Coronavirus Disease 2019 Related Deaths Research Articles

Mortality Rates of the Spanish Flu and Coronavirus Disease 2019 in the Netherlands: A Historical Comparison

Abstract The coronavirus disease 2019 (COVID-19) pandemic has been called the deadliest disease event in history. In this study, we compared the cause-specific mortality rate of the Spanish flu (1918–1920) with that of COVID-19 (2020–2022) in the Netherlands. During the periods of exposure, about 50 000 people died of COVID-19 and 32 000 people of the Spanish flu. In absolute numbers, COVID-19 seems to be deadlier than Spanish flu. However, the crude mortality rates for COVID-19 and Spanish flu were 287 and 486 per 100 000 inhabitants, respectively. Comparing age-standardized mortality rates, there would have been 28 COVID-19– and 194 Spanish flu–related deaths in 1918–1920, or 214 Spanish flu– and 98 COVID-19–related deaths in 2020–2022 per 100 000 inhabitants per year. Thus, taking the population differences into account, the Spanish flu would have been deadlier than COVID-19.

Clinical impact and cost-effectiveness of the updated COVID-19 mRNA Autumn 2023 vaccines in Germany

Objectives To assess the potential clinical impact and cost-effectiveness of coronavirus disease 2019 (COVID-19) mRNA vaccines updated for Autumn 2023 in adults aged ≥60 years and high-risk persons aged 30–59 years in Germany over a 1-year analytic time horizon (September 2023–August 2024). Methods A compartmental Susceptible-Exposed-Infected-Recovered model was updated and adapted to the German market. Numbers of symptomatic infections, a number of COVID-19 related hospitalizations and deaths, costs, and quality-adjusted life-years (QALYs) gained were calculated using a decision tree model. The incremental cost-effectiveness ratio of an Autumn 2023 Moderna updated COVID-19 (mRNA-1273.815) vaccine was compared to no additional vaccination. Potential differences between the mRNA-1273.815 and the Autumn Pfizer-BioNTech updated COVID-19 (XBB.1.5 BNT162b2) vaccines, as well as societal return on investment for the mRNA-1273.815 vaccine relative to no vaccination, were also examined. Results Compared to no autumn vaccination, the mRNA-1273.815 campaign is predicted to prevent approximately 1,697,900 symptomatic infections, 85,400 hospitalizations, and 4,100 deaths. Compared to an XBB.1.5 BNT162b2 campaign, the mRNA-1273.815 campaign is also predicted to prevent approximately 90,100 symptomatic infections, 3,500 hospitalizations, and 160 deaths. Across both analyses we found the mRNA-1273.815 campaign to be dominant. Conclusions The mRNA-1273.815 vaccine can be considered cost-effective relative to the XBB.1.5 BNT162b2 vaccine and highly likely to provide more benefits and save costs compared to no vaccine in Germany, and to offer high societal return on investment.

Mortality from chronic liver disease: Recent trends and impact of the COVID-19 pandemic.

Prepandemic time trends in mortality from chronic liver disease (CLD) differed according to specific cause of death (decreasing for liver cirrhosis, stable or increasing for liver cancer), etiology (increasing for nonalcoholic fatty liver disease, generally decreasing for other etiologies), and world region (decreasing in areas with the highest burden of hepatitis B virus, increasing in Eastern Europe and other countries). The coronavirus disease 2019 (COVID-19) pandemic affected mortality of patients with CLD both directly, with a higher risk for severe illness and death depending on age, stage and etiology of the disease, and indirectly, through social isolation and loss of support, harmful drinking, and difficulties in access to care. Nevertheless, only sparse data are available on variations in CLD as a cause of death during the pandemic. In the USA, in 2020-2021 a growth in mortality was registered for all liver diseases, more marked for alcoholic liver disease, especially among young people aged 25-44 years and in selected ethnic groups. COVID-19 related deaths accounted only for a minor part of the excess. Further data from mortality registers of other countries are warranted, preferably adopting the so-called multiple cause-of-death approach, and extended to deaths attributed to viral hepatitis and liver cancer.

