Skip to main content

Advertisement

SpringerLink
Log in

Impact of El Niño–Southern Oscillation and Indian Ocean Dipole on malaria transmission over India in changing climate

  • Original Paper
  • Published:
International Journal of Environmental Science and Technology Aims and scope Submit manuscript

Abstract

An effort is made to understand the role of El Nino-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events on the malaria transmission intensity over India during the period 1951–2020 (70 years) with the help of a realistically simulated dynamical malaria model. The results suggest that the La Nina years pose a greater threat of malaria disease, especially in the densely populated Indian states. During El Nino years, the malaria transmission intensity and distribution over India greatly reduce, except in the regions such as Orissa, Chhattisgarh, Jharkhand, Western Ghats, parts of Madhya Pradesh, and Andhra Pradesh. It is found that in the positive IOD years, the malaria transmission intensity increases (decreases) over the entire central Indian region and along coastal regions of Tamil Nadu and Kerala (southern peninsular states of India and northeast India). An almost opposite behavior is seen during the negative IOD years. The malaria transmission variability over India is becoming increasingly heterogeneous in recent decades during the El Nino and La Nina years as a result of global warming. The period of 1986–2020 witnessed a substantial decrease (increase) in the malaria transmission intensity during the positive (negative) IOD years, except for a few regions of India. The implications of the results presented in the paper linking the ENSO and IOD signals with the intensity and distribution of malaria over India in a warming world are enormous, especially for the densely populated Indian states.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Data availability

The ERA5 reanalysis air temperature data (https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5), and IMD rainfall dataset (https://www.imdpune.gov.in/Clim_Pred_LRF_New/Grided_Data_Download.html) used in this study are freely available for research purpose.

References

  • Abiodun GJ, Maharaj R, Witbooi P, Okosun KO (2016) Modelling the influence of temperature and rainfall on the population dynamics of Anopheles arabiensis. Malar J 15(1):1–15

    Article  Google Scholar 

  • Anyamba A, Chretien JP, Britch SC, Soebiyanto RP, Small JL, Jepsen R, Forshey BM, Sanchez JL, Brett M, Jose L, Smith RD, Harris R, Tucker CJ, Karesh WB, Linthicum KJ (2019) Global disease outbreaks associated with the 2015–2016 El Niño event. Sci Rep 9(1):1–14

    Article  CAS  Google Scholar 

  • Balk D, Pozzi F, Yetman, G, Deichmann, U, Nelson A (2005) The distribution of people and the dimension of place: methodologies to improve the global estimation of urban extents In: International Society for Photogrammetry and Remote Sensing, proceedings of the urban remote sensing conference, pp 14–16

  • Behera SK, Ratnam JV (2018) Quasi-asymmetric response of the Indian summer monsoon rainfall to opposite phases of the IOD. Sci Rep 8(1):1–8

    Article  Google Scholar 

  • Behera SK, Yamagata T (2001) Subtropical SST dipole events in the southern Indian Ocean. Geophys Res Lett 28(2):327–330

    Article  Google Scholar 

  • Behera SK, Morioka Y, Ikeda T, Doi T, Ratnam JV, Nonaka M, Tsuzuki A, Imai C, Kim Y, Hashizume M, Iwami S, Kruger P, Maharaj R, Sweijd N, Minakawa N (2018) Malaria incidences in South Africa linked to a climate mode in southwestern Indian Ocean. Environ Dev 27:47–57

    Article  Google Scholar 

  • Bhattacharya S, Sharma C, Dhiman RC, Mitra AP (2006) Climate change and malaria in India. Curr Sci 90(3):369–375

    Google Scholar 

  • Boschat G, Simmonds I, Purich A et al (2016) On the use of composite analyses to form physical hypotheses: an example from heat wave-SST associations. Sci Rep 6:29599. https://doi.org/10.1038/srep29599

    Article  CAS  Google Scholar 

  • Bouma MJ, van der Kaay HJ (1996) The EI Niño Southern Oscillation and the historic malaria epidemics on the Indian subcontinent and Sri Lanka: an early warning system for future epidemics? Tropical Med Int Health 1(1):86–96

    Article  CAS  Google Scholar 

  • Bouma MJ, Siraj AS, Rodo X, Pascual M (2016) El Niño-based malaria epidemic warning for Oromia, Ethiopia, from August 2016 to July 2017. Tropical Med Int Health 21(11):1481–1488

    Article  CAS  Google Scholar 

  • Castro MC (2017) Malaria transmission and prospects for malaria eradication: the role of the environment. Cold Spring Harb Perspect Med 7(a025601):1–12

    CAS  Google Scholar 

  • Chaturvedi S, Dwivedi S (2020) Estimating the malaria transmission over the Indian subcontinent in a warming environment using a dynamical malaria model. J Water Health 18(3):358–374

    Article  Google Scholar 

  • Chaturvedi S, Dwivedi S (2021) Understanding the effect of climate change in the distribution and intensity of malaria transmission over India using a dynamical malaria model. Int J Biometeorol 65(7):1161–1175

