Social deprivation and SARS-CoV-2 testing: a population-based analysis in a highly contrasted southern France region.

Background: Testing was the cornerstone of the COVID-19 epidemic response in most countries until vaccination became available for the general population. Social inequalities generally affect access to healthcare and health behaviors, and COVID-19 was rapidly shown to impact deprived population more drastically. In support of the regional health agency in Provence-Alpes-Côte d'Azur (PACA) in South-Eastern France, we analyzed the relationship between testing rate and socio-demographic characteristics of the population, to identify gaps in testing coverage and improve targeting of response strategies. Methods: We conducted an ecological analysis of SARS-CoV-2/COVID-19 testing rate in the PACA region, based on data aggregated at the finest spatial resolution available in France (IRIS) and by periods defined by public health implemented measures and major epidemiological changes. Using general census data, population density, and specific deprivation indices, we used principal component analysis followed by hierarchical clustering to define profiles describing local socio-demographic characteristics. We analyzed the association between these profiles and testing rates in a generalized additive multilevel model, adjusting for access to healthcare, presence of a retirement home, and the age profile of the population. Results: We identified 6 socio-demographic profiles across the 2,306 analyzed IRIS spatial units: privileged, remote, intermediate, downtown, deprived, and very deprived (ordered by increasing social deprivation index). Profiles also ranged from rural (remote) to high density urban areas (downtown, very deprived). From July 2020 to December 2021, we analyzed SARS-CoV-2/COVID-19 testing rate over 10 periods. Testing rates fluctuated strongly but were highest in privileged and downtown areas, and lowest in very deprived ones. The lowest adjusted testing rate ratios (aTRR) between privileged (reference) and other profiles occurred after implementation of a mandatory healthpass for many leisure activities in July 2021. Periods of contextual testing near Christmas displayed the largest aTRR, especially during the last periods of 2021 after the end of free convenience testing for unvaccinated individuals. Conclusion: We characterized in-depth local heterogeneity and temporal trends in testing rates and identified areas and circumstances associated with low testing rates, which the regional health agency targeted specifically for the deployment of health mediation activities.

Inequalities in provision of hip and knee replacement surgery for osteoarthritis by age, sex, and social deprivation in England between 2007-2017: A population-based cohort study of the National Joint Registry.

BACKGROUND: While the United Kingdom National Health Service aimed to reduce social inequalities in the provision of joint replacement, it is unclear whether these gaps have reduced. We describe secular trends in the provision of primary hip and knee replacement surgery between social deprivation groups. METHODS AND FINDINGS: We used the National Joint Registry to identify all hip and knee replacements performed for osteoarthritis from 2007 to 2017 in England. The Index of Multiple Deprivation (IMD) 2015 was used to identify the relative level of deprivation of the patient living area. Multilevel negative binomial regression models were used to model the differences in rates of joint replacement. Choropleth maps of hip and knee replacement provision were produced to identify the geographical variation in provision by Clinical Commissioning Groups (CCGs). A total of 675,342 primary hip and 834,146 primary knee replacements were studied. The mean age was 70 years old (standard deviation: 9) with 60% and 56% of women undergoing hip and knee replacements, respectively. The overall rate of hip replacement increased from 27 to 36 per 10,000 person-years and knee replacement from 33 to 46. Inequalities of provision between the most (reference) and least affluent areas have remained constant for both joints (hip: rate ratio (RR) = 0.58, 95% confidence interval [0.56, 0.60] in 2007, RR = 0.59 [0.58, 0.61] in 2017; knee: RR = 0.82 [0.80, 0.85] in 2007, RR = 0.81 [0.80, 0.83] in 2017). For hip replacement, CCGs with the highest concentration of deprived areas had lower overall provision rates, and CCGs with very few deprived areas had higher provision rates. There was no clear pattern of provision inequalities between CCGs and deprivation concentration for knee replacement. Study limitations include the lack of publicly available information to explore these inequalities beyond age, sex, and geographical area. Information on clinical need for surgery or patient willingness to access care were unavailable. CONCLUSIONS: In this study, we found that there were inequalities, which remained constant over time, especially in the provision of hip replacement, by degree of social deprivation. Providers of healthcare need to take action to reduce this unwarranted variation in provision of surgery.

