CORRELAÇÃO CRUZADA ENTRE AS OCORRÊNCIAS DE INFECÇÕES POR CHIKUNGUNYA E CONDIÇÕES METEOROLÓGICAS NO ESTADO DA BAHIA
DOI:
https://doi.org/10.56238/revgeov17n4-215Palavras-chave:
Variáveis Atmosféricas, Arbovirose, Séries Temporais, DFA, ρ_DCCAResumo
Condições climáticas sabidamente influenciam na disseminação de certos tipos de doenças. Neste sentido, variáveis meteorológicas, como temperatura, umidade relativa do ar, entre outras, podem contribuir para a ocorrência de surtos e epidemias. Então, estudar se há uma relação entre as variáveis meteorológicas e o número de casos dessas epidemias é importante para o controle e a prevenção delas, como, por exemplo, no caso da Chikungunya. Logo, este artigo tem como objetivo analisar os níveis de autocorrelação e de correlação cruzada entre os casos de infecção pelo vírus da Chikungunya e variáveis meteorológicas, como temperatura, umidade relativa do ar e precipitação. Para o estudo de caso, escolheu-se o Estado da Bahia, no período de 2015 a 2024, com dados extraídos das bases públicas do DATASUS e do INMET. As análises foram realizadas com os métodos estatísticos DFA e DCCA. A partir da análise de autocorrelação, observa-se a presença de memória fortemente persistente com sinais de sazonalidade nos dados. No que tange à correlação cruzada entre os casos de Chikungunya e as variáveis meteorológicas, os resultados destacam que: não há correlação cruzada entre o número de casos de Chikungunya e as três variáveis meteorológicas, isto é, se pequenas escalas temporais são analisadas. Porém, em grandes escalas temporais, observa-se que a umidade relativa do ar apresenta correlação cruzada positiva com os casos de Chikungunya. No complemento da análise, realizou-se o estudo das correlações cruzadas entre os dados, com o implemento de defasagem temporal. Finalmente, os resultados obtidos destacam a alternância das correlações cruzadas entre as variáveis meteorológicas e os casos de Chikungunya, reforçando a importância de considerar todas as escalas temporais e suas defasagens.
Downloads
Referências
Abreu, Filipe Vieira Santos de, Cecilia Siliansky de Andreazzi, Maycon Sebastião Alberto Santos Neves, et al. 2022. “Ecological and Environmental Factors Affecting Transmission of Sylvatic Yellow Fever in the 2017–2019 Outbreak in the Atlantic Forest, Brazil”. Parasites & Vectors 15 (1): 23. https://doi.org/10.1186/s13071-021-05143-0.
Arcanjo, Danielle Beatriz Marques Campos, Paloma Oliveira Vidal, José Yure Gomes dos Santos, Larissa Paola Rodrigues Venancio, Lincoln Suesdek, e Jaime Henrique Amorim. 2020. “Geometric Morphometrics of Aedes Aegypti Populations and Study of Transmission of Arboviral Diseases in Barreiras, Brazil”. Revista Brasileira de Entomologia 64: e201960. https://doi.org/10.1590/1806-9665-RBENT-2019-60.
Bangoura, Salifou T., Alpha-Kabinet Keita, Maladho Diaby, et al. 2025. Arbovirus Epidemics as Global Health Imperative, Africa, 2023 - Volume 31, Number 2—February 2025 - Emerging Infectious Diseases journal - CDC. https://doi.org/10.3201/eid3102.240754.
BRASIL, Ministério da Agricultura e Pecuária. 2024. “Instituto Nacional de Meteorologia (INMET)”. Banco de Dados Meteorológicos para Ensino e Pesquisa (BDMEP). https://bdmep.inmet.gov.br/.
BRASIL, Ministério da Saúde. 2025. Transferência de Arquivos – Departamento de Informática do Sistema Único de Saúde - DATASUS. https://datasus.saude.gov.br/transferencia-de-arquivos/.
