COVID-19 Case Fatality Rates Research Articles

The Relationship Between Poverty and COVID-19 Infection and Case-Fatality Rates in Germany during the First Wave of the Pandemic

Abstract The relationship between poverty and the infection and case-fatality rates of COVID-19 has emerged as a controversial but understudied topic. In previous studies and reports from the UK and US evidence emerged that poverty-related indicators had a significant statistical effect on case and mortality rates on district level. For Germany, it has largely been assumed that poverty is an equally relevant factor influencing the transmission rates of the outbreak. This was mostly due to anecdotal evidence from local outbreaks in meat processing plants and reported incidents of infection clusters in poorer city districts. This paper addresses the lack of statistical evidence and investigates thoroughly the link between poverty-related indicators and detected infection and mortality rates of the outbreak using multivariate, multilevel regression while also considering the urban-rural divide of the country. As proxies for poverty the unemployment rate, the per capita presence of general practitioners (physicians), per capita GDP, and the rate of employees with no professional job training is evaluated in relation to the accumulated case and mortality numbers on district level taken from RKI data of June and July 2020. Interestingly, the study finds no general evidence for a poverty-related effect on mortality for German districts during the first wave in the first half of 2020. Furthermore, only employment in low qualification jobs approximated by the job training variable consistently affected case numbers in urban districts in the expected direction.

Situation assessment and natural dynamics of COVID-19 pandemic in Nigeria, 31 May 2020

BackgroundThe coronavirus disease (COVID-19) remains a global public health issue due to its high transmission and case fatality rate. There is apprehension on how to curb the spread and mitigate the socio-economic impacts of the pandemic, but timely and reliable daily confirmed cases' estimates are pertinent to the pandemic's containment. This study therefore conducted a situation assessment and applied simple predictive models to explore COVID-19 progression in Nigeria as at 31 May 2020. MethodsData used for this study were extracted from the websites of the European Centre for Disease Control (World Bank data) and Nigeria Centre for Disease Control. Besides descriptive statistics, four predictive models were fitted to investigate the pandemic natural dynamics. ResultsThe case fatality rate of COVID-19 was 2.8%. A higher number of confirmed cases of COVID-19 was reported daily after the relaxation of lockdown than before and during lockdown. Of the 36 states in Nigeria, including the Federal Capital Territory, 35 have been affected with COVID-19. Most active cases were in Lagos (n = 4064; 59.2%), followed by Kano (n = 669; 9.2%). The percentage of COVID-19 recovery in Nigeria (29.5%) was lower compared to South Africa (50.3%), but higher compared to Kenya (24.1%). The cubic polynomial model had the best fit. The projected value for COVID-19 cumulative cases for 30 June 2020 in Nigeria was 27,993 (95% C.I: 27,001–28,986). ConclusionThe daily confirmed cases of COVID-19 are increasing in Nigeria. Increasing testing capacity for the disease may further reveal more confirmed cases. As observed in this study, the cubic polynomial model currently offers a better prediction of the future COVID-19 cases in Nigeria.

Epidemiology and Outcomes of COVID-19 in Home Dialysis Patients Compared with In-Center Dialysis Patients.

Epidemiology and Outcomes of COVID-19 in Home Dialysis Patients Compared with In-Center Dialysis Patients.

Relative risks of COVID-19 fatality between the first and second waves of the pandemic in Ontario, Canada

ObjectivesTo examine whether the case fatality rate (CFR) of COVID-19 decreased over time and whether the COVID-19 testing rate is a driving factor for the changes if the CFR decreased. MethodsAnalyzing COVID-19 cases, deaths and tests in Ontario, Canada, we compared the CFR between the first wave and the second wave across 26 public health units in Ontario. We also explored whether a high testing rate was associated with a large CFR decrease. ResultsThe first wave CFR ranged from 0.004 to 0.146, whereas the second wave CFR ranged from 0.003 to 0.034. The pooled RR estimate of second wave COVID-19 case fatality, compared with first wave, was 0.24 (95% CI: 0.19-0.32). Additionally, COVID-19 testing percentages were not associated with the estimated relative risk (P=0.246). ConclusionsThe COVID-19 CFR decreased significantly in Ontario during the second wave, and COVID-19 testing was not a driving factor for this decrease.

