State-specific fertility rate changes across the USA following the first two waves of COVID-19.

STUDY QUESTION: How did the first two coronavirus disease 2019 (COVID-19) waves affect fertility rates in the USA? SUMMARY ANSWER: States differed widely in how their fertility rates changed following the COVID-19 outbreak and these changes were influenced more by state-level economic, racial, political, and social factors than by COVID-19 wave severity. WHAT IS KNOWN ALREADY: The outbreak of the COVID-19 pandemic contributed to already declining fertility rates in the USA, but not equally across states. Identifying drivers of differential changes in fertility rates can help explain variations in demographic shifts across states in the USA and motivate policies that support families in general, not only during crises. STUDY DESIGN, SIZE, DURATION: This is an ecological study using state-level data from 50 US states and the District of Columbia (n = 51). The study period extends from 2020 to 2021 with historical data from 2016 to 2019. We identified Wave 1 as the first apex for each state after February 2020 and Wave 2 as the second apex, during Fall/Winter 2020-2021. PARTICIPANTS/MATERIALS, SETTING, METHODS: State-level COVID-19 wave severity, defined as case acceleration during each 3-month COVID-19 wave (cases/100 000 population/month), was derived from 7-day weekly moving average COVID-19 case rates from the US Centers for Disease Control and Prevention (CDC). State-level fertility rate changes (change in average monthly fertility rate/100 000 women of reproductive age (WRA)/year) were derived from the CDC Bureau of Vital Statistics and from 2020 US Census and University of Virginia 2021 population estimates 9 months after each COVID-19 wave. We performed univariate analyses to describe national and state-level fertility rate changes following each wave, and simple and multivariable linear regression analyses to assess the relation of COVID-19 wave severity and other state-level characteristics with fertility rate changes. MAIN RESULTS AND THE ROLE OF CHANCE: Nationwide, fertility dropped by 17.5 births/month/100 000 WRA/year following Wave 1 and 9.2 births/month/100 000 WRA/year following Wave 2. The declines following Wave 1 were largest among majority-Democrat, more non-White states where people practiced greater social distancing. Greater COVID-19 wave severity was associated with steeper fertility rate decline post-Wave 1 in simple regression, but the association was attenuated when adjusted for other covariates. Adjusting for the economic impact of the pandemic (hypothesized mediator) also attenuated the effect. There was no relation between COVID-19 wave severity and fertility rate change following Wave 2. LIMITATIONS, REASONS FOR CAUTION: Our study harnesses state-level data so individual-level conclusions cannot be inferred. There may be residual confounding in our multivariable regression and we were underpowered to detect some effects. WIDER IMPLICATIONS OF THE FINDINGS: The COVID-19 pandemic initially impacted the national fertility rate but, overall, the fertility rate rebounded to the pre-pandemic level following Wave 2. Consistent with prior literature, COVID-19 wave severity did not appear to predict fertility rate change. Economic, racial, political, and social factors influenced state-specific fertility rates during the pandemic more than the severity of the outbreak alone. Future studies in other countries should also consider whether these factors account for internal heterogeneity when examining the impact of the COVID-19 pandemic and other crises on fertility. STUDY FUNDING/COMPETING INTEREST(S): L.G.K. received funding from the National Institute of Environmental Health Sciences (R00ES030403), M.C. from the National Science Foundation Graduate Research Fellowship Program (20-A0-00-1005789), and M.L. and E.S. from the National Institute of Environmental Health Sciences (R01ES032808). None of the authors have competing interests. TRIAL REGISTRATION NUMBER: N/A.

Corrigendum: Transmissibility, hospitalization, and intensive care admissions due to omicron compared to delta variants of SARS-CoV-2 in Catalonia: A cohort study and ecological analysis.

[This corrects the article DOI: 10.3389/fpubh.2022.961030.].

Correlations between SARS-CoV-2 Infections and the Number of COVID-19 Vaccine Doses Administered in Three Italian Provinces.

The aim of this ecological study is to evaluate correlations between the number of COVID-19 vaccine doses administered in three Italian provinces-one in the south, one in the center and one in the north of the country-and the registered numbers of COVID-19 cases in the same areas. The period of January 2021-September 2022 was considered, with specific analysis for fractions of times corresponding to the spread in Italy of the different SARS-CoV-2 variants. The results confirm the reduction of the effectiveness of the vaccines in preventing new COVID-19 cases in Italy, regardless of latitude, after the appearance of the first omicron variants. The new variants omicron 4 and 5 showed an extremely high spread during the Italian summer months; fortunately, the effects of the vaccinations in preventing new cases was improved compared to the previous omicron variants, showing a negative correlation between the new COVID-19 cases and the number of vaccine doses administered.

