Punt Politics as Failure of Health System Stewardship: Evidence from the COVID-19 Pandemic Response in Brazil and Mexico

Pandemic preparedness and response priorities in Latin America: A regional Delphi consensus

OBJECTIVE

The Independent Panel for Pandemic Preparedness and Response issued a series of recommendations for future pandemic preparedness and response. Latin America's COVID-19-related deaths represented 25 % of the global demises, despite harboring less than 8 % of the world's population. As little data exists to support whether the Panel's recommendations reflect public health professionals' priorities in the region the study aimed to define these priorities utilizing a Delphi study.

STUDY DESIGN

A consensus-building modified Delphi technique.

METHODS

For the first two rounds, participants were asked to rank a list of topics across seven domains on a 4-point Likert scale. Topics voted by at least 75 % of participants in either round as very important were included in the final round. Participants ranked the topics from each of the seven domains in numeric order to define top priorities.

RESULTS

A total of 115 responses were obtained across three rounds. Most respondents were involved in direct efforts against COVID-19 (75·0-86·%) and a considerable proportion had more than 16 years of public health experience (37·3-50·0 %). The top priority issues were zoonotic disease-pathogen surveillance systems (27·4 points), robust infection and prevention control programs (22·8 points), and indicator and event-based monitoring and reporting systems (22·1 points).

CONCLUSIONS

Establishing priorities for future pandemics is critical to ensure better health outcomes. The region should strengthen collaboration and enhance its capacities while conducting country-level analysis and defining priorities for future arrangements.

Association between trust in the incumbent president and COVID-19 preventive behaviors during the pandemic in four Latin American countries

The COVID-19 pandemic revealed disparities in policy responses in Latin America. We examined the association between trust in the president and COVID-19 preventive behaviors in Brazil, Chile, Colombia, and Mexico. We used data from the Collaborative COVID-19 Response Survey by the McDonnell Academy at Washington University in St. Louis (United States), from September 2020 to March 2021. Nonprobabilistic sampling included adult citizens from the four countries. Multivariate negative binomial regression models were applied. The study included 8,125 participants, with Brazil showing the lowest adherence to preventive behaviors (65.5%). Increased adoption of preventive behaviors was linked with ages 18-26 (aIRR = 1.05; 95%CI: 1.01-1.09), 60 or more (aIRR = 1.10; 95%CI: 1.05-1.15), and high socioeconomic status (aIRR = 1.09; 95%CI: 1.05-1.13). Decreased engagement was linked to participants from Brazil (aIRR = 0.74; 95%CI: 0.71-0.78), Mexico (aIRR = 0.95; 95%CI: 0.92-0.99), basic education (aIRR = 0.75; 95%CI: 0.68-0.84), intermediate education (aIRR = 0.88; 95%CI: 0.85-0.91), low socioeconomic status (aIRR = 0.91; 95%CI: 0.87-0.94), lack of concern about contracting COVID-19 (aIRR = 0.93; 95%CI: 0.88-0.98), and poor knowledge about COVID-19 (aIRR = 0.92; 95%CI: 0.88-0.96). No significant association was found between trust in the president and preventive behaviors. Targeted communication, public education, and improved access to reliable information are crucial for fostering preventive behaviors. Public health practitioners should not overly concern themselves with political rhetoric, as our study suggests that trust in political authorities may not systematically affect compliance with directives.

