The Brazilian PHC response to the COVID-19 pandemic: individual and collective comprehensiveness and performance profiles

doi:10.21203/rs.3.rs-1909134/v1

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Research Article

The Brazilian PHC response to the COVID-19 pandemic: individual and collective comprehensiveness and performance profiles

https://doi.org/10.21203/rs.3.rs-1909134/v1

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Background

Brazil has more than 33,000 primary health care facilities (PHCF) which could have played an important role in the fight against the COVID. Brazilian primary health care(PHC) should deal with the following axes to reduce the impact of COVID-19 on health needs: COVID-19 treatment; health surveillance; continuity of care; and social support. This article aims to analyze the performance profile of PHC during the pandemic in the five Brazilian macroregions.

Methods

A cross-sectional study was carried out as a survey format, using probability sampling of PHCF. A Composite Index was created, the Covid PHC Index(CPI). The process of creating the CPI started with the selection of the 59 most relevant questions, which were aggregated into 26 variables distributed in axes. CPI with a value equal to 100 would represent a more complete performance of the PHCF. Factor analysis revealed that the axes that encompass collective actions (Health Surveillance and Social Support) behaved in a similar manner and in contrast to those focused on individual actions (COVID-19 Treatment and Continuity of Care). Differences in the distributions of CPI components between macroregions were verified. Associations between the CPI and socioeconomic, political and health indicators of the PHCF localities were also verified.

Results

907 PHCFs participated in the survey. The PCI and its axes didn’t exceed 70, with the highest value being observed in the surveillance axis(70) and the lowest in the social support axis(59). When analyzing the dimension that articulates the practices more focused on individual care (Continuity of Care and COVID-19 Treatment), a greater value is observed in the units of the South region, when compared to those of the Northeast, and the relationship is exactly the opposite in the Collective Dimension. PHCF with the highest CPI belong to municipalities with the lowest MHDI, GDP per capita, population, number of hospitals, and ICU beds.

Conclusions

Primary Health Care

COVID-19 Pandemic

Brazil

Health Services

Family Health Strategy

Health Survey

Facing the coronavirus disease (COVID-19) pandemic has been a task of enormous magnitude for all health systems, requiring a broad and articulated set of responses. Unfortunately, this response was not observed in most countries in the beginning of 2020, which contributed to the high rates of morbidity and mortality [1]. At first, the actions were almost exclusively directed to the expansion of the offer of hospital care and intensive care beds. However, it quickly became clear that these actions would be insufficient and that the pandemic could only be fought by implementing a wide range of actions [2, 3]. Robust intelligence systems capable of notifying actions; PHC services with a well-defined role; social isolation measures articulated with social support policies for the most vulnerable populations; strong health surveillance associated with community actions; and significant investments in the development of vaccines, were pointed out, even in the beginning of 2020, as essential to face the most dramatic health situation in the last 100 years [4–6].

In Brazil, the magnitude of this fight against the disease was even greater, as the health crisis was added to a political, economic and ethical crisis aggravated by the denialist actions of the Presidency of the Republic [7–11]. Undoubtedly, the combination of the federal government's necropolitics with the country's social inequality, where a large part of the population, especially the black population, lives in a situation of social vulnerability, amplified the devastating potential of Covid-19 [6–8].

The first case of Covid-19 was reported in Brazil on February 26, 2020 and on March 22 of the same year, cases had already been reported in all states of the Federation. The pandemic in the country led to a high number of deaths and cases, amounting to more than 600,000 deaths in the beginning of 2022, affecting especially the black and poor population [12, 13]. The rates were higher and more accelerated in states with greater social inequality. The risk of illness or death, as well as the seroprevalence of antibodies, was higher in the black population, those with a lower level of schooling, those in the lowest income quintile or living in the poorest areas of the cities [14, 15]. The scenario was just not more dramatic due to the decentralized structure of the Brazilian health system, most state and municipal governments implemented actions to circumvent the obstacles imposed by the federal administration and minimize the effects of the pandemic [16–19].

It is recalled that the Brazilian Unified Health System, called SUS (the acronym in Portuguese of Sistema Único de Saúde) since 1990, offers free and universal health care (Paim, 2011) [20]. The SUS, despite its reduced funding, has improved the population's health conditions and ensured the expansion of access to health services in general and particularly to primary health care (PHC). There are currently more than 33,000 primary health care facilities (PHCF) with strong capillarity throughout the territory. Undoubtedly, these services could play a central role in the fight against the COVID-19 pandemic. In PHC, there is a huge set of actions and strategies that can and should be implemented in the prevention, care and control of the epidemic, as previously corroborated by a large amount of literature [21–26]. The implementation of these actions, especially when they are part of a global plan to face health emergencies, led to better responses in some countries [27–29].

The Brazilian PHC model, widely recognized worldwide, was the Family Health Strategy (FHS) until 2017, characterized by the combination of individual care with strong community and regional actions. Its coverage comprises over 130 million people (approximately 63% of the population). Currently, about 43,000 multi-professional teams of the FHS are the gateway to the system and source of continued care for defined populations in specific territories. By integrating health promotion, disease prevention and surveillance, treatment and rehabilitation, delivered by physicians, nurses, dentists and more than 300,000 community health workers, the FHS represents one of the most significant innovations in PHC since Alma Ata, joining both Primary Care (PC) and essential public health (PH) functions [30, 31]. However, this model has been losing centrality in health policies in Brazil since 2019, especially with the policies implemented by the far-right government of Jair Bolsonaro, which led to the loss of FHS priority as a care model for the Brazilian PHC.

Medina et al. (2020) [24], dialoguing with the organization model of the Brazilian PHC, proposed four essential axes for its performance during the pandemic: COVID-19 treatment; health surveillance; continuity of care; and social support. Carrying out activities in these four axes would not only allow a better fight against the pandemic but would also reduce the impact of COVID-19 on the other health needs of the population.

This article was conceived based on the perspective of the need for (re)organization of PHC services to face the COVID-19 pandemic, with the aim to analyze the performance profile of PHC services during the pandemic in the five Brazilian macroregions.

A cross-sectional study was carried out as a survey format, using probability sampling. The reference population comprised the set of Primary Health Care Facilities (PHCF) registered in the National Registry of Health Establishments (CNES, Cadastro Nacional dos Estabelecimentos de Saúde) in December 2020. This population was stratified considering the five macroregions of the country. For the smallest (North and Midwest), intermediate (South) and largest (Southeast and Northeast) ones, the sample sizes were defined as 100, 150 and 200, respectively, corresponding to sampling errors of 10 of 8 and 7 percentage points, totaling 750 units. For the total of Brazil, the sampling error is 3.92, considering a design effect of 1.20, due to weighting.