Does BCG vaccine prevent contract and severity of COVID-19 infection in India? A situational analysis

Background: The COVID-19 pandemic has created worldwide emergency with morbidities, mortality and panic. The BCG vaccine, usually given to prevent childhood tuberculosis, surfaced as an option as suggested by some ecological observations. However, some others studies could not establish and explain the protective effects of BCG vaccination against COVID-19 pandemic. India is one country with high BCG vaccination coverage and is among the countries with lowest COVID-19 case fatality rate. Aims and Objectives: We examine the relationship between the BCG coverage and COVID-19 burden in various states/UTs of India. Materials and methods: The information on BCG coverage and morbidity and mortality of COVID-19 was obtained from NFHS and www.covid19India.org respectively. Results: The analysis suggested very weak positive relationship of BCG coverage with cases and deaths due to COVID-19. Moderate positive relationship was observed between BCG coverage and COVID-19 case fatality rate even after adjusting for health system performance. Conclusion: The conclusion of the study is against the role of BCG vaccination in containing the COVID-19 pandemic. The positive correlation which is not significant may be spurious and affected by many confounding factors like co-morbid conditions, testing strategies, population level immunity for other viral infections etc. Hence, the states and UTs should not be complacent by the hypothesized role of BCG vaccine in COVID-19 control. Rather, they should continue with the principles of social distancing, contact tracing, treating and surveillance of COVID-19.

Sociodemographic and Health-related Determinants of COVID-19 Prevalence and Case Fatality Rate in Indonesia

Indonesia is a country with the highest COVID-19 confirmed cases and mortality rate among southeast Asian countries. This study was conducted to identify the correlation between sociodemographic factors and the number of confirmed cases and mortality rates due to COVID-19 in Indonesia. This research is an ecological study where secondary data published by the Indonesian government was used. Spearman correlation were used in this study. This study showed that sociodemographic conditions in Indonesia varied greatly. Spearman correlation test results showed that a significant relationship (p-value < 0.05) between the number of COVID-19 confirmation cases with population density, population growth, decreased mobility outside the home, hypertension and diabetes prevalence, number of health workers (general practitioners, specialist doctors, and nurses) as well as the number of COVID-19 specialized hospitals. Significant correlations (p-value < 0.05) were also shown by the relationship between COVID-19 mortality rates and a dense population, a large decrease in mobility to the workplace, number of smokers, and number of health workers. Equitable development is expected to reduce sociodemographic and health disparities so that each region has good preparedness in dealing with outbreaks without the occurrence of areas that are more severely affected by outbreaks compared to other regions.

Statistical models in trends of COVID-19 case fatality rates, India: a secondary data analysis

Background: The COVID-19 is potentially severe acute respiratory infectious disease, increasing day by day. Hence, to control of COVID-19 cases and deaths due to, study has been under taken with an objective to establish the models of trends in COVID-19 Case Fatality Rates for states of India, so that containment performance is assessed taking model as reference level. Materials and methods: The state-wise data from Kaggle website were used to study the levels and trends in Case Fatality Rate per 100 cases (Cured + Deaths) using Modified Logistic Regression Model, using SPSS-22 and Microsoft Office-10. The model is useful, where; deaths due to COVID-19 were more than one. Results: Himachal Pradesh was the best in controlling the disease, as per COVID-19 Active Cases and Case Fatality Rate. In Himachal Pradesh, COVID-19 stabilized by 45 days of presence of the disease, while, in Kerala by 100 days. Furthermore, the decline in COVID-19 in Himachal Pradesh was steadier and smoother as compared to comparable state Kerala. The worst group of states in controlling the COVID-19 Case Fatality Rate in poorest to better order was Maharashtra followed by Delhi, Rajasthan, Uttar Pradesh and Bihar, along with wide fluctuation in Active Cases and Case Fatality Rates. Conclusion: The worst affected state by COVID-19 was Maharashtra followed by Delhi, Rajasthan etc., reasons may be large movements of daily wagers/ temporary workers. Hence, the containment of COVID-19 is expected to be achieved by restriction in public movement and unrest in communities.

