Optimal Lead Time for Dengue Forecast |
Prediction of a rise in dengue cases and sufficient time to allow timely decisions |
Singapore |
Hii, Y. L. et al. (2012HII Y, ROCKLÖV J, WALL S, NG L, TANG C & NG N. 2012. Optimal Lead Time for Dengue Forecast. Accessed 13 Jul 2023. Available at: Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3475667/ . https://www.ncbi.nlm.nih.gov/pmc/article...
) |
No |
Climate and Dengue Fever: Early warning based on temperature and rainfall |
Forecast of dengue cases based on temperature and cumulative rainfall |
Singapore |
Hii, Y. L. (2013HII Y. 2013. Climate and Dengue Fever: Early warning based on temperature and rainfall. Accessed 16 Jul 2023. Available at: Available at: https://www.diva-portal.org/smash/get/diva2:615782/FULLTEXT02.pdf . https://www.diva-portal.org/smash/get/di...
) |
No |
Impact of meteorological factors on the spatiotemporal patterns of dengue fever incidence |
This study presents a novel integration of a distributed lag nonlinear model and Markov random fields to assess the nonlinear lagged effects of weather variables on temporal dynamics of dengue fever and to account for the geographical heterogeneity |
Taiwan |
Chien, L-C.; Yu, H-L. (2014CHIEN LC & YU HL. 2014. Impact of meteorological factors on the spatiotemporal patterns of dengue fever incidence. Environment International, 73: 46-56. Available at: https://www.sciencedirect.com/science/article/pii/S0160412014002025. https://www.sciencedirect.com/science/ar...
) |
Yes |
Data mining techniques for predicting dengue outbreak in geospatial domain using weather parameters for New Delhi, India |
Forecast of dengue cases based on data mining techniques, like as multi-regression and Naive-Bayes approach to model the relation between dengue cases and weather parameters. |
India |
Agarwal, N. et al. (2018AGARWAL N, KOTI S, SARAN S & KUMAR S. 2018. Data mining techniques for predicting dengue outbreak in geospatial domain using weather parameters for New Delhi, India. Accessed 13 Jul 2023. Available at: Available at: https://www.jstor.org/stable/26495794 . https://www.jstor.org/stable/26495794...
) |
No |
Ensemble method for dengue prediction |
Forecast of dengue cases using ensemble models created by combining three disparate types of component models: two-dimensional Method of Analogues models incorporating both dengue and climate data; additive seasonal Holt-Winters models with and without wavelet smoothing; and simple historical models. |
Peru and Puerto Rico |
Buczak, A. L. et al. (2018BUCZAK A, BAUGHER B, MONIZ L, BAGLEY T, BABIN S & GUVEN E. 2018. Ensemble method for dengue prediction. PLoS ONE, 13(1): 0189988. Available at: https://doi.org/10.1371/journal.pone.0189988. https://doi.org/10.1371/journal.pone.018...
) |
Yes |
Revisiting the role of rainfall variability and its interactive effects with the built environment in urban dengue outbreaks. |
This study identifies the meteorological measurements most relevant to dengue variations, namely weekly minimum temperature, and weekly maximum 24-hour precipitation, obtaining the relative risk (RR) in relation to the number of human cases and a continuous lag period of 20 weeks. |
Taiwan |
Chen, T-H. K.; Chen, V. Y-J.; Wen, T. (2018CHEN TH, CHEN VJ & WEN TH. 2018. Revisiting the role of rainfall variability and its interactive effects with the built environment in urban dengue outbreaks. Applied Geography, 101: 14-22. Available at: https://doi.org/10.1016/j.apgeog.2018.10.005. https://doi.org/10.1016/j.apgeog.2018.10...
) |
Yes |
A combination of climatic conditions determines major within-season dengue outbreaks in Guangdong Province, China |
Forecast of dengue cases based on multi-scale modeling framework, parameterized by available weather, vector and human case data. |
China |
Wang X, et al. (2019WANG X, TANG S, WU J, XIAO Y & CHEKE R. 2019. A combination of climatic conditions determines major within-season dengue outbreaks in Guangdong Province, China. Accessed 15 Jul 2023. Available at: Available at: https://parasitesandvectors.biomedcentral.com/articles/10.1186/s13071-019-3295-0 . https://parasitesandvectors.biomedcentra...
) |
No |
Prediction of dengue outbreaks in Kerala state using disease surveillance and meteorological data |
Forecast of dengue cases based on multivariate (temperature and cumulative rainfall) models. |
India |
Nayak, S. D. P.; Narayan, K. A. (2020NAYAK S & NARAYAN K. 2019. Prediction of dengue outbreaks in Kerala state using disease surveillance and meteorological data. International Journal of Community Medicine and Public Health. 6(10): 4392-4400. Available at: https://www.ijcmph.com/index.php/ijcmph/article/view/5262. https://www.ijcmph.com/index.php/ijcmph/...