[Influence of the social deprivation index on outcomes during the COVID-19 pandemic]. / Influencia del índice de privación social en resultados durante la pandemia de COVID-19.

OBJECTIVE: To see the relationship between the population deprivation index and the use of the health services, adverse evolution and mortality during the COVID-19 pandemic. METHOD: Retrospective cohort study of patients with SARS-CoV-2 infection from March 1, 2020 to January 9, 2022. The data collected included sociodemographic data, comorbidities and prescribed baseline treatments, other baseline data and the deprivation index, estimated by census section. Multivariable multilevel logistic regression models were performed for each outcome variable: death, poor outcome (defined as death or intensive care unit), hospital admission, and emergency room visits. RESULTS: The cohort consists of 371,237 people with SARS-CoV-2 infection. In the multivariable models, a higher risk of death or poor evolution or hospital admission or emergency room visit was observed within the quintiles with the greatest deprivation compared to the quintile with the least. For the risk of being hospitalized or going to the emergency room, there were differences between most quintiles. It has also been observed that these differences occurred in the first and third periods of the pandemic for mortality and poor outcome, and in all due for the risk of being admitted or going to the emergency room. CONCLUSIONS: The groups with the highest level of deprivation have had worse outcomes compared to the groups with lower deprivation rates. It is necessary to carry out interventions that minimize these inequalities.

Influence of social deprivation index on in-hospital outcomes of COVID-19.

While it is known that social deprivation index (SDI) plays an important role on risk for acquiring Coronavirus Disease 2019 (COVID-19), the impact of SDI on in-hospital outcomes such as intubation and mortality are less well-characterized. We analyzed electronic health record data of adults hospitalized with confirmed COVID-19 between March 1, 2020 and February 8, 2021 from the INSIGHT Clinical Research Network (CRN). To compute the SDI (exposure variable), we linked clinical data using patient's residential zip-code with social data at zip-code tabulation area. SDI is a composite of seven socioeconomic characteristics determinants at the zip-code level. For this analysis, we categorized SDI into quintiles. The two outcomes of interest were in-hospital intubation and mortality. For each outcome, we examined logistic regression and random forests to determine incremental value of SDI in predicting outcomes. We studied 30,016 included COVID-19 patients. In a logistic regression model for intubation, a model including demographics, comorbidity, and vitals had an Area under the receiver operating characteristic curve (AUROC) = 0.73 (95% CI 0.70-0.75); the addition of SDI did not improve prediction [AUROC = 0.73 (95% CI 0.71-0.75)]. In a logistic regression model for in-hospital mortality, demographics, comorbidity, and vitals had an AUROC = 0.80 (95% CI 0.79-0.82); the addition of SDI in Model 2 did not improve prediction [AUROC = 0.81 (95% CI 0.79-0.82)]. Random forests revealed similar findings. SDI did not provide incremental improvement in predicting in-hospital intubation or mortality. SDI plays an important role on who acquires COVID-19 and its severity; but once hospitalized, SDI appears less important.

Impact of social deprivation on clinical outcomes of adults hospitalised with community-acquired pneumonia in England: a retrospective cohort study.

