COVID-19 was first detected in Brazil on March 1, 2020, making it the first Latin American country to report a case of the novel coronavirus. Since then, the number of infections has risen drastically, reaching approximately 38 million cases by May 11, 2025. Meanwhile, the first local death due to the disease was reported in March 19, 2020. Four years later, the number of fatal cases had surpassed 700,000. The highest COVID-19 death toll in Latin America With a population of more than 211 million inhabitants as of 2023, Brazil is the most populated country in Latin America. This nation is also among the most affected by COVID-19 in number of deaths, not only within the Latin American region, but also worldwide, just behind the United States. These figures have raised a debate on how the Brazilian government has dealt with the pandemic. In fact, according to a study carried out in May 2021, more than half of Brazilians surveyed disapproved of the way in which former president Jair Bolsonaro had been dealing with the health crisis. In comparison, a third of respondents had a similar opinion about the Ministry of Health. Brazil’s COVID-19 vaccination campaign rollout Brazil’s vaccination campaign started at the beginning of 2021, when a nurse from São Paulo became the first person in the country to get vaccinated against the disease. A few years later, roughly 88 percent of the Brazilian population had received at least one vaccine dose, while around 81 percent had already completed the basic immunization scheme. With more than 485.2 million vaccines administered as of March 2023, Brazil was the fourth country with the most administered doses of the COVID-19 vaccine globally, after China, India, and the United States.Find the most up-to-date information about the coronavirus pandemic in the world under Statista’s COVID-19 facts and figures site.

A preferência eleitoral por Bolsonaro no 1º turno de 2018 por estado, mostra-se um forte valor preditivo da quantidade de mortes por COVID-19, excesso de mortes por 100000 e intensidade na redução do crescimento populacional brasileiro no 1º trimestre de 2021

The coronavirus pandemic is the biggest cause of mortality in Brazil in 2021, according to DATASUS, 21.42% of patients admitted to any hospital, whether CTI or not, die due to this infection. Being caused by a respiratory virus, where transmission only occurs if, sine qua non, contact occurs between two or more human beings and exchange of saliva and sputum particles between them. It is clear and clear that, among the few but effective measures to reduce contagion and, consequently, deaths, is the orientation to use facial protection and to reduce or, if possible, end contact between people who have not been vaccinated or who have not had COVID in the last 6 months. It is also notorious that these basic and scientifically proven health concepts are not presented with a concept of truth for the President of our country, and probably for a large part of his supporters, but how can this be demonstrated? How much does example and information matter in a global pandemic that is known to be transmissible through contact and agglomeration? It is these answers that we seek through the exposure and comparison between numerical data from the states of the federation and their relationship with the election of the 1st round of 2018 and the demographic data of mortality, birth rate, excess of deaths, mortality by COVID and others in the first quarter of 2021

A pandemia de coronavirus é a maior causa de mortalidade no Brasil em 2021. Segundo o painel de registro civil brasileiro, somente de janeiro a março de 2021 foram registrados 441007 óbitos, enquanto no mesmo período de 2019 este número foi de 297952, um excesso de mortes de 143055, o que corresponde a um aumento de 48%, muito além do esperado de +- 5%. Ainda segundo o DATASUS, 21,42% dos pacientes internados com diagnóstico de COVID-19, sendo em CTI ou não, veem a falecer devido a esta infecção. A COVID-19, infecção sistêmica causada por um virus respiratório, onde a transmissão somente ocorre se , sine qua non, ocorrer contato entre dois ou mais seres humanos e troca de partículas de saliva e escarro entre eles, por via aérea ou por mucosas e superfícies contaminadas, É nítido e claro, que entre as poucas, mas eficazes medidas para diminuição do contágio e consequentemente das mortes, estão orientações de comportamento, como usar proteção facial e diminuir, ou se possível, findar o contato entre pessoas não vacinadas ou que não tiveram COVID nos últimos 6 meses. Estes conceitos sanitários básicos e cientificamente comprovados não são brindados como conceito de verdade para o Presidente de nosso país, e provavelmente para uma grande parte de seus apoiadores e eleitores, mas como demonstrar isso? Quanto se combate um vírus desconhecido e sem tratamento curativo eficaz, o exemplo, a informação padronizada e as práticas de distanciamento social são primordiais e essenciais para o êxito no achatamento da curva de transmissão e na proteção dos indivíduos mais predispostos a complicações e principalmente a morte ?

