Assessing the Effect of Climate Variables on the Incidence of Dengue Cases in the Metropolitan Region of Panama City.

Vicente Navarro Valencia,Javier E Sanchez-Galan,Juan Miguel Pascale,Yamilka Díaz,Maciej F Boni

doi:10.3390/ijerph182212108

Abstract

The present analysis uses the data of confirmed incidence of dengue cases in the metropolitan region of Panama from 1999 to 2017 and climatic variables (air temperature, precipitation, and relative humidity) during the same period to determine if there exists a correlation between these variables. In addition, we compare the predictive performance of two regression models (SARIMA, SARIMAX) and a recurrent neural network model (RNN-LSTM) on the dengue incidence series. For this data from 1999–2014 was used for training and the three subsequent years of incidence 2015–2017 were used for prediction. The results show a correlation coefficient between the climatic variables and the incidence of dengue were low but statistical significant. The RMSE and MAPE obtained for the SARIMAX and RNN-LSTM models were 25.76, 108.44 and 26.16, 59.68, which suggest that any of these models can be used to predict new outbreaks. Although, it can be said that there is a limited role of climatic variables in the outputs the models. The value of this work is that it helps understand the behaviour of cases in a tropical setting as is the Metropolitan Region of Panama City, and provides the basis needed for a much needed early alert system for the region.

Highlights

As the global population grows and becomes more connected, human pathogens that were previously localized may expand their range and require greater collective action for disease control
First the incidence was tabulated per township size, using all data collected on dengue cases, including laboratory confirmed and epidemiological link cases
Dengue virus was reintroduced in Panama in 1993, since all four serotypes has circulating causing several outbreaks [7]

Summary

Introduction

As the global population grows and becomes more connected, human pathogens that were previously localized may expand their range and require greater collective action for disease control. One of the more likely candidates for geographic expansion is dengue virus (DENV), an Aedes-transmitted flavivirus that infects hundreds of millions of people per year [1] and is predicted to expand its range as the climate warms [2]. DENV circulates in the global tropics as four distinct serotypes (called DENV1, DENV2, DENV3 and DENV4) that show seasonal epidemic patterns, endemic behavior, and infrequent outbreaks, depending on the regional climate and altitude. All four serotypes of DENV have been circulating in the canal lands for more than 25 years [7]

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