Investigating the 'Bolsonaro effect' on the spread of the Covid-19 pandemic: An empirical analysis of observational data in Brazil

Brazil counts among the countries the hardest hit by the Covid-19 pandemic. A great deal has been said about the negative role played by President Bolsonaro's denialism, but relatively few studies have attempted to measure precisely what impact it actually had on the pandemic. Our paper conducts econometric estimates based on observational data at municipal level to quantitatively assess the 'Bolsonaro effect' over time from March 2020 to December 2022. To our knowledge, this paper presents the most comprehensive investigation of Bolsonaro's influence in the spread of the pandemic from two angles: considering Covid-19 mortality and two key transmission mitigation channels (social distancing and vaccination); and exploring the full pandemic cycle (2020-2022) and its dynamics over time. Controlling for a rich set of relevant variables, our results find a strong and persistent 'Bolsonaro effect' on the death rate: municipalities that were more pro-Bolsonaro recorded significantly more fatalities. Furthermore, evidence suggests that the president's attitude and decisions negatively influenced the population's behaviour. Firstly, pro-Bolsonaro municipalities presented a lower level of compliance with social distancing measures. Secondly, vaccination was relatively less widespread in places more in favour of the former president. Finally, our analysis points to longer-lasting and damaging repercussions. Regression results are consistent with the hypothesis that the 'Bolsonaro effect' impacted not only on Covid-19 vaccination, but has affected vaccination campaigns in general thereby jeopardizing the historical success of the National Immunization Program in Brazil.

Self-perception of mental health, COVID-19 and associated sociodemographic-contextual factors in Latin America

This study aimed to estimate the prevalence of alterations in self-perceived mental health during the COVID-19 pandemic and their associated factors in four Latin American countries. This is a cross-sectional study based on data collected from adults in 2021 through the Collaborative Response COVID-19 Survey by the MacDonnell Academy at Washington University in St. Louis (United States). The sample was composed of 8,125 individuals from Brazil, Colombia, Mexico, and Chile. A generalized linear model for a binary outcome variable with a logistic link and fixed country effects was used. There were 2,336 (28.75%) individuals who considered having suffered alterations in self-perceived mental health. Unemployed individuals (OR = 1.40; 95%CI: 1.24-1.58), those with bad/regular quality of life (OR = 5.03; 95%CI: 4.01-6.31), and those with high socioeconomic status (OR = 1.66; 95%CI: 1.41-1.96) had a higher risk of self-perceived mental health alterations than those with full-time employment, excellent quality, and low socioeconomic status. According to the fixed-effects model, Brazilians living in the country during the pandemic, who disagreed with their government's decisions (OR = 2.05; 95%CI: 1.74-2.42) and lacked trust in their government (OR = 2.10; 95%CI: 1.74-2.42) had a higher risk of having self-perceived mental health alterations. Nearly 30% of respondents indicated that the COVID-19 pandemic altered their self-perceived mental health. This outcome was associated with political, sociodemographic, and health risk factors. These findings should help policymakers develop post-pandemic community interventions.

Prevalence of SARS-CoV-2 infection and impact of the COVID-19 pandemic in avocado farmworkers from Mexico

Introduction

The COVID-19 pandemic disproportionately affected farmworkers in the United States and Europe, leading to increased morbidity and mortality. However, little is known about the specific impact of the pandemic on agriculture and food production workers in low- and middle-income countries. This study aimed to investigate the prevalence of SARS-CoV-2 infection and assess the mental health and economic consequences of the COVID-19 pandemic among avocado farmworkers in Michoacan, Mexico.

Methods

We conducted a cross-sectional study of adult farmworkers (n = 395) in May 2021. We collected survey data, nasal swabs and saliva samples for SARS-CoV-2 RNA detection, and blood samples for immunoglobulin G (IgG) reactivity measurements.

Results

None of the farmworkers tested positive for SARS-CoV-2 RNA. However, among unvaccinated farmworkers (n = 336, 85%), approximately one-third (33%) showed evidence of past infection (positive for IgG against SARS-CoV-2). Unvaccinated farmworkers who lived with other farmworkers (aRR = 1.55; 95% CI: 1.05, 2.05), had ever lived with someone with COVID-19 (aRR = 1.82; 95% CI: 1.22, 2.43), and who had diabetes (aRR = 2.19; 95% CI: 1.53, 2.85) had a higher risk of testing IgG-positive for SARS-CoV-2 infection. In contrast, unvaccinated farmworkers living in more rural areas (outside of Tingambato or Uruapan) (aRR = 0.71; 95% CI: 0.46, 0.96) or cooking with wood-burning stove (aRR = 0.75; 95% CI: 0.55, 0.96) had a lower risk of IgG-positivity. Moreover, 66% of farmworkers reported a negative impact of the pandemic on their lives, 29% reported experiencing food insecurity and difficulty paying bills, and 10% reported depression or anxiety symptoms.

