key: cord-284883-bkydu285
authors: Luis Silva, L.; Dutra, A. C.; Iora, P. H.; Ramajo, G. L. R.; Messias, G. A. F.; Gualda, I. A. P.; Scheidt, J. F. H. C.; Amaral, P. V. M. d.; Staton, C.; Rocha, T. A. H.; Andrade, L.; Vissoci, J. R. N.
title: Brazil Health Care System preparation against COVID-19
date: 2020-05-13
journal: nan
DOI: 10.1101/2020.05.09.20096719
sha: 
doc_id: 284883
cord_uid: bkydu285

Background: The coronavirus disease outbreak from 2019 (COVID-19) is associated with a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a highly contagious virus that claimed thousands of lives around the world and disrupted the health system in many countries. The assessment of emergency capacity in every country is a necessary part of the COVID-19 response efforts. Thus, it is extremely recommended to evaluate the health care system to prepare the country to tackle COVID-19 challenges. Methods and Findings: A retrospective and ecological study was performed with data retrieved from the public national healthcare database (DATASUS). Numbers of intensive care unit and infirmary beds, general or intensivists physicians, nurses, nursing technicians, and ventilators from each Regional Health Unity were extracted, and the beds per health professionals and ventilators per population rates were assessed. The accessibility to health services was also performed using a spatial overlay approach to verify regions that lack assistance. It was found that Brazil lacks equity, integrity, and may struggle to assist with high complexity for the COVID-19 patients in many regions of the country. Conclusions: Brazilian health system is insufficient to tackle the COVID-19 in some regions of the country where the coronavirus may be responsible for high rates of morbidity and mortality.

The coronavirus disease 2019 is associated with the novel severe acute respiratory syndrome coronavirus-2 (SARS-Cov-2) identified in December 2019 (1) . As of May 9, 2020, COVID-19 has globally infected 4,018,342 people resulting in 278,756 deaths (2) [report 104]. The WHO declared COVID-19 a public health emergency of international concern (PHEIC) by the end of January 2020 under the International Health Regulations (IHR) (3) . Few weeks after the PHEIC declaration, the COVID-19 outbreak was declared to be a pandemic, drawing attention worldwide (4) .

The pandemic led to the adoption of several non-pharmacological interventions ranging from social distancing guidelines to national-level lockdowns by different countries (5) . These stringent interventions have severely impacted the way of living of many people and disrupted the already precarious health system in many countries (6) . In response to the COVID-19 pandemic, several countries undertook analyses for the necessary health system strengthening efforts. According to studies dedicated to characterizing the clinical evolution of the disease, 39% of the cases demand emergency care, with a subset of 5% needing ICU and 2.9 % demanding ventilator support to sustain life (33) . In the U.S., the percentage of patients needing ventilator support was even higher, reaching up to 12,2%.

The response effort to tackle the COVID-19 requires a strong organization of the emergency network (7) . The lack of beds, iniquities in the distribution of hospitals, and inadequate availability of ventilators could hamper the actions aiming to decrease the negative consequences of the COVID-19 (8) . Unfortunately, usually, the distribution of the health resources within the countries are characterized by inequities (9) . Due to the COVID-19 consequences, the scenario faced by low and medium-income countries is even more staggering (8) . The historic challenges regarding an insufficient number of health professionals, iniquities in the distribution of human resources (10) , low accessibility to emergency care services (11) , and economic issues create additional pressures to be addressed, aiming is to achieve an adequate COVID-19 response.

As the COVID-19 spreads around the world, the hospital systems lack measures against the virus (12) , and many countries are experiencing shortages of hospital supplies (13) . For example, as of March 11, in Italy, where there were 12,462 cases of COVID-19 and 827 deaths, 1,028 of 5,200 beds in intensive care units (ICU) are occupied. A few days later, there were no more ICU beds available (14). In the United States of America, it is estimated that the disease will stress bed capacity, equipment, and health care personnel, as never seen before (15) . The Brazilian case is not an exception (11) . In order to reduce the burden of COVID-19, the hospital administrators, governments, policy-makers, and researchers must be prepared for a surge in the Healthcare System (16) .