Amplified effect of social vulnerability on health inequality regarding COVID-19 mortality in the USA: the mediating role of vaccination allocation.

BACKGROUND: Vaccination reduces the overall burden of COVID-19, while its allocation procedure may introduce additional health inequality, since populations characterized with certain social vulnerabilities have received less vaccination and been affected more by COVID-19. We used structural equation modeling to quantitatively evaluate the extent to which vaccination disparity would amplify health inequality, where it functioned as a mediator in the effect pathways from social vulnerabilities to COVID-19 mortality. METHODS: We used USA nationwide county (n = 3112, 99% of the total) level data during 2021 in an ecological study design. Theme-specific rankings of social vulnerability index published by CDC (latest data of 2018, including socioeconomic status, household composition & disability, minority status & language, and housing type & transportation) were the exposure variables. Vaccination coverage rate (VCR) during 2021 published by CDC was the mediator variable, while COVID-19 case fatality rate (CFR) during 2021 published by John Hopkinson University, the outcome variable. RESULTS: Greater vulnerabilities in socioeconomic status, household composition & disability, and minority status & language were inversely associated with VCR, together explaining 11.3% of the variance of VCR. Greater vulnerabilities in socioeconomic status and household composition & disability were positively associated with CFR, while VCR was inversely associated with CFR, together explaining 10.4% of the variance of CFR. Our mediation analysis, based on the mid-year data (30th June 2021), found that 37.6% (mediation/total effect, 0.0014/0.0037), 10% (0.0003/0.0030) and 100% (0.0005/0.0005) of the effects in the pathways involving socioeconomic status, household composition & disability and minority status & language, respectively, were mediated by VCR. As a whole, the mediation effect significantly counted for 30.6% of COVID-19 CFR disparity. Such a mediation effect was seen throughout 2021, with proportions ranging from 12 to 32%. CONCLUSIONS: Allocation of COVID-19 vaccination in the USA during 2021 led to additional inequality with respect to COVID-19 mortality. Viable public health interventions should be taken to guarantee an equitable deployment of healthcare recourses across different population groups.

Late surges in COVID-19 cases and varying transmission potential partially due to public health policy changes in 5 Western states, March 10, 2020-January 10, 2021.

OBJECTIVE: This study investigates the SARS-CoV-2 transmission potential in North Dakota, South Dakota, Montana, Wyoming, and Idaho from March 2020 through January 2021. METHODS: Time-varying reproduction numbers, R t , of a 7-day-sliding-window and of non-overlapping-windows between policy changes were estimated utilizing the instantaneous reproduction number method. Linear regression was performed to evaluate if per-capita cumulative case-count varied across counties with different population size or density. RESULTS: The median 7-day-sliding-window R t estimates across the studied region varied between 1 and 1.25 during September through November 2020. Between November 13 and 18, R t was reduced by 14.71% (95% credible interval, CrI, [14.41%, 14.99%]) in North Dakota following a mask mandate; Idaho saw a 1.93% (95% CrI [1.87%, 1.99%]) reduction and Montana saw a 9.63% (95% CrI [9.26%, 9.98%]) reduction following the tightening of restrictions. High-population and high-density counties had higher per-capita cumulative case-count in North Dakota on June 30, August 31, October 31, and December 31, 2020. In Idaho, North Dakota, South Dakota and Wyoming, there were positive correlations between population size and per-capita weekly incident case-count, adjusted for calendar time and social vulnerability index variables. CONCLUSIONS: R t decreased after mask mandate during the region's case-count spike suggested reduction in SARS-CoV-2 transmission.

Transmissibility, hospitalization, and intensive care admissions due to omicron compared to delta variants of SARS-CoV-2 in Catalonia: A cohort study and ecological analysis.

