Mortality From the Influenza Pandemic of 1918–1919: The Case of India

Abstract

Estimates of worldwide mortality from the influenza pandemic of 1918–1919 vary widely, from 15 million to 100 million. In terms of loss of life, India was the focal point of this profound demographic event. In this article, we calculate mortality from the influenza pandemic in India using panel data models and data from the Census of India. The new estimates suggest that for the districts included in the sample, mortality was at most 13.88 million, compared with 17.21 million when calculated using the assumptions of Davis (1951). We conclude that Davis’ influential estimate of mortality from influenza in British India is overstated by at least 24%. Future analyses of the effects of the pandemic on demographic change in India and worldwide will need to account for this significant downward revision.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2

References

  1. Afkhami, A. (2003). Compromised constitutions: The Iranian experience with the 1918 influenza pandemic. Bulletin of the History of Medicine, 77, 367–392.

    Article  Google Scholar 

  2. Almond, D. (2006). Is the 1918 influenza pandemic over? Long–term effects of in utero influenza exposure in the post–1940 U.S. population. Journal of Political Economy, 114, 672–712.

    Article  Google Scholar 

  3. Census of India. (Various years). Calcutta, India: Superintendent, Government Printing.

  4. Davis, K. (1951). The population of India and Pakistan. Princeton, NJ: Princeton University Press.

    Google Scholar 

  5. Government of India. (1920). Annual report of the Sanitary Commissioner with the Government of India for 1918. Calcutta, India: Superintendent, Government Printing.

    Google Scholar 

  6. Government of India. (Various years). Annual report of the Sanitary Commissioner with the Government of India. Calcutta, India: Superintendent, Government Printing.

  7. Johnson, N. P. A. S., & Mueller, J. (2002). Updating the accounts: Global mortality of the 1918–1920 “Spanish” influenza pandemic. Bulletin of the History of Medicine, 76, 105–115.

    Article  Google Scholar 

  8. Jordan, E. O. (1927). Epidemic influenza: A survey. Chicago, IL: American Medical Association.

    Google Scholar 

  9. Klein, I. (1973). Death in India, 1871–1921. The Journal of Asian Studies, 32, 639–659.

    Article  Google Scholar 

  10. Klein, I. (1974). Population and agriculture in northern India, 1872–1921. Modern Asian Studies, 8, 191–216.

    Article  Google Scholar 

  11. Klein, I. (1988). Plague, policy and popular unrest in British India. Modern Asian Studies, 22, 723–755.

    Article  Google Scholar 

  12. Klein, I. (1990). Population growth and mortality in British India Part II: The demographic revolution. Indian Economic and Social History Review, 27, 33–63.

    Article  Google Scholar 

  13. Marten, J. T. (1923). Census of India, 1921 (Vol. I, Part I) (Report). Calcutta, India: Superintendent of Government Printing.

  14. Mazumder, B., Almond, D., Park, K., Crimmins, E. M., & Finch, C. E. (2010). Lingering prenatal effects of the 1918 influenza pandemic on cardiovascular disease. Journal of Developmental Origins of Health and Disease, 1, 26–34. doi:10.1017/S2040174409990031

    Article  Google Scholar 

  15. Mills, I. D. (1986). The 1918–1919 influenza pandemic—The Indian experience. Indian Economic and Social History Review, 23, 1–40.

    Article  Google Scholar 

  16. Morens, D. M., Taubenberger, J. K., & Fauci, A. S. (2009). The persistent legacy of the 1918 influenza virus. New England Journal of Medicine, 361, 225–229.

    Article  Google Scholar 

  17. Patterson, K. D., & Pyle, G. (1991). The geography and mortality of the 1918 influenza pandemic. Bulletin of the History of Medicine, 65, 4–21.

    Google Scholar 

  18. SAS Institute, Inc. (2011a). SAS/ETS(R) 9.2 user’s guide: The PANEL procedure. Retrieved from http://support.sas.com/documentation/cdl/en/etsug/60372/HTML/default/viewer.htm#panel_toc.htm

  19. SAS Institute, Inc. (2011b). SAS/STAT(R) 9.2 user’s guide : The MIXED procedure (2nd ed.). Retrieved from http://support.sas.com/documentation/cdl/en/statug/63033/HTML/default/viewer.htm#mixed_toc.htm

  20. Taubenberger, J. K., & Morens, D. M. (2006). 1918 influenza: The mother of all pandemics. Emerging Infectious Diseases, 12, 15–22.

    Article  Google Scholar 

  21. Waring, J. I. (1971). A history of medicine in South Carolina 1900–1970. Columbia: South Carolina Medical Association.

    Google Scholar 

  22. Yeatts, M. W. M. (1943). Census of india, 1941 (Vol. I, Part I) (Report). Simla, India: Government of India Press.

Download references

Acknowledgments

This research was made possible by Grant No. 1R21DA025917-01A1 from the National Institute on Drug Abuse (NIDA) of the National Institutes of Health. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of NIDA. The authors would also like to thank participants of the XXXIII Annual Conference of the Indian Association for the Study of Population (IASP) held in Lucknow, India, in 2011, for their input.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Siddharth Chandra.

