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Article

Epidemiological Monitoring of COVID-19 in a Brazilian City: The Interface between the Economic Policies, Commercial Behavior, and Pandemic Control

by
Veronica Perius de Brito
,
Alice Mirane Malta Carrijo
,
Marcos Vinicius Teixeira Martins
and
Stefan Vilges de Oliveira
*
Faculty of Medicine, Federal University of Uberlândia, Pará Avenue, 1720, Uberlândia 38405-315, Brazil
*
Author to whom correspondence should be addressed.
World 2022, 3(2), 344-356; https://doi.org/10.3390/world3020019
Submission received: 26 April 2022 / Revised: 6 June 2022 / Accepted: 8 June 2022 / Published: 13 June 2022 / Corrected: 21 July 2022

Abstract

:
The new Coronavirus disease (COVID-19) pandemic was responsible for one of the worst public health crises in Brazil, which led to the implementation of economic policies to keep social distance. Our aim is to perform an epidemiological analysis of the COVID-19 pandemic in Uberlândia, Minas Gerais, in 2021, highlighting the impact of government commercial policies on pandemic control. This is an epidemiological, observational, and analytical study with secondary data. We constructed a regression for count data using the Poisson model. Data adherence to the regression was verified by Cameron & Trivedi and the Likelihood Ratio tests. According to the Poisson model, there was a statistically significant association (p < 0.001) between the adoption of rigid commercial interventions and the drop in deaths. Moreover, we revealed a consistency between the economic policies and the number of screening tests applied, which may have contributed to the deaths behavior. This study shows the importance of institutionalizing economic policies and their positive impacts on pandemic control; however, it raises the discussion about the serious repercussions of these measures on population vulnerability.

1. Introduction

At the end of 2019, the first cases of pneumonia of obscure origin were reported in the city of Wuhan, China. The pathogen responsible was called Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), and due to its high transmissibility and spread on a global scale, it quickly became a serious threat to public health [1]. Therefore, on 11 March 2020, the disease caused by the new coronavirus (COVID-19) was declared a pandemic by the World Health Organization (WHO) [2].
The clinical profile of the disease is quite variable, characterized by asymptomatic patients with mild symptoms, such as cough and headache, or severe conditions, marked by pneumonia, adult respiratory distress syndrome, septic shock, and death [3]. There are several risk factors associated with the severity of the infection, among which are advanced age and the presence of comorbidities, such as Systemic Arterial Hypertension, Diabetes Mellitus, obesity, cardiovascular diseases, lung disease, and chronic renal failure, among others [4].
Due to COVID-19, Brazil faced one of the worst public health crises in its history, with serious political, economic, and social repercussions [5]. It is believed that the genesis of this sanitary chaos lies in the country’s significant social inequality, marked by populations living in precarious situations of housing, hygiene, and access to water [5] associated with the limited capacity of health services and insufficient government strategies to control viral dissemination [6].
The scenario of the city of Uberlândia, located in the Minas Gerais triangle, did not differ from the national chaos, with massive infection of the population, frightening progression in the number of fatal victims, as well as overcrowding of the city’s health system [7,8]. Faced with this, it became necessary not only to release campaigns aimed at the use of personal protective masks and hygiene measures but also to implement government decrees to stop commercial activities in the municipality as a way of maintaining social distance [8].
However, the high economic impact of adopting these measures challenged their compliance. After all, Brazilian municipalities have a large population contingent in a situation of poverty, which, without institutional plans of minimum income and protection to work, reached a situation of extreme vulnerability, hindering their survival and dignity [9]. Thus, a great impasse arose between the maintenance of commercial closure for viral containment and the need for flexibility aimed at promoting the economic movement of the city and guaranteeing a source of income for countless workers.
A more promising future began to be traced when, in a joint action of several nations, research was carried out with the aim of knowing the biomolecular aspects of SARS-CoV-2 and, from that, safe, effective, and emergency vaccines were created by regulatory agencies [10,11]. From this, the vaccine has become a potent weapon in the fight against the pandemic, relieving the health condition of cities and mitigating the important economic implications of social isolation [11].
This fluctuating epidemiological conjuncture meant that the decrees of the city of Uberlândia regarding commercial operation were reviewed every two weeks by the Municipal Committee to Combat COVID-19, which evaluated the health context of the city and decided on which activities could operate [12]. This highlights the importance of Health Surveillance in determining the dynamics of the disease in each municipality and, in this way, guiding the decisions made by the management of the various services [8].
In view of this, the present study aims to analyze the epidemiological profile of COVID-19 in the municipality of Uberlândia during the year 2021, highlighting the impact of municipal decrees of commercial opening and closing on the number of cases and deaths recorded in the city.