Brazil is characterized by severe social disparities and health inequities. On May 9 155,939 cases were confirmed and 10,627 deaths (17) (https://covid.saude.gov.br/). However, this number is under-reported, and the real number is estimated to be nine times greater, . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

The copyright holder for this preprint this version posted May 13, 2020. . https://doi.org/10.1101/2020.05.09.20096719 doi: medRxiv preprint according to some simulations (18) . To further the concern, The Imperial College estimates that up to 1 million people will fall ill due to COVID-19 in Brazil (19) .

During the last decade, Brazil is struggling to increase the funding of the public unified system (SUS). Despite the efforts performed in 2016, the Constitution Amendment 95 (E.C. 95 acronym in Portuguese) reduced the budget of the Ministry of Health by almost seven billion reais by year (20) . Before the EC95, the Brazilian Health System was already underfunded (21) . Two years after the EC95, the consequences regarding the lack of funding were aggravated by the COVID-19 pandemic. Additionally, Brazil is also facing a political crisis contributing to divergences between the administrative levels in the country.

The consequences of all these elements combined could hamper the response actions to tackle the COVID-19. The availability of information during a crisis is essential to support the decision-making process based on evidence. Taking this point into consideration the present work addresses critical aspects regarding the organization of the emergency network system in Brazil, jointly with the spatial expansion of COVID-19 cases within the country, and to highlight where the efforts currently performed in Brazil were capable of coping with the lack of access to emergency care needed to cope COVID-19 consequences.

The present paper is an ecological, observational, and cross-sectional study using a spatial analysis approach. The data sources are based on secondary data from the Unified Health System (SUS) (22) . To fulfill the defined objective, the adequacy parameters in terms of human resources, health care structure, and accessibility to emergency care services were analyzed in comparison with the reported incidence of COVID-19.

According to data from the Brazilian Institute of Geography and Statistics (IBGE), Brazil is located in South America with a territorial area of 8.510.820,623 km 2 and has a total of 210,147,125 inhabitants, with Human Development Index (HDI) of 0.51 with diversified values for the municipalities ranging from 0.41 to 0.86 (figure 1) (23). For the assessment of methodological quality, we followed the Guideline Strengthening the Reporting of Observational Studies in Epidemiology (STROBE).

To characterize the Brazilian emergency care services network, three sources were used: National Register of Health Facilities (CNES acronym in Portuguese), population data from the IBGE, and COVID-19 cases reported by Secretariat of Surveillance of the Ministry of Health (https://covid.saude.gov.br/). Data regarding hospitals, professionals (nurses, nursing technicians, doctors, and physiotherapists), and equipment (ventilators, ICU, and infirmary beds) were obtained from . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

The copyright holder for this preprint this version posted May 13, 2020. . https://doi.org/10.1101/2020.05.09.20096719 doi: medRxiv preprint the CNES website using R through the microdatasus package (24) . The population data and thematic maps were fetched from the IBGE (23).

The match between the number of health professionals and the recommended suitability parameters were compared using the guidelines from the National Health Surveillance Agency (ANVISA) Resolution of the Collegiate Board of Directors (RDC). The ANVISA RDC number 7 provides the minimum requirements for the operation of Intensive Care Units, in which ten ICU beds are required for each one intensive care physician and one physiotherapist, one intensive care nurse for every eight beds, and two nursing assistants for each bed (25) The building of thematic maps was carried out by grouping the municipalities by Health Regions Unity (H.R.) using software QGIS 3.0. The (H.R.) is a continuous geographic space constituted by a group of bordering municipalities delimited by cultural, economic, and social identities, created by the Ministry of Health in order to mitigate the disparities in the country (26) .

