ABSTRACT Background : The Covid-19 pandemic associated with the SARS-CoV-2 has caused very high death tolls in many countries, while it has had less prevalence in other countries of Africa and Asia. Climate and geographic conditions, as well as other epidemiologic and demographic conditions, were a matter of debate on whether or not they could have an effect on the prevalence of Covid-19. Objective : In the present work, we sought a possible relevance of the geographic location of a given country on its Covid-19 prevalence. On the other hand, we sought a possible relation between the history of epidemiologic and demographic conditions of the populations and the prevalence of Covid-19 across four continents (America, Europe, Africa, and Asia). We also searched for a possible impact of pre-pandemic alcohol consumption in each country on the two year death tolls across the four continents. Methods : We have sought the death toll caused by Covid-19 in 39 countries and obtained the registered deaths from specialized web pages. For every country in the study, we have analysed the correlation of the Covid-19 death numbers with its geographic latitude, and its associated climate conditions, such as the mean annual temperature, the average annual sunshine hours, and the average annual UV index. We also analyzed the correlation of the Covid-19 death numbers with epidemiologic conditions such as cancer score and Alzheimer score, and with demographic parameters such as birth rate, mortality rate, fertility rate, and the percentage of people aged 65 and above. In regard to consumption habits, we searched for a possible relation between alcohol intake levels per capita and the Covid-19 death numbers in each country. Correlation factors and determination factors, as well as analyses by simple linear regression and polynomial regression, were calculated or obtained by Microsoft Exell software (2016). Results : In the present study, higher numbers of deaths related to Covid-19 pandemic were registered in many countries in Europe and America compared to other countries in Africa and Asia. The analysis by polynomial regression generated an inverted bell-shaped curve and a significant correlation between the Covid-19 death numbers and the geographic latitude of each country in our study. Higher death numbers were registered in the higher geographic latitudes of both hemispheres, while lower scores of deaths were registered in countries located around the equator line. In a bell shaped curve, the latitude levels were negatively correlated to the average annual levels (last 10 years) of temperatures, sunshine hours, and UV index of each country, with the highest scores of each climate parameter being registered around the equator line, while lower levels of temperature, sunshine hours, and UV index were registered in higher latitude countries. In addition, the linear regression analysis showed that the Covid-19 death numbers registered in the 39 countries of our study were negatively correlated with the three climate factors of our study, with the temperature as the main negatively correlated factor with Covid-19 deaths. On the other hand, cancer and Alzheimer's disease scores, as well as advanced age and alcohol intake, were positively correlated to Covid-19 deaths, and inverted bell-shaped curves were obtained when expressing the above parameters against a country’s latitude. Instead, the (birth rate/mortality rate) ratio and fertility rate were negatively correlated to Covid-19 deaths, and their values gave bell-shaped curves when expressed against a country’s latitude. Conclusion : The results of the present study prove that the climate parameters and history of epidemiologic and demographic conditions as well as nutrition habits are very correlated with Covid-19 prevalence. The results of the present study prove that low levels of temperature, sunshine hours, and UV index, as well as negative epidemiologic and demographic conditions and high scores of alcohol intake may worsen Covid-19 prevalence in many countries of the northern hemisphere, and this phenomenon could explain their high Covid-19 death tolls. Keywords : Covid-19, Coronavirus, SARS-CoV-2, climate, temperature, sunshine hours, UV index, cancer, Alzheimer disease, alcohol.

Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve. The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj. The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 . The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 . The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed. COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken down by race and ethnicity. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the COVID-19 update. The following data show the number of COVID-19 cases and associated deaths per 100,000 population by race and ethnicity. Crude rates represent the total cases or deaths per 100,000 people. Age-adjusted rates consider the age of the person at diagnosis or death when estimating the rate and use a standardized population to provide a fair comparison between population groups with different age distributions. Age-adjustment is important in Connecticut as the median age of among the non-Hispanic white population is 47 years, whereas it is 34 years among non-Hispanic blacks, and 29 years among Hispanics. Because most non-Hispanic white residents who died were over 75 years of age, the age-adjusted rates are lower than the unadjusted rates. In contrast, Hispanic residents who died tend to be younger than 75 years of age which results in higher age-adjusted rates. The population data used to calculate rates is based on the CT DPH population statistics for 2019, which is available online here: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Population-Statistics. Prior to 5/10/2021, the population estimates from 2018 were used. Rates are standardized to the 2000 US Millions Standard population (data available here: https://seer.cancer.gov/stdpopulations/). Standardization was done using 19 age groups (0, 1-4, 5-9, 10-14, ..., 80-84, 85 years and older). More information about direct standardization for age adjustment is available here: https://www.cdc.gov/nchs/data/statnt/statnt06rv.pdf Categories are mutually exclusive. The category “multiracial” includes people who answered ‘yes’ to more than one race category. Counts may not add up to total case counts as data on race and ethnicity may be missing. Age adjusted rates calculated only for groups with more than 20 deaths. Abbreviation: NH=Non-Hispanic. Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical

From July to September 2020, a total of around 24 percent of adults aged 18 years or older in the United States stated that they had their routine cancer screening test delayed or cancelled due to the COVID-19 pandemic. This statistic illustrates the percentage of U.S. adults who had their routine cancer screening tests delayed or cancelled due to the COVID-19 pandemic in 2020.

Structure and levels of age covariate in the best fitted models for different types of cancer.

Heart disease is currently the leading cause of death in the United States. In 2022, COVID-19 was the fourth leading cause of death in the United States, accounting for almost six percent of all deaths that year. The leading causes of death worldwide are similar to those in the United States. However, diarrheal diseases and neonatal conditions are major causes of death worldwide, but are not among the leading causes in the United States. Instead, accidents and chronic liver disease have a larger impact in the United States.

Racial differences

In the United States, there exist slight differences in leading causes of death depending on race and ethnicity. For example, assault, or homicide, accounts for around three percent of all deaths among the Black population but is not even among the leading causes of death for other races and ethnicities. However, heart disease and cancer are still the leading causes of death for all races and ethnicities.

Leading causes of death among men vs women

Similarly, there are also differences in the leading causes of death in the U.S. between men and women. For example, among men, intentional self-harm accounts for around two percent of all deaths but is not among the leading causes of death among women. On the other hand, influenza and pneumonia account for more deaths among women than men.

ABSTRACT Background : The Covid-19 pandemic has caused very high death tolls across the world in the last two years. Geographic latitude, climate factors, and other human related conditions such as epidemiologic and demographic history are taught to have played a role in the prevalence of Covid-19. Objective : This observational study aimed to investigate possible relations between geographic latitude-associated climate factors and Covid-19 death numbers in 29 countries. The study also aimed to investigate the relationship between geographic latitude and the history of epidemiologic (cancer, Alzheimer's disease) and demographic factors (birth rate, mortality rate, fertility rate, people aged 65 and over), as well as alcohol intake habits. And finally, the study also aimed to evaluate the relationships between epidemiologic and demographic factors, as well as alcohol intake habits with Covid-19 deaths. Methods : We sought the Covid-19 death toll in 29 countries in Europe, Africa, and the Middle East (located in both hemispheres and between the meridian lines "-15°" and "+50°"). We obtained the death numbers for Covid-19 and other geographic (latitude, longitude) and climate factors (average annual temperature, sunshine hours, and UV index) and epidemiologic and demographic parameters as well as data on alcohol intake per capita from official web pages. Based on records of epidemiologic and demographic history, and alcohol intake data, we have calculated a General Immune Capacity (GIC) score for each country. Geographic latitude and climate factors were plotted against each of Covid-19 death numbers, epidemiologic and demographic parameters, and alcohol intake per capita. Data was analysed by simple linear regression or polynomial regression. All statistical data was collected using Microsoft Excell software (2016). Results : Our observational study found higher death numbers in the higher geographic latitudes of both hemispheres, while lower scores of deaths were registered in countries located around the equator line and low latitudes. When the Covid-19 death numbers were plotted against the geographic latitude of each country, an inverted bell-shaped curve was obtained (coefficient of determination R2=0.553). In contrast, bell-shaped curves were obtained when latitude was plotted against annual average temperature (coefficient of determination R2= 0.91), average annual sunshine hours (coefficient of determination R2= 0.79) and average annual UV index (coefficient of determination R2= 0.89). In addition, plotting the latitude of each country against the General Immune Capacity score of each country gave an inverted bell-shaped curve (coefficient of determination R2=0.755). Linear regression analysis of the General Immune Capacity score of each country and its Covid-19 deaths showed a very significant negative correlation (coefficient of determination R² = 0,71, p=6.79x10-9). Linear regression analysis of the Covid-19 death number plotted against the average annual temperature temperature and the average annual sunshine hours or the average annual UV index gave very significant negative correlations with the following coefficients of determination: (R2 = 0.69, p = 1.94x10-8), (R2 = 0.536, p = 6.31x10-6) and (R2 = 0.599, p = 8.30x10-7), respectively. Linear regression analysis of the General Immune Capacity score of each country plotted against its average annual temperature temperature and the average annual sunshine hours or the average annual UV index gave very significant negative correlations, with the following coefficients of determination: (R2 = 0.86, p = 3.63x10-13), (R2 = 0.69, p = 2.18x10-8) and (R2 = 0.77, p= 2.47x10-10), respectively. Conclusion : The results of the present study prove that at certain geographic latitudes and their three associated climate parameters are negatively correlated to Covid-19 mortality. On the other hand, our data showed that the General Immune Capacity score, which includes many human related parameters, is inversely correlated to Covid-19 mortality. Likewise, geographic location and health and demographic history were key elements in the prevalence of the Covid-19 pandemic in a given country. On the other hand, the study points to the possible protective role of UV light against Covid-19. The therapeutic potential of UV light against the Covid-19 associated with SARS-Cov-2 is discussed.