Conclusion

The COVID-19 pandemic has significantly affected the mental health and financial well-being of avocado farmworkers. Consequently, the implementation of interventions and prevention efforts, such as providing mental health support and food assistance services, is imperative.

A critical analysis of health system in Nepal; Perspective's based on COVID-19 response

Background

Nepal moved from a unitary government to a federal system of government in 2015 under its constitution. Nepal is a federal democratic republic governed by three levels of government: a federal, provincial, and local level. The response to COVID-19 in Nepal has been majorly led and controlled by the federal government. All three levels of government are performing their responsibilities; however, they face various challenges in responding to COVID-19. This study aimed to critically analyze Nepal's health system in the context of the COVID-19 response.

Methods

We conducted semi-structured in-depth interviews by telephone among the policymakers, health workers, and stakeholders at the federal, provincial, and local levels (n = 41) between January to July 2021. The interviews were audio recorded, transcribed into English, and coded using inductive-deductive approaches.

Results

COVID-19 considerably impacted routine health care, mainly maternity services and immunization. Inadequate financial resources, inadequate human resources, and the lack of ventilators, ICUs, and X-ray services were the significant challenges in tackling and managing COVID-19 effectively.

Conclusion

The study found that all three levels of government perform their roles and responsibilities and effectively manage the pandemic. The federal and provincial governments focused more on the plans and policy development, while the local government demonstrated greater accountability in implementing those plans and policies. Therefore, all three tiers of government need to coordinate together for preparing and communicating information in times of emergency. Besides, it is imperative to empower local governments to maintain Nepal's federal health system.

Virological evidence of the impact of non-pharmaceutical interventions against COVID-19 in Ecuador, a resource-limited setting

Ecuador had substantial COVID-19-mortality during 2020 despite early implementation of non-pharmaceutical interventions (NPIs). Resource-limited settings like Ecuador have high proportions of informal labour which entail high human mobility, questioning efficacy of NPIs. We performed a retrospective observational study in Ecuador's national reference laboratory for viral respiratory infections during March 2020-February 2021 using stored respiratory specimens from 1950 patients, corresponding to 2.3% of all samples analysed within the Ecuadorian national surveillance system per week. During 2020, detection of SARS-CoV-2 (Pearson correlation; r = -0.74; p = 0.01) and other respiratory viruses (Pearson correlation; r = -0.68; p = 0.02) by real-time RT-PCR correlated negatively with NPIs stringency. Among respiratory viruses, adenoviruses (Fisher's exact-test; p = 0.026), parainfluenzaviruses (p = 0.04), enteroviruses (p < 0.0001) and metapneumoviruses (p < 0.0001) occurred significantly more frequently during months of absent or non-stringent NPIs (characterized by <55% stringency according to the Oxford stringency index data for Ecuador). Phylogenomic analyses of 632 newly characterized SARS-CoV-2 genomes revealed 100 near-parallel SARS-CoV-2 introductions during early 2020 in the absence of NPIs. NPI stringency correlated negatively with the number of circulating SARS-CoV-2 lineages during 2020 (r = -0.69; p = 0.02). Phylogeographic reconstructions showed differential SARS-CoV-2 dispersion patterns during 2020, with more short-distance transitions potentially associated with recreational activity during non-stringent NPIs. There were also fewer geographic transitions during strict NPIs (n = 450) than during non-stringent or absent NPIs (n = 580). Virological evidence supports that NPIs had an effect on virus spread and distribution in Ecuador, providing a template for future epidemics in resource-limited settings and contributing to a balanced assessment of societal costs entailed by strict NPIs.

