Effects of climatological parameters in modeling and forecasting seasonal influenza transmission in Abidjan, Cote d’Ivoire
Abstract Background In temperate regions, influenza epidemics occur in the winter and correlate with certain climatological parameters. In African tropical regions, the effects of climatological parameters on influenza epidemics are not well defined. This study aims to identify and model the effects...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2016-09-01
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| Series: | BMC Public Health |
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| Online Access: | http://link.springer.com/article/10.1186/s12889-016-3503-1 |
| _version_ | 1811263835230699520 |
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| author | A.K. N’gattia D. Coulibaly N. Talla Nzussouo H.A. Kadjo D. Chérif Y. Traoré B.K. Kouakou P.D. Kouassi K.D. Ekra N.S. Dagnan T. Williams I. Tiembré |
| author_facet | A.K. N’gattia D. Coulibaly N. Talla Nzussouo H.A. Kadjo D. Chérif Y. Traoré B.K. Kouakou P.D. Kouassi K.D. Ekra N.S. Dagnan T. Williams I. Tiembré |
| author_sort | A.K. N’gattia |
| collection | DOAJ |
| description | Abstract Background In temperate regions, influenza epidemics occur in the winter and correlate with certain climatological parameters. In African tropical regions, the effects of climatological parameters on influenza epidemics are not well defined. This study aims to identify and model the effects of climatological parameters on seasonal influenza activity in Abidjan, Cote d’Ivoire. Methods We studied the effects of weekly rainfall, humidity, and temperature on laboratory-confirmed influenza cases in Abidjan from 2007 to 2010. We used the Box-Jenkins method with the autoregressive integrated moving average (ARIMA) process to create models using data from 2007–2010 and to assess the predictive value of best model on data from 2011 to 2012. Results The weekly number of influenza cases showed significant cross-correlation with certain prior weeks for both rainfall, and relative humidity. The best fitting multivariate model (ARIMAX (2,0,0) _RF) included the number of influenza cases during 1-week and 2-weeks prior, and the rainfall during the current week and 5-weeks prior. The performance of this model showed an increase of >3 % for Akaike Information Criterion (AIC) and 2.5 % for Bayesian Information Criterion (BIC) compared to the reference univariate ARIMA (2,0,0). The prediction of the weekly number of influenza cases during 2011–2012 with the best fitting multivariate model (ARIMAX (2,0,0) _RF), showed that the observed values were within the 95 % confidence interval of the predicted values during 97 of 104 weeks. Conclusion Including rainfall increases the performances of fitted and predicted models. The timing of influenza in Abidjan can be partially explained by rainfall influence, in a setting with little change in temperature throughout the year. These findings can help clinicians to anticipate influenza cases during the rainy season by implementing preventive measures. |
| first_indexed | 2024-04-12T19:52:13Z |
| format | Article |
| id | doaj.art-a0e86777e5a5427994d6d3f6bbc40de7 |
| institution | Directory Open Access Journal |
| issn | 1471-2458 |
| language | English |
| last_indexed | 2024-04-12T19:52:13Z |
| publishDate | 2016-09-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Public Health |
| spelling | doaj.art-a0e86777e5a5427994d6d3f6bbc40de72022-12-22T03:18:46ZengBMCBMC Public Health1471-24582016-09-011611710.1186/s12889-016-3503-1Effects of climatological parameters in modeling and forecasting seasonal influenza transmission in Abidjan, Cote d’IvoireA.K. N’gattia0D. Coulibaly1N. Talla Nzussouo2H.A. Kadjo3D. Chérif4Y. Traoré5B.K. Kouakou6P.D. Kouassi7K.D. Ekra8N.S. Dagnan9T. Williams10I. Tiembré11Department of Epidemiology, Institut National d’Hygiène PubliqueDepartment of Epidemiology, Institut National d’Hygiène PubliqueInfluenza Division, U.S. Centers for Disease Control and PreventionDepartment of Virology, Respiratory Diseases, Pasteur InstituteDepartment of Epidemiology, Institut National d’Hygiène PubliqueDepartment of Epidemiology, Institut National d’Hygiène PubliqueDepartment of Virology, Respiratory Diseases, Pasteur InstituteDepartment of Epidemiology, Institut National d’Hygiène PubliqueDepartment of Epidemiology, Institut National d’Hygiène PubliqueDepartment of Epidemiology, Institut National d’Hygiène PubliqueInfluenza Division, U.S. Centers for Disease Control and PreventionDepartment of Epidemiology, Institut National d’Hygiène PubliqueAbstract Background In temperate regions, influenza epidemics occur in the winter and correlate with certain climatological parameters. In African tropical regions, the effects of climatological parameters on influenza epidemics are not well defined. This study aims to identify and model the effects of climatological parameters on seasonal influenza activity in Abidjan, Cote d’Ivoire. Methods We studied the effects of weekly rainfall, humidity, and temperature on laboratory-confirmed influenza cases in Abidjan from 2007 to 2010. We used the Box-Jenkins method with the autoregressive integrated moving average (ARIMA) process to create models using data from 2007–2010 and to assess the predictive value of best model on data from 2011 to 2012. Results The weekly number of influenza cases showed significant cross-correlation with certain prior weeks for both rainfall, and relative humidity. The best fitting multivariate model (ARIMAX (2,0,0) _RF) included the number of influenza cases during 1-week and 2-weeks prior, and the rainfall during the current week and 5-weeks prior. The performance of this model showed an increase of >3 % for Akaike Information Criterion (AIC) and 2.5 % for Bayesian Information Criterion (BIC) compared to the reference univariate ARIMA (2,0,0). The prediction of the weekly number of influenza cases during 2011–2012 with the best fitting multivariate model (ARIMAX (2,0,0) _RF), showed that the observed values were within the 95 % confidence interval of the predicted values during 97 of 104 weeks. Conclusion Including rainfall increases the performances of fitted and predicted models. The timing of influenza in Abidjan can be partially explained by rainfall influence, in a setting with little change in temperature throughout the year. These findings can help clinicians to anticipate influenza cases during the rainy season by implementing preventive measures.http://link.springer.com/article/10.1186/s12889-016-3503-1ModelingInfluenzaClimatological parametersAbidjan |
| spellingShingle | A.K. N’gattia D. Coulibaly N. Talla Nzussouo H.A. Kadjo D. Chérif Y. Traoré B.K. Kouakou P.D. Kouassi K.D. Ekra N.S. Dagnan T. Williams I. Tiembré Effects of climatological parameters in modeling and forecasting seasonal influenza transmission in Abidjan, Cote d’Ivoire BMC Public Health Modeling Influenza Climatological parameters Abidjan |
| title | Effects of climatological parameters in modeling and forecasting seasonal influenza transmission in Abidjan, Cote d’Ivoire |
| title_full | Effects of climatological parameters in modeling and forecasting seasonal influenza transmission in Abidjan, Cote d’Ivoire |
| title_fullStr | Effects of climatological parameters in modeling and forecasting seasonal influenza transmission in Abidjan, Cote d’Ivoire |
| title_full_unstemmed | Effects of climatological parameters in modeling and forecasting seasonal influenza transmission in Abidjan, Cote d’Ivoire |
| title_short | Effects of climatological parameters in modeling and forecasting seasonal influenza transmission in Abidjan, Cote d’Ivoire |
| title_sort | effects of climatological parameters in modeling and forecasting seasonal influenza transmission in abidjan cote d ivoire |
| topic | Modeling Influenza Climatological parameters Abidjan |
| url | http://link.springer.com/article/10.1186/s12889-016-3503-1 |
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