Causes of Death

Research Team

Knowing the patterns and trends in causes of death by age and sex in a population is critical to understanding how to target interventions to maximize population health. Approximately 44% of the world’s population has their births and deaths recorded in a vital registration system, leaving a huge portion of the population for which cause of death is unknown.

Many of the populations we know least about reside in resource-poor settings where known interventions could help prevent certain causes of death. In addition, causes of death are frequently inaccurately or inconsistently recorded. Because enormous investments of time, infrastructure, and money would be required to provide complete vital registration worldwide, reliable and timely alternative methods for estimating causes of death must be developed.

The Causes of Death research team is creating new analytic tools that produce consistent trends across versions of the International Classification of Diseases (ICD), redistribute deaths mistakenly assigned to nonfatal diseases or symptoms that are not the actual underlying cause of death, and help fill in the gaps where data are missing. In many instances, for a given population in which there is a lack of data, estimates for causes of death may be made through comparison to similar populations. Pooling all available data on causes of death – including vital registration, household surveys, verbal autopsies, and hospital records – has enhanced the research team’s ability to create high-performing methods.

The research team aims to provide others with a suite of methods and tools to utilize the data available for a given population, no matter how incomplete, to produce a fuller understanding of the causes of death at the population level and give policymakers the information they need to ultimately improve population health.

Key Activities

Refine hospital methods using data from multiple settings

IHME has developed a method to use hospital data to calculate population-level causes of death. Because data on hospital discharges are collected in facilities in every country, this method is one of the only ways to produce estimates of the distribution of causes of death in countries where there are no vital registration data available. This method is currently being tested and improved by applying it to data from multiple countries, including Australia, Iran, the Philippines, Papua New Guinea, and Bangladesh.

Produce and publish estimates of trends in select causes of death by country

Country-specific results over time for a select set of causes are likely to be particularly interesting to the global research and policymaking community. Initial candidates include certain cancers, HIV/AIDS, major cardiovascular diseases, cirrhosis, congenital syphilis, tuberculosis, digestive diseases, and several injuries. In selecting causes that have particular policy interest we will consider multiple factors, including which conditions appear to have the most compelling trends or interesting developments over time, which causes hold the most ongoing interest for donors, and for which the story being told may be a new or fresh perspective as compared to previous studies. To the degree possible and appropriate, we will submit publications for presentation at relevant conferences as well.

Tailor cause of death estimation analytic tools for use in select subnational settings

From both a research and policy perspective, there is compelling reason to believe that subnational estimations of causes of death would be useful for multiple countries. Large and diverse countries, among them the United States, Brazil, and India, may well have regionally specific patterns of causes within their borders that have markedly different implications for health policy implementation. The conceptual basis of the methods for estimating causes of death globally will still hold for subnational analysis. However, the analytic tools will likely need to be adapted. In particular, we will need to implement stochastic garbage coding algorithms to deal with the combination of garbage codes and small numbers for certain causes of death. Therefore CODEm (the cause of death ensemble modeling approach) and CoDCorrect (the tool used for fitting estimations of cause of death for age and sex collectively into the mortality envelope for that age-sex) will need to be adapted. The team will develop the approach for doing so in general and then make specific adjustments as needed.

Make iCoD available for public use and adapt it for more flexible use

The research team has developed iCoD as a tool for visualizing and assessing the data used in cause of death analyses. It currently allows the user to view data points by age, sex, and country and to call up on screen citation information for all data points. Currently the tool is suitable for internal use. Its user interface and functional operability will be enhanced by the research team so that there can be an efficient and clear tool for use in the public domain hosted on the IHME website.

Refine hospital methods using data from multiple settings as part of the National Health and Medical Research Council (NHMRC) project and other datasets

Building upon work begun last year, the research team will work with colleagues at the University of Queensland in collaboration with institutions from the Philippines, Bangladesh, and Papua New Guinea to apply the hospital method to ascertain causes of death in their countries. Together, the collaborators will aim to adapt the hospital method so that it can incorporate not only data from hospital death records but also complementary information collected from household surveys implemented as part of the NHMRC project.