Assessing pandemic preparedness, response, and lessons learned from the COVID-19 pandemic in four south American countries: agenda for the future

Introduction

The COVID-19 pandemic emerged in a context that lacked adequate prevention, preparedness, and response (PPR) activities, and global, regional, and national leadership. South American countries were among world's hardest hit by the pandemic, accounting for 10.1% of total cases and 20.1% of global deaths.

Methods

This study explores how pandemic PPR were affected by political, socioeconomic, and health system contexts as well as how PPR may have shaped pandemic outcomes in Argentina, Brazil, Colombia, and Peru. We then identify lessons learned and advance an agenda for improving PPR capacity at regional and national levels. We do this through a mixed-methods sequential explanatory study in four South American countries based on structured interviews and focus groups with elite policy makers.

Results

The results of our study demonstrate that structural and contextual barriers limited PPR activities at political, social, and economic levels in each country, as well as through the structure of the health care system. Respondents believe that top-level government officials had insufficient political will for prioritizing pandemic PPR and post-COVID-19 recovery programs within their countries' health agendas.

Discussion

We recommend a regional COVID-19 task force, post-pandemic recovery, social and economic protection for vulnerable groups, improved primary health care and surveillance systems, risk communication strategies, and community engagement to place pandemic PPR on Argentina, Brazil, Colombia, and Peru and other South American countries' national public health agendas.

Non-pharmaceutical interventions to combat COVID-19 in the Americas described through daily sub-national data

This dataset covers national and subnational non-pharmaceutical interventions (NPI) to combat the COVID-19 pandemic in the Americas. Prior to the development of a vaccine, NPI were governments' primary tools to mitigate the spread of COVID-19. Variation in subnational responses to COVID-19 is high and is salient for health outcomes. This dataset captures governments' dynamic, varied NPI to combat COVID-19 for 80% of Latin America's population from each country's first case through December 2021. These daily data encompass all national and subnational units in Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Mexico, and Peru. The dataset includes individual and aggregate indices of nine NPI: school closures, work suspensions, public event cancellations, public transport suspensions, information campaigns, local travel restrictions, international travel controls, stay-at-home orders, and restrictions on the size of gatherings. We also collected data on mask mandates as a separate indicator. Local country-teams drew from multiple data sources, resulting in high-quality, reliable data. The dataset thus allows for consistent, meaningful comparisons of NPI within and across countries during the pandemic.

The potential impact of PM2.5 on the covid-19 crisis in the Brazilian Amazon region

OBJECTIVE

This study aims to assess covid-19 morbidity, mortality, and severity from 2020 to 2021 in five Brazilian Amazon states with the highest records of wildfires.

METHODS

A distributed lag non-linear model was applied to estimate the potential exposure risk association with particulate matter smaller than 2.5-µm in diameter (PM2.5). Daily mean temperature, relative humidity, percentual of community mobility, number of hospital beds, days of the week, and holidays were considered in the final models for controlling the confounding factors.

RESULTS

The states of Para, Mato Grosso, and Amazonas have reported the highest values of overall cases, deaths, and severe cases of covid-19. The worrying growth in the percentual rates in 2020/2021 for the incidence, severity, and mortality were highlighted in Rondônia and Mato Grosso. The growth in 2020/2021 in the estimations of PM2.5 concentrations was higher in Mato Grosso, with an increase of 24.4%, followed by Rondônia (14.9%).

CONCLUSION

This study establishes an association between wildfire-generated PM2.5 and increasing covid-19 incidence, mortality, and severity within the studied area. The findings showed that the risk of covid-19 morbidity and mortality is nearly two times higher among individuals exposed to high concentrations of PM2.5. The attributable fraction to PM2.5 in the studied area represents an important role in the risk associated with covid-19 in the Brazilian Amazon region.