Do malnutrition, pre-existing morbidities, and poor household environmental conditions aggravate susceptibility to Coronavirus disease (COVID-19)? A study on under-five children in India

BackgroundThe novel Coronavirus disease 2019 (2019-nCoV) outbreak, caused by severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2), has become the worst serious global risk to humanity in the last century and linked with various risk factors. ObjectiveTo find out the risk zone associated with Coronavirus disease among children under-five age using malnourished status, pre-existing morbidity conditions, poor household environmental conditions, and also with case fatality rate (CFR) and active case rate (ACR) of COVID-19 in India. Data sources & methodsData was collected from the 4th round of the National Family Health Survey (NFHS)-4, 2015–16, and CFR and ACR of COVID-19 related data collected from the Ministry of Health and Family Welfare (MoHFW) on 18th May 2020. Mean, standard deviation, and Z-score statistical methods have been employed to identify the risk factors zone and Hot Spot analysis (Getis-Ord Gi) has been done. ResultsThe states and union territories (UTs) which have a high composite vulnerability score (CVS) of COVID-19 among under-five children are in Meghalaya (CVS = 1), Uttar Pradesh (CVS = 0.93), Jharkhand (CVS = 0.86), Bihar (CVS = 0.74), Madhya Pradesh (CVS = 0.74), and Odisha (CVS = 0.55). The states and UTs which have low composite vulnerability score of COVID-19 among under-five children are in Sikkim (CVS = -0.90), Daman & Diu (CVS = -0.76) Lakshadweep (CVS = -0.74), Kerala (CVS = -0.72), Chandigarh (CVS = -0.71). The COVID-19 high-risk zones (hot spot: 99% Confidence interval [CI]) were observed in Madhya Pradesh, Uttar Pradesh, Jharkhand, Bihar, and Meghalaya states of India, which are spatially high clustered and the low-risk zones (cold spot: 95% CI) were observed in Kerala, Mizoram states of India. ConclusionsWell-built public health measures, including rapidly searching in high focus areas and testing of COVID-19, should be performed in vulnerable regions of COVID-19.

Climate change, environmental factors, and COVID-19: Current evidence and urgent actions

Climate change, environmental factors, and COVID-19: Current evidence and urgent actions

Multilevel modeling of county-level excessive alcohol use, rurality, and COVID-19 case fatality rates in the US.

Reports of disparities in COVID-19 mortality rates are emerging in the public health literature as the pandemic continues to unfold. Alcohol misuse varies across the US and is related to poorer health and comorbidities that likely affect the severity of COVID-19 infection. High levels of pre-pandemic alcohol misuse in some counties may have set the stage for worse COVID-19 outcomes. Furthermore, this relationship may depend on how rural a county is, as access to healthcare in rural communities has lagged behind more urban areas. The objective of this study was to test for associations between county-level COVID-19 mortality, pre-pandemic county-level excessive drinking, and county rurality. We used national COVID-19 data from the New York Times to calculate county-level case fatality rates (n = 3,039 counties and county equivalents; October 1 -December 31, 2020) and other external county-level data sources for indicators of rurality and health. We used beta regression to model case fatality rates, adjusted for several county-level population characteristics. We included a multilevel component to our model and defined state as a random intercept. Our focal predictor was a single variable representing nine possible combinations of low/mid/high alcohol misuse and low/mid/high rurality. The median county-level COVID-19 case fatality rate was 1.57%. Compared to counties with low alcohol misuse and low rurality (referent), counties with high levels of alcohol and mid (β = -0.17, p = 0.008) or high levels of rurality (β = -0.24, p<0.001) demonstrated significantly lower case fatality rates. Our findings highlight the intersecting roles of county-level alcohol consumption, rurality, and COVID-19 mortality.

Covid-19 in end-stage renal disease patients with renal replacement therapies: A systematic review and meta-analysis

The novel coronavirus (COVID-19), caused by SARS-CoV-2, showed various prevalence and case-fatality rates (CFR) among patients with different pre-existing chronic conditions. End-stage renal disease (ESRD) patients with renal replacement therapy (RRT) might have a higher prevalence and CFR due to reduced immune function from uremia and kidney tropism of SARS-CoV-2, but there was a lack of systematic study on the infection and mortality of the SARS-CoV-2 infection in ESRD patients with various RRT. We searched five electronic databases and performed a systematic review and meta-analysis up to June 30, 2020, to evaluate the prevalence and case fatality rate (CFR) of the COVID-19 infection among ESRD patients with RRT. The global COVID-19 data were retrieved from the international database on June 30, 2020, for estimating the prevalence and CFR of the general population as referencing points. Of 3,272 potential studies, 34 were eligible studies consisted of 1,944 COVID-19 confirmed cases in 21,873 ESRD patients with RRT from 12 countries in four WHO regions. The overall pooled prevalence in ESRD patients with RRT was 3.10% [95% confidence interval (CI) 1.25-5.72] which was higher than referencing 0.14% global average prevalence. The overall estimated CFR of COVID-19 in ESRD patients with RRT was 18.06% (95% CI 14.09-22.32) which was higher than the global average at 4.98%. This meta-analysis suggested high COVID-19 prevalence and CFR in ESRD patients with RRT. ESRD patients with RRT should have their specific protocol of COVID-19 prevention and treatment to mitigate excess cases and deaths.