Purpose: We aim to compare the severity of infections between omicron and delta variants in 609,352 SARS-CoV-2 positive cases using local hospitalization, vaccination, and variants data from the Catalan Health Care System (which covers around 7. 8 million people). Methods: We performed a substitution model to establish the increase in transmissibility of omicron using variant screening data from primary care practices (PCP) and hospital admissions. In addition, we used this data from PCP to establish the two periods when delta and omicron were, respectively, dominant (above 95% of cases). After that, we performed a population-based cohort analysis to calculate the rates of hospital and intensive care unit (ICU) admissions for both periods and to estimate reduction in severity. Rate ratios (RR) and 95% confidence intervals (95% CI) were calculated and stratified by age and vaccination status. In a second analysis, the differential substitution model in primary care vs. hospitals allowed us to obtain a population-level average change in severity. Results: We have included 48,874 cases during the delta period and 560,658 during the omicron period. During the delta period, on average, 3.8% of the detected cases required hospitalization for COVID-19. This percentage dropped to 0.9% with omicron [RR of 0.46 (95% CI: 0.43 to 0.49)]. For ICU admissions, it dropped from 0.8 to 0.1% [RR 0.25 (95% CI: 0.21 to 0.28)]. The proportion of cases hospitalized or admitted to ICU was lower in the vaccinated groups, independently of the variant. Omicron was associated with a reduction in risk of admission to hospital and ICU in all age and vaccination status strata. The differential substitution models showed an average RR between 0.19 and 0.50. Conclusion: Both independent methods consistently show an important decrease in severity for omicron relative to delta. The systematic reduction happens regardless of age. The severity is also reduced for non-vaccinated and vaccinated groups, but it remains always higher in the non-vaccinated population. This suggests an overall reduction in severity, which could be intrinsic to the omicron variant. The fact is that the RR in ICU admission is systematically smaller than in hospitalization points in the same direction.

A Self-Managed Online Mindfulness Program in a University-Wide Learning Management System Orientation Site: A Real-World Ecological Validation Study.

The efficacy of mindfulness-based interventions in randomised-controlled trials and large experimental studies has been demonstrated in university student populations. Whilst these investigations have provided insight into the nature of the delivery of mindfulness-based practices, there has been little research in the implementation of self-managed online student wellbeing and mindfulness programs at university. This ecological validation study conducted in 2020 evaluated a real-world implementation of a large, university-wide, online mindfulness-based program that was accessible fully online via the tertiary institutions' Learning Management System (LMS) student orientation site. The total sample included 833 participants from a range of disciplines and faculties at Monash University, Australia. At the end of the study, 236 (28.3%) participants were retained and completed the follow-up survey. Participants had the option to engage with the fully self-managed online mindfulness program for a 12-week semester. The mindfulness practices were pre-recorded, audio-guided sessions, and 10-15 min in length. Baseline and end of semester questionnaires included the 14-item Warwick-Edinburgh Mental Wellbeing Scale, 10-item Perceived Stress Scale and the 18-item Five Facet Mindfulness Questionnaire. Participants who engaged with the mindfulness program over 3 or more weeks showed significant improvements in all three outcome measures, and all participants showed significant improvements in wellbeing at the end of semester. Learning analytics obtained via the LMS revealed that 58.6% (n = 489) had not logged into the mindfulness program at all, almost a third (31.0%, n = 259) logged into the program materials once or twice, and 10.2% (n = 85) of the whole sample engaged with the program actively, having logged in three or more times. The total number of student logins peaked in week 2, reduced between week 2 and week 7 and thereafter activity remained stable until the end of the semester. We hypothesise that the changes in wellbeing, stress and mindfulness at the end of the semester seen in the low engagement participants may partly be explained by the circumstances of COVID-19 restrictions improving. This study has revealed and discusses the complexities of student behaviour and implications for implementing an online mindfulness program in the real- world setting of a university.

The association between greenness exposure and COVID-19 incidence in South Korea: An ecological study.