Quantifying COVID-19 policy impacts on subjective well-being during the early phase of the pandemic: A cross-sectional analysis of United States survey data from March to August 2020

To stop the spread of COVID-19, a number of public health policies and restrictions were implemented during the pre-vaccination phase of the pandemic. This study provides a quantitative assessment of how these policies impacted subjective well-being (SWB) in the United States over a 6-month period spanning March to August 2020. We study two specific research objectives. First, we aim to quantify the impacts of COVID-19 public health policies at different levels of stringency on SWB. Second, we train and implement a conditional inference tree model for predicting individual SWB based both on socio-demographic characteristics and policies then in place. Our results indicate that policies such as enforcing strict stay-at-home requirements and closing workplaces were negatively associated with SWB, and that an individual's socio-demographic characteristics, including income status, job, and gender, conditionally interact with policies such as workplace closure in a predictive model of SWB. Therefore, although such policies may have positive health implications, they also have secondary environmental and social implications that need to be taken into account in any cost-benefit analysis of such policies for future pandemic preparedness. Our proposed methodology suggests a way to quantify such impacts through the lens of SWB, and to further advance the science of pandemic preparedness from a public health perspective.

Computational methods applied to syphilis: where are we, and where are we going?

Syphilis is an infectious disease that can be diagnosed and treated cheaply. Despite being a curable condition, the syphilis rate is increasing worldwide. In this sense, computational methods can analyze data and assist managers in formulating new public policies for preventing and controlling sexually transmitted infections (STIs). Computational techniques can integrate knowledge from experiences and, through an inference mechanism, apply conditions to a database that seeks to explain data behavior. This systematic review analyzed studies that use computational methods to establish or improve syphilis-related aspects. Our review shows the usefulness of computational tools to promote the overall understanding of syphilis, a global problem, to guide public policy and practice, to target better public health interventions such as surveillance and prevention, health service delivery, and the optimal use of diagnostic tools. The review was conducted according to PRISMA 2020 Statement and used several quality criteria to include studies. The publications chosen to compose this review were gathered from Science Direct, Web of Science, Springer, Scopus, ACM Digital Library, and PubMed databases. Then, studies published between 2015 and 2022 were selected. The review identified 1,991 studies. After applying inclusion, exclusion, and study quality assessment criteria, 26 primary studies were included in the final analysis. The results show different computational approaches, including countless Machine Learning algorithmic models, and three sub-areas of application in the context of syphilis: surveillance (61.54%), diagnosis (34.62%), and health policy evaluation (3.85%). These computational approaches are promising and capable of being tools to support syphilis control and surveillance actions.

Impact of vaccination on infection or death from COVID-19 in individuals with laboratory-confirmed cases: Case-control study

OBJECTIVES

The objective of this study is to estimate the effectiveness of COVID-19 vaccines in people treated within the social security system whose vaccination status was reported to the epidemiological surveillance system.

STUDY DESIGN

Case-control study.

METHODS

This was a case-control study conducted. The records of individuals with suspected cases of COVID-19 registered in the epidemiological surveillance system between February 1 and June 30, 2021, were studied. RT-qPCR was performed to determine SARS-CoV-2 infection; those with a positive result were considered cases, and those with a negative result were considered controls. The ratio between cases and controls was 1:1.3. The crude and adjusted vaccine effectiveness was considered the prevention of symptomatic infection and death and calculated as the difference between the dose and the risk, with a survival analysis among vaccinated people.

RESULTS

A total of 94,416 individuals were included, of whom 40,192 were considered cases and 54,224 controls; 3,781 (4.00%) had been vaccinated against COVID-19. Vaccination also proved to be a protective factor against COVID-19, especially in the population who received a second dose (OR = 0.31; 95% CI 0.28-0.35). With the application of the vaccine, there was a protective effect against mortality (OR = 0.76; 95% CI 0.66-0.87). Disease prevention was higher for the BNT162-2 mRNA vaccine (82%) followed by the ChAdOx1 vaccine (33%). In the survival analysis, vaccination provided a protective effect.