2. Materials and Methods

This is an epidemiological, observational, and analytical study, using secondary data, of the reported cases of COVID-19 to the Municipal Health Department of Uberlândia (MG). These records were obtained through the Uberlândia Municipal Information Bulletin. Notifications from 1 January 2021, to 31 December 2021, were analyzed.
The municipality of Uberlândia is located in the southeast region of Brazil, west of the state capital, Belo Horizonte [13]. It is the second-largest city in Minas Gerais, considered the second most populous state in Brazil [14]. According to the Brazilian Institute of Geography and Statistics, the municipality has a population of 699,097 inhabitants [13] with a population density of 146.78 inhab/km2 and a Municipal Human Development Index of 0.789 [13]. The representative map of the study site is represented in Figure 1.
The variables analyzed were: the number of confirmed cases and deaths, number of hospitalizations in ICUs and wards, number of screening tests performed and hospitalizations by sex (male and female) and by age group (0–5, 6–12, 13–39, 40–59, 60–69, 70–79, and 80 years and over).
To assess the impact of the opening and closing of commercial establishments, all decrees of the Municipal Committee to Combat COVID-19 of the Municipality of Uberlândia established during the study period were used. In these, the three possible phases of the municipal plan for the operation of economic activities are defined. The activities authorized in each of these phases are specified below:
  • Rigid: Agriculture, livestock, and related areas services; manufacturing of food and beverage products; food services; financial services (banking and insurance); production chain and essential accessory activities; construction; factories; energy; steel industry; health; communication and press; transport; vehicles; post offices; water and sewage treatment; hotels; legal activities; higher education and public transport.
  • Intermediate: Activities of the rigid phase; recreation and leisure activities; rent; curricular and extracurricular teaching; activities related to cultural and environmental heritage; travel agency; sports activities and social clubs; publicity; professional, scientific, and technical activities; sales representatives; photographic activities; beauty and aesthetic salons; jewelry and costume jewelry; driver training; duty-free stores; design and decoration; books and stationery; agricultural products; sporting goods, electronic games, weapons, and fireworks; antiques; department and varieties; other ancillary activities.
  • Flexible: Activities of the rigid and intermediate phases; events; recreation and leisure activities; movie theaters; other personal service activities.
The periods of the year 2021 that the city remained in each of these phases are represented in Figure 2.
For the tabulation, processing, and conduction of statistical analyses, Microsoft Office Excel and RStudio software were used. After conditioning the data, first, the descriptive statistics of the data, measures of central tendency, and confidence intervals were analyzed, considering a 95% confidence value. To analyze possible temporal variations, Student’s T statistical tests were used for independent samples and Mann–Whitney U tests were used in cases where the assumptions for parametric tests were not met.
In a second moment, a regression was carried out for counting data, considering confirmed deaths as the dependent variable and the other aforementioned parameters as independent variables. To verify the data adherence to Poisson regression or negative Binomial, the Cameron & Trivedi [15] test and the Likelihood Ratio test were used, considering 95% confidence.
The Poisson and Negative Binomial models are part of what is known as regression models for count data. In this type of model, the objective is to understand the behavior of a specific dependent, quantitative, discrete, non-negative variable, based on a set of independent variables, considering a certain exposure, which in this article was of a temporal nature, defined in days [16].
Finally, in order to better understand the impact of screening tests on mortality, a paired regression analysis was conducted considering the stratification of notifications according to the phases of the municipal plan.
The study described does not require analysis and approval by the Research Ethics Committee as it is secondary, domain and publicly accessible data. All data used are available for public access and use in the Daily Municipal Bulletin published by the Municipality of Uberlândia and do not allow the identification of patients, being in accordance with the Resolution nº 466/2012 of the National Health Council that establishes norms and regulatory guidelines for research involving human beings [17].