Different vaccination strategies for preventing coronavirus disease 2019 in Kenya: A dynamic modelling study of health impact and cost-effectiveness

Background: Vaccination can significantly reduce the health impact and economic burden of coronavirus disease 2019 (COVID-19), but vaccination levels for COVID-19 in most African countries lag far behind global averages. We assessed the cost-effectiveness of different COVID-19 vaccination strategies in Kenya and determined the optimal vaccination strategy. Methods: Using a dynamic transmission model, we divided the population into three groups: 0-18 years, 19-58 years and 58+ years. We assessed the effectiveness and cost-effectiveness of three vaccination strategies at different numbers of daily vaccinations based on previous studies and public databases. Nine scenarios were modeled and compared to no-continuation-vaccination to calculate the number of averted diseases, averted deaths, and net benefits of different vaccination strategies. One-way sensitivity analysis and probabilistic sensitivity analysis were conducted to assess the stability of our findings. Results: Compared to no-continuation-vaccination for various vaccination scenarios, all vaccination strategies were found to be effective and cost-saving. The incremental net benefit ranged from 0.235 billion USD to 2.305 billion USD, and prioritizing vaccination boosters for individuals aged 19-58 was identified as the most cost-effective option. On the other hand, prioritizing vaccination for the unvaccinated population aged 58 and above could potentially reduce COVID-19 related deaths by 1.59%-56.60%, which was the most effective approach in avoiding cause-specific deaths. However, all vaccination strategies were found to be ineffective in controlling the infection trend when compared to no intervention under different vaccination scenarios, with only 474,318-5,306,865 infections potentially being prevented. Conclusion: Timely and widespread vaccination against COVID-19 in Kenya is effective and cost-effective, a specific vaccination strategy should be selected based on decision-making needs. Priority vaccination for the elderly without vaccination may be more cost-effective compared with other vaccination strategies.

Correlation between relative age-standardized mortality rates and COVID-19 mortality over time in Italy.

This study was planned to estimate the contribution of coronavirus disease 2019 (COVID-19) related mortality on excess deaths recorded in Italy since the beginning of the pandemic. Official data on weekly number of COVID-19 related deaths in Italy were retrieved from the website of the Italian Ministry of Health, whilst information on weekly relative age-standardised mortality rates (rASMRs) in Italy during the COVID-19 pandemic was downloaded from the UK Office for National Statistics website. Univariate and multivariate correlation was conducted to explore the association between these two variables throughout the pandemic. Significant univariate correlation was found between rASMR and number of official COVID-19 related deaths throughout the pandemic period. Such correlation was especially high during predominance of pre-Alpha and Alpha variants, remained significant during Delta variant predominance, but become no longer significant during Omicron variant predominance. In multivariable analysis, we estimated that COVID-19 may have contributed to 72% of the excess mortality recorded in Italy throughout the pandemic. The impact was higher during pre-Alpha and Alpha periods (i.e., 78% and 89%, respectively), decreased to 41% during Delta variant predominance, and became no longer significant after emergence of the Omicron variant. These results would suggest that COVID-19 may have largely contributed to excess mortality in Italy until the recent emergence of the Omicron variant, by which time previous loss of vulnerable people and radical changes in delivering healthcare may have paradoxically contributed to improve the cumulative death rate in the country.

Standardized Cumulative Metrics of Excess Mortality to Monitor Health System Resilience Throughout COVID-19 and Other Respiratory Virus Resurgences.

Monitoring morbidity and mortality in resurgences of respiratory infections poses significant challenges, as shown by coronavirus disease 2019 (COVID-19). For example, case fatality rates and deaths attributed to specific respiratory pathogens are known to suffer from significant biases undermining their comparability through time and space. As a result, it is difficult to evaluate the protective effect of public health interventions or quantify the impact of a resurgence on the general population through direct recording of COVID-19 related deaths. To overcome these limitations, more robust, less-biased metrics, such as all-cause deaths, have been proposed for monitoring the effect of an epidemic over a population and over time. More specifically, metrics of excess mortality over time, which have been used for influenza surveillance in the past, are increasingly considered important for COVID-19 surveillance. Here, we discuss excess mortality surveillance focusing on standardized single-point and standardized cumulative metrics that allow comparability of excess mortality through space and time. We explain why z score allows for comparison of excess mortality between countries and different periods, while cumulative z score allows assessment of excess mortality over long periods. Our commentary reiterates the importance of standardized statistics of excess mortality for COVID-19 surveillance as we move toward a coexistence with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that will allow drawing conclusions from best practices in different health systems and different periods.