Impact

The methods developed as part of the Causes of Death research team’s work will assist researchers with analytic approaches to draw value from whatever data they have available. The estimates produced using these methods will provide policymakers, in particular, with the most systematically generated set of numbers available and will encompass the largest known collected set of cause of death data.

Related Publications & Presentations

Research Articles Policy Reports

Murray CJL†‡, Vos T, Lozano R, Naghavi M, Flaxman AD, Michaud C, Ezzati M, Shibuya K, Salomon JA, Abdalla S*, Aboyans V*, Abraham J*, Ackerman I*, Aggarwal R*, Ahn SY*, Ali MA*, Alvarado M*, Anderson HR*, Anderson LM*, Andrews KG*, Atkinson C*, Baddour LM*, Bahalim AD*, Barker-Collo S*, Barrero LH*, Bartels DH*, Basáñez M-G*, Baxter A*, Bell ML*, Benjamin EJ*, Bennett D*, Bernabé E*, Bhalla K*, Bhandari B*, Bikbov B*, Abdulhak AB*, Birbeck G*, Black JA*, Blencowe H*, Blore JD*, Blyth F*, Bolliger I*, Bonaventure A*, Boufous S*, Bourne R*, Boussinesq M*, Braithwaite T*, Brayne C*, Bridgett L*, Brooker S*, Brooks P*, Brugha TS*, Bryan-Hancock C*, Bucello C*, Buchbinder R*, Buckle G*, Budke CM*, Burch M*, Burney P*, Burstein R*, Calabria B*, Campbell B*, Canter CE*, Carabin H*, Carapetis J*, Carmona L*, Cella C*, Charlson F*, Chen H*, Tai-Ann Cheng A*, Chou D*, Chugh SS*, Coffeng LE*, Colan SD*, Colquhoun S*, Colson KE*, Condon J*, Connor MD*, Cooper LT*, Corriere M*, Cortinovis M*, Courville de Vaccaro K*, Couser W*, Cowie BC*, Criqui MH*, Cross M*, Dabhadkar KC*, Dahiya M*, Dahodwala N*, Damsere-Derry J*, Danaei G*, Davis A*, De Leo D*, Degenhardt L*, Dellavalle R*, Delossantos A*, Denenberg J*, Derrett S*, Des Jarlais DC*, Dharmaratne SD*, Dherani M*, Diaz-Torne C*, Dolk H*, Dorsey ER*, Driscoll T*, Duber H*, Ebel B*, Edmond K*, Elbaz A*, Eltahir Ali S*, Erskine H*, Erwin PJ*, Espindola P*, Ewoigbokhan SE*, Farzadfar F*, Feigin V*, Felson DT*, Ferrari A*, Ferri CP*, Fèvre EM*, Finucane MM*, Flaxman S*, Flood L*, Foreman K*, Forouzanfar MH*, Fowkes FGR*, Fransen M*, Freeman MK*, Gabbe BJ*, Gabriel SE*, Gakidou E*, Ganatra HA*, Garcia B*, Gaspari F*, Gillum RF*, Gmel G*, Gonzalez-Medina D*, Gosselin R*, Grainger R*, Grant B*, Groeger J*, Guillemin F*, David Gunnell*, Gupta R*, Haagsma J*, Hagan H*, Halasa YA*, Hall W*, Haring D*, Haro*, James E Harrison JM*, Havmoeller R*, Hay RJ*, Higashi H*, Hill C*, Hoen B*, Hoffman H*, Hotez PJ*, Hoy D*, Huang JJ*, Ibeanusi SE*, Jacobsen KH*, James SL*, Jarvis D*, Jasrasaria R*, Jayaraman S*, Johns N*, Jonas