3. Results

3.1. Behavior of Cases and Deaths

The behavior of both cases (p-value = 0.0012) and deaths (p-value = 0.0104) daily, for the analyzed period, showed an important downward trend. Figure 3 shows the distribution of records according to the notification date.

3.2. Profile of Hospitalized Individuals

As for the sex of hospitalized individuals, there was greater male participation. With regard to age, there is a predominance of age groups between 40 and 59 years, followed by those between 60 and 69. Confidence intervals and mean daily notification values according to the parameters analyzed in this study can be observed in Table 1.

3.3. Selecting The Regression Model for Multivariate Analysis of Deaths

As an initial stage of the multivariate analysis process, the characterization of the distribution of daily COVID-19 death counts was carried out, aiming to find evidence of the phenomenon of data overdispersion, which would justify the choice of the negative binomial model, given the better adherence to the data in these contexts, when compared to the Poisson model. In Figure 4, it is possible to observe the histogram referring to the number of confirmed daily deaths from COVID-19.
The visual analysis of the aforementioned histogram does not seem to show the presence of an important dispersion in the distribution of the dependent variable. So, to statistically evaluate this characteristic, the test of Cameron & Trivedi [15] was used, which did not show evidence of overdispersion for the data (p-value = 0.6235).
Furthermore, to ensure the best suitability of the Poisson model, when compared to the negative binomial, preliminary versions were built for the two regression models, which were submitted to the Likelihood Ratio test, with no differences being observed in their predictive capabilities. Thus, considering the results of the two tests described, the Poisson model was chosen. More information about the results obtained through the Likelihood Ratio test can be seen in Table 2.

3.4. Applying the Poisson Model

The generated regression model was considered satisfactory for the study context, according to the indicators specified below. The generated model parameters, as well as coefficient values, significance levels, and efficiency indicators, can be seen in Table 3.

3.5. Applying Univariate Regressions to Correlate Screening Tests and Deaths

For a better understanding of the effects of performing screening tests on the number of deaths, univariate regressions were applied, considering the stratification of data according to the applied phases of the municipal plan. The behavior shown in the above procedure can be seen in Figure 5, where the lines correspond to the regressions obtained and the points to the data dispersion.