São estas respostas que procuramos através da exposição e comparação entre dados numéricos dos estados da federação e suas relações com a eleição do 1º turno de 2018 e os dados demográficos de mortalidade, natalidade, excesso de mortes, mortalidade por COVID e outros no 1º trimestre de 2021 Este banco de dados mostra com dados do registro civil, CONASS, MS e TSE que existe estreita relação ( estatisticamente significante p=0,000845 e RR=725) entre o excesso de mortes e sua intensidade com a votação no candidato 17 - Bolsonaro no 1º turno da eleição de 2018. Dos 15 piores estados em se tratando de excesso de óbitos por 100000 entre 1ºtrimestre de 2021/2019, 100% deles Bolsonaro foi o vencedor do pleito e em somente 2 não alcançou mais de 52,5% dos votos.

Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

The difficulties of death figures

This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

Where are these numbers coming from?

The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

Brazil recorded 16779136 Coronavirus Recovered since the epidemic began, according to the World Health Organization (WHO). In addition, Brazil reported 617271 Coronavirus Deaths. This dataset includes a chart with historical data for Brazil Coronavirus Recovered.

In April 2021, Brazil reached a new record of deaths due to COVID-19 in a day, with more than 4,200 thousand fatalities reported within 24 hours. That same month, the country's gross domestic product (GDP) was expected to increase by 3.17 percent during the year, down from a growth of nearly 3.5 percent forecast two months earlier. Since then, expectations have improved, with a forecast growth of 5.27 percent as of the third week of July.By December 2020, Brazil's GDP was forecast to decrease by 4.4 percent during 2020, an improvement in comparison to the 6.5 percent decrease forecast by the beginning of July. This figure, which had remained stable at a 2.3 percent forecast growth during the first months of the year, decreased for five consecutive months amidst the outbreak of COVID-19 in Brazil. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Abstract Objective To compare death rates by COVID-19 between pregnant or postpartum and nonpregnant women during the first and second waves of the Brazilian pandemic. Methods In the present population-based evaluation data from the Sistema de Informação da Vigilância Epidemiológica da Gripe (SIVEP-Gripe, in the Portuguese acronym), we included women with c (ARDS) by COVID-19: 47,768 in 2020 (4,853 obstetric versus 42,915 nonobstetric) and 66,689 in 2021 (5,208 obstetric versus 61,481 nonobstetric) and estimated the frequency of in-hospital death. Results We identified 377 maternal deaths in 2020 (first wave) and 804 in 2021 (second wave). The death rate increased 2.0-fold for the obstetric (7.7 to 15.4%) and 1.6-fold for the nonobstetric groups (13.9 to 22.9%) from 2020 to 2021 (odds ratio [OR]: 0.52; 95% confidence interval [CI]: 0.47–0.58 in 2020 and OR: 0.61; 95%CI: 0.56– 0.66 in 2021; p < 0.05). In women with comorbidities, the death rate increased 1.7-fold (13.3 to 23.3%) and 1.4-fold (22.8 to 31.4%) in the obstetric and nonobstetric groups, respectively (OR: 0.52; 95%CI: 0.44–0.61 in 2020 to OR: 0.66; 95%CI: 0.59–0.73 in 2021; p

How did Brazil become a global epicenter of the outbreak? After seeming to ease, is the virus making a comeback?

A world leader in infections and deaths.

Latin America became an epicenter of the coronavirus pandemic in May, driven by Brazil’s ballooning caseload. Ten months after its first known case, Brazil has had more than 7.9 million cases and over 200,000 deaths.

In early June, Brazil began averaging about 1,000 deaths per day from Covid-19, joining the United States — and later India — as the countries with the world’s largest death tolls.

This dataset contains information about COVID-19 in Brazil extracted on the date 16/06/2021. It is the most updated dataset available about Covid in Brazil

Features:

🔍 date: date that the data was collected. format YYYY-MM-DD.
🔍 state: Abbreviation for States. Example: SP
🔍 city: Name of the city (if the value is NaN, they are referring to the State, not the city)
🔍 place_type: Can be City or State
🔍 order_for_place: Number that identifies the registering order for this location. The line that refers to the first log is going to be shown as 1, and the following information will start the count as an index.
🔍 is_last: Show if the line was the last update from that place, can be True or False
🔍 city_ibge_code: IBGE Code from the location
🔍confirmed: Number of confirmed cases.
🔍deaths: Number of deaths.
🔍estimated_population: Estimated population for this city/state in 2020. Data from IBGE
🔍estimated_population_2019: Estimated population for this city/state in 2019. Data from IBGE.
🔍confirmed_per_100k_inhabitants: Number of confirmed cases per 100.000 habitants (based on estimated_population).
🔍death_rate: Death rate (deaths / confirmed cases).

