DOI: 10.5061/dryad.v6wwpzh5h
title: Brazilian municipal health policies during the COVID-19 pandemic

description: Brazil was one of the countries most impacted by the COVID-19 pandemic in
 Latin America and the world considering the number of cases, deaths, and
 the duration of lockdowns. Between 2020 and 2022, both pharmacological and
 non-pharmacological interventions (NPIs) were adopted at the municipal
 level, with 5,568 municipalities and the Federal District taking
 health-related actions. We present a new dataset revealing the complexity
 of this situation by reporting data based on thirty-seven surveys taken by
 mayors between 23 March 2021 and 24 March 2022. The number of
 participating municipalities in each survey varied over time. The database
 indicates in which rounds each municipality participated. The minimum
 number of participating municipalities was 1,328 (23.8%), while the
 maximum reached 3,591 (64.49%), showing significant variation. The median
 was 2,461 (44.19%), and the mean of 2,482 (44.57%) suggests that, in
 general, municipal participation was close to the median, suggesting the
 data are representative. Finally, the first quartile was 2,063, and the
 third quartile was 2,831. The table titled “participation” presents the
 participation percentages for each of the rounds. This dataset deals with
 the need to monitor and share information about fragmented policies
 designed to tackle health crises like the COVID-19 pandemic. Quantifying
 these initiatives and how they varied across municipalities can help us to
 understand the effectiveness of interventions in reducing virus
 transmission. We offer information over time on a series of measures to
 encourage social distancing, implement the vaccination programme, provide
 infrastructure to treat infected people, and facilitate how local
 governments would eventually ease these measures. This information can
 contribute to the institutional learning of health systems worldwide,
 assisting in future situations where a highly contagious virus challenges
 society.
description: Information on local NPI policies related to COVID-19 was
 collected through a telephone survey conducted directly with mayors, who
 had the option of receiving a password-protected link to respond to the
 online questionnaire later or to update previous responses. We focused on
 information concerning three essential dimensions related to the pandemic
 response: the monitoring of restrictive measures, infrastructure to treat
 infected people, and the implementation of the vaccination programme. We
 have included the week that respondents received the questionnaire, the
 initial date the questionnaire was presented to respondents, and the final
 date of questionnaire submission. We collaborated with
 the Brazilian Confederation of Municipalities (CNM) to collect these data.
 The cooperation was formalised in a meeting with the CNM on 9 April 2020,
 and a written agreement was signed by the first and last authors of this
 article. The authors were given permission to describe, publish, and
 analyse the dataset. Prior to this current dataset with information from
 2021 and 2022, the first and last authors of this dataset had already
 shared an initial dataset with lockdown measures in Brazil that refer to a
 survey conducted on October 19 2020,
 https://doi.org/10.5061/dryad.vdncjsxs2. Similar to our previous dataset
 that refers to a single survey in the initial days of COVID-19 pandemic,
 the data we now share on 37 surveys, are freely available to the public
 and to other academics for analysis. As Brazil’s
 largest association of municipalities, the CNM has the email and phone
 numbers of all elected mayors in the country; the wide reach of the
 association makes it an ideal partner for large-scale data collection. The
 partnership was established to study the impact of decentralised measures
 in Brazil and the effects of decentralisation on the spread of infectious
 diseases. After the establishment of the cooperation agreement, the CNM
 added other questions to the questionnaire that were of interest to its
 municipal monitoring, such as questions related to the possible impact of
 the pandemic on municipal budgets. Thirty-seven rounds
 of questionnaires were conducted, totalling 239 questions. Our database
 has 15 columns related to municipal identification, 4 on waiting for a
 bed, 6 on stock and yield of vaccines, 5 on intubation sets, 6 on
 restrictive measures, 3 on oxygen stocks in hospitals, COVID-19 centres,
 and other facilities, 4 on the stock of vaccines, 1 on financial
 resources, 3 on the situation in the UPAs, 3 on the social consequences of
 the pandemic, 2 on the care of people with health consequences resulting
 from COVID-19 infection, and 198 on vaccination.
 <strong>Usage notes</strong> As
 not all municipal authorities answered all the questions, we suggest that
 users of this dataset consider additional sources of information to
 document the implementation of missing policies, preferably using official
 sources of information such as local decrees. However, as decrees are not
 always available online, secondary sources, such as media reports, may
 need to be consulted. We invite researchers to use
 these data to deepen their understanding of the pandemic and support
 health policymakers’ efforts in other health emergencies. Additionally, by
 combining our database with other government sources, such as those from
 the Superior Electoral Court, we offer tools to investigate effects of
 politics on public health policies during the pandemic and thus generate
 institutional learning for health systems, empirically demonstrating how
 political decisions influence public health policies. For example, we can
 analyse how the alignment of a particular mayor with the former president,
 elected in 2018, their party affiliation, and other such factors affected
 political decisions relating to pandemic response measures.