COVID-19 Breakthrough Infections in Vaccinated Patients With CLL in Israel.

COVID-19 Breakthrough Infections in Vaccinated Patients With CLL in Israel.

Predictors of COVID-19 Related Fatalities during the First Three Months of the Pandemic: An Ecological Study of 114 Countries

Background: Coronavirus disease 2019 (COVID-19) has costed the lives of more than 2 million people during the first wave of the pandemic with the number of fatalities varying among different countries. Thus, we aimed to assess the associations of specific demographic, clinical and political variables with COVID-19 related fatalities in various countries, during the first three months of the pandemic. Methods: We analyzed publicly available data from 192 regions (114 countries) and built a log-linear regression model with random intercepts in order to identify predictors of COVID-19 fatalities during the first three months of the pandemic. We used country-level data including total population, the percentage of people aged 65 and above, number of ICU beds per 100,000 people, geographical latitude and number of days from the first confirmed COVD-19 case to establishment of specific preventive control measures as explanatory variables of our statistical model. Results: In our multivariate statistical model, one unit increases in the total population (in 10,000,000 units), percentage of population aged 65 and above and the number of days from the first confirmed COVID-19 case to the imposition of preventive measures, were related to 3.8% (95% CI: 0.8% to 6.9%), 7.1% (95% CI: 0.9% to 13.6%) and 1.8% (95% CI: 0.3% to 3.6%), respectively, higher number of COVID-19 related deaths. Conclusion: Our findings imply positives associations of total population, percentage of population aged 65 and above and number of days from the first confirmed COVID-19 case to the imposition of preventive measures with COVID-19 fatal cases, during the first three months of the pandemic. Future non-ecological studies are warranted to confirm our results.

Predictors of COVID-19 Related Fatalities during the First Three Months of the Pandemic: An Ecological Study of 114 Countries

Background: Coronavirus disease 2019 (COVID-19) has costed the lives of more than 2 million people during the first wave of the pandemic with the number of fatalities varying among different countries. Thus, we aimed to assess the associations of specific demographic, clinical and political variables with COVID-19 related fatalities in various countries, during the first three months of the pandemic. Methods: We analyzed publicly available data from 192 regions (114 countries) and built a log-linear regression model with random intercepts in order to identify predictors of COVID-19 fatalities during the first three months of the pandemic. We used country-level data including total population, the percentage of people aged 65 and above, number of ICU beds per 100,000 people, geographical latitude and number of days from the first confirmed COVD-19 case to establishment of specific preventive control measures as explanatory variables of our statistical model. Results: In our multivariate statistical model, one unit increases in the total population (in 10,000,000 units), percentage of population aged 65 and above and the number of days from the first confirmed COVID-19 case to the imposition of preventive measures, were related to 3.8% (95% CI: 0.8% to 6.9%), 7.1% (95% CI: 0.9% to 13.6%) and 1.8% (95% CI: 0.3% to 3.6%), respectively, higher number of COVID-19 related deaths. Conclusion: Our findings imply positives associations of total population, percentage of population aged 65 and above and number of days from the first confirmed COVID-19 case to the imposition of preventive measures with COVID-19 fatal cases, during the first three months of the pandemic. Future non-ecological studies are warranted to confirm our results.

Risk Factors for Sudden Death Within 2 Days After Diagnosis of COVID-19 in Korea.

