COVID-19 Deaths Research Articles

Estimated number of COVID-19 deaths averted by vaccination in Belgium

Abstract Background Vaccination campaigns have been rolled out globally to limit the impact of COVID-19 on severe health outcomes, including mortality. We aimed to estimate the number of averted deaths by COVID-19 vaccination in the Belgian population aged ≥65 years, between January 2021 and January 2023. Methods Nationwide data on COVID-19 infections, vaccinations and all-cause mortality were individually linked. We estimated Vaccine Effectiveness against COVID-19 mortality (VE) in persons having received a vaccine dose in the last 6 months using a Cox proportional hazards model adjusted for age, sex, time since vaccination, previous infection, comorbidities, province and income. COVID-19 death was defined as a death within 1-7 weeks after a positive SARS-CoV-2 laboratory-test. Based on obtained VE estimates, vaccine coverage and national COVID-19 mortality data, we estimated the number of averted deaths (expected deaths without vaccinating minus the reported deaths). Results By January 31st 2023, 11,033 COVID-19 deaths have been reported in Belgium. The average vaccine coverage was 48% during alpha, 85% during delta and 63% during omicron dominance. VE was estimated at 0-59 days after vaccination, for 65-79 year and ≥80 year-olds respectively, at 65% (58%-60%) and 35% (28%-41%) during Alpha, at 84% (82%-87%) and 79% (77%-81%) during Delta and at 83% (80%-85%) and 71% (68%-73%) during Omicron dominance. We estimated 10,042 deaths averted (range: 8,917-11,188) among the Belgian population aged ≥65 years, representing a 48% reduction (range 45%-50%) in the expected deaths. Out of 10,042 averted deaths, the majority was averted during Delta (47%; 4,670) or Omicron dominance (43%; 4,366), compared to during Alpha dominance (10%; 1,006). Conclusions Vaccinating against COVID-19 led to an important reduction in COVID-19-related mortality among the Belgian population ≥65 years, in particular during Delta and Omicron dominance, underscoring the effectiveness of vaccines against mortality. Key messages • Vaccinating against COVID-19 led to an important reduction of 48% in COVID-19-related mortality among the Belgian population ≥65 years, in particular during Delta and Omicron dominance. • Vaccine effectiveness against COVID-19 mortality was estimated as high in the Belgian population ≥65 years (range: 71-84%) during Delta and Omicron dominance, also among elderly over 80 years.

The effect of Covid deaths on premature mortality trends in Northern Dimension partnership countries

Abstract Background Potential Years Life Lost (PYLL) is an established method to measure, follow trends and compare disease burden within and between countries. Northern Dimension Partnership in Health and Social wellbeing (NDPHS) network was established in 2003 and includes the following countries: Estonia, Finland, Germany, Iceland, Latvia, Lithuania, Norway, Poland, Russia, and Sweden. Due to the Russian invasion to Ukraine, Russia is now excluded from the collaboration. Methods Premature mortality is defined as a death before the age of 70 years. PYLL-rates per 100,000 population are presented in six cause of deaths categories: total mortality, external causes, vascular diseases, cancers, alcohol-related deaths and suicides. Furthermore, 2021 data included deaths due to the Covid infection. Data were obtained from Eurostat and analyses are standardized to EU standard population. Results PYLL-rates declined from 2003 to 2017 in all countries and in most causes of death sub-groups. The total (all causes, all countries) PYLL-rate declined between 2003 and 2017 from 7072 to 5154 in men and from 3263 to 2532 in women. However, from 2017 to 2021 the total PYLL-rate increased to 5469 in men and 2623 in women. The increase was explained by Covid mortality. When Covid deaths were excluded, a minor decrease was observed also between 2017 and 2021. In 2021, total PYLL-rates vary largely between countries: from 2804 to 12,393 in men and from 1781 to 4460 in women. Differences between countries in Covid-related and other cause-specific PYLL-rates were also large. In all countries and causes of death sub-groups PYLL-rates were markedly higher in men compared to women. Conclusions The number of years lost due to premature preventable mortality have declined markedly in all NDPHS countries in the last two decades. Between 2017 and 2021, some increase was observed due to the Covid-related deaths. Differences between countries in premature mortality are still large. Key messages • The number of years lost due to premature preventable mortality have declined markedly in all NDPHS countries since 2003 but still, in 2021, differences between countries were large. • Covid-related deaths caused an increase in premature mortality between 2017 and 2021.