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To identify regions with a high incidence of COVID-19, simultaneously presenting a lack of emergency network was used as a spatial overlay approach. The first step comprised the development of an emergency infrastructure index (EII). The EII was obtained computing the number of beds registered, by the ratio of professionals and equipment according to the last competence of February 2020 from CNES.

To evaluate the geographical accessibility to emergency care service care was used the two-step floating catchment area (2SFCA) technique. With this approach, it was possible to assess the accessibility to emergency care services by the interaction of two geographic characteristics: (a) the volume of available hospital beds weighted by population within 2 hours of travel distance, and (b) the proximity of hospitals within a 2 hours displacement from . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 13, 2020. . https://doi.org/10.1101/2020.05.09.20096719 doi: medRxiv preprint each municipality (11) . The 2SFCA method generated two accessibility indexes for each municipality in Brazil, one regarding the network available in February 2020, and a secondary one highlighting where the COVID-19 new exclusive beds increased the access to emergency services. Both indexes created the conditions to identify regions with a lack of access to emergency care, as well as the regions being benefited by the expansion of the ICU beds dedicated to the CODVID-19 response. To highlight regions with a high incidence of COVID-19 and a lack of emergency structure, an overlap analysis was conducted to select the municipalities concurrently, showing a pattern of high incidence, jointly with a lack of access to emergency services.

Once the EII was computed, and the municipalities with high incidence within regions with low access to emergency care services care were identified, a Getis-Ord-Gi analysis was performed. Thus, it was possible to point out three spatial clusters: (1) emergency care services accessibility on February 20; (2) municipalities with low access to emergency care services and high COVID-19 incidence, (3) accessibility to ICU beds exclusively dedicated to COVID-19 response in March 2020.

Following the Resolution No. 510/16 of the National Health Council and considering that we used secondary sources which are available in governmental and online databases, the dispensation of the consent form was requested to the Ethics Committee.

COVID-19 has shown a fast growth rate in Brazil. The total number of confirmed deaths in the country initially increased at a similar pace as Germany and Iran. However, differently than these countries, it has not yet shown a decrease in its growth rate ( Figure 1A) . Subnationally, the growth rate of confirmed deaths shows an unequal pattern. Likely due to different state-level isolation policies, the states of São Paulo, Rio de Janeiro, Ceará, and Amazonas have shown a much faster growth rate than the rest of the country ( Figure 1B) . Nonetheless, the country as a whole seems to be still far from its peak number of new deaths by COVID-19.