We aimed to analyze the risk factors for sudden death after diagnosis of coronavirus disease 2019 (COVID-19) in South Korea and to provide evidence for informing prevention and control interventions for patients at risk of sudden death. We included 30,302 COVID-19 related deaths registered in the patient management information system (Central Disease Control Headquarters) between January 1, 2021, and December 15, 2022. We collected their epidemiological data recorded by the reporting city, province, or country. We performed multivariate logistic regression analysis to identify risk factors for sudden death after diagnosis of COVID-19. Among the 30,302 deaths, there were 7,258 (24.0%) and 23,044 (76.0%) sudden and non-sudden deaths, respectively. Sudden death means a person who died within 2 days of diagnosis and who did not receive inpatient treatment. Underlying condition, vaccination status, and place of death were significantly associated with the survival period in all age groups. Moreover, region, sex, and prescription were significantly associated with the survival period only in certain age groups. However, reinfection was not significantly associated with the survival period in any age group. To our knowledge, this is the first study on the risk factors for sudden death after a diagnosis of COVID-19, which included age, underlying condition, vaccination status, and place of death. Additionally, individuals aged < 60 years without an underlying condition were at high risk for sudden death. However, this group has relatively low interest in health, as can be seen from the high non-vaccination rate (16.1% of the general population vs. 61.6% of the corresponding group). Therefore, there is a possibility for the presence of an uncontrolled underlying disease in this population. In addition, many sudden deaths occurred due to delayed hospital visits to continue economic activities even after the onset of COVID-19 symptoms (7 days overall vs. 10 days average for the group). In conclusion, 'continued interest in health' is a key factor in avoiding sudden death in the economically active group (under 60 years of age).

Inter-Country COVID-19 Contagiousness Variation in Eight African Countries.

The estimates of contiguousness parameters of an epidemic have been used for health-related policy and control measures such as non-pharmaceutical control interventions (NPIs). The estimates have varied by demographics, epidemic phase, and geographical region. Our aim was to estimate four contagiousness parameters: basic reproduction number (R0), contact rate, removal rate, and infectious period of coronavirus disease 2019 (COVID-19) among eight African countries, namely Angola, Botswana, Egypt, Ethiopia, Malawi, Nigeria, South Africa, and Tunisia using Susceptible, Infectious, or Recovered (SIR) epidemic models for the period 1 January 2020 to 31 December 2021. For reference, we also estimated these parameters for three of COVID-19's most severely affected countries: Brazil, India, and the USA. The basic reproduction number, contact and remove rates, and infectious period ranged from 1.11 to 1.59, 0.53 to 1.0, 0.39 to 0.81; and 1.23 to 2.59 for the eight African countries. For the USA, Brazil, and India these were 1.94, 0.66, 0.34, and 2.94; 1.62, 0.62, 0.38, and 2.62, and 1.55, 0.61, 0.39, and 2.55, respectively. The average COVID-19 related case fatality rate for 8 African countries in this study was estimated to be 2.86%. Contact and removal rates among an affected African population were positively and significantly associated with COVID-19 related deaths (p-value < 0.003). The larger than one estimates of the basic reproductive number in the studies of African countries indicate that COVID-19 was still being transmitted exponentially by the 31 December 2021, though at different rates. The spread was even higher for the three countries with substantial COVID-19 outbreaks. The lower removal rates in the USA, Brazil, and India could be indicative of lower death rates (a proxy for good health systems). Our findings of variation in the estimate of COVID-19 contagiousness parameters imply that countries in the region may implement differential COVID-19 containment measures.

COVID-19 in Africa: An Explorative Cross-Sectional Analysis of Twenty-One African Countries From January to June 2020.