Acknowledgements

This dataset was downloaded from the URL bello. Thanks, Brasil.IO! Their main goal is to make all Brazilian data available to the public DATASET URL: https://brasil.io/dataset/covid19/files/ Cities map file https://geoftp.ibge.gov.br/organizacao_do_territorio/malhas_territoriais/malhas_municipais/municipio_2020/Brasil/BR/

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City level open access data from 26 States and the Federal District and from the Brazilian Institute of Geography and Statistics (IBGE) [20], the Department of Informatics of Brazilian Public Health System – DATASUS, Ministry of Health, the Brazilian Agricultural Research Corporation (Embrapa) and from Brazil.io. Data from all 5,570 cities in Brazil were included in the analysis. COVID-19 data included cases and deaths reported between February 26th, 2020 and February 4th, 2021. The following outcomes were computed: a) days between the first case in Brazil until the first case in the city; b) days between the first case in the city until the day when 1,000 cases were reported; and c) days between the first death in city until the day when 50 deaths inhabitants were reported. Descriptive analyses were performed on the following: proportion of cities reaching 1,000 cases; number of cases at three, six, nine and 12 months after first case; cities reporting at least one COVID-19 related death; number of COVID-19 related deaths at three, six, nine and 12 months after first death in the country. All incidence data is adjusted for 100,000 inhabitants.The following covariates were included: a) geographic region where the city is located (Midwest, North, Northeast, Southeast and South), metropolitan city (no/yes) and urban or rural; b) social and environmental city characteristics [total area (Km2), urban area (Km2), population size (inhabitants), population living within urban area (inhabitants), population older than 60 years (%), indigenous population (%), black population (%), illiterate older than 25 years (%) and city in extreme poverty (no/yes)]; c) housing conditions [household with density >2 per dormitory (%), household with garbage collection (%), household connected to the water supply system (%) and household connected to the sewer system (%)]; d) job characteristics [commerce (%) and informal workers (%)]; e) socioeconomic and inequalities characteristics [GINI index; income per capita; poor or extremely poor (%) and households in informal urban settlements (%)]; f) health services access and coverage [number of National Public Health System (SUS) physicians per inhabitants (100,000 inhabitants), number of SUS nurses per inhabitants (100,000 inhabitants), number of intensive care units or ICU per inhabitants (100,000 inhabitants). All health services access and coverage variables were standardized using z-scores, combined into one single variable categorized into tertiles.

Abstract This paper aims to assess the magnitude and profile of deaths from post-COVID conditions in Brazil. Descriptive study based on preliminary data from the 2021 Mortality Information System. Records with ICD code B94.8 as the Basic Cause and with code U09 in some lines of part I or II of the declaration were considered for analysis. The distribution of deaths by geographic region, semester of occurrence, sex, age group, ethnicity/skin color, schooling, and place of occurrence was evaluated. We identified 2,948 deaths from conditions subsequent to COVID-19 were recorded, ranging from 0.5 deaths per 1,000 records in the Northeast Region to 3.6/1,000 in the Midwest Region. More than half occurred among males (58.0%), those aged 60 years or older (66.9%), and whites (51.8%). Conclusion: Deaths from post-COVID conditions had distinct sociodemographic characteristics between regions.

The excess of monthly deaths by state in Brazil, mainly in 2021, point to an unprecedented mortuary catastrophe in Brazil How has the government of Brazil acted and has acted to protect its citizens from the most important, intense and deadly event of all time, in these 521 years of Brazilian history? How great is the risk of death that its inhabitants are facing, is it possible to measure and compare with other similar human beings, but who have different governments? Can we really measure, based on scientific, safe and verified data, the performance, willingness and result of actions and even the examples that the federal government of Brazil promoted in 18 months of the years 2020 and 2021? YES, we can ! Fortunately, in this era of free and unquestionable virtual environments, it is possible to develop reliable and fast ways to search, classify, verify, index, compare and publish known health epidemiological indices of human health! The internet and the Dataverse of the Harvard School allowed, not only scientists and physicians, as any being on Earth, to consult, understand and compare results that will remain available for generations, between the past and the present, but also between countries, as in this set we deal with the safest and most important health index, we show absolute numbers of deaths and births... All the most used epidemiological variables of birth and mortality per month in Brazil, from January 2014 to June 2021, by state, country and 2 large groups of states (based on a single criterion - votes Bolsonaro 1st round 2018 > 50%) All most used epidemiological variables from mortality per month in Brazil , Jan-2015 to Jun-2021, per state and country We show the death rate, number of net deaths, excess deaths, births, birth rate, annual growth rate, growth rate variation, P-score, excess mortality rate by months by state (UF), percentage of seniors over 70 years old from January 2014 to June 2021