) |
Yes |
An Association between Rainy Days with Clinical Dengue Fever in Dhaka, Bangladesh: Findings from a Hospital Based Study |
Identification of the influence of climatic variability on the occurrence of clinical dengue requiring hospitalization |
Bangladesh |
Rahman, K. M. et al. (2020RAHMAN K, SHARKER Y, RUMI R, KHAN M, SHOMIK M, RAHMAN M, BILLAH S, RAHMAN M, STREATFIELD P, HARLEY D & LUBY S. 2020. An Association between Rainy Days with Clinical Dengue Fever in Dhaka. Accessed 11 Jul 2023. Available at: Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7765799/ . https://www.ncbi.nlm.nih.gov/pmc/article...
) |
No |
An accurate mathematical model predicting number of dengue cases in tropics. |
Forecast of dengue cases using model based on machine learning technique and multivariate approach. |
Sri Lanka |
Edussuriya, C.; Deegalla, S.; Gawarammana, I. (2021EDUSSURIYA C, DEEGALLA S & GAWARAMMANA I. 2021. An accurate mathematical model predicting number of dengue cases in tropics. PloS Negl Trop Dis, 15(11): 0009756. Available at: https://doi.org/10.1371/journal.pntd.0009756. https://doi.org/10.1371/journal.pntd.000...
) |
Yes |
Dengue disease dynamics are modulated by the combined influences of precipitation and landscape: A machine learning approach |
Forecast of dengue cases using a model-based (MOB) recursive partitioning, implemented to test the combined influences of landscape and climate factors on ovitrap index (vector mosquito occurrence) and dengue incidence. |
Philippines |
Micanaldo, E. F. et al. (2021MICANALDO E, CARVAJAL T, RYO M, NUKAZAWA K, AMALIN D & WATANABE K. 2021. Dengue disease dynamics are modulated by the combined influences of precipitation and landscape: A machine learning approach, Science of the Total Environment 792. Accessed 16 Jul 2023. Available at: Available at: https://doi.org/10.1016/j.scitotenv.2021.148406 . https://doi.org/10.1016/j.scitotenv.2021...
) |
Yes |
Predicting the number of dengue cases 8 weeks after |
Forecast of dengue cases based on daily temperature and daily rainfall |
Singapore |
Ying, C. X. et al. (2021YING C, SIN K, YU Y, ARIBOU Z & YUNJUE Z. 2021. Predicting the number of dengue cases 8 weeks after. Accessed 12 Jul 2023. Available at: Available at: https://medium.com/@conankoh/predicting-the-number-of-dengue-cases-8-weeks-after-6ce91e925b1a . https://medium.com/@conankoh/predicting-...
) |
No |
Modeling present and future climate risk of dengue outbreak, a case study in New Caledonia |
Forecast of dengue cases based on statistical estimation and a machine learning classifier to estimate the probability for a week to be epidemic under current climate data and this probability was then estimated under climate change scenarios |
New Caledonia |
Ochida, N. et al. (2022OCHIDA N, MANGEAS M, DUPONT-ROUZEYROL M, DUTHEIL C, FORFAIT C, PELTIER A, DESCLOUX E & MENKES C. 2022. Modeling present and future climate risk of dengue outbreak, a case study in New Caledonia. Accessed 10 Jul 2023. Available at: Available at: https://ehjournal.biomedcentral.com/articles/10.1186/s12940-022-00829-z . https://ehjournal.biomedcentral.com/arti...
) |
No |
Prediction of dengue fever outbreaks using climate variability and Markov chain Monte Carlo techniques in a stochastic susceptible-infected-removed model |
Forecast of dengue cases based on climate, geography, and environmental factors |
Singapore |
Martheswaran, T. K. et al. (2022MARTHESWARAN T, HAMDI H, AL-BARTY A, ZAID A & DAS B. 2022. Prediction of dengue fever outbreaks using climate variability and Markov chain Monte Carlo techniques in a stochastic susceptible-infected-removed model. Accessed 11. Available at: https://www.nature.com/articles/s41598-022-09489-y. https://www.nature.com/articles/s41598-0...