Introduction: Africa has surprisingly recorded better gains in containing the coronavirus spread than countries with the better health indices, such as the USA and UK. The low rate of coronavirus disease 2019 (COVID-19) cases and death in Africa represents a puzzle with different biological and social theories such as low COVID-19 testing capacity, substantial young population, few old people, favourable climate, genetic admixture, infectious disease antibodies, and sound community health care systems proposed. We aimed to understand the COVID-19 preventive measures in a group of twenty-one systematically selected African countries that may explain the low burden of COVID-19 in Africa.Methods: Data (COVID-19, health, socioeconomic, and demographics indices) of twenty-one systemically selected African countries were retrieved from the various official country and multilateral organization sources such as Worldbank, and the United nations development Programme (UNDP). The extracted data were analyzed in three large groups: international travel restrictions, physical and social distancing, and movement restrictions (lockdown measures; curfews, partial or/and national lockdowns). Data cleaning, analysis (including Pearson correlation), and visualization were done with Microsoft Excel and Graph Pad Prism version 9 (https://www.graphpad.com/).Result: Southern Africa had the greatest number of cases and deaths within the period studied compared to East Africa, which was the least COVID-19 affected sub-region (in terms of COVID-19 cases and deaths). We observed that coronary artery disease death rate was highly correlated with COVID-19 death density (number of COVID-19 deaths/total population) and similarly observed a correlation between the number of cases and deaths and number of in-country arrivals, pandemic preparedness (health security index), COVID-19 containment, and health index (not correlated with deaths). Finally, we noted that the most effective preventive strategy was the 'use of a face mask'.Conclusion: Africa had fewer COVID-19 cases and COVID-19 related deaths. Our data shows that the rapidity and stringency of COVID-19 preventive measures and government policies, and the low level of tourism in Africa compared to other countries (i.e., low COVID-19 seeding rate) may have been contributory to these favorable statistics. We hope these findings impact how the preparedness for pandemics can be enhanced to decrease the burden of preventable deaths and morbidity.

COVID-19 Vaccine Hesitancy during the Perinatal Period: Understanding Psychological and Cultural Factors to Improve Care and Address Racial/Ethnic Health Inequities.

COVID-19 Vaccine Hesitancy during the Perinatal Period: Understanding Psychological and Cultural Factors to Improve Care and Address Racial/Ethnic Health Inequities.

COVID-19 pandemic over 2020 (withlockdowns) and 2021 (with vaccinations): similar effects for seasonality and environmental factors

How is the dynamics of Coronavirus Disease 2019 (COVID-19) in 2020 with an health policy of full lockdowns and in 2021 with a vast campaign of vaccinations? The present study confronts this question here by developing a comparative analysis of the effects of COVID-19 pandemic between April–September 2020 (based upon strong control measures) and April–September 2021 (focused on health policy of vaccinations) in Italy, which was one of the first European countries to experience in 2020 high numbers of COVID-19 related infected individuals and deaths and in 2021 Italy has a high share of people fully vaccinated against COVID-19 (>89% of population aged over 12 years in January 2022). Results suggest that over the period under study, the arithmetic mean of confirmed cases, hospitalizations of people and admissions to Intensive Care Units (ICUs) in 2020 and 2021 is significantly equal (p-value<0.01), except fatality rate. Results suggest in December 2021 lower hospitalizations, admissions to ICUs, and fatality rate of COVID-19 than December 2020, though confirmed cases and mortality rates are in 2021 higher than 2020, and likely converging trends in the first quarter of 2022. These findings reveal that COVID-19 pandemic is driven by seasonality and environmental factors that reduce the negative effects in summer period, regardless control measures and/or vaccination campaigns. These findings here can be of benefit to design health policy responses of crisis management considering the growth of COVID-19 pandemic in winter months having reduced temperatures and low solar radiations ( COVID-19 has a behaviour of influenza-like illness). Hence, findings here suggest that strategies of prevention and control of infectious diseases similar to COVID-19 should be set up in summer months and fully implemented during low-solar-irradiation periods (autumn and winter period).

Short-term association between COVID-19 related deaths, hospitalized patients and air pollution during the first lockdown in the four largest cities in Germany

ABSTRACT Identifying risk factors of coronavirus disease 2019 (COVID-19) for its clinical course became important during the current global health crisis. This study explores the relationship between ambient air quality and the clinical course of COVID-19 during the first German lockdown. Daily air pollutant concentrations (PM10, O3 and NO2) and confirmed COVID-19-related hospital cases and deaths in the four largest German cities are used for multivariate regression analysis to study the correlation of air pollutants with COVID-19-related hospitalised or ICU patients and deaths. A significant positive association of O3 with patients and deaths is observed. NO2 shows a positive correlation with hospitalised and ICU patients. A 10 µg/m3 increase in O3 is linked to a 27% (95% CI: 15% to 39%) increase of COVID-19-related deaths. However, PM10 is associated with a decrease in deaths. Altogether, these findings indicate that air pollutants seem to have a significant influence on the course of COVID-19 infections.