A County-Level Analysis of Socioeconomic and Clinical Predictors of COVID-19 Incidence and Case-Fatality Rates in Georgia, March-September 2020.

The global COVID-19 pandemic has affected various populations differently. We investigated the relationship between socioeconomic determinants of health obtained from the Robert Wood Johnson Foundation County Health Rankings and COVID-19 incidence and mortality at the county level in Georgia. We analyzed data on COVID-19 incidence and case-fatality rates (CFRs) from the Georgia Department of Public Health from March 1 through August 31, 2020. We used repeated measures generalized linear mixed models to determine differences over time in Georgia counties among quartile health rankings of health outcomes, health behaviors, clinical care, social and economic factors, and physical environment. COVID-19 incidence per 100 000 population increased across all quartile county groups for all health rankings (range, 23.1-51.6 in May to 688.4-1062.0 in August). COVID-19 CFRs per 100 000 population peaked in April and May (range, 3312-6835) for all health rankings, declined in June and July (range, 827-5202), and increased again in August (range, 1877-3310). Peak CFRs occurred later in counties with low health rankings for health behavior and clinical care and in counties with high health rankings for social and economic factors and physical environment. All interactions between the health ranking quartile variables and month were significant (P < .001). County-level Gini indices were associated with significantly higher rates of COVID-19 incidence (P < .001) but not CFRs. From March through August 2020, COVID-19 incidence rose in Georgia's counties independent of health rankings categorization. Differences in time to peak CFRs differed at the county level based upon key health rankings. Public health interventions should incorporate unique strategies to improve COVID-19-related patient outcomes in these environments.

Anxiety during the Pandemic: Racial and ethnic differences in the trajectory of fear

BackgroundIn addition to the threat of serious illness, COVID-19 brought abrupt changes in lifestyle resulting in widespread fear among many Americans. This study examines the evolution of anxiety over the first months of the COVID-19 pandemic, testing for differential experiences among vulnerable populations. MethodsPhase 1 of the Census Bureau's Household Pulse Survey details the frequency of anxiety among a nationally representative sample of adults from April 23, 2020 through July 21, 2020. Negative binomial regression assessed differences in the frequency of anxiety among demographic, income, health and employment status cohorts. Propensity score matching to the 2019 National Health Interview Survey allowed previous anxiety and health status to be included in the model. ResultsAnxiety frequency for 944,719 individuals was observed over three months. Whites, blacks and Hispanics showed increasing frequency of anxiety over the time period, particularly blacks. Prior to COVID-19, 13% of respondents reported regular or semiregular anxiety, compared to 25–35% during the pandemic. Regression analysis suggests that frequent anxiety was highly and positively correlated with COVID-19 case fatality rate and higher levels of frequency were observed among those with poor health, incomes below $25,000, and without paid employment. LimitationsCausal inference was not able to be investigated due to the cross-sectional study design. ConclusionsWhile blacks showed lower levels of anxiety initially, the proportion of the population experiencing regular anxiety increased nearly 20% over the first months of the COVID-19 pandemic. This rapid increase in anxiety could be due to inequity in health and economic outcomes among blacks.