The choice of analyzing the five macroregions of Brazil stems from the heterogeneity of the Brazilian territory, which lies on a pattern of socio-spatial exclusion, with important effects on the provision of public goods and services, including health, as shown in Table 1.

Table 1

Population, economic and health information. Brazil and Regions (2019).
	North	Northeast	Southeast	South	Midwest	Brazil
Population^a	18,430,980	57,071,654	88,371,433	29,975,984	16,297,074	210,147,125
Population density^b	4.8	36.7	95.6	53.2	10.1	24.7
Gross Domestic Product (GDP) per capita^b (R$)	22,811	18,359	44,330	42,438	44,876	35,162
Gini Index^b	0.537	0.560	0.528	0.467	0.506	0.544
Percentage of population with adequate water supply^b	90.5	91.4	99.6	99.5	99.3	96.5
Percentage of population with adequate sanitary facilities^b	56.4	65.6	93.3	88.6	72.6	80.3
Percentage of population with regular waste collection/disposal^b	71.7	74.8	91.9	90.5	86.4	84.9
Nurses SUS/1000 inhabitants^c	0.9	1.1	1.1	1.2	1.1	1.1
Physicians SUS/1000 inhabitants^c	0.9	1.1	1.7	1.7	1.5	1.4
Hospital beds SUS/1000 inhabitants^c	0.8	1,0	0.7	1.1	0.9	0.9
UCI beds Adult SUS/100k inhabitants^c	4.6	5.9	8.1	9.2	6.8	7.2
UCI beds Neonatal SUS/1000 live births^c	1.1	1.3	2,0	2.4	1.4	1.7
Ventilators in use SUS/100k inhabitants^c	14.2	16.2	23.8	22.6	23.5	20.7
% of hospital admissions sensitive to primary care^c	28.7	24.5	20,0	20.9	21.9	22.1
Crude hospital admission rates (SUS)/1000 inhabitants^c	55.5	57.8	54.7	72.9	58.8	58.5
Infant mortality rates (< 1 year of age)/1000 live births^c	15.1	13.7	11.5	10.2	11.8	12.4
% of children under 1 year of age with immunization with tetravalent/pentavalent vaccine^c	70.0	71.9	69.8	73.9	70.1	71.0
Estimated population coverage by Primary Health Care teams^c	70.7	83.8	68.1	77.7	70.5	74.2
Population coverage (%) by private health plans^d	9.3	11.6	32.7	23.1	19.9	22.5
^aFederal Accounting Court TCU)
^bBrazilian Institute of Geography and Statistics (IBGE)
^cDATASUS - SUS Information Technology Department SUS –Brazil’s Unified Health System
^dNational Supplementary Health Agency(ANS)

Considering a response rate of 80%, 945 PHCF were randomly sampled. The inclusion criteria for PHCF were: being operational during the pandemic period and having a doctor, nurse or dentist working there for more than six months. Anticipating the need to exclude units after the beginning of the fieldwork, a reserve of units was also drawn aiming to replace those that did not belong to the study population (units mistakenly registered in the CNES as being Primary Care units) or that did not meet the inclusion criteria. A total of 40 units were included from this reserve. The four axes of PHC action in the fight against COVID-19 proposed by Medina et al (2020) were used as a theoretical reference, guiding the creation of the questionnaire and the analysis of the results (Fig. 1). Data collection was carried out between July 15 and November 12, 2021. In each selected Primary Health Care Facilities (PHCF), the manager or another health professional who met the inclusion criteria was invited to answer the online questionnaire. The study data were collected and managed using the Research Electronic Data Capture (REDCap) tool [32]. This is a secure web-based software platform designed to support data capture for research studies. Among others, data were collected on: the physical structure of the PHCF and available connectivity resources; basic supplies for the care of users with COVID-19; reorganization process for the COVID-19 treatment; care continuity actions; use of teleconsultation, telehealth and telemonitoring; characteristics of access to the secondary and tertiary network in cases that required intensive clinical care; surveillance actions in the territories and social support actions.

The descriptive analysis consisted in characterizing the study population regarding the different variables raised in the survey through the estimation of proportions and respective confidence intervals (95% confidence level), for each of the regions and for the country as a whole.

The different probabilities of drawing samples used in the strata for the selection of the sample units were compensated by the introduction of weights in the data analysis stage, corresponding to the inverse of the sampling fractions used in the strata.

After the descriptive analysis of the variables and dialoguing with the presumed theoretical framework, we verified that it was necessary to classify the PHCFs according to the comprehensiveness of the actions carried out in the four axes, i.e., to identify which PHCF performed a greater number of actions considered crucial in the fight against COVID-19 in Brazil. For this purpose, a Composite Index was created, called Covid Primary Health Care Index (CPI).

The process of creating the CPI started with the definition of the most relevant issues in each axis, which was carried out by a group of researchers with more than 25 years of study om the Brazilian PHC. In this first stage, 59 questions were selected, aggregated into 26 variables distributed in the four axes (Chart 1). To verify and guarantee the coherence and consistency of the Index, the non-parametric correlations (Spearman) between the index, the axes and the initially proposed variables were tested, followed by the factor analysis (principal components analysis), aiming to validate its structure and, finally, the consistency analysis (Cronbach's alpha), leading to the final model. The details of this process can be seen in the Additional file 1.

Chart 1 – CPI axes: selected aggregate and component variables.