Unravelling COVID-19 social mortality patterns using conditional inference tree algorithm

Abstract Background The COVID-19 pandemic led to significant excess mortality in 2020 in Belgium. By using microlevel cause-specific mortality data for the total Belgian adult population in 2020, three outcomes were considered in this study aiming at predicting sociodemographic (SD) and socioeconomic (SE) patterns of 1) COVID-19 specific death compared to survival; 2) all other causes of death (OCOD) compared to survival; 3) COVID-19 specific deaths compared to all OCOD. Methods Multivariable logistic regression models were fitted for the three outcomes. In addition, we computed conditional inference tree (CIT) algorithms, complementing regression models, to identify and rank the strongest SD and SE predictors of the three outcomes. Results Older people, males, people living in collectivities, first-generation migrants, and deprived SE groups experienced higher odds of dying from COVID-19 compared to survival; living in collectivities was identified by the CIT as the strongest predictor followed by age and sex. Education emerged as one of the strongest predictors for people not living in collectivities. Overall, similar patterns were observed for all OCOD except for first- and second-generation migrants having lower odds of all OCOD compared to survival; age group was identified by the CIT as the strongest predictor. Older people, males, people living in collectivities, first- and second-generation migrants, and people with lower levels of education had higher odds of COVID-19 death compared to all OCOD; living in collectivities was identified by the CIT as the strongest predictor followed by age, sex, and migration status. Education and income emerged as the strongest predictors among people not living in collectivities. Conclusions This study identified important SD and SE disparities in COVID-19 mortality underlying the importance of implementing preventive measures, particularly within the most vulnerable populations, in infectious disease pandemic preparedness. Key messages • Living in collectivities appeared to be the strongest predictor of COVID-19 death across all age groups, highlighting the importance of preventive measures in reducing the transmission of the virus. • Poor education plays a crucial role in predicting COVID-19 death among people not living in collectivities, highlighting the importance of targeting preventive measures towards low educated groups.

COVID-19 premature mortality in Serbia: Does the place of death matter?

Abstract Background The COVID-19 pandemic has significantly impacted healthcare services provision in Serbia and globally. Many people did not seek or reach healthcare due to various reasons, and a significant number of COVID-19 deaths were not confirmed by laboratory testing. Within the project of the Laboratory for Strengthening Capacity and Performance of Health System and Workforce for Health Equity, we assessed the differences in years of life lost (YLL) of COVID-19 death cases according to the place of death. Methods The Statistical Office of the Republic of Serbia provided average life expectancy and anonymous individual mortality data of the Serbian population in 2020, 2021, and 2022, where COVID-19 was the underlying cause of death (ICD-X codes: laboratory confirmed - U07.1 and clinically diagnosed - U07.2), also disaggregated by the place of death (at home or in a hospital). Analytical statistics and nonparametric tests were used to assess the differences in premature mortality by place of death with a significance level set at p < 0.05. Results In all observed years, a total of 45,632 death cases due to COVID-19 occurred (94.3% in hospital and 5.7% at home). Most COVID-19 deaths were coded as U07.1 (93.8% in hospital, 91.3% at home). An average of 12.12±7.50 YLLs was estimated per death, with a median of 11.50. There was a significant difference (p < 0.001) in the median number of YLLs between those who died in the hospital (11.50) and those who died at home (6.78). Furthermore, deaths occurring at home had fewer YLLs but were more frequently coded as U07.2 (p < 0.001). Conclusions The place of death is relevant when assessing the impact of COVID-19 on premature mortality in Serbia. On average, persons who died at home due to COVID-19 had a lower number of YLLs compared to those who died in a hospital. More research is necessary on the other factors contributing to premature mortality and inequalities in the COVID-19 burden in Serbia. Key messages • During the first three years of the COVID-19 pandemic in Serbia, 5.7% of COVID-19 deaths occurred at home, resulting in an average of 9.89 years of life lost. • The COVID-19 pandemic highlights the need to investigate deaths that occur at home and improve pandemic preparedness.