Brito, Carlos, Melissa Barreto Falcão, Maria de Fatima Pessoa Militão de Albuquerque, Thiago Cerqueira-Silva, Maria Glória Teixeira, e Rafael Freitas de Oliveira Franca. 2025. “Chikungunya: From Hypothesis to Evidence of Increased Severe Disease and Fatalities”. Viruses 17 (1): 62. https://doi.org/10.3390/v17010062.
Camara, Ana Julia Alves, Valdério Anselmo Reisen, Glaura Conceicao Franco, e Pascal Bondon. 2025. “Combining Generalized Linear Autoregressive Moving Average and Bootstrap Models for Analyzing Time Series of Respiratory Diseases and Air Pollutants”. Mathematics 13 (5). https://doi.org/10.3390/math13050859.
Campos, Gubio S., Antonio C. Bandeira, e Silvia I. Sardi. 2015. Zika Virus Outbreak, Bahia, Brazil - Volume 21, Number 10—October 2015 - Emerging Infectious Diseases journal - CDC. https://doi.org/10.3201/eid2110.150847.
Carpena, Pedro, Manuel Gómez-Extremera, e Pedro A. Bernaola-Galván. 2022. “On the Validity of Detrended Fluctuation Analysis at Short Scales”. Entropy 24 (1): 61. https://doi.org/10.3390/e24010061.
Castillo, José Maria Del, Gabriela Marques Pereira de Alencar, Marcus Vinicius Dantas da Nóbrega, et al. 2018. “Echocardiographic Evaluation of Late Cardiac Abnormalities Caused by the Chikungunya Fever”. Arq Bras Cardiol: Imagem Cardiovasc 31 (3): 183–90.
Cheng, Qu, Qinlong Jing, Philip A. Collender, et al. 2023. “Prior Water Availability Modifies the Effect of Heavy Rainfall on Dengue Transmission: A Time Series Analysis of Passive Surveillance Data from Southern China”. Frontiers in Public Health 11 (dezembro). https://doi.org/10.3389/fpubh.2023.1287678.
Costa, Denise Maria do Nascimento, Carlos Eduardo Machado, Precil Diego Neves, et al. 2022. “Chikungunya Virus as a Trigger for Different Renal Disorders: An Exploratory Study”. Journal of Nephrology 35 (5): 1437–47. https://doi.org/10.1007/s40620-022-01256-6.
Costa, Moisés Domingos Namila da, Andréa de Almeida Brito, Arleys Pereira Nunes de Castro, Rui Manuel Teixeira Santos Dias, e Gilney Figueira Zebende. 2024. “Trends in the Air Temperature: A Practical Approach for Auto- and Cross-Correlation Analysis”. Advances in Meteorology 2024 (1): 3098248. https://doi.org/10.1155/2024/3098248.
Danko, David C., John C. Papciak, James Golden, et al. 2025. “The Challenges and Opportunities in Creating a One Health Warning System for Pandemics”. Cell Reports Sustainability 2 (9). https://doi.org/10.1016/j.crsus.2025.100485.
Daude, Matheus Martins, Erika Regina Manuli, Geovana Maria Pereira, et al. 2024. “Simultaneous Detection of Arboviruses by a Multiplex RT-qPCR Assay in Tocantins, a Northern State of Brazil”. The Brazilian Journal of Infectious Diseases 28 (4). https://doi.org/10.1016/j.bjid.2024.103855.
Daudt-Lemos, Matheus, Alice Ramos-Silva, Renan Faustino, et al. 2025. “Rising Incidence and Spatiotemporal Dynamics of Emerging and Reemerging Arboviruses in Brazil”. Viruses 17 (2): 158. https://doi.org/10.3390/v17020158.
Delrieu, Méryl, Jean-Philippe Martinet, Olivia O’Connor, et al. 2023. “Temperature and transmission of chikungunya, dengue, and Zika viruses: A systematic review of experimental studies on Aedes aegypti and Aedes albopictus”. Current Research in Parasitology & Vector-Borne Diseases 4 (janeiro): 100139. https://doi.org/10.1016/j.crpvbd.2023.100139.