INTRODUCTION: Socioeconomic deprivation has been associated with an increased incidence of infection and poorer clinical outcomes during influenza pandemics and the COVID-19 pandemic. The aim of this study was to determine the relationship between deprivation and adverse clinical outcomes following hospital admission with community-acquired pneumonia (CAP), specifically 30-day all-cause mortality and non-elective hospital readmission. METHODS: Data from the British Thoracic Society national CAP audit on patients admitted to hospital with CAP in England between 1 December 2018 and 31 January 2019 were linked to patient-level Hospital Episode Statistics data and Index of Multiple Deprivation (IMD) scores. Multivariable logistic regression models were used to examine the association between deprivation and (a) 30-day mortality and (b) 30-day readmission with p values for trend reported. Age was examined as a potential effect modifier on the effect of IMD quintile on mortality and subsequent subanalysis in those <65 and ≥65 years was performed. RESULTS: Of 9165 adults admitted with CAP, 24.7% (n=2263) were in the most deprived quintile. No significant trend between deprivation and mortality was observed (p trend=0.38); however, the association between deprivation and mortality differed by age group. In adults aged<65 years, 30-day mortality was highest in the most deprived and lowest in the least deprived quintiles (4.4% vs 2.5%, aOR 1.83, 95% CI 0.84 to 4.0) with a significant trend across groups (p trend=0.04). Thirty-day readmission was highest in the most deprived quintile (17.1%) with a significant p trend across groups (p trend 0.003). Age-adjusted odds of readmission were highest in the most deprived compared with the least deprived (aOR 1.41, 95% CI 1.16 to 1.73). CONCLUSIONS: In adults aged<65 years hospitalised with CAP in England, mortality varied inversely with indices of social deprivation. There was also a significant association between deprivation and 30-day readmission. Strategies are required to decrease health inequalities in pneumonia mortality and hospital readmissions associated with deprivation.

The effect of social deprivation on the dynamic of SARS-CoV-2 infection in France: a population-based analysis.

BACKGROUND: Data on health inequalities related to the dynamic of SARS-CoV-2 infection in France are scarce. The aim of this study was to analyse the association between an area-based deprivation indicator and SARS-CoV-2 incidence, positivity, and testing rates between May 2020 and April 2021. METHODS: We analysed data reported to the Système d'Information de Dépistage Populationnel surveillance system between May 14, 2020 and April 29, 2021, which records the results of all SARS-CoV-2 tests in France. Residential addresses of tested individuals were geocoded to retrieve the associated aggregated units for the statistical information (IRIS) scale, corresponding to an area comprising 2000 inhabitants relatively homogenous in terms of socioeconomic characteristics. A social deprivation score was assigned to each area using the European Deprivation Index (EDI). We fitted negative binomial generalised additive models to model the age-standardised and sex-standardised ratios for SARS-CoV-2 incidence, positivity rates, and testing rates, and to estimate incidence rate ratios (IRRs) and 95% CIs of their association with EDI quintiles, using the first quintile (least deprived) as the reference category, adjusted for week, population density, and region. FINDINGS: Analyses were based on 70 990 478 SARS-CoV-2 tests, of which 5 000 972 were positive. SARS-CoV-2 incidence was higher in the most deprived areas than the least deprived areas (IRR 1·148 [95% CI 1·138-1·158]) and positivity rates were also higher (IRR 1·283 [1·273-1·294]), whereas testing rates were lower in the most deprived areas than the least deprived areas (IRR 0·905 [0·904-0·907]). SARS-CoV-2 incidence and positivity rates remained higher in the most deprived areas than the least deprived areas during the second and third national lockdowns, and variation in testing rate was observed according to population density. INTERPRETATION: Our results highlight a positive social gradient between deprivation and the risk of testing positive for SARS-CoV-2, with the highest risk among individuals living in the most deprived areas and a negative social gradient for testing rate. These findings might reflect structural barriers to health-care access in France and lower capacity of deprived populations to benefit from protective measures. FUNDING: None.

Risk of SARS-CoV-2 infection in migrants and ethnic minorities compared with the general population in the European WHO region during the first year of the pandemic: a systematic review.