AXES	Aggregate variables	Component variables
COVID-19 TREATMENT	1.1 Equipment (oximeter, O₂, thermometer)	Availability and sufficiency of oximeter, O₂ and thermometer
	1.2 RT-PCR and rapid (Ag) test supplies	Access to and sufficiency of RT-PCR and rapid (Ag) tests
	1.3 Change in PHCF operation	Increase in working hours and design of a specific workflow for respiratory symptoms, maintained at the time of research
	1,4 Institutional transportation and referral of critically-ill patients	Provision of Mobile Emergency Care Service (SAMU) or Municipal Department of Health (SMS) transportation x other. Clear definition of patient referral
	1.5 Remote follow-up modalities	Phone calls, WhatsApp (messages) and Video calls
	1.6 In-person consultation	In-person consultations
	1.7 Home or peridomiciliary visits	Home or peridomiciliary visits
HEALTH SURVEILLANCE	2.1 Territory information	Information on confirmed cases of covid-19 and on patients hospitalized due to Covid-19
	2.2 Notification (ILI)	Notification on Influenza-like Ilness
	2.3 Test collection	Collection of material for RT-PCR and rapid test (Ag)
	2.4 Health Education	Encouraging social isolation and other preventive initiatives (hand washing, masks and ventilation)
	2.5 Case Surveillance	Case monitoring, active search for contacts; and monitoring quarantine/isolation contacts
SOCIAL SUPPORT	3.1 Social support activities carried out by the PHCF or the CHW	Distribution of basic food items and access to the Bolsa Família (conditional cash transfer program) enrollment
	3.2 Knowledge of the PHCF about the existence of initiatives of the population in its territory	Improving access to water and cleanliness of common areas; distribution of meals; combating fake news about covid-19 and ensuring conditions for proper isolation
	3.3 Social articulation	Cooperation of the PHCF with social movements and with other sectors (government departments, ,companies, churches) in order to cope with the pandemic
CONTINUITY OF CARE	4.1 Routine consultations/care	Offer of consultations: spontaneous demand, medical and nursing consultations and dental care.
	4.2 Maternal-child health care	Offer of prenatal and childcare consultations and preventive examination for cervical cancer
	4.3 Routine vaccination	Offer of routine vaccination
	4.4 NTCDs Care	Offer of care to people with SAH, DM and other NTCDs
	4.5 Home carer	Offer of home visits by health professionals
	4.6 Multidisciplinary care (NASF/FHSC)	Offer of FHSC-PHC Professional Activity
	4.7 Mental Health Care	Offer of mental health care
	4.8 Remote patient follow-up modalities	Phone calls, WhatsApp (messages) and Video calls
	4.9 List of priority patients	Existence of a list of priority group users
	4.10 Electronic request of exams/ prescription	Digital exam request and electronic prescription
	4.11 Home delivery of medicines	Existence of home delivery of medicines

The index was built with equal weights for the axes and the variables in it, according to the formula below:

Covid Primary Health Care Index(CPI):

$$Index={\underset{\_}{X}}_{ {e}_{1}}^{{ e}_{n}};where {e}_{*}={\underset{\_}{X}}_{ {v}_{1}}^{{ v}_{n}}$$

Axes: e₁ to e_n 0 ≤ e_*≤1

Variables: v1 to v_n 0 ≤ v*≤1

In brief, a CPI with a value equal to 100 would represent a more complete performance of the PHCF and a value equal to zero, the failure to carry out any of the actions considered relevant when fighting the COVID-19 pandemic. The same reasoning is valid for the respective score of each axis. To facilitate the discussion, the range from zero to one hundred was divided into quartiles, corresponding to very low, low, medium and high values.

The factor analysis revealed that the axes that encompass more collective actions (Health Surveillance and Social Support) behaved in a similar manner and in contrast to the axes more focused on individual actions (COVID-19 Treatment and Continuity of Care). Therefore, two dimensions were defined, the individual and the collective one, which articulate the axes and also express the characteristics of the Brazilian PHC.

Aiming to verify possible differences in the distributions of CPI, dimensions and variables between the regions, the median and interquartile range were used as reference. Kruskal-Wallis test was used for the set of data and Dunn's test, with Bonferroni correction, for multiple comparisons between the regions.

Associations were also verified between the CPI categorized according to its median and the socioeconomic, demographic, political, structural and COVID-19 surveillance variables of the municipalities in which the PHCFs were located, using the Mann-Whitney test.

The study was approved by the Research Ethics Committee of FSP/USP under CAAE number 31414420.8.0000.5421 and statement number 4,827,811 of July 5, 2021.

A total of 907 PHCFs participated in the survey, corresponding to 95.8% of the selected PHCFs, with no differences between the regions. Most respondents were nurses (82.9%), followed by physicians (7.8%). Reflecting the preponderance of FHS in the country, 92.7% (95%CI: 90.7–94.2) of the responses were from PHCF with FHS, with a difference between regions, as a greater number of PHCF without FHS was found in the Southeast and South regions (Table 2).

Table 2

Characteristics of survey respondents and of the Primary Health Care Facilities, july 2021, Brazil
Brazil and Regions ^a	North % (CI 95%)	Northeast % (CI 95%)	Southeast % (CI 95%)	South % (CI 95%)	Midwest % (CI 95%)	Brazil %^b (CI 95%)
Respondent’s profession, p = 0.0401
Nurse	79.20	86.28	80.24	83.33	85.25	83.26
Nurse	(71.15–85.46)	(81.13–90.2)	(74.8–84.75)	(77.25–88.04)	(77.75–90.53)	(80.53–85.67)
Physician	11.20	7.08	5.65	8.07	9.84	7.33
Physician	(6.73–18.07)	(4.38–11.26)	(3.37–9.32)	(4.91–12.97)	(5.65–16.57)	(5.74–9.31)
Other^c	9.60	6.64	14.11	8.60	4.92	9.42
Other^c	(5.52–16.19)	(4.03–10.73)	(10.30–19.04)	(5.33–13.60)	(2.22–10.56)	(7.59–11.63)
Percentage of respondents with management post or function at the PHCF	59.20	63.27	68.15	62.37	59.02	64.02
	(50.34–67.50)	(56.77–69.33)	(62.07–73.66)	(55.16–69.06)	(50.05–67.42)	(60.63–67.28)
Percentage of PHCF according to the number of Family Health Strategy teams p < 0.0001
0	1.60	1.77	14.92	11.29	2.46	7.35
0	(0.4–6.21)	(0.66–4.63)	(10.99–19.93)	(7.46–16.72)	(0.79–7.39)	(5.8–9.25)
1	58.40	71.24	57.26	56.99	59.84	62.78
1	(49.54–66.75)	(64.98–76.78)	(51.00–63.29)	(49.75–63.94)	(50.87–68.19)	(59.43–66.02)
2	20.80	10.18	10.48	16.13	17.21	12.57
2	(14.54–28.85)	(6.85–14.87)	(7.23–14.97)	(11.5–22.16)	(11.47–25.01)	(10.51–14.96)
3	11.20	5.75	5.65	9.14	10.66	7.04
3	(6.73–18.07)	(3.36–9.67)	(3.37–9.32)	(5.75–14.23)	(6.27–17.54)	(5.52–8.95)
4 or more	8.00	11.06	11.69	6.45	9.84	10.26
4 or more	(4.34–14.27)	(7.57–15.88)	(8.24–16.34)	(3.69–11.04)	(5.65–16.57)	(8.3–12.61)