CONCLUSIONS

There was a positive impact of vaccines for the prevention of symptomatic COVID-19, with a second dose generating greater efficacy and a reduction in deaths.

Achieving Universal Health Coverage in Low- and Middle-Income Countries: Challenges for Policy Post-Pandemic and Beyond

Background

Achieving universal health coverage (UHC) is critical for ensuring equity, improving health, and protecting households from financial catastrophe. The COVID-19 pandemic derailed the progress made across primary health targets. This article aims to review the policy challenges to achieve UHC in a post-pandemic world.

Methods

A narrative review of 118 peer reviewed and grey literature was conducted. A total of 77 published articles were identified using an electronic search in PubMed and Scopus and a bibliographic search of relevant literature. Another 41 Reports, websites, blogs, news articles, and data were manually sourced from international agencies (WHO, World Bank, IMF, FAO, etc.), government agencies, and non-government organizations.

Findings

The challenges were identified and discussed under five broad findings: i) weak public health care systems ii) challenges to building resilient health systems, iii) health care financing and financial risk protection, iv) epidemiological and demographic challenges, and v) governance and leadership.

Conclusion

LMICs in Africa and South Asia face significant challenges to achieving UHC by 2030. As countries recover from the pandemic's aftermath, significant investments and innovations are needed to ensure progress toward UHC. Efficient resource mobilization through internal accruals, international cooperation, and resource sharing is needed.

Populism and health. An evaluation of the effects of right-wing populism on the COVID-19 pandemic in Brazil

What are the effects of right-wing populism in the struggle against COVID-19? We explore data from Brazil, a country whose populist radical right-wing president was among the prominent denialists regarding the effects of the pandemic. Using cross-sectional and weekly-panel data for 5,570 municipalities during 2020, we present evidence that social distancing was weakened, and the number of cases and deaths were higher in places where the president had received greater electoral support during the 2018 presidential elections. Placebo tests using traditional right-wing vote and data on Severe Acute Respiratory Syndrome (SARS) before the pandemic outbreak indicate that the former does not correlate with health outcomes, and the populist share of the vote does not correlate with the latter. Hence, we find strong indications that right-wing populism relates to a poor response to the disease.

Healthcare of pregnant women with diabetes during the COVID-19 pandemic: a Southern Brazilian cross-sectional panel data

OBJECTIVES

To evaluate the indirect effects of the COVID-19 pandemic on the care of women with pregnancies complicated by gestational or pre-existing diabetes, and their maternal-fetal outcomes.

METHODS

A cross-sectional panel data conducted in a University Hospital in Southern Brazil. Maternal-fetal outcomes and predictors of care from 235 pregnant women with type 1, type 2, or gestational diabetes were evaluated. Two time periods were compared: six months preceding the pandemic, in 2019, and the COVID-19 period from September 2020 to March 2021. Comparisons were performed using analysis of variance, Mann-Whitney U, Fisher's exact and T-tests. Risks were calculated using the Poisson regression with robust estimates.

RESULTS

Maternal age was lower (32.1 ± 6.8 vs. 34.4 ± 6.6, p=0.009) and rates of depression/anxiety were higher (16.5 vs. 7.4%, p=0.046) in the group evaluated during the COVID-19. Neonatal hypoglycemia (RR 4.04; 95% CI 1.37-11.98, p=0.012), and SGA rates (RR 4.29; 95% CI 1.93-9.54, p<0.001) were higher in the group assessed before the pandemic.

CONCLUSIONS

Despite economic, social and structural impacts of the pandemic, parameters of maternal care were similar; diabetes control improved, and neonatal hypoglycemia and SGA rates were lower among pregnant women with diabetes during the pandemic.

