COVID-19 Case Fatality Rates Research Articles

The spatial-temporal variations and influencing factors of COVID-19 case fatality rate: a worldwide study in 30 countries from February 2021 to May 2022.

To evaluate the variations in COVID-19 case fatality rates (CFRs) across different regions and waves, and the impact of public health interventions, social and economic characteristics, and demographic factors on COVID-19 CFRs, we collected data from 30 countries with the highest incidence rate in three waves. We summarized the CFRs of different countries and continents in each wave through meta-analysis. Spearman's correlation and multiple linear regression were employed to estimate the correlation between influencing factors and reduction rates of CFRs. Significant differences in CFRs were observed among different regions during the three waves (P<0.001). An association was found between the changes in fully vaccinated rates (r s =0.41), population density (r s =0.43), the proportion of individuals over 65years old (r s =0.43), and the reduction rates of case fatality rate. Compared to Wave 1, the reduction rates in Wave 2 were associated with population density (β=0.19, 95%CI: 0.05-0.33) and smoking rates (β=-4.66, 95%CI: -8.98 - -0.33), while in Wave 3 it was associated with booster vaccine rates (β=0.60, 95%CI: 0.11-1.09) and hospital beds per thousand people (β=4.15, 95%CI: 1.41-6.89). These findings suggest that the COVID-19 CFRs varied across different countries and waves, and promoting booster vaccinations, increasing hospital bed capacity, and implementing tobacco control measures can help reduce CFRs.

Sociopolitical context and COVID-19 fatality rates in OECD countries: a configurational approach

BackgroundThe effectiveness of crisis response can be influenced by various structural, cultural, and functional aspects within a social system. This study uses a configurational approach to identify combinations of sociopolitical conditions that lead to a high case fatality rate (CFR) of COVID-19 in OECD countries.MethodsA Fuzzy set qualitative comparative analysis (QCA) is conducted on a sample of 38 OECD countries. The outcome to be explained is high COVID-19 CFR. The five potentially causal conditions are level of democracy, state capacity, trust in government, health expenditure per capita, and the median age of population. A comprehensive QCA robustness test protocol is applied, which includes sensitivity ranges, fit-oriented robustness, and case-oriented robustness tests.ResultsNone of the causal conditions in both the presence and negation form were found to be necessary for high or low levels of COVID-19 CFR. Two different combinations of sociopolitical conditions were usually sufficient for the occurrence of a high CFR of COVID-19 in OECD countries. Low state capacity and low trust in government are part of both recipes. The entire solution formula covers 84 percent of the outcome. Some countries have been identified as contradictory cases. The explanations for their COVID-19 CFR require more in-depth case studies.ConclusionsFrom a governance perspective, the weakness of government in effectively implementing policies, and the citizens’ lack of confidence in their government, combined with other structural conditions, serve as barriers to mounting an effective response to COVID-19. These findings can support the idea that the effects of social determinants of COVID-19 outcomes are interconnected and reinforcing.

Epidemiological Pattern and Case Fatality Rate among COVID-19 Patients during First and Second Wave of Pandemic in Madhesh Province, Nepal

