BackgroundWeather 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.MethodWe 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.ResultsWe 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.ConclusionOur 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s40249-015-0075-8) contains supplementary material, which is available to authorized users.

Background: Leptospirosis is an important public health problem in Sri Lanka. Most people become infected by contact with leptospires in soil and in surface water. Survival of leptospires in the environment depends upon the moisture in soil, humidity, temperature and surface water. Leptospires are spread by flood water and waterways. Therefore, the weather of an area influences the leptospirosis incidence of that area. Objectives: To find out the correlations between the leptospirosis incidence in the district of Kandy, Sri Lanka, and local weather variables and then to explore the utility of the findings. Methods: We gathered data on reported leptospirosis cases in the Kandy district and mid-year population data and calculated weekly incidences for 2006 to 2015. Daily weather data from Katugastota weather station was obtained and converted into weekly data. We plotted time series graphs and observed the correlation between six aggregated weather parameters and leptospirosis incidence. Those weather parameters were rainfall, the count of wet days per week, days with rainfall >100 mm per week, minimum temperature, average temperature and average humidity. Then we looked for correlations between leptospirosis incidence and those weather parameters by performing the wavelet analysis. Results: Our wavelet analysis results show peaks of wet days per week, days with rainfall >100 mm per week, minimum temperature, average temperature and average humidity respectively after 2, 3, 13, 20 and 1 week lags were followed by peaks of leptospirosis incidence. Nadirs (troughs) of rainfall after a week were followed by nadirs of leptospirosis incidence. Conclusions: All weather parameters studied are correlated with local leptospirosis incidence and the climate in Kandy is conducive for leptospirosis transmission. Leptospirosis incidence in the Kandy district is high compared to the national and global incidence. Therefore, leptospirosis preventive work in Kandy deserves more attention, especially during months with favorable weather for leptospirosis transmission.

BackgroundTemperature, humidity, and other weather variables influence dengue transmission. Published studies show how the diurnal fluctuations of temperature around different mean temperatures influence dengue transmission. There are no published studies about the correlation between diurnal range of humidity and dengue transmission.ObjectiveThe goals of this study were to determine the correlation between dengue incidence and diurnal fluctuations of temperature and humidity in the Sri Lankan city of Kandy and to explore the possibilities of using that information for better control of dengue.DesignWe calculated the weekly dengue incidence in Kandy during the period 2003–2012, after collecting data on all of the reported dengue patients and estimated midyear populations. Data on daily maximum and minimum temperatures and night-time and daytime humidity were obtained from two weather stations, averaged, and converted into weekly data. The number of days per week with a diurnal temperature range (DTR) of >10°C and <10°C and the number of days per week with a diurnal humidity range (DHR) of >20 and <15% were calculated. Wavelet time series analysis was performed to determine the correlation between dengue incidence and diurnal ranges of temperature and humidity.ResultsThere were negative correlations between dengue incidence and a DTR >10°C and a DHR >20% with 3.3-week and 4-week lag periods, respectively. Additionally, positive correlations between dengue incidence and a DTR <10°C and a DHR <15% with 3- and 4-week lag periods, respectively, were discovered.ConclusionsThese findings are consistent with the results of previous entomological studies and theoretical models of DTR and dengue transmission correlation. It is important to conduct similar studies on diurnal fluctuations of humidity in the future. We suggest ways and means to use this information for local dengue control and to mitigate the potential effects of the ongoing global reduction of DTR on dengue incidence.

Background Leptospirosis is a bacterial zoonosis. Leptospirosis incidence (LI) in Sri Lanka is high. Infected animals pass leptospires to the environment with their urine. Leprospires' survival in the environment to infect a new host depends on meteorological factors. El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) modulate the weather in Sri Lanka. Objectives The determination of interrelationship between the LI in the Hambantota District, and local meteorological parameters, ENSO and IOD. Methods We acquired notified leptospirosis cases in the Hambantota District and population data. We calculated weekly leptospirosis incidences for 2008 to 2017.Weather data from two weather stations was obtained, averaged and converted into weekly data. We plotted time series graphs and observed the correlation between seven aggregated weather parameters and LI. We estimated cross-correlations between those weather parameters and LI. As our principal analysis we determined correlation between LI and seven local weather parameters, Nino 3.4, Nino4 and Dipole Mode Index (DMI) indices using wavelet analysis. Results Our wavelet analysis results showed troughs of minimum, maximum, mean temperatures, soil temperature, the evaporation rate, the duration of sunshine were followed by peaks in LI and peaks of rainfall followed by peaks of LI, all after lag periods. Our time series graphs and cross-correlation determination results are generally in agreement with these results. However there was no significant correlation between rainfall and LI in the cross-correlation analysis. There were peaks of LI following both peaks and troughs of DMI. There was no clear correlation between both Nino indices and LI. Discussion This may be the first long-term study demonstrating soil temperature, evaporation rate and IOD are correlating with LI. The correlation pattern of LI with temperature parameters differs from similar past studies and we explain the reasons. We propose ways to control high LI we observed after periods of weather favorable for transmission of leptospirosis.