Association between fatality rate of COVID-19 and selenium deficiency in China

BackgroundCOVID-19 has impacted populations around the world, with the fatality rate varying dramatically across countries. Selenium, as one of the important micronutrients implicated in viral infections, was suggested to play roles.MethodsAn ecological study was performed to assess the association between the COVID-19 related fatality and the selenium content both from crops and topsoil, in China.ResultsTotally, 14,045 COVID-19 cases were reported from 147 cities during 8 December 2019–13 December 2020 were included. Based on selenium content in crops, the case fatality rates (CFRs) gradually increased from 1.17% in non-selenium-deficient areas, to 1.28% in moderate-selenium-deficient areas, and further to 3.16% in severe-selenium-deficient areas (P = 0.002). Based on selenium content in topsoil, the CFRs gradually increased from 0.76% in non-selenium-deficient areas, to 1.70% in moderate-selenium-deficient areas, and further to 1.85% in severe-selenium-deficient areas (P < 0.001). The zero-inflated negative binomial regression model showed a significantly higher fatality risk in cities with severe-selenium-deficient selenium content in crops than non-selenium-deficient cities, with incidence rate ratio (IRR) of 3.88 (95% CIs: 1.21–12.52), which was further confirmed by regression fitting the association between CFR of COVID-19 and selenium content in topsoil, with the IRR of 2.38 (95% CIs: 1.14–4.98) for moderate-selenium-deficient cities and 3.06 (1.49–6.27) for severe-selenium-deficient cities.ConclusionsRegional selenium deficiency might be related to an increased CFR of COVID-19. Future studies are needed to explore the associations between selenium status and disease outcome at individual-level.

Local Response to the COVID-19 Pandemic: The Case of Indonesia

Local governments play an important role in the COVID-19 pandemic response. They can identify the local vulnerabilities and respond accordingly. In this commentary, we are examining the relationship between COVID-19 case and fatality numbers and provincial governments in Indonesia using correlations and data visualization. We use the public health development index, regional sustainable development index, competitiveness index, and their components as proxies for provincial government capacity and strength. We have found some evidence of a negative relationship between COVID-19 case fatality and death rates and various indices of provincial strength. The correlations are higher when we examine provinces in island regions, such as Java and Sumatra, separately. Some of our findings suggest that stronger provincial governments are a good defense against the pandemic. At the same time there are differences between regions, which is a concern in terms of all-of-government response to the pandemic.

The relationship between measures of individualism and collectivism and the impact of COVID-19 across nations

BackgroundThe global COVID-19 pandemic has been characterized by marked variations in prevalence, mortality and case fatality across nations. The available evidence to date suggests that social factors significantly influence these variations. The sociological concepts of individualism and collectivism provide a broad explanatory framework for the study of these factors. There is evidence to suggest that cross-cultural variations in collectivism may have emerged via a process of natural selection, as a protective mechanism against infectious diseases. As a test of this hypothesis, this paper examined the association between indices of individualism and collectivism and the prevalence, mortality and case fatality rates of COVID-19 across nations. Study designThis study was a population-level association study based on data in the public domain and from prior publications. MethodsData on four standard measures of individualism/collectivism were obtained from the original publications. These were correlated with estimates of the nation-wide prevalence, mortality and fatality rates for COVID-19 in 94 countries, obtained from the Johns Hopkins Medical University real-time dashboard. ResultsIndividualism was positively correlated with COVID-19 prevalence, mortality and case fatality rates; conversely, measures of collectivism were negatively correlated with these parameters. The strongest association was between scores for individualism and mortality rate, and remained significant after correcting for several potential confounders. ConclusionsThese findings are consistent with the prior hypothesis of a relationship between individualism-collectivism and the impact of infectious disease across populations, and have implications in terms of social strategies aimed at minimizing the impact of COVID-19.

COVID-19 case-fatality disparities among people with intellectual and developmental disabilities: Evidence from 12 US jurisdictions

BackgroundThere is evidence from two US states that people with intellectual and developmental disabilities (IDD) are at more severe risk during the COVID-19 pandemic. Research has not explored whether this increased risk is consistent across the US. ObjectiveThis study compared COVID-19 case-fatality rates among people with IDD in 11 states and the District of Columbia that are publicly reporting data. MethodsCumulative data reported through March 31 – April 13, 2021 were analyzed. Case-fatality rates and risk ratio with 95% confidence intervals for IDD settings were compared the overall case-fatality rate for the jurisdictions from Johns Hopkins’ Center for Systems Science and Engineering COVID-19 data. ResultsSettings were reported as receiving any services, community or institutional residential services, or living in own/family home. Comparison of case-fatality rates between people with IDD and their respective jurisdiction populations demonstrates that case-fatality rates were consistently higher for people with IDD living in congregate residential settings (fifteen instances) and receiving 24/7 nursing services (two instances). Results were mixed for people with IDD living in their own or a family home (eight instances). ConclusionsThese findings highlight that people with IDD, especially those living in residential settings, are experiencing higher case-fatality rates from COVID-19 than the general population across multiple US jurisdictions. Short-term and long-term public health interventions addressing COVID-19 risks will not be able to properly address the needs of people with IDD until all states begin reporting COVID-19 outcomes for this population.