Background &amp; Objectives: Evaluating multi-wave patterns of COVID-19 infection, hospitalization, and mortality across spatial scales can inform public health strategies for future pandemics. However, there is limited understanding of these patterns in developing countries, including Nepal. This study aimed to analyze epidemiological patterns, fatality rates, and factors associated with severe outcomes during the first and second waves of COVID-19 in Madhesh Province, Nepal. Materials and Methods: This retrospective cross-sectional study used provincial health records from Madhesh Province, covering April 9, 2020, to December 15, 2021, to analyze 37,551 positive COVID-19 cases and 1,037 deaths across two waves. The study examined changes in COVID-19-related deaths, with data on demographics, residence, isolation sites, treatment hospitals, care levels, and testing laboratories. The frequency and percentage of the variables were presented. The case fatality rate (CFR) for different categories were calculated. Additionally, the case fatality rate ratio (CFRR) for the first wave against second wave was obtained. Finally, case fatality risk ratios with 95% confidence intervals were presented. A p-value of &lt;0.05 was set as statistically significant. Results: The case fatality rate (CFR) for COVID-19 was significantly higher in the second wave, especially among the elderly (≥47 years), and in institutional isolation (7.82%). Tertiary level care and private hospitals consistently showed higher CFRs. Furthermore, the multivariable analysis of risk ratios (RR) for COVID-19 case fatality in revealed that the 25–34 year age group had the highest RR (2.39). Similarly, males had a higher RR (1.42) than females, and institutional isolation had a substantially higher RR (93.33) compared to home isolation. Primary level care RR (28.11) and government hospitals RR (4.32) showed a higher risk. Place of residence also impacted the RR, with Sarlahi (7.68) having higher. Conclusion: A significant increase in COVID-19 case fatality rates during the second wave, particularly among the elderly and those in institutional isolation. Higher mortality was observed in tertiary hospitals and among those who were tested in private laboratories, with substantial variations in risk ratios based on age, isolation type, and place of residence.

Incidence of Severe COVID-19 Outcomes and Immunization Rates in Apulian Individuals with Inflammatory Bowel Disease: A Retrospective Cohort Study.

The etiology of Inflammatory Bowel Disease (IBD) is not fully understood but is believed to involve a dysregulated immune response to intestinal microbiota in genetically susceptible individuals. Individuals with IBD are at increased risk of infections due to immunosuppressive treatments, comorbidities, and advanced age. Current evidence indicates that IBD patients are not at higher risk of SARS-CoV-2 infection compared to the general population, though the risk of severe outcomes remains debated. A retrospective observational study was conducted using Apulian regional health data from 2020 to 2022. This study included 1029 IBD patients and 3075 controls, matched by age and sex. COVID-19 incidence, hospitalization, and case fatality rates were analyzed alongside vaccination coverage. No significant differences in COVID-19 incidence (IRR = 0.97), hospitalization (p = 0.218), or lethality (p = 0.271) were evidenced between IBD patients and the general population. Vaccination rates were high in both groups, with slightly higher uptake in IBD patients. Multivariate analysis identified age and male sex as risk factors for severe COVID-19 outcomes, while vaccination significantly reduced hospitalization and lethality risks. IBD patients in Apulia do not have an increased risk of COVID-19 infection or severe outcomes compared to the general population. Vaccination is crucial in protecting IBD patients, and ongoing efforts to promote vaccination within this population are essential. Future research should focus on the impact of specific IBD treatments on COVID-19 outcomes and the long-term effectiveness of vaccines.

COVID-19 Case Fatality Rates in the Texas Prison System.

The case fatality rate (CFR) is an important metric in the correctional setting because it permits assessment of the lethality of an infectious agent independent of its underlying variations in transmissibility and incidence. Several studies have reported that incarceration is associated with both increased COVID-19 incidence and mortality. CFR, sometimes referred to as infection fatality rate for COVID-19, was used to compare mortality in a population at two points in time. A retrospective cohort study design was used to assess age-adjusted mortality among people diagnosed with COVID-19 in the Texas prison system and the Texas nonincarcerated population from January 1, 2020, through December 31, 2021. For each 6-month period under study, the Texas prison population had a substantially lower age-adjusted CFR compared with the Texas nonincarcerated population. However, in the absence of information on underlying COVID-19 severity, comorbidities, and other potential confounding factors in these two populations, it is difficult to make strong inferences based on a comparison of their CFRs. Future research, with careful attention to bias and confounding, should examine the specific health system factors that may be used to reduce morbidity and mortality associated with infectious disease outbreaks in prisons.