El-Sayed, Amr, e Mohamed Kamel. 2020. “Climatic Changes and Their Role in Emergence and Re-Emergence of Diseases”. Environmental Science and Pollution Research 27 (18): 22336–52. https://doi.org/10.1007/s11356-020-08896-w.
Faranda, Davide, Gabriele Messori, Erika Coppola, et al. 2024. “ClimaMeter: Contextualizing Extreme Weather in a Changing Climate”. Weather and Climate Dynamics 5 (3): 959–83. https://doi.org/10.5194/wcd-5-959-2024.
Farias, Pablo Cantalice Santos, André Filipe Pastor, Juliana Prado Gonçales, et al. 2023. “Epidemiological profile of arboviruses in two different scenarios: dengue circulation vs. dengue, chikungunya and Zika co-circulation”. BMC Infectious Diseases 23 (1): 177. https://doi.org/10.1186/s12879-023-08139-6.
Figueredo, Marcos Batista, Roberto Luiz Souza Monteiro, Alexandre do Nascimento Silva, José Roberto de Araújo Fontoura, Andreia Rita da Silva, e Carolina Aparecida Pereira Alves. 2023. “Analysis of the Correlation between Climatic Variables and Dengue Cases in the City of Alagoinhas/BA”. Scientific Reports 13 (1): 7512. https://doi.org/10.1038/s41598-023-34349-8.
Filho, Aloísio S. Nascimento, Thiago B. Murari, Paulo Ferreira, Hugo Saba, e Marcelo A. Moret. 2021. “A Spatio-Temporal Analysis of Dengue Spread in a Brazilian Dry Climate Region”. Scientific Reports 11 (1): 11892. https://doi.org/10.1038/s41598-021-91306-z.
Gardini Sanches Palasio, Raquel, Patricia Marques Moralejo Bermudi, Fernando Luiz de Lima Macedo, Lidia Maria Reis Santana, e Francisco Chiaravalloti-Neto. 2023. “Zika, Chikungunya and Co-Occurrence in Brazil: Space-Time Clusters and Associated Environmental–Socioeconomic Factors”. Scientific Reports 13 (1): 18026. https://doi.org/10.1038/s41598-023-42930-4.
Granger Neto, Henry Paul, Cínthya Viana Souza Rocha, Thiago Macêdo Lopes Correia, et al. 2022. “Natural Vertical Cotransmission of Dengue Virus and Chikungunya Virus from Aedes Aegypti in Brumado, Bahia, Brazil”. Revista Da Sociedade Brasileira de Medicina Tropical 55: e0427. https://doi.org/10.1590/0037-8682-0427-2021.
Guedes, Everaldo Freitas, Cláudia Ferreira da Cruz, e Florêncio Mendes Oliveira Filho. 2025. “Quantifying the Influence of Climatic Variables on the Incidence of Diseases in Salvador-BA”. Fluctuation and Noise Letters 24 (03): 2550029. https://doi.org/10.1142/S0219477525500294.
Guedes, Everaldo Freitas, Ivan Costa da Cunha Lima, Gilney Figueira Zebende, e Aloísio Machado Silva-Filho. 2021. SlidingWindows: Methods for Time Series Analysis. Versão 0.2.0. Released abril 11. https://cran.r-project.org/web/packages/SlidingWindows/index.html.
Heath, Katherine, Lincoln Muniz Alves, e Michael B. Bonsall. 2025. “Climate Change, Urbanisation and Transmission Potential: Aedes Aegypti Mosquito Projections Forecast Future Arboviral Disease Hotspots in Brazil”. PLOS Neglected Tropical Diseases 19 (9): e0013415. https://doi.org/10.1371/journal.pntd.0013415.
