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X Demographics
Mendeley readers
| Title |
A study of the correlation between dengue and weather in Kandy City, Sri Lanka (2003 -2012) and lessons learned
|
|---|---|
| Published in |
Infectious Diseases of Poverty, September 2015
|
| DOI | 10.1186/s40249-015-0075-8 |
| Pubmed ID | |
| Authors |
N D B Ehelepola, Kusalika Ariyaratne, W M N P Buddhadasa, Sunil Ratnayake, Malani Wickramasinghe |
| Abstract |
Weather variables affect dengue transmission. This study aimed to identify a dengue weather correlation pattern in Kandy, Sri Lanka, compare the results with results of similar studies, and establish ways for better control and prevention of dengue. We collected data on reported dengue cases in Kandy and mid-year population data from 2003 to 2012, and calculated weekly incidences. We obtained daily weather data from two weather stations and converted it into weekly data. We studied correlation patterns between dengue incidence and weather variables using the wavelet time series analysis, and then calculated cross-correlation coefficients to find magnitudes of correlations. We found a positive correlation between dengue incidence and rainfall in millimeters, the number of rainy and wet days, the minimum temperature, and the night and daytime, as well as average, humidity, mostly with a five- to seven-week lag. Additionally, we found correlations between dengue incidence and maximum and average temperatures, hours of sunshine, and wind, with longer lag periods. Dengue incidences showed a negative correlation with wind run. Our results showed that rainfall, temperature, humidity, hours of sunshine, and wind are correlated with local dengue incidence. We have suggested ways to improve dengue management routines and to control it in these times of global warming. We also noticed that the results of dengue weather correlation studies can vary depending on the data analysis. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 176 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 1% |
| Bhutan | 1 | <1% |
| Brazil | 1 | <1% |
| Unknown | 172 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 25 | 14% |
| Researcher | 24 | 14% |
| Student > Master | 21 | 12% |
| Student > Ph. D. Student | 15 | 9% |
| Student > Postgraduate | 9 | 5% |
| Other | 26 | 15% |
| Unknown | 56 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 31 | 18% |
| Agricultural and Biological Sciences | 16 | 9% |
| Nursing and Health Professions | 14 | 8% |
| Environmental Science | 12 | 7% |
| Mathematics | 8 | 5% |
| Other | 32 | 18% |
| Unknown | 63 | 36% |