Counting the dead is one of the world’s best investments to reduce premature mortality

Vital statistics on causes of death (COD) by age, gender, social status and geography have transformed health in developed countries. Robust COD information, especially for adult deaths, remains uncommon in most developing countries as most deaths do not occur in hospitals. I recommend five low-cost options to improve rapidly COD systems in countries with inadequate systems. Implementing these improvements over the next few years is feasible at low cost given advances in information technology and data capture. COD systems would transform disease control priorities, approaching in quality and matching in relevance what has taken more than a century to produce in many developed countries. Counting the dead is one of the world’s best investments to improve global health.

In 1869, the Sanitary Commissioner of India wrote “for sanitary purposes it is indispensable to know the relative mortality in small and, as far as possible, well-defined tracts to ascertain the death rates in each of these communities; to see how far this arises from preventable causes; and to apply the remedies” (1).

In this paper, I argue that over 140 years later counting the dead is one of the best investments to reduce premature mortality worldwide as it is one of the most robust ways to measure accurately the effectiveness of investments aimed at reducing child and adult mortality. With rapid expansion of information technologies, developing countries have an opportunity to improve health by rapidly introducing systems that reliably measure the causes of death (COD) and key risk factors that increase mortality. COD systems implemented worldwide would spur research into avoidable mortality and new risk factors by identifying diseases that are common in one locality but rare somewhere else. These differences must reflect major, measurable differences in largely unknown causative factors and in some intermediate determinants of disease risk. COD systems would also transform disease control priorities, help detect new epidemics, enable the evaluation of disease control programs and improve accountability for expenditures on disease control (2,3). A practicable, worldwide, rapid expansion of COD systems may be able to collect representative data by 2020, particularly for adults, and particularly in sub-Saharan Africa.

About 56 million deaths occur worldwide every year (4). Certification of deaths with causes assigned by physicians is nearly universal for the 8 million deaths occurring in developed countries. However, death registration and medical attention at the time death is low among the 48 million deaths in developing countries (defined as low- and middle-income countries) (5). Among 115 countries that reported mortality to the World Health Organization (WHO) (4), only 64 countries had good quality vital registration that also covered COD. Fully 75 countries, including 90% of those in Africa, did not provide data on COD for any year after 1990.

Historic Development of COD Systems
Earlier crude COD systems in urban European cities were remarkably useful in helping to control plague and other epidemics (6). Death registration began in the late 1830s in England and even earlier in Sweden. Death by social class was recorded in England beginning in 1921 (7). In 1852, the first mortality report by the Massachusetts Sanitary Commission noted that the average age of farmers who died was 65 years whereas mechanics died at an average of 47 years. The report suggested that this fact “should urge physicians … to inquire into the causes which shorten the lives of so large a proportion of the inhabitants of our State” (8). Public health in industrialized countries was transformed when vital statistics on age, sex and socioeconomic distribution of births and deaths became available in the late 19th and 20th centuries (2,3). COD statistics have demonstrated major reductions in under-five mortality and tuberculosis mortality during the 20th century, but more importantly they have also identified unexpected causes of mortality. For example, in the 1940s, the dramatic increase in lung cancer deaths in British and American men after World War II spurred research leading to the discovery of smoking as a cause of a range of diseases, including lung cancer (9). In the early 1980s, routine mortality data from San Francisco revealed an exceptional increase in immune-related deaths among young men and signaled the start of the American HIV epidemic (10). Routinely collected data have helped to prompt further research and public health action, and have contributed to the enormous increases in life expectancy in developed countries in the 20th century (11).

The Limitations of Civil Registration
Universal civil registration of deaths with medical certification is a laudable goal (12,13), but full civil registration can take several decades. Even the United States took the better part of a century to increase death certification, and some states did not reach complete coverage until the 1970s. Developing countries have shown little progress in the expansion of civil registration, and COD statistics lag further behind (14). Reasons for the low civil registration in developing countries include limited access to medical care and the fact that most deaths occur at home rather than in hospitals. Incentives for households to register deaths in most developing countries are quite limited as pension and insurance schemes or enforceable familial inheritance and property rights are uncommon. Strategies to increase civil registration include increasing medical attention at death and training health care workers (12). Requiring burial or cremation grounds to register deaths is practicable in urban settings, but less so in rural areas.