Country-specific determinants for COVID-19 case fatality rate and response strategies from a global perspective: an interpretable machine learning framework

BackgroundThere are significant geographic inequities in COVID-19 case fatality rates (CFRs), and comprehensive understanding its country-level determinants in a global perspective is necessary. This study aims to quantify the country-specific risk of COVID-19 CFR and propose tailored response strategies, including vaccination strategies, in 156 countries.MethodsCross-temporal and cross-country variations in COVID-19 CFR was identified using extreme gradient boosting (XGBoost) including 35 factors from seven dimensions in 156 countries from 28 January, 2020 to 31 January, 2022. SHapley Additive exPlanations (SHAP) was used to further clarify the clustering of countries by the key factors driving CFR and the effect of concurrent risk factors for each country. Increases in vaccination rates was simulated to illustrate the reduction of CFR in different classes of countries.FindingsOverall COVID-19 CFRs varied across countries from 28 Jan 2020 to 31 Jan 31 2022, ranging from 68 to 6373 per 100,000 population. During the COVID-19 pandemic, the determinants of CFRs first changed from health conditions to universal health coverage, and then to a multifactorial mixed effect dominated by vaccination. In the Omicron period, countries were divided into five classes according to risk determinants. Low vaccination-driven class (70 countries) mainly distributed in sub-Saharan Africa and Latin America, and include the majority of low-income countries (95.7%) with many concurrent risk factors. Aging-driven class (26 countries) mainly distributed in high-income European countries. High disease burden-driven class (32 countries) mainly distributed in Asia and North America. Low GDP-driven class (14 countries) are scattered across continents. Simulating a 5% increase in vaccination rate resulted in CFR reductions of 31.2% and 15.0% for the low vaccination-driven class and the high disease burden-driven class, respectively, with greater CFR reductions for countries with high overall risk (SHAP value > 0.1), but only 3.1% for the ageing-driven class.ConclusionsEvidence from this study suggests that geographic inequities in COVID-19 CFR is jointly determined by key and concurrent risks, and achieving a decreasing COVID-19 CFR requires more than increasing vaccination coverage, but rather targeted intervention strategies based on country-specific risks.

Exploring COVID-19 case fatality rate trends in the UnionTerritory of Jammu &amp; Kashmir, India: A comprehensive study

Background: In 2021, India witnessed a resurgence in Coronavirus cases, marking the onset of the second wave of the pandemic, six months after the first wave peaked in September 2020. This study aims to investigate trends and disparities in COVID-19 case-fatality rates across various districts within the Union territory of Kashmir Division during the period of escalating cases after the decline of the initial wave. Methods: A cross-sectional study was conducted in a region of the Union territory of Jammu &amp; Kashmir, India. After obtaining necessary permissions, data collection took spanned from November 1, 2020, to May 8, 2021. Aggregated weekly data from various zones in India was collected during the study period and exploratory analysis was conducted. Results: The data analysis reveals that, from November 2020 to May 2021, COVID-19 cases in the Union Territory of Jammu &amp; Kashmir demonstrated fluctuating tendencies. Notably, there was a substantial surge in March 2020, especially in Srinagar, which suggests the possibility of localised breakouts or dynamics of transmission. Even though Rapid Antigen Test (RAT) positivity rates were originally low in all districts, by the end of the study period, they had significantly increased, particularly in Srinagar and Shopian. This suggests that the dynamics of virus transmission may have changed, either as a result of new variations or behavioural changes. Conclusion: Our findings highlight those disparities in case-fatality rates between districts, whether low or high, are significantly influenced by the number of confirmed cases. Case-fatality rates were highly impacted by variations in the testing accessibility, containment strategies, and healthcare infrastructure. The results highlight how crucial it is to allocate resources fairly and implement focused interventions in order to lessen the pandemic's effects and safeguard the region's public health.