Hu, Kun, Plamen Ch. Ivanov, Zhi Chen, Pedro Carpena, e H. Eugene Stanley. 2001. “Effect of trends on detrended fluctuation analysis”. Physical Review E 64 (1). https://doi.org/10.1103/PhysRevE.64.011114.
Hussain-Alkhateeb, Laith, Tatiana Rivera Ramírez, Axel Kroeger, Ernesto Gozzer, e Silvia Runge-Ranzinger. 2021. “Early warning systems (EWSs) for chikungunya, dengue, malaria, yellow fever, and Zika outbreaks: What is the evidence? A scoping review”. PLoS Neglected Tropical Diseases 15 (9): e0009686. https://doi.org/10.1371/journal.pntd.0009686.
Imai, Chisato, e Masahiro Hashizume. 2015. “A Systematic Review of Methodology: Time Series Regression Analysis for Environmental Factors and Infectious Diseases”. Tropical Medicine and Health 43 (1): 1–9. https://doi.org/10.2149/tmh.2014-21.
Jesus, Augusto César Parreiras de, Paula Luize Camargos Fonseca, Hugo José Alves, et al. 2024. “Retrospective epidemiologic and genomic surveillance of arboviruses in 2023 in Brazil reveals high co-circulation of chikungunya and dengue viruses”. BMC Medicine 22 (1): 546. https://doi.org/10.1186/s12916-024-03737-w.
Kraemer, Moritz U. G., Robert C. Reiner, Oliver J. Brady, et al. 2019. “Past and Future Spread of the Arbovirus Vectors Aedes Aegypti and Aedes Albopictus”. Nature Microbiology 4 (5): 854–63. https://doi.org/10.1038/s41564-019-0376-y.
Kwapień, Jarosław, Paweł Oświęcimka, e Stanisław Drożdż. 2015. “Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations”. Physical Review E 92 (5): 052815. https://doi.org/10.1103/PhysRevE.92.052815.
Lopes, Rafael, Xavier Basagaña, Leonardo S. L. Bastos, Fernando A. Bozza, e Otavio T. Ranzani. 2025. “Ambient Temperature and Dengue Hospitalization in Brazil: A 10-Year Period Case Time Series Analysis”. Environmental Epidemiology 9 (1): e360. https://doi.org/10.1097/EE9.0000000000000360.
Lühken, Renke, Leif Rauhöft, Björn Pluskota, et al. 2024. “High vector competence for chikungunya virus but heavily reduced locomotor activity of Aedes albopictus from Germany at low temperatures”. Parasites & Vectors 17 (1): 502. https://doi.org/10.1186/s13071-024-06594-x.
Lwande, Olivia Wesula, Vincent Obanda, Anders Lindström, et al. 2020. “Globe-Trotting Aedes aegypti and Aedes albopictus: Risk Factors for Arbovirus Pandemics”. Vector-Borne and Zoonotic Diseases 20 (2): 71–81. https://doi.org/10.1089/vbz.2019.2486.
Mahony, Colin R., e Alex J. Cannon. 2018. “Wetter Summers Can Intensify Departures from Natural Variability in a Warming Climate”. Nature Communications 9 (1): 783. https://doi.org/10.1038/s41467-018-03132-z.
Marinho, Robson dos Santos Souza, Rodrigo Lopes Sanz Duro, Mânlio Tasso de Oliveira Mota, et al. 2022. “Environmental Changes and the Impact on the Human Infections by Dengue, Chikungunya and Zika Viruses in Northern Brazil, 2010–2019”. International Journal of Environmental Research and Public Health 19 (19). https://doi.org/10.3390/ijerph191912665.
Masson-Delmotte, V., P. Zhai, A. Pirani, et al. 2021. “IPCC AR6 Working Group 1: Summary for Policymakers”. https://www.ipcc.ch/report/ar6/wg1/chapter/summary-for-policymakers/.