Risk of long COVID in migrants and the contribution of vaccinations, disease severity, social inequalities and preexisting health: A nationwide register study in Sweden

Abstract Background and aim A number of studies have found higher COVID-19 infection rates, hospitalizations and deaths in migrants and ethnic minorities throughout the Corona Pandemic. Some recent evidence also suggests higher risk of long COVID in migrants although less is known about the risk factors for long COVID in this population. The objective of our study is to examine the risk of long COVID in migrants and to examine whether preexisting health conditions, disease severity, social inequalities and vaccinations contribute to the association. Methods We used linked Swedish administrative registers to estimate the risk of a long COVID diagnosis in the population that had a confirmed COVID-19 infection. Poisson regressions were used to calculate incidence rate ratios between the Swedish born and migrant groups. Adjustments for preexisting health conditions, disease severity, vaccinations and social inequalities were separately introduced. Results Higher risks of long COVID were found among migrants from Africa, Asia, Eastern Europe, Finland, Middle-East and South America. While the contribution of vaccinations and social inequalities were modest, we found that disease severity (i.e. whether the person was hospitalized or treated in an intensive care unit) primarily contributed to the higher risk of long COVID found in migrants. Conclusions The greater exposure and impact of the COVID-19 virus among migrants during the pandemic also affected the longer-term consequences of infection in this at-risk population.

SARS-CoV-2 Infection And COVID-19 Outcomes Among Mental Disorders: A Register-based Study in Catalonia

Abstract This study aimed to study the risk of SARS-CoV-2 infection and severe COVID-19 outcomes across different mental diagnoses and to assess the role of sex in these associations. We used electronic health records from Catalonia to identify adults receiving inpatient/outpatient mental health care between 2017-2019 with diagnosis of non-affective psychosis (NAP), bipolar disorder (BD), depressive disorder (DEP), stress-related disorders, neurotic/somatoform disorders (NSD), and substance misuse (SUB) (exposed). Outcomes included SARS-CoV-2 infection, COVID-19 hospitalization, and COVID-19-related death. Adjusted logistic regression analyses were conducted. 785,378 adults were included (70.3% < 65 years old; 57.1% women). Compared to unexposed, those with NAP [OR (95%CI): 0.84 (0.80-0.88)], BD [0.80 (0.75-0.86)], DEP [0.97 (0.94-1.00)] and SUB [0.81 (0.78-0.84)] had a lower risk of SARS-CoV-2 infection, while people with NSD presented an increased risk [1.03 (1.01-1.06)]. Among those infected, people with DEP, NSD, and SUB had a lower risk of COVID-19 hospitalization, but higher risk of COVID-19-related death [1.23 (1.07-1.41); 1.26 (1.07-1.48); 1.48 (1.24-1.71), respectively]. A higher COVID-19-related death was also found in people with NAP and BD [1.68 (1.34-2.12); 2.02 (1.50-2.73)]. Sex-stratified analysis showed that women with NSD were especially vulnerable to infection [1.07 (1.03-1.11)], and women with DEP and NSD to COVID-19-related death [1.24 (1.05-1.47); 1.26 (1.02-1.54)]. These results suggest different vulnerabilities to infection and COVID-19 hospitalization and death across mental disorders. These findings have implications for pandemic preparedness, highlighting the need for specific public health strategies to mitigate the excess of mortality of people with certain mental disorders.

