Risks of malaria epidemics in relation to El Niño and Southern Oscillation (ENSO) events have been mapped and studied at global level. In India, where malaria is a major public health problem, no such effort has been undertaken that inter-relates El Niño, Indian Summer Monsoon Rainfall (ISMR) and malaria. The present study has been undertaken to find out the relationship between ENSO events, ISMR and intra-annual variability in malaria cases in India, which in turn could help mitigate the malaria outbreaks.
Correlation coefficients among ‘rainfall index’ (ISMR), ‘+ winter ONI’ (NDJF) and ‘malaria case index’ were calculated using annual state-level data for the last 22 years. The ‘malaria case index’ representing ‘relative change from mean’ was correlated to the 4 month (November–February) average positive Oceanic Niño Index (ONI). The resultant correlations between ‘+ winter ONI’ and ‘malaria case index’ were further analysed on geographical information system platform to generate spatial correlation map.
The correlation between ‘+ winter ONI’ and ‘rainfall index’ shows that there is great disparity in effect of ENSO over ISMR distribution across the country. Correlation between ‘rainfall index’ and ‘malaria case index’ shows that malaria transmission in all geographical regions of India are not equally affected by the ISMR deficit or excess. Correlation between ‘+ winter ONI’ and ‘malaria case index’ was found ranging from −0.5 to + 0.7 (p < 0.05). A positive correlation indicates that increase in El Niño intensity (+ winter ONI) will lead to rise in total malaria cases in the concurrent year in the states of Orissa, Chhattisgarh, Jharkhand, Bihar, Goa, eastern parts of Madhya Pradesh, part of Andhra Pradesh, Uttarakhand and Meghalaya. Whereas, negative correlations were found in the states of Rajasthan, Haryana, Gujarat, part of Tamil Nadu, Manipur, Mizoram and Sikkim indicating the likelihood of outbreaks in La Nina condition.
The generated map, representing spatial correlation between ‘ + winter ONI’ and ‘malaria case index’, indicates positive correlations in eastern part, while negative correlations in western part of India. This study provides plausible guidelines to national programme for planning intervention measures in view of ENSO events. For better resolution, district level study with inclusion of IOD and ‘epochal variation of monsoon rainfall’ factors at micro-level is desired for better forecast of malaria outbreaks in the regions with ‘no correlation’.
Goklany IM. Climate change and malaria. Science. 2004;306:56–7. CrossRef
Bhattacharya S, Sharma C, Dhiman RC, Mitra AP. Climate change and malaria in India. Curr Sci. 2006;90:369–75.
Gill CA. The role of meteorology in malaria. Indian J Med Res. 1921;8:633–93.
Yacob M, Swaroop S. The forecasting of epidemic malaria in the Punjab. J Mal Inst India. 1944;5:319–35.
Stern PC, Easterling WE. Making climate forecasts matter. Committee on the Human Dimensions of Global Change. Commission on Behavioral and Social Sciences and Education. National Research Council. National Academy Press, Washington, DC. 1999.
Bouma MJ, Dye C. Cycles of malaria associated with El Niño in Venezuela. J Am Med Assoc. 1997;278:1772–4. CrossRef
Kovats SR, Bouma MJ, Haines A. El Niño and health. WHO sustainable development and healthy environments. Geneva: Task Force on Climate and Health; 1999.
Thomson MC, Mason SJ, Phindela T, Connor SJ. Use of rainfall and sea surface temperature monitoring for malaria early warning in Botswana. Am J Trop Med Hyg. 2005;73:214–22. PubMed
Rajeevan M, Mc Phaden MJ. Tropical Pacific upper ocean heat content variations and Indian summer monsoon rainfall. Geophys Res Lett. 2004;31:18203. CrossRef
Central Bureau of Health Intelligence (CBHI). http://cbhidghs.nic.in/. Accessed 04 June 2015.
National Vector Borne Disease Control Programme (NVBDCP). www.nvbdcp.gov.in/. Accessed 02 June 2015.
Climate Prediction Center, Center for Weather and Climate Prediction, NOAA, USA(CPC-NOAA). http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ensoyears.shtml. Accessed 04 June 2015.
Indian Meteorological Department (IMD, Pune). http://www.imdpune.gov.in/. Accessed 11 Apr 2016.
Harman C, Johns M. Voronoi natural neighbors interpolation. 2008. http://web.cs.swarthmore.edu/~adanner/cs97/s08/papers/harman_johns.pdf. Accessed 17 Nov 2015.
Wang B, Wu Z, Li J, Liu J, Chang C, Ding Y, Wu G. How to measure the strength of the East Asian summer monsoon. Am Met Soc. 2008;21:4449–63.
Bouma MJ. Epidemiology and control of malaria in northern Pakistan. Dordrecht: ICG Printing; 2005.
Kovats RS, Bouma MJ, Hajat S, Worrall E, Haines A. El Niño and health. Lancet. 2003;362:1481–9. PubMed
Sikka DR. Some aspects of the large-scale fluctuations of summer monsoon rainfall over India in relation to fluctuations in the planetary and regional scale circulation parameters. Proc Indian Acad Sci-Earth Planet Sci. 1980;89:179–95.
Rasmusson EM, Carpenter TH. The relationship between the eastern Pacific sea surface temperature and rainfall over India and Sri Lanka. Mon Weather Rev. 1983;111:517–28. CrossRef
Ashok K, Guan Z, Yamagata T. Impact of the Indian Ocean dipole on the decadal relationship between the Indian monsoon rainfall and ENSO. Geophys Res Lett. 2001;28:4499–502. CrossRef
Kripalani RH, Kulkarni A. Climate impact of El Nino/LaNina on the Indian monsoon: a new prespective. Weather. 1997;52:39–46. CrossRef
- El Niño Southern Oscillation as an early warning tool for malaria outbreaks in India
Ramesh C. Dhiman
- BioMed Central
Neu im Fachgebiet Innere Medizin
Meistgelesene Bücher aus der Inneren Medizin
Mail Icon II