Monitoring Trends and Differences in COVID-19 Case Fatality Rates in a Union Territory of India: Inferential Data Analysis

Objective: To understand the challenges posed by the second wave of COVID-19 cases in the Union Territory of Jammu and Kashmir, India. Materials and Methods: The study utilised weekly aggregated surveillance data from November 2020 to May 2021. Ethical clearance was obtained, and an exploratory trend analysis was performed using Excel 2019. Results: Distinct trends in active cases, symptomatic patients tested, case fatality rate (CFR) and rapid antigen test (RAT) positivity rates were observed across the 10 districts in the Kashmir division. Srinagar exhibited notable variations, and CFR showed district-specific differences. Conclusion: This study underscores the significance of tailored strategies, government interventions and community resilience.

Novel genetic association of the Furin gene polymorphism rs1981458 with COVID-19 severity among Indian populations

SARS CoV-2, the causative agent for the ongoing COVID-19 pandemic, it enters the host cell by activating the ACE2 receptor with the help of two proteasesi.e., Furin and TMPRSS2. Therefore, variations in these genes may account for differential susceptibility and severity between populations. Previous studies have shown that the role of ACE2 and TMPRSS2 gene variants in understanding COVID-19 susceptibility among Indian populations. Nevertheless, a knowledge gap exists concerning the COVID-19 susceptibility of Furin gene variants among diverse South Asian ethnic groups. Investigating the role of Furin gene variants and their global phylogeographic structure is essential to comprehensively understanding COVID-19 susceptibility in these populations. We have used 450 samples from diverse Indian states and performed linear regression to analyse the Furin gene variant's with COVID-19 Case Fatality Rate (CFR) that could be epidemiologically associated with disease severity outcomes. Associated genetic variants were further evaluated for their expression and regulatory potential through various Insilco analyses. Additionally, we examined the Furin gene using next-generation sequencing (NGS) data from 393 diverse global samples, with a particular emphasis on South Asia, to investigate its Phylogeographic structure among diverse world populations. We found a significant positive association for the SNP rs1981458 with COVID-19 CFR (p < 0.05) among diverse Indian populations at different timelines of the first and second waves. Further, QTL and other regulatory analyses showed various significant associations for positive regulatory roles of rs1981458 and Furin gene, mainly in Immune cells and virus infection process, highlighting their role in host immunity and viral assembly and processing. The Furin protein–protein interaction suggested that COVID-19 may contribute to Pulmonary arterial hypertension via a typical inflammation mechanism. The phylogeographic architecture of the Furin gene demonstrated a closer genetic affinity of South Asia with West Eurasian populations. Therefore, it is worth proposing that for the Furin gene, the COVID-19 susceptibility of South Asians will be more similar to the West Eurasian population. Our previous studies on the ACE2 and TMPRSS2 genes showed genetic affinity of South Asian with East Eurasians and West Eurasians, respectively. Therefore, with the collective information from these three important genes (ACE2, TMPRSS2 and Furin) we modelled COVID-19 susceptibilityof South Asia in between these two major ancestries with an inclination towards West Eurasia. In conclusion, this study, for the first time, concluded the role of rs1981458 in COVID-19 severity among the Indian population and outlined its regulatory potential.This study also highlights that the genetic structure for COVID-19 susceptibilityof South Asia is distinct, however, inclined to the West Eurasian population. We believe this insight may be utilised as a genetic biomarker to identify vulnerable populations, which might be directly relevant for developing policies and allocating resources more effectively during an epidemic.

Meteorological Conditions and PM2.5 Impact on COVID-19 Case Fatality Ratios (CFR) in Bangkok Metropolitan Region

The emergence of a novel coronavirus strain triggered a global health crisis, impacting both health and economies worldwide, including Thailand since 2019. While prior research hinted at connections between environmental factors and rising COVID-19 cases, these links remained inconclusive. This study investigated indoor and outdoor (I/O) ratios and explored potential correlations between fine particulate matter (PM2.5), meteorological conditions, and the case fatality rate (CFR%) of COVID-19 in Bangkok and its metropolitan area from January to December 2021. In Spearman’s Rank correlation analysis, the results found that CFR% exhibited a positive correlation with relative humidity (RH) (r=0.187) and a negative correlation with PM2.5 (r=-0.190) and wind speed (WS) (r=-0.039). The generalized additive model (GAM) indicated that RH, PM2.5, temperature, and WS adversely affect the CFR% of COVID-19. Consistent relationships between PM2.5, RH, and WS were observed in both Spearman’s Rank correlation and the GAM model. This study underscored the complexity of understanding pandemic dynamics across seasons, I/O ratios, and the influence of lag days. By presenting the results, they may serve as a valuable reference for planning interventions during future pandemics.