Excess all-cause mortality in 21 countries during 2022: COVID-19 impact by C-MOR project

Abstract National published COVID-19 mortality estimates do not fully encompass the extent of the pandemic’s impact on mortality. To address this challenge, calculating excess all-cause mortality at the national level is important. Our focus was on understanding total weekly excess mortality for 2022, by analysing mortality data across 2020-2022, from 21 countries participating in the international consortium (C-MOR), which provided data for examination. Excess mortality was calculated by comparing the weekly 2022 age-standardized mortality rates per 100,000 population against a baseline mortality, estimated using historical data from 2015-2019. Excess cumulative mortality for 2022 was found in all 21 countries. The excess mortality for the total population varied between 8.6 and 116.2, with the minimum excess belonging to Peru and the maximum to Georgia. Australia, Austria, Cyprus, Denmark, Estonia, Georgia, Greece, Israel, and Norway showed a higher excess in 2022 than in 2020, while Australia, Austria, Cyprus, Denmark, Israel, Italy, Norway, Spain, and Sweden also showed a higher excess in 2022 than in 2021. Mauritius showed a significant excess mortality for the first time in 2022. For all countries, but Australia, the % of COVID-19 deaths out of all deaths decreased in 2022 compared to 2021. Contrary to the ‘harvesting effect’, which would expect a decline in mortality rates post-pandemic, our results underscore a sustained excess mortality throughout 2022. The 2022 excess deaths are mainly non-COVID-related, stemming from broader pandemic impacts on healthcare systems and other factors. Conversely, in Australia, international boarders reopened in 2022, resulting in the first community-wide transmission and a substantial rise in excess deaths. Our study reveals nuanced excess mortality dynamics post-vaccination, providing crucial insights for policymakers and stressing the necessity of continued vigilance and adaptive strategies against COVID-19’s diverse impacts. Key messages • All countries investigated experienced continued all-cause excess mortality during 2022, compared to pre-pandemic years. For most, excess mortality in 2022 was higher than in 2021 and 2020. • For all countries, except Australia, the contribution of COVID-19 deaths to the mortality estimates in 2022 is decreased, highlighting the impact of indirect pandemic related effects on mortality.

Rural–Urban Divide of COVID-19 Fatalities in India—Investigating the Role of Lifestyle Disorder Diseases

AbstractUsing data on weekly COVID-19 infections and fatalities at the district level for 19 states and 4 union territories of India, we investigate the determinants of COVID-19 deaths focusing exclusively on the second wave of infections. We include several macroeconomic and structural indicators for districts namely, per capita district domestic product, the degree of urbanization, population density, percentage of aged population, share of agriculture, poverty, among several others. Our findings suggest that fatalities have a clear rural–urban divide. Rural agricultural districts with more poor people have experienced less cases and fatalities. Fatalities are more clustered in prosperous and dense industrial districts. Regions having higher COVID-19 fatalities also have a higher proportion of ageing population with urban life-style disorder related diseases such as obesity, diabetes, and hypertension. Prevalence of respiratory illnesses further aggravates the effects of some of these life-style disorder diseases on COVID-19 fatalities.

Pre-COVID-19 cognitive social capital trajectories and peri-COVID-19 depression in China, 2014–2020: A longitudinal study