BACKGROUND: The rapid spread of COVID-19 has caused an emergency situation worldwide. Investigating the association between environmental characteristics and COVID-19 incidence can be of the occurrence and transmission. The objective of this study was to evaluate the association between greenness exposure and COVID-19 cases at the district levels in South Korea. We also explored this association by considering several environmental indicators. METHODS: District-level data from across South Korea were used to model the cumulative count of COVID-19 cases per 100,000 persons between January 20, 2020, and February 25, 2021. Greenness exposure data were derived from the Environmental Geographic Information Service of the Korean Ministry of Environment. A negative binomial mixed model evaluated the association between greenness exposure and COVID-19 incidence rate at the district level. Furthermore, we assessed this association between demographic, socioeconomic, environmental statuses, and COVID-19 incidence. RESULTS: Data from 239 of 250 districts (95.6%) were included in the analyses, resulting in 127.89 COVID-19 cases per 100,000 persons between January 20, 2020 and February 25, 2021. Several demographic and socioeconomic variables, districts with a higher rate of natural greenness exposure, were significantly associated with lower COVID-19 incidence rates (incidence rate ratio (IRR), 0.70; 95% confidence interval (CI), 0.54-0.90; P-value = 0.008) after adjusting covariates, but no evidence for the association between built greenness and COVID-19 incidence rates was found. CONCLUSION: In this ecological study of South Korea, we found that higher rates of exposure to natural greenness were associated with lower rates of COVID-19 cases.

Causal Effect of the Tokyo 2020 Olympic and Paralympic Games on the Number of COVID-19 Cases under COVID-19 Pandemic: An Ecological Study Using the Synthetic Control Method.

Previous studies have not assessed the causal effect of the Olympic Games on the spread of pandemics. Using the synthetic control method and the national public city data in Japan recorded from February to September 2021, we estimated the causal effects of the Tokyo 2020 Olympic and Paralympic Games on the number of coronavirus disease 2019 (COVID-19) cases. The difference between the number of COVID-19 cases in Tokyo and a counterfactual "synthetic Tokyo" (created using synthetic control method) after the opening of the Tokyo 2020 Games (23 July 2021) widened gradually and then considerably over time. It was predicted that the Tokyo 2020 Games increased the number of COVID-19 cases in Tokyo by approximately 469.4 per 100,000 population from the opening of the event to 30 September. However, sensitivity analysis of the ratio of the pre- and post-game root mean square prediction errors using regression weights did not suggest robustness. Our results showed that the Tokyo 2020 Games probably increased the number of COVID-19 cases even under preventive regulations; however, the extent of this increase was difficult to estimate clearly due to an overlap with the fifth wave associated with the Delta variant.

Geographical distribution of trace elements (selenium, zinc, iron, copper) and case fatality rate of COVID-19: a national analysis across conterminous USA.

Severe outcome particularly death is the largest burden of COVID-19. Clinical observations showed preliminary data that deficiency in certain trace elements, essential for the normal activity of immune system, may be associated with worse COVID-19 outcome. Relevant study of environmental epidemiology has yet to be explored. We investigated the geographical association between concentrations of Se, Zn, Fe and Cu in surface soils and case fatality rate of COVID-19 in USA. Two sets of database, including epidemiological data of COVID-19 (including case fatality rate, from the University of John Hopkinson) and geochemical concentration data of Se, Zn, Fe and Cu in surface soils (from the National Geochemical Survey), were mapped according to geographical location at the county level across conterminous USA. Characteristics of population, socio-demographics and residential environment by county were also collected. Seven cross-sectional sampling dates, with a 4-week interval between adjacent dates, constructed an observational investigation over 24 weeks from October 8, 2020, to March 25, 2021. Multivariable fractional (logit) outcome regression analyses were used to assess the association with adjustment for potential confounding factors. In USA counties with the lowest concentration of Zn, the case fatality rate of COVID-19 was the highest, after adjustment for other influencing factors. Associations of Se, Fe and Cu with case fatality rate of COVID-19 were either inconsistent over time or disappeared after adjustment for Zn. Our large study provides epidemiological evidence suggesting an association of Zn with COVID-19 severity, suggesting Zn deficiency should be avoided.

The effect of known and unknown confounders on the relationship between air pollution and Covid-19 mortality in Italy: A sensitivity analysis of an ecological study based on the E-value.