4. Discussion

The pandemic caused by SARS-CoV-2 has become a global threat resulting in increasing numbers of infected people and deaths in a short period of time [1]. Despite little knowledge about the characteristics of the virus and the behavior of the disease, preliminary studies and investment of resources in scientific research supported measures adopted by the WHO and other governmental spheres to contain viral spread [1,12,18,19,20].
Faced with this scenario, the municipality of Uberlândia, on 27 February 2020, created the Municipal Committee to Combat COVID-19 in order to implement preventive actions for the public health of the city [19]. However, even in the face of these preventive measures, the first quarter of 2021 stood out in relation to the large number of new daily cases of the disease, which culminated in numerous fatal victims [21]. This dramatic phase may have been characterized by the massive and simultaneous infection of the population which, consequently, culminated in the overcrowding of the Unified Health System (SUS) and, in turn, in the lack of beds and health care [7,8].
It is worth mentioning that the state of Minas Gerais was among the 10 federative units in the country with the highest rates of contamination [22]. Findings in the literature demonstrate a possible ineffectiveness of social isolation measures in some regions of Minas Gerais, such as the Jequitinhonha and Norte de Minas mesoregions, where economically disadvantaged people are more likely to live in housing with a high number of individuals, which, therefore, favor the risk of infection [23]. In addition to this social vulnerability, other factors, such as those of an economic and climatic nature, as well as the flow of transport, contribute to the understanding of the spread of the virus in this state [24].
Nationally, this mass contamination, in the first quarter of 2021, called the second epidemic wave, placed Brazil in second place in the ranking of countries with the highest numbers of cases and deaths from COVID-19 in the world [25]. This fact can be understood by the harm caused by the premature relaxation of measures to combat the disease [26] and by the mutations of SARS-CoV-2 for immune evasion [27]. When extending the analysis to the rest of the South American countries, we can also see a large contamination rate associated with high mortality, a scenario that can be explained by the socioeconomic conditions in this region. After all, social vulnerability is considered a central aspect in the spread of the disease, especially the level of socioeconomic development and infrastructure of the cities that can be responsible for satisfactory results, or not, in coping with the pandemic [28].
However, when analyzing the entire period, a downward trend is observed with a statistically significant variation in the number of cases (p-value = 0.0012) and deaths (p-value = 0.0104) by COVID-19. Among the hypotheses that motivated this reduction, emphasis is given to vaccination, which is considered essential for the prevention of morbidity and mortality, especially in a scenario where there are no effective prophylactic medications or treatment [29].
In Uberlândia, vaccination against COVID-19 started on 3 February 2021, and initially included elderly people living in long-stay institutions, elderly people over 85 years of age, and health professionals [30]. Subsequently, the campaign was extended to priority groups and the general population in descending order of age, according to the guidelines of the national vaccination plan [30,31]. At the end of the analyzed period, a total of 1,259,303 doses were administered, including the first dose, second dose, single dose, and booster dose [30]. This amount includes 79.3% of the population of Uberlândia vaccinated with two doses or a single dose.
Discussions about the effectiveness of vaccines are complex, especially in the case of the COVID-19 pandemic. This is because the development of the vaccine against the SARS-CoV-2 virus was carried out concurrently with the understanding of the pathogen itself and under a period of great political repercussions [29]. However, it is worth mentioning the reduction in the number of cases and deaths from the disease as vaccination advances in the city, a fact that highlights the role of the vaccine in controlling this infection, as well as in reducing mortality [29].
As it is an RNA genome virus, mutations are natural replication events that can change the way SARS-CoV-2 behaves in infections. In Brazil, cases of COVID-19 have been identified by different variants, each of which differs in terms of transmissibility, virulence, risk of reinfection, and resistance to neutralizing antibodies [32], a fact that implies the behavior of the disease during the period of time in a given region. In this municipality, the trend of a statistically significant decrease in the number of cases and deaths may have been influenced not only by vaccination but also by the circulation of a variant with lower transmissibility and pathogenicity.
Among the measures instituted to contain the viral spread in this city, the paralysis of commercial activities as a way of maintaining social distance stands out [20]. During most of 2021, the municipality adopted the intermediate phase, with the exception of March, which included the rigid phase, and October, November, and December, which was in the flexible phase with the greater opening of commercial establishments [12].
A previous study highlighted the relationship between the degree of commercial openness and the increase in the moving average of confirmed cases and deaths from the disease [8]. This association is still plausible since the intermediate phase of the municipal plan for the operation of economic activities concentrates the greatest dispersion of deaths from COVID-19 when compared to the rigid and flexible phases. Furthermore, the rigid phase adopted during the month of March may have contributed to the reduction in infection and deaths in the subsequent period, as it is inferred that it reduced contact between people, one of the forms of viral propagation [1].
This association is also confirmed in the Poisson regression model, which used deaths as an estimated dependent variable and showed statistical significance (p < 0.001) with the phases of the commercial opening plan in this municipality. This behavior reinforces the discussion in the literature about the effectiveness of social distancing measures to control the pandemic and prevent the collapse of local health systems [8].
However, the economic impact caused by the adoption of these commercial closure measures makes the discussion complex and controversial since it highlights the vulnerability of a population contingent in a situation of poverty without institutional plans for minimum income and labor protection [9]. This issue is a topic of national debate, as the stoppage of commercial activities has direct consequences on the quality of life of the population of underdeveloped or developing countries [8].