BackgroundSocial capital is dynamic; however, little is known about the association of its dynamics with peri-pandemic health. We examined the longitudinal association of pre-COVID-19 cognitive social capital trajectories with peri-COVID-19 depressive symptoms and the moderating effect of province-level COVID-19 severity on the association in China. MethodsWe employed four-wave data from China Family Panel Studies between 2014 and 2020. Depressive symptoms in 2020 were measured by the 8-item Center for Epidemiological Studies-Depression Scale. Pre-COVID-19 cognitive social capital from 2014 to 2018 included dichotomized (high/low) generalized trust, trust in neighbors, trust in local government officials, and reciprocity, each of which included five trajectories: persistently low, decreased, fluctuated, increased, and persistently high. Province-level COVID-19 severity in 2020 was a factor score constructed by the number of provincial COVID-19 cases and deaths. We conducted mixed-effects linear regression to answer our research question. ResultsPersistently low generalized trust (β: 0.46; 95 % CI: 0.15,0.78), persistently low (β: 0.57; 95 % CI: 0.22, 0.92), decreased (β: 0.36; 95 % CI: 0.07, 0.65) and increased (β: 0.40; 95 % CI: 0.12, 0.68) trust in neighbors, and persistently low (β: 0.39; 95 % CI: 0.02, 0.77) and decreased (β: 0.68; 95 % CI: 0.38, 0.97) reciprocity, compared with their persistently high trajectories, were associated with a higher level of peri-COVID-19 depressive symptoms. We did not find robust evidence to support the moderating effect of province-level COVID-19 severity. ConclusionsLong-term strategies to increase cognitive social capital and prevent cognitive social capital decline are needed to protect mental health against a pandemic.

Indirect and direct effects of nighttime light on COVID-19 mortality using satellite image mapping approach

The COVID-19 pandemic has highlighted the importance of understanding environmental factors in disease transmission. This study aims to explore the spatial association between nighttime light (NTL) from satellite imagery and COVID-19 mortality. It particularly examines how NTL serves as a pragmatic proxy to estimate human interaction in illuminated nocturnal area, thereby impacting viral transmission dynamics to neighboring areas, which is defined as spillover effect. Analyzing 43,199 COVID-19 deaths from national mortality data during January 2020 and October 2022, satellite-derived NTL data, and various environmental and socio-demographic covariates, we employed the Spatial Durbin Error Model to estimate the direct and indirect effect of NTL on COVID-19 mortality. Higher NTL was initially directly linked to increased COVID-19 mortality but this association diminished over time. The spillover effect also changed: during the early 3rd wave (December 2020 – February 2021), a unit (nanoWatts/sr/cm2) increase in NTL led to a 7.9% increase in neighboring area mortality (p = 0.013). In contrast, in the later 7th wave (July – September 2022), dominated by Omicron, a unit increase in NTL resulted in an 8.9% decrease in mortality in neighboring areas (p = 0.029). The shift from a positive to a negative spillover effect indicates a change in infection dynamics during the pandemic. The study provided a novel approach to assess nighttime human activity and its influence on disease transmission, offering insights for public health strategies utilizing satellite imagery, particularly when direct data collection is impractical while the collection from space is readily available.

Water Security in the Context of the Piracicaba River Sub-Basin During the COVID-19 Pandemic

Objective: To analyze the challenges for water security in municipalities belonging to the Piracicaba River (SP) sub-basin, during the COVID-19 pandemic. Method: This is an exploratory and bibliographical research with a qualitative approach and case study and with a technical documentary procedure. The data sources were: Water Resources Situation Report; number of COVID-19 cases and deaths obtained from the Brazilian Ministry of Health website. In addition, a questionnaire on aspects related to water was administered to experts from the Technical Chamber for Conservation and Protection of Natural Resources of the Piracicaba, Capivari and Jundiaí River Basin Committees. Results and conclusions: The number of cases and deaths from the COVID-19 pandemic increased significantly in the 1st half of 2021 compared to the same period in 2020. The experts interviewed attributed high importance to prevention measures, the trend of decreasing water availability and the reduction of losses from water distribution systems. Research implications: The research presented theoretical reflections on the COVID-19 pandemic and water security. Water is an extremely important resource, especially in times of epidemics, as occurred with COVID-19. Water security affects the availability of water both to meet the needs of the population and to maintain ecosystems. Originality/value: The research carried out highlights the need for public policies regarding water and sanitation in order to achieve the protection of the population's health and sustainable development.