Medauar, Caique C., Samuel A. Silva, Luis Carlos C. Carvalho, Ícaro M. Galvão, e Philype V. Macêdo. 2020a. “Spatial-Temporal Variability of Rainfall and Mean Air Temperature for the State of Bahia, Brazil”. Anais Da Academia Brasileira de Ciências 92: e20181283. https://doi.org/10.1590/0001-3765202020181283.
Nakase, Taishi, Marta Giovanetti, Uri Obolski, e José Lourenço. 2024. “Population at Risk of Dengue Virus Transmission Has Increased Due to Coupled Climate Factors and Population Growth”. Communications Earth & Environment 5 (1): 475. https://doi.org/10.1038/s43247-024-01639-6.
Nunes, Marcio Roberto Teixeira, Nuno Rodrigues Faria, Janaina Mota de Vasconcelos, et al. 2015. “Emergence and Potential for Spread of Chikungunya Virus in Brazil”. BMC Medicine 13 (1): 102. https://doi.org/10.1186/s12916-015-0348-x.
Oliveira, Jéssica B., Thiago B. Murari, Aloisio S. Nascimento Filho, Hugo Saba, Marcelo A. Moret, e Claudia Andrea L. Cardoso. 2023. “Paradox between adequate sanitation and rainfall in dengue fever cases”. Science of The Total Environment 860 (fevereiro): 160491. https://doi.org/10.1016/j.scitotenv.2022.160491.
Olliaro, Piero, Florence Fouque, Axel Kroeger, et al. 2018. “Improved Tools and Strategies for the Prevention and Control of Arboviral Diseases: A Research-to-Policy Forum”. PLOS Neglected Tropical Diseases 12 (2): e0005967. https://doi.org/10.1371/journal.pntd.0005967.
Peng, C. K., SV Buldyrev, S. Havlin, M. Simons, HE Stanley, e AL Goldberger. 1994. “Mosaic organization of DNA nucleotides”. Physical Review E 49 (2): 1685–89. https://doi.org/10.1103/PhysRevE.49.1685.
Podobnik, Boris, e H. Eugene Stanley. 2008. “Detrended Cross-Correlation Analysis: A New Method for Analyzing Two Non-stationary Time Series”. Physical Review Letters 100 (8): 084102. https://doi.org/10.1103/PhysRevLett.100.084102.
Rocklöv, Joacim, e Robert Dubrow. 2020. “Climate Change: An Enduring Challenge for Vector-Borne Disease Prevention and Control”. Nature Immunology 21 (5): 479–83. https://doi.org/10.1038/s41590-020-0648-y.
Rohr, Jason R., e Jeremy M. Cohen. 2020. “Understanding how temperature shifts could impact infectious disease”. PLOS Biology 18 (11): e3000938. https://doi.org/10.1371/journal.pbio.3000938.
Sánchez, José Daniel, Carolina Álvarez Ramírez, Emilio Cevallos Carrillo, Juan Arias Salazar, e César Barros Cevallos. 2025. “Time Series Analysis of Dengue, Zika, and Chikungunya in Ecuador: Emergence Patterns, Epidemiological Interactions, and Climate-Driven Dynamics (1988–2024)”. Viruses 17 (9). https://doi.org/10.3390/v17091201.
Santos, Eslaine S., José G. V. Miranda, Hugo Saba, et al. 2022. “Network Analysis of Spreading of Dengue, Zika and Chikungunya in the State of Bahia Based on Notified, Confirmed and Discarded Cases”. Frontiers in Physics 10 (dezembro). https://doi.org/10.3389/fphy.2022.1047835.
Santos, Tarcis A. O. dos, Alberto S. de Arruda, Paulo H. Z. de Arruda, e Gilney F. Zebende. 2026. “Multi-Scale Dynamics of Carbon Dioxide Flux and Its Environmental Drivers in the Pantanal Wetland”. Biogeosciences 23 (2): 565–83. https://doi.org/10.5194/bg-23-565-2026.