BackgroundMeteorological factors affect dengue transmission. Mechanisms of the way in which different diurnal temperatures, ranging around different mean temperatures, influence dengue transmission were published after 2011.ObjectiveWe endeavored to determine the correlation between dengue incidence and diurnal temperature ranges (DTRs) in Colombo district, Sri Lanka, and to explore the possibilities of using our findings to improve control of dengue.DesignWe calculated the weekly dengue incidence in Colombo during 2005–2014, after data on all of the reported dengue patients and estimated mid-year populations were collected. We obtained daily maximum and minimum temperatures from two Colombo weather stations, averaged, and converted them into weekly data. Weekly averages of DTR versus dengue incidence graphs were plotted and correlations observed. The count of days per week with a DTR of >7.5°C and <7.5°C were also calculated. Wavelet time series analysis was performed to determine the correlation between dengue incidence and DTR.ResultsWe obtained a negative correlation between dengue incidence and a DTR>7.5°C with an 8-week lag period, and a positive correlation between dengue incidence and a DTR<7.5°C, also with an 8-week lag.ConclusionsLarge DTRs were negatively correlated with dengue transmission in Colombo district. We propose to take advantage of that in local dengue control efforts. Our results agree with previous studies on the topic and with a mathematical model of relative vectorial capacity of Aedes aegypti. Global warming and declining DTR are likely to favor a rise of dengue, and we suggest a simple method to mitigate this.

Background: Severe wheezing is a common medical emergency. Past studies have demonstrated associations between exacerbation of wheezing and meteorological factors and atmospheric pollution. There are no past studies from Sri Lanka that analyzed correlation between daily multiple meteorological variables and exacerbation of wheezing. Objectives: To determine the correlations between daily counts of patients nebulized at the Outpatient Department (OPD) of Teaching Hospital -Kandy (THK) and local meteorological variables, and to explore the utility of that information. Design: We considered daily counts of patients nebulized at the OPD of THK as an indicator of exacerbations of wheezing in the population catered to by this hospital. We determined the correlations between daily counts of patients nebulized at OPD and the following meteorological variables for four years: daily rainfall, minimum temperature, maximum temperature, diurnal temperature range, difference between maximum temperature and the temperature at 1800 hours, daytime humidity, nighttime humidity, barometric pressure and visibility. We utilized wavelet time series method for data analysis. Results: All nine meteorological parameters studied were correlated with the daily counts of patients nebulized with average lag periods ranging from 5 to 15 days. Peaks of daily rainfall, maximum temperature, diurnal temperature range, difference between maximum temperature and the temperature at 1800 hours and daytime humidity were followed by peaks of counts of patients nebulized (positive correlations). Troughs of minimum temperature, nighttime humidity, barometric pressure and visibility were followed by peaks of patients nebulized (negative correlations). Conclusions: The THK shall expect more patients with acute wheezing after extremes of weather. Minimum temperature has been consistently correlated with the exacerbation of respiratory symptoms in the past studies in other countries as well. Hence, prescribing the inhalation of more drugs on unusually cold days (prophylactically) may help prevent acute exacerbation of wheezing in patients on treatment for asthma and COPD.

Background Leptospirosis is a bacterial zoonosis. Leptospirosis incidence (LI) in Sri Lanka is high. Infected animals excrete leptospires into the environment via their urine. Survival of leptospires in the environment until they enter into a person and several other factors that influence leptospirosis transmission are dependent upon local weather. Past studies show that rainfall and other weather parameters are correlated with the LI in the Kandy district, Sri Lanka. El Niño Southern Oscillation (ENSO), ENSO Modoki, and the Indian Ocean Dipole (IOD) are teleconnections known to be modulating rainfall in Sri Lanka. There is a severe dearth of published studies on the correlations between indices of these teleconnections and LI. Methods We acquired the counts of leptospirosis cases notified and midyear estimated population data of the Kandy district from 2004 to 2019, respectively, from weekly epidemiology reports of the Ministry of Health and Department of Census and Statistics of Sri Lanka. We estimated weekly and monthly LI of Kandy. We obtained weekly and monthly teleconnection indices data for the same period from the National Oceanic and Atmospheric Administration (NOAA) of the USA and Japan Agency for Marine-Earth Science and Technology (JAMSTEC). We performed wavelet time series analysis to determine correlations with lag periods between teleconnection indices and LI time series. Then, we did time-lagged detrended cross-correlation analysis (DCCA) to verify wavelet analysis results and to find the magnitudes of the correlations detected. Results Wavelet analysis displayed indices of ENSO, IOD, and ENSO Modoki were correlated with the LI of Kandy with 1.9–11.5-month lags. Indices of ENSO showed two correlation patterns with Kandy LI. Time-lagged DCCA results show all indices of the three teleconnections studied were significantly correlated with the LI of Kandy with 2–5-month lag periods. Conclusions Results of the two analysis methods generally agree indicating that ENSO and IOD modulate LI in Kandy by modulating local rainfall and probably other weather parameters. We recommend further studies about the ENSO Modoki and LI correlation in Sri Lanka. Monitoring for extreme teleconnection events and enhancing preventive measures during lag periods can blunt LI peaks that may follow.

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