The New SARS-CoV-2 Variants and Their Epidemiological Impact in Mexico

The COVID-19 disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus started its deadly journey into a global pandemic in Wuhan, China, in December 2019, where it was first isolated. Subsequently, multiple variants of the virus have been identified worldwide. In this review, we discuss the overall landscape of the pandemic in Mexico, including its most prevalent variants, their surveillance at a genomic level, and how they impacted the epidemiology of the disease. We also evaluate the heterologous vaccination in Mexico and how it may have influenced group immunity and helped mitigate the pandemic. Finally, we present an integrated view that could help us to understand the pandemic and serve as an example of the situation in Latin America.

Application of Data Science for Cluster Analysis of COVID-19 Mortality According to Sociodemographic Factors at Municipal Level in Mexico

Mexico is among the five countries with the largest number of reported deaths from COVID-19 disease, and the mortality rates associated to infections are heterogeneous in the country due to structural factors concerning population. This study aims at the analysis of clusters related to mortality rate from COVID-19 at the municipal level in Mexico from the perspective of Data Science. In this sense, a new application is presented that uses a machine learning hybrid algorithm for generating clusters of municipalities with similar values of sociodemographic indicators and mortality rates. To provide a systematic framework, we applied an extension of the International Business Machines Corporation (IBM) methodology called Batch Foundation Methodology for Data Science (FMDS). For the study, 1,086,743 death certificates corresponding to the year 2020 were used, among other official data. As a result of the analysis, two key indicators related to mortality from COVID-19 at the municipal level were identified: one is population density and the other is percentage of population in poverty. Based on these indicators, 16 municipality clusters were determined. Among the main results of this research, it was found that clusters with high values of mortality rate had high values of population density and low poverty levels. In contrast, clusters with low density values and high poverty levels had low mortality rates. Finally, we think that the patterns found, expressed as municipality clusters with similar characteristics, can be useful for decision making by health authorities regarding disease prevention and control for reinforcing public health measures and optimizing resource distribution for reducing hospitalizations and mortality.

Brazil's health system functionality amidst of the COVID-19 pandemic: An analysis of resilience

Background

As of December 31, 2020, Brazil had the second-highest burden of COVID-19 worldwide. Given the absence of federal government coordination, it was up to the local governments to maintain healthcare provision for non-COVID health issues. In this descriptive study, we aimed to discuss the SUS functionality and resilience, describing the impact of the pandemic on non-COVID health services delivery while considering the regional inequalities of the allocation of financing health system, health infrastructure and health workforce.

Methods

We used input-output framework based on the World Health Organization (WHO) Health System Building Blocks to estimate health system functionality and resilience. An ecological assessment was designed to calculated mean relative changes to compare the first year of the pandemic in Brazil with the previous one. All data used in this study were anonymized and made available by the Brazilian Ministry of Health. Input indicators were categorized in health system financing (federal funding received as well as expenditure of both state and city governments), health system's infrastructure (hospital beds) and health workforce (healthcare workers positions). Output indicators were categorized into nine different groups of service delivery procedures. To explore the relationship between the variation in procedures with socioeconomic conditions, we used the Socioeconomic Vulnerability Index (SVI).

Findings

State governments had a 38·6% increase in federal transfers, while municipal governments had a 33·9% increase. The increase of ICU beds reached its peak in the third quarter of 2020, averaging 72·1% by the end of the year. The country also saw an increase in jobs for registered nurses (13·6%), nurse assistants (8·5%), physiotherapists (7·9%), and medical doctors (4·9%). All procedures underwent expressive reduction: Screenings (−42·6%); Diagnostic procedures (−28·9%); Physician appointments (−42·5%); Low and medium complexity surgeries (−59·7%); High complexity surgeries (−27·9%); Transplants (−44·7%); Treatments and clinical procedures due to injuries of external causes (−19·1%); Irrepressible procedures (−8·5%); and Childbirths (−12·6%). The most significant drop in procedures happened in the first quarter of the pandemic, followed by progressive increase; most regions had not yet recovered by the end of 2020. State-level changes in numbers of procedures point towards a negative trend with SVI.

