An investigation into the cyclical incidence of dengue fever.

The purpose of this research was to review the topic of dengue fever transmission and investigate the relationship between seasonal temperature fluctuations and cyclical dengue fever incidence. Data from Puerto Rico (1988-1992) were used to test the model proposed. Dengue fever is a viral disease caused by any one of four antigenically distinct serotypes. It is transmitted by Aedes mosquitoes and infects 80 million people per year. Currently, dengue is endemic in specific tropical and subtropical regions worldwide and epidemic dengue has been reported in the Americas, Asia and some Pacific Islands. Data for Puerto Rico were collected from the NCDC/NOAA and a study conducted by Perez et al. (1994). Multivariate linear regression analysis was used to determine if a relationship exists between the monthly mean temperature lagged and the monthly incidence of dengue fever in Puerto Rico. Statistical significance was achieved and a second-order model produced an R2 of 0.71. A residual analysis reveals positive autocorrelation, thus weakening the model's power to predict monthly dengue incidence. This suggests that other forces or factors related to the history of the herd immunity, the introduction of a new serotype, or demographic transitions are also influencing the cyclical transmission of dengue fever. Case clustering information, regional dengue distributions, and population density transformations must also be obtained in order to assess the forecasting ability of this model. Additional research is needed to avoid oversimplifying the problem. Without such attempts at establishing significant correlations, dengue prevention and control will remain a formidable task for many developing and developed countries.