Appendices

Appendix 1: List of Districts Used in the Analysis (colonial spellings)

Name Name Name Name Name Name
Agra Budaun Garhwal Kanara Muzaffarpur Satara
Ahmedabad Bulandshahr Garo Hills Kangra Mymensingh Saugor
Ahmednagar Buldana Gaya Karachi Nadia Shahabad
Ajmer Merwara Burdwan Ghazipur Karnal Nagpur Shahjahanpur
Akola Cachar Goalpara Kheri NainiTal Shahpur
Aligarh Calcutta Godavari East Khulna Nasik Sheikhupura
Allahabad Cawnpore Godavari West Kistna Nellore Sholapur
Almora Champaran Gonda Kolaba Nilgiris Sialkot
Ambala Chanda Gorakhpur Koraput Nimar Sibsagar
Amraoti Chhindwara Gujranwala Kurnool Noakhali Singhbhum
Amritsar Chingleput Gujrat Lahore North Arcot Sitapur
Anantapur Chittagong Guntur Lakhimpur Nowgong SouthArcot
Attock Chittoor Gurdaspur Larkana Pabna South Kanara
Azamgarh Coimbatore Gurgaon Lucknow Palamau Sukkur
Bahraich Cuddapah Hamirpur Ludhiana 24 Parganas Sultanpur
Bakarganj Cuttack Hardoi Madras Partabgarh Surat
Balaghat Dacca Hazaribagh Madura Pilibhit Sylhet
Balasore Darbhanga Hissar Mainpuri Poona Tanjore
Ballia Darjeeling Hooghly Malabar Puri Thana
Banda Darrang Hoshangabad Malda Purnea TharParkar
Bankura Dehra Dun Hoshiarpur Manbhum Rae Bareli Tinnevelly
BaraBanki Dera Ghazi Khan Howrah Mandla Raipur Tippera
Bareilly Dharwar Hyderabad Meerut Rajshahi Trichinopoly
Basti Dinajpur Jalaun Mianwali Ramnad Unao
Belgaum Drug Jalpaiguri Midnapore Ranchi Upper Sind Frontier
Bellary East Khandesh Jaunpur Mirzapur Rangpur Vizagapatam
Betul Etah Jessore Monghyr Ratnagiri Wardha
Bhagalpur Etawah Jhang Montgomery Rawalpindi West Khandesh
Bhandara Faridpur Jhansi Moradabad Rohtak Yeotmal
Bijapur Farrukhabad Jhelum Multan Saharanpur  
Bijnor Fatehpur Jubbulpore Murshidabad Salem  
Birbhum Ferozepore Jullundur Muttra Sambalpur  
Bogra Fyzabad Kaira Muzaffargarh Santal Parganas  
Broach and Panch Mahals Ganjam Kamrup Muzaffarnagar Saran  

Appendix 2: Details of Random-Coefficients Models

As discussed previously, the general model estimated is

$$ LPO{{P}_{{it}}} = {{\pi }_{{0i}}} + {{\pi }_{{1i}}}{{T}_{t}} + {{\pi }_{{2i}}}FL{{U}_{t}} + {{\pi }_{{3i}}}{{T}_{t}}FL{{U}_{t}} + {{\varepsilon }_{{it}}}, $$

where i and t index districts and time in years. The coefficient estimates π 0i , π 1i , π 2i , and π 3i are defined as

$$ \matrix{ {{\pi_{{0i}}} = {\gamma_{{00}}} + {\zeta_{{0i}}}} \hfill \\ {{\pi_{{1i}}} = {\gamma_{{10}}} + {\zeta_{{1i}}}} \hfill \\ {{\pi_{{2i}}} = {\gamma_{{20}}} + {\zeta_{{2i}}}} \hfill \\ {{\pi_{{3i}}} = {\gamma_{{30}}} + {\zeta_{{3i}}}} \hfill , \\ }<!end array> $$

where it is assumed that

$$ {\varepsilon_{{ij}}}\sim N(0,\sigma_{\varepsilon }^2) $$

and

$$ \left[ {\matrix{ {{\zeta_{{0i}}}} \hfill \\ {{\zeta_{{1i}}}} \hfill \\ {{\zeta_{{2i}}}} \hfill \\ {{\zeta_{{3i}}}} \hfill \\ }<!end array> } \right] \sim N\left( {\left[ {\matrix{ 0 \hfill \\ 0 \hfill \\ 0 \hfill \\ 0 \hfill \\ }<!end array> } \right],\left[ {\matrix{ {\sigma_0^2} \hfill &{{\sigma_{{01}}}} \hfill &{{\sigma_{{02}}}} \hfill &{{\sigma_{{03}}}} \hfill \\ {{\sigma_{{10}}}} \hfill &{\sigma_1^2} \hfill &{{\sigma_{{12}}}} \hfill &{{\sigma_{{13}}}} \hfill \\ {{\sigma_{{20}}}} \hfill &{{\sigma_{{21}}}} \hfill &{\sigma_2^2} \hfill &{{\sigma_{{23}}}} \hfill \\ {{\sigma_{{30}}}} \hfill &{{\sigma_{{31}}}} \hfill &{{\sigma_{{32}}}} \hfill &{\sigma_3^2} \hfill \\ }<!end array> } \right]} \right). $$

The coefficients are modeled as varying randomly across districts, and the estimates reported in Table 1 are the mean coefficients across all districts. Details of these models are provided in SAS (2011b).

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Chandra, S., Kuljanin, G. & Wray, J. Mortality From the Influenza Pandemic of 1918–1919: The Case of India. Demography 49, 857–865 (2012). https://doi.org/10.1007/s13524-012-0116-x

Download citation

Keywords

  • Influenza
  • Pandemic
  • India
  • Mortality
  • Population loss