Overall-temporal-changes (ACd,r, per 100,000 people) from 2001 to 2016, in age-standardised fitted mortality rates for deprivation levels 1 and 10 and all regions in England for both genders; 95% credible intervals in brackets.

In 2021, the highest COVID-19 mortality occurred in cancer patients over 60 years of age. Cancer was also responsible for the most significant mortality among COVID-19 infected under 60 years of age.

The first cases of coronavirus infection in Poland were reported on 4 March 2020.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

In 2023, the leading causes of death in Canada were malignant neoplasms (cancer) and diseases of the heart. Together, these diseases accounted for around 44 percent of all deaths in Canada that year. COVID-19 was the sixth leading cause of death in Canada in 2023 with 2.4 percent of deaths. The leading causes of death in Canada In 2023, around 84,629 people in Canada died from cancer, making it by far the leading cause of death in the country. In comparison, an estimated 57,890 people died from diseases of the heart, while 20,597 died from accidents. In 2023, the death rate for diabetes mellitus was 18.1 per 100,000 population, making it the seventh leading cause of death. Diabetes is a growing problem in Canada, with around eight percent of the population diagnosed with the disease as of 2023. What is the deadliest form of cancer in Canada? In Canada, lung and bronchus cancer account for the largest share of cancer deaths, followed by colorectal cancer. In 2023, the death rate for lung and bronchus cancer was 41.8 per 100,000 population, compared to 19.6 deaths per 100,000 population for colorectal cancer. However, although lung and bronchus cancer are the deadliest cancers for both men and women in Canada, breast cancer is the second-deadliest cancer among women, accounting for 13.4 percent of all cancer deaths. Colorectal cancer is the second most deadly cancer among men in Canada followed by prostate cancer. In 2023, colorectal cancer accounted for around 11.2 percent of all cancer deaths among men in Canada, while prostate cancer was responsible for 10.5 percent of such deaths.