) |
No |
The practicality of Malaysia dengue outbreak forecasting model as an early warning system |
Forecast of dengue cases using and comparing following forecasting models: Autoregressive Distributed Lag (ADL), Hierarchical Forecasting (Bottom-up and Optimal combination) and three Machine Learning methods: (Artificial Neural Network (ANN), Support Vector Machine (SVM) and Random Forest) |
Malaysia |
Ismail, S. et al. (2022ISMAIL S, FILDES R, AHMAD R, MOHAMAD-ALI W & OMAR T. 2022. The practicality of Malaysia dengue outbreak forecasting model as an early warning system. Accessed 17 Jul 2023. Available at: Available at: https://www.sciencedirect.com/science/article/pii/S2468042722000604 . https://www.sciencedirect.com/science/ar...
) |
Yes |
Análise espacial da distribuição dos casos de dengue e a relação com fatores entomológicos, ambientais e socioeconômicos. |
This study confirms the characteristic of opportunist species that was already registered for the Aedes aegypti, especially in relation to its ability to quickly adapt to take advantage of different types of containers in the most varied stages of its life. |
Brazil |
Scandar, S. A. S. (2007SCANDAR S. 2007. Análise espacial da distribuição dos casos de dengue e a relação com fatores entomológicos, ambientais e socioeconômicos. Accessed 15 Jul 2023. Available at: Available at: https://www.teses.usp.br/teses/disponiveis/6/6132/tde-19032008-155959/publico/Sirle18042007.pdf . https://www.teses.usp.br/teses/disponive...
) |
Yes |
Modelo Econométrico para Previsão da Incidência de Dengue no Município do Rio de Janeiro. |
Forecast of dengue cases based on an econometric model estimated from time series of dengue cases and climate variables. |
Brazil |
Amaral, M. R. S.; Vaughon, A. P.; Duarte, K. S. (2009AMARAL M, VAUGHON A & DUARTE K. 2009. Modelo Econométrico para Previsão da Incidência de Dengue no Município do Rio de Janeiro. Accessed 13 Jul 2023. Available at: Available at: http://www.din.uem.br/sbpo/sbpo2009/artigos/56147.pdf . http://www.din.uem.br/sbpo/sbpo2009/arti...
) |
Yes |
Interação entre fatores socioeconômicos ambientais e ocorrência de casos da dengue no Ceará |
Analyze through regression models the impact of environmental socioeconomic variables on notification of dengue cases. |
Brazil |
Sousa, W. L. et al. (2016SOUSA W, ASEVEDO M, ARAUJO J & DIAS J. 2016. Interação entre fatores socioeconômicos ambientais e ocorrência de casos da dengue no Ceará. Accessed 19 Jul 2023. Available at: Available at: https://www.revistaespacios.com/a17v38n14/a17v38n14p31.pdf . https://www.revistaespacios.com/a17v38n1...
) |
Yes |
Analysis of climate factors and dengue incidence in the metropolitan region of Rio de Janeiro, Brazil |
This study examined the incidence of dengue fever related to the climate influence by using temperature and rainfall variables to create a mathematical model based on an auto-regressive moving average with exogenous inputs (ARMAX). |
Brazil |
Xavier L. L. et al. (2021XAVIER L, HONÓRIO N, PESSANHA J & PEITER P. 2021. Analysis of climate factors and dengue incidence in the metropolitan region of Rio de Janeiro, Brazil. PLoS ONE, 16(5): 0251403. Available at: https://doi.org/10.1371/journal.pone.0251403. https://doi.org/10.1371/journal.pone.025...
) |
Yes |
Impact of Climate Change on Human Infectious Diseases: Dengue |
It is analyzed the effect of seasonal factors and the relationship between climate variables and dengue risk |
Brazil |
Souza, A.; Abreu, M. C.; Oliveira-Júnior, J. F. (2021SOUZA A, ABREU M & OLIVEIRA-JÚNIOR J. 2021. Impact of Climate Change on Human Infectious Diseases: Dengue. Accessed 16 Jul 2023. Available at: Available at: https://www.scielo.br/j/babt/a/pnS3BcrVbdFPPhPXHtynvBS/# . https://www.scielo.br/j/babt/a/pnS3BcrVb...
) |
No |
Influência do Clima na Incidência de Doenças Causadas pelo Aedes Aegypti no Município de Manaus/AM, Brasil |
Forecast of dengue cases based on an ARIMAX model estimated from time series of dengue cases, maximum temperature and rainfall. |
Brazil |
Santos, P. S. et al. (2021SANTOS P, LISBINSKI F, MARCHEZINI B & ADAMI A. 2021. Influência do clima na incidência de doenças causadas pelo aedes aegypti no município de Manaus-AM, Brasil. Accessed 12 Jul 2023. Available at: Available at: https://brsa.org.br/wp-content/uploads/wpcf7-submissions/7233/artigo-dengue-enaber-id.pdf . https://brsa.org.br/wp-content/uploads/w...
) |
Yes |