las medidas restrictivas adoptadas en América

Introduction: In America, the United States was particularly affected by the COVID-19 pandemic. Objectives: To estimate how many daily COVID-19 deaths per 100,000 population would have been avoided if each one of five restrictive measures had been implemented at the time of diagnosis and to estimate a multiple linear regression model predictive of the number of deaths per 100,000 population based on the measures adopted by the countries. Methods: A simple linear regression was performed between the days elapsed since the first COVID-19 diagnosed case and the implementation of each of the five restrictive measures by the 27 American countries studied and the number of COVID-19 deaths per 100,000 population. Results: For each day between the first COVID-19 reported case and the adoption of restrictive measures, between 0.250 (p = 0.021) and 0.600 (p = 0.001) patients per 100,000 population died, depending on the measure in question. Conclusions: Adoption of restrictive measures and social distancing are necessary for reducing the number of people infected with COVID-19 and their mortality. In addition, promptness of their establishment is essential in order to reduce the number of deaths.

Estimación del número de fallecimientos evitables por COVID-19 en relación con las medidas restrictivas adoptadas en Europa

Introduction: In December 2019, a new coronavirus emerged in Wuhan, China, which has become a global health problem. Objectives: To estimate how many daily COVID-19 deaths per 100,000 population could have been avoided if each one of five restrictive measures had been implemented at the time the first case was diagnosed, and to estimate a multiple linear regression model predictive of the number of deaths per 100,000 population. Methods: A simple linear regression was performed between the days elapsed since the first COVID-19 diagnosed case, implementation of each one of the five restrictive measures carried out by the 39 European studied countries, the number of hospital beds per 1,000 population (independent variables) and the number of COVID-19 deaths per 100,000 population. Results: For each day elapsed from the first COVID-19 reported case to the adoption of restrictive measures, between 0.611 (p = 0.004) and 1.863 (p = 0.000) patients died per 100,000 population, depending on the implemented measure. Conclusions: Restrictive measures and social distancing, as well as promptness of their implementation, are necessary for achieving a decrease in COVID-19 infections and mortality.

The role of social capital in COVID-19 deaths

BackgroundThe COVID-19 pandemic has shown a continuously increasing trend with a large variation in the number of COVID-19 deaths across countries. In response, many countries have implemented non pharmaceutical methods of intervention, such as social distancing and lockdowns. This study aims to investigate the relationship of four dimensions of social capital (community attachment, social trust, family bond, and security) and several control variables with COVID-19 deaths.MethodsWe retrieved data from open access databases and a survey. COVID-19 death-related data were collected from the website “Centre for Systems Science and Engineering (CSSE) at Johns Hopkins University”. Social capital-related data were collected from a large-scale survey that included web-based and face-to-face surveys covering 100,956 respondents across all regions/provinces/states of 37 countries in 2017. Data regarding population density, number of hospital beds, and population aged 65 or older were retrieved from the World Development Indicators (WDIs). Data on country lockdowns were obtained from the website “National responses to the 2019-20 coronavirus pandemic”. Linear regressions were applied to identify the relationship between social capital and COVID-19 deaths.ResultsWe found that COVID-19 deaths were associated with social capital both positively and negatively. Community attachment and social trust were associated with more COVID-19 deaths, and family bond and security were associated with fewer deaths. COVID-19 deaths were positively associated with population density, ageing population, and interactions between four dimensions of social capital-related factors and the ageing population. Furthermore, the number of hospital beds and early lockdown policy were negatively associated with COVID-19 deaths.ConclusionsThe results indicate that the role of social capital in dynamically evolving threats, such as the current COVID-19 pandemic, is not always negative or positive. Therefore, people’s behaviour should be changed to support countries’ response to the COVID-19 threat.

COVID-19-Related Mortality across the Gulf Cooperation Council Countries: Based on Countries’ Available Data Up to November, 2020