Net total Deaths per state Brazil Jan/2014 to Aug/2021 Two files with all net deaths (no traumatic) and general mortality rate in Brazil per state All mortality rates was per 100000 and was computed with population of year (2014 to 2021) Source: IBGE, SIM/MS SUS and Registro Civil Arpen Portal from Brazil All geographic variables was a geojson and flag link file Provenance info was set for all data

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Brazilian COVID-19 Parliamentary Commission of Inquiry (PCI), 2021

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This dataset has 3,397,933 tweets, splitted in days and weeks, extracted over a period of 26 weeks. It contains textual data from tweets, data about users (@ and description), and data about interactions between users. It can be used to improve textual cleaning techniques, toxic speech detection, clustering, and even Social Network Analysis and social graph studies. Data format is parquet.

This dataset is part of a paper[1], published by its author, which aimed to do a social network analysis related to the CPI topic, to investigate evidence of political polarization. The source codes and jupyter notebooks are available on GitHub.

[1] Uniting Politics and Pandemic: a Social Network Analysis on the COVID Parliamentary Commission of Inquiry in Brazil. WebMedia 2022. Lucas Raniére J. Santos, Leandro B. Marinho, Caludio E. C. Campelo.

Disclosure of information with far right's ideas, negationism of science and anti-vaccine attitude x Risk of COVID-19

The electoral preference by Bolsonaro in the first round of Brazil presidential election 2018 per state, shows a relation with the amount of deaths by Covid-19 per 100000, excess death per 100,000, increased P-score and intensity in reducing Brazilian population growth in the 1st quarter 2021

Content

In the period from January to April (1st Quadrimester Q1) from 2021 and 2019 per state (UF)

Main variables for each of the 27 Brazilian states and 4 States groups

1. The main population rates: - Number deaths, excess deaths, births, birth rate, mortality rate, vegetative growth, p-score, total population, population> 70A., Demographic density

2. The main rates of Pandemic by Coronavirus - Covid-19:

   • No. Total cases, cases Q1, Nº Total deaths, Nº Q1 deaths, Total deaths / 100000 hab, mortality rate, cases / 100000 hab

3. The main metrics of the 2018 presidential election:

   • Voters, voting paragraphs, nº of votes in Bolsonararo 1st turn, nº of abstinences.

Groups of Brazilian UFS (Federation States)

1. States that Bolsonaro received more than 50% of the votes in the 1st turn
2. States that Bolsonaro received less than 50% of the votes in the 1st turn and more than 50% in the 2nd turn
3. States that Bolsonaro received less than 50% of the votes in the 1st and 2nd shifts
4. Sum of the 27 Brazilian states

PT(BR) - version

Divulgação de informações com idéias da extrema direita, negacionismo da ciência e atitude anti-vacina x risco de Covid-19

A preferência eleitoral por Bolsonaro no 1º turno de 2018 por estado, mostra-se relacionada com a quantidade de mortes por COVID-19, excesso de mortes por 100000, aumento do P-score e intensidade na redução do crescimento populacional brasileiro no 1ºquadrimestre de 2021.

No período de Janeiro a Abril(1º Quadrimestre Q1) de 2021 e 2019 por estado (UF)

Principais variáveis

1. As principais taxas populacionais: - nº mortes, excesso de mortes, nº nascimentos, taxa de natalidade, taxa de mortalidade, crescimento vegetativo, P-score, população total, população > 70a., densidade demográfica

2. As principais taxas da pandemia por Coronavirus - COVID-19:

   • nº casos totais, nº casos Q1, nº mortes totais, nº mortes Q1, mortes totais/100000 hab, taxa de Mortalidade, casos/100000 hab

3. As principais métricas da eleição presidencial de 2018:

   • nº eleitores, nº votantes, nº de votos em Bolsonaro 1º turno, nº de abstinências.

Grupos de UFs (Estados da Federação)

1.Estados que Bolsonaro recebeu mais de 50% dos votos no 1º turno 2.Estados que Bolsonaro recebeu menos que 50% dos votos no 1º turno e mais de 50% no 2º turno 3.Estados que Bolsonaro recebeu menos que 50% dos votos no 1º e 2º turnos 4.Soma dos 27 Estados Brasileiros

ABSTRACT This work makes use of artificial intelligence to contribute with empirical evidence that help predict death by COVID-19, enabling the improvement of health protocols used in health systems in Brazil and providing society with more tools to combat COVID-19. Data from January to September 2021 for Brazil are used in order to predict death by COVID-19 based on the clinical status of patients who used the Unified Health System in the studied period, in which three classification algorithms were tried: Logistic Regression (LR), Decision Tree (DT), and Random Forest (RF). The LR, DT, and RF models had a mean accuracy of 76%, 76%, and 77% in predicting death, respectively. In addition, it was possible to infer that when patients reach a point that require the use of ventilatory support and ICU, added to age, their chance of dying of COVID-19 is greater.