Even basic data on age and sex-specific all cause mortality rates can identify trends for rapidly changing diseases such as those in childhood. Similarly, the very large increases in all-cause death rates among young adults in selected sub- Saharan countries from 1990-2000 have enabled the estimation of the impact of HIV infection on mortality (15,16). This is because the “signal” of HIV-attributable mortality (increased deaths) exceeds the “noise” of misclassification from competing mortality. Civil registration would be similarly useful to document pandemic influenza, as the overall death rates would increase substantially during the pandemic phase. For example, a simple analysis of age-specific death rates from India’s census data suggested that 17-20 million Indians died of the influenza epidemic in 1918-1917.

Modern Relevance of COD Measurement
The modern relevance of various COD systems depends on their specific uses, the disease and age group of interest, and on random or systematic misclassification of COD. The major objective for most low- and middle-income countries would be COD systems that obtain more representative data on age-, gender- and social stratum-specific mortality rates for the major diseases. Hospital records with medical certification of COD are insufficient, given that most deaths occur out of hospital, and given that the age and distribution of causes between hospital and home deaths vary greatly (18).

Verbal autopsies involve a structured investigation of the circumstances and health symptoms leading to the death through an interview of a relative or associate of the deceased (18). The addition of verbal autopsies for child deaths to Demographic and Health Surveys (DHS) (19), and other surveys have removed much of the substantial uncertainty that existed in the 1960s on information on COD for children (20). However, there are still enormous gaps in knowledge for COD of adults worldwide, such as the proportion of adult deaths due to malaria (21).

For most infectious conditions, such as meningitis, the cause of death is directly related to the infective agent. In contrast, chronic diseases such as myocardial infarction may be caused by several factors such as smoking, elevated blood pressure or blood lipids. Chronic diseases are already the leading cause of death worldwide (22) so reliable measurement of causes of adult mortality and their underlying risk factors is required in particular for developing countries. In Western countries there has been limited use of “co-morbid” codes on death certificates (23) and the completion of these codes on death certificates in developing countries, where implemented, is quite low. Simply asking about the dead person’s risk factors can be useful. “Household case-control” methods have successfully measured exposure to tobacco in several countries. These involve asking living relatives of those who have died about the tobacco and alcohol use of the deceased and themselves. The Indian Million Death Study (MDS) used such methods to estimate that India currently has about one million deaths from smoking (24). A retrospective study of one million deaths in China compared the proportions of smokers and non-smokers who have died of tobacco-attributable diseases versus non-tobacco related diseases (chiefly injuries) to calculate the excess number of deaths in smokers (25).

Five Options for Expanding COD Reporting
In regions that lack a system for the complete registration of deaths and have low levels of medical attention at the time of death, five complementary approaches are practicable for obtaining better COD data in the medium term (by 2020). The first and most robust option (sometimes called Sample Vital Registration with Verbal Autopsy (26); is the establishment of a Sample Registration System (SRS), such as the one conducted in India.

India’s SRS has worked in representative areas of the country since 1971 (27). China also began a similar system (28). From 2001 onward, India’s SRS has added an enhanced version of a verbal autopsy (18,29), which reliably classifies the major diseases leading to death prior to age 70 years, but which is much less reliable for deaths above age 70 years (30,31). Given that the mean age of deaths in India and other developing countries is far lower than in developed countries, verbal autopsy remains a very relevant approach.

India’s SRS efforts are called the Million Death Study as it will eventually capture information on about one million deaths in India (about 300,000 from 1997-2003, and 650,000 from 2004-2014; (18)). The first round of results has already established the major causes of maternal (32) and child deaths (33) in India. The MDS has attributed about 100,000 deaths to HIV—about a quarter of previous estimates (34). It also noted that cancer death rates were similar in rural and urban areas, and cancer death rates were 2-fold higher in the least educated adults compared with the most educated adults (35). In all cases, direct measurement through the MDS yields novel insights into India’s avoidable mortality.

