Evidence map›Paper›PMID 34870262›Full record

ArticleLancet regional health. Americas2022

Fire association with respiratory disease and COVID-19 complications in the State of Pará, Brazil.

Lucas Schroeder, Eniuce Menezes de Souza, Clévia Rosset, Ademir Marques Junior, Juliano André Boquett, Vinicius Francisco Rofatto, Diego Brum, Luiz Gonzaga, Marcelo Zagonel de Oliveira, Mauricio Roberto Veronez

Open access · goldAbstract read
In one paragraph

Article in Lancet regional health. Americas, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 36% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Observational
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 5 institutions in 1 country.

Lucas SchroederPost Graduate Program in Applied Computing, Unisinos University. São Leopoldo, RS, Brazil.
Eniuce Menezes de SouzaDepartment of Statistics, State University of Maringá. Maringá, PR, Brazil.
Clévia RossetMedical Genomics Laboratory, Hospital de Clínicas de Porto Alegre. Porto Alegre, RS, Brazil.
Ademir Marques JuniorPost Graduate Program in Applied Computing, Unisinos University. São Leopoldo, RS, Brazil.
Juliano André BoquettPost-graduate Program in Genetics and Molecular Biology, Institute of Biosciences, Federal University of Rio Grande do Sul. Porto Alegre, RS, Brazil.
Vinicius Francisco RofattoInstitute of Geography, Federal University of Uberlândia. Monte Carmelo, MG, Brazil.
Diego BrumPost Graduate Program in Applied Computing, Unisinos University. São Leopoldo, RS, Brazil.
Luiz GonzagaPost Graduate Program in Applied Computing, Unisinos University. São Leopoldo, RS, Brazil.
Marcelo Zagonel de OliveiraVizlab | X-Reality and Geoinformatics Lab, Unisinos University. São Leopoldo, RS, Brazil.
Mauricio Roberto VeronezPost Graduate Program in Applied Computing, Unisinos University. São Leopoldo, RS, Brazil.
Universidade do Vale do Rio dos Sinos · BRHospital de Clínicas de Porto Alegre · BRUniversidade Estadual de Maringá · BRUniversidade Federal de Uberlândia · BRUniversidade Federal do Rio Grande do Sul · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBrazil has faced two simultaneous problems related to respiratory health: forest fires and the high mortality rate due to COVID-19 pandemics. The Amazon rain forest is one of the Brazilian biomes that suffers the most with fires caused by droughts and illegal deforestation. These fires can bring respiratory diseases associated with air pollution, and the State of Pará in Brazil is the most affected. COVID-19 pandemics associated with air pollution can potentially increase hospitalizations and deaths related to respiratory diseases. Here, we aimed to evaluate the association of fire occurrences with the COVID-19 mortality rates and general respiratory diseases hospitalizations in the State of Pará, Brazil.

methodsWe employed machine learning technique for clustering k-means accompanied with the elbow method used to identify the ideal quantity of clusters for the k-means algorithm, clustering 10 groups of cities in the State of Pará where we selected the clusters with the highest and lowest fires occurrence from the 2015 to 2019. Next, an Auto-regressive Integrated Moving Average Exogenous (ARIMAX) model was proposed to study the serial correlation of respiratory diseases hospitalizations and their associations with fire occurrences. Regarding the COVID-19 analysis, we computed the mortality risk and its confidence level considering the quarterly incidence rate ratio in clusters with high and low exposure to fires.

findingsUsing the k-means algorithm we identified two clusters with similar DHI (Development Human Index) and GDP (Gross Domestic Product) from a group of ten clusters that divided the State of Pará but with diverse behavior considering the hospitalizations and forest fires in the Amazon biome. From the auto-regressive and moving average model (ARIMAX), it was possible to show that besides the serial correlation, the fires occurrences contribute to the respiratory diseases increase, with an observed lag of six months after the fires for the case with high exposure to fires. A highlight that deserves attention concerns the relationship between fire occurrences and deaths. Historically, the risk of mortality by respiratory diseases is higher (about the double) in regions and periods with high exposure to fires than the ones with low exposure to fires. The same pattern remains in the period of the COVID-19 pandemic, where the risk of mortality for COVID-19 was 80% higher in the region and period with high exposure to fires. Regarding the SARS-COV-2 analysis, the risk of mortality related to COVID-19 is higher in the period with high exposure to fires than in the period with low exposure to fires. Another highlight concerns the relationship between fire occurrences and COVID-19 deaths. The results show that regions with high fire occurrences are associated with more cases of COVID deaths.

interpretationThe decision-make process is a critical problem mainly when it involves environmental and health control policies. Environmental policies are often more cost-effective as health measures than the use of public health services. This highlight the importance of data analyses to support the decision making and to identify population in need of better infrastructure due to historical environmental factors and the knowledge of associated health risk. The results suggest that The fires occurrences contribute to the increase of the respiratory diseases hospitalization. The mortality rate related to COVID-19 was higher for the period with high exposure to fires than the period with low exposure to fires. The regions with high fire occurrences is associated with more COVID-19 deaths, mainly in the months with high number of fires.

fundingNo additional funding source was required for this study.

Indexed as

ARIMAXCOVID-19FireHospitalizationsIncidence rate ratioK-MeansMortalityRespiratory diseasesRiskSARS-Cov-2Time series analysis

Identifiers

PMID34870262
PMCPMC8632600
OpenAlexW3210344198

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.