Conventional and frugal methods of estimating COVID-19-related excess deaths and undercount factors

Creators: Dedhe, Abhishek M.; Chowkase, Aakash A.; Gogate, Niramay V.; Kshirsagar, Manas M.; Naphade, Rohan; Naphade, Atharv; Kulkarni, Pranav; Naik, Mrunmayi; Dharm, Aarya; Raste, Soham; Patankar, Shravan; Jogdeo, Chinmay M.; Sathe, Aalok; Kulkarni, Soham; Bapat, Vibha; Joshi, Rohinee; Deshmukh, Kshitij; Lele, Subhash; Manke-Miller, Kody J.; Cantlon, Jessica F.; Pandit, Pranav S.

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Abstract

Across the world, the officially reported number of COVID-19 deaths is likely an undercount. Establishing true mortality is key to improving data transparency and strengthening public health systems to tackle future disease outbreaks. In this study, we estimated excess deaths during the COVID-19 pandemic in the Pune region of India. Excess deaths are defined as the number of additional deaths relative to those expected from pre-COVID-19-pandemic trends. We integrated data from: (a) epidemiological modeling using pre-pandemic all-cause mortality data, (b) discrepancies between media-reported death compensation claims and official reported mortality, and (c) the “wisdom of crowds” public surveying. Our results point to an estimated 14,770 excess deaths [95% CI 9820–22,790] in Pune from March 2020 to December 2021, of which 9093 were officially counted as COVID-19 deaths. We further calculated the undercount factor—the ratio of excess deaths to officially reported COVID-19 deaths. Our results point to an estimated undercount factor of 1.6 [95% CI 1.1–2.5]. Besides providing similar conclusions about excess deaths estimates across different methods, our study demonstrates the utility of frugal methods such as the analysis of death compensation claims and the wisdom of crowds in estimating excess mortality.

Copyright and License

© The Author(s) 2024. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Acknowledgement

This work was partially supported by prize money from the Johns Hopkins Center for Bioengineering Innovation and Design’s COVID-19 Design Challenge 2020 awarded to A.M.D., P.K., S.P., S.R., Dr. Samvid Kurlekar, and Gauri Kapoor. Jnana Prabodhini Foundation’s SurveyMonkey account, that was used to conduct the wisdom of crowds public survey, was partially sponsored by SurveyMonkey’s COVID-19 Support-A-Charity program. Funding for publishing this article open access was provided by the University of California Libraries under a transformative open access agreement with the publisher. This work did not receive any additional funding from grants or other sources. We thank the Pune Knowledge Cluster, a national-level Science and Innovation Cluster set up by the Office of the Principal Scientific Advisor (Government of India), for sharing a dataset about monthly all-cause mortality in Pune from January 2014 through December 2022. Within the Pune Knowledge Cluster, we thank Dr. Raghunath Mashelkar, Dr. L.S. Shashidhara, Dr. Ajit Kembhavi, Dr. Priyanka Nagaraj, and Priyanki Shah for their research support. We thank Nour Al-Zaghloul and Hugo Angulo for laboratory research support at Carnegie Mellon University. Within the Jnana Prabodhini Foundation, we thank Ganesh Kuber, Dr. Swapneeta Date, Revati Desphande, Parnavi Habde, Chinmay Shah, Tejas Shende, Rohan Shinde, Pranav Kajgaonkar, and Pranav A. Kulkarni, as well as Jnana Prabodhini (Pune)'s Educational Resource Centre, Nagari Vasti Abhyas Gat, and Yuvak Vibhag for their research and outreach support. We thank Dr. Suneeta Kulkarni, Dr. Vicki Hegelson, Dr. Joy Monteiro, Dr. Mihir Arjunwadkar, Dr. Murad Banaji, Dr. Wändi Bruine de Bruin, Dr. Bhalchandra Pujari, Joshua de Souza, Aparajita Chandrasekhar, Muhammad Hadi, Dr. Varun Chowdhry, Apoorva Khadilkar, Lakshmi Kumar, Dr. Samvid Kurlekar, Shreyas Chaudhari, Chinmayi Bankar, Bhargavi Patel, Shreyas Gajendragadkar, Rhugwed Ponkshe, Tushar Joshi, Mohit Diwase, Sushant Pawar, and Nachiket Panse for their support and feedback. We are grateful to the participants of our survey. All data analyses were conducted using the Python and R programming languages, Microsoft Excel, and Google Sheets. All figures and tables were created using the R programming language, Microsoft Excel, Google Sheets, and DataWrapper.

Contributions

A.M.D. was the principal investigator of this study. S.L., K.J.M.-M., J.F.C., and P.S.P. were senior faculty investigators in this study. A.M.D., A.A.C., N.V.G., M.M.K., P.K., S.L., K.J.M.-M., J.F.C., and P.S.P. developed the study concept and contributed to the study design. A.M.D., A.A.C., N.V.G., M.M.K., P.K., S.R., S.P., C.M.J., A.S., V.B., and R.J. collected the data. A.M.D., A.A.C., N.V.G., R.N., A.N., P.K., M.N., S.P., S.K., S.L., J.F.C., and P.S.P. performed the data analysis. A.M.D., A.A.C., N.V.G., M.M.K., K.D., J.F.C., and P.S.P. wrote the manuscript. A.M.D., N.V.G., A.D., S.R., and S.K., created the figures. A.M.D. and P.S.P. are the corresponding authors of this study. All authors read the manuscript, discussed the results, and commented on the manuscript.

Data Availability

All data generated or analyzed during this study are included in this published article and its supplementary information files.

Conflict of Interest

The authors declare no competing interests.

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