Table 2

Characteristics of survey respondents and of the Primary Health Care Facilities, july 2021, Brazil (continued)
Brazil and Regions ^a	North % (CI 95%)	Northeast % (CI 95%)	Southeast % (CI 95%)	South % (CI 95%)	Midwest % (CI 95%)	Brazil %^b (CI 95%)
Number of consultation offices per PHCF p < 0.0001
2 or less	47.20	50.88	34.27	32.26	40.98	41.87
2 or less	(38.58–55.99)	(44.37–57.37)	(28.61–40.42)	(25.91–39.33)	(32.58–49.95)	(38.51–45.31)
3 or more	52.80	49.12	65.73	67.74	59.02	58.13
3 or more	(44.01–61.42)	(42.63–55.63)	(59.58–71.39)	(60.67–74.09)	(50.05–67.42)	(54.69–61.49)
Conectivity of the PHCF
Fixed line p < 0.0001	18.40	15.04	79.03	93.01	62.30	50.43
Fixed line p < 0.0001	(12.52–26.22)	(10.94–20.34)	(73.5–83.67)	(88.31–95.91)	(53.34–70.48)	(47.83–53.04)
Cell phones p = 0.0002	26.40	20.35	29.03	41.40	35.25	27.77
Cell phones p = 0.0002	(19.39–34.85)	(15.59–26.13)	(23.7–35.01)	(34.51–48.64	(27.26–44.16)	(24.86–30.88)
Internet connection p < 0.0001	76.80	90.71	97.58	98.39	97.54	93.33
Internet connection p < 0.0001	(68.56–83.40)	(86.15–93.87)	(94.71–98.91)	(95.1–99.48)	(92.61–99.21)	(91.4–94.86)
Good quality internet and adequacy to the activities of the PHCF p < 0.0001	58.40	78.32	77.42	81.72	71.31	76.26
	(49.54–66.75)	(72.45–83.23)	(71.78–82.21)	(75.48–86.66)	(62.62–78.67)	(73.23–79.05)
PHCF availability of computers with camera, microphone and internet connectivity	16.80	26.99	25.81	38.71	27.87	27.46
	(11.19–24.44)	(21.59–33.17)	(20.73–31.63)	(31.96–45.93)	(20.60–36.52)	(24.49–30.65)
Use of private cellphone to contact health care users p < 0.0001
No	7.20	4.87	8.87	14.52	3.28	7.58
No	(3.78–13.30)	(2.71–8.59)	(5.90-13.12)	(10.13–20.37)	(1.23–8.45)	(5.99–9.55)
Yes - eventually	26.40	22.57	37.90	30.65	26.23	29.21
Yes - eventually	(19.39–34.85)	(17.57–28.50)	(32.06–44.12)	(24.42–37.67)	(19.16–34.79)	(26.20-32.42)
Yes - frequently	66.40	72.57	53.23	54.84	70.49	63.21
Yes - frequently	(57.64–74.16)	(66.36–78.01)	(46.98–59.37)	(47.61–61.87)	(61.77–77.94)	(59.88–66.42)

Table 2

Characteristics of survey respondents and of the Primary Health Care Facilities, july 2021, Brazil (continued)
Brazil and Regions^a	North % (CI 95%)	Northeast % (CI 95%)	Southeast % (CI 95%)	South % (CI 95%)	Midwest % (CI 95%)	Brazil %^b (CI 95%)
Remote modalities Covid-19 treatment
Phone calls p < 0,0001	69.60	80.97	89.52	89.25	90.98	84.68
Phone calls p < 0,0001	(60.95–77.06)	(75.3–85.59)	(85.03–92.77)	(83.90–92.97)	(84.41–94.95)	(82.01-87.02)
WhatsApp messages p < 0,0001	65.60	73.01	56.05	70.97	65.57	66.09
WhatsApp messages p < 0,0001	(56.82–73.43)	(66.83–78.41)	(49.79–62.12)	(64.01–77.06)	(56.68–73.49)	(62.78–69.26)
Video calls p=0,0075	19.20	26.99	16.94	17.20	16.39	20.91
Video calls p=0,0075	(13.19–27.10)	(21.59–33.17)	(12.75–22.14)	(12.42–23.35)	(10.80–24.10)	(18.19–23.92)
Remote modalities Continuity of care
Phone calls p = 0,0001	33.60	34.51	50.40	49.46	49.46	42.63
Phone calls p = 0,0001	(25.84–42.36)	(28.58–40.97)	(44.19–56.61)	(42.31-56.64)	(42.31-56.64)	(39.29–46.05)
WhatsApp messages	42.40	45.13	41.94	42.47	45.08	43.5
WhatsApp messages	(34.01–51.26)	(38.74–51.69)	(35.93–48.19)	(35.54–47.71)	(36.45–54.02)	(40.09–46.98)
Video calls	15.20	15.93	15.32	9.68	16.39	14.83
Video calls	(9.89–22.65)	(11.70–21.32)	(11.34–20.38)	(6.17–14.86)	(10.8–24.1)	(12.5–17.5)
Covid-19 treatment for users with severe conditions p < 0.0001	37.60	19.91	29.84	47.85	34.43	29.66
	(29.52–46.44)	(15.19–25.65)	(24.45–35.85)	(40.74–55.05)	(26.51–43.32)	(26.72–32.78)
PHCF organized a unique workflow for users with respiratory symptoms in 2020 p < 0.0001	81.60	85.84	94.76	93.55	89.34	89.69
	(73.78-87.48)	(80.64-89.82)	(91.17-96.94)	(88.96-96.31)	(82.46-93.73)	(87.36-91.62)
a Number of responses: Brazil = 907; North = 125; Northeast = 226; Southeast = 248; South = 186; Midwest = 122.
b Result for Brazil calculated according to sample weights
c Dental Surgeon. physiotherapist. social assistant. physical educator. nutritionist. pharmacist. psychologist

The majority of respondents, 62.8% (95%CI: 59.4–66.0), work in PHCF with only one FHS team and with an equally small availability of consultation offices. The connectivity structure of PHCF shows marked differences between the Brazilian regions (Table 2). In the pandemic scenario, the availability of these elements can be considered even more essential for the provision of adequate care.