The determination of the commercial closure by the Brazilian government affected informal and formal workers, with the most affected sectors being restaurants, tourism, and transportation. It is estimated that the Gross Domestic Product projection during the pandemic was negative, around 8%, due to the fall in industrial production, trade sales, and the volume of services rendered. It is believed that economic activity was maintained mainly by agricultural and livestock production, despite the generalized drop in commodity prices. Furthermore, it is estimated that, in this period, 60% of small business owners had their credit applications denied by banks due to the lack of proof of payment guarantees [33].
In order to help the unemployed and informal workers, the Brazilian government launched a policy called Emergency Support, which corresponds to a benefit of approximately $125 a month to contribute to individual and family expenses. There were an estimated 70 million requests during the pandemic, which means that about 1 in 3 Brazilians made the request [33]. Thus, the need for periods of flexibility is discussed in order to guarantee a source of income and economic movement [8], a scenario in which vaccination is highlighted as an alternative to alleviate the health condition of cities [11].
Unlike the phases of the municipal plan, the Poisson model generated showed that the stratification of the number of hospitalizations by sex does not seem to have a significant impact on the number of registered daily deaths. However, there is a quantitative predominance of males among hospitalized individuals. This finding reiterates data from recent studies that show that the severity of COVID-19 has a gender sensitivity, that is, it affects men and women differently, with a tendency to more severe clinical conditions among men [34,35].
Several theories have emerged in order to explain the pathophysiological mechanisms responsible for this sensitivity. Among them, there is a higher expression and activity of the Angiotensin II converting enzyme (ACE II) in men, considered a gateway for the virus to enter the human body [34,35]. Moreover, androgen receptors (AR) seem to play a key role in the transcription of transmembrane serine protease II (TMPRSS2), which is essential for viral dissemination throughout the body; therefore, due to the greater production of dihydrotestosterone in men, there is greater expression and activation of RA and, consequently, transcription of TMPRSS2 [34,35].
In addition, it should be noted that both the cell-mediated and humoral immune responses are more vigorous among females due to estrogenic action, that is, it is believed that women have a stronger immune system to fight infection [35]. Still, the behavioral difference between the genders also seems to play a relevant role, after all, there is a greater record of smokers and patients with chronic comorbidities, such as Systemic Arterial Hypertension, among men, further increasing their vulnerability to a more serious infection requiring treatment hospitalization [35].
Regarding the age group of hospitalized patients, emphasis is given to individuals between 40 and 59 years old, followed by those between 60 and 69 years old. This scenario can be explained by the configuration of age as an important predictor of mortality, as well as a risk factor for more severe clinical conditions and unfavorable outcomes [35,36]. The genesis of this susceptibility is multifactorial and involves the senile weakening of the immune system, increased levels of pro-inflammatory cytokines with advancing age, higher viral load, and a greater number of associated comorbidities [37]. The regression model used reinforces that this stratification of hospitalizations by age group has a significant statistical impact on the number of deaths reported in this city.
As for the place of admission, it was found that the difference in the average daily rate between admissions to the Infirmary and the ICU was slight. This can be explained by the prevalence of hospitalizations among patients with risk factors and chronic comorbidities, such as advanced age, cardiovascular diseases, and diabetes, among others [38]. Thus, these individuals are more likely to progress to serious complications involving multiple organ dysfunction and, consequently, require care in intensive care units [38]. It is worth noting that in relation to the type of hospitalization, the regression model used shows a significant statistical impact (p < 0.05) in the reduction in registered deaths.
Furthermore, the natural history of hospitalizations for COVID-19 often leads to the development of renal failure, liver dysfunction, alteration of the coagulation system, sepsis, and acute respiratory failure. After all, it is a multisystem disease associated with an uncontrolled immune response [38,39]. Thus, many of these patients previously admitted to the Infirmary need to be referred to an ICU room in order to receive adequate cardiovascular and ventilatory support [38].
Finally, the evaluation of the effects of performing screening tests on the number of deaths considering the phases of the municipal plan after applying univariate regressions (Figure 5) revealed consistency between the actions taken by the government, the number of tests applied, and the subsequent deaths. This can be seen by observing the predominantly decreasing curves during the Intermediate and Rigid phases of the plan, that is, during these periods, the increase in the number of tests performed was accompanied by a reduction in the number of deaths.
These findings seem to reveal the positive impact between the adoption of a scenario with less commercial openness by the government and the number of tests carried out, that is, the municipal risk communication strategy based on more rigid interventions seems to have been effective in stimulating universal testing, a fact that conditions an early search for medical support. Thus, there is a favorable prognosis since COVID-19, like many other infections, seems to be more susceptible to therapy in its early stages, with decreasing therapeutic responsiveness in its advanced stages, especially after hospitalization [40]. In addition, early diagnosis leads to immediate quarantine, reducing viral spread, increasing contagion, and, consequently, the possibility of deaths [40].
In this context, the search for testing to confirm the diagnosis of COVID-19 overloaded not only the public health sector but also the private sector. Due to the government’s difficulties in offering tests to the entire population and in the face of risk communication, individuals resorted to private laboratories, paying for the exams, in order to obtain the result confirming the disease or not [41].
Still, the drop in the number of deaths observed in these phases, especially in the rigid one, seems to point to the effectiveness of the municipal plan in reducing interpersonal contact and, therefore, controlling viral dissemination, mass contamination, and its fatal outcomes [1]. This scenario reiterates the importance of social distancing measures institutionalized by the government for the pandemic contingency; however, once again, it awakens the discussion about the complex paradox between the imposition of commercial closure and the need for economic movement to guarantee a minimum income and protection of the population against extreme social vulnerability [8].
Within the limitations of the study, the possible underreporting of the number of cases and deaths that occurred in the period is highlighted, since secondary data was used. Still, there may have been incomplete/incorrect filling of information by health institutions.

