Findings from a scoping review

COVID-19 vaccination at a hospital in Paris: Spatial analyses and inverse equity hypothesis

Background

Vaccination against SARS-CoV-2 has been deployed in France since January 2021. Without specific action for different population subgroups, the inverse equity hypothesis postulates that people in the most deprived neighbourhoods will be the last to benefit. The article aims to study whether the inverse care law has been verified in the context of vaccination against SARS-CoV-2 from a vaccination centre of a hospital in the Paris region.

Methods

We performed a spatial analysis using primary data from the vaccination centre of the Avicenne Hospital in Bobigny from January 8th to September 30th, 2021. Primary data variables include the vaccinated person's date, age, and postal address. Secondary data calculates access times between residential neighbourhoods and the vaccination centre and social deprivation index. We performed flow analysis, k-means aggregation, and mapping.

Results

32,712 people were vaccinated at the study centre. Vaccination flow to the hospital shows that people living in the most disadvantaged areas were the last to be vaccinated. The number of people immunized according to the level of social deprivation then scales out with slightly more access to the vaccination centre for the most advantaged. The furthest have travelled more than 100 km, and more than 1h45 of transport time to get to this vaccination centre.

Conclusion

The study confirms the inverse equity hypothesis and shows that vaccination preparedness strategies must consider equity issues. Public health interventions should be implemented according to proportionate universalism and use community health, health mediation, and outreach activities for more equity.

A social acceptability scale: Validation in the context of government measures to curb the COVID-19 pandemic in Senegal

INTRODUCTION

In March 2020, the government of Senegal introduced a curfew, a ban on travel between regions, the closure of markets, and a ban on attending places of worship to contain the spread of the COVID-19 pandemic. As part of research into the response to COVID-19, we developed a scale to measure the social acceptability of these measures.

METHODS

We used Sekhon's theoretical framework of acceptability (TFA) to formulate the content of the scale items. We assessed the homogeneity of the scale using Cronbach's Alpha and average interitem correlations. We measured the dimensional properties of the scale using rating scale models. We tested the sensitivity of the scale to sociodemographic characteristics using mixed linear regressions and rating scale models.

RESULTS

The final scale consisted of seven items corresponding to the constructs of acceptability. Analysis performed on data from 813 individuals showed that the scale has satisfactory statistical properties (Cronbach's α > 0.8, Loevinger's coefficient>0.3, intraclass correlation>0.4).

CONCLUSION

This scale was one of the first to test the TFA. The small number of items was advantageous for use under challenging data collection contexts. Measuring the acceptability of public health interventions with this tool can help in their design and implementation.

Factors associated with the utilization of diagnostic tools among countries with different income levels during the COVID-19 pandemic

BACKGROUND

Disparities in the utilization of essential medical products are a key factor contributing to inequality in health outcomes. We aimed to analyze the trends and influencing factors in using Coronavirus disease 2019 (COVID-19) diagnostic tools and disparities in countries with different income levels.

METHODS

We conducted a cross-sectional study using open and publicly available data sources. Data were mainly collected from the Foundation for Innovative New Diagnostics, "Our World in Data," and the Global Burden of Disease databases. Negative binomial regression model and generalized linear mixed model were employed to investigate into five sets of factors associated with the usage of diagnostics: severity of COVID-19, socioeconomic status, health status, medical service capacity, and rigidity of response. Dominance analysis was utilized to compare the relative importance of these factors. The Blinder-Oaxaca decomposition was used to decompose the difference in the usage of diagnostics between countries.

RESULTS

The total COVID-19 testing rate ranged from 5.13 to 22,386.63 per 1000 people from March 2020 to October 2022 and the monthly testing rate declined dramatically from January 2022 to October 2022 (52.37/1000 vs 5.91/1000).. The total testing rate was primarily associated with socioeconomic status (37.84%), with every 1 standard deviation (SD) increase in Gross Domestic Product per capita and the proportion of people aged ≥ 70, the total testing rate increased by 88% and 31%. And so is the medical service capacity (33.66%), with every 1 SD increase in health workforce density, the number increased by 38%. The monthly testing rate was primarily associated with socioeconomic status (34.72%) and medical service capacity (28.67%), and the severity of COVID-19 (21.09%). The average difference in the total testing rates between high-income and low-income countries was 2726.59 per 1000 people, and 2493.43 (91.45%) of the differences could be explained through the five sets of factors.

CONCLUSIONS

Redoubling the efforts, such as local manufacturing, regulatory reliance, and strengthening the community health workforce and laboratory capacity in low- and middle-income countries (LMICs) cannot be more significant for ensuring sustainable and equitable access to diagnostic tools during pandemic.