The index values of the four analyzed axes for the country as a whole, did not exceed 70, with the highest value being observed in the surveillance axis and the lowest in the social support axis (Table 3).

Table 3

CPI axes. dimensions and aggregate variables: average scores and 95% CI. Brazil and regions.
CPI axes and aggregate variables	North	Northeast	Southeast	South	Midwest	Brazil	Significant differences
1. COVID-19 TREATMENT	65 (61–68)	64 (62–67)	68 (65–70)	70 (67–73)	64 (61–67)	66 (65–67)	S > N; NE
1.1 Equipment (oximeter, O₂, thermometer)	58 (53–63)	55 (52–59)	74 (70–77)	84 (81–87)	71 (66–76)	67 (65–69)	S > all regions SE; MW > N;NE;
1.2 Supplies for RT-PCR and rapid tests (Ag)	45 (38–53)	50 (44–55)	54 (49–59)	63 (57–69)	48 (40–55)	52 (49–55)	S > N. NE;MW
1.3 Change in PHCF (PHC facilities) operation	54 (48–60)	60 (57–64)	64 (61–67)	66 (63–70)	63 (58–67)	62 (60–64)	S; SE > N
1.4 Institutional transportation/referrals	93 (91–95)	94 (93–96)	95 (94–97)	94 (92–95)	92 (90–95)	94 (93–95)	ns
1.5 Remote follow-up modalities	52 (46–57)	60 (56–64)	54 (51–58)	59 (55–63)	58 (53–63)	57 (55–59)	NE > N; SE
1.6 In-person consultations	74 (66–81)	60 (54–67)	67 (61–72)	63 (56–70)	62 (53–70)	64 (61–67)	ns
1.7 HV (home visit) or peridomiciliary visit	77 (69–84)	70 (64–76)	67 (61–72)	59 (52–66)	58 (49–67)	67 (64–70)	N > S; MW
2. HEALTH SURVEILLANCE	69 (65–73)	71 (69–74)	71 (68–74)	69 (65–72)	67 (64–71)	70 (69–72)	ns
2.1 Territory Information	63 (56–71)	76 (71–81)	74 (70–79)	70 (64–76)	66 (58–73)	73 (70–75)	NE > N; MW
2.1 ILI (Influenza-like Illness) Notification	77 (69–84)	72 (66–78)	72 (66–77)	60 (53–67)	65 (56–73)	70 (67–73)	S < N. NE; SE
2.3 Test collection	26 (19–32)	21 (16–26)	36 (31–41)	44 (38–51)	32 (25–39)	30 (28–33)	S > N; NE < S; SE
2.4 Health Education	95 (92–98)	97 (96–99)	89 (86–92)	89 (86–92)	91 (87–95)	93 (92–94)	N > S; SE; NE > S. SE;MW
2.5 Case Surveillance	85 (80–90)	90 (87–93)	83 (79–87)	80 (75–84)	83 (78–89)	86 (84–87)	NE > S

Table 3

CPI axes. dimensions and aggregate variables: average scores and 95% CI. Brazil and regions (continued)
CPI axes and aggregate variables	North	Northeast	Southeast	South	Midwest	Brazil	Significant differences
3. SOCIAL SUPPORT	60 (56–64)	62 (60–65)	57 (54–60)	57 (53–60)	61 (57–64)	59 (58–61)	NE > S; SE
3.1 PHCF and CHW social support activities	61 (56–66)	66 (63–69)	57 (53–60)	57 (53–61)	66 (61–71)	61 (60–63)	NE; MW > S;;SE
3.2 Population initiatives (knowledge of the PHCF)	81 (75–86)	84 (80–87)	78 (74–82)	77 (72–81)	82 (76–87)	80 (78–83)	ns
3.3 Social articulation	37 (30–44)	37 (32–42)	35 (30–40)	37 (31–42)	34 (27–41)	36 (33–39)	ns
4. CONTINUITY OF CARE	66 (64–69)	66 (64–68)	60 (58–62)	61 (59–64)	64 (61–67)	63 (62–65)	N; NE > S; SE
4.1 Routine consultations/care	82 (78–85)	81 (78–84)	74 (71–77)	80 (77–83)	81 (77–85)	79 (77–80)	SE < all regions
4.2 Maternal-child health care	86 (82–90)	88 (85–90)	83 (80–86)	83 (80–87)	86 (83–90)	85 (84–87)	ns
4.3 Routine vaccination	90 (86–95)	96 (94–98)	88 (84–91)	86 (81–90)	88 (83–93)	91 (89–93)	NE > all regions
4.4 NTCD care	89 (86–93)	86 (82–89)	82 (78–85)	83 (79–87)	85 (80–89)	84 (82–86)	ns
4.5 Home care	77 (71–83)	73 (68–78)	62 (57–67)	74 (68–79)	69 (63–75)	70 (67–72)	SE < N. NE e S
4.6 Multidisciplinary care –(NASF/FHSC)	48 (40–56)	47 (41–52)	33 (28–39)	30 (24–36)	48 (40–56)	40 (37–43)	N e NE > S e SE; MW > SE
4.7 Mental Health Care	82 (76–88)	80 (76–85)	75 (70–79)	78 (73–83)	79 (73–85)	78 (76–81)	ns
4.8 Modalities of remote patient follow-up	41 (37–45)	42 (40–45)	43 (40–45)	41 (38–44)	43 (40–47)	34 (31–36)	ns
4.9 List of priority patients	90 (84–95)	96 (93–98)	92 (89–96)	93 (89–96)	91 (86–96)	93 (92–95)	ns
4.10 Electronic request of exams/ Prescription	9 (4–14)	7 (4–10)	10 (6–13)	9 (6–13)	13 (8–18)	9 (7–11)	MW > NE
4.11 Home delivery of medication	43 (34–52)	42 (36–49)	30 (24–36)	25 (19–31)	31 (23–39)	35 (32–38)	N; NE > S; SE
INDEX (CPI)	65 (63–67)	66 (64–68)	64 (62–66)	64 (62–66)	64 (62–67)	65 (64–66)	ns
Collective dimension	64 (61–67)	66 (64–68)	62 (60–64)	60 (58–62)	62 (59–65)	63 (62–65)	NE > S
Individual dimension	65 (63–68)	64 (62–66)	65 (63–67)	69 (67–71)	66 (63–69)	65 (64–66)	S > NE
*Dunn test p < 0.05; ns – not significant

In the 'COVID-19 treatment' axis, the lowest value was observed for the availability of tests (PCR and rapid tests). The implementation of remote modalities for monitoring cases, essential in an epidemic with the characteristics of COVID-19, also obtained a value of 57. On the other hand, it is noteworthy the high score observed for the variable institutional transport and referral of critically-ill patients to the other levels of the system (92–95). The other variables reached values between 62 and 67. When comparing the regions, a greater completeness of actions, in the Covid-19 Treatment axis, is observed in the PHCFs in the South region, when compared to those in the North and Northeast. This performance stems from a greater availability of supplies and tests, as well as changes in the opening hours of the units and the creation of specific workflows for respiratory symptoms. On the other hand, the introduction of modalities such as remote monitoring and home or peridomiciliary visits was greater in the Northeast and North regions. The availability of supplies for the monitoring of cases (oximeter, O₂, infrared thermometer) was lower in the North and Northeast regions (Table 3).