The MDS identified nearly 200,000 malaria deaths below age 70 years – about 15 times that estimated by WHO using indirect methods (Figure 1; (21)). Similar results from smaller studies in Africa, where malaria is common, have also shown a “U-shaped” mortality pattern (Figure 2; (36-38)). The relevance of this finding is simple. According to WHO, use of powerful artemisinin combination therapies, as well as prevention through insecticide impregnated mosquito nets, has substantially reduced malaria mortality in children in Africa (39). Similar efforts might well reduce adult deaths from malaria worldwide.

A second option for selected African countries with limited or no vital registration and no cause of death data is to enhance the ongoing INDEPTH network (40), a group of around 42 demographic surveillance sites (DSS) in 19 countries (Figure 3). This would involve efforts to expand the sample size in each country and make the sites more (or fully) representative of the population. Well-planned DSS efforts, such as the Adult Morbidity and Mortality Project in Tanzania, strengthen vital statistics and survey capacity, and have prompted the use of COD data to monitor and evaluate various national programs at local and regional levels, including those for malaria and HIV/AIDS (41).

A third option is retrospective surveys of mortality that accompany the globally standardized DHS begun by the US Government and now covering about 90 countries (19). This would use the DHS representative sampling frame to record COD among deaths in DHS households over the last 5-10 years. DHS have limitations, such as small sample size, and an overwhelming focus on child and maternal health. However, addition of a module for adult verbal autopsy to the DHS sampling frame is practicable.

A related fourth option for large countries is the implantation of large, well-planned retrospective surveys of mortality using census sample frames. For example, much is known about variation of disease in China as a result of mortality studies that began there nearly three decades ago. A complete national survey of the causes of all deaths, carried out in 1973-75 (42), remains an important epidemiological study. The study reviewed 20 million deaths, retrospectively clarifying and coding their causes. By yielding the first assessment of age- and cause-specific mortality rates for each province and county, and for China as a whole, the study revealed the large variation in disease rates across the country, which in turn brought about health interventions and further research. For example, a randomized trial of hepatitis B vaccination of children began after the survey showed that liver cancer rates in Qidong were 100 times higher than those in the United Kingdom (42). Mozambique recently conducted a national COD survey of over 11,000 deaths, based on deaths identified in the preceding census (38).

Finally, for a small number of countries that have reasonable levels of civil registration of death, but more limited COD data, it is possible to expand medically-certified COD, while concurrently instituting household-based verbal autopsies for deaths that occur without medical attention. Such pilot programs are currently underway in Brazil, Iran, Sri Lanka, Thailand and Turkey (14).

Developing countries can generate within a few years much needed data on COD at low cost – less than $1 per participant per year (18,43). Novel COD systems are feasible within a few years if they can use electronic data capture, mobile phones and the internet. These novel COD systems can match in quality and relevance what has taken more than a century to produce in many developed countries. A global investment of $100 million dollars might be able to cover about 50 distinct populations (small countries or sub-national regions of large countries) by 2020. The revised United Nations Millennium Development Goals for 2030 should include an explicit goal that each country adopts reliable COD systems. Given the astonishing power of these statistics, counting the dead is one of the world’s best investments to improve global health.H

The author declares no conflicts of interest

I thank Philip Setel, Arthur Slutsky and Alan Bernstein for useful comments and Ansely Wong for help with the manuscript.

About the Author
Professor Prabhat Jha is the University of Toronto Endowed Professor in Disease Control and Canada Research Chair at the Dalla Lana School of Public Health, and the founding Director of the Centre for Global Health Research at St. Michael’s Hospital in Toronto. Professor Jha is a lead investigator of the Million Death Study in India, which quantifies the causes of premature mortality in over 1 million homes from 1997-2014. He also served as Senior Scientist for the World Health Organization, where he co-led the work on health and poverty for the Commission on Macroeconomics and Health.