    Article  Google Scholar 

  • Chaves LF, Satake A, Hashizume M, Minakawa N (2012) Indian Ocean Dipole and rainfall drive a Moran effect in East Africa malaria transmission. J Infect Dis 205(12):1885–1891

    Article  Google Scholar 

  • Dhiman RC, Sarkar S (2017) El Niño Southern Oscillation as an early warning tool for malaria outbreaks in India. Malar J 16(1):1–7

    Article  Google Scholar 

  • Dwivedi S (2012) Forecasting the peak anomalies of dominant intrinsic modes of Indian Ocean Dipole. Deep Sea Res Part I Oceanogr Res Papers 70:73–82. https://doi.org/10.1016/j.dsr.2012.10.005

    Article  Google Scholar 

  • Dwivedi S, Goswami BN, Kucharski F (2015) Unraveling the missing link of ENSO control over the Indian monsoon rainfall. Geophys Res Lett 42:8201–8207

    Article  Google Scholar 

  • Dwivedi S, Pandey P, Goswami BN (2022) Nonstationarity and Potential Multi-Decadal Variability in Indian Summer Monsoon Rainfall and Southern Annular Mode Teleconnection. Clim Dyn 59:671–683

    Article  Google Scholar 

  • Gething, P., Van Boeckel, T., Smith, D., Guerra, C., Patil, A., Snow, R., & Hay, S. (2011). Modelling the global constraints of temperature on transmission of Plasmodium falciparum and P. vivax. Parasit Vectors, 4, 92.

  • Harp, R. D., Colborn, J. M., Candrinho, B., Colborn, K. L., Zhang, L., & Karnauskas, K. B. (2021). Interannual climate variability and malaria in Mozambique. GeoHealth, 5(2), e2020GH000322.

  • Hashizume M, Terao T, Minakawa N (2009) The Indian Ocean dipole and malaria risk in the highlands of western Kenya. Proc Natl Acad Sci 106(6):1857–1862

    Article  CAS  Google Scholar 

  • Hashizume M, Chaves LF, Minakawa N (2012) Indian Ocean Dipole drives malaria resurgence in East African highlands. Sci Rep 2(1):1–6

    Article  Google Scholar 

  • Hersbach H et al (2020) The ERA5 global reanalysis. Q J R Meteorol Soc 146(730):1999–2049

    Article  Google Scholar 

  • Kilian AH, Langi P, Talisuna A, Kabagambe G (1999) Rainfall pattern, El Nino and malaria in Uganda. Trans R Soc Trop Med Hyg 93:22–23

    Article  CAS  Google Scholar 

  • Kovats RS (2000) El Niño and human health. Bull World Health Organ 78:1127–1135

    CAS  Google Scholar 

  • Kovats RS, Bouma MJ, Hajat S, Worrall E, Haines A (2003) El Nino and Health. Lancet 362:1481–1489

    Article  Google Scholar 

  • Leedale J, Tompkins AM, Caminade C, Jones AE, Nikulin G, Morse AP (2016) Projecting malaria hazard from climate change in eastern Africa using large ensembles to estimate uncertainty. Geospat Health 11:102–114

    Article  Google Scholar 

  • Lindblade KA, Walker ED, Onapa AW, Katungu J, Wilson ML (1999) Highland malaria in Uganda: prospective analysis of an epidemic associated with El Nino. Trans R Soc Trop Med Hyg 93:480–487

    Article  CAS  Google Scholar 

  • Lindsay SW, Bodker R, Malima R, Msangeni HA, Kisinza W (2000) Effect of 1997–98 El Nino on highland malaria in Tanzania. Lancet 355:989–990

    Article  CAS  Google Scholar 

  • Loevinsohn ME (1994) Climatic warming and increased malaria incidence in Rwanda. Lancet 343:714–718

    Article  CAS  Google Scholar 

  • Mordecai EA, Paaijmans KP, Johnson LR, Balzer C, Ben-Horin T, Moor E, McNally A, Pawar S, Ryan SJ, Smith TC et al (2013) Optimal temperature for malaria transmission is dramatically lower than previously predicted. Ecol Lett 16:22–30

    Article  Google Scholar 

  • Paaijmans KP, Wandago MO, Githeko AK, Takken W (2007) Unexpected high losses of Anopheles gambiae larvae due to rainfall. Plos One 2:e1146

    Article  Google Scholar 

  • Paaijmans KP, Cator LJ, Thomas MB (2013) Temperature-dependent pre-bloodmeal period and temperature-driven asynchrony between parasite development and mosquito biting rate reduce malaria transmission Intensity. Plos One 8(1):e55777

    Article  CAS  Google Scholar 

  • Pai DS, Rajeevan M, Sreejith OP, Mukhopadhyay B, Satbha NS (2014) Development of a new high spatial resolution (0.25× 0.25) long period (1901–2010) daily gridded rainfall data set over India and its comparison with existing data sets over the region. Mausam 65(1):1–18