BackgroundChildhood cancer represents a leading cause of death and disease burden in high income countries (HICs) and low-and-middle income countries (LMICs). It is postulated that the current COVID-19 pandemic has hampered global development of pediatric oncology care programs. This systematic review aimed to comprehensively review the global impact of COVID-19 on childhood cancer clinical outcomes and care delivery.MethodsA systematic search was conducted on PubMed, Embase, Medline, and the African Medical Index from inception to November 3, 2021 following PRISMA guidelines. A manual search was performed to identify additional relevant studies. Articles were selected based on predetermined eligibility criteria.FindingsThe majority of studies reported patients with cancer and COVID-19 presenting as asymptomatic (HICs: 33.7%, LMICs: 22.0%) or with primary manifestations of fever (HICs: 36.1%, LMICs: 51.4%) and respiratory symptoms (HICs: 29.6%, LMICs: 11.7%). LMICs also reported a high frequency of patients presenting with cough (23.6%) and gastrointestinal symptoms (10.6%). The majority of patients were generally noted to have a good prognosis; however the crude mortality rate was higher in LMICs when compared to HICs (8.0% vs 1.8%). Moreover, the pandemic has resulted in delays and interruptions to cancer therapies and delays in childhood cancer diagnoses in both HICs and LMICs. However, these findings were disproportionately reported in LMICs, with significant staff shortages, supply chain disruptions, and limited access to cancer therapies for patients.ConclusionsThe COVID-19 pandemic has resulted in delays and interruptions to childhood cancer therapies and delays in childhood cancer diagnoses, and disproportionately so within LMICs. This review provides lessons learned for future system-wide disruptions to care, as well as provides key points for moving forward better with care through the remainder of this pandemic.Systematic Review RegistrationCRD42021266758, https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=266758

Update 2 March 2023: Following the merger of NHS Digital and NHS England on 1st February 2023 we are reviewing the future presentation of the NHS Outcomes Framework indicators. As part of this review, the annual publication which was due to be released in March 2023 has been delayed. Further announcements about this dataset will be made on this page in due course. Directly standardised mortality rate from cancer for people aged under 75, per 100,000 population. To ensure that the NHS is held to account for doing all that it can to prevent deaths from cancer in people under 75. Some different patterns have been observed in the 2020 mortality data which are likely to have been impacted by the coronavirus (COVID-19) pandemic. Statistics from this period should also be interpreted with care. Legacy unique identifier: P01733

We collected county-level cumulative COVID-19 confirmed cases and death from Mar 25 to Nov 12, 2020, across the contiguous United States from USAFacts (usafacts.org). We considered Mar 25 to Jun 3 as the “1st wave”, Jun 4 to Sep 2 as the “2nd wave”, and Sep 3 to Nov 12 as the “3rd wave” of COVID-19. For the 2nd and 3rd waves, we analyzed the targeted counties in the sunbelt region (including AL, AZ, AR, CA, FL, GA, KS, LA, MS, NV, NM, NC, OK, SC, TX, TN, and UT states) and great plains region (including IA, IL, IN, KS, MI, MO, MN, ND, NE, OH, SD, and WI states), respectively. MIR, as a proxy for survival rate, is calculated by dividing the number of confirmed deaths in each county by the confirmed cases in the same county at the same time-period multiplied by 100. MIR ranges from 0%-100%, 100% indicating the worst situation where all confirmed cases have died.

Thirty-eight potential risk factors (covariates), including county-level MR of comorbidities & disorders, demographics & social factors, and environmental factors, were retrieved from the University of Washington Global Health Data Exchange (http://ghdx.healthdata.org/us-data). Comorbidities and disorders include CVD, cardiomyopathy and myocarditis and myocarditis, hypertensive heart disease, peripheral vascular disease, atrial fibrillation, cerebrovascular disease, diabetes, hepatitis, HIV/AIDS, tuberculosis (TB), lower respiratory infection, interstitial lung disease and pulmonary sarcoidosis, asthma, COPD, ischemia, mesothelioma, tracheal cancer, leukemia, pancreatic cancer, rheumatic disease, drug use disorder, and alcohol use disorder. Demographics & social factors include age, female African American%, female white American%, male African American%, male white American%, Asian%, smokers%, unemployed%, income rate, food insecurity, fair/poor health, and uninsured%. Environmental factors include county population density, air quality index (AQI), temperature, and PM. A descriptive table, including all potential risk factors, is provided in Table S1).