Regional disparities in COVID-19 case fatality rates: A comparative analysis of Nigerian Geopolitical Regions in 2020 and 2023

In December 2019, first case of COVID-19 was documented in the Wuhan, China. The symptoms commonly associated with COVID-19 include cough, fever, fatigue, and breathing difficulties. In 30th January 2020, the WHO declared COVID-19 a Public Health Emergency of International Concern. The coronavirus entered Nigeria through an infected Italian citizen who came in contact with a Nigerian citizen who was subsequently infected with the coronavirus. The coronavirus then spread to other citizens in Lagos and to other parts of the country. This study focuses on analysing the Case fatality rates (CFR) of COVID-19 in different geopolitical regions of Nigeria in the years 2020 and 2023. The regions considered are North Central, North East, North West, South South, South West and South East. This was a retrospective study using national surveillance data collected from all 36 States and Federal Capital Territory (FCT) in Nigeria. Epidemiological indices of COVID-19 of 12th July, 2020 and data as at 26th February, 2023 were downloaded from the official update database of the Nigeria Centre for Disease Control (NCDC) and World Health Organisation (WHO) weekly report within the same period of this study The confirmed cases and deaths were extracted directly while the Case fatality rates (CFR) were computed. The total confirmed cases, death cases, and Cases Fatality Rates (CFR) as at 12th July 2020 was 31,323, 706 and 2.3% respectively. However, in 2023, the values had changed to 440,139 confirmed cases, 3156 death cases an a CRF of 0.7% respectively. The North Central region was observed to have the highest fatality rate of 62.1% and 47.2% in 2020 and 2023 respectively. The North East accounted for 32.5% and 12.6%, Noth West 36.4% and 16.4%, South- South, 37.5% and 12.4%, South East 16.9% and 4.7% and South West 15.4% and 10.1% respectively in 2020 and 2023. The 6 geopolitical regions of the country experience decrease at different proportion in Case Fatality Rates and this can be attributed to various factors, including increased vaccination coverage, better understanding of the virus, improved healthcare infrastructure and more effective public health measures. Despite the decrease in case fatality rate, regional disparities still exist which may be linked to underlying socioeconomic and healthcare disparities between regions. Addressing these disparities is crucial for a more equitable response to future pandemics

Country-based modelling of COVID-19 case fatality rate: A multiple regression analysis.

The spread of the severe acute respiratory syndrome coronavirus 2 outbreak worldwide has caused concern regarding the mortality rate caused by the infection. The determinants of mortality on a global scale cannot be fully understood due to lack of information. To identify key factors that may explain the variability in case lethality across countries. We identified 21 Potential risk factors for coronavirus disease 2019 (COVID-19) case fatality rate for all the countries with available data. We examined univariate relationships of each variable with case fatality rate (CFR), and all independent variables to identify candidate variables for our final multiple model. Multiple regression analysis technique was used to assess the strength of relationship. The mean of COVID-19 mortality was 1.52 ± 1.72%. There was a statistically significant inverse correlation between health expenditure, and number of computed tomography scanners per 1 million with CFR, and significant direct correlation was found between literacy, and air pollution with CFR. This final model can predict approximately 97% of the changes in CFR. The current study recommends some new predictors explaining affect mortality rate. Thus, it could help decision-makers develop health policies to fight COVID-19.

Description of the COVID-19 epidemiology in Malaysia.

