Spatio-temporal distribution of Dengue, Zika and Chikungunya in Cali, Colombia: 2014-2016
DOI:
https://doi.org/10.22267/rus.242603.330Keywords:
Vector borne diseases, Arbovirus infections, Disease outbreaks, Space-time clusteringAbstract
Introduction: Emerging and re-emerging arboviral infections have become a public health challenge in the Americas due to their epidemic potential. Objective: To determine the spatio-temporal distribution of the dengue, Zika, and chikungunya viruses during an epidemic period in Cali, Colombia. Materials and methods: Multi-method descriptive ecological and exploratory study of confirmed and suspected cases reported to the epidemiological surveillance system between 2014 and 2016. Results: 40,168 cases were analyzed, and it was found that dengue was the most frequent arboviral infection (59.2 %). The most affected individuals were women (65 %) and those with a mean age of 34.5 years. Although arboviral infections spread out throughout the city, the three diseases were concentrated in significant groups located at the center-east and northeast areas of Cali (p<0.01; z=-203.7). Conclusions: This study identified critical zones for the three arboviral infections, which are located in areas with low socioeconomic status. Likewise, the results suggest that in addition to eco-epidemiological and bio-psychosocial factors, temperature, precipitation, and the aedic index may play an important role in the spatio-temporal behavior of these diseases. A multidisciplinary and collaborative approach is necessary, which must involve communities and authorities to implement effective control strategies, especially during epidemic periods.
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Balakrishnan VS. WHO launches global initiative for arboviral diseases. Lancet Microbe [Internet]. 2022;3(6):e407. DOI: 10.1016/s2666-5247(22)00130-6
Wilder-Smith A, Gubler DJ, Weaver SC, Monath TP, Heymann DL, Scott TW. Epidemic arboviral diseases: priorities for research and public health. Lancet Infect Dis [Internet]. 2017;17(3):e101–e106. DOI: 10.1016/S1473-3099(16)30518-7
Espinal MA, Andrus JK, Jauregui B, Waterman SH, Morens DM, Santos JI, et al. Emerging and reemerging aedes-transmitted arbovirus infections in the region of the americas: Implications for health policy. Am J Public Health [Internet]. 2019;109(3):387–392. DOI: 10.2105/AJPH.2018.304849
Dick OB, San Martín JL, Montoya RH, del Diego J, Zambrano B, Dayan GH. The History of Dengue Outbreaks in the Americas. Am J Trop Med Hyg [Internet]. 2012;87(4):584–593. DOI: 10.4269/AJTMH.2012.11-0770
Vyhmeister E, Provan G, Doyle B, Bourke B. Multi-cluster and environmental dependant vector born disease models. Heliyon [Internet]. 2020;6(9):e04090. DOI: 10.1016/j.heliyon.2020.e04090
Ramirez B, on behalf of the TDR-IDRC Research Initiative on Vector Borne Diseases and Climate Change. Support for research towards understanding the population health vulnerabilities to vector-borne diseases: Increasing resilience under climate change conditions in Africa. Infect Dis Poverty [Internet]. 2017;6(1):164. DOI: 10.1186/S40249-017-0378-Z
Benedum CM, Seidahmed OME, Eltahir EAB, Markuzon N. Statistical modeling of the effect of rainfall flushing on dengue transmission in Singapore. PLoS Negl Trop Dis [Internet]. 2018;12:e0006935. DOI: 10.1371/JOURNAL.PNTD.0006935
Arcari P, Tapper N, Pfueller S. Regional variability in relationships between climate and dengue/DHF in Indonesia. Singap J Trop Geogr [Internet]. 2007;28(3):251–272. DOI: 10.1111/J.1467-9493.2007.00300.X