Minimally Invasive Tissue Sampling as an Alternative to Complete Diagnostic Autopsies in the Context of Epidemic Outbreaks and Pandemics: The Example of Coronavirus Disease 2019 (COVID-19).

BackgroundInfectious diseases’ outbreak investigation requires, by definition, conducting a thorough epidemiological assessment while simultaneously obtaining biological samples for an adequate screening of potential responsible pathogens. Complete autopsies remain the gold-standard approach for cause-of-death evaluation and characterization of emerging diseases. However, for highly transmissible infections with a significant associated lethality, such as COVID-19, complete autopsies are seldom performed due to biosafety challenges, especially in low-resource settings. Minimally invasive tissue sampling (MITS) is a validated new approach based on obtaining postmortem samples from key organs and body fluids, a procedure that does not require advanced biosafety measures or a special autopsy room.MethodsWe aimed to review the use of MITS or similar procedures for outbreak investigation up to 27 March 2021 and their performance for evaluating COVID-19 deaths.ResultsAfter a literature review, we analyzed in detail the results of 20 studies conducted at international sites, whereby 216 COVID-19–related deaths were investigated. MITS provided a general and more granular understanding of the pathophysiological changes secondary to the infection and high-quality samples where the extent and degree of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)–related damage could be evaluated.ConclusionsMITS is a useful addition in the investigation and surveillance of infections occurring in outbreaks or epidemics. Its less invasive nature makes the tool more acceptable and feasible and reduces the risk of procedure-associated contagion, using basic biosafety measures. Standardized approaches protocolizing which samples should be collected—and under which exact biosafety measures—are necessary to facilitate and expand its use globally.

Vaccine-induced immune responses against SARS-CoV-2 infections

Vaccination against coronavirus disease 2019 (COVID-19) is one of the most effective tools to curb the pandemic. Multiple vaccine candidates based on different platforms are available for emergency use presently. However, in common all the vaccines target spike protein, which is a dominant immunogen of severe acute respiratory syndrome corona virus 2 (SARS-CoV-2). Adequate immunogenicity and efficacy are demonstrated by many of the vaccines in clinical phase III trials. The emergence of the new variant of concern is believed to be associated with less susceptibility to the post-infection or post-vaccination mounted immunity. It is a global concern currently threatening the progression of the vaccination drive. Nevertheless, the results of the presently available phase III clinical trials promote COVID-19 vaccination to prevent disease severity and COVID-19 related deaths. Cross-immunity towards the new variants of concern especially against the South African variant is yet to be explored and managed adequately.

The Disproportionate Impact of COVID-19 among Undocumented Immigrants and Racial Minorities in the US.

Severe 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.

Assessment of Retrospective COVID-19 Spatial Clusters with Respect to Demographic Factors: Case Study of Kansas City, Missouri, United States

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The United States (U.S.) has the highest number of reported COVID-19 infections and related deaths in the world, accounting for 17.8% of total global confirmed cases as of August 2021. As COVID-19 spread throughout communities across the U.S., it became clear that inequities would arise among differing demographics. Several researchers have suggested that certain racial and ethnic minority groups may have been disproportionately impacted by the spread of COVID-19. In the present study, we used the daily data of COVID-19 cases in Kansas City, Missouri, to observe differences in COVID-19 clusters with respect to gender, race, and ethnicity. Specifically, we utilized a retrospective Poisson spatial scan statistic with respect to demographic factors to detect daily clusters of COVID-19 in Kansas City at the zip code level from March to November 2020. Our statistical results indicated that clusters of the male population were more widely scattered than clusters of the female population. Clusters of the Hispanic population had the highest prevalence and were also more widely scattered. This demographic cluster analysis can provide guidance for reducing the social inequalities associated with the COVID-19 pandemic. Moreover, applying stronger preventive and control measures to emerging clusters can reduce the likelihood of another epidemic wave of infection.

Incidence of healthcare-associated coronavirus disease 2019 (COVID-19) in the state of Geneva.

An examination of all coronavirus disease 2019 (COVID-19) cases and patient movements in Geneva indicated important disease activity within the healthcare system since the beginning of the pandemic. We estimate that 4.3% of all COVID-19 cases were likely acquired within the healthcare system, contributing to 62% of the COVID-19-related deaths.