Did the design and planning of testing and contact tracing interventions for COVID-19 consider social inequalities in health? A multiple case study from Brazil, Canada, France & Mali

The COVID-19 pandemic has led to an unprecedented global crisis. It has exposed and exacerbated weaknesses in public health systems worldwide, particularly with regards to reaching the most vulnerable populations, disproportionately impacted by the pandemic. The objective of our study was to examine whether and how social inequalities in health (SIH) were considered in the design and planning of public health responses to COVID-19 in jurisdictions of Brazil, Canada, France, and Mali. This article reports on a qualitative multiple case study of testing and contact tracing interventions in regions with high COVID-19 incidence in each country, namely: Manaus (Brazil), Montréal (Canada), Île-de-France (France), and Bamako (Mali). We conducted interviews with 108 key informants involved in these interventions in the four jurisdictions, focusing on the first and second waves of the pandemic. We analyzed our data thematically using a theoretical bricolage framework. Our analysis suggests that the lack of a common understanding of SIH among all actors involved and the sense of urgency brought by the pandemic eclipsed the prioritization of SIH in the initial responses. The pandemic increased intersectoral collaboration, but decision-making power was often unequal between Ministries of Health and other actors in each jurisdiction. Various adaptations to COVID-19 interventions were implemented to reach certain population groups, therefore improving the accessibility, availability, and acceptability of testing and contact tracing. Our study contributes to identifying lessons learned from the current pandemic, namely that the ways in which SIH are understood shape how interventions are planned; that having clear guidelines on how to integrate SIH into public health interventions could lead to more inclusive pandemic responses; that for intersectoral collaboration to be fruitful, there needs to be sufficient resources and equitable decision-making power between partners; and that interventions must be flexible to respond to emerging needs while considering long-standing structural inequalities.

Considering social inequalities in health in COVID-19 response: insights from a French case study

The COVID-19 pandemic highlighted the impact of social inequalities in health (SIH). Various studies have shown significant inequalities in mortality and morbidity associated with COVID-19 and the influence of social determinants of health. The objective of this qualitative case study was to analyze the consideration of SIH in the design of two key COVID-19 prevention and control interventions in France: testing and contact tracing. Interviews were conducted with 36 key informants involved in the design of the intervention and/or the government response to the pandemic as well as relevant documents (n = 15) were reviewed. We applied data triangulation and a hybrid deductive and inductive analysis to analyze the data. Findings revealed the divergent understandings and perspectives about SIH, as well as the challenges associated with consideration for these at the beginning stages of the pandemic. Despite a shared concern for SIH between the participants, an epidemiological frame of reference dominated the design of the intervention. It resulted in a model in which consideration for SIH appeared as a complement, with a clinical goal of the intervention: breaking the chain of COVID-19 transmission. Although the COVID-19 health crisis highlighted the importance of SIH, it did not appear to be an opportunity to further their consideration in response efforts. This article provides original insights into consideration for SIH in the design of testing and contact-tracing interventions based upon a qualitative investigation.

Knowledge of COVID-19 and the impact on indigents' access to healthcare in Burkina Faso

BACKGROUND

COVID-19 constitutes a global health emergency of unprecedented proportions. Preventive measures, however, have run up against certain difficulties in low and middle-income countries. This is the case in socially and geographically marginalized communities, which are excluded from information about preventive measures. This study contains a dual objective, i) to assess knowledge of COVID-19 and the preventive measures associated with it concerning indigents in the villages of Diebougou's district in Burkina Faso. The aim is to understand if determinants of this understanding exist, and ii) to describe how their pathways to healthcare changed from 2019 to 2020 during the COVID-19 pandemic.

METHODS

The study was conducted in the Diebougou healthcare district, in the south-west region of Burkina Faso. We relied on a cross-sectional design and used data from the fourth round of a panel survey conducted among a sample of ultra-poor people that had been monitored since 2015. Data were collected in August 2020 and included a total of 259 ultra-poor people. A multivariate logistic regression to determine the factors associated with the respondents' knowledge of COVID-19 was used.

RESULTS

Half of indigents in the district said they had heard about COVID-19. Only 29% knew what the symptoms of the disease were. The majority claimed that they protected themselves from the virus by using preventive measures. This level of knowledge of the disease can be observed with no differences between the villages. Half of the indigents who expressed themselves agreed with government measures except for the closure of markets. An increase of over 11% can be seen in indigents without the opportunity for getting healthcare compared with before the pandemic.

CONCLUSIONS

This research indicates that COVID-19 is partially known and that prevention measures are not universally understood. The study contributes to reducing the fragmentation of knowledge, in particular on vulnerable and marginalized populations. Results should be useful for future interventions for the control of epidemics that aim to leave no one behind.