JB*, Karthikeyan G*, Kassebaum N*, Kawakami N*, Keren A*, Khoo J-P*, King CH*, Knowlton LM*, Kobusingye O*, Koranteng A*, Krishnamurthi R*, Laden F*, Lalloo R*, Laslett LL*, Lathlean T*, Lin JL*, Lipnick M*, Lipshultz SE*, Liu W*, Loane M*, Ohno SL*, Lyons R*, Mabweijano J*, MacIntyre MF*, Mekzadeh R*, Mallinger L*, Manivannan S*, Marcenes W*, March L*, Margolis DJ*, Marks GB*, Marks R*, Matsumori A*, Matzopoulos R*, Mayosi BM*, McAnulty JH*, McDermott MM*, McGill N*, McGrath J*, Medina-Mora ME*, Meltzer M*, Mensah GA*, Merriman TR*, Meyer A-C*, Miglioli V*, Miller*, Ted R Miller M*, Mitchell PB*, Mock C*, Mocumbi AO*, Moffitt TE*, Mokdad AA*, Monasta L*, Montico M*, Moradi-Lakeh M*, Moran A*, Morawska L*, Mori R*, Murdoch ME*, Mwaniki MK*, Naidoo K*, Nair MN*, Naldi L*, Narayan KMV*, Nelson PK*, Nelson RG*, Nevitt MC*, Newton CR*, Nolte S*, Norman P*, Norman R*, O’Donnell M*, O’Hanlon S*, Olives C*, Omer SB*, Ortblad K*, Osborne R*, Ozgediz D*, Page A*, Pahari B*, Pandian JD*, Panozo Rivero A*, Patten SB*, Pearce N*, Perez Padilla R*, Perez-Ruiz F*, Perico N*, Pesudovs K*, Phillips D*, Phillips MR*, Pierce K*, Pion S*, Polanczyk GV*, Polinder S*, Pope CA III*, Popova S*, Porrini E*, Pourmalek F*, Prince M*, Pullan RL*, Ramaiah KD*, Ranganathan D*, Razavi H*, Regan M*, Rehm JT*, Rein DB*, Remuzzi G*, Richardson K*, Rivara FP*, Roberts T*, Robinson C*, Rodriguez De Leòn F*, Ronfani L*, Room R*, Rosenfeld LC*, Rushton L*, Sacco RL*, Saha S*, Sampson U*, Sanchez-Riera L*, Sanman E*, Schwebel DC*, Scott JG*, Segui-Gomez M*, Shahraz S*, Shepard DS*, Shin H*, Shivakoti R*, Singh D*, Singh GM*, Singh JA*, Singleton J*, Sleet DA*, Sliwa K*, Smith E*, Smith JL*, Stapelberg NJC*, Steer A*, Steiner T*, Stolk WA*, Stovner LJ*, Sudfeld C*, Syed S*, Tamburlini G*, Tavakkoli M*, Taylor HR*, Taylor JA*, Taylor WJ*, Thomas B*, Thomson WM*, Thurston GD*, Tleyjeh IM*, Tonelli M*, Towbin JA*, Truelsen T*, Tsilimbaris MK*, Ubeda C*, Undurraga EA*, van der Werf MJ*, van Os J*, Vavilala MS*, Venketasubramanian N*, Wang M*, Wang W*, Watt K*, Weatherall DJ*, Weinstock MA*, Weintraub R*, Weisskopf* MG, Weissman MM*, White RA*, Whiteford H*, Wiebe N*, Wiersma ST*, Wilkinson JD*, Williams HC*, Williams SRM*, Witt E*, Wolfe F*, Woolf*AD, Wulf S*, Yeh P-H*, Zaidi AKM*, Zheng Z-J*, Zonies D*, Alan D Lopez† . Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. The Lancet. 2012 Dec 13; 380: 2197–2223.

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† Joint senior authors

‡ Corresponding author

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