A Space Distributed Model and Its Application for Modeling the COVID-19 Pandemic in Ukraine

A space distributed model based on reaction–diffusion equations, which was previously developed, is generalized and applied to COVID-19 pandemic modeling in Ukraine. Theoretical analysis and a wide range of numerical simulations demonstrate that the model adequately describes the second wave of the COVID-19 pandemic in Ukraine. In particular, comparison of the numerical results obtained with the official data shows that the model produces very plausible total numbers of the COVID-19 cases and deaths. An extensive analysis of the impact of the parameters arising from the model is presented as well. It is shown that a well-founded choice of parameters plays a crucial role in the applicability of the model.

Spatial and Ethno-national Health Inequalities: Health and Mortality Gaps between Palestinians and Jews in Israel.

This research adopts an analytical spatial perspective to explain ethno-national health inequality between Palestinians and Jews in Israel. The work identifies the forces that instigated and maintained the spatial segregation of Palestinians and elaborates the role of segregation in generating health gaps between Palestinians and Jews. The analysis suggests a novel conceptualization of two types of segregation: (a) exclusion from the center and confinement to the periphery and (b) segregation within the geographic periphery. Using administrative data on COVID-19 incidence, hospitalization, and death and various health indicators for localities, I devise a decomposition method that evaluates the relative contribution of each type of segregation to the total health gap. The findings indicate that the segregation of Palestinians from the center and their confinement to peripheral regions are crucial determinants of their poor health outcomes and that the segregation of the Palestinian community within the geographic periphery also contributes to poorer health.

Health expenditure and fiscal marksmanship before and during the coronavirus pandemic across the federal states of India

This study examined state-level health expenditure, fiscal marksmanship, and COVID-19 deaths among selected states in India. It (1) compared health expenditure between the pre-COVID-19 and the COVID-19 period in India and selected states; (2) investigated the fiscal marksmanship in the context of health expenditure at the national and state level; and (3) assessed the relationship between COVID-19 deaths, population density, health expenditure, and fiscal marksmanship. The study period from 2017 to 2021 was divided into pre-COVID-19 (2017-late – 2019) and COVID-19 (late-2019 – 2021). This study focused on India and selected Indian states, using data from state budget documents, Census 2011 for population density, and COVID-19 data from the government website. Descriptive statistics, percentages, ratios, graphs, and tools such as Theil’s U-Statistic and Pearson’s correlation were employed for analysis. Simple linear regression was used to analyze the impact of fiscal marksmanship and other variables on the case fatality ratio. This study revealed challenges in maintaining fiscal discipline during COVID-19, with disparities in capital expenditure among states. The results emphasized the need for increased health spending and structural changes to enhance resilience to future health crises, advocating for investments in infrastructure and services to improve preparedness.

Multimorbidity raises the odds of decease in COVID-19 patients: An Iranian prospective study

Introduction: The prevalence of noncommunicable diseases is high in Iran. We postulated that multimorbidity may affect the rate of mortality from COVID-19. So, we investigated the relationship between multimorbidity and COVID-19 mortality. Methods: We used medical reports for collecting clinical laboratory data of patients with COVID-19 in this prospective investigation. Moreover, we documented whether the patient had a known diagnosis of different comorbidities. The patients with more than one comorbidity were considered multimorbidity. The length of follow-up was till participants were discharged from the hospital or deceased. The main outcome was to evaluate the relationship between multimorbidity and death in COVID-19 hospitalized patients. Results: The present prospective study included 1842 patients with COVID-19 with a multimorbidity rate of 37.40%. About 24.6% of participants with more than four comorbidities died. However, this value was about 17% in participants with less than four comorbidities. The odds of mortality from COVID-19 were 53% greater in patients with diabetes. Also, the odds of death were 2.05 (1.21, 3.45) times greater in patients with comorbidities≥4. Conclusion: The results indicated a high rate of multimorbidity in patients with COVID-19 which is related to a higher death rate. So, in countries with higher multimorbidity rates such as Iran, it is necessary to design efficient approaches to alleviate the spread of COVID-19.