  1. Mitra B. India’s mortality measurement systems. In: Asma S, Jha P, Gupta PC, editors. Centers for Disease Control and Prevention. Counting the dead in India in the 21st century. Proceedings of the International Workshop on Certification on Causes of Death, Mumbai. US Centers for Disease Control; 1999.
  2. Jha P. Avoidable mortality in India: past progress and future prospects. Natl Med J India. 2002;15 Suppl 1:32-6.
  3. Jha P. Reliable mortality data: a powerful tool for public health. Natl Med J India. 2001;14:129-31. PMid:11467137
  4. Mathers C, Ma Fat D, Inoue M, Rao C, Lopez AD. Counting the dead and what they died of: an assessment of the global status of cause of death data. Bull World Health Organ. 2005;83:171-7. PMid:15798840 PMCid:2624200
  5. World Bank. World Development Indicators (accessed Oct 25, 2011)
  6. Greenwood M. Medical Statistics from Graunt to Farr. The Fitzpatrick Lectures for the Years 1941 to1943. Cambridge: Cambridge University Press; 1948.
  7. Caselli G. Health Transition and Cause-specific Mortality. In: Schofield R, Reher D, Bideau A, editors. The Decline of Mortality in Europe. Oxford: Clarendon Press; 1991.
  8. Shattuck L. Report of the Sanitary Commission of Massachusetts, 1850 (accessed Oct 25, 2011).
  9. Doll R, Peto R, Boreham J, Sutherland I. Mortality in relation to smoking: 50 years’ observations on male British doctors. BMJ. 2004;328:1519. PMid:15213107 PMCid:437139
  10. Gottlieb MS, Schroff R, Schanker HM, Weisman JD, Fan PT, Wolf RA, et al. Pneumocystis carinii pneumonia and mucosal candidiasis in previously healthy homosexual men: evidence of a new acquired cellular immunodeficiency. N Eng J Med. 1981;305:1425-31. PMid:6272109
  11. Jha P, Slutsky AS, Brown D, Nagelkerke N, Brunham BG, Bergeron MG, et al. Global IDEA Scientific Advisory Committee Health and economic benefits of an accelerated program of research to combat global infectious diseases. CMAJ. 2004;171:1203-8. PMid:15534314
  12. Mahapatra P, Shibuya K, Lopez AD, Coullare F, Notzon FC, Rao C, et al. Civil registration systems and vital statistics: successes and missed opportunities. Lancet 2007;370:1719-25.
  13. AbouZahr C, Cleland J, Coullare F, Macfarlane SB, Notzon FC, Setel P, et al. The way forward. Lancet. 2007;370:1791-9.
  14. Hill K, Lopez AD, Shibuya K, Jha P. Interim measures for meeting needs for health sectordata: births, deaths, and causes of death. Lancet2007;370:1726-35.
  15. Araya T, Tensou B, Davey G, Berhane Y.Burial surveillance detected significant reduction in HIV-related deaths in Addis Ababa, Ethiopia. Trop Med Int Health. 2011. doi:10.1111/j.1365-3156.2011.02867.
  16. Hallett TB, Zaba B, Todd J, Lopman B, Mwita W,Biraro S, et al. Estimating incidence fromprevalence in generalised HIV epidemics: methods and validation. PLoS Med. 2008;5:e80. PMid:18590346 PMCid:2288620
  17. Davis K. The Population of India and Pakistan. Princeton: Princeton University Press; 1951.
  18. Jha P, Gajalakshmi V, Gupta PC, Kumar R, Mony P, Dhingra N et al. Prospective study of one million deaths in India: rationale, design, and validation results. PLoS Med. 2006;3:e18. PMid:16354108 PMCid:1316066
  19. Demographic and Health Surveys (Accessed Oct 25, 2011).
  20. Black RE, Cousens S, Johnson HL, Lawn JE,Rudan I, Bassani DG, et al. Global, regional, and national causes of child mortality in 2008: a systematic analysis. Lancet 2010;375:1969-87.
  21. Dhingra N, Jha P, Sharma VP, Cohen AA, Jotkar RM, Rodriguez PS, et al. Adult and child malaria mortality in India: a nationally representative mortality survey. Lancet. 2010;376:1768-74.
  22. Jha P. Avoidable global cancer deaths and total deaths from smoking. Nat Rev Cancer. 2009;9:655-64.
  23. Wall MM, Huang J, Oswald J, McCullen D. Factors associated with reporting multiple causes of death. BMC Med Res Methodol. 2005;5:4. PMid:15655070 PMCid:548504
