Your search found 6 records
1 Briet, Olivier J. T.. 2004. Analysis of impacts of climate variability on malaria transmission in Sri Lanka and the development of an early-warning system. In WHO; WMO; UNEP. Workshop report of the Synthesis Workshop on Climate Variability, Climate Change and Health in Small-Island States, Bandos Island, Maldives, 1-4 December 2003. Geneva, Switzerland: WHO. pp.26-27.
(Location: IWMI-HQ Call no: IWMI 616.9362 G744 BRI Record No: H036048)
2 Briet, Olivier J. T.; Galappaththy, G. N. L.; Konradsen, Flemming; Amerasinghe, Priyanie H.; Amerasinghe, Felix Prashantha. 2005. Maps of the Sri Lanka malaria situation preceding the tsunami and key aspects to be considered in the emergency phase and beyond. Malaria Journal, 4(8):11p.
Malaria ; Maps ; Disease vectors ; Waterborne diseases ; Public health ; Natural disasters ; Reservoirs / Sri Lanka
(Location: IWMI-HQ Call no: IWMI 616.9362 G744 BRI Record No: H036727)
3 Briet, Olivier J. T.; Vounatsou, Penelope; Gunawardena, Dissanayake M.; Galappaththy, Gawrie N. L.; Amerasinghe, Priyanie H. 2008. Temporal correlation between malaria and rainfall in Sri Lanka. Malaria Journal, 7(77): 14p.
(Location: IWMI HQ Call no: IWMI 614.532 G744 BRI Record No: H041347)
Background: Rainfall data have potential use for malaria prediction. However, the relationship between rainfall and the number of malaria cases is indirect and complex. Methods: The statistical relationships between monthly malaria case count data series and monthly mean rainfall series (extracted from interpolated station data) over the period 1972 – 2005 in districts in Sri Lanka was explored in four analyses: cross-correlation; cross-correlation with pre-whitening; inter-annual; and seasonal inter-annual regression. Results: For most districts, strong positive correlations were found for malaria time series lagging zero to three months behind rainfall, and negative correlations were found for malaria time series lagging four to nine months behind rainfall. However, analysis with pre- whitening showed that most of these correlations were spurious. Only for a few districts, weak positive (at lags zero and one) or weak negative (at lags two to six) correlations were found in pre- whitened series. Inter-annual analysis showed strong negative correlations between malaria and rainfall for a group of districts in the centre-west of the country. Seasonal inter-annual analysis showed that the effect of rainfall on malaria varied according to the season and geography. Conclusion: Seasonally varying effects of rainfall on malaria case counts may explain weak overall cross-correlations found in pre-whitened series, and should be taken into account in malaria predictive models making use of rainfall as a covariate.
4 Briet, Olivier J. T.; Vounatsou, Penelope; Gunawardena, Dissanayake M.; Galappaththy, Gawrie N. L.; Amerasinghe, Priyanie H. 2008. Models for short term malaria prediction in Sri Lanka. Malaria Journal, 7(76):11p.
(Location: IWMI HQ Call no: IWMI 616.9362 BRI Record No: H041349)
5 Rajakaruna, R. S.; Amerasinghe, Priyanie H.; Galappaththy, G. N. L.; Konradsen, F.; Briet, Olivier J. T.; Alifrangis, M. 2008. Current status of malaria and anti-malarial drug resistance in Sri Lanka. Ceylon Journal of Science (Biological Sciences), 37(1):15-22.
(Location: IWMI HQ Call no: IWMI 614.532 G744 RAJ, PER Record No: H041484)
http://www.sljol.info/index.php/CJSBS/article/viewPDFInterstitial/493/531
https://vlibrary.iwmi.org/pdf/H041484.pdf
https://vlibrary.iwmi.org/pdf/H041484.pdf
Even though malaria continues to cause high morbidity and mortality in most of the malaria endemic countries in the world, it is currently not a major health problem in Sri Lanka. Despite the low malaria incidence, the development and spread of anti-malarial drug resistance, combined with a recent increase in the armed conflict hindering provision of effective health services will make it difficult to control malaria in Sri Lanka. Since chloroquine (CQ) resistant Plasmodium falciparum was first reported from Dambulla area in 1984, the number has increased to more than 50% observed in vivo from various endemic areas. In concordance with this, single nucleotide polymorphisms (SNPs) in genes of P. falciparum responsible for CQ resistance are present. A limited number of trials have investigated the efficacy of the second line drug, sulfadoxine/ pyrimethamine (SP) against P. falciparum and a few cases of resistance have been reported. Moreover, SNPs in P. falciparum genes responsible for SP resistance are present and may constitute a sign of evolving SP resistance development. For P. vivax, drug resistance is not yet recorded as a problem in Sri Lanka, however the prevalence of SP resistant SNPs in P. vivax populations seems high and may pose a risk despite that SP is not used directly against P. vivax infections. Continuous monitoring of drug efficacy in vivo, as well by measuring the prevalence of SNPs related to drug resistance are major issues to be addressed.
6 Briet, Olivier J. T.; Vounatsou, P.; Amerasinghe, Priyanie H. 2008. Malaria seasonality and rainfall seasonality in Sri Lanka are correlated in space. Geospatial Health, 2(2):183-190.
(Location: IWMI HQ Call no: IWMI 614.532 G744 BRI Record No: H041642)
Powered by DB/Text WebPublisher, from