Impact of pharmaceutical and non-pharmaceutical interventions on COVID-19 in Tunisia

BackgroundIn COVID-19 management, a variety of pharmaceutical interventions (PI) and non- pharmaceutical interventions (NPI) were adopted to limit the spread of the disease and its associated deaths. We aimed to evaluate the impact of PI and NPI on risks of COVID-19 transmission and deaths.MethodWe collected aggregate data from March 2nd, 2020, to December 1, 2022 from the Tunisian Ministry of Health's website and OurWorldInData.org site. NPI Periods (NPIP: March 2020 to March 2021) and PI Periods (PIP) were distributed to NPIP1, 2, 3 and 4 and to PIP1, 2, 3 and 4, respectively. We calculated the Relative Risks (RR) and 95% Confidence Intervals (CI) by comparing the subsequent period with previous one.ResultsThe risk of SARS-CoV-2 transmission increased progressively from the zero cases period (NPIP2) to the mitigate strategy period (NPIP3) (RR = 14.0; 95% CI: 12.4–15.8) and to the stop-and-go epidemic control period (NPIP4) (RR = 23.1 (95% CI: 22.4–23.9). It was stabilized in the targeted vaccination period (PIP1) (RR = 1.08, 95% CI: 1.07–1.08) and reduced during the mass vaccination period (PIP2) (RR: 0.50, 95% CI: 0.50–0.51). SARS-CoV-2 transmission, increased during PIP3 concomitant with the Omicron wave (RR = 2.65, 95% CI: 2.64–2.67). It remained at a low level in PIP4 (RR = 0.18; 95% CI: 0.18–0.18).Compared to NPIP2, NPIP3 and NPIP4 were associated with a higher risk of COVID-19 mortality (RR = 3.337; 95% CI: 1.797–6.195) and (RR = 72.63 (95% CI: 54.01–97.68), respectively. Since the start of the immunization program, the risk of COVID-19 death has consistently decreased. In comparison to each previous period, the risk transitioned in PIP1 to RR = 0.91; 95% CI: 0.88–0.93, then to RR = 0.85; 95% CI: 0.83–0.88 in PIP2, to RR = 0.47; 95% CI: 0.45–0.50 in PIP3, and to RR = 0.19; 95% CI: 0.18–0.24 during PIP4.ConclusionIn terms of lowering the risk of transmission and mortality, the NP strategy at the beginning of the epidemic outperformed the IP strategy during the outbreak.

Socio-Economic Factors and Their Influence on Covid-19 Deaths in Latin America: Role of Knowledge and Its Economic Implications

Socio-Economic Factors and Their Influence on Covid-19 Deaths in Latin America: Role of Knowledge and Its Economic Implications

COVID-19 Deaths and Minority Health Social Vulnerability, in the U.S., January 1, 2020 through June 24, 2023.