Back in December 2019, the novel coronavirus disease 2019 (Covid-19) started rapidly spreading worldwide, especially in Italy that was among the most affected countries. The geographical distribution of air pollution and Covid-19 mortality in Italy suggested atmospheric pollution as a worsening factor of severe Covid-19 health outcomes. The present nationwide ecological study focused on all 107 Italian territorial areas, aiming to assess the potential association between Particulate Matter concentration, less than 2.5 µm in diameter (exposure), and Covid-19 mortality rate (outcome) throughout 2020, by looking at 28 potential confounders. A potential positive association between exposure and outcome was observed when performing a multivariate regression analysis with a Negative Binomial model, suggesting that an increase of 1 µg/m3 in the exposure is associated with an increase of 9.0% (95% CI: 6.5%-11.6%) in the average Covid-19 mortality rate, conditional on all 28 potential confounders. A sensitivity analysis, based on the E-value, shows that a hypothetical unmeasured confounder would have to be associated with both PM2.5 concentration and Covid-19 mortality rate by a rate ratio of at least 1.40-fold each to explain away the exposure-outcome association, conditional on all 28 covariates included in the main analysis model. Moreover, the Observed Covariate E-value (OCE) was reported to provide a contextualization of the E-value on the observed covariates included in the study. The OCE sensitivity analysis shows that a set of unknown confounders similar in size and magnitude to the set of the considered climatic factors could potentially explain away the estimated exposure-outcome association. Consequently, the role of climatic factors in the Covid-19 pandemic is worth of further investigation.

The association between malaria prevalence and COVID-19 mortality.

BACKGROUND: The number of persons infected with COVID-19 continues to increase with deaths reported daily across the globe. High income countries such as the US, the UK, Italy and Belgium have reported high COVID-19 related deaths but low-and-middle-income countries have recorded fewer deaths despite having poor healthcare system. This study aimed to investigate the association between malaria prevalence and COVID-19 mortality. METHODS: An ecological study was conducted with data from 195 countries. Spearman's correlation was used to test the association between the population variables and COVID-19 mortality. Generalized linear model with Poisson distribution was used to determine the significant predictors of COVID-19 mortality. RESULTS: There was a significant positive correlation between median age, life expectancy, 65+ mortality and COVID-19 mortality while malaria prevalence, sex ratio and cardiovascular mortality were negatively correlated with COVID-19 mortality. Malaria prevalence, life expectancy and mortality rate were significant on multivariate regression analysis. CONCLUSION: The results of this study support the hypotheses that there are reduced COVID-19 deaths in malaria endemic countries, although the results need to be proved further by clinical trials.

An Ecological Study Assessing the Relationship between Public Health Policies and Severity of the COVID-19 Pandemic.

Reliance on government-led policies have heightened during the COVID-19 pandemic. Further research on the policies associated with outcomes other than mortality rates remains warranted. We aimed to determine associations between government public health policies on the severity of the COVID-19 pandemic. This ecological study including countries reporting ≥25 daily COVID-related deaths until end May 2020, utilised public data on policy indicators described by the Blavatnik school of Government. Associations between policy indicators and severity of the pandemic (mean mortality rate, time to peak, peak deaths per 100,000, cumulative deaths after peak per 100,000 and ratio of mean slope of the descending curve to mean slope of the ascending curve) were measured using Spearman rank-order tests. Analyses were stratified for age, income and region. Among 22 countries, containment policies such as school closures appeared effective in younger populations (rs = -0.620, p = 0.042) and debt/contract relief in older populations (rs = -0.743, p = 0.009) when assessing peak deaths per 100,000. In European countries, containment policies were generally associated with good outcomes. In non-European countries, school closures were associated with mostly good outcomes (rs = -0.757, p = 0.049 for mean mortality rate). In high-income countries, health system policies were generally effective, contrasting to low-income countries. Containment policies may be effective in younger populations or in high-income or European countries. Health system policies have been most effective in high-income countries.

Assessing Health Consequences of Vitamin D Fortification Utilizing a Societal Experiment Design: Methodological Lessons Learned from the D-Tect Project.

By utilizing historical changes in Danish legislation related to mandatory vitamin D fortification of margarine, which was implemented in the mid 1930s and abruptly abandoned in June 1985, the studies in the D-tect project investigated the effects of vitamin D on health outcomes in individuals, who during gestation were exposed or unexposed to extra vitamin D from fortified margarine. This paper reviews and narratively summarizes the analytic approaches alongside the results of the societal fortification experiment studies from the D-tect project and addresses the challenges in designing societal experiment studies and evaluating their results. The latter are discussed as lessons learned that may be useful for designers of similar studies, expected to be extensively utilized while researching the health consequences of the COVID-19 pandemic by comparing individuals born before and after the epidemic. In the D-tect project, 16 articles based on the societal fortification experiment were published analyzing 10 different outcomes and using different statistical approaches. Lessons learned included the detail of the analysis of the historical information on the exposure, availability and validity of the outcome data, variety of analytical approaches, and specifics concerning vitamin D effect evaluation, such as consideration of the influence of sunshine or season. In conclusion, the D-tect project clearly demonstrated the cost-effectiveness and research potential of natural- or societal-experiment-based studies.