Rodríguez RC, Carrasquilla G, Porras A, Galera-Gelvez K, Yescas JGL, Rueda-Gallardo JA. The Burden of Dengue and the Financial Cost to Colombia, 2010–2012. Am J Trop Med Hyg [Internet]. 2016;94(5):1065–1072. DOI: 10.4269/AJTMH.15-0280
Freitas LP, Carabali M, Yuan M, Jaramillo-Ramirez GI, García Balaguera C, Restrepo BN, et al. Spatio-temporal clusters and patterns of spread of dengue, chikungunya, and Zika in Colombia. PLoS Negl Trop Dis [Internet]. 2022;16(8):e0010334. DOI: 10.1371/JOURNAL.PNTD.0010334
Cuéllar L, Concepción M, Ramírez B, Álvarez ÁM, Díaz C. Los sistemas de información geográfica y su empleo en un sistema de vigilancia integrado para la prevención del dengue en un municipio de ciudad de La Habana. GeoFocus [Internet]. 2014;(9):166–183. Available from: https://www.geofocus.org/index.php/geofocus/article/view/186
Ordoñez-Sierra G, Sarmiento-Senior D, Jaramillo Gomez JF, Giraldo P, Porras Ramírez A, Olano VA. Multilevel analysis of social, climatic and entomological factors that influenced dengue occurrence in three municipalities in Colombia. One Health [Internet]. 2021;12:100234. DOI: 10.1016/J.ONEHLT.2021.100234
Eastin MD, Delmelle E, Casas I, Wexler J, Self C. Intra- and Interseasonal Autoregressive Prediction of Dengue Outbreaks Using Local Weather and Regional Climate for a Tropical Environment in Colombia. Am J Trop Med Hyg [Internet]. 2014;91(3):598–610. DOI: 10.4269/AJTMH.13-0303
Corporación Autónoma Regional del Valle del Cauca (CVC). Portal GeoCVC [Internet]. Valle del Cauca (COL): CVC; 2014. Available from: https://geo.cvc.gov.co
Rodriguez-Morales AJ, Galindo-Marquez ML, García-Loaiza CJ, Sabogal-Roman JA, Marin-Loaiza S, Ayala AF, et al. Mapping Zika virus disease incidence in Valle del Cauca. Infection [Internet]. 2017;45(1):93–102. DOI: 10.1007/S15010-016-0948-1
Rico-Mendoza A, Porras-Ramírez A, Chang A, Encinales L, Lynch R. Co-circulation of dengue, chikungunya, and Zika viruses in Colombia from 2008 to 2018. Rev Panam Salud Publica [Internet]. 2019;43:e49. DOI: 10.26633/RPSP.2019.49
Villamil-Gómez W, Restom Merlano J, Bonilla-Aldana K, Salas-Matta LA, Rodríguez-Morales AJ. Arbovirosis endemoepidémicas. Medicine - Programa de Formación Médica Continuada Acreditado. 2022;13(58):3398–3414. DOI: 10.1016/J.MED.2022.05.030
Caicedo-Hurtado MI, Castillo-Valencia M. Tipologías de pobreza en Cali: un análisis con base en el SISBEN. Tendencias [Internet]. 2021;22(1):39–70. DOI: 10.22267/RTEND.202102.154
Santos LLM, de Aquino EC, Fernandes SM, Ternes YMF, Feres VCR. Dengue, chikungunya, and Zika virus infections in Latin America and the Caribbean: a systematic review. Rev Panam Salud Publica [Internet]. 2023;47:e34. DOI: 10.26633/RPSP.2023.34
Gomes Mol MP, Matos Quieroz JT, Gomes J, Heller L. Gestión adecuada de los residuos sólidos como factor de protección contra los casos de dengue. Rev Panam Salud Publica [Internet]. 2020;44:e22. DOI: 10.26633/RPSP.2020.22
Krystosik AR, Curtis A, Labeaud AD, Dávalos DM, Pacheco R, Buritica P, et al. Neighborhood Violence Impacts Disease Control and Surveillance: Case Study of Cali, Colombia from 2014 to 2016. Int J Environ Res Public Health [Internet]. 2018;15(10):2144. DOI: 10.3390/IJERPH15102144
Delmelle E, Hagenlocher M, Kienberger S, Casas I. A spatial model of socioeconomic and environmental determinants of dengue fever in Cali, Colombia. Acta Trop [Internet]. 2016;164:169–176. DOI: 10.1016/J.ACTATROPICA.2016.08.028