Background: The world has endured a high burden of mortality and morbidity due to Covid-19 over the last year. There may be factors that account for differences in mortality rates. The Gulf Corporation Council (GCC) countries share similar cultural identities, socioeconomic conditions, population structure and display similar health-status composition of their population. There is a demand for data on the differentials of the COVID-19 pandemic across all countries. This statistical analysis primarily compared the crude mortality rates, and estimates the relative risk of COVID-19 death rates across the GCC countries using longitudinal study design.
 Methods: This statistical analysis used downloaded data from Our World in Data, which was last updated on November 19, 2020. We computed COVID-19 crude mortality rates for the GCC countries individually. We estimated COVID-19 death rates for the GCC countries and compared them to the reference largest country Saudi Arabia. To adjust for most relevant confounding factors for COVID-19 deaths, a Poisson mixed effect regression model was fitted with COVID-19 new cases and the number test per case as fixed effect predictors of COVID-19 deaths. 
 Results: The estimated relative risk of COVID-19 deaths rates for UAE and Qatar was 0.352 (95% CI: 0.220-0.564, p-value <0.001) and 0.467 (95% CI: 0.287-0.762, p-value = 0.002), respectively, showing 64.8% and 53.3% fewer COVID-19 death rates compared to Saudi Arabia, individually. No statistically significant difference was found between Bahrain, Kuwait and Oman as compared with Saudi Arabia.
 Conclusion: The UAE has the lowest COVID-19 death rate among any other GCC countries, followed by Qatar. In addition, the number of tests per case were negatively associated with the number of Covid-19 deaths. Besides, the number of new COCID-19 infections relative to the number of patients correlates with the number of patient deaths.

Perspectives on Fewer Sars-2 Corona virus (COVID-19) Deaths in Africa

Globally, more than two million people, about 53,000 in Africa have died from COVID-19 infection. By any metric, Africa has so far fared better than most parts of the world including, some of the most developed and affluent nations like the United States of America in the fight to contain the COVID-19 pandemic. Analysis of published COVID-19 data shows that Africa, with a population four times greater than that of the United States recorded forty times less number of positive cases and at least thirty fold decrease in the number of COVID-19 deaths. The data also demonstrates that the population case positivity and fatality rates in Europe are respectively ~24 and ~23 folds greater than those of Africa. The vast disparity in the metrics between advanced nations in Europe and the United States, with substantial healthcare budgets and the developing nations of Africa is worth examining. In this article, we offer some perspectives to explain Africa’s low case positivity and death rates from COVID-19 infections. While many factors contribute to the world’s collective vulnerability to the pandemic, structural, demographic and sound public health policy together are essential in fighting off the disease.

Violence and COVID-19 across the Globe.

Violence and COVID-19 across the Globe Virginia Brennan, PhD, MAEditor, JHCPU As the summer of 2021 simmers on, JHCPU again publishes a large collection of papers delving into the complex sea of health inequities. In this Note, to stand in for the large array of topics the issue covers, I highlight a small selection, two papers concerning violence, two on COVID-19, and two concerning sub-Saharan African nations. Violence courses through American society unabated, rising exponentially over time. Much of this is gun violence, and virtually all of it inflicts both physical and mental trauma. The first highlighted paper on violence is by Corbin et al., who worked with 88 survivors of violent assault (gunshot, stabbing, or assault) who had presented to emergency rooms within the previous month, administering clinical scales for PTSD (PCL-5), depression (PHQ-8), and sleep (PROMIS®) to evaluate the mental health sequelae of violence. They report, "High proportions of participants met criteria for prospective PTSD (59.1%), major depression (44.3%) or disordered sleep (34.1%), with 27.3% meeting criteria for all three conditions." The authors conclude that survivors of violence should routinely be assessed for these conditions and referred for treatment as needed. This work serves as a powerful reminder of the seen and unseen damage inflicted by violence. Maternal morbidity as a term of art in public health refers to death due to complications from pregnancy or childbirth and does not encompass deaths due to "accidental or incidental" causes, specifically homicide, suicide, substance overdose, and motor vehicle accidents. As Bright et al. report, such traumatic causes of maternal death (death during pregnancy and a brief neonatal period) are far more common than medical causes of maternal death. Furthermore, pregnancy appears to be a time of increased vulnerability to violence; the authors note that in the U.S. in 2015, "4% of all deaths of women of reproductive age were attributed to homicide, but between 8% and 13% of maternal deaths were attributed to homicide." An underlying implication, on my reading, is advice something like this: "If you want to talk about major causes of maternal mortality, then talk about guns, drugs, and cars." The authors argue for three practical steps to reduce these traumatic causes of maternal death. COVID-19 continues its battle with the world population over 20 months since its inception. I highlight two of a number of papers in this issue concerning the pandemic. The first concerns Centers for Independent Living, federally-funded, community-based organizations designed and operated by people with disabilities. Centers for Independent Living initiatives include individual and systems advocacy, peer support, information and referral, independent living skills training, and transition services. Kennedy and colleagues surveyed 144 Center for Independent Living administrators and staff concerning what is needed by people with disabilities during the COVID-19 [End Page ix] pandemic. The strongest outcome recalls a refrain so often heard during crises: This emergency has laid bare the already over-burdened lives of a group of people most at risk, in this case people with disabilities. What the people with disabilities need during the pandemic is what they have always needed, but more so: health and safety, long-term supportive services, and reduction of social isolation and economic insecurity. Hernandez Caceres and colleagues analyzed the time series of daily cases in the World Health Organization African Region (WHOAR) from February 26th to December 29th, 2020. They provide an overview of the first wave (peaking around July 20th, 2020) and the second wave (either ongoing or having given way to a third wave) across WHOAR. The authors also provide basic reproduction numbers for the virus in WHOAR. Editor's note: By July 2021, both the number of confirmed cases and the number of COVID-19 deaths in sub-Saharan Africa have exceeded the predictions for August 2021 made by these models. The Literature Review by Abasse et al. might better be classified as a policy brief. It concerns the health system and the health status of the citizens of a particular sub-Saharan country—Comoro Islands—in systematic comparison with those of its neighbors, Mauritius and Seychelles. The Comoros, which was colonized by the French...