Predictive Role of Population Density and Use of Public Transport for Major Outcomes of SARS-CoV-2 Infection in the Italian Population: An Ecological Study.

BACKGROUND: This study aimed at assessing how population density (PD), aging index (AI), use of public transport (URPT), and PM10 concentration (PI) modulated the trajectory of the main COVID-19 pandemic outcomes in Italy, also in the recrudescence phase of the epidemic. STUDY DESIGN: Ecological study. METHODS: For each region, we recovered data about cases, deaths, and case fatality rate (CFR) recorded since both the beginning of the epidemic and September 1, 2020. Data about total hospitalizations were included as well. RESULTS: PD correlated with, and was the best predictor of, total and partial cases, total and partial deaths, and total hospitalizations. Moreover, URPT correlated with, and was the best predictor of, total CFR. Besides, PI correlated significantly with total and partial cases, total and partial deaths, and total hospitalizations. CONCLUSION: PD explains COVID-19 morbidity, mortality, and severity while URPT is the best predictor of disease lethality. These findings should be interpreted with caution due to the ecological fallacy.

The association between opioids, environmental, demographic, and socioeconomic indicators and COVID-19 mortality rates in the United States: an ecological study at the county level.

BACKGROUND: The spread of the COVID-19 pandemic throughout the world presents an unprecedented challenge to public health inequities. People who use opioids may be a vulnerable group disproportionately impacted by the current pandemic, however, the limited prior research in this area makes it unclear whether COVID-19 and opioid use outcomes may be related, and whether other environmental and socioeconomic factors might play a role in explaining COVID-19 mortality. The objective of this study is to evaluate the association between opioid-related mortality and COVID-19 mortality across U.S. counties. METHODS: Data from 3142 counties across the U.S. were used to model the cumulative count of deaths due to COVID-19 up to June 2, 2020. A multivariable negative-binomial regression model was employed to evaluate the adjusted COVID-19 mortality rate ratios (aMRR). RESULTS: After controlling for covariates, counties with higher rates of opioid-related mortality per 100,000 persons were found to be significantly associated with higher rates of COVID-19 mortality (aMRR: 1.0134; 95% CI [1.0054, 1.0214]; P = 0.001). Counties with higher average daily Particulate Matter (PM2.5) exposure also saw significantly higher rates of COVID-19 mortality. Analyses revealed rural counties, counties with higher percentages of non-Hispanic whites, and counties with increased average maximum temperatures are significantly associated with lower mortality rates from COVID-19. CONCLUSIONS: This study indicates need for public health efforts in hard hit COVID-19 regions to also focus prevention efforts on overdose risk among people who use opioids. Future studies using individual-level data are needed to allow for detailed inferences.

Predictors of Covid-19 case fatality rate: An ecological study.

BACKGROUND: The outbreak of novel coronavirus (Covid-19) has a significant burden on global health and could be associated with significant mortality. Limited information exists about determinants of its fatality worldwide. Thus, this ecological study examined the association of various predictors with Covid-19 fatality. METHODS: International data bases of Covid-19 statistics and health metrics available primarily at WHO were reviewed to collect information for 113 countries. The dependent variable was Covid-19 case fatality rate. Independent variables were demographic, social, clinical, economic, heath care and child health factors. RESULTS: Case fatality rate of Covid-19 varies across countries with an average of 4.2 ± 3.8%, and about half of countries had fatality rate >3.2% (median). Significant relationships were observed between Covid-19 fatality rate and socio-economic, clinical, and health variables at the unadjusted regression analysis. At the multivariate adjusted model, percentage of population with age>60 years was positively associated with Covid-19 fatality (B = 0.032, p = 0.005), while Polio-3 immunization at 1-year old was inversely related (B = -0.057, p = 0.017). CONCLUSIONS: This ecological investigation highlights the higher risk of death among elderly with Covid-19 pandemic and suggests that Polio-3 immunization coverage among 1-year-olds may be associated with better survival. Future research is warranted to validate these findings.

Airports, highways and COVID-19: An analysis of spatial dynamics in Brazil.