BackgroundBreast cancer is considered a health problem at a worldwide level. In Brazil, the South and Southeast regions have the highest mortality rates. Understanding how they dealt with the diagnostic of a stigmatized disease amid the COVID-19 pandemic and its potential repercussions, may enable healthcare professionals to of life. Thus, this study is aimed at understanding the perception of women about the discovery of breast cancer and the impact of the disease on their lives.MethodsA qualitative study, with the participation of forty women with breast cancer, under chemotherapy treatment. It was performed in a hospital specialized in oncology, in Juiz de Fora, Brazil, in 2020 and 2021. Data collection was carried out with semi-structured interviews, which were analyzed with Bardin Content Analysis.ResultsBased on the central theme "Discovery of the disease", these categories were developed: "Discovery" and "Impact of the disease". A large part of women noticed a change in the breast, even before routine checks. Upon the impact of cancer diagnosis, negative feelings arise, then going through a process of acceptance and coping. Some barriers were faced due to the COVID-19 pandemic, which caused delays in the diagnostic and impact caused by social isolation. Family, friends, and healthcare professionals integrated an important supporting network in order to help coping with the disease.ConclusionThe consequences of a breast cancer diagnosis can be devastating. It is necessary that healthcare professionals know and embrace the feelings, beliefs, and values as a part of the aspects related to health. Valuing the supporting network of women suffering from the disease may favor the process of accepting and coping with the neoplasm. The COVID-19 pandemic is highlighted as an obstacle to be overcome specially when it comes to diagnostic assistance and availability of a support network. In that sense, it is worth mentioning the importance of a healthcare team able to offer full assistance, with quality. The need of further studies to determine the impact of the pandemic in the long run.

Abstract Background: This study analyzed the causes of death in the Korean population in 2020. Methods: Cause-of-death data for 2020 from Statistics Korea were examined based on the Korean Standard Classification of Diseases and Causes of Death, 7th revision and the International Statistical Classification of Diseases and Related Health Problems, 10th revision. Results: In total, 304,948 deaths occurred, reflecting an increase of 9,838 (3.3%) from 2019. The crude death rate (the number of deaths per 100,000 people) was 593.9, corresponding to an increase of 19.0 (3.3%) from 2019. The 10 leading causes of death, in descending order, were malignant neoplasms, heart diseases, pneumonia, cerebrovascular diseases, intentional self-harm, diabetes mellitus, Alzheimer’s disease, liver diseases, hypertensive diseases, and sepsis. Cancer accounted for 27.0% of deaths. Within the category of malignant neoplasms, the top 5 leading organs of involvement were the lung, liver, colon, stomach, and pancreas. Sepsis was included in the 10 leading causes of death for the first time. Mortality due to pneumonia decreased to 43.3 (per 100,000 people) from 45.1 in 2019. The number of deaths due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was 950, of which 54.5% were in people aged 80 or older. Conclusion: These changes reflect the continuing increase in deaths due to diseases of old age, including sepsis. The decrease in deaths due to pneumonia may have been due to protective measures against SARS-CoV-2. With the concomitant decrease in fertility, 2020 became the first year in which Korea’s natural total population decreased.

Univariate and multivariate analysis of post-COVID-19 diagnosis characteristics for mortality.

Univariate and multivariate analysis of baseline characteristics for Extended hospitalization.

In Italy, approximately 722,000 deaths were registered in 2022. According to the data, ischemic heart diseases were the most common cause of death in the country, with 59,052 cases registered, closely followed by cerebrovascular diseases. COVID-19 was the third illness causing the largest number of deaths in Italy. COVID-19 death comorbidities Most patients admitted to the hospital and later deceased with the coronavirus (COVID-19) infection showed one or more comorbidities. Hypertension was the most common pre-existing health condition, detected in 65.8 percent of patients who died after contracting the virus. Type 2-diabetes, ischemic heart disease, and atrial fibrillation were also among the most common comorbidities in COVID-19 patients who lost their lives. Cancer deaths The number of people who died from a tumor in Italy decreased constantly between 2006 and 2021. Indeed, the rate of deaths due to cancer among Italians dropped from 28.7 deaths per 10,000 inhabitants in 2006 to 23.3 in 2021. The Italian region with the highest cancer mortality rate was Campania, followed by Sardinia, and Sicily.

