scholarly journals The correlation between three teleconnections and leptospirosis incidence in the Kandy District, Sri Lanka, 2004–2019

2021 ◽  
Vol 49 (1) ◽  
Author(s):  
N. D. B. Ehelepola ◽  
Kusalika Ariyaratne ◽  
A. M. S. M. C. M. Aththanayake ◽  
Kamalanath Samarakoon ◽  
H. M. Arjuna Thilakarathna
Keyword(s):  
Time Series ◽  
Sri Lanka ◽  
Wavelet Analysis ◽  
Southern Oscillation ◽  
Population Data ◽  
Enso Modoki ◽  
Cross Correlation Analysis ◽  
Teleconnection Indices ◽  
Weather Parameters ◽  
Time Lagged

Abstract 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.

scholarly journals The interrelationship between meteorological parameters and leptospirosis incidence in Hambantota district, Sri Lanka 2008–2017 and practical implications

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245366
Author(s):  
N. D. B. Ehelepola ◽  
Kusalika Ariyaratne ◽  
D. S. Dissanayake
Keyword(s):  
Time Series ◽  
Sri Lanka ◽  
Wavelet Analysis ◽  
Soil Temperature ◽  
Cross Correlation ◽  
Evaporation Rate ◽  
Meteorological Parameters ◽  
Long Term Study ◽  
Cross Correlation Analysis ◽  
Weather Parameters

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.

scholarly journals Wavelet analysis of the singular spectral reconstructed time series to study the imprints of solar–ENSO–geomagnetic activity on Indian climate

2016 ◽  
Vol 23 (5) ◽  
pp. 361-374 ◽  
Author(s):  
Sri Lakshmi Sunkara ◽  
Rama Krishna Tiwari
Keyword(s):  
Time Series ◽  
Wavelet Analysis ◽  
Tree Ring ◽  
Geomagnetic Activity ◽  
Southern Oscillation ◽  
Temperature Variability ◽  
Temperature Record ◽  
Western Himalayas ◽  
Reconstructed Time Series ◽  
Indian Temperature

Abstract. To study the imprints of the solar–ENSO–geomagnetic activity on the Indian subcontinent, we have applied singular spectral analysis (SSA) and wavelet analysis to the tree-ring temperature variability record from the Western Himalayas. Other data used in the present study are the solar sunspot number (SSN), geomagnetic indices (aa index), and the Southern Oscillation Index (SOI) for the common time period of 1876–2000. Both SSA and wavelet spectral analyses reveal the presence of 5–7-year short-term ENSO variations and the 11-year solar cycle, indicating the possible combined influences of solar–geomagnetic activities and ENSO on the Indian temperature. Another prominent signal corresponding to 33-year periodicity in the tree-ring record suggests the Sun-temperature variability link probably induced by changes in the basic state of the Earth's atmosphere. In order to complement the above findings, we performed a wavelet analysis of SSA reconstructed time series, which agrees well with our earlier results and increases the signal-to-noise ratio, thereby showing the strong influence of solar–geomagnetic activity and ENSO throughout the entire period. The solar flares are considered responsible for causing the atmospheric circulation patterns. The net effect of solar–geomagnetic processes on the temperature record might suggest counteracting influences on shorter (about 5–6-year) and longer (about 11–12-year) timescales. The present analyses suggest that the influence of solar activities on the Indian temperature variability operates in part indirectly through coupling of ENSO on multilateral timescales. The analyses, hence, provide credible evidence of teleconnections of tropical Pacific climatic variability and Indian climate ranging from inter-annual to decadal timescales and also suggest the possible role of exogenic triggering in reorganizing the global Earth–ocean–atmospheric systems.

scholarly journals Hospital presentations for self-poisoning during COVID-19 in Sri Lanka: an interrupted time-series analysis

2021 ◽  
Author(s):  
Duleeka Knipe ◽  
Tharuka Silva ◽  
Azra Aroos ◽  
Lalith Senarathna ◽  
Nirosha Madhuwanthi Hettiarachchi ◽  
...  
Keyword(s):  
Time Series ◽  
Sri Lanka ◽  
Time Series Analysis ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Series Analysis

Following the infection dynamics of the tropical trematode Oligogonotylus mayae in its intermediate and definitive hosts for 13 years