BACKGROUND: Migrants and ethnic minorities have suffered a disproportionate impact of the COVID-19 pandemic compared to the general population from different perspectives. Our aim was to assess specifically their risk of infection in the 53 countries belonging to the World Health Organization European Region, during the first year of the pandemic. METHODS: We conducted a systematic review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PROSPERO CRD42021247326). We searched multiple databases for peer-reviewed literature, published on Medline, Embase, Scisearch, Biosis and Esbiobase in 2020 and preprints from PubMed up to 29/03/2021. We included cross-sectional, case-control, cohort, intervention, case-series, prevalence or ecological studies, reporting the risk of SARS-CoV-2 infection among migrants, refugees, and ethnic minorities. RESULTS: Among the 1905 records screened, 25 met our inclusion criteria and were included in the final analysis. We found that migrants and ethnic minorities during the first wave of the pandemic were at increased exposure and risk of infection and were disproportionately represented among COVID-19 cases. However, the impact of COVID-19 on minorities does not seem homogeneous, since some ethnic groups seem to be more at risk than others. Risk factors include high-risk occupations, overcrowded accommodations, geographic distribution, social deprivation, barriers to access to information concerning preventive measures (due to the language barrier or to their marginality), together with biological and genetic susceptibilities. CONCLUSIONS: Although mixed methods studies will be required to fully understand the complex interplay between the various biological, social, and cultural factors underlying these findings, the impact of structural determinants of health is evident. Our findings corroborate the need to collect migration and ethnicity-disaggregated data and contribute to advocacy for inclusive policies and programmatic actions tailored to reach migrants and ethnic minorities.

Detecting Racial/Ethnic Health Disparities Using Deep Learning From Frontal Chest Radiography.

PURPOSE: The aim of this study was to assess racial/ethnic and socioeconomic disparities in the difference between atherosclerotic vascular disease prevalence measured by a multitask convolutional neural network (CNN) deep learning model using frontal chest radiographs (CXRs) and the prevalence reflected by administrative hierarchical condition category codes in two cohorts of patients with coronavirus disease 2019 (COVID-19). METHODS: A CNN model, previously published, was trained to predict atherosclerotic disease from ambulatory frontal CXRs. The model was then validated on two cohorts of patients with COVID-19: 814 ambulatory patients from a suburban location (presenting from March 14, 2020, to October 24, 2020, the internal ambulatory cohort) and 485 hospitalized patients from an inner-city location (hospitalized from March 14, 2020, to August 12, 2020, the external hospitalized cohort). The CNN model predictions were validated against electronic health record administrative codes in both cohorts and assessed using the area under the receiver operating characteristic curve (AUC). The CXRs from the ambulatory cohort were also reviewed by two board-certified radiologists and compared with the CNN-predicted values for the same cohort to produce a receiver operating characteristic curve and the AUC. The atherosclerosis diagnosis discrepancy, Δvasc, referring to the difference between the predicted value and presence or absence of the vascular disease HCC categorical code, was calculated. Linear regression was performed to determine the association of Δvasc with the covariates of age, sex, race/ethnicity, language preference, and social deprivation index. Logistic regression was used to look for an association between the presence of any hierarchical condition category codes with Δvasc and other covariates. RESULTS: The CNN prediction for vascular disease from frontal CXRs in the ambulatory cohort had an AUC of 0.85 (95% confidence interval, 0.82-0.89) and in the hospitalized cohort had an AUC of 0.69 (95% confidence interval, 0.64-0.75) against the electronic health record data. In the ambulatory cohort, the consensus radiologists' reading had an AUC of 0.89 (95% confidence interval, 0.86-0.92) relative to the CNN. Multivariate linear regression of Δvasc in the ambulatory cohort demonstrated significant negative associations with non-English-language preference (ß = -0.083, P < .05) and Black or Hispanic race/ethnicity (ß = -0.048, P < .05) and positive associations with age (ß = 0.005, P < .001) and sex (ß = 0.044, P < .05). For the hospitalized cohort, age was also significant (ß = 0.003, P < .01), as was social deprivation index (ß = 0.002, P < .05). The Δvasc variable (odds ratio [OR], 0.34), Black or Hispanic race/ethnicity (OR, 1.58), non-English-language preference (OR, 1.74), and site (OR, 0.22) were independent predictors of having one or more hierarchical condition category codes (P < .01 for all) in the combined patient cohort. CONCLUSIONS: A CNN model was predictive of aortic atherosclerosis in two cohorts (one ambulatory and one hospitalized) with COVID-19. The discrepancy between the CNN model and the administrative code, Δvasc, was associated with language preference in the ambulatory cohort; in the hospitalized cohort, this discrepancy was associated with social deprivation index. The absence of administrative code(s) was associated with Δvasc in the combined cohorts, suggesting that Δvasc is an independent predictor of health disparities. This may suggest that biomarkers extracted from routine imaging studies and compared with electronic health record data could play a role in enhancing value-based health care for traditionally underserved or disadvantaged patients for whom barriers to care exist.