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The copyright holder for this preprint this version posted May 13, 2020. CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 13, 2020. February 2020) . In terms of professionals and beds per 10,000 inhabitants, the southern region had the highest rates for ICU beds, ventilators, physicians, nurses, and technicians. In contrast, the northern region had the lowest ones (Table 1 ). Figure 2 shows the rates of beds and professionals per Health Regions. The ICU beds per intensivist varied from zero to 53, zero to 156.5 per intensive care nurse, zero to 0.21 per technician, and zero to 2 per physiotherapist. In addition, hospital beds per physician varied from 0.10 to 7.14, 0.52 to 11.26 per nurse, 0.19 to 2.58 per technician, and 1.32 to 31.28 per physiotherapist. Figure 2 shows the distribution of professionals, beds, and ventilators throughout the territory, and classifies this distribution according to RDC number 7. In A, most H.R. is by the RDC, which determines up to 10 intensivists for each ICU bed. However, 132 HR do not have ICU beds and / or have no intensivist. In B, only 54 H.R. are working according to the recommended amount of 1 critical care nurse for each 8 ICU beds. C and D show that 322 HR are working correctly with the capacity of 1 nursing assistant and one physiotherapist for every 2 and 10 beds, respectively. In the second row of figure 1 , F, G, and H show that there are nurses, nursing technicians and physiotherapists working above the limit of 1 nurse per 8 infirmary bed, one nursing technician for each two-infirmary bed and one physiotherapist per 10 infirmary bed. . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 13, 2020. Panel A in figure 5 depicts the COVID-19 incidence by the Brazilian municipality up to 04/29/2020. It is possible to observe that all states and regions currently are presenting COVID-19 cases with a highlight to the states of Amazonas, Amapá, Espírito Santo, and Santa Catarina, where it is already noted areas with hot colors. The hot colors indicate higher levels of incidence. In terms of deaths, all state capitals of the North, Northeast, and southeast regions are presenting high levels of mortality when compared with the rest of the country. Figure 6 presents three maps characterizing the Brazilian situation in terms of emergency services and the COVID-19 incidence. Panel A exhibits the accessibility index to ICU beds by population. The map highlights a higher accessibility index close to the state capitals of the Brazilian states. The map B emphasizes the municipalities presenting a COVID-19 incidence higher than the national average of 16.49, simultaneously with an accessibility index lower than the national mean 21 per 100,000 inhabitants Thus, every municipality in the map B is facing challenges in terms of emergency care services and a high COVID-19 incidence for the Brazilian standards. Map C presents the accessibility index of the new beds created exclusively to offer intensive care to COVID-19 patients. Few beds with this specific purpose were open in the states of the North and Midwest region of the country. Figure 7 shows the result of spatial clustering analysis to identify trends in access, as well as in the COVID-19 incidence. Panel A exhibits a hot spot covering the Southeast, Midwest, and South regions of the country. The states covered by the red layer presents the spatially significant group of municipalities with higher levels of access to ICU beds by population. On the opposite side, the blue layer highlights the regions facing geographical barriers to grant access to ICU beds to the population. To build the map B, the same approach was used, but this time only applied to the municipalities with high COVID-19 incidence and a low index of accessibility to ICU beds. The red color characterized a group of municipalities in the South and Midwest regions. Despite the higher availability of beds in these regions, it was possible to observe a statistically significant group of municipalities within these regions with barriers to access ICU beds. Map C illustrates the cluster of accessibility regarding the ICU beds created to tackle the COVID-19. The lack of overlay between the red color of maps B and C is pointing out a mismatch of the response efforts dedicated to addressing the COVID-19 challenge. The regions in map B characterized as hotspots were considered cold spots regarding the creation of ICU beds dedicated to COVID-19. The result suggests that the use of scarce resources needed to put in order ICU beds are not being directed to municipalities lacking access to emergency care services, despite their high levels of COVID-19 incidence. 

The ongoing COVID-19 pandemic has caused nearly 4 million confirmed cases and claimed over 278,756 lives worldwide as of May 9, 2020 (2) [report 104]. It is noteworthy to mention that the COVID-19 outbreak is a challenge to the health systems worldwide (27) , and although the outcome for the crisis caused by this disease is uncertain, SARS-CoV-2 will overwhelm health care infrastructure for months (28) . In this study, the Brazilian health system was evaluated to verify its capacity to tackle the COVID-19 challenge.

According to the WHO, it is recommended one doctor and one nurse per 1,000 inhabitants as a parameter of health care for the population (29). To strengthen the WHO recommendations, the Brazilian Health Governments has established in the Resolution of the Collegiate Board of Directors number 7/2010, the quantities of ICU and infirmary beds per intensivists, general physicians, nurses, nursing technician and physiotherapists (25) . Although Table 1 shows that in Brazil, there is a sufficient number of physicians in the country, figure 1 shows that these professionals are not evenly distributed to accomplish the WHO recommendations and CBR. In addition, the number of nurses does not meet the criteria in the north and midwest. To illustrate the problem, figure 1 shows that Brazil has desert zones of ICU assistance and regions where these professionals have to take care of beds far beyond the quantities stipulated by the RDC. Bahtt et al., 2017 verified that professionals in critical care that were caring for more patients per shift were more likely to experience burnout (30). Halpern et al., 2017 informed that intensivists are also in shortage in the United States of America, and this situation may be attributed to burnout (31) . Therefore, the combat against the COVID-19 may be a difficult task in these regions, since providing access and affordable care for the large urban populations is already a challenge for many countries (32).