Since the COVID-19 pandemic began, it has spread rapidly across the world and has resulted in recurrent outbreaks. This study aims to describe the COVID-19 epidemiology in terms of COVID-19 cases, deaths, ICU admissions, ventilator requirements, testing, incidence rate, death rate, case fatality rate (CFR) and test positivity rate for each outbreak from the beginning of the pandemic in 2020 till endemicity of COVID-19 in 2022 in Malaysia. Data was sourced from the GitHub repository and the Ministry of Health's official COVID-19 website. The study period was from the beginning of the outbreak in Malaysia, which began during Epidemiological Week (Ep Wk) 4 in 2020, to the last Ep Wk 18 in 2022. Data were aggregated by Ep Wk and analyzed in terms of COVID-19 cases, deaths, ICU admissions, ventilator requirements, testing, incidence rate, death rate, case fatality rate (CFR) and test positivity rate by years (2020 and 2022) and for each outbreak of COVID-19. A total of 4,456,736 cases, 35,579 deaths and 58,906,954 COVID-19 tests were reported for the period from 2020 to 2022. The COVID-19 incidence rate, death rate, CFR and test positivity rate were reported at 1.085 and 0.009 per 1,000 populations, 0.80 and 7.57%, respectively, for the period from 2020 to 2022. Higher cases, deaths, testing, incidence/death rate, CFR and test positivity rates were reported in 2021 and during the Delta outbreak. This is evident by the highest number of COVID-19 cases, ICU admissions, ventilatory requirements and deaths observed during the Delta outbreak. The Delta outbreak was the most severe compared to other outbreaks in Malaysia's study period. In addition, this study provides evidence that outbreaks of COVID-19, which are caused by highly virulent and transmissible variants, tend to be more severe and devastating if these outbreaks are not controlled early on. Therefore, close monitoring of key epidemiological indicators, as reported in this study, is essential in the control and management of future COVID-19 outbreaks in Malaysia.

Predicting consequences of COVID-19 control measure de-escalation on nosocomial transmission and mortality: a modelling study in a French rehabilitation hospital

Infection control measures are effective for nosocomial COVID-19 prevention but bear substantial health-economic costs, motivating their "de-escalation" in settings at low risk of SARS-CoV-2 transmission. Yet consequences of de-escalation are difficult to predict, particularly in light of novel variants and heterogeneous population immunity. To estimate how infection control measure de-escalation influences nosocomial COVID-19 risk. An individual-based transmission model was used to simulate SARS-CoV-2 outbreaks and control measure de-escalation in a French long-term care hospital with multi-modal control measures in place (testing and isolation, universal masking, single-occupant rooms). Estimates of COVID-19 case fatality rates (CFRs) from reported outbreaks were used to quantify excess COVID-19 mortality due to de-escalation. In a population fully susceptible to infection, de-escalating both universal masking and single rooms resulted in hospital-wide outbreaks of 114 (95% CI: 103-125) excess infections, compared with five (three to seven) excess infections when de-escalating only universal masking or 15 (11-18) when de-escalating only single rooms. When de-escalating both measures and applying CFRs from the first wave of COVID-19, excess patient mortality ranged from 1.57 (1.41-1.71) to 9.66 (8.73-10.57) excess deaths/1000 patient-days. By contrast, when applying CFRs from subsequent pandemic waves and assuming susceptibility to infection among 40-60% of individuals, excess mortality ranged from 0 (0-0) to 0.92 (0.77-1.07) excess deaths/1000 patient-days. The de-escalation of bundled COVID-19 control measures may facilitate widespread nosocomial SARS-CoV-2 transmission. However, excess mortality is probably limited in populations at least moderately immune to infection and given CFRs resembling those estimated during the 'post-vaccine' era.