Epidemiological characteristics, reinfection possibilities and vaccine development of SARS CoV2: A global review.

According to the World Health Organization (WHO), there are 37,704,153 cases and 10,79,029 deaths due to COVID-19 till the 13th October 2020 in the world. Day by day, rise in the number of COVID-19 deaths has created great pressure on health facilities, governmental bodies, and health workers. There is a need for knowledge regarding lifecycle, transmission, and different strains of SARSCoV2, so that countries can stop the disease as early as possible. The present study was conducted to review various epidemiological aspects along with measures used in the containment and prevention of this new pandemic. The scientific literature database was searched using the terms: coronavirus, 2019-nCoV, SARSCoV2, and COVID-19. Articles with appropriate topics fulfilling the objective of the present work were included. The epidemiological characteristics regarding life-cycle, intermediate hosts, viability on various surfaces, strains, case fatality rate, and their implication to reduce the transmission of SARSCoV2 have been identified. According to Centers for Disease Control and Prevention, Atlanta (updated till October 05, 2020) people with recurrent or persistent positive COVID-19 tests in South Korea and USA did not show to have live virus in their bodies. As per WHO web-page information till 15 October 2020, there were 42 candidate vaccines in clinical evaluation and 156 vaccines are in preclinical evaluation phase. As the virus can easily be transmitted to the people either via droplets, fomites, and may be via the fecal–oral route, knowledge regarding the above-mentioned areas is needed for time to be prepared for the next waves of the COVID-19 pandemic.

COVID-19 Induced Economic Uncertainty: A Comparison between the United Kingdom and the United States

The purpose of this study is to investigate the effects of the COVID-19 pandemic on economic policy uncertainty in the US and the UK. The impact of the increase in COVID-19 cases and deaths in the country and the increase in the number of cases and deaths outside the country may vary. To examine this, the study employs the bootstrap ARDL cointegration approach from March 8, 2020 to May 24, 2020. According to the bootstrap ARDL results, a long-run equilibrium relationship is confirmed for five out of the ten models. The long-term coefficients obtained from the ARDL models suggest that an increase in COVID-19 cases and deaths outside of the UK and the US has a significant effect on economic policy uncertainty. The US is more affected by the increase in the number of COVID-19 cases. The UK, on the other hand, is more negatively affected by the increase in the number of COVID-19 deaths outside the country than the increase in the number of cases. Moreover, another significant finding from the study demonstrates that COVID-19 is a factor of great uncertainty for both countries in the short-term.

Correlation of subway turnstile entries and COVID-19 incidence and deaths in New York City.

In this paper, we show a strong correlation between turnstile entries data of the New York City (NYC) subway provided by NYC Metropolitan Transport Authority and COVID-19 deaths and cases reported by the NYC Department of Health from March to May 2020. This correlation is obtained through linear regression and confirmed by the prediction of the number of deaths by a Long Short-Term Memory neural network. The correlation is more significant after considering incubation and symptomatic phases of this disease as experienced by people who died from it. We extend the analysis to each individual NYC borough. We also estimate the dates when the number of COVID-19 deaths and cases would approach zero by using the Auto-Regressive Integrated Moving Average model on the reported deaths and cases. We also backward forecast the dates when the first cases and deaths might have occurred.

Infection fatality risk for SARS-CoV-2 in community dwelling population of Spain: nationwide seroepidemiological study

ObjectiveTo estimate the infection fatality risk for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), based on deaths with confirmed coronavirus disease 2019 (covid-19) and excess deaths from all causes.DesignNationwide seroepidemiological...