Interpretation

The Brazilian Government did not consider that socioeconomically vulnerable states were at a higher risk of being impacted by the overburden of the health system caused by the COVID-19, which resulted in poorer health system functionality for those vulnerable states. The lack of proper planning to improve health system resilience resulted in the decrease of a quarter of the amount of healthcare procedures increasing the already existing health disparities in the country.

Funding

MCTIC/CNPQ/FNDCT/MS/SCTIE/DECIT N^o 07/2020.

COVID-19 and Chagas Disease in Buenos Aires, Argentina

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2. COVID-19 leads, in most patients, to mild-to-moderate symptoms, but some develop severe disease and succumbed to death. People with medical conditions have a higher risk of death than those without them. Chagas disease (CD) can cause cardiac diseases in approximately one-third of affected people. The aim of this study is to find out if there is any clinical association between Chagas disease and COVID-19 severity. This is a cohort study of 29 patients who were hospitalized with COVID-19 and had a diagnosis of chronic Trypanosoma cruzi infection. This coinfected cohort was matched by sex, age, presence of comorbidities, and requirement of hospitalization on intensive care unit (ICU) at admission with a control cohort of patients hospitalized due to COVID-19 without CD in a 3:1 ratio (n = 87). The clinical outcomes evaluated were as follows: days of hospitalization, death, and requirement of ICU and mechanical respiratory assistance (MV). The study protocol was approved by the Institutional Ethics in Research Committee. The Chagas disease/COVID-19 coinfected cohort had a median age of 55 years old (49.0, 66.0); 17 (59%) were male. All patients survived the acute COVID-19. Three of them were admitted to the ICU, and two required MV. Twenty-two (75.8%) required supplemental oxygen. There were no statistical differences in any laboratory parameters between the groups except for lactic acid dehydrogenase, which showed higher levels in the coinfected cohort, with a median of 573 U/L (interquartile range: 486.00, 771.00) vs. 476 U/L (346.00, 641.00) in the control group (p = 0.007). There were no differences in clinical outcomes between both groups. On the cohort with Chagas disease, there were zero deaths, three (10.3%) were admitted in the ICU, and two (6.9%) required MV, while for the control group there were six deaths (6.6%), 13 required ICU (14.9%), and 11 required MV (12.6%), without a statistically significant difference. This small series of coinfected Chagas disease and COVID-19 does not suggest differences in clinical evolution compared to non-Chagas patients. This data is similar to a Brazilian cohort. More data of this population with and without cardiomyopathy is needed to optimize the follow-up and recommendation for the population affected by this neglected tropical disease about COVID-19.

Indoor Dining and In-Person Learning: A Comparison of 30 US Cities

With limited US federal leadership on closing and re-opening strategies to mitigate the COVID-19 pandemic, cities and states were left to enact their own policies. This article examines two key sets of policies-in-person learning in public elementary schools and indoor dining-across 30 of the largest US cities in the summer, fall, and winter of 2020. We review indoor dining and in-person elementary education policy decisions between 1 May 2020 and 14 December 2020 across 30 US cities. We review the public health evidence, political power, and jurisdictional challenges that cities faced, and the policy implications of these factors. Overwhelmingly, indoor dining re-opened in cities while in-person elementary schools were kept closed; indoor dining re-opened in all cities in fall 2020, while only 40% of public elementary schools re-opened for in-person instruction. Looking ahead to fully bringing students back for in-person learning, and considering future potential community outbreaks, this retrospective analysis can help inform city and state governments on policy decisions around indoor dining and reopening/closing schools for in-person learning.