The Surveillance axis attained the highest value and was also the most homogeneous one, with no differences between regions. Health education activities, which include encouraging social isolation and other preventive initiatives (hand washing, wearing masks) were carried out to a high degree and in practically all PHCFs in the Northeast and North regions. Test collection in the PHCFs attained a low value, with an important impact on surveillance actions, which may have been minimized by a higher value related to the information variable, representing the information about confirmed cases and hospitalizations of residents living in the area covered by the PHCF.

In the Social Support axis, lower values were observed in the articulation of the PHCF with other social sectors and with the organized community movements. However, important activities such as enrollment in cash transfer programs and/or basic food basket distribution were led by the PHCF, together with the Community Health Workers (CHWs). The Northeast region showed the best performance in this axis (Table 3).

The Continuity of Care axis attained an average value in the index, with emphasis on the Northeast and North regions. The actions with the lowest values were electronic prescriptions and requests for exams, inclusion of modalities of remote patient monitoring of such as telephone calls, WhatsApp messages and video calls with the NASF team (FHSC - Family Health Support Center: a multidisciplinary team consisting of physical therapists, psychologists, nutritionists, among others). On the other hand, traditional actions such as routine vaccination, care for users with chronic diseases and maternal and child health showed high values, with no differences between the regions, with the exception of routine vaccination, which was higher in the Northeast Region (Table 3).

When analyzing the dimension that articulates the practices more focused on individual care (Continuity of Care and COVID-19 Treatment), a greater value is observed in the units of the South region, when compared to those of the Northeast, and the relationship is exactly the opposite in the Collective Dimension, with the Northeast exhibiting higher scores than the South, with the Midwest region showing an intermediate pattern (Table 3).

Comparing the units showing indices above and below the median with the socioeconomic, political and health indicators, an association is observed between the units with the highest CPI and the fact that they belong to municipalities with the lowest MHDI, GDP per capita, population, percentage of votes on President Bolsonaro in the second round of the 2018 presidential election, number of hospitals, and ICU beds. On the other hand, higher FHS coverage was associated with a higher CPI (Table 4). Regarding the classification of the municipality as rural or urban, the difference in the proportions of indices above the median was significant, as 66% of the PHCFs located in rural municipalities had better index results, whereas in urban areas, the percentage was 43%. No differences were observed regarding the mortality rate, or the number of confirmed cases/100,000 inhabitants.

Table 4

Socioeconomic. demographic. political. structural and health surveillance variables: median and interquartile range (IQR) distributions and associations with CPI
Variable	CPI below median score (≤ 65)	CPI above median score (> 65)	Significant associations
Variable	Median (IQR)	Median (IQR)	p
HDIM ¹	72 (65–76)	70 (62–75)	0.0135*
HDIM - education	64 (55–70)	61 (52–68)	0.0103*
HDIM – life expectancy	83 (79–85)	82 (79–85)	0.0964
HDIM - income	71 (63–75)	69 (60–74)	0.0163*
GDP ~ ² (R$)	1,560,979 (468,057 − 8,165,793)	636,170 (178,059 − 4,040,635)	< 0.0001*
GDP per capita (R$)	25,963 (15,884 − 40,668)	22,671 (13,025–38,369)	0.0144*
Population estimates ³	62,508 (23,331 − 232,491)	30,430 (13,491 − 126,970)	< 0.0001*
% of voting in Bolsonaro ⁴	63 (38–72)	57 (33–69)	0.0028*
Hospitals and equipment ⁵
Hospitals (n)	2 (1–7)	1 (1–4)	< 0.0001*
Ventilators (n)	15 (2-122)	5 (0–56)	< 0.0001*
Hospitals with ICU ⁵
ICU - types
ICU ii Adult (n)	0 (0–1)	0 (0–1)	0.0063*
ICU ii Pediatric (n)	0 (0–0)	0 (0–0)	0.2171
ICU ii Adult Covid (n)	0 (0–1)	0 (0–1)	0.0001*
ICU ii Pediatric Covid (n)	0 (0–0)	0 (0–0)	0.4688
Total of ICU (n)	1 (0–4)	0 (0–2)	0.0001*
ICU beds ⁵
ICU beds ii Adult (n)	0 (0–19)	0(0–10)	0.0070*
ICU beds ii Pediatric (n)	0 (0–0)	0 (0–0)	0.2177
ICU beds ii Adult Covid (n)	0 (0–20)	0 (0–12)	0.0003*
ICU beds ii Pediatric Covid (n)	0 (0–0)	0 (0–0)	0.4723
Total of ICU beds (n)	8 (0–53)	0 (0–30)	0.0001*
Coverage ⁶
Family Health Strategy (%)	80 (50–100)	97 (65–100)	< 0.0001*
Primary Health Care (%)	90 (62–100)	100 (77–100)	< 0.0001*
Covid-19 – cases and deaths ⁷
Confirmed cases/100k	10,815 (7,330 − 14,136)	10,376 (6,903-14.190)	0.1946
Mortality rate	0.024 (0.018–0.032)	0.024 (0.017–0.034)	0.5553
* Mann-Whitney significant test results p < 0.05
Sources: 1. UNDP - United Nations Development; 2. IBGE—Brazilian Institute of Geography and Statistics; 3. TCU – Federal Accounting Court; 4. TSE – Superior Electoral Court; 5. CNES—National Register of Health Facilities 6. e-gestor AB—Primary Care Information System Program; 7. Wesley Cota repository: wcota/covid19br

To the best of our knowledge, this is the first national study with a representative sample of PHCFs carried out in Brazil. In the beginning of the pandemic, our group conducted a first survey, but with a convenience sample [33]. Thus, it can be said that the present study is a portrayal not only of the reorganization of Brazilian PHC after 18 months of the pandemic, but it also reflects several debates and disputes of the Brazilian health policy during the period.