Experience from Lombardia has shown that 9% of patients with COVID-19 were admitted in the ICU treatment, whereas this number varied from 5 to 32% in some cities in China (33) . On the other hand, in Brazil, there are no available large data of ICU patients at the moment, and supposing that those numbers might appear in the country as well, only 4 out of 438 Health Regionals could manage this number of patients.

In terms of nursing care in ICU accessibility, figure 1 shows that there are large regions of care voids, probably because there are low amounts of ICU nurses in Brazil (34) . Besides that, it's possible to visualize that there are regions where ICU and generalist nurses are responsible for more than eight ICU and infirmary beds, which may represent a risk of unfavorable outcome for the COVID-19 treatment since that high amount of patients per nurse are associated with a range of negative patient outcomes (35, 36) .

The pandemic has led to severe shortages of many essential supplies, such as ICU beds and ventilators (37) . Based on Italy's numbers that 10 to 25% of hospitalized patients will require ventilation, the Centers for Disease Control and Prevention estimates that in the USA, there will be between 1.4 to 31 patients per ventilator this period (29, 37). Brazil, on the other hand, 2.5 to 3.4 million people will require hospitalization, according to The Imperial . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 13, 2020. College of London (19) , which represents 4 to 13 patients per ventilator if distributed equally. The numbers may represent a satisfactory amount of equipment. However, figure 1 shows that there are no ventilators in some H.R. that are potential places to have a high number of deaths.

The most staggering result was obtained through the spatial cluster analysis. Brazil is currently facing a double crisis. The political positioning of the president is going against the technical recommendations of the Ministry of Health and WHO. Consequently, there is a disagreement between the Federal administration, and the states and municipalities. On account of that situation, each administrative level is conducting several response actions against COVID-19 without country-level coordination. The spatial clusters analysis highlighted that new beds created to tackle the COVID-19 were misplaced. The hot spot clusters of municipalities with high incidence and lack of access are not overlapping with the hot spot cluster of new beds dedicated to the COVID-19. This situation calls attention for the misplacement of scarce resources during a pandemic. The scenario depicted is the result of a lack of coordination at the national level. The consequence of misplacing the new COVID-19 ICU beds is an increase in the chance of deaths due to a lack of emergency care services for municipalities currently presenting a COVID-19 incidence above the national average.

From now on, Brazil has several difficulties in treating patients in critical care. This paper shows that there is an insufficient number of ICU beds, ventilators, and a huge lack of professionals in healthcare. Additionally, the misplacement of the new beds aiming to fight the COVID-19 pandemic contributes to worsening the situation observed through the other indicators assessed. Developed countries like Italy and the United States demonstrate that COVID-19 can overwhelm the healthcare capacities of well-resourced nations very fast (16, 38) . Therefore, the SARS-CoV-2 epidemic in middle-income countries, such as Brazil (39), may be devastating. Our findings suggest that strong leadership is needed to coordinate the response efforts against the COVID-19.

The limitations of this work rely on the complex data available. Health data from health information systems, including health-facility records, surveys, or vital statistics, may not be representative of the entire population of a country and, in some cases, may not even be accurate (40). The CNES database presents some limitations well known by the Brazilian scientific community (41) . Despite this, the information regarding the availability of COVID-19 beds was published just a month ago, calling attention to the occurrence of efforts aiming to improve the quality of the data available to policymakers.

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The copyright holder for this preprint this version posted May 13, 2020. . https://doi.org/10.1101/2020.05.09.20096719 doi: medRxiv preprint

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We would like to thank the coordination for the Improvement of Higher Education Personnel (CAPES). The authors declare no conflicts of interest.

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