PurposeThis study aimed to describe the demographic and clinical characteristics of cancer patients with COVID-19, exploring factors associated with adverse outcomes.Patients and methodsThis retrospective cohort study methodically extracted and curated data from electronic medical records (EMRs) of numerous healthcare institutions on cancer patients diagnosed with a confirmed SARS-CoV-2 infection between May 2020 and August 2021, to identify risk factors linked to extended hospitalization and mortality. The retrieved information encompassed the patients’ demographic and clinical characteristics, including the incidence of prolonged hospitalization, acute complications, and COVID-19-related mortality.ResultsA total of 1446 cancer patients with COVID-19 were identified (mean [Standard deviation] age, 59.2 [14.3] years). Most patients were female (913 [63.1%]), non-white (646 [44.7%]), with non-metastatic (818 [56.6%]) solid tumors (1318 [91.1%]), and undergoing chemotherapy (647 [44.7%]). The rate of extended hospitalization due to COVID-19 was 46% (n = 665), which was significantly impacted by age (p = 0.012), sex (p = 0.003), race and ethnicity (p = 0.049), the presence of two or more comorbidities (p = 0.006), hematologic malignancies (p = 0.013), metastatic disease (p = 0.002), and a performance status ≥ 2 (p = 0.001). The COVID-19-related mortality rate was 18.9% (n = 273), and metastatic disease (

ObjectiveTo analyze the clinical characteristics and prognostic impacts of SARS-CoV-2 Omicron infection among cancer inpatients during the December 2022 – February 2023 surge, in order to provide scientific evidence for clinical treatment and prevention and control measures.MethodsA retrospective analysis was conducted on the clinical features, prognosis, and vaccination status of cancer in-patients infected with the Omicron variant during the COVID-19 pandemic of December 2022 – February 2023.ResultsA total of 137 cancer inpatients were included in the study, with a median age of 61 years, and 75 patients (54.74%) were male. The main symptoms were cough (69 cases, 50.36%), expectoration (60 cases, 43.80%), and fever (53 cases, 39.69%). Chest CT examination revealed bilateral pneumonia in 47 cases (34.31%, 47/137) and pleural effusion in 24 cases (17.52%, 24/137). Among the cancer patients, 116 cases (84.67%, 116/137) had solid tumors, and 21 cases (15.33%, 21/137) had hematologic malignancies, with the main types being breast cancer (25 cases, 18.25%) and lung cancer (24 cases, 17.52%). Among the cancer patients, 46 cases (33.58%) were asymptomatic, 81 cases (59.12%) had mild disease, 10 cases (7.30%) had severe infection, and 8 cases (5.84%) died. A total of 91 patients (66.42%) had been vaccinated, with 58 patients (42.34%) receiving three doses. Multivariate analysis showed that cerebral infarction and hypoproteinemia were risk factors for death from COVID-19 infection.ConclusionCancer patients infected with SARS-CoV-2 Omicron typically exhibit mild disease manifestations, but some cancer patients infected with the Omicron variant might progress to severe illness, and even death, necessitating close monitoring and attention during the early stages of infection. Additionally, the presence of cerebral infarction and hypoproteinemia significantly increases the risk of death.

As of 2022, the countries with the highest death rates worldwide were Ukraine, Bulgaria, and Moldova. In these countries, there were 17 to 21 deaths per 1,000 people. The country with the lowest death rate is Qatar, where there is just one death per 1,000 people. Leading causes of death The leading causes of death worldwide are by far, ischaemic heart disease and stroke, accounting for a combined 27 percent of all deaths in 2019. In that year, there were 8.89 million deaths worldwide from ischaemic heart disease and 6.19 million from stroke. Interestingly, a worldwide survey from that year found that people greatly underestimate the proportion of deaths caused by cardiovascular disease, but overestimate the proportion of deaths caused by suicide, interpersonal violence, and substance use disorders. Death in the United States In 2022, there were around 3.27 million deaths in the United States. The leading causes of death in the United States are currently heart disease and cancer, accounting for a combined 40 percent of all deaths in 2022. Lung and bronchus cancer is the deadliest form of cancer worldwide, as well as in the United States. In the U.S. this form of cancer is predicted to cause around 65,790 deaths among men alone in the year 2024. Prostate cancer is the second-deadliest cancer for men in the U.S. while breast cancer is the second deadliest for women. In 2022, the fourth leading cause of death in the United States was COVID-19. Deaths due to COVID-19 resulted in a significant rise in the total number of deaths in the U.S. in 2020 and 2021 compared to 2019.