Validation of a social deprivation index and association with cognitive function and decline in older adults.

OBJECTIVES: Previous work using a US sample has shown that an index of social deprivation (SoDep Index) is associated with cognitive functioning and decline in older adults. This study aimed to replicate these findings using a European sample (Survey of Health, Ageing and Retirement in Europe, SHARE). DESIGN: We analyzed data of 51,630 respondents aged 50 years and older (M: 63.5 years, standard deviation [SD]: 9.1) with at least two cognitive assessments (follow-up M: 6.06 years, SD: 3.86). Cognitive scores were transformed to Z-scores. Multiple growth curve modeling was used to model cognitive status and decline as predicted by the SoDep Index. In a sensitivity analysis, we constructed a new SoDep Index (SoDep Indexnew) including further social deprivation domains. RESULTS: Adjusting for covariates, a unit increase in SoDep Index was associated with a cognitive score of 0.037 SDs smaller (p < .001) and a decline 0.003 SDs per year faster (p < .001). Of the covariates, depressive symptoms, chronic disease burden, male gender, and widowhood were also associated with poorer cognition. Being divorced was associated with better cognition. Sensitivity analysis confirmed findings. Compared to the SoDep Index, the SoDep Indexnew showed a more pronounced association with both cognition and cognitive decline. CONCLUSIONS: We were able to replicate results showing an association between SoDep Index and cognitive function and decline. The sensitivity analysis further emphasizes the relevance of financial security. This strengthens the implication that preventing social deprivation can contribute to reducing the dementia burden by raising cognitive functioning in the older population. The findings are relevant to policy-makers and health care practitioners.

Risk factors for PICU admission and death among children and young people hospitalized with COVID-19 and PIMS-TS in England during the first pandemic year.

Identifying which children and young people (CYP) are most vulnerable to serious infection due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is important to guide protective interventions. To address this question, we used data for all hospitalizations in England among 0-17 year olds from 1 February 2019 to 31 January 2021. We examined how sociodemographic factors and comorbidities might be risk factors for pediatric intensive care unit (PICU) admission among hospitalizations due to the following causes: Coronavirus Disease 2019 (COVID-19) and pediatric inflammatory multi-system syndrome temporally associated with SARS-CoV-2 (PIMS-TS) in the first pandemic year (2020-2021); hospitalizations due to all other non-traumatic causes in 2020-2021; hospitalizations due to all non-traumatic causes in 2019-2020; and hospitalizations due to influenza in 2019-2020. Risk of PICU admission and death from COVID-19 or PIMS-TS in CYP was very low. We identified 6,338 hospitalizations with COVID-19, of which 259 were admitted to a PICU and eight CYP died. We identified 712 hospitalizations with PIMS-TS, of which 312 were admitted to a PICU and fewer than five CYP died. Hospitalizations with COVID-19 and PIMS-TS were more common among males, older CYP, those from socioeconomically deprived neighborhoods and those who were of non-White ethnicity (Black, Asian, Mixed or Other). The odds of PICU admission were increased in CYP younger than 1 month old and decreased among 15-17 year olds compared to 1-4 year olds with COVID-19; increased in older CYP and females with PIMS-TS; and increased for Black compared to White ethnicity in patients with COVID-19 and PIMS-TS. Odds of PICU admission in COVID-19 were increased for CYP with comorbidities and highest for CYP with multiple medical problems. Increases in odds of PICU admission associated with different comorbidities in COVID-19 showed a similar pattern to other causes of hospitalization examined and, thus, likely reflect background vulnerabilities. These findings identify distinct risk factors associated with PICU admission among CYP with COVID-19 or PIMS-TS that might aid treatment and prevention strategies.