  24. Jha P, Jacob B, Gajalakshmi V, Gupta PC, Dhingra N, Kumar R, et al. A nationally representative case-control study of smoking and death in India. N Engl J Med. 2008;358:1137-47. PMid:18272886
  25. Liu BQ, Peto R, Chen ZM, Boreham J, Wu YP, Li JY, et al. Emerging tobacco hazards in China: 1. Retrospective proportional mortality study of one million deaths. BMJ. 1998;317:1411-22. PMid:9822393 PMCid:28719
  26. Setel PW, Sankoh O, Mathers C, Velkoff VA, Rao C, Gonghuan Y, et al. Sample registration of vital events with verbal autopsy: a renewed commitment to measuring and monitoring vital statistics. Bull World Health Organ. 2005;83:611-7. PMid:16184280 PMCid:2626308
  27. Registrar General. Compendium of India’s Fertility and Mortality Indicators 1971-1999; 2001.
  28. Yang GH, Hu JP, Rao KQ, Ma JM, Rao C, Lopez AD. Mortality registration and surveillance in China: history, current situation and challenges. Population Health Metrics. 2005;3:3. PMid:15769298 PMCid:555951
  29. Registrar General of India and Centre for Global Health. Causes of death in India, 2001-2003 Sample Registration System. New Delhi: Government of India; 2009.
  30. Anker M, Black R, Coldham C, Kalter H, Quigley M, et al. A standard verbal autopsy for investigating causes of death in infants and children. WHO; Report No.: WHO/CDS/CRS/ISR/99.4; 1999.
  31. Gajalakshmi V, Peto R. Verbal autopsy of80,000 adult deaths in Tamil Nadu, South India.BMC Public Health. 2004;4:47. PMid:15488138 PMCid:535898
  32. Registrar General of India and Centre for Global Health Research. Maternal mortality in India: 1997-2003. Trends, causes and risk factors. RGI: New Delhi; 2006.
  33. Million Death Study Collaborators. Causes of neonatal and child mortality in India: a nationally representative mortality survey. Lancet. 2010;376:1853-6.
  34. Jha P, Kumar R, Khera A, Bhattacharya M, Arora P, Gajalakshmi V, et al. HIV mortality and infection in India: estimates from nationally representative mortality survey of 1.1 million homes. BMJ. 2010;340:c621. PMid:20179131 PMCid:2827715
  35. Dikshit R, Gupta PC, Ramasundarahettige C,et al for the Million Death Study Collaborators. Cancer mortality in India: a nationally representative survey Lancet. 2012 Mar 28. [Epub ahead of print]
  36. Adjuik M, Smith T, Clark S, Todd J, Garrib A, Kinfu Y, et al. Cause-specific mortality rates in sub-Saharan Africa and Bangladesh. Bull World Health Organ. 2006;84:181-8.
  37. Bawah AA, Binka FN. How many years of life could be saved if malaria were eliminated from a hyperendemic area of Northern Ghana? Am J Trop Med Hyg. 2007;77 Suppl 6:145-52. PMid:18165487
  38. Instituto Nacional de Estatístic. Mortalidade em Moçambique Inquérito Nacional sobre Causas de Mortalidade, 2007/8 (accessed Oct 31, 2011).
  39. World Health Organization. World Malaria Report 2011. Geneva: World Health Organization; 2011.
  40. INDEPTH Network Population and Health in Developing Countries: Population, Health and Survival at INDEPTH Sites. IDRC: Canada; 2002.
  41. Setel P, Abeyasekera S, Ward P, Hemed Y, Whitting D, Mswia R, et al. Development, Validation, and Performance of a Rapid Consumption Expenditure Proxy for Measuring Income Poverty in Tanzania: Experience from AMMP Demographic Surveillance Sites, in Measuring Health Equity in Small Areas. Findings from Demographic Surveillance Systems. The INDEPTH Network, Editor, Ashgate: Abingdon UK. p. 169-183; 2005.
  42. Chen J, Campbell TC, Li J, Peto R. Diet, Lifestyle and Mortality in China. A study of the characteristics of 65 Chinese counties. Oxford: Oxford University Press; 1990.
  43. Rommelmann V, Setel PW, Hemed Y, Angeles G,Mponezya H, Whiting D, et al. Costs and resultsof information systems for poverty and health indicators in the United Republic of Tanzania. Bull World Health Organ. 2005;83:569-77. PMid:16184275 PMCid:2626321

Share your thoughts

Leave a Reply

You must be logged in to post a comment.