ABSTRACT
OBJECTIVE@#To investigate whether major dengue outbreaks in the last two decades in Kaohsiung follow a precise temporal pattern.@*METHODS@#Government daily lab-confirmed dengue case data from three major dengue outbreaks occurring during the last two decades in Kaohsiung in 2002, 2014 and 2015, is utilized to compute the corresponding weekly cumulative percentage of total case numbers. We divide each of the three time series data into two periods to examine the corresponding weekly cumulative percentages of case numbers for each period. Pearson's correlation coefficient was calculated to compare quantitatively the similarity between the temporal patterns of these three years.@*RESULTS@#Three cutoff points produce the most interesting comparisons and the most different outcomes. Pearson's correlation coefficient indicates quantitative discrepancies in the similarity between temporal patterns of the three years when using different cutoff points.@*CONCLUSIONS@#Temporal patterns in 2002 and 2014 are comparatively more similar in early stage. The 2015 outbreak started late in the year, but ended more like the outbreak in 2014, both with record-breaking number of cases. The retrospective analysis shows that the temporal dynamics of dengue outbreaks in Kaohsiung can strongly vary from one year to another, making it difficult to identify any common predictor.
ABSTRACT
Objective To investigate whether major dengue outbreaks in the last two decades in Kaohsiung follow a precise temporal pattern. Methods Government daily lab-confirmed dengue case data from three major dengue outbreaks occurring during the last two decades in Kaohsiung in 2002, 2014 and 2015, is utilized to compute the corresponding weekly cumulative percentage of total case numbers. We divide each of the three time series data into two periods to examine the corresponding weekly cumulative percentages of case numbers for each period. Pearson's correlation coefficient was calculated to compare quantitatively the similarity between the temporal patterns of these three years. Results Three cutoff points produce the most interesting comparisons and the most different outcomes. Pearson's correlation coefficient indicates quantitative discrepancies in the similarity between temporal patterns of the three years when using different cutoff points. Conclusions Temporal patterns in 2002 and 2014 are comparatively more similar in early stage. The 2015 outbreak started late in the year, but ended more like the outbreak in 2014, both with record-breaking number of cases. The retrospective analysis shows that the temporal dynamics of dengue outbreaks in Kaohsiung can strongly vary from one year to another, making it difficult to identify any common predictor.