5. Conclusions

The present study reiterates the COVID-19 pandemic as one of the worst public health crises with social, economic, and political consequences. This chaos was also present in the Minas Gerais city of Uberlândia, characterized by periods of massive and simultaneous infection of the population, overcrowding of the health system, and increasing numbers of fatal victims. Among the measures instituted by the government in order to contain the viral spread, special attention was given to the interface generated between the stoppage of commercial activities and the effective impact on the behavior of the disease in the city.
In the analyzed period, there was a downward trend with a statistically significant variation in the number of cases and deaths from the disease in question. This reduction was attributed to the vaccination of the population, the possible lower transmissibility and pathogenicity of the variant of the virus circulating in the region at the time, and even the intermediate and rigid phases of commercial opening adopted by the local government. The latter presents statistical significance in relation to the daily deaths recorded, according to the Poisson regression model used for data analysis.
These findings underscore the importance of social distancing measures, although they represent complex decisions given their repercussions on the population’s income, as well as on the movement of the economy. Furthermore, it is evident that understanding the epidemiological profile of the disease in the city combined with the outcomes in people’s health can support future preventive actions in the field of municipal public health.

Author Contributions

Conceptualization, V.P.d.B., A.M.M.C. and S.V.d.O.; methodology, M.V.T.M., S.V.d.O. and V.P.d.B.; software, M.V.T.M.; validation, V.P.d.B., A.M.M.C., M.V.T.M. and S.V.d.O.; formal analysis, M.V.T.M. and A.M.M.C.; investigation, V.P.d.B. and A.M.M.C.; resources, S.V.d.O.; data curation, M.V.T.M., S.V.d.O. and V.P.d.B.; writing—original draft preparation, V.P.d.B., A.M.M.C., M.V.T.M. and S.V.d.O.; writing—review and editing, V.P.d.B., A.M.M.C., M.V.T.M. and S.V.d.O.; visualization, S.V.d.O. and M.V.T.M.; supervision, S.V.d.O.; project administration, S.V.d.O.; funding acquisition, none. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Informed Consent Statement