Abstract 226: Statewide Out-of-hospital Cardiac Arrest During the Covid-19 Pandemic

Introduction: Little is known about statewide out-of-hospital cardiac arrests (OOHCA) during a global pandemic. Objective: To characterize the impact of the COVID-19 pandemic on state OOHCA rates. Methods: Data for non-traumatic, OOHCA were obtained and analyzed from a statewide EMS information system from March 1, 2000 to May 31, 2020 (pandemic) and compared to data obtained from the same 3-month period the prior year (control). Analysis occurred using a web-based application designed to analyze state EMS data. OOHCA were identified using a validated data filter applied to 911 calls and limited to transporting EMS units. Shockable OOHCA and arrests occurring in 5 counties with the highest number of COVID-19 deaths during the pandemic were also analyzed. Results: There were 4,665 OOHCAs identified during the pandemic compared to 3,261 OOHCA during the control period, a 43.1% increase (p<0.00001). Bystander AED use (10% vs 10%), bystander CPR (38% vs. 38%), and bystander witnessed arrests (34% and 33%) were similar. Rates of EMS termination of resuscitation (TOR) were higher (59% vs. 47%), while endotracheal intubation (ETI) (12% vs. 31%), and ROSC (5% vs. 8%) were lower during the COVID-19 period. Blacks had a higher rate of OOHCA during the pandemic period (26.6% vs 18.6%, p<0.00001). Overall shockable OOHCA increased by 14.8% (403 vs. 351, p=0.002) during the pandemic. Bystander AED use (10% vs 11%), bystander CPR (55% vs. 51%), and bystander witnessed (71% and 71%) were similar. Rates of field TOR were 33% vs. 24%, ETI were 14% vs. 31%, and ROSC were 16% vs. 17%. Within the 5 highest impact counties total OOHCA increased by 61.4% (2,702 vs. 1,674, p<0.00001) and shockable OOHCAs increased by 21.4% (207 vs 170, p=0.004). Conclusions: OOHCA and shockable OOHCA increased during the COVID-19 pandemic statewide and to a higher degree in the 5 high impact counties. Little change was noted in rates of bystander AED use, CPR, and witnessed arrests. EMS TOR rates increased while ETI rates decreased. ROSC rates decreased in the overall OOHCA group but were not significantly changed in shockable OOHCA. OOHCA involving the black race occurred more frequently. Further research is warranted to understand the causes of these observations.

All-cause mortality supports the COVID-19 mortality in Belgium and comparison with major fatal events of the last century

BackgroundThe COVID-19 mortality rate in Belgium has been ranked among the highest in the world. To assess the appropriateness of the country’s COVID-19 mortality surveillance, that includes long-term care facilities deaths and deaths in possible cases, the number of COVID-19 deaths was compared with the number of deaths from all-cause mortality. Mortality during the COVID-19 pandemic was also compared with historical mortality rates from the last century including those of the Spanish influenza pandemic.MethodsExcess mortality predictions and COVID-19 mortality data were analysed for the period March 10th to June 21st 2020. The number of COVID-19 deaths and the COVID-19 mortality rate per million were calculated for hospitals, nursing homes and other places of death, according to diagnostic status (confirmed/possible infection). To evaluate historical mortality, monthly mortality rates were calculated from January 1900 to June 2020.ResultsNine thousand five hundred ninety-one COVID-19 deaths and 39,076 deaths from all-causes were recorded, with a correlation of 94% (Spearman’s rho, p < 0,01). During the period with statistically significant excess mortality (March 20th to April 28th; total excess mortality 64.7%), 7917 excess deaths were observed among the 20,159 deaths from all-causes. In the same period, 7576 COVID-19 deaths were notified, indicating that 96% of the excess mortality were likely attributable to COVID-19. The inclusion of deaths in nursing homes doubled the COVID-19 mortality rate, while adding deaths in possible cases increased it by 27%. Deaths in laboratory-confirmed cases accounted for 69% of total COVID-19-related deaths and 43% of in-hospital deaths. Although the number of deaths was historically high, the monthly mortality rate was lower in April 2020 compared to the major fatal events of the last century.ConclusionsTrends in all-cause mortality during the first wave of the epidemic was a key indicator to validate the Belgium’s high COVID-19 mortality figures. A COVID-19 mortality surveillance limited to deaths from hospitalised and selected laboratory-confirmed cases would have underestimated the magnitude of the epidemic. Excess mortality, daily and monthly number of deaths in Belgium were historically high classifying undeniably the first wave of the COVID-19 epidemic as a fatal event.