Impacts of income inequality and the mediation role of reporting delays on COVID-19 deaths during 2020 and 2021 in Hong Kong: an observational study

ObjectiveTo estimate the impacts of demographic factors and income disparities on the case fatality rate (CFR) of COVID-19 in Hong Kong, taking into account the influence of reporting delays (ie,...

Case fatality rates of COVID‐19 during epidemic periods of variants of concern: A meta-analysis by continents

ObjectivesTo calculate the case fatality rates (CFR) of COVID‐19 during epidemic periods of different variants of concern (VOC) by continents. MethodsWe systematically searched five authoritative databases (Web of Science, PubMed, Embase, Cochrane Library, and MedRxiv) for epidemiological studies on the CFR of COVID-19 published between January 1, 2020, and March 31, 2023. After identifying the epidemic trends of variants, we used a random-effects model to calculate the pooled CFRs during periods of different VOCs. This meta-analysis was conducted following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and registered with PROSPERO (CRD42023431572). ResultsThere were variations in the CFRs among different variants of COVID-19 (Alpha: 2.62%, Beta: 4.19%, Gamma: 3.60%, Delta: 2.01%, Omicron: 0.70%), and disparities in CFRs also existed among continents. On the whole, the CFRs of COVID-19 in Europe and Oceania were slightly lower than in other continents. There was a statistically significant association between the variant, HDI value, age distribution, coverage of full vaccination of cases, and the CFR. ConclusionsThe CFRs of COVID-19 varied across the epidemic periods of different VOCs, and disparities existed among continents. The CFR value reflected combined effects of various factors within a certain context. Caution should be exercised when comparing CFRs due to disparities in testing capabilities and age distribution among countries, etc.

Association of air pollution and weather conditions during infection course with COVID-19 case fatality rate in the United Kingdom

Although the relationship between the environmental factors, such as weather conditions and air pollution, and COVID-19 case fatality rate (CFR) has been found, the impacts of these factors to which infected cases are exposed at different infectious stages (e.g., virus exposure time, incubation period, and at or after symptom onset) are still unknown. Understanding this link can help reduce mortality rates. During the first wave of COVID-19 in the United Kingdom (UK), the CFR varied widely between and among the four countries of the UK, allowing such differential impacts to be assessed. We developed a generalized linear mixed-effect model combined with distributed lag nonlinear models to estimate the odds ratio of the weather factors (i.e., temperature, sunlight, relative humidity, and rainfall) and air pollution (i.e., ozone, N{O}_{2}, S{O}_{2}, CO, P{M}_{10} and P{M}_{2.5}) using data between March 26, 2020 and September 15, 2020 in the UK. After retrospectively time adjusted CFR was estimated using back-projection technique, the stepwise model selection method was used to choose the best model based on Akaike information criteria and the closeness between the predicted and observed values of CFR. The risk of death reached its maximum level when the low temperature (6 °C) occurred 1 day before (OR 1.59; 95% CI 1.52–1.63), prolonged sunlight duration (11–14 h) 3 days after (OR 1.24; 95% CI 1.18–1.30) and increased P{M}_{2.5} (19 μg/m3) 1 day after the onset of symptom (OR 1.12; 95% CI 1.09–1.16). After reopening, many COVID-19 cases will be identified after their symptoms appear. The findings highlight the importance of designing different preventive measures against severe illness or death considering the time before and after symptom onset.

A closer look: Additional study of relationship between indoor radon exposure and the Covid-19 case fatality rate