2020 ◽  
Vol 94 ◽  
Author(s):  
A.L. May-Tec ◽  
N.A. Herrera-Castillo ◽  
V.M. Vidal-Martínez ◽  
M.L. Aguirre-Macedo
Keyword(s):  
Time Series ◽  
Cross Correlation ◽  
Southern Oscillation ◽  
Fish Host ◽  
Snail Host ◽  
Monthly Data ◽  
Infection Dynamics ◽  
Infection Parameters ◽  
Over Time

Abstract We present a time series of 13 years (2003–2016) of continuous monthly data on the prevalence and mean abundance of the trematode Oligogonotylus mayae for all the hosts involved in its life cycle. We aimed to determine whether annual (or longer than annual) environmental fluctuations affect these infection parameters of O. mayae in its intermediate snail host Pyrgophorus coronatus, and its second and definitive fish host Mayaheros urophthalmus from the Celestun tropical coastal lagoon, Yucatan, Mexico. Fourier time series analysis was used to identify infection peaks over time, and cross-correlation among environmental forcings and infection parameters. Our results suggest that the transmission of O. mayae in all its hosts was influenced by the annual patterns of temperature, salinity and rainfall. However, there was a biannual accumulation of metacercarial stages of O. mayae in M. urophthalmus, apparently associated with the temporal range of the El Niño-Southern Oscillation (five years) and the recovery of the trematode population after a devasting hurricane. Taking O. mayae as an example of what could be happening to other trematodes, it is becoming clear that environmental forcings acting at long-term temporal scales affect the population dynamics of these parasites.

scholarly journals Hydrology of inland tropical lowlands: the Kapuas and Mahakam wetlands

2017 ◽  
Vol 21 (5) ◽  
pp. 2579-2594 ◽  
Author(s):  
Hidayat Hidayat ◽  
Adriaan J. Teuling ◽  
Bart Vermeulen ◽  
Muh Taufik ◽  
Karl Kastner ◽  
...  
Keyword(s):  
Time Series ◽  
Groundwater Recharge ◽  
Potential Evapotranspiration ◽  
Southern Oscillation ◽  
Tropical Rainfall Measuring Mission ◽  
Threshold Level ◽  
Phase Array ◽  
Catchment Scale ◽  
Tropical Regions ◽  
Rainfall Estimates

Abstract. Wetlands are important reservoirs of water, carbon and biodiversity. They are typical landscapes of lowland regions that have high potential for water retention. However, the hydrology of these wetlands in tropical regions is often studied in isolation from the processes taking place at the catchment scale. Our main objective is to study the hydrological dynamics of one of the largest tropical rainforest regions on an island using a combination of satellite remote sensing and novel observations from dedicated field campaigns. This contribution offers a comprehensive analysis of the hydrological dynamics of two neighbouring poorly gauged tropical basins; the Kapuas basin (98 700 km2) in West Kalimantan and the Mahakam basin (77 100 km2) in East Kalimantan, Indonesia. Both basins are characterised by vast areas of inland lowlands. Hereby, we put specific emphasis on key hydrological variables and indicators such as discharge and flood extent. The hydroclimatological data described herein were obtained during fieldwork campaigns carried out in the Kapuas over the period 2013–2015 and in the Mahakam over the period 2008–2010. Additionally, we used the Tropical Rainfall Measuring Mission (TRMM) rainfall estimates over the period 1998–2015 to analyse the distribution of rainfall and the influence of El-Niño – Southern Oscillation. Flood occurrence maps were obtained from the analysis of the Phase Array type L-band Synthetic Aperture Radar (PALSAR) images from 2007 to 2010. Drought events were derived from time series of simulated groundwater recharge using time series of TRMM rainfall estimates, potential evapotranspiration estimates and the threshold level approach. The Kapuas and the Mahakam lake regions are vast reservoirs of water of about 1000 and 1500 km2 that can store as much as 3 and 6.5 billion m3 of water, respectively. These storage capacity values can be doubled considering the area of flooding under vegetation cover. Discharge time series show that backwater effects are highly influential in the wetland regions, which can be partly explained by inundation dynamics shown by flood occurrence maps obtained from PALSAR images. In contrast to their nature as wetlands, both lowland areas have frequent periods with low soil moisture conditions and low groundwater recharge. The Mahakam wetland area regularly exhibits low groundwater recharge, which may lead to prolonged drought events that can last up to 13 months. It appears that the Mahakam lowland is more vulnerable to hydrological drought, leading to more frequent fire occurrences than in the Kapuas basin.

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