Silva, Marcos Vinícius da, Jhon Lennon Bezerra da Silva, Maria Beatriz Ferreira, et al. 2024. “Geostatistical modeling of the rainfall patterns and monthly multiscale characterization of drought in the South Coast of the Northeast Brazilian via Standardized Precipitation Index”. Atmospheric Research 311 (dezembro): 107668. https://doi.org/10.1016/j.atmosres.2024.107668.
Simões, Yagho de Souza, Eduardo Henrique Borges Cohim Silva, e Heráclio Alves de Araújo. 2018. “Rainfall Zoning of Bahia State, Brazil: An Update Proposal”. Revista Ambiente & Água 13: e2171. https://doi.org/10.4136/ambi-agua.2171.
Skalinski, Lacita Menezes, Ana Paula Razal Dalvi, Márcio Natividade, et al. 2022. “The triple epidemics of arboviruses in Feira de Santana, Brazilian Northeast: Epidemiological characteristics and diffusion patterns”. Epidemics 38 (março): 100541. https://doi.org/10.1016/j.epidem.2022.100541.
Souza, Jose Herberto M., Tácita B. Barros, Palloma P. Almeida, et al. 2021. “Dynamics of Transmission of Urban Arbovirus Dengue, Zika and Chikungunya in Southwestern Region of Bahia, Brazil”. Anais Da Academia Brasileira de Ciências 93: e20200670. https://doi.org/10.1590/0001-3765202120200670.
Souza, Tailan Santos de, e Patricia dos Santos Nascimento. 2021. “Variabilidade Espacial e Temporal Da Precipitação Pluviométrica Na Região Hidrográfica Do Paraguaçu - BA”. Revista Cerrados 19 (01): 203–29. https://doi.org/10.46551/rc24482692202109.
Teixeira, Maria Glória, Lacita Menezes Skalinski, Enny S. Paixão, et al. 2021. “Seroprevalence of Chikungunya virus and living conditions in Feira de Santana, Bahia-Brazil”. PLOS Neglected Tropical Diseases 15 (4): e0009289. https://doi.org/10.1371/journal.pntd.0009289.
WHO. 2019. “International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10)”. https://icd.who.int/browse10/2019/en?utm_source.
WHO. 2025. “New WHO Guidelines for Clinical Management of Arboviral Diseases: Dengue, Chikungunya, Zika and Yellow Fever”. https://www.who.int/news/item/10-07-2025-new-who-guidelines-for-clinical-management-of-arboviral-diseases--dengue--chikungunya--zika-and-yellow-fever.
Wyk, Hannah Van, Joseph N. S. Eisenberg, e Andrew F. Brouwer. 2023. “Long-term projections of the impacts of warming temperatures on Zika and dengue risk in four Brazilian cities using a temperature-dependent basic reproduction number”. PLOS Neglected Tropical Diseases 17 (4): e0010839. https://doi.org/10.1371/journal.pntd.0010839.
Zebende, G. F. 2011. “DCCA cross-correlation coefficient: Quantifying level of cross-correlation”. Physica A: Statistical Mechanics and its Applications 390 (4): 614–18. https://doi.org/10.1016/j.physa.2010.10.022.
Zebende, G. F., dir. 2021. Tutorial DFA , DCCA e rho_DCCA. 22:46. https://www.youtube.com/watch?v=poDn6RmtEKo.
Zebende, G. F., A. A. Brito, e A. P. Castro. 2020. “DCCA cross-correlation analysis in time-series with removed parts”. Physica A: Statistical Mechanics and its Applications 545 (maio): 123472. https://doi.org/10.1016/j.physa.2019.123472.
Zebende, G. F., e A. Machado Filho. 2009. “Cross-correlation between time series of vehicles and passengers”. Physica A: Statistical Mechanics and its Applications 388 (23): 4863–66. https://doi.org/10.1016/j.physa.2009.07.046.
Zebende, G. F., e E. F. Guedes. 2022. “Detrended Correlogram Method for Non-Stationary Time-Series Analysis”. Fluctuation and Noise Letters 21 (02): 2250012. https://doi.org/10.1142/S0219477522500122.