In September 2022, the author of this text asked the scientific community an astonishing question: is there a connection between the Covid-19 case fatality rate and the radon exposure in interior spaces? And – if so – is it a correlation? Is it just a coincidence or even a causality? Radon exposure is particularly high in regions that have seen high mortality rates related to SARS-CoV-2. It was demonstrated that there is at least a correlation. This statement based on a comparison of four states of Germany. Of course, such a comparison is rather vague due to various geological situations. It is relatively rough, as the measures against the spread of the SARS-CoV-2 have been different from one state in Germany to another. Due to that, this paper takes a closer look to that phenomenon. It focuses on three districts in northern Bavaria: Ansbach, Bad Kissingen and Wunsiedel. The last one is situated close to Thuringia as well as the Czech Republic. It was declared as radon preservation area – the only one in Bavaria – and is rather affected by radon. Bad Kissingen represents a region with a medium average indoor radon activity concentration. It is located at the north at the border to Hesse. Ansbach is characterized of a lower risk to get affected by radon. It is in the vicinity to Baden Wuerttemberg in the west. Even this second comparison cannot provide a definitive answer to the questions named above. Nevertheless, this article will push that topic a little forward and by that support the answer to a possible relationship between indoor radon activity concentration and the Covid-19 case fatality rate. Possibly it puts little more focus more on radon protection than it happened during the pandemic years.

Global trends in COVID-19 incidence and case fatality rates (2019-2023): a retrospective analysis.

Analyzing and comparing COVID-19 infection and case-fatality rates across different regions can help improve our response to future pandemics. We used public data from the WHO to calculate and compare the COVID-19 infection and case-fatality rates in different continents and income levels from 2019 to 2023. The Global prevalence of COVID-19 increased from 0.011 to 0.098, while case fatality rates declined from 0.024 to 0.009. Europe reported the highest cumulative infection rate (0.326), with Africa showing the lowest (0.011). Conversely, Africa experienced the highest cumulative case fatality rates (0.020), with Oceania the lowest (0.002). Infection rates in Asia showed a steady increase in contrast to other continents which observed initial rises followed by decreases. A correlation between economic status and infection rates was identified; high-income countries had the highest cumulative infection rate (0.353) and lowest case fatality rate (0.006). Low-income countries showed low cumulative infection rates (0.006) but the highest case fatality rate (0.016). Initially, high and upper-middle-income countries experienced elevated initial infection and case fatality rates, which subsequently underwent significant reductions. COVID-19 rates varied significantly by continent and income level. Europe and the Americas faced surges in infections and low case fatality rates. In contrast, Africa experienced low infection rates and higher case fatality rates, with lower- and middle-income nations exceeding case fatality rates in high-income countries over time.

Pandemic impact on aneurysmal subarachnoid hemorrhage in Peru’s high COVID-19 lethality setting: A public institutional experience

Background: The COVID-19 pandemic in 2020 profoundly impacted healthcare worldwide, and Peru was particularly affected, experiencing the highest COVID-19 case fatality rate globally. Methods: We conducted a retrospective comparative study of patients presenting with aneurysmal subarachnoid hemorrhage (SAH) at a public Peruvian national referral center specializing in cerebrovascular diseases. Two study periods were considered, one during the first wave of the COVID-19 pandemic and a second identical period in 2019. Variables included patient demographics, comorbidities, COVID-19 infection status, clinical presentation, treatment approaches, and hospital outcomes. Results: We analyzed 114 patients with aneurysmal SAH, 65 (57.0%) treated in 2019 and 49 (43.0%) in 2020. The mean time from emergency admission to the day of definitive treatment during 2019 and 2020 was 2.72 and 1.93 days, respectively. Likewise, the mean time from symptom onset to the date of definitive treatment was 6.71 and 7.70 days, respectively. We identified significant associations between complications such as sepsis, respiratory failure, acute kidney failure, and hospital mortality. The proportion of fatalities was significantly higher in 2020 compared to 2019 (36.7% vs. 15.4%, respectively). Interestingly, there was no statistically significant association between COVID-19 infection status and mortality during the 2020 period. Conclusion: Patients with aneurysmal SAH treated during the pandemic had a higher proportion of sepsis, respiratory failure, acute kidney failure, and mortality compared to the pre-pandemic period. Reallocating healthcare resources to prioritize COVID-19 patients may have inadvertently neglected or delayed care for patients with other emergency conditions, such as aneurysmal SAH. This highlights the importance of maintaining adequate care for non-infectious emergencies during a pandemic.