Krystosik AR, Curtis A, Buritica P, Ajayakumar J, Squires R, Dávalos D, et al. Community context and sub-neighborhood scale detail to explain dengue, chikungunya and Zika patterns in Cali, Colombia. PLoS ONE [Internet]. 2017;12(8):e0181208. DOI: 10.1371/JOURNAL.PONE.0181208
Espinoza-Gomez F, Newton-Sanchez OA, Nava-Zavala AH, Zavala-Cerna MG, Rojas-Larios F, Delgado-Enciso I, et al. Demographic and climatic factors associated with dengue prevalence in a hyperendemic zone in Mexico: an empirical approach. Trans R Soc Trop Med Hyg [Internet]. 2021;115:63–73. DOI: 10.1093/TRSTMH/TRAA083
Bhatia S, Bansal D, Patil S, Pandya S, Ilyas QM, Imran S. A Retrospective Study of Climate Change Affecting Dengue: Evidences, Challenges and Future Directions. Front Public Health [Internet]. 2022;10:884645. DOI: 10.3389/FPUBH.2022.884645
Nguyen VH, Tuyet-Hanh TT, Mulhall J, Van Minh H, Duong TQ, Van Chien N, et al. Deep learning models for forecasting dengue fever based on climate data in Vietnam. PLoS Negl Trop Dis [Internet]. 2022;16(6):e0010509. DOI: 10.1371/JOURNAL.PNTD.0010509
Li L, Fang Z, Zhou H, Tang Y, Wang X, Liang G, et al. Dengue Risk Forecast with Mosquito Vector: A Multicomponent Fusion Approach Based on Spatiotemporal Analysis. Comput Math Methods Med [Internet]. 2022;2022:2515432. DOI: 10.1155/2022/2515432
Cassab A, Morales V, Mattar S. Factores climáticos y casos de Dengue en Montería, Colombia. 2003-2008. Rev Salud Pública [Internet]. 2011;13(1):115–128. Available from: https://revistas.unal.edu.co/index.php/revsaludpublica/article/view/33540
Yavari Nejad F, Varathan KD. Identification of significant climatic risk factors and machine learning models in dengue outbreak prediction. BMC Med Inform Decis Mak [Internet]. 2021;21(1):141. DOI: 10.1186/S12911-021-01493-Y
Coalson JE, Anderson EJ, Santos EM, Garcia VM, Romine JK, Luzingu JK, et al. The Complex Epidemiological Relationship between Flooding Events and Human Outbreaks of Mosquito-Borne Diseases: A Scoping Review. Environ Health Perspect [Internet]. 2021;129(9):096002. DOI: 10.1289/EHP8887
Dey SK, Rahman M, Howlader A, Siddiqi UR, Uddin KMM, Borhan R, Rahman EU. Prediction of dengue incidents using hospitalized patients, metrological and socio-economic data in Bangladesh: A machine learning approach. PLoS ONE [Internet]. 2022;17(7):e0270933. DOI: 10.1371/JOURNAL.PONE.0270933
Organización Panamericana de la Salud. Estrategia para la prevención y el control de las enfermedades arbovirales. Washington DC (USA): PAHO/WHO; 2016. Available from: https://iris.paho.org/handle/10665.2/31412
Desjardins MR, Casas I, Victoria AM, Carbonell D, Dávalos DM, Delmelle EM. Knowledge, attitudes, and practices regarding dengue, chikungunya, and Zika in Cali, Colombia. Health Place [Internet]. 2020;63:102339. DOI: 10.1016/J.HEALTHPLACE.2020.102339
Hernández Y, Castro M, Pérez S, Pérez A, Lloyd LS, Pérez D. Comunicación para la prevención de arbovirosis: adecuación de iniciativas de la OPS al contexto cubano. Rev Panam Salud Publica [Internet]. 2018;42:e146. DOI: 10.26633/RPSP.2018.146
Vega-Casanova J, Vega-Estarita L, Arroyave-Cabrera J. Lecciones aprendidas en la comunicación en salud y de riesgo en el manejo del virus del Chikungunya y otras enfermedades transmitidas por el mismo vector. Revista Científica Salud Uninorte [Internet]. 2016;32(1):35–55. DOI: 10.14482/SUN.32.1.8472
Ogunlade ST, Adekunle AI, Meehan MT, McBryde ES. Quantifying the impact of Wolbachia releases on dengue infection in Townsville, Australia. Sci Rep [Internet]. 2023;13(1):14932. DOI: 10.1038/s41598-023-42336-2
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