Patient consent was waived because all data used are available for public access and do not allow the identification of patients, being in accordance with the Resolution nº 466/2012 of the National Health Council that establishes norms and regulatory guidelines for research involving human beings.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Map indicating the study location.
Figure 1. Map indicating the study location.
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Figure 2. Municipal Plan Stages for the functioning of economic activities at Uberlândia.
Figure 2. Municipal Plan Stages for the functioning of economic activities at Uberlândia.
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Figure 3. Distribution of deaths and registered cases according to the date of notification to the Municipal Health Department of Uberlândia (MG).
Figure 3. Distribution of deaths and registered cases according to the date of notification to the Municipal Health Department of Uberlândia (MG).
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Figure 4. Histogram of deaths due to COVID-19 reported to the Municipal Health Department of Uberlândia.
Figure 4. Histogram of deaths due to COVID-19 reported to the Municipal Health Department of Uberlândia.
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Figure 5. Behavior of deaths by COVID-19 notified to the Municipal Health Department of Uberlândia (MG), according to phases of the municipal plan and screening tests performed.
Figure 5. Behavior of deaths by COVID-19 notified to the Municipal Health Department of Uberlândia (MG), according to phases of the municipal plan and screening tests performed.
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Table 1. Distribution of COVID-19 notifications to the Municipal Health Department of Uberlândia (MG), according to the parameters of the present study.
Table 1. Distribution of COVID-19 notifications to the Municipal Health Department of Uberlândia (MG), according to the parameters of the present study.
VariableSpecificationTotalDaily AverageCI (95%)
Confirmed cases-86,585237.22±15.49
Confirmed deaths-24506.71±0.68
HospitalizationsICU52,997145.20±9.51
Nursery65,963180.72±13.57
Tests-365,5121001.40±53.84
SexMale68,518187.72±12.74
Female50,500138.36±10.30
Age0–518865.17±0.41
6–124971.36±0.13
13–3917,20047.12±3.36
40–5946,106126.32±9.29
60–6924,44066.96±5.83
70–7917,39247.65±3.37
80+11,52631.58±2.18
Phases of the municipal planFlexible77 *--
Intermediary244 *--
Rigid44 *--
* Number of days in 2021 that the city remained in the respective phase of the Municipal Plan.
Table 2. Likelihood Ratio Test for Poisson and negative binomial models regarding COVID-19 notifications to the Municipal Health Department of Uberlândia (MG).
Table 2. Likelihood Ratio Test for Poisson and negative binomial models regarding COVID-19 notifications to the Municipal Health Department of Uberlândia (MG).
ModelsDegrees of FreedomLogLikChi-Squarep-Value
Poisson16−750.43
Negative binomial17−750.440.00980.9212
Table 3. Poisson model data referring to COVID-19 notifications to the Municipal Health Department of Uberlândia (MG).
Table 3. Poisson model data referring to COVID-19 notifications to the Municipal Health Department of Uberlândia (MG).
ParameterStateCoefficient
Intercept-−0.5421 ***
(0.1403)
Phases of the municipal planIntermediary1.1016 ***
(0.1735)
Rigid0.9978 ***
(0.2308)
Confirmed cases-0.0001
Type of hospitalization (0.0004)
ICU−0.0133
(0.0075)
Nursery−0.0149 *
(0.0076)
Screening tests performed-−0.0001 **
(0.0000)
SexMale0.0119
(0.0064)
Female0.0092
(0.0066)
Age0–5−0.0020
(0.0084)
6–120.0110
(0.0169)
13–390.0138 **
(0.0053)
40–590.0032
(0.0040)
60–690.0103 *
(0.0046)
70–790.0080
(0.0043)
80 or more0.0034
(0.0051)
IndicatorsValues
N365
AIC1532.8649
BIC1595.2633
*** p < 0.001; ** p < 0.01; * p < 0.05.
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de Brito, V.P.; Carrijo, A.M.M.; Martins, M.V.T.; de Oliveira, S.V. Epidemiological Monitoring of COVID-19 in a Brazilian City: The Interface between the Economic Policies, Commercial Behavior, and Pandemic Control. World 2022, 3, 344-356. https://doi.org/10.3390/world3020019

AMA Style

de Brito VP, Carrijo AMM, Martins MVT, de Oliveira SV. Epidemiological Monitoring of COVID-19 in a Brazilian City: The Interface between the Economic Policies, Commercial Behavior, and Pandemic Control. World. 2022; 3(2):344-356. https://doi.org/10.3390/world3020019

Chicago/Turabian Style

de Brito, Veronica Perius, Alice Mirane Malta Carrijo, Marcos Vinicius Teixeira Martins, and Stefan Vilges de Oliveira. 2022. "Epidemiological Monitoring of COVID-19 in a Brazilian City: The Interface between the Economic Policies, Commercial Behavior, and Pandemic Control" World 3, no. 2: 344-356. https://doi.org/10.3390/world3020019

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