Several recent studies have investigated if support for Jair Bolsonaro in the presidential election of 2018 is positively associated with COVID-19 infections and deaths in Brazil. In these studies, COVID-19 outcomes in 2020 and 2021 are the dependent variables, and votes for Jair Bolsonaro in the 2018 presidential election (as a proxy for ideology) are the key explanatory variable. This article discusses why ecological research designs are difficult to test empirically. We discuss why correlations between vote shares and COVID-19 outcomes using aggregate data can produce biased inferences, and we specifically focus on measurement error, aggregation bias, and spatial and temporal dynamics.

As of May 2, 2023, there were roughly 687 million global cases of COVID-19. Around 660 million people had recovered from the disease, while there had been almost 6.87 million deaths. The United States, India, and Brazil have been among the countries hardest hit by the pandemic.

The various types of human coronavirus The SARS-CoV-2 virus is the seventh known coronavirus to infect humans. Its emergence makes it the third in recent years to cause widespread infectious disease following the viruses responsible for SARS and MERS. A continual problem is that viruses naturally mutate as they attempt to survive. Notable new variants of SARS-CoV-2 were first identified in the UK, South Africa, and Brazil. Variants are of particular interest because they are associated with increased transmission.

Vaccination campaigns Common human coronaviruses typically cause mild symptoms such as a cough or a cold, but the novel coronavirus SARS-CoV-2 has led to more severe respiratory illnesses and deaths worldwide. Several COVID-19 vaccines have now been approved and are being used around the world.

WHO: COVID-2019: Number of Patients: Death: New: Brazil data was reported at 0.000 Person in 24 Dec 2023. This stayed constant from the previous number of 0.000 Person for 23 Dec 2023. WHO: COVID-2019: Number of Patients: Death: New: Brazil data is updated daily, averaging 204.000 Person from Feb 2020 (Median) to 24 Dec 2023, with 1398 observations. The data reached an all-time high of 4,249.000 Person in 10 Apr 2021 and a record low of 0.000 Person in 24 Dec 2023. WHO: COVID-2019: Number of Patients: Death: New: Brazil data remains active status in CEIC and is reported by World Health Organization. The data is categorized under High Frequency Database’s Disease Outbreaks – Table WHO.D002: World Health Organization: Coronavirus Disease 2019 (COVID-2019): by Country and Region (Discontinued).

DATABASE - This was a longitudinal retrospective cohort study of patients ≥20 years-old who were hospitalised due to COVID-19 in 52 hospitals comprising a private Brazilian healthcare network (Rede D’Or São Luiz). Participating institutions were tertiary hospitals distributed across four (Northeast, Central-West, Southeast, and South) of Brazil’s five macro-regions. Data were extracted from the institutional central database comprised of COVID-19 diagnoses and related deaths (both of which are of compulsory notification to the BMH). Participating hospitals utilized a standardized data collection model including weekly reporting to the BMH. The study period included the first 13 months of the pandemic, i.e., from March 1st, 2020 to March 31st, 2021. All patients hospitalised due to COVID-19 (as the primary diagnosis upon admission) who were either discharged or died were included

As of May 2, 2023, the outbreak of the coronavirus disease (COVID-19) had spread to almost every country in the world, and more than 6.86 million people had died after contracting the respiratory virus. Over 1.16 million of these deaths occurred in the United States.

Waves of infections Almost every country and territory worldwide have been affected by the COVID-19 disease. At the end of 2021 the virus was once again circulating at very high rates, even in countries with relatively high vaccination rates such as the United States and Germany. As rates of new infections increased, some countries in Europe, like Germany and Austria, tightened restrictions once again, specifically targeting those who were not yet vaccinated. However, by spring 2022, rates of new infections had decreased in many countries and restrictions were once again lifted.

What are the symptoms of the virus? It can take up to 14 days for symptoms of the illness to start being noticed. The most commonly reported symptoms are a fever and a dry cough, leading to shortness of breath. The early symptoms are similar to other common viruses such as the common cold and flu. These illnesses spread more during cold months, but there is no conclusive evidence to suggest that temperature impacts the spread of the SARS-CoV-2 virus. Medical advice should be sought if you are experiencing any of these symptoms.