Community versus individual risk of SARS-CoV-2 infection in two municipalities of Louisiana, USA: An assessment of Area Deprivation Index (ADI) paired with seroprevalence data over time.

OBJECTIVE: Determine whether an individual is at greater risk of severe acute respiratory distress syndrome coronavirus 2 (SARS-CoV-2) infection because of their community or their individual risk factors. STUDY DESIGN AND SETTING: 4,752 records from two large prevalence studies in New Orleans and Baton Rouge, Louisiana were used to assess whether zip code tabulation areas (ZCTA)-level area deprivation index (ADI) or individual factors accounted for risk of infection. Logistic regression models assessed associations of individual-level demographic and socioeconomic factors and the zip code-level ADI with SARS-CoV-2 infection. RESULTS: In the unadjusted model, there were increased odds of infection among participants residing in high versus low ADI (both cities) and high versus mid-level ADI (Baton Rouge only) zip codes. When individual-level covariates were included, the odds of infection remained higher only among Baton Rouge participants who resided in high versus mid-level ADI ZCTAs. Several individual factors contributed to infection risk. After adjustment for ADI, race and age (Baton Rouge) and race, marital status, household size, and comorbidities (New Orleans) were significant. CONCLUSIONS: While higher ADI was associated with higher risk of SARS-CoV-2 infection, individual-level participant characteristics accounted for a significant proportion of this association. Additionally, stage of the pandemic may affect individual risk factors for infection.

COVID-19 vaccination during pregnancy: coverage and safety.