Determinants of COVID-19 Case Fatality Rate in the United States: Spatial Analysis Over One Year of the Pandemic.

Background: The United States continues to account for the highest proportion of the global Coronavirus Disease-2019 (COVID-19) cases and deaths. Currently, it is important to contextualize COVID-19 fatality to guide mitigation efforts.Objectives: The objective of this study was to assess the ecological factors (policy, health behaviors, socio-economic, physical environment, and clinical care) associated with COVID-19 case fatality rate (CFR) in the United States.Methods: Data from the New York Times’ COVID-19 repository and the Centers for Disease Control and Prevention Data (01/21/2020 - 02/27/2021) were used. County-level CFR was modeled using the Spatial Durbin model (SDM). The SDM estimates were decomposed into direct and indirect impacts.Results: The study found percent positive for COVID-19 (0.057% point), stringency index (0.014% point), percent diabetic (0.011% point), long-term care beds (log) (0.010% point), premature age-adjusted mortality (log) (0.702 % point), income inequality ratio (0.078% point), social association rate (log) (0.014% point), percent 65 years old and over (0.055% point), and percent African Americans (0.016% point) in a given county were positively associated with its COVID-19 CFR. The study also found food insecurity, long-term beds (log), mental health-care provider (log), workforce in construction, social association rate (log), and percent diabetic of a given county as well as neighboring county were associated with given county’s COVID-19 CFR, indicating significant externalities.Conclusion: The spatial models identified percent positive for COVID-19, stringency index, elderly, college education, race/ethnicity, residential segregation, premature mortality, income inequality, workforce composition, and rurality as important ecological determinants of the geographic disparities in COVID-19 CFR.

Regime shifts in the COVID-19 case fatality rate dynamics: A Markov-switching autoregressive model analysis

The 2019 novel coronavirus disease (COVID-19) has spread rapidly to many countries around the world from Wuhan, the capital of China’s Hubei province since December 2019. It has now a huge effect on the global economy. As of 13 September 2020, more than 28, 802, 775, and 920, 931 people are infected and dead, respectively. The mortality of COVID-19 infections is increasing as the number of infections increase. Many countries published control measures to contain its spread. Even though there are many drugs and vaccines under trial by pharmaceutical companies and research groups, no specific vaccine or drug has yet been found. Therefore, it is necessary to explain the behaviour of the case fatality rate (CFR) of COVID-19 using the most updated COVID-19 epidemiological data before 13 September 2020. The dynamics in the CFR were analyzed using the Markov-switching autoregressive (MSAR) models. Results showed that the two-regime and three-regime MSAR approach better captured the non-linear dynamics in the CFR time series data for each of the top heavily infected countries including the world. The results also showed that rises in CFRs are more volatile than drops. We believe that this information can be useful for the government to establish appropriate policies in a timely manner.

Factors potentially influencing case fatality rate in different stages of COVID-19 outbreak in Europe

IntroductionThe aim of this study was to analyze the changes in COVID-19 case fatality rates (CFR) in time and to examine the link between CFR and country-specific indicators referring to quality of healthcare, population and epidemiology in different stages of the COVID-19 outbreak in 30 European countries (EU27 + Switzerland, Norway and United Kingdom).Material and methodsWe distinguished three 70-day time phases of the outbreak: 17 March–25 May; 1 June–9 August; 15 August–23 October 2020. The applied COVID-19 dataset was based on data maintained by OurWorldInData.org retrieved in November 2020. Spearman’s rank correlation coefficient analysis was used to examine the link between CFR and country-specific indicators referring to population, epidemiology and quality of healthcare.ResultsCOVID-19 CFR in analyzed European countries declined from mid-March to end-October. CFR phase 1 was positively correlated with COVID-19 mortality, daily cumulative index (DCI), urbanization and proportion of the population aged &gt; 80; CFR phase 2 was positively correlated with COVID-19 mortality and DCI; CFR phase 3 was positively correlated with COVID-19 mortality, median age, poverty, prevalence of obesity, smoking and cardiovascular disease and negatively correlated with Healthcare Access and Quality Index, Health Care Index and gross domestic product per capita.ConclusionsResults of our correlation analyses support the concept that the decline in CFR is real and, depending of the phase of the outbreak, different factors play a role. From the public health perspective, measures implemented to reduce the viral transmission, isolating the most vulnerable and improving the overall quality of the healthcare system are advisable.