description: # Brazilian municipal health policies during the COVID-19 pandemic
 [https://doi.org/10.5061/dryad.v6wwpzh5h](https://doi.org/10.5061/dryad.v6wwpzh5h) ## Description of the data and file structure This dataset gathers information on the processes and activities of the pandemic response in Brazil, as well as the epidemiological outcomes of the COVID-19 pandemic in Brazilian municipalities. Five documents are available: the database (**bank_measures_complete_2**.Rda**), the codebook (**codebook_complete_2(1).csv**), the table with the municipal participation rate (**participation.csv**), a table detailing which questions are included in each round of the surveys (**table_contention.csv**), and the (**manipulation_base.R**) that describes the process of manipulating and cleaning the data. Further details about each document are provided below. ### bank\_measues\_complete\_2.Rda This is the database containing all the questions and all the rounds conducted with the municipalities. The document *codebook_complete.csv* provides the codebook for all the variables present in the referred database. ### codebook\_complete\_2(1).csv It provides a detailed description of the information and the explanations of the respective codes present in the *bank_measures_complete.Rda* database. Detailed information in the file *codebook_complete.csv*: * *group*: The "group" variable gathers a set of questions related to the same analytical dimension. * *letter*: For each "group", that is, for each dimension that groups a series of questions, a letter from the alphabet is assigned as a code. * *code*: This variable indicates the number that the corresponding information represents in the *bank_measures_complete.Rda* database. * *questions*: It presents the description of the question asked, which is recorded in the *bank_measures_complete.Rda* database. * *variables*: This variable indicates the code of the corresponding question in the *bank_measures_complete.Rda* database. * *values*: It provides the explanations for each coding associated with the values assigned to a given response. ### participation.csv This table presents the percentages of municipalities that participated in each round of interviews, considering the total number of municipalities in Brazil. The minimum number of participating municipalities was 1,328 (23.8%), while the maximum reached 3,591 (64.49%), indicating significant variation in participation. The median was 2,461 (44.19%), and the mean, at 2,482 (44.57%), suggests that, overall, the participation of municipalities was close to the median, reinforcing the representativeness of the data. Finally, the first quartile was 2,063, and the third quartile was 2,831, highlighting the asymmetric distribution of participation among municipalities. Detailed information in the file *participation.csv*: * *Interview sequence*: In this variable, the order of interviews is presented in ascending order, ranging from a scale of 1 to 37. * *Interview week*: The date on which the interviews were conducted. * *Responding municipalities*: It presents the number of municipalities that participated in the mentioned round of interviews. * *Total municipalities*: Total number of municipalities in Brazil. * *% of respondents*: The percentage of municipalities that participated in each round of interviews relative to the total number of municipalities. ### table\_contention.csv The document provides the total number of occurrences of each question throughout the 37 rounds and lists the rounds in which this question appeared. Over time, different questions were asked to the mayors that reflect different stages of the pandemic, and the table in question shows the frequency of each one, as well as indicating in which specific rounds they were conducted Detailed information in the file *table_contention.csv*: * *group*: The "group" variable gathers a set of questions related to the same analytical dimension. * *letter*: For each "group", that is, for each dimension that groups a series of questions, a letter from the alphabet is assigned as a code. * *code*: This variable indicates the number that the corresponding information represents in the *bank_measures_complete.Rda* database. * *questions*: It presents the description of the question asked, which is recorded in the *bank_measures_complete.Rda* database. * *variables*: This variable indicates the code of the corresponding question in the *bank_measures_complete.Rda* database. * *how_many_times_it_appears*: This variable presents the number of times a specific question was asked across the 37 rounds of interviews. Thus, a question could have been asked at least once or up to 37 times, corresponding to the total number of rounds conducted. * *23-25/03/2021*: "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *29-31/03/2021*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *05-08/04/2021*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *12-15/04/2021*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *19-22/04/2021*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *26-30/04/2021*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *03-06/05/2021*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *10-13/05/2021*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *17-20/05/2021*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *24-28/05/2021*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *31/05/2021-02/06/2021*: "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *02-07/06/2021*: "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *14-17/06/2021*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *21-24/06/2021*: "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *28/06/2021 - 02/07/2021*: "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *05-08/07/2021*: "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *12-15/07/2021*: "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *22-25/07/2021*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *26-29/07/2021*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *04-05/08/2021*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *09-12/08/2021*:  "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *16-19/08/2021*: "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *23-26/08/2021*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *30/08/2021 - 02/09/2021*:    "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *13-16/09/2021*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *20-23/09/2021*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *27-30/09/2021*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *04-07/10/2021*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *18-22/10/2021*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *25-28/10/2021*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *16-19/11/2021*: "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *06-09/12/2021*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *10-13/01/2022*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *31/01/2022 - 03/02/2022*:  "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *14-17/02/2022*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *07-10/03/2022*:   "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. * *21-24/03/2022*: "Yes" indicates that the question is present in this specific round, while "No" means that the question was not asked in this round. ## *manipulation\_base* File "manipulation_base.R" script was included to demonstrate to the reader the process carried out to pre-process the present database. ## Version changes *10-mar-2025* In the codebook_complete_2 (1), only one word was changed in columns 52 to 61A. The File "manipulation_base.R script was included to show the reader how we pre-processed the data.