BACKGROUND: Concerns have been raised regarding a potential surge of COVID-19 in pregnancy, secondary to the rising numbers of COVID-19 in the community, easing of societal restrictions, and vaccine hesitancy. Although COVID-19 vaccination is now offered to all pregnant women in the United Kingdom; limited data exist on its uptake and safety. OBJECTIVE: This study aimed to investigate the uptake and safety of COVID-19 vaccination among pregnant women. STUDY DESIGN: This was a cohort study of pregnant women who gave birth at St George's University Hospitals National Health Service Foundation Trust, London, United Kingdom, between March 1, 2020, and July 4, 2021. The primary outcome was uptake of COVID-19 vaccination and its determinants. The secondary outcomes were perinatal safety outcomes. Data were collected on COVID-19 vaccination uptake, vaccination type, gestational age at vaccination, and maternal characteristics, including age, parity, ethnicity, index of multiple deprivation score, and comorbidities. Further data were collected on perinatal outcomes, including stillbirth (fetal death at ≥24 weeks' gestation), preterm birth, fetal and congenital abnormalities, and intrapartum complications. Pregnancy and neonatal outcomes of women who received the vaccine were compared with that of a matched cohort of women with balanced propensity scores. Effect magnitudes of vaccination on perinatal outcomes were reported as mean differences or odds ratios with 95% confidence intervals. Factors associated with antenatal vaccination were assessed with logistic regression analysis. RESULTS: Data were available for 1328 pregnant women of whom 140 received at least 1 dose of the COVID-19 vaccine before giving birth and 1188 women who did not; 85.7% of those vaccinated received their vaccine in the third trimester of pregnancy and 14.3% in the second trimester of pregnancy. Of those vaccinated, 127 (90.7%) received a messenger RNA vaccine and 13 (9.3%) a viral vector vaccine. There was evidence of reduced vaccine uptake in younger women (P=.001), women with high levels of deprivation (ie, fifth quintile of the index of multiple deprivation; P=.008), and women of Afro-Caribbean or Asian ethnicity compared with women of White ethnicity (P<.001). Women with prepregnancy diabetes mellitus had increased vaccine uptake (P=.008). In the multivariable model the fifth deprivation quintile (most deprived) (adjusted odds ratio, 0.10; 95% confidence interval, 0.02-0.10; P=.003) and Afro-Caribbean ethnicity (adjusted odds ratio, 0.27; 95% confidence interval, 0.06-0.85; P=.044) were significantly associated with lower antenatal vaccine uptake, whereas prepregnancy diabetes mellitus was significantly associated with higher antenatal vaccine uptake (adjusted odds ratio, 10.5; 95% confidence interval, 1.74-83.2; P=.014). In a propensity score-matched cohort, the rates of adverse pregnancy outcomes of 133 women who received at least 1 dose of the COVID-19 vaccine in pregnancy were similar to that of unvaccinated pregnant women (P>.05 for all): stillbirth (0.0% vs 0.2%), fetal abnormalities (2.2% vs 2.5%), postpartum hemorrhage (9.8% vs 9.0%), cesarean delivery (30.8% vs 34.1%), small for gestational age (12.0% vs 12.8%), maternal high-dependency unit or intensive care admission (6.0% vs 4.0%), or neonatal intensive care unit admission (5.3% vs 5.0%). Intrapartum pyrexia (3.7% vs 1.0%; P=.046) was significantly increased but the borderline statistical significance was lost after excluding women with antenatal COVID-19 infection (P=.079). Mixed-effects Cox regression showed that vaccination was not significantly associated with birth at <40 weeks' gestation (hazard ratio, 0.93; 95% confidence interval, 0.71-1.23; P=.624). CONCLUSION: Of pregnant women eligible for COVID-19 vaccination, less than one-third accepted COVID-19 vaccination during pregnancy, and they experienced similar pregnancy outcomes with unvaccinated pregnant women. There was lower uptake among younger women, non-White ethnicity, and lower socioeconomic background. This study has contributed to the body of evidence that having COVID-19 vaccination in pregnancy does not alter perinatal outcomes. Clear communication to improve awareness among pregnant women and healthcare professionals on vaccine safety is needed, alongside strategies to address vaccine hesitancy. These strategies include postvaccination surveillance to gather further data on pregnancy outcomes, particularly after first-trimester vaccination, and long-term infant follow-up.

Hospitalisation and mortality from COVID-19 in Mexican indigenous people: a cross-sectional observational study.

BACKGROUND: Despite having a large indigenous population, little is known about the differences in COVID-19-related health outcomes between indigenous and non-indigenous patients in Mexico. The aim of this study is to analyse the variation in hospitalisation and death between indigenous and non-indigenous patients with COVID-19 to guide future policies and clinical practice. METHODS: We used data from the Mexican Ministry of Health (MoH) to study the hospitalisation and death of adults with laboratory-confirmed SARS-CoV-2 in MoH facilities between 1 March 2020 and 28 February 2021. Predicted probabilities of hospitalisation and death were adjusted for sociodemographic and presentation to care characteristics as well as municipal social deprivation index and health jurisdiction-level index of human resource and hospital equipment availability. RESULTS: Of 465 676 hospitalised adults with COVID-19, 5873 (1.3%) were identified as indigenous. Indigenous patients had higher odds of hospitalisation (adjusted OR (aOR)=1.9, 95% CI 1.8 to 2.0), death (aOR=1.3, 95% CI 1.1 to 1. 3) and early mortality (aOR=1.2, 95% CI 1.0 to 1.4), compared with non-indigenous patients. Living in municipalities with high social deprivation was associated with a higher risk of hospitalisation and early death. Living in areas with low healthcare resources was associated with a higher risk of hospitalisation but not death. Being male, aged 51 years or older, having diabetes, hypertension and obesity were associated with an incremental probability of hospitalisation and death among indigenous patients. CONCLUSIONS: Indigenous patients with COVID-19 in Mexico have a higher risk of hospitalisation and death than non-indigenous individuals. Our findings can guide future efforts to protect this population from SARS-CoV-2 infection and associated outcomes.