Delivering Systemic Anti-Cancer Treatment Via Another Route of Administration As an Option to Reduce Exposure to COVID-19 in Patients with Multiple Myeloma in the UK

Introduction:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a strain of coronavirus that causes a respiratory illness known as COVID-19. COVID-19 is a pandemic affecting many countries globally.(1) As of 23rd July 2020, there have been 297,146 lab-confirmed cases of COVID-19 in the UK and 45,554 people who tested positive for the virus have died.(2) Patients with multiple myeloma (MM) are at a higher risk of contracting the virus and experiencing more severe outcomes.(3-6) The higher risk is driven by a compromised immune system, the use of immunosuppressive agents and patient characteristics aligning with key risk factors - patients with MM are often elderly and have multiple co-morbidities.(7) In light of the COVID-19 outbreak, NHS England and NICE have issued guidance to modify usual care to reduce patient exposure to COVID-19. For patients with cancer, NICE recommend delivering systemic anti-cancer treatment in different and less immunosuppressive regimens, different locations (ideally at home) or via another (less invasive and/or less resource intensive) route of administration where possible.(8)(9)The objective of this analysis is to explore the impact of switching patients from intravenous (IV) treatments requiring hospital administrations to subcutaneous (SC) or oral alternatives which can be administered at home or in an outpatient setting which reduces the patient's potential exposure to COVID-19.Methods:A decision tree model was developed in Microsoft Excel® (Figure 1). Patients enter the model and are assigned a probability of being treated; those that are treated are then assigned a probability of IV, SC or oral-based therapy. Based on the route of administration, patients are assigned a probability of contracting COVID-19 and, for those patients that do contract the virus, a probability of death from the virus is estimated. The model compares the outcomes from two identical decision trees: one informed by the pre-COVID-19 treatment pathway and one informed by the post-COVID-19 pathway. Model inputs, including COVID-19 inputs (e.g., number of active and diseased COVID-19 cases among patients with MM), have been informed by the literature and clinical opinion. Costs reflected in the model include: treatment of COVID-19, treatment for MM and administration of MM treatments. Scenario analyses explore lower and upper bounds for key inputs. Results are presented from a UK perspective and a 1-year time horizon (from model entry) is considered.Results:Per the model, treating patients with oral therapies is shown to reduce the number of COVID-19 cases and the number of COVID-19 deaths in patients with MM compared with IV- and SC-delivered therapies. These outcomes translate into cost savings driven by costs avoided in treating COVID-19. There was a limited difference in the costs of treating the underlying MM despite the switch. However, there were additional cost savings demonstrated through avoiding expensive and resource intensive administration appointments associated with IV therapies, and to a lesser extent SC therapies. The use of oral therapies has also aided the increase in telemedicine for routine appointments - scenarios exploring this demonstrate further savings. These results are driven by the perceived risk attached to each of the different routes of administration - scenario analyses demonstrated that assuming even the lower bound risk (an assumed additional risk of 10%) for IV therapies vs. oral therapies, a significant number of COVID-19 cases and deaths were avoided, and costs reduced.Conclusions:Changes to the treatment pathway for patients with MM in light of the COVID-19 pandemic aim to reduce the exposure to the virus for these patients. The model demonstrates that simply switching the route of administration can reduce the number of COVID-19 cases and deaths . This has important implications in avoiding severe outcomes, decreasing the spread of the virus and reducing the cost and resource use burden to the healthcare system. In addition, the model reflects potential efficiencies which may extend beyond the COVID-19 pandemic (e.g. telemedicine) to optimize clinical practice for patients with MM in the longer-term.DisclosuresCranmer:Takeda: Current Employment. Podkonjak:Takeda: Current Employment. Benson:Takeda: Current Employment. Dabora:Takeda: Current Employment. Jackson:Merck Sharp and Dohme: Honoraria; Chugai: Honoraria; Amgen: Honoraria; Janssen: Honoraria; Celgene: Honoraria; Takeda: Honoraria; Roche: Honoraria.

Effect of Implementation of the Lockdown on the Number of COVID-19 Deaths in Four European Countries.

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Does CAGE framework predict COVID-19 infection?

This paper identifies the national factors related to the number of COVID-19 infections and COVID-19 deaths in each country using the CAGE framework in the international business field. Multiple regression analyses are conducted at multiple time points, with the number of COVID-19 infections and COVID-19 in each country as the dependent variables and cultural factors, administrative and political factors, geographic factors, and economic factors of each country as the independent variables. The analyses reveal the following four points: (1) The cultural, geographical, and economic factors are not significantly associated with the number of COVID-19 infections or deaths. (2) The Administrative and political factors (corruption, government information policy) are negatively associated with the number of COVID-19 infections. (3) None of the factors are associated with the number of COVID-19 deaths. (4) The significance of the correlation between independent and dependent variables changes with time.

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Nursing facilities have suffered the double injury of an immediate reduction in occupancy and the reputational harm of the high number of COVID-19 deaths and infections.