Health disparities, leading to worse health outcomes such as elevated COVID-19 mortality rates, are rooted in social and structural factors. These disparities notably impact individuals from lower socioeconomic backgrounds and more socially vulnerable areas. We analyzed the relationship between COVID-19 deaths and social vulnerability using the Minority Health Social Vulnerability Index (MHSVI). COVID-19 death data in the U.S. was obtained from the Centers for Disease Control and Prevention (CDC) National Center for Health Statistics, where COVID-19 deaths were defined using the ICD-10 code U07.1. MHSVI composite scores were calculated for 3089 U.S. counties and categorized into social vulnerability quartiles, where values ranged from 0 (lowest vulnerability) to 1 (highest vulnerability). Negative binomial regression was employed to determine death rate ratios for each quartile within each theme. Finally, a multivariate negative binomial regression including all MHSVI sub-themes, excluding the overall index ranking, was used to assess the association between each theme and COVID-19 death rates independently. There were 1,134,272 COVID-19 deaths from January 1, 2020 through June 24, 2023. Adjusted rate ratios for COVID-19 deaths in the overall index ranking were 1.06 (95% CI 0.99-1.13), 1.14 (95% CI 1.06-1.22), and 1.41 (95% CI 1.31-1.52) for the second, third and fourth quartiles, respectively. Sub-themes of socioeconomic status (SES), household characteristics (HC), racial and ethnic minority status (REMS), housing type and transportation (HTT), and medical vulnerability (MV) revealed increasing death rates in higher vulnerability quartiles. The healthcare infrastructure and access (HIA) theme had decreasing death rate ratios of 0.74 (95% CI 0.71-0.78), 0.59 (95% CI 0.56-0.62), and 0.42 (95% CI 0.39-0.44) for the second, third, and fourth quartiles, respectively. Finally, the multivariate analysis showed that the HC, HTT, HIA, and MV themes were associated with COVID-19 deaths (P < 0.05). Counties that were identified as more socially vulnerable experienced higher death rates from COVID-19. These areas may need additional public health and social support during future pandemics.

Cross-Country Assessment of Socio-Ecological Drivers of COVID-19 Dynamics in Africa: A Spatial Modelling Approach

Understanding how countries’ socio-economic, environmental, health status, and climate factors have influenced the dynamics of COVID-19 is essential for public health, particularly in Africa. This study explored the relationships between African countries’ COVID-19 cases and deaths and their socio-economic, environmental, health, clinical, and climate variables. It compared the performance of Ordinary Least Square (OLS) regression, the spatial lag model (SLM), the spatial error model (SEM), and the conditional autoregressive model (CAR) using statistics such as the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Root Mean Square Error (RMSE), and coefficient of determination (R2). Results showed that the SEM with the 10-nearest neighbours matrix weights performed better for the number of cases, while the SEM with the maximum distance matrix weights performed better for the number of deaths. For the cases, the number of tests followed by the adjusted savings, Gross Domestic Product (GDP) per capita, dependence ratio, and annual temperature were the strongest covariates. For deaths, the number of tests followed by malaria prevalence, prevalence of communicable diseases, adjusted savings, GDP, dependence ratio, Human Immunodeficiency Virus (HIV) prevalence, and moisture index of the moistest quarter play a critical role in explaining disparities across countries. This study illustrates the importance of accounting for spatial autocorrelation in modelling the dynamics of the disease while highlighting the role of countries’ specific factors in driving its dynamics.

COVID-19 Deaths in Transnational Settings: Disrupted Bereavement and Pandemic-Related Prolonged Grief Disorder in the Latinx Immigrant Population.

The Latinx immigrant population experienced one of the highest COVID-19 death rates. Those left behind have exhibited rising rates of mental illness, particularly, pandemic-related prolonged grief disorder. The Latinx immigrant population is uniquely vulnerable to this disorder as a result of disrupted culturally appropriate bereavement practices, constrained social support, and concurrent COVID-19 stressors and immigration-related trauma. Despite a rising call for research on pandemic-related prolonged grief disorder, little is known about the true prevalence, cause, and appropriate treatment protocol behind this disorder in the Latinx immigrant population. Four areas of research critical to the identification and understanding of pandemic-related prolonged grief disorder in this population are recommended: 1) death and bereavement in transnational settings, 2) immigrant social networks and disrupted bereavement, 3) COVID-19 stressors and grieving, and 4) prolonged grief disorder and mental illness comorbidities. An understanding of these four contributing areas to Latinx immigrants' vulnerability to prolonged grief disorder is imperative to providers' development of assessments and treatment protocols needed to identify and treat prolonged grief disorder in this population.