The first issue to be highlighted are the deep structural deficiencies that PHC workers in Brazil have to face on a daily basis, which were once again demonstrated in our results. Although the working conditions have significantly improved in recent years, with several programs aimed at improving the PHCF structure and HR provision, the lack of structure remains a reality in several parts of the country, especially in the North and Northeast regions [34, 35], which concentrate more vulnerable populations, with less access to a structured network of health services, once again reissuing the Inverse Care Law [36].

The physical structure, represented by the number of available consultation offices, was a structural obstacle to the offer of adequate care to users at the time of the pandemic, when different workflows for symptomatic respiratory patients must be established. That was overcome by the teams’ creativity, which often created exclusive flows for this type of care in areas outside the PHCF. We may acknowledge that, despite the structural difficulties, a rapid and important change was observed in the organization of both internal and external flows, i.e., what was within the governance of the PHC teams, was carried out promptly. This reorganization of PHCF was also observed in other countries [27, 28] and occurred promptly, being one of the most common responses observed in these services.

The lack of an effective connectivity in all Brazilian PHCFs was drastically felt at this time, especially in the Northeast and North regions. Overcoming this constraint, we highlight one of the most important findings of this study, which demonstrates the strong commitment of our PHC teams to healthcare. Even without institutional resources, the professionals started using their own equipment, such as their mobile phones, to guarantee care. This contributed to a rapid change in the care processes, with the introduction of different forms of remote monitoring, both for users with COVID-19 and for those who needed regular care. A more effective national telehealth policy, with adequate financial support, such as what happened in Australia [37], would have resulted in a gain of scale related to these spontaneous initiatives by professionals, and would have made a difference in the Brazilian scenario.

The introduction of remote modalities to monitor users with COVID-19 was a worldwide practice in PHC, having been reported in the most diverse realities [38, 39]. Undeniably, this introduction will indicate a fundamental change in the type of PHC operations not only in Brazil, but also in the world. Baines et al. carried out, before the pandemic, a scope review on the obstacles and facilitators of the introduction of remote actions in PHC scenarios [40]. Among the obstacles, the lack of understanding of the purposes and effectiveness of remote consultations, the conception that only part of the users would be able to adhere to this practice, and that it should be aimed only at less complex cases were identified. It can be said that within a few months, these issues were minimized for most PHC professionals worldwide, who were rapidly forced to incorporate these tools into their daily lives. Although the changes are extensive, it is worth recalling that the implementation of remote procedures is easier in larger health units, which have good administrative and information technology support, a reality far removed from that observed in the Brazilian scenario [41].

One of the greatest difficulties faced by the PHC was, undoubtedly, to guarantee the continuity of care, which did not occur only in Brazil. Especially in the beginning of the pandemic, the focus of PHC performance was largely on the screening and care of patients with respiratory conditions [22, 38, 42, 43]. At first, elective care was significantly reduced in almost all countries; however, this had to change with the progression of the pandemic. The results found herein are in line with the world scenario, but already indicate adaptations in the work processes to maintain the continuity of care, especially for priority groups. Even though there was a reduction in their activities, the responses to the set of questions related to the continuity of care through routine actions offered in PHC and their adaptations indicate concern with the maintenance of the users' health.

Improving the capacity of the teams, their articulation with the other levels of the system, guaranteeing the coordination of care and, of course, the improvement of the infrastructure are crucial for the Brazilian PHC in order to offer continuous and quality health care. These improvements are essential, as it is very likely that PHC services will have their demand for continuous care increased, especially with an increase in the prevalence of mental health disorders and users with long-term COVID-19 [44–46].

Haldane et al (2020) [47] analyzed the first proposals made by the governments for the performance of PHC services in 14 countries, using as a reference the design by Patel (2008) [48] for the performance of PHC when facing a pandemic. Overall, the documents proposed changes in the work processes, suggesting procedures that would guarantee continuity of care and at the same time reduce the risk of contagion, both for users and professionals, whereas all of them indicated measures to control the epidemic. However, few of them emphasized surveillance actions.

The need to include surveillance actions linked to PHC services stands out in the international literature [49], recalling that the PHC model most often incorporated in the health systems of central capitalist countries is very focused on the physician, the General Practitioner, with a weak community dimension and scarce surveillance actions in the territory. From this perspective, the Brazilian FHS model that virtuously articulates these dimensions and is also supported by a multidisciplinary practice, would start from a higher level in the fight against COVID-19, even more so when it had a network of more than 43,000 FHS teams and 300,000 CHWs. Unfortunately, the totality of this power was wasted by the policy carried out by the Ministry of Health, which did not fulfill its role in policy formulation and definition [50].

The PHC teams carried out the surveillance actions that were under their governance, but the lack of tests prevented the implementation of the test, trace and isolation model to contain the pandemic. This model, associated with the social isolation measures, had positive results in some countries [51] and was identified as one of the most important pillars to combat the spread of the pandemic, before the availability of vaccines. And it could have lessened the immense impact of COVID-19 on the Brazilian population.

Brazil comprises, one could say, many, many ‘countries’, as it is a territory characterized by immense social inequality, demanding a greater role from PHC in guaranteeing care, especially for the most vulnerable populations, which requires the performance of social and intersectoral support actions. These actions, which were already important before the pandemic, took on greater centrality with the advent of COVID-19. There is no way to face the pandemic without guaranteeing decent conditions for the population survival. Despite this importance, this axis was the most fragile one among our results, especially the carrying out of intersectoral actions, demonstrating the immense challenge that is to incorporate these practices into the daily life of PHC teams. The exception was observed in the Northeast region, where social support actions such as distribution of basic food baskets and help for the population to enroll in cash transfer programs were carried out in more than half of the PHCFs.

The results also indicate different profiles in the fight against COVID-19 by the regions. Overall, greater completeness was observed regarding the variables, axes and dimensions related to collective actions in the Northeast and North regions, conveying their greater adherence to one of the main characteristics of Brazilian PHC, its community approach. These actions, in general, have greater local and municipal governability. They demand changes in the work processes, in which the key piece is the FHS through its multiprofessional characteristic and with the central presence of the CHW. On the other hand, the individual dimension is evident especially in the PHCF of the South and Southeast regions. In part, the greatest performance difficulties in the individual dimension in the North and Northeast regions originate from the lack of structural conditions, which make this performance difficult.