INTRODUCTION: The high transmissibility and infectivity of the new coronavirus, the high proportion of asymptomatic transmitters and the rapid and continuous spatial displacement of people, by the different mechanisms of locomotion, are elements that can contribute to the dissemination of COVID-19. This study aims to describe the geographical dispersion of COVID-19 in the state of Bahia and the importance of major airports and highways in the dynamics of disease transmission. METHODS: This is an ecological study involving all cases of COVID-19 registered in the state of Bahia between March 6, date of the first registered case and May 16, 2020. After collection, an exploratory spatial analysis was performed, considering the cases accumulated on the last day of each epidemiological week. RESULTS: The first cases of COVID-19 were concentrated in areas served by three important airport complexes in the state, located in Salvador, Ilhéus and Porto Seguro. From week 16-20, there was a more intense expansion of COVID-19 to the interior of the state. A global spatial autocorrelation was observed (I Moran 0.2323; p = 0.01), with the influence of distance: positive correlation at distances less than 205.8 km (I Moran 0.040; p = 0.01) and greater than 800 km (I Moran 0.080; p = 0.01). CONCLUSIONS: Based on the spatial dispersion pattern of COVID-19 in the state of Bahia, airports and highways that cross the state were responsible for the interiorization of the disease.

Socioeconomic, demographic and healthcare determinants of the COVID-19 pandemic: an ecological study of Spain.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has posed a major challenge to health, economic and political systems around the world. Understanding the socioeconomic, demographic and health determinants affecting the pandemic is of interest to stakeholders. The purpose of this ecological study is to analyse the effect of the different socioeconomic, demographic and healthcare determinants on the mortality rate and estimated cumulative incidence of COVID-19 first wave in the Spanish regions. METHODS: From the available data of the 17 Spanish regions (Autonomous Communities), we have carried out an ecological study through multivariate linear regression using ordinary least squares. To do this, we conducted an analysis using two distinct dependent variables: the logarithm of mortality rate per 1,000,000 inhabitants and the estimated cumulative incidence. The study has 12 explanatory variables. RESULTS: After applying the backward stepwise multivariate analysis, we obtained a model with nine significant variables at different levels for mortality rate and a model with seven significant variables for estimated cumulative incidence. Among them, six variables are statistically significant and of the same sign in both models: "Nursing homes beds", "Proportion of care homes over 100 beds", "Log GDP per capita", "Aeroplane passengers", "Proportion of urban people", and the dummy variable "Island region". CONCLUSIONS: The different socioeconomic, demographic and healthcare determinants of each region have a significant effect on the mortality rate and estimated cumulative incidence of COVID-19 in territories where the measures initially adopted to control the pandemic have been identical.

Global epidemiology and socio-economic development correlates of the reproductive ratio of COVID-19.

BACKGROUND: The most commonly cited argument for imposing or lifting various restrictions in the context of the coronavirus disease 2019 (COVID-19) pandemic is an assumed impact on the reproductive ratio of the pathogen. It has furthermore been suggested that less-developed countries are particularly affected by this pandemic. Empirical evidence for this is lacking. METHODS: Based on a dataset covering 170 countries, patterns of empirical 7-d reproductive ratios during the first months of the COVID-19 pandemic were analysed. Time trends and associations with socio-economic development indicators, such as gross domestic product per capita, physicians per population, extreme poverty prevalence and maternal mortality ratio, were analysed in mixed linear regression models using log-transformed reproductive ratios as the dependent variable. RESULTS: Reproductive ratios during the early phase of a pandemic exhibited high fluctuations and overall strong declines. Stable estimates were observed only several weeks into the pandemic, with a median reproductive ratio of 0.96 (interquartile range 0.72-1.34) 6 weeks into the analysis period. Unfavourable socio-economic indicators showed consistent associations with higher reproductive ratios, which were elevated by a factor of 1.29 (95% confidence interval 1.15 to 1.46), for example, in the countries in the highest compared with the lowest tertile of extreme poverty prevalence. CONCLUSIONS: The COVID-19 pandemic has allowed for the first time description of the global patterns of reproductive ratios of a novel pathogen during pandemic spread. The present study reports the first quantitative empirical evidence that COVID-19 net transmissibility remains less controlled in socio-economically disadvantaged countries, even months into the pandemic. This needs to be addressed by the global scientific community as well as international politics.