    Article  Google Scholar 

  • Pandey P, Dwivedi S, Goswami BN, Kucharski F (2020) A new perspective on ENSO-Indian summer monsoon rainfall relationship in a warming environment. Clim Dyn 55(11):3307–3326

    Article  Google Scholar 

  • Rayner NA, Parker DE, Horton EB, Folland CK, Alexander LV, Rowell DP, Kent EC, Kaplan A (2003) Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J Geophys Res: atmos 108(D14)

  • Saji NH, Yamagata T (2003) Possible impacts of Indian Ocean dipole mode events on global climate. Clim Res 25(2):151–169

    Article  Google Scholar 

  • Saji NH, Goswami BN, Vinayachandran PN, Yamagata T (1999) A dipole mode in the tropical Indian Ocean. Nature 401(6751):360–363

    Article  CAS  Google Scholar 

  • Sarkar S, Gangare V, Singh P, Dhiman RC (2019) Shift in potential malaria transmission areas in India, using the fuzzy-based climate suitability malaria transmission (FCSMT) model under changing climatic conditions. Int J Environ Res Public Health 16(18):3474. https://doi.org/10.3390/ijerph16183474

    Article  Google Scholar 

  • Singh Parihar R, Bal PK, Kumar V, Mishra SK, Sahany S, Salunke P, Dash SK, Dhiman RC (2019) Numerical modeling of the dynamics of malaria transmission in a highly endemic region of India. Sci Rep 9(1):1–9

    Article  CAS  Google Scholar 

  • Singh N, Sharma VP (2002) Patterns of rainfall and malaria in Madhya Pradesh, central India. Ann Trop Med Parasitol 96:349–359

    Article  CAS  Google Scholar 

  • Smith J, Tahani L, Bobogare A, Bugoro H, Otto F, Fafale G, Hiriasa D, Kazazic A, Beard G, Amjadali A, Jeanne I (2017) Malaria early warning tool: linking inter-annual climate and malaria variability in northern Guadalcanal. Solomon Isl Malar J 16(1):1–16

    Google Scholar 

  • Thomson M, Indeje M, Connor S, Dilley M, Ward N (2003) Malaria early warning in Kenya and seasonal climate forecasts. Lancet 362(9383):580

    Article  Google Scholar 

  • Thomson M, Mason SJ, Phindela T, Connor SJ (2005) Use of rainfall and sea surface temperature monitoring for malaria early warning in Botswana. Am J Trop Med Hyg 73:214–221

    Article  Google Scholar 

  • Tompkins AM, Ermert V (2013) A regional-scale, high resolution dynamical malaria model that accounts for population density, climate and surface hydrology. Malar J 12(1):1–24

    Article  Google Scholar 

  • Trenberth KE, Hoar TJ (1997) El Niño and climate change. Geophys Res Lett 24(23):3057–3060

    Article  Google Scholar 

  • Watts N et al (2019) The 2019 report of The Lancet Countdown on health and climate change: ensuring that the health of a child born today is not defined by a changing climate. The Lancet 394(10211):1836–1878

    Article  Google Scholar 

  • Wilks D (1995) Statistical methods in the atmospheric sciences: an introduction. Academic Press, Cambridge, p 467

    Google Scholar 

Download references

Acknowledgments

SC is thankful to the DST, Govt. of India, for providing the INSPIRE Fellowship. SD is thankful to the DST-FIST for proving infrastructural support to the KBCAOS. The authors are thankful to the IMD and ERA5 data centers for making their datasets freely available. Thanks are also due to Dr. Adrian Tompkins, ICTP, Italy, for providing VECTRI-related training to SC from time to time.

Funding

No funding was received for conducting this study.

Author information

Authors and Affiliations

  1. K Banerjee Centre of Atmospheric and Ocean Studies and M N Saha Centre of Space Studies, University of Allahabad, Prayagraj, Uttar Pradesh, 211002, India

    S. Chaturvedi & S. Dwivedi

Authors
  1. S. Chaturvedi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S. Dwivedi
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization was contributed by SD; methodology, investigation, validation, and formal analysis were contributed by SC and SD; writing—original draft was contributed by SC and SD; supervision was contributed by SD. Both the authors have read and agreed to the present version of the manuscript.

Corresponding author

Correspondence to S. Dwivedi.

Ethics declarations

Conflict of interest

The authors have no competing interests to declare that are relevant to the content of this article.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Additional information

Editorial responsibility: S.R. Sabbagh-Yazdi.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chaturvedi, S., Dwivedi, S. Impact of El Niño–Southern Oscillation and Indian Ocean Dipole on malaria transmission over India in changing climate. Int. J. Environ. Sci. Technol. 21, 91–100 (2024). https://doi.org/10.1007/s13762-023-04836-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13762-023-04836-6

Keywords

Search

Navigation