In a sense, these two profiles reflect the clash of political projects that have disputed the Brazilian PHC since 2016. The care model of the Family Health Strategy (FHS) has been suffering threats and setbacks that contribute to its de-characterization. Federal initiatives promote a model of individual assistance, responding to acute problems, without connections, continuity, coordination and population and territorial responsibility. The priority of the family health teams has been abolished and the presence of Community Health Workers in the teams has been reduced. Incentives for the hiring of support professionals have been extinct. The “Mais Médicos” (More Doctors) Program, which sent physicians to remote and disadvantaged areas, was discontinued, leaving hundreds of municipalities without doctors. Changes in federal funding constrain the universality of care. The commodification of PHC, the least commercial, more public, and the most efficient sector of SUS, is promoted. With a distinct pace of implementation in the country, depending on the locoregional contexts and institutions, these setbacks produce a greater diversification of care models [52, 53], as it has been clearly seen in the face of the COVID-19 pandemic in our study. It must be crystal clear that only the articulation of the individual and collective dimensions is capable of responding to the various health problems of the Brazilian population, further aggravated by the pandemic.

When we change the scale of analysis, leaving that of the regions and moving on to the municipalities, the results found also show the potential and limits of PHC. The CPI was higher precisely in the PHCF located in municipalities that would have, to begin with, greater difficulty in autonomously coping with COVID-19 (poorer, small municipalities, with rural economy, with fewer complex health services, such as hospitals and ICU beds), which certainly contributed to the reduction of health inequities. In this sense, the expanded role of the PHCF and its plasticity is reinforced, including when it provided care for users with severe conditions. And it is clear that this scenario would be even more virtuous if the effective integration of PHCFs with a network of services with the other levels of complexity were guaranteed throughout the country.

In line with the study by Xavier et al (2022) [54], which showed that the cities where Jair Bolsonaro had the most votes were also the ones that had more deaths from COVID-19 in 2021, differences were observed between the indices (CPI) of the PHCFs according to the percentage of votes for this candidate, with PHCFs above the index median being located in municipalities that were less aligned with the president’s ideas.

The study results showed the power of the PHC to face the pandemic, given the size of the network of family health teams and the diversity of agents that constitute it to perform their health surveillance and comprehensive and universal care functions.

Although it reduced the volume of its routine activities, PHC reinvented itself and faced a scenario of strong structural needs, often maximizing public resources by combining them with private ones, demonstrating once again its strong commitment to the population health. We reiterate that the FHS, with the community action in the territories, supporting and carrying out health surveillance and comprehensive care, is an effective way to contain the pandemic, but to do that, it needs more investments and technological incorporation.

It is essential to further activate the community attributes of the FHS for the control of the pandemic; strengthening the integration of the SUS services network and the association with solidarity initiatives of community organizations and intersectoral coordination to support the population in its numerous vulnerabilities; guarantee the continuity of promotion, prevention and care actions, creating new work processes in health surveillance, social and health support for vulnerable groups, in the continuity of routine care for those who need it.

The two observed performance profiles, with different emphasis on the individual and collective dimensions, convey not only the clash of political projects that dispute the Brazilian PHC since 2016, but also the structural inequalities that exist between the different regions. The Brazilian FHS project and the SUS project are civilizing projects, crucial for the construction of an egalitarian and democratic society, capable of facing not only the COVID-19 pandemic, but also the other challenges of the Brazilian health context, with protagonism and resilience

CPI – Covid-19 Primary Healthcare Index; CHW – Community Health Worker; CNES - National Register of Health Facilities; FHS - Family Health Strategy. FHSC - Family Health Support Center; GDP – Gross Domestic Product HDIM – Human Development Index at the municipal level; HR – Human Resources; ICU – Intensive Care Unit; NASF – Multidisciplinary care; NTCD – Non-transmissible Chronic Diseases; PHC – Primary Health Care; PHFC - Primary Health Care Facilities; SAMU - Mobile emergency care service; SMS – Municipal Department of Health; SUS – Brazil’s Unified Health System;

Ethics approval and consent to participate

All methods were performed in accordance with the relevant guidelines and regulations, in accordance with the Declaration of Helsinki. The Research was approved by the Ethics and Research Committee of the School of Public Health. University of Sao Paulo (FSP/USP) under reference number CAAE 31414420.8.0000.5421 and statement number 4.827.811 as of July 5th 2021. Informed consent to participate in the study was obtained from all participants

Consent for publication

Not applicable

Availability of data and materials

The datasets generated and/or analysed during the current study are not publicly available as they include particular information that was consented. but are available in aggregate data, from the corresponding author on reasonable request.

The consulted data sources are open to public access and can be reached at the following websites: IBGE—Brazilian Institute of Geography and Statistics. https://www.ibge.gov.br/estatisticas/sociais/populacao/9662-censo-demografico-2010.html?=&t=o-que-e ; DATASUS—SUS Information Technology Department. https://datasus.saude.gov.br/informacoes-de-saude-tabnet/; UNDP: United Nations Development Program; https://www.br.undp.org/content/brazil/pt/home/idh0/atlas-do-desenvolvimento-humano/atlas-dos-municipios.html; e-gestor PHC: https://egestorab.saude.gov.br/; TCU – Federal Accounting Court https://portal.tcu.gov.br/inicio/; TSE – Superior Electoral Court https://www.tse.jus.br/eleitor/estatisticas-de-eleitorado/eleitorado

Competing interests

The authors declare that they have no competing interests

Funding

Umane Foundation

Pan American Health Organization (PAHO)

Authors' contributions

AB contributed to the conception and design of the work; analysis. interpretation of data; having drafted the work and revised it. LG contributed to the conception and design of the work; analysis. interpretation of data and revision. PHSM contributed to the conception and design of the work; analysis; interpretation of data and revision. SS contributed to the analysis. interpretation of data; having substantively revised the work. LAF, MHMM, FBN and GC contributed to the conception and design of the work; analysis. interpretation of data and revision. PSC contributed to the analysis. interpretation of data and revision. MCGP contributed to the design of the work and revision.

All authors read and approved the final manuscript

Acknowledgements

A. Bousquat and L. Giovanella are Conselho Nacional de Desenvolvimento Científico e Tecnológico—CNPq fellow in research productivity

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The Brazilian PHC response to the COVID-19 pandemic: individual and collective comprehensiveness and performance profiles

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